review of literature on diabetes in india

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• Published: 02 December 2014

The economic burden of diabetes in India: a review of the literature

• Charles AK Yesudian 1 ,
• Mari Grepstad 2 ,
• Erica Visintin 2 &
• Alessandra Ferrario 2 , 3  

Globalization and Health volume  10 , Article number:  80 ( 2014 ) Cite this article

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Diabetes and its complications are a major cause of morbidity and mortality in India, and the prevalence of type 2 diabetes is on the rise. This calls for an assessment of the economic burden of the disease.

To conduct a critical review of the literature on cost of illness studies of diabetes and its complications in India.

A comprehensive literature review addressing the study objective was conducted. An extraction table and a scoring system to assess the quality of the studies reviewed were developed.

A total of nineteen articles from different regions of India met the study inclusion criteria. The third party payer perspective was the most common study design (17 articles) while fewer articles (n =2) reported on costs from a health system or societal perspective. All the articles included direct costs and only a few (n =4) provided estimates for indirect costs based on income loss for patients and carers. Drug costs proved to be a significant cost component in several studies (n =12). While middle and high-income groups had higher expenditure in absolute terms, costs constituted a higher proportion of income for the poor. The economic burden was highest among urban groups. The overall quality of the studies is low due to a number of methodological weaknesses. The most frequent epidemiological approach employed was the prevalence-based one (n =18) while costs were mainly estimated using a bottom up approach (n =15).

The body of literature on the costs of diabetes and its complications in India provides a fragmented picture that has mostly concentrated on the direct costs borne by individuals rather than the healthcare system. There is a need to develop a robust methodology to perform methodologically rigorous and transparent cost of illness studies to inform policy decisions.

Diabetes is one of the leading causes of morbidity and mortality worldwide [ 1 ]-[ 3 ] and a major problem in India. In 2012, 60% of all deaths in India were due to non-communicable diseases (NCDs), including cardiovascular diseases (26%), chronic respiratory diseases (13%), cancer (7%), diabetes (2%) and other NCDs (12%) [ 4 ],[ 5 ]. Currently accounting for 43% of total disability adjusted life years (DALYs), the prevalence of NCDs is expected to increase in the coming years due to ongoing large-scale urbanisation and increasing life expectancy [ 3 ].

The prevalence of diabetes in 2013 in India is only slightly higher than the world average (9.1% vs. 8.3% worldwide) [ 3 ]. However, due to its very large population, India has the world’s largest population living with diabetes after China. In 2013, there were 65.1 million people between 20 and 79 years of age with diabetes and this number was predicted to rise to 109 million by 2035. The growing epidemic of type 2 diabetes in India has been highlighted in several studies [ 6 ]-[ 9 ].

Studies have shown large regional and socioeconomic differences in the prevalence of type 2 diabetes in India. Self-reported prevalence is lower in rural areas than in urban areas ranging from 3.1% in rural areas to 7.3% in urban areas [ 10 ]. The disease appears to be more prevalent in the south of the country as compared to the northern and eastern parts [ 11 ]. However, the absence of large well-planned national studies on diabetes prevalence have led to incomplete and unreliable nationwide data on the prevalence of diabetes in India [ 6 ].

Financing and delivery of health care in India has been left largely to the private sector [ 12 ]. In 2012, public health care funding was lower in India than other countries in the region, with a general government funding for health accounting for 33% of total health expenditure in India compared to an average of 52% in the South East Asia region [ 13 ]. Nevertheless, at 4% of India’s gross domestic product (GDP) the share of health expenditure is equivalent to the average of the South East Asia region [ 14 ].

At the 56 th World Health Assembly in Geneva in 2012, universal health coverage was identified as essential to consolidate public health advances [ 15 ]. While various health programmes and policies have previously attempted to achieve universal health coverage in India, there is still a long way to go. In 2010, only about 19 percent of the population (240 million people) was covered by the country’s central and state government-sponsored health insurance [ 16 ]. When including private insurance and other schemes, some 25 percent of the population (300 million people) was covered [ 16 ]. Thus, the financial burden of health care falls heavily on individuals with the government contributing to one third of total health spending and out-of-pocket payments representing about 58% of total health spend in 2012 [ 13 ].

The assessment of the economic and social impact of diabetes in India is important for several reasons. First, India is considered the diabetes capital of the world [ 17 ], yet not enough is done to tackle the disease. An article published in 2007 suggests that an estimated USD 2.2 billion would be needed to sufficiently treat all cases of type 2 diabetes in India [ 18 ]. In comparison, health spending per capita in 2012 was USD 61 [ 19 ]. Second, by 2025, most people with diabetes in developing countries will be in the 45 to 64 year age group, thus threatening the economic productivity of the country and the income-earning ability of individuals [ 20 ]. Third, the management of diabetes and its complications can be expensive, which poses serious obstacles to the strengthening of the Indian health care system and the Government’s plan to achieve universal health coverage by 2022.

As the burden of diabetes on total health care spending is likely to increase and, potentially, will have important consequences on the sustainability of health care financing, this study presents a critical review of the literature on cost of illness of diabetes and its complications in India and also makes recommendations on areas requiring further attention and research.

A comprehensive literature review of the direct and indirect costs of diabetes in India was conducted in October 2014 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [ 21 ] guidelines.

Search strategy

Searches were performed for all papers published up to 18 October 2014 in relevant databases (PubMed, Web of Science and Scopus). Reference lists in the articles included in the review were searched to identify further eligible articles.

Search terms

Search terms and their combinations are presented in Table  1 . Databases were searched using the primary term “India” in combination with one term associated with diabetes and complications from diabetes (column 2, Table  1 ) and one term associated with costs (column 3, Table  1 ).

Inclusion criteria

Papers were included if they provided original research findings on the cost (direct and indirect) of diabetes and its complications in India, were written in English and met the inclusion criteria following the PICOS approach, adapted to meet the needs of the review [ 22 ]. We did not include cost-benefit, cost-effectiveness, cost-minimisation and cost-utility analyses. The population considered consisted of people diagnosed with type 1 or 2; the contexts of interest were hospitals, clinics, and home settings in India, outcomes comprised direct and indirect costs for health systems, households and individuals; and, the relevant study designs were randomised controlled trials (RCTs), cohort and observational studies and surveys.

Critical review of the data and quality of the studies

The review included articles reporting on the economic burden of diabetes using both quantitative and qualitative methods to elicit information on costs. In conducting our analysis, we have developed two extraction tables in two different Excel spreadsheets [ 23 ] in which the data was summarised. In the first one, we used predefined categories such as the year published, the research objectives, the methods and the sample characteristics for each article. Relevant findings were classified using a framework developed to guide the analysis of retrieved cost data (Table  2 ). Historical conversion rates from www.xe.com/currencytables/ were applied to report on cost estimates in both INR and USD throughout the article.

In the second spreadsheet we listed a number of technical criteria for a sound cost of illness study (COI). The quality indicators were selected based on criteria proposed by previous reviews and good practice guidelines [ 24 ]-[ 27 ] and adjusted in accordance with specific features of diabetes. Following data extraction, a score of either 0, 0.5 or 1 was assigned for each quality indicator. This led to a maximum obtainable score of 17.

An indicator was assigned the score of 1 if the quality and the appropriateness of the parameter were high, a score of 0.5 was assigned in the case quality parameter was only partially met and a score of 0 was assigned if there was no information on the particular parameter (unless a logical reason justifying the lack of this information was provided).

All the details of the parameters employed are presented in Table  3 .

A total of nineteen studies met the inclusion criteria. The flow of information through the different phases of the review is depicted in Figure  1 .

Flow chart of the study selection process.

A summary of the main features of the studies included is presented in Table  4 . Eighteen studies were observational studies of which twelve were cross-sectional, four were cohort longitudinal and two were case control studies. Only one study was a RCT.

Sixty-three percent of the studies dealt with the general costs of diabetes while 21% focused only on diabetes complications, including diabetic foot wound (DFW) and chronic kidney disease, and 16% of the studies analysed the cost of a specific drug for the treatment of diabetes (Figure  2 ).

Study objective.

The study samples varied from 50 to 5,516 individuals, and from local, regional, cross-regional to national studies. A summary of the studies reviewed is presented in Table  5 .

With regards to the type of diabetes analysed, most studies (n =11) considered the cost of diabetes mellitus type 2, six studies considered the costs of both, only one study focused on the cost of diabetes mellitus type 1 and one study did not clearly define the type of diabetes considered (Figure  3 ).

Type of diabetes considered.

Different types and perspectives of costs

Overall, the majority of the studies included only direct costs in their evaluation (n =14), 4 studies included direct and indirect costs and only one study included direct, indirect and intangible costs (Figure  4 ).

Costs included.

Most studies (17 studies) report on the costs to the individual, while only two studies report on costs for the health system.

Health system perspective

Both studies using a health system perspective reported costs for consultations and medicines [ 31 ],[ 38 ] and drug costs [ 31 ],[ 38 ]. Studies reported that the costs to hospitals and other health providers constituted only a small part of total diabetes costs. In the study on ambulatory diabetes care in northern India, the authors found that the mean cost borne by the hospital over a six-month period was 2.83% of the total direct costs. No study reflected on indirect costs from a societal perspective, although one study provided annual societal indirect costs at INR 15,376.30 (USD 393.25) [ 38 ].

Direct costs

Direct costs were investigated in all the reviewed studies. Detailed costing data for these studies are provided in Table  6 . The most common cost item reported on was drug costs (12 studies), followed by hospital related costs (11 studies), consultation costs (11 studies), laboratory costs (10 studies) and transport costs. Less common cost items were surgery costs (3 studies), monitoring costs (2 studies) and food costs (2 studies). In six studies providing estimates for cost components as well as total costs, drug costs accounted for more than half of the total direct costs [ 31 ],[ 34 ],[ 36 ],[ 40 ],[ 41 ],[ 43 ],[ 47 ]. A study from Delhi reported that the average annual direct cost of type 2 diabetes was INR 6,212.4 (USD 143.14) in 2005, of which more than half were drug costs (INR 3,324; USD 76.59) [ 34 ]. Similarly, a study from northern India on diabetes type 1 and 2 reported a total direct cost of INR 4,966 (USD 114.4) over six months in 2005 a ; 62% of the total direct cost were drug costs (INR 3,076; USD 70.88) [ 31 ] Table  6 .

Indirect costs

Indirect costs of diabetes and its complications were reported in four studies. A study from northern India reported a total INR 2,087 (USD 48.09) indirect costs over a six-month period in 2005 a . Patient income loss accounted for 61% of the total indirect cost (INR 1,263, USD 29.10) while the remainder 39% (INR 823, USD 18.96) was due to income loss of the carer [ 31 ].

Socioeconomic burden of diabetes

Several studies investigated differences in costs as related to one or several demographic and socioeconomic parameters by looking at levels of income, education and occupational status, and by comparing costs in rural and urban populations [ 30 ],[ 31 ],[ 34 ],[ 36 ],[ 43 ],[ 48 ]. Several studies found that lower income groups generally spent a larger proportion of their income on diabetes care, that urban populations spent more in absolute terms, and that cost of complications weighed heavily on overall costs.

Within the diabetes population, low income individuals bear the highest burden of diabetes [ 40 ]. A study on type 2 diabetes in seven states in India during the period 1998 to 2005 found spending to be higher among the urban than the rural population both in absolute terms and as a proportion of income. This was due to higher expenditure on medical consultations, laboratory tests and drugs, which the authors attributed to the use of more expensive treatments in urban areas (which have remained unavailable in rural areas). Also, in lower-income groups spending was higher in the urban than the rural population, possibly because awareness of diabetes care was better among the urban poor [ 36 ]. A Chennai-based study in 1999 compared costs for type 2 diabetes in public and private institutions and found that individuals seeking care in private hospitals were economically better off, and that families who could afford it preferred private provision over state-funded care as the public hospitals were crowded and the staff overworked [ 42 ]. A study from Bangalore with cost data from 1997 and 1998 found that uneducated, unemployed people in semi-urban or rural areas were more likely to be diagnosed later as they could not afford to consult a doctor, and therefore developed complications [ 38 ]. Treatment costs were found to be significantly higher in those who were more educated in a study from northern India [ 43 ]. Patients with less than five year of education spent INR 398.66 (USD 9.19), while those with more than five years education spent INR 2,810.20 (USD 64.77).

Complications

Sixty-nine percent of the studies included complications in their evaluation of the cost of diabetes. Only 32% of the studies [ 29 ],[ 33 ],[ 40 ],[ 45 ],[ 46 ] have specified the type of complications included while 37% of the studies only identified the presence of a number of complications (1 to 3) without specifying the type (Figure  5 ).

Complications included.

Studies considering diabetes complications indicated that they weighed heavily on the overall costs. For example, the number of complications per patient was found to be positively correlated with the patient’s healthcare expenditure [ 30 ],[ 36 ]. However, no significant urban/rural differences were found in the prevalence of complications of diabetes [ 36 ]. Studies argued that any measure to reduce hospitalisation costs would sharply reduce the economic burden for households and society, and increase patients’ quality of life [ 30 ]. Further, that substantial cost savings could be achieved by focusing on provision of care in outpatient settings [ 40 ].

Two studies compared costs of diabetes care for patients with and without complications [ 35 ],[ 46 ]. A study from Chennai reporting on costs from 2008 and 2009 found that total costs for patients without complications were INR 4,493 (USD 92.15) compared to INR 14,691.75 (USD 301.32) for patients with complications b [ 35 ]. Among the different types of complications investigated, foot complications incurred the highest costs; patients with foot complications spent four times more than patients with no complications. Patients with renal disease, cardiovascular and retinal complications spent three times more than those without complications. Consultation and hospitalisation costs were especially high for patients with complications (on average INR 1,085 (USD 22.25) for consultation costs and INR 5,256.4 (USD 107.80) for hospital costs compared to patients without complications INR 350 (USD 7.18) for consultation costs and INR 1,083 (USD 22.21).

Quality analysis

The analysis focused on the key elements necessary to perform a good cost of illness analysis. Most of the studies (n =11) scored less than 10 on 17 points scale. Interestingly, the remaining 8 studies reached a score slightly higher, with a maximum score of 13.5. The median score was 9.5.

Overall studies lacked an accurate and precise definition of the disease, with only 4 articles referring to WHO definition of diabetes, and only 3 studies gave a clear definition of the type of diabetes considered.

Most studies developed their research over an adequate period, usually of 6 months, while two studies did not specify the timeframe.

Although we considered discounting in the qualitative table, we have not accounted for it as a quality element for two main reasons. First, the prevalence-based studies considered a time short-term horizon and the need to apply a discount rate is the subject of an on-going debate [ 27 ]. Second, for incidence-based studies, the appropriate approach for calculating the discount is still an unsettled matter in the literature [ 49 ].

The majority of the studies (84%) considered an appropriate number of patients or household for the purpose of their study objective. The benchmark employed is based on the work of Krathwohl, which provides a number of questions to individuate if the sample is appropriate in comparison with the purpose of the study [ 50 ].

The remaining 16% of the studies consider samples that either are too small or do not state the size of the sample considered. Further, it is important to note that the majority of the studies only considered the middle and high-income portion of the Indian population due to the difficulties involved in collecting data on the low-income classes.

All studies used a questionnaire, or a survey, to collect the data based on self-assessment of illness and costs. In addition, 12 out of 19 studies validated the reliability of the self-assessment against hospital bills and clinical records retrieved directly from the hospitals or practitioners.

The second part of the quality analysis considered the appropriateness of the various types of costs that each study included. The appropriateness of cost inclusion was benchmarked against the study objectives and the minimum requirements for a sound cost of illness study according to international best practice [ 27 ],[ 51 ]. Only 52% of the studies included the appropriate costs, both in terms of their objective and in terms of minimal requirements for a sound cost of illness analysis. In one case, it was not possible to assess the relevance and the appropriateness of the costs included due to a lack of information on data sources and categories of cost.

In terms of methods, most studies lacked sufficient details on the methods used. In particular, 42% of the studies did not specify how costs were estimated. Only 32% of the studies adopted the incremental costs method, which is the most appropriate for diabetes, and only 4 studies mentioned the use of either matched control (n =2) or regression method [ 24 ] (Figure  6 ).

Results indicate that the prevalence-based approach, with a bottom-up quantification of the costs, was the most common method used to conduct cost of diabetes studies in India. Notably, 16 studies employed a prevalence-based approach and measured diabetes attributable costs that occurred concurrently with prevalent cases over a specified time period, usually 6 months (Figure  6 ).

Cost estimation methods.

A bottom-up approach was used in 15 studies by assigning costs to individuals with diabetes based on clinical practice data.

Regarding the evaluation of uncertainty, the majority of the studies did not perform any type of analysis. In fact, only one study performed a sensitivity analysis and 3 studies conducted linear or multivariate regressions.

In addition to inconsistencies regarding the type and extent of information provided on methods, a discussion of limitations was largely absent (Figure  7 ). 50% of the studies did not mention any limitation, while 11% mentioned only one minor limitation, such as related to the size of the sample (n =2). Only 39% of the studies provided a comprehensive discussion of the limitations of the cost components, data, assumptions and research methods.

Limitations discussed.

Regarding the statistical methods employed, 14 studies performed the necessary statistical analysis for a good quality study. The majority employed the student t-test to determine the statistical significance and the Wilcoxon matched pair signed-rank test to verify the validity of the data. A number of studies employed the Chi-square test and percentage value to validate their data. A large number of studies used the statistical package SPSS to analyse the data.

Two studies state the presence of statistical analysis. However, they did not identify which statistical formulas had been used. One study even declared that it had not performed any kind of any statistical analysis at all.

11 studies presented the standard deviation along with the mean estimate while 4 studies included only the mean.

Discussion and recommendations

With the population of people living with diabetes predicted to rise above 109 million by 2035 [ 17 ], there is an urgent need to act at all levels of authority in India, and with additional coordination at the national level. Further, there are several specific areas in which policy makers could concentrate efforts to reduce the impact of the economic burden of disease.

Firstly, the economic burden falls heavily on patients and their families and requires better health care coverage. There is a need to mitigate the serious adverse effects of high out-of-pocket expenditure, including impoverishment of catastrophic spending and cost of complications. To this end, efforts, such as the expert group set up by the Planning Commission of India to achieve universal health coverage by 2022 [ 52 ] need to be considered in order to increase coverage and pool healthcare costs across the population. Policies aiming to strengthen health systems are also essential in this process.

Secondly, high costs and suboptimal access to drugs contribute significantly to the burden of the disease and should be addressed through market shaping strategies. While hospitalisation and complications are major components of the costs of diabetes, drug costs constitute an important part of the expenses, often representing more than 50% of total direct costs for households. A study based on a large dataset, found that drug costs accounted for 58% of out–of-pocket expenditure on diabetes [ 53 ]. Another study on drug costs as share of expenses paid out of pocket by quintile group revealed progressive private spending on health, with the poorest spending 75.42 percent on drugs, compared to 65.9 percent spent on drugs by the richest in 2009–10 [ 12 ]. By further comparison, studies of diabetes in Western countries shows that drug costs constitute a much lower share of total direct health expenditure on diabetes, ranging from 6.2 percent to 10.5 percent [ 54 ],[ 55 ] in Europe and 12 percent in the United States [ 56 ]. In addition to better drug coverage for individuals, Indian authorities, together with the international community, should aim to employ market-shaping mechanisms to increase the access of medicines in India. Poor procurement procedures and weak supply chain systems are major barriers to access to medicines in India, contributing to low competition, low quality, high price and variable availability of drugs [ 12 ]. Pooled drug procurement of essential medicines between several Indian states has proven efficient for essential medicines [ 57 ], and should therefore be considered for medications for diabetes and related drugs.

Thirdly, lower expenditure among the rural and low income population may be due to issues of access and affordability rather than lower need [ 6 ], and late detection of the disease in these settings often leads to catastrophic spending for individuals and households [ 38 ]. Early detection and treatment provided in outpatient settings has been identified as an important means for cost reduction [ 30 ],[ 40 ] and should thus be strengthened. Socioeconomic differences and the urban–rural divide suggest divergence in disease outcomes. In other words, the relatively wealthier population living in urban areas spend more on diabetes care and have better outcomes, while relatively poorer people living in rural areas tend to have more difficulties accessing diabetes care, and therefore spend less on diabetes care and tend to have worse health outcomes [ 58 ]. Mobile health units, which can increase access in remote areas, may help mitigate these socioeconomic differences.

With regards to the methodological quality of the studies considered, only a few of the studies adhered to recognised standards of methodological quality, which utilised a transparent methodology, and thus provided credible results.

The aim of COI is to identify, measure and value the resources consumed by a disease in order to determine not only the total cost, but also all the elements and methods used to design the analysis itself [ 24 ]. However, the majority of the studies failed to achieve this aim due to a lack of solid methodology.

First of all, the lack of both a clear definition and foundation in the literature, or justifications for applying new approaches, for the methods employed affect the reproducibility of the studies. Notably, the total costs were often calculated without providing a detailed list of unit costs and resource consumption was also rarely described. In addition, the majority of the studies lacked of a clear epidemiological definition of diabetes which also lead to comparability problems [ 59 ].

Secondly, the lack of a clear justification of the cost components and the data sources, together with the lack of a discussion on the intrinsic limitations of the study, produced doubts about the quality of the research. The absence of these elements could either be indicative of lack of accuracy of the study or even aimed at hiding possible gaps and/or errors in the collection of data and the calculations of costs [ 51 ].

To enhance the transparency of the cost of illness studies, it appears fundamental to provide sufficient documentation on data sources, assumptions and estimation methods [ 51 ].

In terms of costs included, there are a number of factors that could have led to possible biases in the estimation of the economic burden of diabetes in India.

One of such factor is the absence, in the majority of studies, of the cost of complication or a description of complication profile of the included patients. In particular, studies failed to include health care utilisation costs associated with chronic complications of diabetes, which are usually the most expensive [ 59 ]. Indeed, according to WHO [ 59 ] data and to a number of studies outside India [ 60 ], the treatment of patient with diabetes for other complications and comorbidities is a major source of the increasing in the health care expenditure on diabetes.

The exclusion of the estimation of the intangible costs and the loss of productivity leads to an underestimation of diabetes. Loss in productivity for the patient or carers was shown to represent up to half of the total costs of diabetes [ 30 ]. Despite difficulties in their extraction and quantification, both costs are important for a comprehensive calculation of the actual cost of the disease, which affects not only diabetes patients, but also their families and the society [ 25 ],[ 51 ]. The inclusion of intangible costs is especially important in studies aiming to give a general analysis of the burden of this disease in the country or in a specific region.

In terms of perspective of analysis, the third party payer is the most common perspective adopted in the studies reviewed. The exclusion of the perspective of the healthcare sector and the households as well as the governments and local authorities excludes a number of key costs, such administrative costs and personnel costs.

The implementation of a comprehensive and accurate estimation of the cost of diabetes enables the use this cost as both a baseline and a reference, which can help to identify the programmes and strategies most effective in reducing costs associated with diabetes [ 50 ].

From a methodological perspective, most studies used a prevalence-based epidemiological approach and a bottom up quantification of the costs method, both of which are considered the most accurate and consistent for the calculation of the burden of diabetes [ 25 ],[ 51 ]. Nevertheless, they also lack of other major elements for a complete COI.

The absence of an estimation of uncertainty in a large number of the studies is an important limitation. Due to the large number of uncertainties involved in a COI, it is necessary to consider alternative values for all important parameters and assumptions [ 50 ],[ 51 ]. Therefore, it is necessary to conduct a proper sensitivity analysis [ 26 ],[ 29 ],[ 61 ].

