|
| |
 |
|
| ORIGINAL ARTICLE |
|
| Year : 2021 | Volume
: 17
| Issue : 1 | Page : 1-4 |
|
Factors associated with stroke burden in India
Manas Pratim Roy
Department of Pediatrics, Safdarjung Hospital, New Delhi, India
| Date of Submission | 21-Nov-2020 |
| Date of Acceptance | 06-Feb-2021 |
| Date of Web Publication | 18-May-2021 |
Correspondence Address:
Dr. Manas Pratim Roy
Department of Pediatrics, Safdarjung Hospital, New Delhi - 110 029
India
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/amjm.amjm_73_20
Objective: Stroke is one of the largest public health challenges in India. Several factors have been implicated for stroke. The present paper aims to explore associated factors from nationally representative data. Among different variables, smoking, alcohol, smokeless tobacco (SLT), second-hand smoking (SHS), use of clean fuel, and economic condition were considered. Methods: Data were taken from three reports – National Family Health Survey 4, Global Adult Tobacco Survey 2: India 2016–17, and India: Health of the Nation's States. The state-wise analysis was done. Spearman's correlation coefficient and multivariate linear regression were used. Results: Five states from the eastern part of India, viz., West Bengal, Odisha, Tripura, Assam, and Chhattisgarh, recorded the highest burden of stroke. The use of SLT was significantly related to stroke burden (r 0.476). Clean fuel and better economic conditions were found to reduce stroke burden (r S722;0.449 and − 0.363, respectively). SLT (B 21.029, P = 0.011) and SHS at work (B 25.905, P = 0.030) were associated with stroke burden significantly. Conclusion: States with the highest proportion of SLT need special intervention to reduce stroke burden in the country.
Keywords: Second-hand smoking, smokeless tobacco, stroke
How to cite this article:
Roy MP. Factors associated with stroke burden in India. Amrita J Med 2021;17:1-4 |
| Introduction | |  |
Globally, stroke caused 6.17 million deaths in 2017, accounting for 11% of deaths.[1],[2] India suffers 7.3% of deaths due to stroke. Considered as an important cause for disability, it is responsible for 3.5% of disability-adjusted life-years (DALY) in India.[3] As a major cardiovascular disease (CVD), it is of paramount importance. It may be of interest that half of the CVD deaths in India in 2016 were in people younger than 70 years.[4]
Risk factors such as diet, alcohol, smoking, and lack of exercise have been cited in the literature for all noncommunicable diseases (NCDs). Although regional variations are there, smoking and diabetes were pointed as risk factor for ischemic stroke while hypertension for hemorrhagic type.[5] Alcohol and less physical activity have also been implicated for stroke.[5],[6] INTERSTROKE study highlighted potentially modifiable risk factors such as blood pressure, smoking, diet, and physical activity are associated with the majority of strokes.[5] Bardach et al. pointed out the role of binge drinking on stroke.[6]
Since the prevalence of high systolic blood pressure, high total cholesterol, and high fasting plasma glucose increased across all state groups since 1990 and fruit intake is lowest in South Asia, it could be readily explained why stroke rose from 12th place in 1990 to 5th in 2016, in terms of DALY in India.[3],[4],[7] Poor access to services/ investigations/ treatments, as experienced by the patients in low income countries, tend to push the burden higher. Irrespective of economic status, access to stroke unit was found to improve recovery.[8] With India's target to reduce premature mortality from NCD by 25% by 2025, along with acute case management, there is an urgent need to find out ways for risk reduction.[9] Hypertension, diabetes, and smoking were reported earlier as common risk factors for developing stroke. Out of these three, diabetes was linked to poor outcome at the end of 3 months from stroke.[10] Tobacco has already been associated with self-reported stroke, while moderate physical activity is less likely to be associated with stroke.[11] The present paper aims to analyze certain modifiable risk factors for stroke from the latest available national data.
| Methods | | |
Data were taken from multiple sources. Data on clean fuel and alcohol consumption were from National Family Health Survey (2015–16) (NFHS) 4.[12] Smokeless tobacco (SLT) use, smoking, and secondhand smoking (SHS) were considered under tobacco, and data were retrieved from Global Adult Tobacco Survey (GATS) 2 report.[13] Data on DALY, summation of years of life lost due to premature death and years lived with disability, were retrieved from India 2016–17 and India: Health of the Nation's States, a report by ICMR, IHME, and PHFI.[3] A total of 29 states and one union territory (UT) were included for analysis as state/UT was kept as the unit for analysis.
