Users Online: 2342 Home Print this page Email this page Small font sizeDefault font sizeIncrease font size
 

 

Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 
     

 Table of Contents  
ORIGINAL ARTICLE
Year : 2022  |  Volume : 66  |  Issue : 2  |  Page : 128-135  

Prevalence and Associated Factors of Stroke among Older Adults in India: Analysis of the Longitudinal Aging Study in India-Wave 1, 2017–2018


1 PhD Scholar, Department of Epidemiology and Public Health, Central University of Tamil Nadu, Thiruvarur, Tamil Nadu, India
2 Assistant Professor, Department of Epidemiology and Public Health, Central University of Tamil Nadu, Thiruvarur, Tamil Nadu, India

Date of Submission09-Aug-2021
Date of Decision29-Nov-2021
Date of Acceptance01-Dec-2021
Date of Web Publication12-Jul-2022

Correspondence Address:
Naveen Kumar Kodali
Department of Epidemiology and Public Health, Central University of Tamil Nadu, Thiruvarur - 610 005, Tamil Nadu
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijph.ijph_1659_21

Rights and Permissions
   Abstract 


Introduction: Stroke is one of the leading causes of death and disability in India. Stroke survivors may suffer from lifelong physical and cognitive frailty. There is a need for more studies on the prevalence and determinants of this debilitating disease at the national level. Thus, assessing the factors associated with stroke is vital to developing appropriate preventive strategies in India. Methods: Data from the Longitudinal Aging Study in India wave 1 (2017–2018) are utilized for this analysis. The survey collected demographics, social, economic, and health data, including lifestyle factors and stroke, from 65,900 older adults ≥45 years representing all states and union territories. Stroke prevalence was calculated for each independent variable, and the differences were compared using the χ2 test. An unconditional multivariable logistic regression model was used to obtain the adjusted odds ratios (AOR) and 95% confidence intervals (CIs) of each lifestyle and socioeconomic variable for stroke prevalence. Results: The prevalence of self-reported stroke was 1.71% (95% CI: 1.61–1.80). Older adults with hypertension (AOR=3.69, 95% CI: 2.95–4.62), family history of stroke (AOR=3.09; 95% CI: 2.33–4.12), arrhythmias (AOR=2.27; 95% CI: 1.20–4.29), physical inactivity (AOR=1.91; 95% CI: 1.55–2.34) were strong contributors of stroke. Diabetes and high cholesterol individuals have 1.5 times more odds for stroke than those without those conditions. Increasing age (AOR=1.57 for 55–69 older adults, and AOR 2.05 for ≥70 years), male sex (AOR=1.75; 95% CI 1.36–2.26), and rich (AOR=1.58; 95% CI: 1.21–2.06) were also associated with increased odds for stroke. Conclusion: The prevalence of stroke was high among adults aged ≥45 years in India. Hypertension, family history of stroke, arrhythmias, and low physical activity were significant contributors to stroke. The findings suggest that preventing and controlling these lifestyle conditions and behaviors may help prevent stroke.

Keywords: India, lifestyle factors, older adults, stroke


How to cite this article:
Kodali NK, Bhat LD. Prevalence and Associated Factors of Stroke among Older Adults in India: Analysis of the Longitudinal Aging Study in India-Wave 1, 2017–2018. Indian J Public Health 2022;66:128-35

How to cite this URL:
Kodali NK, Bhat LD. Prevalence and Associated Factors of Stroke among Older Adults in India: Analysis of the Longitudinal Aging Study in India-Wave 1, 2017–2018. Indian J Public Health [serial online] 2022 [cited 2022 Aug 13];66:128-35. Available from: https://www.ijph.in/text.asp?2022/66/2/128/350652




   Introduction Top


Stroke is the top second cause of death and disability worldwide after ischemic heart diseases.[1] Evidence shows that stroke is disproportionately higher in the low- and middle-income countries.[2] Stroke is the fifth leading cause of disability-adjusted life years in India.[3] There were 6.5 million stroke cases in India, accounting for 7. 1% of total deaths in 2016.[4] Stroke is a brain attack that causes sensory, motor, and cognitive defects,[5] and stroke survivors may need short-term or lifelong support, leading to enormous human and economic costs.[6]

The growing number of older people and life expectancy will increase the burden of NCDs and may put substantial strain on the health-care system in the coming years in India. For example, India's surge in the aging population describes most of the increase in ischemic heart disease and stroke deaths from 156 to 209 per 100,000 between 1990 and 2017.[3] The leading cause of hospitalization (18.1%) and outpatient visits (32%) among the elderly in India were for cardiovascular diseases, as reported from the 75th Round of the National Sample Survey.[7] From a public health perspective, it is paramount to assess the prevalence of stroke and its determinants for directed strategies for prevention and management.[6],[8]