Cost of illness studies are an important instrument for informing and raising awareness among policy-makers by providing economic information to support their decisions. Further, results of this type of economic evaluation are often used to justify the allocation of more resources to prevent and treat a certain illness [ 26 ],[ 39 ]. More efforts in designing study methodologies are necessary to improve the quality of studies on the cost of diabetes in India.

Therefore, it would appear advantageous to develop and implement standardised guidelines regarding the conduct of comprehensive and accurate cost of illness studies in India. Certainly, a well designed methodology and an accurate computation and inclusion of all the costs would enhance the COI validity as a policy tool.

Limitations

This review provides a fragmented picture of the economic burden of diabetes in India. Given the heterogeneity of study designs and diversity of methods used in the literature reviewed, we were unable to generate meaningful aggregate data for meta-analysis purposes. This heterogeneity also complicated the synthesis of the papers, and comparisons should be treated with caution due to the variability in study design and thematic focus. Future studies should aim to explore optimal methodological study designs that may facilitate the production of meaningful national estimates for meta-analysis.

This study has aimed to inform the discussion on the economic burden of diabetes by reviewing the literature on diabetes costs for individuals and society. We found that most studies on the costs of diabetes and its complications in India have focused on the costs borne by patients, both direct and indirect, and less evidence exist on the economic burden for the health care system and society. Three areas of concern were identified for policy interventions. First, the heavy economic burden of diabetes borne by individuals should be reduced via the improvement of universal healthcare coverage. Second, market shaping mechanisms should be considered to improve the access to affordable medicines, which constitutes an important part of private costs. Finally, early disease detection and treatments in outpatient settings provide cost saving ways of tackling the disease.

As the epidemiological burden of diabetes increases, the economic burden on households is expected to rise and the economically disadvantaged will be the most affected. Future initiatives to tackle diabetes type 1 and 2 should be grounded in evidence-based and integrated strategies of prevention and disease management, and implemented at all levels of authority. Cost of illness analysis should be a basis on which strategies for mitigating the effects of this pervasive illness gain a higher priority on the health policy agenda.

a The authors do not provide the year of data collection and the year of article publication is used as a proxy.

b Values are averaged across the different types of complications: renal, cardiovascular, foot, retinal.

Abbreviations

Chronic renal failure

Chronic kidney disease

Disability adjusted life years

Gross domestic product

Kidney transplant

Diabetic foot wound

Indian rupee

Non-communicable diseases

Preferred reporting items for systematic reviews and meta-analyses

Randomised controlled trials

World health organization

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Acknowledgements

This study was funded by an unrestricted educational grant from Novo Nordisk Switzerland. The authors would like to thank Ms Marsha Fu and Danica Kwong for their editorial assistance.

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AF received travel reimbursement and speaker fees from Novo Nordisk for delivering two presentations on diabetes in EU5 at national diabetes conferences in Portugal and Spain.

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All authors contributed to the literature review and in the appraisal of the retrieved information. CAKJ wrote the first draft, MG and EV analysed the data and redrafted subsequent versions of the article with the input of AF up to its final version. All authors contributed to the critical revision of the article for important intellectual content and approved the final manuscript.

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Yesudian, C.A., Grepstad, M., Visintin, E. et al. The economic burden of diabetes in India: a review of the literature. Global Health 10 , 80 (2014). https://doi.org/10.1186/s12992-014-0080-x

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Literature Review Of Diabetes In India

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More about Literature Review Of Diabetes In India

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• Diabetes mellitus
• Blood sugar
• Diabetes mellitus type 2

• Review Article
• Published: 17 June 2020

Economic menace of diabetes in India: a systematic review

• Sumit Oberoi 1 &
• Pooja Kansra 1  

International Journal of Diabetes in Developing Countries volume  40 ,  pages 464–475 ( 2020 ) Cite this article

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Diabetes mellitus is recognised as a major chronic pandemic disease that does not consider any ethnic and monetary background. There is a dearth of literature on the cost of diabetes in the Indian context. Therefore, the present study aims to capture the evidence from the literature on the cost of diabetes mellitus in India.

An extensive literature was reviewed from ACADEMIA, NCBI, PubMed, ProQuest, EBSCO, Springer, JSTOR, Scopus and Google Scholar. The eligibility criterion is based on ‘PICOS’ procedure, and only those studies which are available in the English language, published between 1999 and February 2019, indexed in ABDC, EBSCO, ProQuest, Scopus and peer-reviewed journals are included.

A total of thirty-two studies were included in the present study. The result indicates that the median direct cost of diabetes was estimated to be ₹18,890/- p.a. for the north zone, ₹10,585/- p.a. for the south zone, ₹45,792/- p.a. for the north-east zone and ₹8822/- p.a. for the west zone. Similarly, the median indirect cost of diabetes was ₹18,146/- p.a. for the north zone, ₹1198/- p.a. for the south zone, ₹18,707/- p.a. for the north-east and ₹3949/- p.a. for the west zone.

The present study highlighted that diabetes poses a high economic burden on individuals/households. The study directed the need to arrange awareness campaign regarding diabetes and associated risk factors in order to minimise the burden of diabetes.

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Introduction.

‘Diabetes is a metabolic disease characterised by hyperglycemia resulting from defects in insulin secretion, insulin action or both’ [ 1 ]. With rising pervasiveness globally, diabetes is conceded as a major chronic pandemic disease which does not consider any ethnic background and monetary levels both in developing and developed economies and has also been designated with the status of ‘public health priority’ in the majority of the countries [ 2 , 3 ]. Individuals with diabetes are more susceptible to develop any of the associated complications, viz. macrovascular or microvascular. As a consequence, people experience frequent and exhaustive confrontation with the health care systems [ 4 ]. The treatment cost for diabetes and its associated complications exert an enormous economic burden both at the household and national levels [ 5 , 6 , 7 , 8 , 9 ].

In a developing nation like India, the majority of diabetes patients experience a substantial cost burden from out-of-pocket (OOP). Also, the dearth of insurance schemes and policies escalate the cost of diabetes care [ 2 ]. Instantaneous urbanisation and socio-economic transitions, viz. rural to urban migration, low exercise regimen, lifestyle disorder, etc., have resulted in an escalation of diabetes prevalence in India over the last couple of decades [ 10 , 11 , 12 , 13 , 14 ]. According to the International Diabetes Federation [ 15 ], ‘India is the epicentre of diabetes mellitus and it was found that in 2017 India had the second-largest populace of 73 million diabetic patients, after China. And the figure is expected to be just double 134 million by 2045’. Considering that fact, the epidemiologic transition of diabetes has a colossal economic burden [ 16 ]. The estimated country-level health care expenditure on diabetes mellitus in India after amending purchasing power difference was 31 billion US dollars in 2017, pushing India in fourth place globally after the USA, China and Germany. Looking at the economic burden, in India, diabetes alone exhausts 5 to 25% share of an average Indian household earning [ 17 , 18 , 19 ].

Chronic nature and the rising epidemic of diabetes have everlasting consequences on the nation’s economy and health status [ 20 ]. Therefore, managing diabetes and its comorbidities is a massive challenge in India due to several issues and stumbling blocks, viz. dearth of awareness regarding diabetes, its risk factors, prevention strategies, health care systems, poverty-stricken economy, non-adherence to medicines, etc. Altogether, these issues and problems remarkably contribute to the economic menace of diabetes in India [ 20 , 21 , 22 , 23 , 24 ].

After a perspicuous representation of the economic menace of diabetes in India, policymakers and health experts should provide healthier prospects to enhance the quality of life of millions [ 19 ]. Thus, the present study aims at capturing the evidence from the literature on the cost of diabetes mellitus in India, reviewing the materials and methods used to estimate the costs and, lastly, exploring future research area. For the accomplishment of the objective, the paper has been divided into five sections. The ‘ Introduction ’ section of the study discusses diabetes and its economic burden. The ‘ Materials and methods ’ section deals with materials and methods applied for data extraction and quality assessment. The ‘ Results ’ section of the present study reports the results of the study. The ‘ Discussion ’ section concludes the discussion along with policy implications and limitations.

Materials and methods

A comprehensive literature review was carried out by following the ‘Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines’ [ 25 ]. The article suggests a minimum set of guidelines and procedures of writing items to enhance the quality of the systematic review. A search was performed between February and March 2019 for the accumulation and review of studies published up to January 2019.

Literature search

An extensive desk search was executed for all published articles and book chapters in relevant databases such as ACADEMIA, NCBI, PubMed, ProQuest, EBSCO, Springer, ResearchGate, Google Scholar, JSTOR and Scopus. For better insight, a literature search was performed on the World Health Organization (WHO) and International Diabetes Federation (IDF) libraries available online. Additional articles were investigated by scrutinising the backward referencing lists or references of the included articles. The search terms and keywords were adjusted by following different databases using words or phrases, viz. ‘India’, ‘Diabetes Mellitus or Diabetes’, ‘Economic Burden’, ‘Economic Menace’, ‘Costs of Diabetes’, ‘Health Care Utilization’, ‘Cost of Illness’, ‘Out-of-Pocket Expenditure’, ‘Diabetes Care’, ‘Health Economics’, ‘Direct/Indirect Costs’, ‘Cost Analysis’, ‘Hospitalization’, ‘Diabetic Complications’, ‘Developing Countries’, ‘Lifestyle Modification’, ‘Non-communicable diseases’, ‘Expenses by patients’, ‘Comorbidity Burden’ and ‘Treatment Costs’ were utilised to attain expected results. A total of 412 studies were acquired including duplicates by exercising the desk search criteria. Further, a comprehensive analysis of the studies was performed as per the recommendations suggested by Moher et al. [ 25 ]. Later, 187 articles were identified to be duplicate and removed immediately.

Inclusion criterion

Of the total 225 articles, limited studies managed to clear the eligibility criterion based upon the significant elements of the ‘Patient Intervention Comparison Outcome Study (PICOS)’ procedure [ 26 ]. Title, abstract and keywords of the remaining 225 studies were assessed to determine their relevance. Those articles which have been included (a) were available in English language; (b) were published between 1999 and February 2019; (c) were indexed under ABDC, EBSCO, ProQuest and Scopus; (d) were under journals that are to be peer-reviewed in nature; (e) highlighted unprecedented research outcomes on costs; and (f) were comprising at least one or more demographic zones. Thus, the screening procedure facilitated the selection of 32 articles. Majority of research publications were excluded on the grounds if they (a) did not provide the detailed analysis of how costs were estimated; (b) were conference articles or posters; (c) only presented the costs of diabetes prevention; and (d) were published in non-peer-reviewed journals.

Data extraction and quality assessment of included studies

The exploration includes those articles which highlight the cost burden of diabetes in India. Whilst performing the analysis, two interdependent excel spreadsheets were developed for data to be summarised. In the very first spreadsheet, a predefined category was used, viz. publication title/year, study type, location, diabetes type, methodology and findings. Relevant information is drawn out and presented in Table 1 , highlighting the study characteristics of the included articles. The second excel spreadsheet focuses its attention on the list of technical criteria applied to assess the quality of the articles incorporated in the review process. Copious checklist has been put forward for the quality assessment of the included studies and majority of them emphasise on the economic assessment, viz. cost analysis, cost-benefit analysis (CBA), health care utility analysis, etc. [ 27 , 28 ]. Therefore, the quality indicators developed for the present study were grounded on the criterions suggested by prior literature [ 29 , 30 , 31 , 32 ].

A symbol of (√) yes, (×) no and (±) moderately available was assigned to individual quality indicator. Each symbol was allocated with a score of 1, which leads to a maximum attainable score of 10 for each study reviewed. Hence, a complete detailed analysis of the parameters utilised is presented in Table 2 .

Study characteristics

The characteristics of the included thirty-two studies are presented in Table 1 . A majority of 66% (21) of the studies were published between 2010 and 2019 and the remaining 11 studies (34%) were published in 1999–2009. Year of costing was 1999–2003 for 5 studies; between 2009 and 2013, 10 studies (31%) were included; and for 2014–2019, 12 studies (37%) were included. The cost of diabetes was estimated from various locations such as the south zone ( n  = 11), followed by the north zone ( n  = 8), the north-east zone ( n  = 1) and the west zone ( n  = 1). A large proportion of 11 studies (34%) were defined under India as a whole.

Whilst conducting review studies, it is imperative to initially define the type, study interest, sample size, data source and outlook of the study. The included studies majorly focus on type 2 diabetes ( n  = 9), followed by both type 1 and type 2 studies ( n  = 8), 2 studies were identified under type 1 diabetes and only 1 study was acknowledged under gestational/foot ulcer category, whilst the remaining 12 studies did not define any diabetes type (Table 1 ). Of the total 32 studies, 94% of studies focus on general costs and the remaining 2 studies emphasise on foot ulcers and others. Whilst discussing the cost interests, the complications associated with diabetes were estimated by merely10 studies and the remaining 22 studies (69%) estimated the diabetes cost without any complications. Defining sample size is the utmost priority of the study, 27 studies (83%) of the total 32 studies have properly identified the sample size to be ≤ 100 respondents, only 2 studies specified the population size to be > 100 respondents and 3 studies (10%) did not define or provide the sample size.

Under the source of the cost data section, 16 studies (50%) retrieved data on cost from the patients themselves; for 11 studies (34%), source of cost data was obtained from medical institutes; and the remaining 5 studies (16%) acquired the data on cost from publications. Studies on the economic burden of illness could be done through several perspectives, viz. household, patient, societal and governmental. In the particular study, the patient’s perspective was most commonly acknowledged by 19 studies (61%), 9 studies considered societal perspective, followed by government perspective for 7 studies and lastly, household perspective was adopted by 6 studies as highlighted in Table 1 .

Quality of the reviewed articles

The quality of the included studies is broadly presented in Table 2 . For all 32 studies, research questions and findings were discussed and explained in a very well-defined manner. The presentation of the results was completely in synchronisation with the aim and conclusions derived from the reviewed articles. It was found that 60% (19) of the studies have comprehensively defined the epidemiological definition such as type of diabetes (type 1 and type 2). Limitations experienced by the majority of studies that hampered the quality of the reviewed articles were the absence of a broad definition of diabetes and a lack of adequate sample size. A major proportion of 25 studies (78%) did not extensively define diabetes and 18 studies (56%) moderately considered the sample size.

For most of the reviewed articles, the sampling technique for data collection was addressed and only 1 study did not define the sampling technique. However, 56% (18) of studies lucidly defined the tools and technique employed in the reviewed articles and the remaining 14 studies moderately describe the tools and technique. A majority of 27 studies (84%) have properly classified the cost of diabetes and the remaining 5 studies defined moderately. Hence, based on quality index scores, the majority of the studies ( n  = 11) scored ‘6 Yes’ on a 10-point scale. Interestingly, 5 studies attained a marginally higher score of ‘8 Yes’ of the total 32 studies as presented in Table 2 .

Cost of diabetes

The economic burden of diabetes mellitus has led to numerous studies on the cost of illness. The cost exerted by diabetes can be categorised into three groups: direct cost, indirect cost and intangible cost [ 55 , 56 ]. Direct cost includes both direct health care costs (diagnosis, treatment, care and prevention) and direct non-health care costs (transport, housekeeping, social service and legal cost) [ 1 , 57 ]. Indirect cost includes cost for absenteeism, loss of productivity and disability [ 58 , 59 ]. Lastly, intangible costs embrace cost for social isolation and dependence, low socio-economic status, mental health and behavioral disorder and loss of quality of life [ 56 , 60 , 61 ]. All twenty-one reviewed studies put forward data and statistics to evaluate per capita cost of individual/household at zone level and the remaining eleven studies highlighted the cost of diabetes at the national level (Table 3 ). To have a clear insight on cost, the reviewed articles have been categorised into four different zones, viz. north zone, west zone, south zone and north-east zone.

Under the north zone, 8 studies were included to calculate both direct and indirect costs of diabetes at the individual/household level (Fig. 1 ). The median direct cost of diabetes is estimated to be ₹18,890/- per annum, ranging from ₹999/- to ₹1,09,344/- [ 19 , 35 , 39 , 44 , 46 , 48 , 49 , 50 ]. The most commonly measured costing items under direct cost were expenditure on medicines (7 studies), diagnostic expenses (2 studies), transportation cost (1 study), hospitalisation (2 studies) and consultation fee (3 studies). The median indirect cost of diabetes for the north zone was evaluated to be ₹18,146/- per annum, ranging from ₹4642/- to ₹98,808/- [ 19 , 35 , 46 , 49 ]. For all indirect cost studies, costing items, viz. wage loss and leisure time forgone, were used majorly.

PRISMA Framework for detailed inclusion criterion. Source: Based on Oberoi and Kansra [ 54 ], as suggested by Moher et al. [ 25 ]

South zone includes 11 studies, majorly from Karnataka state (6 studies), followed by Tamil Nadu (4 studies) and Andhra Pradesh (1 study). The median direct cost was assessed to be ₹10,585/-- per annum (Fig. 1 ), ranging from ₹377/- to ₹21,258/- per annum [ 2 , 6 , 7 , 8 , 9 , 33 , 37 , 38 , 40 , 42 , 45 ]. Direct costing items, viz. medicine cost (9 studies), consultation fees (4 studies) and hospitalisation (3 studies), were used in the reviewed article. The median indirect cost of diabetes was ₹1198/- per annum, ranging from ₹462/- to ₹3572/- per annum with major cost items such as monitoring cost (1 study), absenteeism (3 studies) and impairment (1 study) [ 7 , 8 , 9 , 33 , 37 ].

Under the north-east and west zone, only one-one study was observed, to evaluate the direct and indirect cost of diabetes at the individual/household level [ 47 , 51 ]. The median direct cost of diabetes for north-east was evaluated to be ₹45,792/- per annum and ₹8822/- per annum was observed for the west zone (Fig. 1 ). Commonly estimated costing items were surgical procedures, expenditure on drugs/medicines, clinical fees, etc. The median indirect cost estimated for the north-east zone was ₹18,707/- per annum and ₹3949/- per annum was analysed for the west zone. Indirect costing items identified for both reviewed studies were loss of wage, spendings on health class, travelling expenditure and spendings on diet control. Lastly, 11 studies were incorporated to estimate the cost of diabetes for India as a whole at the individual/household level [ 5 , 20 , 22 , 23 , 24 , 34 , 36 , 43 , 51 , 52 , 53 ]. The median direct cost of diabetes for India as a whole was ₹9996/- per annum, ranging from ₹4724/- to ₹25,391/- per annum. Also, the median indirect cost of diabetes at the individual/household level was estimated to be ₹5237/- per annum, ranging from ₹2435/- to ₹12,756/- annually (Figs.  1 and 2 ).

Cost estimates of India and zone-wise cost profile. Source: Based on the author’s compilation and reviewed studies

Complications

Diabetes mellitus is associated with a large number of serious and chronic complications, which act as a major cause of hospitalisation, morbidity and premature mortality in diabetic patients [ 2 , 7 , 8 , 42 ]. Diabetes mellitus is commonly associated with chronic complications both macrovascular and microvascular origin [ 2 , 3 ]. Microvascular complications of diabetes mellitus include retinopathy, autonomic neuropathy, peripheral neuropathy and nephropathy [ 3 , 53 ]. The macrovascular complication of diabetes mellitus broadly includes coronary and peripheral arterial disease [ 2 , 7 ]. Of the total reviewed studies, only 10 studies estimated the cost of complications associated with diabetes (Table 3 ). A couple of studies on diabetes assessed the cost of illness to be 1.4 times higher for individuals with complications as exhibited in Table 3 [ 8 , 52 ]. A similar study by Sachidananda et al. [ 42 ] concluded that the cost of diabetes is 1.8 times higher for complicated non-hospitalised patients and 2.4 times higher for complicated hospitalised patients. Kapur [ 38 ] inferred that individuals with three or more comorbidities encounter 48% more cost of care, amounting to ₹10,593/- annually. According to Cavanagh et al. [ 5 ], India is the most expensive country for a patient with a complex diabetic foot ulcer, where 68.8 months of income was required to pay for treatment. Three reviewed studies incorporated in the study estimated the cost of individual/household with both macrovascular and microvascular complications [ 2 , 7 , 53 ]. Of these 3 reviewed articles, a couple of them primarily concentrate on the cost of illness prompted by renal (kidney) complication [ 2 , 53 ]. Lastly, Eshwari et al. [ 9 ] estimated the total cost for the treatment of diabetes with comorbidities was ₹9133/- annually. Direct cost with complications was ₹8185/- per annum and indirect cost amounts to be ₹508/- annually.

Rising menace of diabetes has been a major concern for India. With a frightening increase in population with diabetes, India is soon going to be crowned as ‘diabetes capital’ of the world. A swift cultural and social alteration, viz. rising age, diet modification, rapid urbanisation, lack of regular exercise regimen, obesity and a sedentary lifestyle, will result in the continuous incidence of diabetes in India. The primary objective of this article is to detect and capture the evidence from published literature on the per capita cost at the individual/household level for both direct and indirect costs of diabetes in India which are available and published since 1999. Of the total 412 records, 32 studies were identified to meet the inclusion criterion. Therefore, the findings of the present study suggest that per annum median direct and indirect cost of diabetes at the individual/household level is very colossal in India.

A large proportion of health care cost is confronted by the patients themselves, which affects the fulfilment of health care because of financial restraints [ 62 ]. The proportion of public health expenditure by the Indian government is the lowest in the world. As a consequence, out-of-pocket (OOP) spending constitutes to be 70% of the total health expenditure. Hence, financing and delivering health care facilities in India is majorly catered by the private sector for more than 70% of diseases in both rural and urban areas [ 24 ].

Direct cost items (expenditure on medicines, diagnostic expenses, transportation cost, hospitalisation and consultation fee) and indirect cost items (loss of wage, spendings on health class and travelling expenditure) were most commonly reported costing items in the present study [ 8 , 9 , 19 , 37 , 46 , 48 ]. Most of the reviewed studies on the cost of diabetes highlighted expenditure on drugs/medicine as the foremost costing item which accounts for a significant share of all direct costs. The finding of the present study is consistent with Yesudian et al. [ 62 ], ‘cost on drugs constitutes 50% of the total direct costs’. The majority of the reviewed articles included in the study justify that the primary cause for such abnormal costs of medicines is the common practice adopted by physicians to prescribe brand-named medicines, rather than generic medicines.

In context to the quality of tools and techniques incorporated by the included studies, a large number of articles (56%) witnessed to acknowledge the standards of tools and techniques. Similarly, the classification of the cost of diabetes was also determined by the majority of reviewed articles (27 articles). But the absence of a comprehensive definition of diabetes and a small size of individuals/households produce dubiousness about the standards or quality of the study. Hence, the limitations experienced by the majority of reviewed articles hampered the quality of the present study. Thus, it is beneficial to develop and suggest standard procedures and framework to conduct a comprehensive and exhaustive study on the cost of diabetes.

Limitations of the study

The present study holds few limitations. Primarily the exclusion of the relevant articles presented as conference papers and those studies published under non-peer-reviewed journals. With the omission of the above literature, some biasness might have been introduced into the review process. Furthermore, the major limitation of the present study is the non-availability of published articles under the central and east zone of India. Also, the studies published under the north-east zone and west zone were only one. Lastly, the heterogeneity in material and methodology used in cost estimation are not analogous. As a consequence, conducting a meta-analysis is not feasible.

The above discussion highlighted a huge economic burden of diabetes in India and variations were recorded in the different zones. It was observed that the cost of drugs/medicines accounts for a major burden of the cost of diabetes. The study suggested few policy interventions to cope with the high economic burden of diabetes. There is a dire need in the country to arrange awareness programmes on diabetes and associated risk factors. The menace of diabetes can be controlled by devising new health care policies, introducing new generic medicines and taxing alcohol/tobacco. Diabetes is a lifestyle disease so along with the above measures, a change in dietary habits, physical activity, beliefs and behavior can reduce its economic burden.