Electricity, liquefied petroleum gas/natural gas, and biogas were considered as clean fuel. For alcohol consumption, the average proportion of males and females taking alcohol was taken into account. Per capita net state domestic product (NSDP) was considered as a parameter for economic condition and expressed in INR (Indian currency), and data for 2015–2016 were taken from the Ministry of Statistics and Programme Implementation, India.[14] NFHS 4 considered people aged between 15 and 49 years while GATS 2 interviewed people aged 15 years or older.
The study was an analysis of anonymous datasets. Therefore, approval from the Ethical Committee was waived. Spearman's correlation coefficient was used for testing association. Multivariate regression was used for finding out factors related to DALY attributed to stroke. P < 0.05 was considered statistically significant. PASW for Windows software (version 19.0; SPSS Inc., Chicago, USA) was used.
| Results | | |
States were different in terms of tobacco use, income, and use of clean fuel. Maximum burden was limited to five states –West Bengal, Odisha, Tripura, Assam, and Chhattisgarh. Out of these, Tripura and Assam recorded high prevalence of SLT.
Use of SLT was significantly related to stroke burden (r 0.476, P = 0.008). In fact, overall tobacco use was also associated with stroke burden (r 0.381, P = 0.038). No relation could be established between smoking/SHS at home and DALY. Weak relationship was there with SHS at work and alcohol consumption. Clean fuel was seen to reduce stroke burden significantly (r–0.449, P = 0.013) [Figure 1]. Similar relation was noted between economic condition and stroke burden (r –0.363, P = 0.049) [Figure 2]. | Figure 1: Relationship between use of clean fuel and stroke burden in India
Click here to view |
 | Figure 2: Relationship between economic condition and stroke burden in India
Click here to view |
On multivariate linear regression, use of SLT (B 29.021, P = 0.011) and SHS at work (B 2.325, P = 0.030) were statistically significant [Table 1].
| Discussion | | |
Stroke burden is much dependent on availability of emergency management as delay in initial intervention results in long-term motor/sensory deficit, adding to disability. However, that does not reduce the importance of prevention. INTERSTROKE study pointed out nine potentially modifiable metabolic and behavioral risk factors, to which 86% of strokes could be attributed.[5] The present study also puts its focus on risk factors.
SHS increased risk of first ischemic stroke among men and women.[15] In fact, a meta-analysis suggested dose-dependent association between exposure to SHS and risk of stroke, with high risk even at low levels of exposure.[16] Passive smoking, by promoting atherosclerosis, could increase the risk for developing stroke.[17] Another study from China supports the role of SHS for causing even stroke mortality.[18] McGhee et al. found a dose–response relationship between stroke mortality and SHS.[19] Relationship of stroke was there with not only number of cigarettes but exposure time to smoking.[20] Women were seen developing stroke due to chronic exposure to smoking by husband earlier.[21] The present study although supports the effect of SHS on stroke, gender-wise differentiation was not attempted.
A meta-analysis suggested higher risk of stroke mortality in users of SLT.[22] Chemicals added for making SLT more attractive may change the chemical composition of tobacco, and their possible role in increasing risk of CVD has been claimed earlier.[23],[24] Few studies found significant risk of fatal ischemic stroke in SLT users.[24],[25] There are different opinions about the effect of SLT on hypertension, a known risk factor for stroke. It has been observed that due to frequent use, SLT causes rise in blood nicotine level, leading to hypertension among the users.[26] Tripura, Manipur, Odisha, and Assam should devise their strategy to bring down the use of SLT among population. In the long run, it is expected to reduce stroke burden in these states.
The present study could not find statistically significant relationship between smoking and stroke. Population-based studies from developing nations have earlier linked smoking with occurrence of stroke.[27] As smoking cessation could reduce the risk for developing CVD better than any other pharmacological intervention, antitobacco campaign may result in reduction in burden of stroke.[28] It may be mentioned that India is implementing Cigarettes and Other Tobacco Products Act (COTPA) since 2003. Patient-wise data, if available, could have yielded different results in this regard.
Low alcohol intake has been associated with low risk, but heavy drinking is known to precipitate stroke.[29] The present study did not have data on amount of alcohol; thus, it was unable to divide alcohol consumption into categories. States such as Arunachal Pradesh, Sikkim, Chhattisgarh, and Telangana, being on the higher side of alcohol consumption, should review their data to take meaningful steps.