Evidence from the INTERSTROKE study indicates that ten potentially modifiable risk factors cause almost 90% of stroke.[9] However, they found variations in the individual risk factors across countries and highlighted that global and region-specific programs are needed to prevent stroke.[9] Understanding the prevalence and the modifiable risk factors associated with stroke from the Indian perspective is essential for preventing stroke. There are not enough studies providing prevalence estimates at the state and national levels and the factors associated with stroke in India.[10] There was not sufficient representation of studies from all the parts of the country; for example, most studies were conducted in the Southern and Northern regions of India.[11] Therefore, our study's objective is to assess the prevalence and the lifestyle and socioeconomic factors associated with stroke among older adults of India using the Longitudinal Aging Study in India (LASI) data.


   Materials and Methods Top


Data and participants

Our study utilized data from the LASI wave 1 (2017–2018) survey executed by the International Institute of Population Sciences in Mumbai, India. A multistage cluster sampling was used for arriving at the unit of analysis (older adults). The data from LASI wave 1 represent the 28 states (except Sikkim) and 7 union territories of India. LASI provides data on many social, economic, and health indicators, including stroke data. The LASI Wave-1 covered a sample of 72,262 individuals from adults aged ≥45 years and their spouses regardless of their age. The final sample size considered for this analysis was 65,900 due to the unavailability of biomarker data for all individuals who may have refused to participate for various reasons. There are 26,674 (40.5%) older adults in the age group of 45–54 years, 41% (27,042) between 55 and 70 years, and 12,184 (18.5%) older adults ≥70 years. There were 38,145 (58.1%) females. All the participants provided informed consent for participation in the survey.

Study variables

Response variable

The response variable is stroke and based on the following question: Ever diagnosed with stroke? The options were 1. Yes, 2. No, and 8. Don't know. The responses were codified as a binary variable (no – 0, absence of stroke, yes – 1, presence of stroke).

Socioeconomic variables

The socioeconomic variables are age group (45–54 years, 55–69 years, and ≥70 years), sex (male or female), and residence location (rural or urban). Respondents were classified as poor, middle, and rich based on monthly per capita consumption expenditure. Educational levels are classified into no formal education, 1–5 school years, 6–12 school years, and college. The caste system in India has four categories: Scheduled Caste (SC), Scheduled Tribe (ST), Other Backward Classes, and Forward Castes (FC). States and union territories were classified into six regions (North, Central, East, Northeast, West, and South).

Lifestyle factors

Participants who reported hypertension, arrhythmias, diabetes mellitus, and high cholesterol diagnosis by a health professional were classified as having those conditions. A positive family history of stroke was limited to the individual's father, mother, brother, and sister. Family members usually have the same traditions, values, faith, and genetics. Body mass index (BMI) was calculated using height and weight measurements (BMI = kg/m2). BMI values were grouped into BMI <25 kg/m2, overweight if BMI is between 25 kg/m2-29.9 kg/m2, and obese if the participants had BMI more than ≥30 kg/m2. The respondents who reported using any form of tobacco and alcohol were differentiated into ever users and never users. Those respondents who have either engaged in moderate at least 150 min or vigorous physical activity at least 75 min or an equivalent combination of moderate and vigorous-intensity activity in a week were considered physically active.

Statistical analysis

All the variables were presented in the form of a distribution table. Categorical variables were shown as prevalence and were compared using χ2 tests between different subcategories, and the quantitative variables were organized as means and significant differences determined with the independent sample t-test. Simple and multiple logistic regressions were employed to attain the unadjusted and adjusted odds ratios (AORs) of lifestyle and sociodemographic variables for stroke. Sample weights were applied during the statistical analysis to obtain accurate estimates. STATA 16. StataCorp LLC, College Station, Texas, USA was used for data analysis and for producing a prevalence map.