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Oberoi, S., Kansra, P. Economic menace of diabetes in India: a systematic review. Int J Diabetes Dev Ctries 40 , 464–475 (2020). https://doi.org/10.1007/s13410-020-00838-z

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Rulla Alsaedi , Kimberly McKeirnan; Literature Review of Type 2 Diabetes Management and Health Literacy. Diabetes Spectr 1 November 2021; 34 (4): 399–406. https://doi.org/10.2337/ds21-0014

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The purpose of this literature review was to identify educational approaches addressing low health literacy for people with type 2 diabetes. Low health literacy can lead to poor management of diabetes, low engagement with health care providers, increased hospitalization rates, and higher health care costs. These challenges can be even more profound among minority populations and non-English speakers in the United States.

A literature search and standard data extraction were performed using PubMed, Medline, and EMBASE databases. A total of 1,914 articles were identified, of which 1,858 were excluded based on the inclusion criteria, and 46 were excluded because of a lack of relevance to both diabetes management and health literacy. The remaining 10 articles were reviewed in detail.

Patients, including ethnic minorities and non-English speakers, who are engaged in diabetes education and health literacy improvement initiatives and ongoing follow-up showed significant improvement in A1C, medication adherence, medication knowledge, and treatment satisfaction. Clinicians considering implementing new interventions to address diabetes care for patients with low health literacy can use culturally tailored approaches, consider ways to create materials for different learning styles and in different languages, engage community health workers and pharmacists to help with patient education, use patient-centered medication labels, and engage instructors who share cultural and linguistic similarities with patients to provide educational sessions.

This literature review identified a variety of interventions that had a positive impact on provider-patient communication, medication adherence, and glycemic control by promoting diabetes self-management through educational efforts to address low health literacy.

Diabetes is the seventh leading cause of death in the United States, and 30.3 million Americans, or 9.4% of the U.S. population, are living with diabetes ( 1 , 2 ). For successful management of a complicated condition such as diabetes, health literacy may play an important role. Low health literacy is a well-documented barrier to diabetes management and can lead to poor management of medical conditions, low engagement with health care providers (HCPs), increased hospitalizations, and, consequently, higher health care costs ( 3 – 5 ).

The Healthy People 2010 report ( 6 ) defined health literacy as the “degree to which individuals have the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions.” Diabetes health literacy also encompasses a wide range of skills, including basic knowledge of the disease state, self-efficacy, glycemic control, and self-care behaviors, which are all important components of diabetes management ( 3 – 5 , 7 ). According to the Institute of Medicine’s Committee on Health Literacy, patients with poor health literacy are twice as likely to have poor glycemic control and were found to be twice as likely to be hospitalized as those with adequate health literacy ( 8 ). Associations between health literacy and health outcomes have been reported in many studies, the first of which was conducted in 1995 in two public hospitals and found that many patients had inadequate health literacy and could not perform the basic reading tasks necessary to understand their treatments and diagnoses ( 9 ).

Evaluation of health literacy is vital to the management and understanding of diabetes. Several tools for assessing health literacy have been evaluated, and the choice of which to use depends on the length of the patient encounter and the desired depth of the assessment. One widely used literacy assessment tool, the Test of Functional Health Literacy in Adults (TOFHLA), consists of 36 comprehension questions and four numeric calculations ( 10 ). Additional tools that assess patients’ reading ability include the Rapid Estimate of Adult Literacy in Medicine (REALM) and the Literacy Assessment for Diabetes. Tests that assess diabetes numeracy skills include the Diabetes Numeracy Test, the Newest Vital Sign (NVS), and the Single-Item Literacy Screener (SILS) ( 11 ).

Rates of both diabetes and low health literacy are higher in populations from low socioeconomic backgrounds ( 5 , 7 , 12 ). People living in disadvantaged communities face many barriers when seeking health care, including inconsistent housing, lack of transportation, financial difficulties, differing cultural beliefs about health care, and mistrust of the medical professions ( 13 , 14 ). People with high rates of medical mistrust tend to be less engaged in their care and to have poor communication with HCPs, which is another factor HCPs need to address when working with their patients with diabetes ( 15 ).

The cost of medical care for people with diabetes was $327 billion in 2017, a 26% increase since 2012 ( 1 , 16 ). Many of these medical expenditures are related to hospitalization and inpatient care, which accounts for 30% of total medical costs for people with diabetes ( 16 ).

People with diabetes also may neglect self-management tasks for various reasons, including low health literacy, lack of diabetes knowledge, and mistrust between patients and HCPs ( 7 , 15 ).

These challenges can be even more pronounced in vulnerable populations because of language barriers and patient-provider mistrust ( 17 – 19 ). Rates of diabetes are higher among racial and ethnic minority groups; 15.1% of American Indians and Alaskan Natives, 12.7% of Non-Hispanic Blacks, 12.1% of Hispanics, and 8% of Asian Americans have diagnosed diabetes, compared with 7.4% of non-Hispanic Whites ( 1 ). Additionally, patient-provider relationship deficits can be attributed to challenges with communication, including HCPs’ lack of attention to speaking slowly and clearly and checking for patients’ understanding when providing education or gathering information from people who speak English as a second language ( 15 ). White et al. ( 15 ) demonstrated that patients with higher provider mistrust felt that their provider’s communication style was less interpersonal and did not feel welcome as part of the decision-making process.

To the authors’ knowledge, there is no current literature review evaluating interventions focused on health literacy and diabetes management. There is a pressing need for such a comprehensive review to provide a framework for future intervention design. The objective of this literature review was to gather and summarize studies of health literacy–based diabetes management interventions and their effects on overall diabetes management. Medication adherence and glycemic control were considered secondary outcomes.

Search Strategy

A literature review was conducted using the PubMed, Medline, and EMBASE databases. Search criteria included articles published between 2015 and 2020 to identify the most recent studies on this topic. The search included the phrases “diabetes” and “health literacy” to specifically focus on health literacy and diabetes management interventions and was limited to original research conducted in humans and published in English within the defined 5-year period. Search results were exported to Microsoft Excel for evaluation.

Study Selection

Initial screening of the articles’ abstracts was conducted using the selection criteria to determine which articles to include or exclude ( Figure 1 ). The initial search results were reviewed for the following inclusion criteria: original research (clinical trials, cohort studies, and cross-sectional studies) conducted in human subjects with type 2 diabetes in the United States, and published in English between 2015 and 2020. Articles were considered to be relevant if diabetes was included as a medical condition in the study and an intervention was made to assess or improve health literacy. Studies involving type 1 diabetes or gestational diabetes and articles that were viewpoints, population surveys, commentaries, case reports, reviews, or reports of interventions conducted outside of the United States were excluded from further review. The criteria requiring articles to be from the past 5 years and from the United States were used because of the unique and quickly evolving nature of the U.S. health care system. Articles published more than 5 years ago or from other health care systems may have contributed information that was not applicable to or no longer relevant for HCPs in the United States. Articles were screened and reviewed independently by both authors. Disagreements were resolved through discussion to create the final list of articles for inclusion.

PRISMA diagram of the article selection process.

Data Extraction

A standard data extraction was performed for each included article to obtain information including author names, year of publication, journal, study design, type of intervention, primary outcome, tools used to assess health literacy or type 2 diabetes knowledge, and effects of intervention on overall diabetes management, glycemic control, and medication adherence.

A total of 1,914 articles were collected from a search of the PubMed, MEDLINE, and EMBASE databases, of which 1,858 were excluded based on the inclusion and exclusion criteria. Of the 56 articles that met criteria for abstract review, 46 were excluded because of a lack of relevance to both diabetes management and health literacy. The remaining 10 studies identified various diabetes management interventions, including diabetes education tools such as electronic medication instructions and text message–based interventions, technology-based education videos, enhanced prescription labels, learner-based education materials, and culturally tailored interventions ( 15 , 20 – 28 ). Figure 1 shows the PRISMA diagram of the article selection process, and Table 1 summarizes the findings of the article reviews ( 15 , 20 – 28 ).

Findings of the Article Reviews (15,20–28)

SAHLSA, Short Assessment of Health Literacy for Spanish Adults.

Medical mistrust and poor communication are challenging variables in diabetes education. White et al. ( 15 ) examined the association between communication quality and medical mistrust in patients with type 2 diabetes. HCPs at five health department clinics received training in effective health communication and use of the PRIDE (Partnership to Improve Diabetes Education) toolkit in both English and Spanish, whereas control sites were only exposed to National Diabetes Education Program materials without training in effective communication. The study evaluated participant communication using several tools, including the Communication Assessment Tool (CAT), Interpersonal Processes of Care (IPC-18), and the Short Test of Functional Health Literacy in Adults (s-TOFHLA). The authors found that higher levels of mistrust were associated with lower CAT and IPC-18 scores.

Patients with type 2 diabetes are also likely to benefit from personalized education delivery tools such as patient-centered labeling (PCL) of prescription drugs, learning style–based education materials, and tailored text messages ( 24 , 25 , 27 ). Wolf et al. ( 27 ) investigated the use of PCL in patients with type 2 diabetes and found that patients with low health literacy who take medication two or more times per day have higher rates of proper medication use when using PCL (85.9 vs. 77.4%, P = 0.03). The objective of the PCL intervention was to make medication instructions and other information on the labels easier to read to improve medication use and adherence rates. The labels incorporated best-practice strategies introduced by the Institute of Medicine for the Universal Medication Schedule. These strategies prioritize medication information, use of larger font sizes, and increased white space. Of note, the benefits of PCL were largely seen with English speakers. Spanish speakers did not have substantial improvement in medication use or adherence, which could be attributed to language barriers ( 27 ).

Nelson et al. ( 25 ) analyzed patients’ engagement with an automated text message approach to supporting diabetes self-care activities in a 12-month randomized controlled trial (RCT) called REACH (Rapid Education/Encouragement and Communications for Health) ( 25 ). Messages were tailored based on patients’ medication adherence, the Information-Motivation-Behavioral Skills model of health behavior change, and self-care behaviors such as diet, exercise, and self-monitoring of blood glucose. Patients in this trial were native English speakers, so further research to evaluate the impact of the text message intervention in patients with limited English language skills is still needed. However, participants in the intervention group reported higher engagement with the text messages over the 12-month period ( 25 ).

Patients who receive educational materials based on their learning style also show significant improvement in their diabetes knowledge and health literacy. Koonce et al. ( 24 ) developed and evaluated educational materials based on patients’ learning style to improve health literacy in both English and Spanish languages. The materials were made available in multiple formats to target four different learning styles, including materials for visual learners, read/write learners, auditory learners, and kinesthetic learners. Spanish-language versions were also available. Researchers were primarily interested in measuring patients’ health literacy and knowledge of diabetes. The intervention group received materials in their preferred learning style and language, whereas the control group received standard of care education materials. The intervention group showed significant improvement in diabetes knowledge and health literacy, as indicated by Diabetes Knowledge Test (DKT) scores. More participants in the intervention group reported looking up information about their condition during week 2 of the intervention and showed an overall improvement in understanding symptoms of nerve damage and types of food used to treat hypoglycemic events. However, the study had limited enrollment of Spanish speakers, making the applicability of the results to Spanish-speaking patients highly variable.

Additionally, findings by Hofer et al. ( 22 ) suggest that patients with high A1C levels may benefit from interventions led by community health workers (CHWs) to bridge gaps in health literacy and equip patients with the tools to make health decisions. In this study, Hispanic and African American patients with low health literacy and diabetes not controlled by oral therapy benefited from education sessions led by CHWs. The CHWs led culturally tailored support groups to compare the effects of educational materials provided in an electronic format (via iDecide) and printed format on medication adherence and self-efficacy. The study found increased adherence with both formats, and women, specifically, had a significant increase in medication adherence and self-efficacy. One of the important aspects of this study was that the CHWs shared cultural and linguistic characteristics with the patients and HCPs, leading to increased trust and satisfaction with the information presented ( 22 ).

Kim et al. ( 23 ) found that Korean-American participants benefited greatly from group education sessions that provided integrated counseling led by a team of nurses and CHW educators. The intervention also had a health literacy component that focused on enhancing skills such as reading food package labels, understanding medical terminology, and accessing health care services. This intervention led to a significant reduction of 1–1.3% in A1C levels in the intervention group. The intervention established the value of collaboration between CHW educators and nurses to improve health information delivery and disease management.

A collaboration between CHW educators and pharmacists was also shown to reinforce diabetes knowledge and improve health literacy. Sharp et al. ( 26 ) conducted a cross-over study in four primary care ambulatory clinics that provided care for low-income patients. The study found that patients with low health literacy had more visits with pharmacists and CHWs than those with high health literacy. The CHWs provided individualized support to reinforce diabetes self-management education and referrals to resources such as food, shelter, and translation services. The translation services in this study were especially important for building trust with non-English speakers and helping patients understand their therapy. Similar to other studies, the CHWs shared cultural and linguistic characteristics with their populations, which helped to overcome communication-related and cultural barriers ( 23 , 26 ).

The use of electronic tools or educational videos yielded inconclusive results with regard to medication adherence. Graumlich et al. ( 20 ) implemented a new medication planning tool called Medtable within an electronic medical record system in several outpatient clinics serving patients with type 2 diabetes. The tool was designed to organize medication review and patient education. Providers can use this tool to search for medication instructions and actionable language that are appropriate for each patient’s health literacy level. The authors found no changes in medication knowledge or adherence, but the intervention group reported higher satisfaction. On the other hand, Yeung et al. ( 28 ) showed that pharmacist-led online education videos accessed using QR codes affixed to the patients’ medication bottles and health literacy flashcards increased patients’ medication adherence in an academic medical hospital.

Goessl et al. ( 21 ) found that patients with low health literacy had significantly higher retention of information when receiving evidence-based diabetes education through a DVD recording than through an in-person group class. This 18-month RCT randomized participants to either the DVD or in-person group education and assessed their information retention through a teach-back strategy. The curriculum consisted of diabetes prevention topics such as physical exercise, food portions, and food choices. Participants in the DVD group had significantly higher retention of information than those in the control (in-person) group. The authors suggested this may have been because participants in the DVD group have multiple opportunities to review the education material.

Management of type 2 diabetes remains a challenge for HCPs and patients, in part because of the challenges discussed in this review, including communication barriers between patients and HCPs and knowledge deficits about medications and disease states ( 29 ). HCPs can have a positive impact on the health outcomes of their patients with diabetes by improving patients’ disease state and medication knowledge.

One of the common themes identified in this literature review was the prevalence of culturally tailored diabetes education interventions. This is an important strategy that could improve diabetes outcomes and provide an alternative approach to diabetes self-management education when working with patients from culturally diverse backgrounds. HCPs might benefit from using culturally tailored educational approaches to improve communication with patients and overcome the medical mistrust many patients feel. Although such mistrust was not directly correlated with diabetes management, it was noted that patients who feel mistrustful tend to have poor communication with HCPs ( 20 ). Additionally, Latino/Hispanic patients who have language barriers tend to have poor glycemic control ( 19 ). Having CHWs work with HCPs might mitigate some patient-provider communication barriers. As noted earlier, CHWs who share cultural and linguistic characteristics with their patient populations have ongoing interactions and more frequent one-on-one encounters ( 12 ).

Medication adherence and glycemic control are important components of diabetes self-management, and we noted that the integration of CHWs into the diabetes health care team and the use of simplified medication label interventions were both successful in improving medication adherence ( 23 , 24 ). The use of culturally tailored education sessions and the integration of pharmacists and CHWs into the management of diabetes appear to be successful in reducing A1C levels ( 12 , 26 ). Electronic education tools and educational videos alone did not have an impact on medication knowledge or information retention in patients with low health literacy, but a combination of education tools and individualized sessions has the potential to improve diabetes medication knowledge and overall self-management ( 20 , 22 , 30 ).

There were several limitations to our literature review. We restricted our search criteria to articles published in English and studies conducted within the United States to ensure that the results would be relevant to U.S. HCPs. However, these limitations may have excluded important work on this topic. Additional research expanding this search beyond the United States and including articles published in other languages may demonstrate different outcomes. Additionally, this literature review did not focus on A1C as the primary outcome, although A1C is an important indicator of diabetes self-management. A1C was chosen as the method of evaluating the impact of health literacy interventions in patients with diabetes, but other considerations such as medication adherence, impact on comorbid conditions, and quality of life are also important factors.

The results of this work show that implementing health literacy interventions to help patients manage type 2 diabetes can have beneficial results. However, such interventions can have significant time and monetary costs. The potential financial and time costs of diabetes education interventions were not evaluated in this review and should be taken into account when designing interventions. The American Diabetes Association estimated the cost of medical care for people with diabetes to be $327 billion in 2017, with the majority of the expenditure related to hospitalizations and nursing home facilities ( 16 ). Another substantial cost of diabetes that can be difficult to measure is treatment for comorbid conditions and complications such as cardiovascular and renal diseases.

Interventions designed to address low health literacy and provide education about type 2 diabetes could be a valuable asset in preventing complications and reducing medical expenditures. Results of this work show that clinicians who are considering implementing new interventions may benefit from the following strategies: using culturally tailored approaches, creating materials for different learning styles and in patients’ languages, engaging CHWs and pharmacists to help with patient education, using PCLs for medications, and engaging education session instructors who share patients’ cultural and linguistic characteristics.

Diabetes self-management is crucial to improving health outcomes and reducing medical costs. This literature review identified interventions that had a positive impact on provider-patient communication, medication adherence, and glycemic control by promoting diabetes self-management through educational efforts to address low health literacy. Clinicians seeking to implement diabetes care and education interventions for patients with low health literacy may want to consider drawing on the strategies described in this article. Providing culturally sensitive education that is tailored to patients’ individual learning styles, spoken language, and individual needs can improve patient outcomes and build patients’ trust.

Duality of Interest

No potential conflicts of interest relevant to this article were reported.

Author Contributions

Both authors conceptualized the literature review, developed the methodology, analyzed the data, and wrote, reviewed, and edited the manuscript. R.A. collected the data. K.M. supervised the review. K.M. is the guarantor of this work and, as such, has full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Prior Presentation

Portions of this research were presented at the Washington State University College of Pharmacy and Pharmaceutical Sciences Honors Research Day in April 2019.

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A review of the epidemiology of diabetes in rural India

Affiliation.

• 1 Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India. [email protected]
• PMID: 21458875
• DOI: 10.1016/j.diabres.2011.02.032

Objective: To describe the extent of problem of diabetes in rural India based on review of available literature and examine the secular trends over a period of 15 years i.e. from 1994 to 2009.

Methods: A systematic search was performed using electronic as well as manual methods. Studies providing details of sample size, age group of participants, criteria used for diagnosis, along with the prevalence of any of the three outcomes of interest i.e. diabetes mellitus, impaired fasting glucose (IFG) or impaired glucose tolerance (IGT), were included.

Results: Analysis of secular trends reveals an increase in diabetes prevalence among rural population at a rate of 2.02 per 1000 population per year. The rate of increase was high in males (3.33 per 1000 per year) as compared to females (0.88 per 1000 per year). High prevalence of IFG and IGT has been observed in southern and northern parts of the country.

Conclusion: The prevalence of diabetes is rising in rural India. There is a large pool of subjects with IFG and IGT at high risk of conversion to overt diabetes. Population-level and individual-level measures are needed to combat this increasing burden of diabetes.

Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Publication types

• Diabetes Mellitus / epidemiology*
• Glucose Intolerance
• India / epidemiology
• Rural Population

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• Open access
• Published: 04 November 2023

Comprehensive analysis of genes associated with migraine in the Indian population: a meta-analysis of genetic association studies with trial sequential analysis

• Amrit Sudershan 1 , 2 ,
• Agar Chander Pushap 3 ,
• Meenakshi Bhagat 4 ,
• Isha Sharma 4 ,
• Hardeep Kumar 5 ,
• Sanjeev K. Digra 6 &
• Parvinder Kumar   ORCID: orcid.org/0000-0003-1039-6638 1 , 4  

Scientific Reports volume  13 , Article number:  19070 ( 2023 ) Cite this article

Metrics details

• Genetic association study

Migraine is a complex disorder with multigenic inheritance and is characterized by the cardinal symptom of unilateral headache. Many genes are responsible for increasing the susceptibility of disease within different populations. Therefore, our primary aim in this review was to catalog the many genes that have been studied in India and after collecting the necessary information, we calculated a more precise risk relationship between an identified variation and migraine. The gene and its associated risk variant were discovered in the Indian population using a PRISMA-based systematic literature review guideline from online databases such as PubMed & Google Scholar. We constructed pooled odds ratios with 95% confidence intervals using multiple genetic models. Also, we looked for heterogeneity using Cochran's Q Test and the I2 statistic. Publication bias was analyzed using Begg's and Egger's tests. A p-value less than 0.05 was judged to be statistically significant for all tests. After a critical analysis, a total of 24 studies explored about 21 genes with 31 variants out of which only nine genes have been studied more than two times in the Indian population and thus were found eligible for the meta-analysis. It has been found, that the ACE- DD variant (allele model: OR: 1.37 [1.11–1.69], I 2  = 0%/ fixed model), ESR1- PvuII (allele model: OR: 1.47 [1.24–1.74], I 2  = 0%/ fixed model) significantly increases the risk of migraine in Indian population. Also, a protective role of the LRP1 -rs11172113variant was observed for both migraine and its clinical subtype i.e., MA (allelic model: OR of 0.65 [0.50–0.83] I 2  = 44% and allele: OR: 0.54 [0.37–0.78], I 2  = 52%) respectively. Overall, the results of this meta-analysis indicated that the ACE-DD variant and the ESR1-PvuII were associated with an increased risk of migraine in the Indian community, while the LRP1-rs11172113 variant was associated with protection from migraine in this population.

Introduction

Migraine is a complex and polygenic disorder, featuring different characteristics such as nausea, vomiting, phonophobia, photophobia, and interestingly the cardinal feature i.e., unilateral headache 1 . International Classification of Headache Disorder 3rd edition (ICHD-3) has classified the disorder into two main clinical subtypes i.e., Migraine with Aura (MA) and Migraine Without Aura (MWA) based on the criteria of presence and absence of aura feature (ICHD-3.org/1-migraine/). Various factors, such as cortical spreading depression (CSD), activation and desensitization of the Trigeminal-vascular system, neurogenic-neuroinflammation, etc., which are collectively responsible for the etiology of migraines, have previously been explored 2 , 3 , 4 , 5 , 6 . Factors that are responsible for increasing the risk of migraine are crucial and are broadly categorized into environmental and genetic factors. Former which is responsible for hindering the susceptibility threshold of pain which is set by the latter factor i.e., genetic risk factors 1 .

Genetic risk factors include genes with changes/variations in the gene sequence with a major type called Single Nucleotide Polymorphism (SNP) or Single Nucleotide Variation (SNV) which are responsible for altering the function of the same. The most recent and updated meta-analysis of the Genome-Wide Association Study (GWAS) data has shown that many genes with modest effects are involved in disease risk 7 . Other than the advanced GWAS, numerous independent studies have been carried out in various populations and have identified various genes that are responsible for disease risk attribution. Using India as an example of a population, which is part of the Asian ethnic group where migraine disorder is very common 8 , 9 , 10 , 11 , 12 , many genes have been studied (Table 1 ) but the association between these genes and migraine risk has been found to be inconsistent 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 .

As a result, in the current review study, we first sought to identify the different genes explored in the Indian population before pooling the risk of similar genes to determine the precise association in the same population. The current study is unique in that it is the first of its kind to include all of the risk genes and variants from the Indian population to determine the precise risk.