As air pollution has been a known factor for stroke, particularly in low- and middle-income countries, clean fuel is expected to save many lives in this country.[30] It is worth mentioning that 99% of deaths due to household air pollution take place in developing countries.[31] Under Ujjwala scheme, the government is promoting its use by ensuring its reach till the lowest economic strata. The step would reduce the extent of indoor air pollution, especially in villages where dependency on biomass fuel is a known fact.
Economic condition is another vital factor. The present study could not find any association. However, a previous one estimated the cost to be USD 6845 for inpatient care of ischemic stroke and USD 8783 for carotid endarterectomy.[32] Therefore, it is obvious that affordability is the primary condition for getting acute care in stroke. The subsequent long-term nature of physiotherapy also incurs cost. For better utilization of “golden hour,” few states in the country are implementing “hub and spoke” model.[33]
National Programme for Prevention and Control of Cancer, Diabetes, CVDs and Stroke is the flagship initiative against NCDs in the country, with a focus on health promotion.[34] Although a dedicated strategy for tackling stroke cases is still missing, the program is expected to take the lead to mitigate the burden.
Among strengths, the study provides clue to future researches on SHS and stroke on Indian population. Data from all states and one UT give this study a pan-India frame. In the absence of enough research paper on national data, this study is supposed to fill the information gap. However, there are certain limitations. The study could not differentiate between ischemic and hemorrhagic stroke. Inclusion of clinical data would have improved the quality of this paper. However, such data were not available. Ecological design prevents it from assuming individual relationship between risk factors and stroke. Although the use of clean fuel was considered, no system was there for considering the effect of outdoor air pollution. Per capita NSDP was a proxy for economic status of the state.
| Conclusion | | |
The higher prevalence of smoking and SLT use is a matter of concern for some states. Health policy should focus more on awareness generation and strict implementation of COTPA for cutting down such risk factors. As there are not much data on health expenditure attributed to stroke, further research should explore that aspect.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | GBD 2017 Causes of Death Collaborators. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: A systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018;392:1736-88.  |
| 2. | |
| 3. | Indian Council of Medical Research, Public Health Foundation of India, and Institute for Health Metrics and Evaluation. India: Health of the Nation's States-the India State-Level Disease Burden Initiative. New Delhi, India: ICMR, PHFI, and IHME; 2017. |
| 4. | India State-Level Disease Burden Initiative CVD Collaborators. The changing patterns of cardiovascular diseases and their risk factors in the states of India: The Global Burden of Disease Study 1990-2016. Lancet Glob Health 2018;6:e1339-51. |
| 5. | O'Donnell MJ, Xavier D, Liu L, Zhang H, Chin SL, Rao-Melacini P, et al. Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries (the INTERSTROKE study): A case-control study. Lancet 2010;376:112-23. |
| 6. | Bardach AE, Caporale JE, Rubinstein AL, Danaei G. Impact of level and patterns of alcohol drinking on coronary heart disease and stroke burden in Argentina. PLoS One 2017;12:e0173704. |
| 7. | Micha R, Khatibzadeh S, Shi P, Andrews KG, Engell RE, Mozaffarian D, et al. Global, regional and national consumption of major food groups in 1990 and 2010: A systematic analysis including 266 country-specific nutrition surveys worldwide. BMJ Open 2015;5:e008705. |
| 8. | Langhorne P, O'Donnell MJ, Chin SL, Zhang H, Xavier D, Avezum A, et al. Practice patterns and outcomes after stroke across countries at different economic levels (INTERSTROKE): An international observational study. Lancet 2018;391:2019-27. |
| 9. | Government of India. National Multisectoral Action Plan for Prevention and Control of Common Non Communicable Diseases (2017-2024). Government of India: New Delhi; 2017. |