   Results Top


[Table 1] shows the frequency distribution of all the study variables. There was a total of 17,175 (26.1%) older adults diagnosed with hypertension, 7398 (11.2%) had diabetes mellitus, 1467 (2.2%) had high cholesterol. Mean systolic blood pressure (SBP) was 127.1 mmHg (male: 127.6 female: 126.8), and diastolic blood pressure (DBP) was 81 mmHg (male: 81.9; female: 80.4). The mean BMI was 22.6 kg/m2 (male: 21.8; female: 23.1). Tobacco ever users were 23,396 (35.6%), alcohol ever users were 9203 (13.9%), physically inactive were 22,923 (34.8%). Adults aged ≥45 years with a positive family history of stroke were 3570 (5.45%), and those with arrhythmias were 713 (1.08%).
Table 1: Frequency distribution of socioeconomic and lifestyle factors in older adults

Click here to view


Prevalence of stroke according to lifestyle and socioeconomic variables

[Table 2] displays the findings of the bivariable association between stroke and lifestyle and socioeconomic variables. The prevalence of stroke was significantly associated with hypertension, diabetes, high cholesterol, physical inactivity, arrhythmias, and a family history of stroke. Stroke was higher in participants with hypertension (4.01%), diabetes mellitus (3.96%), and high cholesterol (3.98%) than those without these conditions. In individuals with stroke, the average SBP was 134 mmHg, and DBP was 82.12 mmHg. For stroke patients, the average SBP and DBP were 6.9 mmHg and 1.1 mmHg higher than the average SBP and DBP for individuals without stroke, respectively. Older adults reporting a family history of stroke had more stroke prevalence (4.74%) than those with no family history of stroke (1.54%). The mean BMI in individuals with stroke (22.8 kg/m2) was slightly higher than those without stroke (22.6 kg/m2), but the association was insignificant. The prevalence of stroke was high in tobacco users than never users of tobacco (2.18% vs. 1.45%), and the same results were found for alcohol users than never users (2.62% vs. 1.56%). Stroke is more prevalent in the physically inactive (2.91%) than the physically active (1.06%)
Table 2: Bivariable association of stroke according to lifestyle and socioeconomic variables

Click here to view


The prevalence of stroke significantly increased with age (0.80% in 45–54 years old, 1.97% in 55–69 years old, and 3.10% in the most senior citizens (≥70 years), and on average, stroke patients were 6 years older than individuals without stroke. Stroke was reported slightly higher in urban areas than in rural areas (2.01% vs. 1.57%) and higher in men than in women (2.39% vs. 1.22%). The prevalence of stroke increased as one moved from the poor to rich (poor [1.41%], middle [1.8%], and rich [2.19%]). The lowest proportion of stroke was found in the college-educated (1.04%) than older adults with low education. Stroke was more prevalent in the SC (1.90%) and FCs (1.94%). There were 1124 (1.71%, 95% CI: 1.61%–1.80%) stroke cases out of 65,888 older adults. [Figure 1] shows the prevalence of stroke across states and union territories among the older adults ≥45 years in India. The self-reported prevalence of diagnosed stroke was highest in West Bengal (3.6%), followed by Goa (3.4%), Lakshadweep (3.4%), Maharashtra (2.6%), Chandigarh (2.5%), and lowest in Meghalaya (0.5%), Jharkhand (0.6%), Haryana (0.7%), and Madhya Pradesh (0.8%).
Figure 1: Prevalence of stroke in older adults (45 years and above).

Click here to view


Association between lifestyle factors and socioeconomic variables with stroke

[Table 3] shows the odds ratios of stroke by lifestyle and socioeconomic variables. Hypertension, diabetes mellitus, high cholesterol, physical inactivity, arrhythmias, and family history of stroke were significantly associated with stroke. In older adults with hypertension, the odds of stroke were 3.7 times more than that of nonhypertensives (AOR = 3.69, 95% CI: 2.95–4.62). Individuals with a family history of stroke have a higher likelihood of stroke (AOR = 3.09; 95% CI: 2.33–4.12), and arrhythmias increased the odds of stroke by 2.3 times (AOR = 2.27; 95% CI: 1.20–4.29). Physically inactivity is significantly associated with higher odds for stroke (AOR = 1.91; 95% CI: 1.55–2.34). Individuals with diabetes mellitus (AOR = 1.52; 95% CI: 1.18–1.96) and high cholesterol (AOR = 1.47; 95% CI: 1.01–2.14) have 1.5 times more odds for stroke than those without diabetes and high cholesterol. BMI was not associated with stroke both in the univariable and multivariable analyses. Alcohol and tobacco use was associated with stroke only in the univariable analysis.
Table 3: Multivariable association between lifestyle and socioeconomic variables with stroke in older adults

Click here to view


Increasing age (AOR = 1.57 for 55–69-year older adults, and AOR: 2.05 for ≥70 years), male sex (AOR = 1.75; 95% CI: 1.36–2.26), rich (AOR = 1.58; 95% CI: 1.21–2.06), and individuals from SCs have higher odds for stroke. Western (AOR = 1.92; 95% CI: 1.34–2.76) and eastern regions (AOR = 1.66; 95% CI: 1.18–2.32) of India have higher odds for stroke than the northern region of India.