Literature survey

The presented review aimed to find out the critical genes that increase the risk of migraine and its clinical subtype in the population of India which belongs to the Asian ethnic group. To achieve the aim, we used the approach of a “systematic way of literature survey” which was done from the online database and search engines such as PubMed-NCBI (National Center for Biotechnology Information) (Pubmed.NCBI.nlm.nih.gov), and Google Scholar (Scholar.google.com.tw) respectively. We bypassed exploring other databases and utilized PubMed because of its comprehensive collection of references, which includes MEDLINE (Medical Literature Analysis and Retrieval System Online), life science journals, and electronic books.

Multiple key terms were used in our search strategy, including “Gene polymorphism with migraine in India OR Gene variant with migraine in India AND migraine genes in India OR migraine polymorphism in India”. Only articles published in the English language were evaluated using the linguistic filters as a factor for publication selection. We also tried to exclude study data if unpublished (Research Square/ Researchsquare.com), incomplete, or only partially available. Because partial and missing data are not included in the study, there is no such detrimental effect and we did our utmost to eliminate any undesirable characteristics. The search was completed and studies were included following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines ( www.prisma-statement.org ) (Supplementary Prisma Check List- S1 ) 38 .

Inclusion and exclusion features

Concerning the study inclusion criteria, the following inclusion criteria should be met and those include “A case–control or cohort study design must be the prime requirement followed by the “the study must represent the Indian population criteria” for the screening of study”, second the “authors must have investigated/ diagnosed the patients according to the criteria of the International Headache Society (IHS) or ICHD-3″ International Classification of Headache Disorders-3, the authors must have looked at the genetic polymorphisms/variants and must have provided the detailed description about the variant under study with proper reference ID (rsID) or change of nucleotide”, “the genotype frequencies of the investigated variants must be stated unambiguously among migraineurs and controls”, “Hardy–Weinberg Equilibrium (HWE) conditions are required for all experiments”, “studies should provide clear data to calculate the odds ratios (ORs) and the corresponding 95% confidence intervals (CI)”.When necessary information was missing from an article, it was sourced from another publication.

Data extraction

The demographic characteristics of each study were extracted, including the state in which the research was conducted, the number of patients and healthy individuals, any cohort data, the genotypic frequency from both cases and controls, the first authors, the years of publication, and the technique used to determine the genotype? Also features such as gene coding protein, chromosomal location, the function of a protein, and polymorphism ID/SNP-ID/rsID were extracted from the online data where required. If any statistical/numerical data were found missing, previous research/references were analyzed. All the data/features extraction was first done by our two authors (A.S, A.C.P, M.B, & I.S) and then the quality was assessed by the other two authors (A.S, A.C.P, & H.K).

Quality assessment

The quality of research articles is an important factor to consider when performing a meta-analysis, which entails pooling independent research studies to determine the precise result. In light of this, the present research assessed the quality of all previously published studies by utilizing the criteria established by the Newcastle–Ottawa scale (NOS) such as (1): selection of cases and controls that include cases and control definition, and their selection(2): comparability (comparability of cases and controls) and (3): ascertainment of exposures (exposure ascertainment, case, and control ascertainment, and non-response rate). Each section with the correct method is assigned one star (1 point) with an exception in Comparability” section which is with two stars (2 points). Therefore, a study will be disqualified if it receives fewer than 5 stars (< 5) (or 5 points), which is considered to be a good study and can only receive a maximum of 9 stars (Ottawa Hospital Research Institute (ohri.ca) (Supplementary File: S F1 -NOS). If any differences in decision-making were noticed concerning article inclusion, data extraction, or quality assessment/ NOS, the third investigator (P.K) investigated and concluded the matter.

Statistical analysis

Genotypic and allelic frequency was first calculated for all studies included in the meta-analysis and then the Chi-square test was used to analyze whether the population is in HWE (p > 0.05 for the population in HWE) or not (p < 0.05). To find out the strength of the association between the variant of interest, and the risk of migraine, the logistic regression utilizing OR (Odds Ratio) model with 95% CI (Confidence Interval) was used. Here odds ratio is defined as the OR > 1 is defined as the odds of exposure among cases being greater than the odds of exposure among controls & OR < 1: the odds of exposure among cases are lower than the odds of exposure among controls. Different genetic models such as allelic (rare allele vs. wild allele), dominant (dominant vs. heterozygote + pure recessive), recessive (recessive vs. dominant + heterozygote), and over-dominant (heterozygote vs. pure dominant + recessive) were used to observe the strength of association (OR) using random: Dersimonian and Laird method or fixed model (Inverse variance method) based on I 2 (I 2  > 75: Random model). I 2 is an estimate to define the proportion of inter-study variability attributed to chance rather than heterogeneity.

The publication bias including reporting bias and heterogeneity of the research studies were assessed using Begg's and Egger's tests and χ2 based on Cochran’s Q Test with I-square (I 2 ) tests respectively. Also, we performed the sensitivity analysis to observe the influence of individual studies on the pooled ORs and 95% CIs by the criteria of “exclusion of each study”.All tests were two-sided, and a value < 0.05 was considered statistically significant. The current meta-analysis process, from the choice of statistical tests to the analysis of the findings, was conducted following the Cochrane guidelines (Training.cochrane.org/handbook/current). All the statistical analysis was done with Meta-Genyo online Statistical Analysis System software (MetaGenyo: Meta-Analysis of Genetic Association Studies).

Trial sequential analysis

To reduce the possibility of random error, the current meta-analysis makes use of a method called Trial Sequential Analysis (TSA), which checks to see if the included trials have sufficient numbers of participants. Based on an overall risk of 5% and a relative risk reduction of 20% (with 80% power), the TSA tool (Copenhagen Trial Unit, Denmark) was used to compute the necessary information size for evaluating the validity of a meta-analysis. (TSA—ctu.dk). With specific settings “Set Effect Measure and model” (Effecet Measure: Odds Ratio, Model: Fixed), “Set Zero Event Handling (SZEH)” (Method: Constant, Value: 1.0, Included trials with no events: checked), “Set Confidence Interval (SCI)” (Conventional/ Coverage: 95%). There are, however, two basic possibilities: (1) no further research is needed if the cumulative Z value/curve exceeds the RIS (Required Information Size); (2) additional studies are needed if the Z curve does not surpass the RIS threshold.

Protein–protein interaction

It is critical to identify the most important wiring connection/most connected node/dot in the gene/protein interaction network used to understand disease progression because any change in the peripheral gene will eventually affect the regulation of the core gene/ most connected node 39 . Therefore, to analyze the most connected gene/node among the studied genes in the respective population, the String v11 (String-db.Org/), a potential protein–protein interaction tool that collects data from several online databases was used. After PPI (Protein–Protein Interaction), the network was built, edited, and analyzed using the Cytoscape tool version 3.9.1, a free and publicly available bioinformatics tool for analyzing and interpreting gene expression profiles, and molecular interaction networks (Cytoscape.org/).

Using the strategy of systematic way of literature survey (Fig.  1 ), a total of 24 studies was found (Table 1 ) which explored about 21 genes with 31 variants (Table 1 ) from 4 different states of India (3 states from north India and 1 state from south India) (Fig.  2 ) (Paint—Microsoft Apps). Only nine genes have been studied more than two times in the Indian population and thus were found eligible for the meta-analysis and these include six studies which have explored MTHFR gene 13 , 16 , 17 , 18 , 22 , 23 , three studies for ACE (I/D polymorphism) 13 , 17 , 24 , LRP1- rs11172113 19 , 26 , 28 , PRDM16- rs2651899 19 , 26 , TRPM8- rs10166942 and rs10504861 21 , 26 , ESR1 PvuII and XbaI 15 , 29 , 37 , DAO- rs10156191, rs2052129 20 , 35 and TNF-α G308A 25 , 30 .

Selection of literature according to PRISMA (Preferred Reporting Items for Systematics Reviews and Meta-Analysis) guidelines.

Indian Map representing different genes explored in 3 different states of India population.

Study characteristics

After finding nine genes eligible for meta-analysis, the second step was the inclusion into the meta-analysis of eligible studies which were done based on the NOS (Table 2 ) and HWE criteria. If the NOS were six or more than it and if the control population were in HWE respectively the study was included After which two variants such as A1298C of MTHFR and rs10166942 of TRPM8 were excluded due to not being found in HWE (Supplementary Tables 2 S1 and 5 S1).

Meta-analysis

Mthfr- c677t.

In the present analysis, a total of 842 cases and 882 control subjects were included which were found after the inclusion of five studies representing four from the north Indian population 13 , 16 , 17 , 18 and one from the south Indian population 22 and exclusion of one study due to not found in HWE 23 (Supplementary Table 1 S1). The frequency of the risk allele was 0.195 (n = 329/1684) in contrast to the wild allele 0.804 (n = 1355/1684)within the case group while in a control group, the frequency of the risk allele was 0.168 (n = 297/1764) in contrast to wild allele i.e., 0.831 (n = 1467/1764) in the control group.

To find out the association, a logistic regression model i.e., Odds Ratio associated with a 95% Confidence Interval, p-value < 0.05 were used. The present meta-analysis has shown that there was no significant association between the variant under study (C677T) and the risk of migraine in the Indian population after utilizing different genetic models and these include the allelic model (OR: 1.04 [0.84–1.29], I 2  = 53%) (Fig.  3 A), recessive model (OR: 1.31 [0.71–2.42], I 2  = 38%), dominant model (OR: 1.08 [0.72–1.62], (I 2  = 53%), and overdominant model (OR: 1.06 [0.70–1.60], (I 2  = 53%). Subgrouping based on the criteria of the ”study conducted in which region of India i.e., such as South India (SI) and North India (NI)”, no significant association was observed (Supplementary Table 11 S1). After sub-grouping based on the clinical subtype i.e., MA and MWA, there was no significant association was found with any genetic models.

( A ) Forest Plot of MTHFR allele model showing the non-significant association with the risk of overall migraine ( B ) Symmetrical Funnel Plot representing no publication bias.

Egger's test, which is based on the connection between standard error and strength of association (log of OR), was used to examine publication bias across all studies included in the meta-analysis (p-value = 0.35). By placing the most accurate research on top and the least precise studies at the bottom of a scatter plot, we were able to create a "funnel plot" that displays the distribution of accuracy across all investigations. All genetic models resulted in symmetrical funnel plots, indicating that no publication bias existed. (Fig.  3 B). The findings of a sensitive analysis performed on all genetic models by systematically removing individual studies showed that the pooled ORs were not significantly altered, confirming the excellent stability of the meta-analysis (Fig.  4 ).

Sensitive plot representing allele model.

There are 3 studies 13 , 17 , 24 (Supplementary Table 3 S1) that observed the frequency and association of polymorphism in the population of the Indian population. After pooling such independent studies, we found that the overall frequency of risk and wild allele was 0.410 (n = 289/704) and 0.589 (n = 415/704) in the patient group respectively. While in the control population, the frequency of the risk allele was considerably low i.e., 0.343 (n = 289/842) in comparison to the frequency of a minor allele in the patient group (q = 0.410).

The present meta-analysis found a significant association between the selected variant and risk of overall migraine after utilizing the allele (Fig.  5 A) and recessive model (OR: 1.37 [1.11–1.69], I 2  = 0%) and (OR: 2.05 [1.36–3.11], I 2  = 0%) respectively in contrast to dominant and over-dominant model (OR: 1.29 [0.96–1.73], I 2  = 0%) and (OR: 0.90 [0.67–1.19], I 2  = 24%) respectively. After subgroup based on the clinical subtype i.e., MA and MWA, the variant showed a significant association after utilizing different genetic modes such as allele (OR: 1.41 [1.06–1.88], I 2  = 0%), recessive (OR: 2.22 [1.29–3.83], I 2  = 0%) in contrast to dominant (OR: 1.32 [0.88–1.98], I 2  = 0%) and over-dominant model (OR: 0.90 [0.60–1.34], I 2  = 39%) in MA group in compare to MWA where allele and recessive model showed significant association (OR: 1.33 [1.05–1.70], I 2  = 42% and OR: 1.94 [1.21–3.11], I 2  = 11%) in comparison to dominant and overdominant model (OR: 1.26 [0.89–1.77], I 2  = 0% and OR: 0.90 [0.65–1.26], I 2  = 0%) respectively. In addition, subgrouping based on the criteria of the ”study conducted in which region of India i.e., such as South India (SI) and North India (NI)”, was not done due to all studies were from north India.

( A ): Forest Plot of ACE allele model showing the significant association with the risk of overall migraine ( B ): Symmetrical Funnel Plot representing no publication bias.

There was no evidence of publication bias because all funnel plots for genetic models were symmetrical (p-value = 0.68) (Fig.  5 B) (Supplementary Table 14 S1). The good stability of the meta-analysis was confirmed by the results of a sensitive study done on all genetic models by carefully removing individual research (Fig.  6 ).

In the present study, we found two variants such as PvuII and XbaI of ESR1 studies in the Indian population by three different research groups 14 , 29 , 37 (Supplementary Tables 6 and 7 S1). Concerning ESR1-PvuII, a significant association has been found where the allele (OR: 1.47 [1.24–1.74], I 2  = 0%), dominant (OR: 1.66 [1.30–2.12], I 2  = 0%), and recessive model (OR: 1.91 [1.31–2.77], I 2  = 0%) significantly increase the risk of migraine. After subgrouping based on clinical type criteria, a significant association was also found in both MA (Allele: OR: 1.72 [1.34–2.20], I 2  = 0%, dominant: OR: 2.63 [1.75–3.96], I 2  = 9%, overdominant: OR: 1.75 [1.23–2.50], I 2  = 0% and recessive: OR: 1.79 [1.07–2.98], I 2  = 0%), and MWA (allele: OR: 1.39 [1.15–1.67], I 2  = 11%, dominant: OR: 1.43 [1.10–1.87], I 2  = 55%), and recessive model: OR: 1.94 [1.30–2.89], I 2  = 0%).

Concerning, after critical literature analysis, only two research publications were found 29 , 37 discussing the impact of XbaI polymorphism on the susceptibility of migraine and its type. The pooled OR of both studies did not show any significant association with the risk of migraine or with the migraine sub-type (Supplementary Table 12 S1). All genetic models resulted in symmetrical funnel plots, indicating that no publication bias existed. The findings of a sensitive analysis performed on all genetic models by systematically removing individual studies showed that the pooled ORs were not significantly altered, confirming the excellent stability of the meta-analysis.

TNF-α G308A

After combining the two studies 25 , 30 (Supplementary Table 8 S1), there was a significant difference between the genotypic frequency in the patient group (GG: 77.80%, GA: 18.45%, & AA: 3.73%) in comparison to a control group (GG: 79.03%, GA: 18.43%, & AA: 2.53%). The frequency of risk allele (q) was found slightly more (q = 0.129) than the control group (q1 = 0.117).

When comparing the pooled results from the experimental (n = 856) and control (n = 868) groups, the association value was not statistically significant for any genetic model under study such as allelic (OR: 1.12 [0.84–1.51] I 2  = 68: random model), dominant (OR: 1.08 [0.77–1.50] , I 2  = 82%: random model), recessive (OR: 1.54 [0.70–3.39], I 2  = 0.0%: fixed model), and over-dominant model (OR: 1.00 [0.70–1.42], I 2  = 89%: random model) (Supplementary Table 15 S1). There was no subgrouping analysis in this variant since only one study investigated the clinical subtype 25 . All genetic models had symmetrical funnel plots, indicating that there was no publication bias. A sensitive investigation of all genetic models was also performed by removing each research one at a time. It was demonstrated that none of the pooled ORs were considerably influenced, indicating the meta-analysis findings' excellent stability.

LRP1 - rs11172113

In the present review, we found two studies 19 , 26 (Supplementary Table 9 S1) representing the north Indian population where the combined frequency of risk allele was less i.e., 0.198 (n = 163/410) in the patient's group in comparison to control group i.e., 0.29 (n = 174/600). To find out the risk using different genetic models, a protective role of variant (allelic model) (Fig.  7 A) was observed with an OR of 0.65 [0.50–0.83] (I 2  = 44%), dominant (OR: 0.48 [0.35–0.66], I 2  = 12%), in contrast to recessive and over-dominant (OR: 1.29 [0.22–7.59], I 2  = 91%) and (OR: 0.10 [0.00–5.43], I 2  = 88%) respectively where the non-significant association was observed.

( A ) LRP1 Allele showing the significant protective effect of a rare variant in the Indian population ( B ) Symmetrical Funnel Plot representing no publication bias.

After clinical sub-grouping of migraine, it was observed that allele (OR: 0.54 [0.37–0.78], I 2  = 52%), dominant (OR: 0.47 [0.30–0.73], I 2  = 0%), and over-dominant (OR: 0.54 [0.34–0.86], I 2  = 0%) significantly showed protective role in MA. But, in the case of MWA, only dominant (OR: 0.68 [0.49–0.95], I 2  = 58%) and over-dominant model (OR: 0.63 [0.45–0.88], I 2  = 0%) showed a protective role in contrast to allele (OR: 0.88 [0.46–1.68], I 2  = 82%) and recessive (OR: 1.12 [0.65–1.93], I 2  = 74%) where a non-significant association was observed. There was no evidence of publication bias because all genetic models produced symmetrical funnel plots(Fig.  7 B). The good stability of the meta-analysis was confirmed by the results of a sensitive study done on all genetic models by carefully deleting individual research(Fig.  8 ).

LRP1 migraine sensitivity plot for allele model.

DAO- rs10156191

After combining studies 20 , 35 (Supplementary Table 10 S1), it was observed that in the patient’s group, the heterozygote (CT: 29.42%) and homozygous recessive (TT: 5.71%) genotypes are slightly greater than the heterozygote (CT: 21.14%) and homozygous recessive (TT: 3.42%) genotype in control’s group. The frequency of the risk allele (q = 0.204) in the patient group was more than the frequency of the risk allele in the control group (q1 = 0.14).

The present meta-analysis provides pieces of evidence that allele (OR: 3.86 [0.37–39.98], I 2  = 81%) and recessive model (OR: 1.47 [0.69–3.12], I 2  = 52%) showed non-significant association with the risk of migraine in contrast to dominant (OR: 1.69 [1.19–2.42], I 2  = 69%) and over-dominant model (OR: 1.62 [1.12–2.34], I 2  = 13%) which significantly increase the risk of migraine in Indian population. All genetic models yielded symmetrical funnel plots, eliminating publication bias. A sensitive study on all genetic models carefully removing individual studies proved the meta-analysis's stability.

PRDM16 -rs2651899

Concerning PRDM16 - rs2651899 (Supplementary Table 4 S1), the frequency of the risk allele in the case group was slightly higher i.e., 0.469 (n = 459/978) compared to risk allele frequency in the control group i.e., 0.471 (n = 330/700). In addition, no significant association was observed in migraine or any clinical subtype (MA and MWA) after utilizing any genetic models (Supplementary Table 13 S1).

After finding a non-significant association for MTHFR- C677T, DAO - rs10156191, TNF-α G308A, and ESR1 -XbaI, the required sample size estimation was done for allele model using TSA. For the MTHFR- C677T, the last point of the Z-curve reached or positioned within the conventional boundary which is considered as a statistically non-significant zone therefore, we cannot conclude that there is any risk association between the variant under study and diseases. Therefore, to achieve power (RIS: 10,616) further studies are required (Fig.  9 ). Concerning remaining DAO - rs10156191, TNF-α G308A, and ESR1 -XbaI, the TSA showed “Boundary RIS is ignored due to little information use”.

TSA graph for MTHFR-C677T (allele model) showed a non-significant result with less sample size/ power therefore required more studies to find out the association.

In the present study, we also aimed to find the most connected node in the list of genes studied in the population of India. Therefore, the String database which is a potential PPI tool that collects data from several online databases was used. Concerning the PPI setting, medium confidence (40%-69%), with active interaction sources which include test mining, experiments, databases, co-expression, neighborhood, gene fusion, and co-occurrence were utilized. We found that there were 32 connections/ edges between the processed 16 nodes/protein with an average node degree of four and six expected number of edges, 0.683 of average local clustering coefficient, and a significant PPI enrichment p-value (1.57e-14). It was observed that the highest degree (Degree: 8) was found with TNF-α followed by APOE and SLC6A4 (Degree: 7) (Table 3 ). String PPI was later edited and presented using Cytoscape tool version 3.9.1, which is an open-source bioinformatics software platform for visualizing molecular interaction networks and integrating them with gene expression profiles and other state data (Fig.  10 ).

Protein–Protein interaction where the TNFA shows the highest node.

Migraine is considered a complex disorder with polygenic inheritance and it has been shown by the most recent and updated meta-analysis of GWAS data has shown that numerous genes contribute to the risk of diseases with small effect sizes 7 . Other than the advanced GWAS, multiple studies have been conducted in different populations and found different genes. Specifying with the example of population, many genes have also been explored in the Indian population belonging to Asian ethnic groups constituted of different states (Fig.  2 ). Within the same population, association disparity was found in many genes and risk of migraine. Therefore, the present meta-analysis aimed to find out the precise risk between the different genes that have been explored in the past.

We have found that the variant ”C677T” of MTHFR showed a non-significant association with the risk of overall migraine in the Indian population which supports the independent studies 13 , 16 , 18 in contrast to the positive association found by different independent studies 17 , 22 , 23 . Comparing the present pooled result with the most recent meta-analysis which discussed the association of C677T with the risk of migraine, showed a significant risk association 40 . However their selection of studies was before December 2018 and only two studies from the Indian population were included 13 , 18 and also missed the inclusion of one more study 17 . In addition to meta-analysis, we have also estimated the ”Required sample Size” using trial sequential analysis and observed that the Z-curve was unable to cross the required information/ sample size (Fig.  9 ). Therefore, we cannot conclude that there is any risk association between the variant under study and diseases and thus required more sample size.

Concerning the ACE -I/D polymorphism, the present meta-analysis showed a significant association between the variant of interest and the risk of migraine and both clinical subtypes such as MA and MWA. This present study supports the independent study by Jasrotia and group and Joshi and group 13 , 17 in contrast non-significant association was observed by Wani and group 24 . Interestingly all studies 13 , 17 , 24 were from north India, thus disparity between such might be due to different sample sizes i.e., control and case subjects. Evidence from the meta-analysis published in 2016 powered with 7334 patients and 22,990 control showed no relationship between the ACE I/D polymorphism and any migraine but upon subgrouping based on the criteria of ethnicity, they observed a protective effect against migraine with aura and without aura at least in the Turkish population 41 .

Regarding ESR1 and its variant studied in the Indian population, only PvuII showed a significant association with the risk of migraine including both of its clinical subtypes in contrast to XbaI. which was consistent with Kumar and group 29 in contrast to Ghosh and group 37 . The other intronic variant i.e., PvuII which is separated by the 50 bp from XbaI, two studies discussed the association in the respective populations, and upon combing both studies, the present pooled meta-analysis showed significant association with the risk of migraine including both of its clinical subtypes which supports the result observed by Joshi and group 14 in contrast to Kumar and group 29 .

TNF-alpha is known for its critical role in pro-inflammation and critical regulator of microglial activation which leads to the initiation of neurogenic-neuroinflammation 6 . But the presence of a functional variant i.e., − 308 G > A leads to elevated plasma level of protein thus hindering the susceptibility of inflammation threshold. In the present study, after analysis of two independent studies 25 , 30 we did not find any significant association after utilizing different genetic models and risk of migraine which was the opposite of what was observed by the included independent study 25 , 30 . This prime reason for such disparity might be due to the different regions one is from north India 25 and the other is from south India 30 . Therefore, it is very important to conduct more studies in the respective population to find out the precise result. Comparing our meta-analytic data with the pre-existing meta-analysis, the results were found consistent with different studies 30 , 42 , 43 , 44 in contrast to Chen and group 44 .