| 10. | Sylaja PN, Pandian JD, Kaul S, Srivastava MV, Khurana D, Schwamm LH, et al. Ischemic stroke profile, risk factors, and outcomes in India: The indo-US collaborative stroke Project. Stroke 2018;49:219-22. |
| 11. | Patel S, Ram F, Patel SK, Kumar K. Association of behavioral risk factors with self-reported and symptom or measured chronic diseases among adult population (18-69 years) in India: Evidence from SAGE study. BMC Public Health 2019;19:560. |
| 12. | International Institute for Population Sciences (IIPS) and ICF. National Family Health Survey (NFHS-4), 2015-16. India. Mumbai: IIPS; 2017. |
| 13. | Tata Institute of Social Sciences, Mumbai and Ministry of Health and Family Welfare, Government of India. Global Adult Tobacco Survey GATS 2. India. 2016-17. |
| 14. | |
| 15. | Iribarren C, Darbinian J, Klatsky AL, Friedman GD. Cohort study of exposure to environmental tobacco smoke and risk of first ischemic stroke and transient ischemic attack. Neuroepidemiology 2004;23:38-44. |
| 16. | Oono IP, Mackay DF, Pell JP. Meta-analysis of the association between secondhand smoke exposure and stroke. J Public Health (Oxf) 2011;33:496-502. |
| 17. | Mack WJ, Islam T, Lee Z, Selzer RH, Hodis HN. Environmental tobacco smoke and carotid arterial stiffness. Prev Med 2003;37:148-54. |
| 18. | Hou L, Han W, Jiang J, Liu B, Wu Y, Zou X, et al. Passive smoking and stroke in men and women: A national population-based case-control study in China. Sci Rep 2017;7:45542. |
| 19. | McGhee SM, Ho SY, Schooling M, Ho LM, Thomas GN, Hedley AJ, et al. Mortality associated with passive smoking in Hong Kong. BMJ 2005;330:287-8. |
| 20. | He Y, Lam TH, Jiang B, Wang J, Sai X, Fan L, et al. Passive smoking and risk of peripheral arterial disease and ischemic stroke in Chinese women who never smoked. Circulation 2008;118:1535-40. |
| 21. | Zhang X, Shu XO, Yang G, Li HL, Xiang YB, Gao YT, et al. Association of passive smoking by husbands with prevalence of stroke among Chinese women nonsmokers. Am J Epidemiol 2005;161:213-8. |
| 22. | Sinha DN, Suliankatchi RA, Gupta PC, Thamarangsi T, Agarwal N, Parascandola M, et al. Global burden of all-cause and cause-specific mortality due to smokeless tobacco use: Systematic review and meta-analysis. Tob Control 2018;27:35-42. |
| 23. | National Cancer Institute and Centers for Disease Control and Prevention. Smokeless Tobacco and Public Health: A Global Perspective. Bethesda, MD: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention and National Institutes of Health, National Cancer Institute. NIH Publication No. 14-7983; 2014. |
| 24. | Vidyasagaran AL, Siddiqi K, Kanaan M. Use of smokeless tobacco and risk of cardiovascular disease: A systematic review and meta-analysis. Eur J Prev Cardiol 2016;23:1970-81. |
| 25. | Hergens MP, Lambe M, Pershagen G, Terent A, Ye W. Smokeless tobacco and the risk of stroke. Epidemiology 2008;19:794-9. |
| 26. | Hergens MP, Lambe M, Pershagen G, Ye W. Risk of hypertension amongst Swedish male snuff users: A prospective study. J Intern Med 2008;264:187-94. |
| 27. | Zhang FL, Guo ZN, Wu YH, Liu HY, Luo Y, Sun MS, et al. Prevalence of stroke and associated risk factors: A population based cross sectional study from northeast China. BMJ Open 2017;7:e015758. |
| 28. | Spence JD. Secondary stroke prevention. Nat Rev Neurol 2010;6:477-86. |
| 29. | Zhang C, Qin YY, Chen Q, Jiang H, Chen XZ, Xu CL, et al. Alcohol intake and risk of stroke: A dose-response meta-analysis of prospective studies. Int J Cardiol 2014;174:669-77. |
| 30. | Lee KK, Miller MR, Shah AS. Air pollution and stroke. J Stroke 2018;20:2-11. |
| 31. | Landrigan PJ, Fuller R, Acosta NJ, Adeyi O, Arnold R, Basu NN, et al. The Lancet commission on pollution and health. Lancet 2018;391:462-512. |
| 32. | Buisman LR, Tan SS, Nederkoorn PJ, Koudstaal PJ, Redekop WK. Hospital costs of ischemic stroke and TIA in the Netherlands. Neurology 2015;84:2208-15. |
| 33. | Sharma S, Padma MV, Bhardwaj A, Sharma A, Sawal N, Thakur S. Telestroke in resource-poor developing country model. Neurol India 2016;64:934-40. [ PUBMED] [Full text] |
| 34. | |
[Figure 1], [Figure 2]
[Table 1]
|
Search Pubmed for