   Discussion Top


We have found that hypertension, family history of stroke, arrhythmias, physical inactivity, diabetes mellitus, and high cholesterol are significantly associated with stroke in older adults. Among the socioeconomic variables, increasing age, males, rich older adults, SCs, western and eastern regions of India were significantly associated with stroke in older adults of India.

In our study, the prevalence of stroke is 1.7%. The WHO-SAGE survey conducted in India found a similar proportion (2%) of a stroke to our study result.[12] A systematic review and meta-analysis of epidemiologic surveys from 1960 to 2018 conducted by Khurana et al.[11] showed that the stroke burden in India is high. Banerjee and Huth's time-series analysis of cardiovascular diseases in India showed that stroke prevalence continues the same trend and is predicted to rise in 2030.[13] According to the WHO-SAGE report, West-Bengal (3.8%) had the highest prevalence of stroke in older adults, followed by Karnataka (2.0%), Rajasthan (1.7%), Uttar Pradesh (1.6), Maharashtra (1.5%), and Assam (1.2%), which are similar to the findings of our study.[14]

Hypertension, family history of stroke, arrhythmias, physical inactivity, diabetes, and high cholesterol were significantly associated with stroke. Hypertension is a major lifestyle disease associated with stroke in our study. Older adults diagnosed with hypertension have 3.7 times more odds of stroke than those with no hypertension, which corresponds to earlier studies.[15],[16] After hypertension, positive family history of stroke is the major contributor to stroke in our study. History of stroke in parents before 65 years was associated with three times more risk for the first stroke in their progenies, consistent with the study results.[17] Positive family history is the chief risk factor for stroke at a young age.[18] Older adults with arrhythmias had 2.2 times more odds for stroke than those without arrhythmias in this study. However, many of Hill's criteria were unclear to support the hypothesis that atrial fibrillation causes stroke.[19] Older adults with diabetes and high cholesterol are 1.5 times more likely to have a stroke than those without these conditions, and the results agree with other studies.[8],[9],[20]

Physical inactivity or low physical activity is also one of the most significant lifestyle factors associated with stroke; physically inactive people have nearly twice the odds of stroke than physically active. Physical inactivity was a strong risk factor (hazard ratio: 1.60) for stroke among older adults.[21] Physically activity can positively influence at least three modifiable risk factors of stroke: hypertension, diabetes mellitus, and body fat.[22] No <40 min/day of moderate to vigorous aerobic physical activity of 3 or 4 days/week is recommended for stroke prevention.[8] Obesity was associated with decreased odds of stroke in older adults in this study. According to a systematic review, observational studies indicated a lower mortality rate of stroke in obese patients (obesity paradox) though the studies are not free of methodological concerns.[23] In the multivariable analysis, alcohol and tobacco use were not significantly associated with stroke, but other studies provided evidence of these factors increasing the likelihood of stroke.[8],[15]

Stroke increased with age (AOR 1.6 for 55–69-year older adults, AOR 2.1 for ≥70 years), consistent with other studies.[10],[11],[12] Individuals above 65 years and above were responsible for 88% of strokes worldwide.[6] Sex differences in stroke show conflicting results. Our results found that stroke was significantly higher in men than women, in line with the previous study.[9] Prabhakaran et al. in India have shown that the disease burden of stroke was similar in both sexes.[4] Studies have also demonstrated that women have more stroke events than men due to longer life expectancy and older age.[24],[25] In this study, college-educated have the lowest odds for stroke; a cohort study conducted in Australia showed that low education is a risk factor for stroke in men and women and stressed that education is vital for positive health.[26] Individuals from higher-income backgrounds were associated with stroke in India in this study. Individuals from wealthy backgrounds have 1.6 times higher odds for stroke than poor older adults, consistent with a previous study.[27] This study has a few limitations. Stroke and many of the exposure variables were self-reported in the survey. The survey did not differentiate stroke data into ischemic stroke and hemorrhagic stroke. One of the essential lifestyle variables, dietary habits, was not included in the analysis due to a lack of data in this survey. Furthermore, cross-sectional surveys are not free of recall bias because of the self-reported questionnaire.