Concerning the LRP1 - rs11172113, the present review observed a protective role of variant (allelic model) (Fig.  7 A) with overall migraine, and such protective effect was found consistent with both of its clinical subtypes. Thus, the present pooled result supports the result that Ghosh and group previously observed 26 in contrast to Kaur and group 19 . Each study was observed in the north Indian population, but such disparity might be due to the low sample size and also the patient group was not in HWE 19 . Comparing our meta-result with the overall pooled result presented by Siokas and the group where they observed a non-significant association between the rs11172113 and risk of migraine (OR: 1,10 [0.84–1.44], I 2 : 68%) 45 .

Strengths and limitations of the present meta-analysis

The prime strength of the present pairwise meta-analysis is the strategy utilized for the literature survey, then the inclusion of searched studies based on the criteria discussed (Section ”Inclusion and exclusion features”), and secondly the use of statistical analysis for finding the risk association between the different risk variants and diseases under consideration. Thirdly, the presentation of pooled summary estimates is considerably simpler to understand. Fourth, we have also found the risk attribution between the selected variants and migraine subtypes (MA and MWA). Fifth, we also presented the protein–protein interaction in an attempt to find out the most connected node in the network of nodes selected from the population under study. Sixth, a precise risk attribution toward the risk of migraine within a specific population i.e., the Indian population has been established. Apart from the strength, the first limitation is that migraine is an extremely heterogeneous condition, as all studies have diagnosed the suspected individual using criteria of ICHD-3 / HIS, but still, there could be misclassification. Second, the present analysis is only limited to clinical subgrouping and no subgroup was done based on gender. Also, there was an incredible disparity in sample size between the studies. Also, the risk of non-significantly associated variants can be modified by different modifier genes which were not explored in the present study. Additionally, the risk of disease can be attributed to the interaction between the markers of the same gene. In addition, concerning with the included studies in the meta-analysis were not enough, therefore for a precise estimate, more studies are required.

Future perspectives

In the present study, we aimed to find out the critical gene or genes that are responsible for the significant risk attribution toward disease susceptibility within a specific population (India) using a high statistical meta-analytical research approach. Different genes such as ACE -I/D, and ESR1 -PvuII showed a significant association with the risk of migraine in contrast to LRP1- rs11172113 and MTHFR -C677T, PRDM16 -rs2651899, DAO -rs10156191which showed protective and non-significant association in respect to Indian population respectively. We also noticed that there was much disparity in the sample size between studies, specifically the patient’s group was even not found in HWE. Also, the ratio between case and control was not even equal in the different studies, and for a fixed sample size, the chi-square test for independence is most powerful if the number of cases is equal to the number of controls (i.e., 1:1) 46 . Additionally, we can increase or recruit more controls to boost the study's statistical power if we are unable to find enough cases, but only up to 4 controls for every one case. Given the expense of recruiting them, adding more controls (more than four) might limit the increase in statistical power beyond this ratio 47 . There have only been a few, sometimes just two, studies exploring specific variants, which makes it necessary for more research to be done to support the risk attribution hypothesis.

In conclusion, this present meta-analysis showed that the ACE-DD variant and ESR1- PvuII showed a significant risk of migraine in the Indian population in contrast to LRP1- rs11172113 which showed a protective role in the respective population.

Data availability

All data generated or analyzed during this study are included in this article. Further inquiries can be directed to the corresponding author.

Abbreviations

International classification of headache disorder 3rd edition

Migraine aura

Migraine without aura

Cortical spreading depression

Genome-wide association study

National center for biotechnology information

Medical literature analysis and retrieval system online

Preferred reporting items for systematics reviews and meta-analysis

International headache society

Hardy–Weinberg equilibrium

Confidence interval

Newcastle–Ottawa quality assessment scale

South India

North India

Single nucleotide polymorphism

Single nucleotide variation

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Acknowledgements

Authors are highly thankful to the Institute of Human Genetics, University of Jammu and Department of Human Genetics (Sri Pratap College, Srinagar, Cluster University Srinagar) for support in the present study.

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Institute of Human Genetics, University of Jammu, Jammu, Jammu and Kashmir, 180006, India

Amrit Sudershan & Parvinder Kumar

Department of Human Genetics, Sri Pratap College, Cluster University of Srinagar, Kashmir, Jammu and Kashmir, India

Amrit Sudershan

Department of Education, Dakshina Bharat Hindi Prachar Sabha, Madras, 600017, India

Agar Chander Pushap

Department of Zoology and Institute of Human Genetics, University of Jammu, Jammu, Jammu and Kashmir, 180006, India

Meenakshi Bhagat, Isha Sharma & Parvinder Kumar

Department of Neurology, Super Specialty Hospital, Jammu, Jammu and Kashmir, 180006, India

Hardeep Kumar

Department of Paediatrics, Sri Maharaja Gulab Singh Hospital, Government Medical College, Jammu, Jammu and Kashmir, 180006, India

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Sudershan, A., Pushap, A.C., Bhagat, M. et al. Comprehensive analysis of genes associated with migraine in the Indian population: a meta-analysis of genetic association studies with trial sequential analysis. Sci Rep 13 , 19070 (2023). https://doi.org/10.1038/s41598-023-45531-3

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• Published: 30 October 2023

Efficacy and safety of tirzepatide, dual GLP-1/GIP receptor agonists, in the management of type 2 diabetes: a systematic review and meta-analysis of randomized controlled trials

• Qian Zhou   ORCID: orcid.org/0000-0001-6957-9821 1   nAff2 ,
• Xingxing Lei 1 , 2 ,
• Shunlian Fu 1 ,
• Pan Liu 1 ,
• Cong Long 1 ,
• Yanmei Wang 3 ,
• Zinan Li 1 , 4 ,
• Qian Xie 1 &
• Qiu Chen 5  

Diabetology & Metabolic Syndrome volume  15 , Article number:  222 ( 2023 ) Cite this article

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Glucose-dependent insulinotropic polypeptide (GIP) and GLP-1 are the main incretin hormones, and be responsible for the insulinotropic incretin effect. The addition of a GIP agonist to a GLP-1agonist has been hypothesized to significantly potentiate the weight-losing and glycemia control effect, which might offer a new therapeutic option in the treatment of type 2 diabetes. The current meta-analysis aims to synthesize evidence of primary efficacy and safety outcomes through clinically randomized controlled trials to evaluate integrated potency and signaling properties.

We conducted comprehensive literature searches in Cochrane Library, Web of Science, Embase and PubMed for relevant literatures investigating the efficacy and/or safety of Tirzepatide published in the English as of May 30, 2023 was retrieved. We synthesized results using standardized mean differences (SMDs) and 95% confidence intervals (95 CIs) for continuous outcomes, and odds ratios (ORs) along with 95 Cis for dichotomous outcomes. All analyses were done using Revman version 5.3, STATA version 15.1 and the statistical package ‘meta’.

Participants treated with weekly Tirzepatide achieved HbA1c and body weight target values significantly lower than any other comparator without clinically significant increase in the incidence of hypoglycemic events, serious and all-cause fatal adverse events. However, gastrointestinal adverse events and decreased appetite events were reported more frequently with Tirzepatide treatment than with placebo/controls.

The Tirzepatide, a dual GIP/GLP-1 receptor co-agonist, for diabetes therapy has opened a new era on personalized glycemia control and weight loss in a safe manner with broad and promising clinical implications.

Introduction

Type 2 diabetes (T2D) is a chronic metabolic condition marked by hyperglycaemia that requires stepwise addition of multiple glucose-lowering medications as the disease progression [ 1 , 2 ]. The net result is a viscous cycle of hyperglycaemia leading to continuous deterioration of metabolic function and necessitating insulin therapy in many cases. Obesity is one of the major modifiable risk factors for type 2 diabetes. The parallel rising prevalence of obesity and T2D (name "diabesity") present a principal global health challenge with increased risk for overall mortality [ 3 ]. In patients with T2D, Glucagon-like peptide-1 receptor agonists (GLP-1Ras) improve the regulation of glucose homeostasis, weight-losing, and long-term benefit cardiovascular outcomes, which have been demonstrated to be accompanied by improved micro- and macrovascular risk factors [ 4 , 5 ]. While real-world evidences of the broad metabolic benefits of GLP-1Ra have emerged, many patients do not achieve their individualised glycemic and body weight (BW) targets with the currently approved incretin, making continuous optimization of these agents an important clinical goal [ 6 ]. Individualizing the glycemic and BW targets for diabesity patients is now the guideline-recommended strategy [ 7 ], how therapy could accomplish this is unknown. Moreover, dose dependent gastrointestinal effects of GLP-1Ra limits the efficacy. Therefore, agents possessing GLP-1 pharmacology that can active alternative pathways might expand the therapeutic index for T2D.

Glucose-dependent insulinotropic polypeptide (GIP) and GLP-1 are the main incretin hormones, potentiate glucose-induced insulin secretion and therefore be responsible for the insulinotropic incretin effect [ 8 ]. The incretin effect accounts for at least 50% of total insulin secreted after oral glucose consumption [ 9 ]. GLP-1 has been exhibited central inhibitory actions on appetite and food intake, comparatively little is seen with the central activity of GIP on appetite [ 10 ]. Emerging evidence has illustrated that combining the GLP-1Ras with GIP Ras is an integrated potency to achieve significantly weight-losing along with glycemia control effect [ 11 ], which may provide a novel therapeutic option for the treatment of T2D [ 12 ]. Tirzepatide (LY3298176), a dual GIP and GLP-1 Ra, was discovered by engineering GLP-1 activity into the GIP sequence, which has the potential to be one of the most effective therapeutics for treating T2D with respect to both glycemia and body weight control as the disease progresses [ 11 ]. The preliminary clinical study showed Tirzepatide was superior to titrated insulin degludec (ID) with unprecedented efficacy in HbA 1c  and body weight in T2DM as approximate thirty percent of patients receiving subcutaneous injection of Tirzepatide 15 mg weekly returned normoglycemia (HbA1C < 5.7% per the American Diabetes Association definition) and a quarter of subjects lost more than fifteen percent (− 7·5 to − 12·9 kg for all Tirzepatide doses) of their weight in a 52-week trial [ 12 ]. Furthermore, Tirzepatide has be the first dual agonist (GLP-1 and GIP Ra) to be licensed for diabetes therapy.

Hence, we hypothesized Tirzepatide possess a unique profile tailored of pharmacology with the synergetic effect and signaling properties in regulating extensive metabolic control. We aimed to systematically retrieve all available randomised, placebo-controlled trials of Tirzepatide in individuals with T2D to discuss evidence for this hypothesis, synthesize evidence of primary efficacy and safety outcomes, and evaluate integrated potency and signaling properties through a clinically relevant systematic review and meta-analysis. Our meta-analysis results will help clinicians to determine the optimal application of Tirzepatide in clinical practice and optimize diabetes management strategies for individuals with T2D.

The protocol for this meta-analysis has been registered on Prospero, the international prospective register of systematic reviews, under the identifier CRD42022355940 ( https://www.crd.york.ac.uk/prospero/#myprospero ). We adhered to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines for conducting, reporting and updating the systematic review and meta-analysis (Additional file 1 : Table S1) [ 13 ].

Search strategy

We conducted a literature search to identify published randomized placebo-controlled trials that tested T2D patients with a weekly subcutaneous injection of a maintenance dose of 5, 10, or 15 mg of Tirzepatide as glucose-lowering medication. Cochrane Library, Web of Science, Embase and PubMed were searched comprehensively for relevant literatures investigating the efficacy and/or safety of Tirzepatide for reports published in the English and up to 30 May 2023. The search strategy included medical subject heading (MeSH) terms and scientific name of the keywords ‘Tirzepatide’, ‘ly3298176’ and ‘Twincretin’. We also manually searched the databases to identify any additional studies, reviews and references lists of eligible studies and conference proceedings.

Study selection

This updated review included trials with a cross-over or parallel design that compared Tirzepatide at three doses (5 mg, 10 mg and 15 mg) with placebo or various hypoglycemic comparators in patients with T2D and evaluate any predefined outcomes of interest, efficacy and safety parameters related to the treatment. The criteria of the individuals with T2D meet the following requirements: (a) individuals with a medical history of physician-diagnosed T2D; or (b) the individuals without prior history of T2D, but with uncontrolled glycemic after admission or taking medication and a new diagnosis of T2D comprised the diabetic group. Eligible study participants were adults (aged 18 years or older) diagnosed with type 2 diabetes, irrespective of either diet and exercise alone or oral antihyperglycaemic medication, for at least 3 months before screening. The databases search results were imported into the reference management software (Endnote V 9.3) and juxtaposed with the results from other search sources after data deduplication. All citations that were generated by the literature search were screened by one reviewer (QZ) and verified by a second independent reviewer (XX) on the basis of title and abstract. The full-text literatures were obtained for all citations of interest and were assessed were screened independently by two reviewers (CL, QC), and any disagreements were resolved by a third reviewer (SL).

Data extraction

We used pre designed forms to extract data for eligible studies. Data extraction procedure included bibliographic information, participants’ demographics and clinical characteristics when present, and information on intervention and outcomes. Two reviewers (SF, QC) independently extracted data in duplicate and tabulated all information extracted from the included studies. Any discrepancies shall be resolved by consensus. Among the included literatures, the primary metabolic parameters end point was the mean absolute changes from baseline in hemoglobin A1c (HbA1c, %), fasting serum glucose (FSG, mg/dL), body weight (BW, kg), and triglyceride (TG, mg/dL), HDL cholesterol (HDL-c, mg/dL), and LDL cholesterol (LDL-c, mg/dL) with Tirzepatide at different doses monotherapy or as adjunctive therapy with various stable antihyperglycaemic therapy, diet and exercise alone or oral medication, and/or insulin, in patients with T2D. Secondary efficacy endpoint was the mean changes of safety and tolerability outcomes of Tirzepatide at different doses. For subgroup, we extracted data at the corresponding time point and glucose-lowering agents of placebo/control group to appraise the efficacy and safety outcomes of Tirzepatide at different doses. Primary outcomes are extracted based on means, standard deviations (or standard error), and the number of patients randomized in each study arm for continuous outcomes. With regard to safety and tolerability outcomes, we considered all adverse events (AEs), serious AEs, Fatal AEs, hypoglycemic events (HEs) (blood glucose level ≤ 5.4 mmol/l), gastrointestinal events (mainly including nausea, vomiting and diarrhoea), decreased appetite, and AEs leading to discontinuation of therapy.

Quality and risk-of-bias assessment

Included trials were assessed for bias with the Cochrane risk-of-bias tool [ 14 ]. Two reviewers (QZ, XX) independently assessed the methodological quality and risk of bias for the primary outcomes in duplicate, and if there were any disagreements, a senior reviewer (QC) would arbitrate. The overall risk of bias was judged to be high in the presence of high bias for one or multiple domains raised concerns, low if all key domains were at low risk of bias, and unclear risk of bias if at any domain was unclear. We evaluated the potential for publication bias and investigated the presence of small study effects for the primary outcomes with visual inspection of the funnel plot and Egger's test. A two tailed P value < 0.05 was considered significant.

Data synthesis

We synthesized results using standardized mean differences (SMDs) and 95% confidence intervals (95 CIs) for continuous outcomes, and odds ratios (ORs) along with 95 CIs for dichotomous outcomes with a fixed-effect model (Mantel–Haenszel approach) or a random-effect model (DerSimonian–Laird method) based on I 2 value (I 2  < 50%, low heterogeneity; I 2  ≥ 50%, high heterogeneity). For dichotomous outcomes. In the case of missing standard deviations (SDs), we calculated them from standard errors, corresponding 95 CIs, interquartile ranges, or other measures (if available) [ 15 ]. All the efficacy estimates were presented as means changes and 95% CIs from baseline unless otherwise noted. We performed separate analysis based on tirzepatide maintenance dose (5 mg, 10 mg or 15 mg) and subsequent subgroup-analyses based on various type of comparators (Placebo, GLP-1 Ra and Insulin). For the potential statistical interstudy heterogeneity, p values were measured from Cochran’s Q test and quantified by using Higgins I 2  statistic. All analyses were done using ReVman version 5.3, STATA version 15.1 and the statistical package ‘meta’.

Study characteristics

After detailed screening, altogether 14 trails met the inclusion criteria, the flow chart of the database search and the study selection process was shown in Fig.  1 . All trials were of substantial size, with 11,158 patients were eventually included in the meta-analysis (Table 1 ). These 14 trials include therapy naive patients (only healthy lifestyle education and dietary interventions) and participants receiving background anti-hyperglycaemic therapy comprised metformin, Sodium-glucose cotransporter 2 (SGLT2) inhibitor or insulin, either as monotherapy or in combination with other medications. The comparators included placebo, GLP-1 Ra and insulin. Among them, four studies are placebo controlled, six trials were conducted with GLP-1 Ra as comparators (Dulaglutide and Semaglutide), four trials are long-acting insulin analogues (Insulin Glargine/IG and Insulin Dulaglutide/ ID). The basic characteristics of participants in treatment and placebo/control groups were similar, such as baseline age and diabetes duration, with a weighted means of 57.9 ± 2.6 kg and 8.7 ± 2.4 years, respectively. All trials used a parallel group design, and three were open-label with follow-up duration ranged from 8 to 72 weeks.

Flowchart of literature search

All included trials were assessed for bias with the Cochrane risk-of-bias tool and all studies exhibited a low risk of selection bias, performance bias, detection bias, and reporting bias. Therefore, overall quality and risk-of-bias for the primary outcomes were assessed as high quality with a low risk of bias (Figs.  2 , 3 ). Other main baseline characteristics of the included RCTs, such as the design, name and dose of study drugs, study details, demographics and outcome-specific data, are reported in Table 1 . In addition, no test for publication bias was conducted due to the limited numbers of the included studies on parameters discussed.

Overall summary of risk of bias in the included studies. + : low risk of bias; −: high risk of bias; ?: unclear risk of bias

Summary of quantitative data analysis with Random effects or fixed effects SMD (95% CI) estimate with a p-value for analysis of primary efficacy outcomes. * Statistically significant variables at P value < 0.05. a Fasting serum glucose, b hemoglobin A1c, c body weight, d triglyceride, e HDL cholesterol, f LDL cholesterol

Glycolipid metabolism

Fasting serum glucose.

The synthesized results of meta-analyses for available data showed a significant reduction in FSG (SMD = − 1.57, 95% CI: − 1.63 to − 1.51, P < 0.05) versus placebo/controls for combined tirzepatide arms intervention group (Table 2 ). Regarding the three different doses of the tirzepatide, a significant decrease in FBG of tirzepatide 10 mg (SMD = − 1.68, 95% CI: − 1.78 to − 1.58, P < 0.05), and superior reduction in tirzepatide 15 mg (SMD = − 4.10, 95% CI: − 4.23 to − 3.97, P < 0.05) was observed. However, the opposite results were observed in the tirzepatide 5 mg subgroup (SMD = 0.19, 95% CI: 0.09 to 0.29, P < 0.05). Numbers and types of drug discrepancies, medication histories, experimental design and approaches in detecting might be the source of these inconsistent results. Therefore, we analyzed each efficacy and safety outcome and different doses of tirzepatide separately based on the type of comparators (Placebo, GLP-1 Ra and Insulin).

Compared with placebo and GLP-1 Ra, all three doses of tirzepatide had a more significant and consistent effect on FSG reduction (all P < 0.05). Compared with insulin (insulin degludec and insulin glargine), except for the 5 mg subgroup (SMD = 0.57, 95% CI: 0.46 to 0.67, P < 0.05). All other subgroups of parameters were consistent with significant statistical significance. Further details can be found in Table 3 . There was difference in the glucose lowering effect between insulin and low tirzepatide dose (5 mg). Of note, the mean subcutaneous injection dose of basal insulin during the study duration was 10 U/day with ID in the SURPASS-3 Randomized Clinical Trial [ 16 ], 10 U/day with IG in SURPASS-4 Trial [ 17 ], > 20 IU/d or > 0.25 IU/kg/d with IG in SURPASS-5 Trial [ 18 ], and 0.33 U kg −1 d −1 with IG in SURPASS-AP-Combo trial [ 19 ].

All tirzepatide doses (5, 10 and 15 mg) significantly reduced HbA1c percent and were superior to various comparators (Placebo, GLP-1 Ras and Insulin) (Tables 2 , 3 ). The results show evidence of a dose-dependent reduction in HbA1c percent versus placebo with tirzepatide 5 mg (SMD = − 4.29, 95% CI: − 4.44 to − 4.14, P < 0.05), 10 mg (SMD = − 2.306, 95% CI: − 9.93 to − 9.45) and 15 mg (SMD = − 9.84, 95% CI: − 10.09 to − 9.6). In all included 12 literatures, only one article reported that there was no significant difference between Tirzepatide 5 mg and Semaglutide 2 mg in change from baseline in HbA1c at week 40 with an estimated treatment difference (ETD) of 0.07% (95 CI: 0.2–0.34; P = 0.606) [ 20 ]. The other 11 articles found that the hypoglycemic hemoglobin effect of three doses (5, 10 and 15 mg) of tirzepatide were superior to any active comparator (placebo, dulaglutide, semaglutide, insulin glargine and insulin degludec). In SURPASS 1–5 Trials, the synthesized results of HbA 1c reduction were between 1.69 to 2.58% across the doses ranging from 5 to 15 mg of tirzepatide once a week, with approximately 24–30 weeks of tirzepatide treatment to reach a new plateau of HbA 1c  and FPG [ 16 , 17 , 18 , 21 , 22 ].

Body weight

Similar to the results of HbA1c, a statistical dose-dependent reduction in BW of three tirzepatide dose groups when compared to the placebo group was observed (all P < 0.05, Table 2 ). Consistently, compared with various anti-hyperglycaemic agents, patients receiving all tirzepatide doses were more efficacious than all comparators with respect to BW loss. Any of the three doses was superior to GLP-1 RAs in achieving significant weight-loss (Table 3 ). The superiority of tirzepatide with respect to BW control was more effective in the comparison versus insulin (Table 3 ). Furthermore, our system-review results have showed evidence of a reduction in bodyweight with subjects dosed with all tirzepatide doses compared with all comparators in the all eligible RCTs. Five clinical trials of SURPASS 1–5 in T2DM subjects have shown that Tirzepatide at 5, 10 or 15 mg weekly reduces BW (5.4 to 11.7 kg) by amounts unprecedented for a single agent [ 16 , 17 , 18 , 21 , 22 ].

Lipid metabolism

There are two RCTs were included to compare the changing in lipid metabolism between the tirzepatide and placebo/control groups. As 40/26 weeks follow-up, the lipid metabolism was significantly improved in all tirzepatide dose treatment groups. More data details are summarized in Table 2 . For Triglycerides (TG), the results of present meta-analysis indicated that there was a significant reduction in all three tirzepatide doses groups with a dose-dependent reduction (SMD = − 5.651, 95% CI: − 5.816 to − 5.485, P < 0.05). However, the opposite results were obtained for Lipoprotein cholesterol (LDL-c). Meta-analysis results show that tirzepatide is not as effective as the control group in reducing LDL-c excluding 5 mg subgroup. For HDL cholesterol (HDL-c) level, there was a substantially increased following tirzepatide administration compared with the placebo/control group (SMD = 2.974, 95% CI: 2.869 to 3.079, P < 0.05). Of note, the type of anti-hyperglycaemic agents and mean dose during the study duration were 1 mg/week with semaglutide [ 22 ], and 1.5 mg/week with dulaglutide, respectively, in the two trials [ 23 ]. Due to the insufficient number of trials reporting lipid outcomes, no analysis was made on other lipid species (such as Total cholesterol).

Safety and tolerability of tirzepatide

All adverse events.

Compared with Insulin, AEs were more frequent with all tirzepatide doses, especially 15 mg (RR = 1.12; 95% CI 1.06 to 1.18) (Table 4 , Fig.  4 ). Compared with GLP-1 Ras, more subjects receiving Tirzepatide 10 mg and 15 mg experienced AEs, while no statistical significance was observed for Tirzepatide 5 mg (Table 4 ). Of note, there was no statistical significance be found when comparing all doses of tirzepatide with placebo separately (P ≥ 0.05, Table 5 ). These AEs were more common in the 10 mg and 15 mg cohorts compared with lower (5 mg) cohort, indicating a dose-dependent increase in AEs production correlating with increased Tirzepatide.

Summary of count data analysis with random effects or fixed effects ORs (95% CI) estimate with a p-value for analysis of primary safety outcomes. *Statistically significant variables at P value < 0.05. a All adverse events, b gastrointestinal events, c decreased appetite, d hypoglycemic events, e discontinuation of therapy, f serious adverse events, g fatal adverse event

Gastrointestinal and decreased appetite events

In clinical trials of tirzepatide intake, the frequently and significantly observed AEs were related to the gastrointestinal system, generally mild or moderate in nature, and nausea, vomiting and diarrhoea were the most commonly adverse effects. Frequency of serious GEs was similar between Tirzepatide and placebo arms. In terms of insulin, statistical analysis was not performed due to limited subgroup. Compared with GLP-1 Ras, gastrointestinal adverse was more frequent with tirzepatide 10 mg and 15 mg, and occurred at a similar incidence on tirzepatide 5 mg (Table 4 ). However, in comparison with placebo/control group, GEs occurred at a higher incidence on tirzepatide 15 mg.

Decreased appetite was the second most commonly AEs with the incidence was reported ranging from 3.8% to 18.9% in tirzepatide treatment groups [ 24 ]. Our meta-analysis results have indicated that all three tirzepatide doses experienced reduced appetite more frequently than all comparators and display some dose-dependency, except Tirzepatide 5 mg. Therefore, it is speculated that tirzepatide produced a more significant effect on glycemic control and weight loss by inhibiting appetite and food intake [ 11 ].

Hypoglycemic events

Frequency of serious HEs was observed no statistical significance between all tirzepatide dose and GLP-1 Ras arms (Tables 4 , 5 ). However, the incidence of all tiracetide doses (5, 10 and 15 mg) was significantly lower than Insulin in terms of hypoglycemia. Compared with Placebo, more subjects taking Tirzepatide experienced hypoglycaemia (Table 4 ). Evaluation of the total hypoglycemic events across all included articles yielded a significant decrease in HEs when all dose groups compared to the control group (Tables 4 , 5 ).

discontinuation of therapy

Our current results found that DT caused by AEs was similar between any of the tirzepatide doses and placebo arms. Compared with GLP-1 Ras, more subjects receiving Tirzepatide 10 mg and 15 mg experienced DT, with no significant difference for Tirzepatide 5 mg (Table 4 ). Compared with insulin, DT due to adverse events occurred at a higher incidence on Tirzepatide 10 mg and 15 mg dose. Therefore, Tirzepatide increased odds of DT when compare with GLP-1 RAs or insulin.

Serious and fatal adverse events

Individual serious AEs have been found no difference in either arm, except Tirzepatide 5 mg compared to GLP-1 Ras. (Tables  4 , 5 ). Across all trials, none of the deaths were considered by the investigators to be related to tirzepatide. We speculate that Tirzepatide was not associated with increased rates of serious AEs and all-cause mortality.

Specifically, participants treated with weekly tirzepatide achieved HbA1c and BW target values significantly lower than any other comparator without clinically significant increase in the incidence of hypoglycemic events, serious and all-cause fatal adverse events when compared with placebo/controls. However, gastrointestinal adverse events and decreased appetite events were reported more frequently with tirzepatide treatment than with placebo/controls.

This systematic review and meta-analysis was designed to summary and synthesis the main efficacy and safety outcomes from the most up-to-date RCTs of weekly tirzepatide doses of 5 mg, 10 mg and 15 mg in individuals with type 2 diabetes. Based on our meta-analysis results, the dose-dependent reduction of HbA1c, FBG and BW induced by tirzepatide compared with placebo and weekly GLP-1 receptor antagonist, as well as insulin regimen has important clinical significance. In terms of lowering of lipid, Tirzepatide resulted in a dose-dependent improve of TG when compared with the GLP-1 Ras (1 mg/week with semaglutide and 1.5 mg/week with dulaglutide). Moreover, our system-review found the most commonly observed side effects were GE and decreased appetite in comparison with various anti-hyperglycaemic agents. The decreased appetite might be contributed to the reduction in weight and it is consistent with previous research reports [ 25 ], indicating a more profound effective on regulating food intake and satiety compared with GLP-1 RAs. [ 26 ] Considering the gastrointestinal system, study has suggested the lower incidence of treatment-related gastrointestinal system did seem to be associated with Lower initial dose and smaller subsequent dose increment [ 27 ]. The incidence of GE and discontinuation due to AEs were similar when compared Tirzepatide with placebo. Therefore, we speculated that the increased odds of DT vs all comparators might be attributed to the severity of GEs experienced with tirzepatide. Notably, this beneficial hypoglycemic effect of tirzepatide was not associated with increased incidence of hypoglycemic events, serious and all-cause fatal adverse events. These results indicate it is possible to achieve well established, but stringent, individualizing the glycemic and BW targets for diabesity patients in a safe manner.

We identified three previous systematic review and meta-analysis with tirzepatide treatment for T2DM, which included four (2783 participants), seven (6609 participants) and six trials (3484 participants), respectively, thorough literature retrieve and review [ 28 , 29 , 30 ]. Discrepancies of include literatures and research methodology render the results of these meta-analysis non-comparable to our findings. Specifically, Bhagavathula et al. summarized the efficacy results in meta-analysis, regardless of the type of comparators (insulin, GLP-1 Ras or placebo) [ 28 ]. In the meta-analysis of Thomas Karagiannis and colleagues [ 29 ], no analysis was performed on the efficacy of blood glucose and blood lipid. The three articles have important limitation of insufficient literature. Dutta, D and colleagues [ 30 ] did not analysis base on therapeutic doses and comparators. Given the availability of new outcomes data and relative importance of this study, we have updated this previous literature search and meta-analysis. Instead, we opted to summary and synthesis systematic review results and produce meta-analysis estimates with potential clinical relevance and value by conducting separate analysis based on different therapeutic doses (5 mg, 10 mg and 15 mg) and type of comparators for HbA 1c , FBG, BW and lipid outcomes with included all RCTs of tirzepatide in the treatment of T2DM published to date. Moreover, the present meta-analysis provides a comprehensive assessment of safety and tolerability results, which is also important the evaluation of efficacy when opting an optimal therapy in clinical treatment.

Recently, unimolecular, multifunctional peptides combining GLP-1Ra with GIP has been considered as a promising therapeutic agent for insight against T2DM, suggested that these two incretins can act on β-cells through distinct metabolic effects synergistically and complementarily [ 31 ]. Acting on both GIP and GLP-1 receptors to potentiate glucose-induced insulin secretion and improve glucose tolerance is attractive because the combination of these mechanisms is hypothesized that the metabolic action of GIP adds to the established clinical benefits of selective GLP-1 Ras, decreasing energy consumption, improving white adipose tissue health and function, increasing insulin response and glucagonostatic response [ 11 ]. Studies have shown that the GIP/GLP-1Ras action did not affect the incretin effects on GIP-stimulated insulin secretion, and strengthened the inherent efficacy and broadened their therapeutic range when both the GIP receptor and GLP-1 receptor are activated [ 32 , 33 ]. We reviewed the multiple functions of GIP/GLP-1RAs in regulating metabolism and energy balance in the contexts of up-to-date findings in T2D indicating that dual GIP/GLP-1As therapy produced profound weight loss, glycemic and BFG control, and lipid improving.

Specifically, multi-functional peptides of GLP-1RAs improve glycemic control by stimulating the glucose-induced insulin secretion [ 34 , 35 ], delaying gastric empty [ 36 , 37 ], and limiting plasma glucagon level [ 38 ], and activating anorexigenic pathways to inhibit of appetite and food intake [ 39 ]. The main difference between GIP and GLP-1Ras is stimulation of plasma glucagon release. Unlike GLP-1, GIP is reportedly glucagonotropic in normoal and/or hypoglycemic state, and normally suppresses glucagon secretion in the hyperglycaemic state [ 40 ]. Regarding adipose tissue regulation of GIP, the consistent report has yet to be established. Some studies had investigated the biological activity of GIP on adipocytes and indicated that GIP is implicated in adipose tissue mass and metabolism by regulating glucose uptake [ 41 ], lipolysis [ 42 ], and the activity of lipoprotein lipases [ 43 , 44 ], some of which suggest the adipogenic effect of GIP with studies indicating GIPR knockout mice and chronic elevation of serum GIP levels in a transgenic mouse would inhabit diet-induced obesity [ 44 , 45 ]. Furthermore, other studies demonstrated that acute GIP infusion to human would increase adipose tissue blood flow [ 46 ], promote insulin sensitivity, glucose tolerance and β-cell function [ 45 ]. A hyperglycemic clamp study has found that GLP-1R expression decreased but GIP R expression increased under the effect of acute hyperglycemia, and is similar with the experimental results of culturing at high-glucose concentrations for 48 hours [ 47 ]. Peptide engineering enables the synthesizing of structural motifs, which would be a hybrid peptide with dual agonism [ 48 , 49 ]. The GLP-1 Ras acts synergistically with GIP activation gain a broad improvement in metabolic health with the hypothesis that enhancing insulin secretion by dual actions on pancreatic β cells [ 50 ], allowing greater weight loss [ 11 ], improving glycemia [ 29 ], restoring sensitivity to GIP [ 51 ] and additional mechanisms of actions [ 5 , 11 ] when compared with single GLP-1 RA or GIP. Therefore, combining the GLP-1 Ras with GIP receptors would produce an effective treatment for diabetes with optimum individualizing the glycemic and BW targets.

Terzepatide is currently the first hybrid peptide with dual GIP/GLP-1 receptor co-agonist approved for improving glycaemic control in patients with T2D, as an adjunct to diet and exercise, in the United States, Europe and the United Arab Emirates [ 24 ]. In addition to the above efficacy, Tirzepatide has been demonstrated to improve intrahepatic triglycerides in T2D when compared to insulin degludec [ 52 ], which may provide new therapeutic strategy for patients with fatty liver as describing for GLP-1 RAs [ 53 ]. Although this compound with subcutaneous injection weekly have achieved unprecedented results in glucose control and weight loss employed in many clinical trials, the quantities may significantly change the potential pathogenesis of T2D [ 54 ] and is related to the remission of diabetes [ 55 , 56 ]. In addition, there are some novel questions with respect to pathogenesis should be addressed as the physiological changing of diabetes, such as disease progression, long-term prognosis, macro- and microvascular complications. More clinical practices are warranted to further integrate long-term efficacy, safety and cost-effectiveness with country-specific cost-utility analysis comparing tirzepatide with various anti-hyperglycaemic agents or independent of this, based on health technology assessments.

At present, more compounds of receptors with dual agonists are being tested, for example, GLP-1R/GR (glucagon receptor), GLP-1R/AR (amylin receptor) and GLP-1R/NPYR (peptide YY binds to neuropeptide Y receptors) [ 57 , 58 ], and might achieve further advances in T2DM, obesity and associated conditions therapy.

Unavoidably, there are several potential limitations in this meta‐analysis. First, the demographics and clinical characteristics of participants often differ (such as background glucose-lowering treatment, Concomitant medication, and intervention duration). Second, the open-label design should be considered as susceptible to subjectivity. Thrid, using self-report assessment for gastrointestinal adverse events has limitations [ 59 ]. An increased risk of nocebo effect and/or placebo effect should be considered to assess AEs [ 60 ]. Final, other residual confounding factors effected on glycaemic control, such as patients with asymptomatic gastroparesis, could not be excluded either. Based on the mentioned above, those confusions may be the main source of this study limitations.

The dual GIP/GLP-1 receptor co-agonist, tirzepatide, for diabetes therapy has opened a new era on personalized glycemia control and weight loss in a safe manner with broad and promising clinical implications. Specifically, we reviewed the multiple functions of GIP/GLP-1RAs in regulating metabolism and energy balance in the context of up-to-date findings in T2DM indicating that dual GIP/GLP-1As therapy produced profound weight loss, glycemic and BFG control, and lipid lowering. The results of this systematic review and meta-analysis indicate it is possible to achieve well established, but stringent, individualizing the glycemic and BW targets for diabesity patients in a safe manner. More clinical practices are warranted to further integrate long-term efficacy, safety and cost-effectiveness with country-specific cost-utility analysis comparing tirzepatide with various anti-hyperglycaemic agents or independent of this, based on health technology assessments.

Availability of data and materials

On request, data were extracted from original research and data used in meta-analyses are accessible.

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The present research was supported by Exploring the clinical efficacy and related mechanisms of Sancai Lianmei Granule for early remission of type 2 diabetes Based on the combination of traditional Chinese medicine and high-throughput sequencing technology (2023zd020). The design of this review was done without the involvement of any funders or sponsors.

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Qian Zhou and Xingxing Lei are contributed equally to this work.

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Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China

Qian Zhou, Xingxing Lei, Shunlian Fu, Pan Liu, Cong Long, Zinan Li & Qian Xie

Chengdu, China

Xingxing Lei

Ya’an Polytechnic College Affiliated Hospital, Ya’an, China

Yanmei Wang

Sichuan Integrative Medicine Hospital, chengdu, China

Hospital of Chengdu University of Traditional Chinese Medicine, No. 39, Shi-er-Qiao Road, Chengdu, 610072, Sichuan Province, People’s Republic of China

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QZ and XL conceptualized, conceived, wrote and evaluated the original manuscript. PL and SF define concepts and search terms, as well as data extraction methods and method evaluation. Data extraction and statistical analysis are planned by YW, NZ and CL. QZ, XQ and QC provide key information. The final written article was authorized and contributed to by all writers.

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Zhou, Q., Lei, X., Fu, S. et al. Efficacy and safety of tirzepatide, dual GLP-1/GIP receptor agonists, in the management of type 2 diabetes: a systematic review and meta-analysis of randomized controlled trials. Diabetol Metab Syndr 15 , 222 (2023). https://doi.org/10.1186/s13098-023-01198-4

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Hypertension care cascade in an urban resettlement colony and slum in Delhi, India: a cross-sectional survey

• Mongjam Meghachandra Singh 1 ,
• Saurav Basu 2 ,
• Heena Lalwani 1 ,
• Shivani Rao 1 ,
• Vansh Maheshwari 2 ,
• Sandeep Garg 3 &
• Nandini Sharma 1  

BMC Public Health volume  23 , Article number:  2116 ( 2023 ) Cite this article

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Metrics details

Hypertension care cascade in resource-limited settings is compromised with a majority of patients with hypertension remaining undiagnosed, untreated, non-adherent, and poorly controlled at every stage. However, there is paucity of information on care and management of hypertensive patients in community-based settings of low-income urban neighbourhoods in India.

This was a community-based cross-sectional study conducted in an urban resettlement colony and slum area in the Northeast District of Delhi. The adult population was screened for hypertension using standardized methods, and adherence to medications was assessed using the Morisky Green Levine scale. Binary logistic regression analysis was conducted to ascertain the sociodemographic predictors of the outcome (presence of hypertension, adherence to antihypertensive medication, blood pressure control). A p-value < 0.05 was considered statistically significant.

We included 8850 adult participants including 5295 females and 3555 males in this study. Nearly 29% of the participants were hypertensive, of which 61.77% were newly diagnosed cases. Furthermore, nearly 81% of the previously diagnosed cases had been initiated on antihypertensive medication, of which 57.54% were adherent to their medications while 36.12% attained controlled blood pressure levels. The odds of having hypertension were significantly higher among males (AOR = 1.87, 95% CI: 1.63 to 2.15), age ≥ 60 years (AOR = 9.15, 95% CI: 7.82 to 10.70), high waist circumference (AOR = 2.24, 95% CI: 1.86 to 2.70) and Body Mass Index of ≥ 25.00 (AOR = 2.55, 95% CI: 2.00 to 3.26). Furthermore, on adjusted analysis, patients of hypertension having diabetes (DM) comorbidity had significantly higher odds of being adherent to anti-hypertensive medications (AOR = 1.81, 95% CI: 1.31 to 2.51) compared to those without DM comorbidity, while tobacco users had significantly lower odds of being adherent to antihypertensive medication (AOR = 0.50, 95% CI: 0.31 to 0.82).

Conclusions

Hypertension care cascade in urban slum-resettlement colony setting revealed a high burden of undiagnosed hypertension, low rates of medication adherence, and poor blood pressure control. Strengthening community screening and primary care continuum of care is necessary to improve the hypertension care cascade from early diagnosis to effective management with optimal health outcomes to reduce patient complications and increase longevity.

Peer Review reports

Hypertension (HTN) signifying elevated blood pressure is an established risk factor for cardiovascular diseases and renal dysfunction resulting in premature and preventable mortality [ 1 , 2 ]. Globally, more than one billion adults have hypertension with majority of them residing in low- and middle- income countries (LMICs) [ 3 ]. In India, evidence from a nationally representative survey indicate that at least one in four adults have hypertension [ 4 ]. Furthermore, there exists considerable regional variation in the prevalence of hypertension in India with nearly one-third of urban adults and one-fourth of rural adults having hypertension [ 5 ]. High burden of hypertension in India is attributed to the ongoing demographic transition and associated increasing aging population, and epidemiological transition related risk factors such as overweight/obesity, sedentary lifestyles, alcohol and tobacco consumption and comorbidities as some of the risk factors associated with hypertension [ 6 ].

To meet the sustainable objective goals for a one-third reduction in premature mortality from NCDs by 2030, the global NCD action plan target of a 25% relative reduction in the prevalence of high blood pressure in adults by 2025 is required [ 7 , 8 ]. Hypertension screening, diagnosis, and effective pharmacological and lifestyle management to lower blood pressure is highly cost-effective and essential for prevention of major microvascular and macrovascular complications resulting from uncontrolled hypertension but the asymptomatic condition is frequently neglected by patients and health systems in the developing world [ 1 , 2 , 9 ]. Consequently, worldwide, there is a high prevalence of deficient hypertension management practices with nearly half the patients with hypertension remaining undiagnosed and not initiated on therapy, while merely one in five achieve optimal blood pressure control [ 10 ]. Evidence from studies evaluating the hypertension care cascades in LMICs signifying the extent of retention of hypertensive patients from the stages of screening, diagnosis, initiation of treatment, and attainment of blood pressure control indicate major losses at all stages representing an ongoing public health challenge [ 11 , 12 , 13 ]. Within LMICs, the pooled estimate of medication non-adherence to hypertension treatment was estimated as 47.34% after pooling data from 42 studies [ 14 ].

Within India, evidence from the fifth series of the National Family Health Survey (NFHS-5, 2019-21), a nationally representative survey in the 15–49 age-group, concluded that only 4 in 10 patients diagnosed with hypertension in India were initiated on anti-hypertensive treatment, while only 3 in 4 on treatment attained optimal blood pressure control [ 15 ]. In the first Indian national NCD survey (2018–19), the prevalence of hypertension in the 18–49 age-group was 28.5% of whom only 14.5% were receiving treatment, and just 12.6% had controlled blood pressure levels [ 16 ]. Among the elderly in India, evidence from the Longitudinal Study of Ageing observed that only one in two patients were initiated on treatment while blood pressure control was achieved in only one in four patients with hypertension [ 17 ]. As per a systematic review of evidence, only 22.5% of patients with hypertension in India have their blood pressure control [ 18 ]. A key driver for poorly controlled hypertension in LMICs including India is either non-initiation, delayed initiation, and among the initiated, non-adherence to antihypertensive medication due to multiple patient, provider, and health system factors [ 19 , 20 ]. Consequently, it is estimated that improved hypertension control can prevent nearly 5,00,000 premature deaths annually in India [ 21 ].

Slums are areas of substandard housing and squalor which as per the WHO usually lacks basic amenities such as improved water and sanitation, with insufficiency of living area, non-durable housing, and no secure tenure, with nearly 130 million people in South Asia, including 49% of the total urban population in India living in slums due to unplanned urbanization and large scale rural to urban migration [ 22 , 23 , 24 ]. Urban resettlement colonies were created in mega-cities like Delhi to house people who were evicted during removal of slums, and are mostly overcrowded, lack adequate sanitation and hygiene [ 25 ]. It is estimated that Delhi includes nearly 34% people living in urban slums and 12% people living in resettlement colonies [ 26 ]. People living in urban slums and disadvantaged neighbourhoods experience multiple adverse determinants of health and risk factors for the development of hypertension high levels of stress, poor nutrition secondary to poverty translating to high salt diets with very low consumption of fresh fruit and vegetables [ 27 ]. Studies in slum settings worldwide have reported disproportionately high prevalence of hypertension compared to the general population [ 28 , 29 , 30 , 31 , 32 , 33 ]. A study from Kolkata in India reported 42% prevalence of hypertension in an urban slum setting [ 30 ]. Furthermore, difficulties in accessibility, affordability, and availability of healthcare services in vulnerable slum populations may delay the screening and diagnosis of hypertension and maintaining adherence to treatment which accentuate the risk of uncontrolled hypertension and resultant complications [ 28 , 29 , 30 ].

In India, extensive screening of hypertension among adults through opportunistic screening in health facilities and community-based screening through frontline workers has been recommended by the National Programme for Prevention & Control of Non-Communicable Diseases (NPNCD) [ 31 ]. Although evidence from national surveys indicates deficient hypertension care and control cascade in India, there is paucity of disaggregated data from populations living in urban slums and resettlement colonies. Moreover, these studies do not collect information on antihypertensive medication adherence and their predictors [ 13 , 15 ].

The objective of this study was to assess the hypertension care cascade and their predictors in populations living in urban slums and resettlement colonies in Delhi i.e., proportion of population with hypertension, proportion of hypertension patients initiated on antihypertensive treatment, proportion of hypertensive patients initiated on treatment that were adherent to treatment, and the proportion of patients on treatment that had controlled blood pressure levels.

Design and Setting: This was a community-based cross-sectional study conducted in an urban resettlement colony and slum area in the Northeast District of Delhi having an estimated ~ 54,614 total population, a site purposively selected, as it represents the field practice area of a government medical college. The study area included Gokalpuri urban resettlement colony (~ 16,878), Sanjay Colony urban slum (~ 4467), Gokalpuri village (~ 8608), and the adjoining Ganga Vihar urban resettlement colony (~ 24,661). A Demographic Developmental and Environmental Surveillance Site (DDESS) was recently established in in the area inclusive of complete Geographic Information System (GIS) based mapping of the sociodemographic correlates of the study population. The household level response rate of the current survey was ~ 97% due to high levels of pre-existing community engagement [ 32 ].

Study Population: This study included all individuals aged ≥ 18 years who were residents of the area for at least 6 months irrespective of their medical history. Data were collected for a period of 2 months from March-April 2023.

Primary Outcome of the study was the detection of Hypertension (including both newly diagnosed or previously diagnosed cases). Hypertension was defined on screening as either a systolic blood pressure (SBP) ≥ 140 mm Hg or diastolic blood pressure (DBP) ≥ 90 mm Hg, or any individual who self-reported themselves as previously diagnosed patients of hypertension.

Secondary outcomes were the proportion of hypertensive patients initiated on treatment, proportion of patients initiated on antihypertensive medications that were adherent to their prescribed treatment, and the proportion who had controlled blood pressure values.

Operational definitions: Those participants who self-reported having hypertension diagnosed by any healthcare provider or currently taking any antihypertensive medication were recorded as ‘previously diagnosed hypertensive’. Newly diagnosed hypertensives were those detected with either SBP ≥ 140 or DBP ≥ 90 upon screening without past history or diagnosis of hypertension. Controlled blood pressure was considered as previously diagnosed hypertensive patients with SBP and DBP less than 140 and 90 mm of Hg, respectively [ 33 ].

Adherence to antihypertensive medications was assessed using the previously validated four-item Morisky Green Levine (MGL) adherence scale [ 34 ]. The MGL scale comprises four questions (pertaining to forgetfulness or carelessness, cessation of prescribed medications when feeling better or worse) where each item has a yes or no response. In our study, we dichotomized the full score on the MGL scale into two groups; those who scored 4 on the MGL scale were considered as adherent and those with scores of < 4 was considered as non-adherent.

Sample Size and Sampling Strategy: The sample size was adequate at 95% confidence levels, 3% absolute precision, design effect of 3.5 considering the heterogeneity in the slum and expecting 50% expected prevalence of adherence to antihypertensive medication [ 20 ]. The entire study area was divided into 16 sectors (clusters). The village and urban slum clusters were selected purposively to ensure survey representativeness, we did purposive (mandatory) selection of participants from the slum and village clusters due to expected heterogeneity in living standards and health behaviours between the slum, village, and resettlement colony population. Three additional clusters from the urban resettlement colony were selected through simple random sampling. House-to-house sampling in the households within the selected clusters was conducted and all eligible and available participants in every open household were recruited in the study. Households that were locked were visited for a second time after approximately a week and nearly 50 houses that were locked even on second visit were excluded.

Methodology: Face to face interviews with respondents in the households were conducted with the participants by a total of ten trained field investigators in the local language, Hindi, using a pretested structured questionnaire. Electronic data collection using EpiCollect android application was conducted which has features of both online and offline data collection and data validation with facility for real-time monitoring [ 35 ]. Weight of the participants was measured with digital weighing scales with least count 0.1 kg, while waist circumference and height were measured using a measuring tape with least count of 1 cm. All the investigators were trained to measure weight, height, and blood pressure in the field settings using standard guidelines to reduce chances of measurement errors.

Supervision of the field investigators and quality assurance with random verification in 5% of the households was conducted by the field supervisor and the project coordinator while data quality was maintained through regular assessment and feedback provided by the project data manager.

Blood pressure (BP) measurement: The BP in all participants was measured as per standard guidelines [ 36 ] by the trained field investigators using an Omron Blood Pressure monitor (OMRON, Kyoto, Japan). Three blood pressure measurements with five-minute intervals between readings at rest were recorded, and the average of the second and third readings was considered as the estimated blood pressure.

Independent variables

The following independent variables were considered in the analysis based on association with the study outcomes observed in previous studies [ 1 , 13 , 14 , 15 , 16 , 29 ].

Age of the participants was stratified into young (18–39), middle (40–59), and older adults (≥ 60 years), gender (male/female): education (stratified into illiterate; those who had studied up to primary school; those who had studied up to secondary school, and those who had studied beyond high school). The income level of the respondents was categorized as those with a monthly household income of median and below (< Rs 46,089) and above median (> Rs 46,095) value of the study sample.

Those who reported currently using tobacco in any form (either smoking or smokeless) were categorized as tobacco users.

Alcohol intake was measured using a single close ended item “Do you consume Alcohol” with options, “Never consume”, “Consume daily”, and “Consume occasionally”. The participants reporting consumption of alcohol either daily or occasionally were classified as “Yes”, or else as “No”.

Participants with absence of regular exercise (at least brisk walking for at least 5 days and 30 min per day) or in occupations not involving vigorously intensive activities were considered as having sedentary lifestyle, while those involved in regular exercise or involved in occupations involving vigorously intensive activities were considered as not having a sedentary lifestyle.

Family history of Hypertension was categorized as Yes (if one or both parents were previously diagnosed as having hypertension) and No (if none of the parents of the participant had been diagnosed as having hypertension).

Body mass index (BMI) was categorized using the Pan Asian classification: underweight (BMI < 18.5), normal (BMI: 18.5–22.9), overweight (BMI: 23.0–24.9), and obese (BMI ≥ 25.0) [ 37 ].

Waist circumference was measured for each participant and categorized as Low (< 80 cm for females and < 94 cm for males), Moderate (80-87.9 cm for females and 94-101.9 cm for males) and High (≥ 88 cm for females and ≥ 102 cm for males) [ 38 ].

Data and statistical analysis

The dataset was cleaned using MS-Excel 365. Descriptive statistics were performed to show the distribution of variables and provide summary statistics. Bivariate analysis was conducted by testing for association of the outcomes (hypertension present, hypertension control, adherence to antihypertensive medication) with the independent variables using chi-square for categorical and independent samples t-test for continuous variables. Furthermore, a binary logistic regression was performed to ascertain independent association with outcome variables. The variables which on test for association had a P-value of < 0.20 in the bivariate analysis were entered into the multivariable analysis. Since education levels have been found to be associated with hypertension in most previous studies, it was included into multivariate model despite having a P-value > 0.20 in the unadjusted analysis. Both unadjusted odds ratio and adjusted odds ratio (AOR) with 95% CI were reported. For the final model, 5% was considered as the statistical significance level. Additionally, a multivariable linear regression was performed to check for associations of sociodemographic and lifestyle variables with systolic and diastolic blood pressure readings of the participants, wherein unadjusted and adjusted B-coefficients with 95% CI were reported. Model assumptions for both regression analysis such as multicollinearity, outliers and goodness of fit of each model was checked. All analysis were performed using Stata (Version 15.0, StataCorp, TX, USA).

The study was approved by the Institutional Ethics Committee. All participants provided written and informed consent. Patients detected with Hypertension on screening with either suboptimal medication adherence or lack of initiation on treatment were briefly counselled on health risks of uncontrolled hypertension, and referred to their nearby local government health facilities for further evaluation and management.

The present study screened 8850 adult participants for hypertension including 5295 females and 3555 males. The household response rate of the survey was ~ 97%. Table  1 reports the distribution of the sociodemographic, lifestyle, and clinical characteristics of the participants. A majority of the participants were females (59.83%), aged 18–39 years (58.96%), and educated above secondary level (61.17%). A total of 563 (6.36%, 95% CI: 5.87 to 6.89) participants were previously diagnosed for diabetes mellitus (DM).

The prevalence of hypertension in the sample was 28.64% (n = 2535, 95% CI: 27.71 to 29.60) including 969 (10.95%) previously diagnosed and 1566 (17.69%) newly diagnosed cases (Fig.  1 ). More than two-third (68.11%) of the previously diagnosed cases were females and above 40 years of age (88.34%). A majority of the newly diagnosed cases were males (53.38%), and middle and elderly (57.85%) aged participants, and those having secondary education and above (60.22%) (Table  2 ). Model 1 reports the factors associated with new cases of hypertension (n = 1566) detected during screening in those without a prior diagnosis of hypertension. Male gender (AOR = 2.25, 95% CI: 1.93 to 2.63) and older age (AOR = 4.06, 95% CI: 3.36 to 4.92) were factors with statistically significant association with undiagnosed hypertension. Lifestyle characteristics such as high waist circumference (AOR = 1.90, 95% CI: 1.54 to 2.35), overweight/obesity (AOR = 2.72, 95% CI: 2.06 to 3.58) and alcohol consumption (AOR = 1.29, 95% CI: 1.05 to 1.57) were also positively associated with the cases of hypertension diagnosed on screening. Model 2 reports the factors associated with total cases of hypertension. On adjusted analysis, the odds of having hypertension were significantly higher among males (AOR = 1.87, 95% CI: 1.63 to 2.15) compared to females, and those aged ≥ 60 years (AOR = 9.15, 95% CI: 7.82 to 10.70) compared to those aged 18–39 years. Moreover, high waist circumference (AOR = 2.24, 95% CI: 1.86 to 2.70) and BMI of ≥ 25.0 (AOR = 2.55, 95% CI: 2.00 to 3.26) was associated with significantly higher odds of having hypertension. The odds of hypertension were also 1.3 times higher among alcohol consumers (AOR = 1.26, 95% CI: 1.04 to 1.51) compared to those reporting not consuming alcohol.

Hypertension care cascade in an urban slum-resettlement colony in Delhi, India

Among the previously diagnosed cases of hypertension (n = 969), 180 (18.58%, 95% CI: 16.25 to 21.15) patients were not on treatment i.e., not taking any antihypertensive medication to lower blood pressure, while among those taking antihypertensive medications (n = 789), only 454 (57.54%, 95% CI: 54.05 to 60.96) were adherent to their prescribed blood pressure lowering drugs. On adjusted analysis, patients of hypertension having DM comorbidity had significantly higher odds of being adherent to anti-hypertensive medications (AOR = 1.81, 95% CI: 1.31 to 2.51) compared to those without DM comorbidity, while tobacco users had significantly lower odds of being adherent to antihypertensive medication (AOR = 0.50, 95% CI: 0.31 to 0.82) (Table  3 ).

Among previously diagnosed hypertensive patients taking antihypertensive medications (n = 789), only 285 (36.12%, 95% CI: 32.83, 39.54) patients achieved controlled blood pressure levels. On adjusted analysis, patients with higher BMI (AOR: 0.13, 95% CI: 0.05 to 0.34) had significantly lower odds of achieving blood pressure control. Furthermore, patients initiated and adhering to antihypertensive medications had nearly 1.5 times higher odds of attaining controlled blood pressure levels (AOR = 1.48, 95% CI: 1.08 to 2.02). Overall, 362 (37.36%, 95% CI: 34.36, 40.46) participants had controlled blood pressure among the previously diagnosed HTN cases (N = 969) (Table  4 ).

A linear regression was performed, adjusting the systolic and diastolic blood pressure values with sociodemographic and lifestyle variables (Table  5 ). Among the participants, males (adjusted B = 8.14, 95% CI: 7.25, 9.03), those aged 60 and above (adjusted B = 17.73, 95% CI: 16.56, 18.90), high waist circumference (adjusted B = 6.27, 95% CI: 5.00, 7.55), BMI ≥ 25.0 (adjusted B = 10.88, 95% CI: 9.44, 12.31), alcohol consumers (adjusted B = 2.41, 95% CI: 1.07, 3.75) and those with DM comorbidity (adjusted B = 3.02, 95% CI: 1.52, 4.52) had a significantly higher systolic BP as compared to their respective counterparts. Similarly, males (adjusted B = 5.00, 95% CI: 4.38, 5.61), those aged 60 and above (adjusted B = 4.86, 95% CI: 4.05, 5.67), high waist circumference (adjusted B = 3.91, 95% CI: 3.04, 4.79), BMI ≥ 25.0 (adjusted B = 9.09, 95% CI: 8.10, 10.08), tobacco users (adjusted B = 1.41, 95% CI: 0.54, 2.28), alcohol consumers (adjusted B = 2.30, 95% CI: 1.38, 3.23) and those with a family history of HTN (adjusted B = 1.72, 95% CI: 1.00, 2.44) had a significantly higher diastolic BP as compared to their respective counterparts.

The present study investigated the prevalence and risk factors of hypertension among adults aged 18 years and over in an urban slum area of Delhi, India. The hypertension care cascade in the present study indicates that nearly 29% of the participants were hypertensive of which 61.77% were newly diagnosed cases, 81.4% of previously diagnosed cases were initiated on antihypertensive medication of which 57.54% were adherent to their medications, while 36.12% attained controlled blood pressure levels. The prevalence of hypertension in this study (~ 29%) is higher than the burden observed in a study conducted in an urban slum of Mumbai (23.6%) [ 39 ] and also the India country level prevalence among young and middle-aged population (NFHS-5) (22.8%) [ 15 ]. However, the overall prevalence is much lower compared to the burden among older adult and elderly population estimates from nationally representative survey data from India (LASI) (36%) [ 17 ]. The burden of hypertension in the present study was also nearly similar to that observed in populated aged ≥ 35 years from urban slum areas in Bangladesh (28.3%) [ 29 ], higher compared to urban slums in Brazil (12.3%) [ 28 ] but lower than urban slums in Kolkata (42%) [ 30 ]. Our study found the prevalence of hypertension to be higher in males (32.21%) than females (26.25%). These proportions are higher than the national estimates in the general populated aged 15–49 years as per NFHS 5 (2019–2021) (males, 24% and females, 21%) [ 40 ].

Advancing age and alcohol consumption were found to be positively associated with the odds of having hypertension, a finding corroborated from previous evidence [ 5 ]. The prevalence of hypertension for the adults aged 45 years and older was found to be 48.51% in our sample, higher than that found from LASI Wave 1 (2017–2018) (45.9%) [ 41 ]. Furthermore, high waist circumference was also identified as a significant predictor of hypertension corroborating the evidence from previous studies [ 42 , 43 ]. However, diabetes status was not an independent predictor of hypertension in this study compared to observations from LASI probably because of the older population sample with greater risk factors in the latter [ 17 ].

Nearly one in five participants had undiagnosed hypertension in the present study, a finding which indicates the need for intensification of screening, both opportunistic and community-based in resource limited settings. Furthermore, male gender and increasing age were associated with undiagnosed hypertension in this study, findings consistent with a single site study conducted in Puducherry, a town in Southern India [ 44 ]. Moreover, in the present study, a high burden of undetected hypertension was independently associated with behavioural/physiological risk factors (moderate-high waist circumference, increasing BMI and alcohol consumption) suggesting an early social transition of cardiovascular disease in the urban poor and the need for integrating and prioritizing lifestyle interventions within primary and secondary prevention strategies for hypertension care and control in India.

In this study we observed nearly one in five previously diagnosed hypertensive cases were not initiated or not taking any anti-hypertensive medications signifying major deficiencies in the continuum of care as these patients possibly did not report back to their health system, a finding also observed in a study in slums in Bangladesh [ 29 ]. Furthermore, a majority of the patients on treatment reported medication nonadherence, a factor which was independently associated with poorly controlled blood pressure levels. Adverse social determinants of health prevalent in urban slum dwellers including poor-socioeconomic status, illiteracy, unemployment, lack of awareness, and out of pocket medication expenses are possible reasons for non-adherence [ 45 , 46 ].

Current tobacco users in previously diagnosed hypertension cases in this study was 113 (11.66%), a finding lower than that observed in cross-sectional studies from slums in Bangladesh (27.33%) [ 29 ], Kolkata (44.35%) [ 30 ], Kenya (32.3%) [ 47 ] and Egypt (43.65%) [ 48 ]. Among those who smoked tobacco, 41.6% women and 35.51% men were hypertensive in our study, comparatively higher than the findings from NFHS-4 (2015–2016), where 15.3% women and 22.4% men who smoked tobacco were found hypertensive [ 49 ]. Promoting healthcare readiness to provide regular tobacco cessation services in the same health facility to patients where they are undergoing hypertension management is crucial since tobacco users apart from increased risk of cancers also contribute independently to an elevated risk of cardiovascular disease, similar to hypertension, and both may synergistically interact to accentuate this potential risk in the patients. The overall control of hypertension was suboptimal even among those reporting taking antihypertensive treatment (36.1%) suggestive of the presence of clinical inertia or failure of intensification of therapy by physicians despite persistently poorly controlled blood pressure levels. This proportion of patients with controlled blood pressure is lower than that reported in studies from Chennai (45.9%) [ 50 ], while greater than Kerala (32.1%) [ 51 ] and Kolkata (26%) [ 30 ] but indicative of a nationally prevalent problem. Another study conducted in urban slums of Kolkata among patients with hypertension reported that patients adherent to antihypertensive medications were 1.71 times more likely to achieve adequate blood pressure control compared to non-adherent patients, a finding similar to the present study [ 52 ].

The study has several strengths including a large sample size ensuring validity of the data, while representativeness was high when considering the problem in urban slum settings. Furthermore, all components of a disease care cascade including medication adherence, an information which is not usually collected in nationally representative secondary surveys were incorporated in this study. However, there are certain limitations to this study. Firstly, the findings of the present study should not be generalized to people living in improved non-slum conditions although we were able to compare the hypertension burden and care cascade outcomes in the present study with estimates derived from multiple large nationally representative datasets. Second, being cross-sectional in nature, the study could not establish causality due to lack of temporal evidence between hypertension and its determinants. Third, some selection bias is possible as those adults who were not available in the household during the survey period were omitted. Similarly. Recall bias could have contributed to overestimation of previously diagnosed cases of hypertension, while social desirability bias may have contributed to inflated measures of antihypertensive medication adherence. Fourth, we did not ascertain adherence to prescribed healthy diet such as salt restriction and consumption of fresh fruits and vegetables in the participants which can influence blood pressure control [ 53 ]. Fourth, as samples were selected through clusters, the possibility of clustering of risk factors in the regression analysis despite checking for multicollinearity cannot be completely ruled out. Fifth, our blood pressure measurements could have some variation due to the white coat effect that may cause a slight elevation in the readings although this phenomenon is unavoidable in large epidemiological surveys [ 54 ].

Our study has some important implications for enhancing the hypertension care and control cascade in slum settings in India and similar low-resource settings in LMICs. First, despite the mandate for annual community-based population screening for hypertension by frontline health workers (FHWs), a large proportion of existing patients with hypertension in slum residing communities remain undiagnosed signifying gaps and inefficient screening [ 31 ]. Refresher training and sensitization of FHWs is crucial since our findings indicate that conducting rapid community surveys for screening hypertension is feasible in such settings. Second, information, education, communication (IEC) campaigns to increase public demand for getting screened for hypertension and adopting healthy lifestyles as preventative strategies warrants high prioritization. Finally, ensuring adherence support for existing patients on antihypertensive medication from nursing and pharmacy staff at primary health facilities, and sensitization and training of doctors to avoid clinical inertia in patients with uncontrolled hypertension and ensure adequacy of drug treatment is an ethical imperative for medical practitioners in slum associated low-resource settings.

In conclusion, hypertension care cascade in urban slum-resettlement colony setting revealed a high burden of undiagnosed hypertension, low rates of medication adherence, and poor blood pressure control. Strengthening community screening and primary care continuum of care is necessary to improve the hypertension care cascade from early diagnosis to effective management with optimal health outcomes to reduce patient complications and increase longevity. Future research should ascertain the individual, community, and health-system factors responsible for missed or delayed screening, diagnosis, and initiation of antihypertensive treatment in urban slum areas.

Data Availability

The dataset used and analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

We thank all the participants for their valuable collaboration.

This research was supported by National Biopharma Mission, Biotechnology Industry Research Assistance Council (BIRAC), Department of Biotechnology, Government of India.

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Mongjam Meghachandra Singh, Heena Lalwani, Shivani Rao & Nandini Sharma

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MMS, NS and HL conceptualized the study; MMS, HL, SR, SG and NS developed the protocol; HL and SR were involved in the data management; SB wrote the first draft of the manuscript; VM and SB conducted the data analysis and interpretation of the data. All authors contributed to critical revision of the manuscript for intellectual content. All authors read and approved the final manuscript. MMS and NS are the guarantors of the paper.

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Singh, M.M., Basu, S., Lalwani, H. et al. Hypertension care cascade in an urban resettlement colony and slum in Delhi, India: a cross-sectional survey. BMC Public Health 23 , 2116 (2023). https://doi.org/10.1186/s12889-023-17021-8

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The economic burden of diabetes in India: a review of the literature

Charles ak yesudian.

School of Health Systems Studies, Tata Institute of Social Sciences, Mumbai, India

Mari Grepstad

LSE Health, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE UK

Erica Visintin

Alessandra ferrario.

Social Policy Department, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE UK

Diabetes and its complications are a major cause of morbidity and mortality in India, and the prevalence of type 2 diabetes is on the rise. This calls for an assessment of the economic burden of the disease.

To conduct a critical review of the literature on cost of illness studies of diabetes and its complications in India.

A comprehensive literature review addressing the study objective was conducted. An extraction table and a scoring system to assess the quality of the studies reviewed were developed.

A total of nineteen articles from different regions of India met the study inclusion criteria. The third party payer perspective was the most common study design (17 articles) while fewer articles (n =2) reported on costs from a health system or societal perspective. All the articles included direct costs and only a few (n =4) provided estimates for indirect costs based on income loss for patients and carers. Drug costs proved to be a significant cost component in several studies (n =12). While middle and high-income groups had higher expenditure in absolute terms, costs constituted a higher proportion of income for the poor. The economic burden was highest among urban groups. The overall quality of the studies is low due to a number of methodological weaknesses. The most frequent epidemiological approach employed was the prevalence-based one (n =18) while costs were mainly estimated using a bottom up approach (n =15).

The body of literature on the costs of diabetes and its complications in India provides a fragmented picture that has mostly concentrated on the direct costs borne by individuals rather than the healthcare system. There is a need to develop a robust methodology to perform methodologically rigorous and transparent cost of illness studies to inform policy decisions.

Diabetes is one of the leading causes of morbidity and mortality worldwide [ 1 - 3 ] and a major problem in India. In 2012, 60% of all deaths in India were due to non-communicable diseases (NCDs), including cardiovascular diseases (26%), chronic respiratory diseases (13%), cancer (7%), diabetes (2%) and other NCDs (12%) [ 4 , 5 ]. Currently accounting for 43% of total disability adjusted life years (DALYs), the prevalence of NCDs is expected to increase in the coming years due to ongoing large-scale urbanisation and increasing life expectancy [ 3 ].

The prevalence of diabetes in 2013 in India is only slightly higher than the world average (9.1% vs. 8.3% worldwide) [ 3 ]. However, due to its very large population, India has the world’s largest population living with diabetes after China. In 2013, there were 65.1 million people between 20 and 79 years of age with diabetes and this number was predicted to rise to 109 million by 2035. The growing epidemic of type 2 diabetes in India has been highlighted in several studies [ 6 - 9 ].

Studies have shown large regional and socioeconomic differences in the prevalence of type 2 diabetes in India. Self-reported prevalence is lower in rural areas than in urban areas ranging from 3.1% in rural areas to 7.3% in urban areas [ 10 ]. The disease appears to be more prevalent in the south of the country as compared to the northern and eastern parts [ 11 ]. However, the absence of large well-planned national studies on diabetes prevalence have led to incomplete and unreliable nationwide data on the prevalence of diabetes in India [ 6 ].

Financing and delivery of health care in India has been left largely to the private sector [ 12 ]. In 2012, public health care funding was lower in India than other countries in the region, with a general government funding for health accounting for 33% of total health expenditure in India compared to an average of 52% in the South East Asia region [ 13 ]. Nevertheless, at 4% of India’s gross domestic product (GDP) the share of health expenditure is equivalent to the average of the South East Asia region [ 14 ].

At the 56 th World Health Assembly in Geneva in 2012, universal health coverage was identified as essential to consolidate public health advances [ 15 ]. While various health programmes and policies have previously attempted to achieve universal health coverage in India, there is still a long way to go. In 2010, only about 19 percent of the population (240 million people) was covered by the country’s central and state government-sponsored health insurance [ 16 ]. When including private insurance and other schemes, some 25 percent of the population (300 million people) was covered [ 16 ]. Thus, the financial burden of health care falls heavily on individuals with the government contributing to one third of total health spending and out-of-pocket payments representing about 58% of total health spend in 2012 [ 13 ].

The assessment of the economic and social impact of diabetes in India is important for several reasons. First, India is considered the diabetes capital of the world [ 17 ], yet not enough is done to tackle the disease. An article published in 2007 suggests that an estimated USD 2.2 billion would be needed to sufficiently treat all cases of type 2 diabetes in India [ 18 ]. In comparison, health spending per capita in 2012 was USD 61 [ 19 ]. Second, by 2025, most people with diabetes in developing countries will be in the 45 to 64 year age group, thus threatening the economic productivity of the country and the income-earning ability of individuals [ 20 ]. Third, the management of diabetes and its complications can be expensive, which poses serious obstacles to the strengthening of the Indian health care system and the Government’s plan to achieve universal health coverage by 2022.

As the burden of diabetes on total health care spending is likely to increase and, potentially, will have important consequences on the sustainability of health care financing, this study presents a critical review of the literature on cost of illness of diabetes and its complications in India and also makes recommendations on areas requiring further attention and research.

A comprehensive literature review of the direct and indirect costs of diabetes in India was conducted in October 2014 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [ 21 ] guidelines.

Search strategy

Searches were performed for all papers published up to 18 October 2014 in relevant databases (PubMed, Web of Science and Scopus). Reference lists in the articles included in the review were searched to identify further eligible articles.

Search terms

Search terms and their combinations are presented in Table  1 . Databases were searched using the primary term “India” in combination with one term associated with diabetes and complications from diabetes (column 2, Table  1 ) and one term associated with costs (column 3, Table  1 ).

Inclusion criteria

Papers were included if they provided original research findings on the cost (direct and indirect) of diabetes and its complications in India, were written in English and met the inclusion criteria following the PICOS approach, adapted to meet the needs of the review [ 22 ]. We did not include cost-benefit, cost-effectiveness, cost-minimisation and cost-utility analyses. The population considered consisted of people diagnosed with type 1 or 2; the contexts of interest were hospitals, clinics, and home settings in India, outcomes comprised direct and indirect costs for health systems, households and individuals; and, the relevant study designs were randomised controlled trials (RCTs), cohort and observational studies and surveys.

Critical review of the data and quality of the studies

The review included articles reporting on the economic burden of diabetes using both quantitative and qualitative methods to elicit information on costs. In conducting our analysis, we have developed two extraction tables in two different Excel spreadsheets [ 23 ] in which the data was summarised. In the first one, we used predefined categories such as the year published, the research objectives, the methods and the sample characteristics for each article. Relevant findings were classified using a framework developed to guide the analysis of retrieved cost data (Table  2 ). Historical conversion rates from www.xe.com/currencytables/ were applied to report on cost estimates in both INR and USD throughout the article.

Classification of costs and economic impact on individuals and society

In the second spreadsheet we listed a number of technical criteria for a sound cost of illness study (COI). The quality indicators were selected based on criteria proposed by previous reviews and good practice guidelines [ 24 - 27 ] and adjusted in accordance with specific features of diabetes. Following data extraction, a score of either 0, 0.5 or 1 was assigned for each quality indicator. This led to a maximum obtainable score of 17.

An indicator was assigned the score of 1 if the quality and the appropriateness of the parameter were high, a score of 0.5 was assigned in the case quality parameter was only partially met and a score of 0 was assigned if there was no information on the particular parameter (unless a logical reason justifying the lack of this information was provided).

All the details of the parameters employed are presented in Table  3 .

Quality indicators for cost of illness studies

A total of nineteen studies met the inclusion criteria. The flow of information through the different phases of the review is depicted in Figure  1 .

Flow chart of the study selection process.

A summary of the main features of the studies included is presented in Table  4 . Eighteen studies were observational studies of which twelve were cross-sectional, four were cohort longitudinal and two were case control studies. Only one study was a RCT.

Study characteristics of included articles

CC = Case Control Study CS = Cross Sectional Study, COH = cohort study, RCT = randomised controlled trial.

*The study does not clearly state whether it refers to diabetes type 1, type 2 or both. We assume type 2 diabetes as the articles references refer to type 2 diabetes studies.

**The information is not provided in the study.

***Year of data collection could not be identified. Year of publication utilised as proxy.

Sixty-three percent of the studies dealt with the general costs of diabetes while 21% focused only on diabetes complications, including diabetic foot wound (DFW) and chronic kidney disease, and 16% of the studies analysed the cost of a specific drug for the treatment of diabetes (Figure  2 ).

Study objective.

The study samples varied from 50 to 5,516 individuals, and from local, regional, cross-regional to national studies. A summary of the studies reviewed is presented in Table  5 .

Main cost data of reviewed studies

Notes: USD current refers to the value reported in the study, USD 2014 it the value adjusted to 2014 price levels using http://www.bls.gov/data/inflation_calculator.htm .

CKD: Chronic kidney disease; INR: Indian rupee.

*Year of data collection could not be identified. Year of publication utilised as proxy.

1 DDD: defined daily dose.

2 Total costs per year are averaged between male and female.

3 Values for patients with complications are average of 5 groups: renal, cardiovascular, foot, retinal, two complications.

4 Values are average of treatment arms: human insulin and blood, glucose monitoring, bovine insulin and blood glucose monitoring, bovine insulin and urine glucose monitoring.

5 Values are average of urban and rural population.

6 Values are average of outpatients and hospital patients with foot problems.

With regards to the type of diabetes analysed, most studies (n =11) considered the cost of diabetes mellitus type 2, six studies considered the costs of both, only one study focused on the cost of diabetes mellitus type 1 and one study did not clearly define the type of diabetes considered (Figure  3 ).

Type of diabetes considered.

Different types and perspectives of costs

Overall, the majority of the studies included only direct costs in their evaluation (n =14), 4 studies included direct and indirect costs and only one study included direct, indirect and intangible costs (Figure  4 ).

Costs included.

Most studies (17 studies) report on the costs to the individual, while only two studies report on costs for the health system.

Health system perspective

Both studies using a health system perspective reported costs for consultations and medicines [ 31 , 38 ] and drug costs [ 31 , 38 ]. Studies reported that the costs to hospitals and other health providers constituted only a small part of total diabetes costs. In the study on ambulatory diabetes care in northern India, the authors found that the mean cost borne by the hospital over a six-month period was 2.83% of the total direct costs. No study reflected on indirect costs from a societal perspective, although one study provided annual societal indirect costs at INR 15,376.30 (USD 393.25) [ 38 ].

Direct costs

Direct costs were investigated in all the reviewed studies. Detailed costing data for these studies are provided in Table  6 . The most common cost item reported on was drug costs (12 studies), followed by hospital related costs (11 studies), consultation costs (11 studies), laboratory costs (10 studies) and transport costs. Less common cost items were surgery costs (3 studies), monitoring costs (2 studies) and food costs (2 studies). In six studies providing estimates for cost components as well as total costs, drug costs accounted for more than half of the total direct costs [ 31 , 34 , 36 , 40 , 41 , 43 , 47 ]. A study from Delhi reported that the average annual direct cost of type 2 diabetes was INR 6,212.4 (USD 143.14) in 2005, of which more than half were drug costs (INR 3,324; USD 76.59) [ 34 ]. Similarly, a study from northern India on diabetes type 1 and 2 reported a total direct cost of INR 4,966 (USD 114.4) over six months in 2005 a ; 62% of the total direct cost were drug costs (INR 3,076; USD 70.88) [ 31 ] Table  6 .

Costing items and estimates per person in studies reporting on direct cost of diabetes for individuals and households INR (USD current value)

1 Total number of studies addressing the costing item.

2 Values are averages between male and female.

5 Values are average of treatment groups: teleophthalmology (screening), hospital (dilated retinal examination), hospital (laser photocoagulation). We assume costs are yearly estimates.

6 Values are average of urban and rural population.

7 Values are average of outpatients and hospital patients with foot problems.

Indirect costs

Indirect costs of diabetes and its complications were reported in four studies. A study from northern India reported a total INR 2,087 (USD 48.09) indirect costs over a six-month period in 2005 a . Patient income loss accounted for 61% of the total indirect cost (INR 1,263, USD 29.10) while the remainder 39% (INR 823, USD 18.96) was due to income loss of the carer [ 31 ].

Socioeconomic burden of diabetes

Several studies investigated differences in costs as related to one or several demographic and socioeconomic parameters by looking at levels of income, education and occupational status, and by comparing costs in rural and urban populations [ 30 , 31 , 34 , 36 , 43 , 48 ]. Several studies found that lower income groups generally spent a larger proportion of their income on diabetes care, that urban populations spent more in absolute terms, and that cost of complications weighed heavily on overall costs.

Within the diabetes population, low income individuals bear the highest burden of diabetes [ 40 ]. A study on type 2 diabetes in seven states in India during the period 1998 to 2005 found spending to be higher among the urban than the rural population both in absolute terms and as a proportion of income. This was due to higher expenditure on medical consultations, laboratory tests and drugs, which the authors attributed to the use of more expensive treatments in urban areas (which have remained unavailable in rural areas). Also, in lower-income groups spending was higher in the urban than the rural population, possibly because awareness of diabetes care was better among the urban poor [ 36 ]. A Chennai-based study in 1999 compared costs for type 2 diabetes in public and private institutions and found that individuals seeking care in private hospitals were economically better off, and that families who could afford it preferred private provision over state-funded care as the public hospitals were crowded and the staff overworked [ 42 ]. A study from Bangalore with cost data from 1997 and 1998 found that uneducated, unemployed people in semi-urban or rural areas were more likely to be diagnosed later as they could not afford to consult a doctor, and therefore developed complications [ 38 ]. Treatment costs were found to be significantly higher in those who were more educated in a study from northern India [ 43 ]. Patients with less than five year of education spent INR 398.66 (USD 9.19), while those with more than five years education spent INR 2,810.20 (USD 64.77).

Complications

Sixty-nine percent of the studies included complications in their evaluation of the cost of diabetes. Only 32% of the studies [ 29 , 33 , 40 , 45 , 46 ] have specified the type of complications included while 37% of the studies only identified the presence of a number of complications (1 to 3) without specifying the type (Figure  5 ).

Complications included.

Studies considering diabetes complications indicated that they weighed heavily on the overall costs. For example, the number of complications per patient was found to be positively correlated with the patient’s healthcare expenditure [ 30 , 36 ]. However, no significant urban/rural differences were found in the prevalence of complications of diabetes [ 36 ]. Studies argued that any measure to reduce hospitalisation costs would sharply reduce the economic burden for households and society, and increase patients’ quality of life [ 30 ]. Further, that substantial cost savings could be achieved by focusing on provision of care in outpatient settings [ 40 ].

Two studies compared costs of diabetes care for patients with and without complications [ 35 , 46 ]. A study from Chennai reporting on costs from 2008 and 2009 found that total costs for patients without complications were INR 4,493 (USD 92.15) compared to INR 14,691.75 (USD 301.32) for patients with complications b [ 35 ]. Among the different types of complications investigated, foot complications incurred the highest costs; patients with foot complications spent four times more than patients with no complications. Patients with renal disease, cardiovascular and retinal complications spent three times more than those without complications. Consultation and hospitalisation costs were especially high for patients with complications (on average INR 1,085 (USD 22.25) for consultation costs and INR 5,256.4 (USD 107.80) for hospital costs compared to patients without complications INR 350 (USD 7.18) for consultation costs and INR 1,083 (USD 22.21).

Quality analysis

The analysis focused on the key elements necessary to perform a good cost of illness analysis. Most of the studies (n =11) scored less than 10 on 17 points scale. Interestingly, the remaining 8 studies reached a score slightly higher, with a maximum score of 13.5. The median score was 9.5.

Overall studies lacked an accurate and precise definition of the disease, with only 4 articles referring to WHO definition of diabetes, and only 3 studies gave a clear definition of the type of diabetes considered.

Most studies developed their research over an adequate period, usually of 6 months, while two studies did not specify the timeframe.

Although we considered discounting in the qualitative table, we have not accounted for it as a quality element for two main reasons. First, the prevalence-based studies considered a time short-term horizon and the need to apply a discount rate is the subject of an on-going debate [ 27 ]. Second, for incidence-based studies, the appropriate approach for calculating the discount is still an unsettled matter in the literature [ 49 ].

The majority of the studies (84%) considered an appropriate number of patients or household for the purpose of their study objective. The benchmark employed is based on the work of Krathwohl, which provides a number of questions to individuate if the sample is appropriate in comparison with the purpose of the study [ 50 ].

The remaining 16% of the studies consider samples that either are too small or do not state the size of the sample considered. Further, it is important to note that the majority of the studies only considered the middle and high-income portion of the Indian population due to the difficulties involved in collecting data on the low-income classes.

All studies used a questionnaire, or a survey, to collect the data based on self-assessment of illness and costs. In addition, 12 out of 19 studies validated the reliability of the self-assessment against hospital bills and clinical records retrieved directly from the hospitals or practitioners.

The second part of the quality analysis considered the appropriateness of the various types of costs that each study included. The appropriateness of cost inclusion was benchmarked against the study objectives and the minimum requirements for a sound cost of illness study according to international best practice [ 27 , 51 ]. Only 52% of the studies included the appropriate costs, both in terms of their objective and in terms of minimal requirements for a sound cost of illness analysis. In one case, it was not possible to assess the relevance and the appropriateness of the costs included due to a lack of information on data sources and categories of cost.

In terms of methods, most studies lacked sufficient details on the methods used. In particular, 42% of the studies did not specify how costs were estimated. Only 32% of the studies adopted the incremental costs method, which is the most appropriate for diabetes, and only 4 studies mentioned the use of either matched control (n =2) or regression method [ 24 ] (Figure  6 ).

Cost estimation methods.

Results indicate that the prevalence-based approach, with a bottom-up quantification of the costs, was the most common method used to conduct cost of diabetes studies in India. Notably, 16 studies employed a prevalence-based approach and measured diabetes attributable costs that occurred concurrently with prevalent cases over a specified time period, usually 6 months (Figure  6 ).

A bottom-up approach was used in 15 studies by assigning costs to individuals with diabetes based on clinical practice data.

Regarding the evaluation of uncertainty, the majority of the studies did not perform any type of analysis. In fact, only one study performed a sensitivity analysis and 3 studies conducted linear or multivariate regressions.

In addition to inconsistencies regarding the type and extent of information provided on methods, a discussion of limitations was largely absent (Figure  7 ). 50% of the studies did not mention any limitation, while 11% mentioned only one minor limitation, such as related to the size of the sample (n =2). Only 39% of the studies provided a comprehensive discussion of the limitations of the cost components, data, assumptions and research methods.

Limitations discussed.

Regarding the statistical methods employed, 14 studies performed the necessary statistical analysis for a good quality study. The majority employed the student t-test to determine the statistical significance and the Wilcoxon matched pair signed-rank test to verify the validity of the data. A number of studies employed the Chi-square test and percentage value to validate their data. A large number of studies used the statistical package SPSS to analyse the data.

Two studies state the presence of statistical analysis. However, they did not identify which statistical formulas had been used. One study even declared that it had not performed any kind of any statistical analysis at all.

11 studies presented the standard deviation along with the mean estimate while 4 studies included only the mean.

Discussion and recommendations

With the population of people living with diabetes predicted to rise above 109 million by 2035 [ 17 ], there is an urgent need to act at all levels of authority in India, and with additional coordination at the national level. Further, there are several specific areas in which policy makers could concentrate efforts to reduce the impact of the economic burden of disease.

Firstly, the economic burden falls heavily on patients and their families and requires better health care coverage. There is a need to mitigate the serious adverse effects of high out-of-pocket expenditure, including impoverishment of catastrophic spending and cost of complications. To this end, efforts, such as the expert group set up by the Planning Commission of India to achieve universal health coverage by 2022 [ 52 ] need to be considered in order to increase coverage and pool healthcare costs across the population. Policies aiming to strengthen health systems are also essential in this process.

Secondly, high costs and suboptimal access to drugs contribute significantly to the burden of the disease and should be addressed through market shaping strategies. While hospitalisation and complications are major components of the costs of diabetes, drug costs constitute an important part of the expenses, often representing more than 50% of total direct costs for households. A study based on a large dataset, found that drug costs accounted for 58% of out–of-pocket expenditure on diabetes [ 53 ]. Another study on drug costs as share of expenses paid out of pocket by quintile group revealed progressive private spending on health, with the poorest spending 75.42 percent on drugs, compared to 65.9 percent spent on drugs by the richest in 2009–10 [ 12 ]. By further comparison, studies of diabetes in Western countries shows that drug costs constitute a much lower share of total direct health expenditure on diabetes, ranging from 6.2 percent to 10.5 percent [ 54 , 55 ] in Europe and 12 percent in the United States [ 56 ]. In addition to better drug coverage for individuals, Indian authorities, together with the international community, should aim to employ market-shaping mechanisms to increase the access of medicines in India. Poor procurement procedures and weak supply chain systems are major barriers to access to medicines in India, contributing to low competition, low quality, high price and variable availability of drugs [ 12 ]. Pooled drug procurement of essential medicines between several Indian states has proven efficient for essential medicines [ 57 ], and should therefore be considered for medications for diabetes and related drugs.

Thirdly, lower expenditure among the rural and low income population may be due to issues of access and affordability rather than lower need [ 6 ], and late detection of the disease in these settings often leads to catastrophic spending for individuals and households [ 38 ]. Early detection and treatment provided in outpatient settings has been identified as an important means for cost reduction [ 30 , 40 ] and should thus be strengthened. Socioeconomic differences and the urban–rural divide suggest divergence in disease outcomes. In other words, the relatively wealthier population living in urban areas spend more on diabetes care and have better outcomes, while relatively poorer people living in rural areas tend to have more difficulties accessing diabetes care, and therefore spend less on diabetes care and tend to have worse health outcomes [ 58 ]. Mobile health units, which can increase access in remote areas, may help mitigate these socioeconomic differences.

With regards to the methodological quality of the studies considered, only a few of the studies adhered to recognised standards of methodological quality, which utilised a transparent methodology, and thus provided credible results.

The aim of COI is to identify, measure and value the resources consumed by a disease in order to determine not only the total cost, but also all the elements and methods used to design the analysis itself [ 24 ]. However, the majority of the studies failed to achieve this aim due to a lack of solid methodology.

First of all, the lack of both a clear definition and foundation in the literature, or justifications for applying new approaches, for the methods employed affect the reproducibility of the studies. Notably, the total costs were often calculated without providing a detailed list of unit costs and resource consumption was also rarely described. In addition, the majority of the studies lacked of a clear epidemiological definition of diabetes which also lead to comparability problems [ 59 ].

Secondly, the lack of a clear justification of the cost components and the data sources, together with the lack of a discussion on the intrinsic limitations of the study, produced doubts about the quality of the research. The absence of these elements could either be indicative of lack of accuracy of the study or even aimed at hiding possible gaps and/or errors in the collection of data and the calculations of costs [ 51 ].

To enhance the transparency of the cost of illness studies, it appears fundamental to provide sufficient documentation on data sources, assumptions and estimation methods [ 51 ].

In terms of costs included, there are a number of factors that could have led to possible biases in the estimation of the economic burden of diabetes in India.

One of such factor is the absence, in the majority of studies, of the cost of complication or a description of complication profile of the included patients. In particular, studies failed to include health care utilisation costs associated with chronic complications of diabetes, which are usually the most expensive [ 59 ]. Indeed, according to WHO [ 59 ] data and to a number of studies outside India [ 60 ], the treatment of patient with diabetes for other complications and comorbidities is a major source of the increasing in the health care expenditure on diabetes.

The exclusion of the estimation of the intangible costs and the loss of productivity leads to an underestimation of diabetes. Loss in productivity for the patient or carers was shown to represent up to half of the total costs of diabetes [ 30 ]. Despite difficulties in their extraction and quantification, both costs are important for a comprehensive calculation of the actual cost of the disease, which affects not only diabetes patients, but also their families and the society [ 25 , 51 ]. The inclusion of intangible costs is especially important in studies aiming to give a general analysis of the burden of this disease in the country or in a specific region.

In terms of perspective of analysis, the third party payer is the most common perspective adopted in the studies reviewed. The exclusion of the perspective of the healthcare sector and the households as well as the governments and local authorities excludes a number of key costs, such administrative costs and personnel costs.

The implementation of a comprehensive and accurate estimation of the cost of diabetes enables the use this cost as both a baseline and a reference, which can help to identify the programmes and strategies most effective in reducing costs associated with diabetes [ 50 ].

From a methodological perspective, most studies used a prevalence-based epidemiological approach and a bottom up quantification of the costs method, both of which are considered the most accurate and consistent for the calculation of the burden of diabetes [ 25 , 51 ]. Nevertheless, they also lack of other major elements for a complete COI.

The absence of an estimation of uncertainty in a large number of the studies is an important limitation. Due to the large number of uncertainties involved in a COI, it is necessary to consider alternative values for all important parameters and assumptions [ 50 , 51 ]. Therefore, it is necessary to conduct a proper sensitivity analysis [ 26 , 29 , 61 ].

Cost of illness studies are an important instrument for informing and raising awareness among policy-makers by providing economic information to support their decisions. Further, results of this type of economic evaluation are often used to justify the allocation of more resources to prevent and treat a certain illness [ 26 , 39 ]. More efforts in designing study methodologies are necessary to improve the quality of studies on the cost of diabetes in India.

Therefore, it would appear advantageous to develop and implement standardised guidelines regarding the conduct of comprehensive and accurate cost of illness studies in India. Certainly, a well designed methodology and an accurate computation and inclusion of all the costs would enhance the COI validity as a policy tool.

Limitations

This review provides a fragmented picture of the economic burden of diabetes in India. Given the heterogeneity of study designs and diversity of methods used in the literature reviewed, we were unable to generate meaningful aggregate data for meta-analysis purposes. This heterogeneity also complicated the synthesis of the papers, and comparisons should be treated with caution due to the variability in study design and thematic focus. Future studies should aim to explore optimal methodological study designs that may facilitate the production of meaningful national estimates for meta-analysis.

This study has aimed to inform the discussion on the economic burden of diabetes by reviewing the literature on diabetes costs for individuals and society. We found that most studies on the costs of diabetes and its complications in India have focused on the costs borne by patients, both direct and indirect, and less evidence exist on the economic burden for the health care system and society. Three areas of concern were identified for policy interventions. First, the heavy economic burden of diabetes borne by individuals should be reduced via the improvement of universal healthcare coverage. Second, market shaping mechanisms should be considered to improve the access to affordable medicines, which constitutes an important part of private costs. Finally, early disease detection and treatments in outpatient settings provide cost saving ways of tackling the disease.

As the epidemiological burden of diabetes increases, the economic burden on households is expected to rise and the economically disadvantaged will be the most affected. Future initiatives to tackle diabetes type 1 and 2 should be grounded in evidence-based and integrated strategies of prevention and disease management, and implemented at all levels of authority. Cost of illness analysis should be a basis on which strategies for mitigating the effects of this pervasive illness gain a higher priority on the health policy agenda.

a The authors do not provide the year of data collection and the year of article publication is used as a proxy.

b Values are averaged across the different types of complications: renal, cardiovascular, foot, retinal.

Acknowledgements

This study was funded by an unrestricted educational grant from Novo Nordisk Switzerland. The authors would like to thank Ms Marsha Fu and Danica Kwong for their editorial assistance.

Abbreviations

Competing interests

AF received travel reimbursement and speaker fees from Novo Nordisk for delivering two presentations on diabetes in EU5 at national diabetes conferences in Portugal and Spain.

Authors’ contributions

All authors contributed to the literature review and in the appraisal of the retrieved information. CAKJ wrote the first draft, MG and EV analysed the data and redrafted subsequent versions of the article with the input of AF up to its final version. All authors contributed to the critical revision of the article for important intellectual content and approved the final manuscript.

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