   Conclusion Top


We have computed unbiased estimates of lifestyle factors associated with stroke. The results can be generalized to the Indian population of adults ≥45 years. Hypertension, family history of stroke, arrhythmias, and physical inactivity increase the odds of stroke. The results suggest that individual and community level interventions are required to prevent stroke. It is also essential to raise the alarm in descendants with a family history of stroke.

Acknowledgment

The authors sincerely thank the Program on Global Aging, Health, and Policy, University of Southern California Dornsife Center for Economic and Social Research, for providing data for this analysis.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
   References Top

1.
Roth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, Baddour LM, et al. Global burden of cardiovascular diseases and risk factors, 1990-2019: Update from the GBD 2019 study. J Am Coll Cardiol 2020;76:2982-3021.  Back to cited text no. 1
    
2.
Marshall IJ, Wang Y, Crichton S, McKevitt C, Rudd AG, Wolfe CD. The effects of socioeconomic status on stroke risk and outcomes. Lancet Neurol 2015;14:1206-18.  Back to cited text no. 2
    
3.
Dandona L, Dandona R, Kumar GA, Shukla DK, Paul VK, Balakrishnan K, et al. Nations within a nation: Variations in epidemiological transition across the states of India, 1990-2016 in the Global Burden of Disease Study. Lancet 2017;390:2437-60.  Back to cited text no. 3
    
4.
Prabhakaran D, Jeemon P, Sharma M, Roth GA, Johnson C, Harikrishnan S, et al. 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.  Back to cited text no. 4
    
5.
Al-Qazzaz NK, Ali SH, Ahmad SA, Islam S, Mohamad K. Cognitive impairment and memory dysfunction after a stroke diagnosis: A post-stroke memory assessment. Neuropsychiatr Dis Treat 2014;10:1677-91.  Back to cited text no. 5
    
6.
Avan A, Digaleh H, Di Napoli M, Stranges S, Behrouz R, Shojaeianbabaei G, et al. Socioeconomic statzus and stroke incidence, prevalence, mortality, and worldwide burden: An ecological analysis from the Global Burden of Disease Study 2017. BMC Med 2019;17:191.  Back to cited text no. 6
    
7.
Ranjan A, Muraleedharan VR. Equity and elderly health in India: Reflections from 75th round National Sample Survey, 2017-18, amidst the COVID-19 pandemic. Global Health 2020;16:93.  Back to cited text no. 7
    
8.
O'Donnell MJ, Chin SL, Rangarajan S, Xavier D, Liu L, Zhang H, et al. Global and regional effects of potentially modifiable risk factors associated with acute stroke in 32 countries (INTERSTROKE): A case-control study. Lancet 2016;388:761-75.  Back to cited text no. 8
    
9.
Yi X, Luo H, Zhou J, Yu M, Chen X, Tan L, et al. Prevalence of stroke and stroke related risk factors: A population based cross sectional survey in south western China. BMC Neurol 2020;20:5.  Back to cited text no. 9
    
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.  Back to cited text no. 10
    
11.
Khurana S, Gourie-Devi M, Sharma S, Kushwaha S. Burden of stroke in India during 1960 to 2018: A systematic review and meta-analysis of community based surveys. Neurol India 2021;69:547-59.  Back to cited text no. 11
[PUBMED]  [Full text]  
12.
Ruan Y, Guo Y, Zheng Y, Huang Z, Sun S, Kowal P, et al. Cardiovascular Disease (CVD) and associated risk factors among older adults in six low-and middle-income countries: Results from SAGE Wave 1. BMC Public Health 2018;18:778.  Back to cited text no. 12
    
13.
Banerjee S, Huth JK. Time-series study of cardiovascular rates in India: A systematic analysis between 1990 and 2017. Indian Heart J 2020;72:194-6.  Back to cited text no. 13
    
14.
Arokiasamy P, Parasuraman S, Sekher TV, Lhungdim H. Study on Global AGEing and Adult Health (SAGE), Wave 1 – India National Report. Mumbai: International Institute of Population Sciences; 2013. p. 254.  Back to cited text no. 14
    
15.
Yusuf S, Joseph P, Rangarajan S, Islam S, Mente A, Hystad P, et al. Modifiable risk factors, cardiovascular disease, and mortality in 155722 individuals from 21 high-income, middle-income, and low-income countries (PURE): A prospective cohort study. Lancet 2020;395:795-808.  Back to cited text no. 15
    
16.
Lawes CM, Vander Hoorn S, Rodgers A; International Society of Hypertension. Global burden of blood-pressure-related disease, 2001. Lancet 2008;371:1513-8.  Back to cited text no. 16
    
17.
Seshadri S, Beiser A, Pikula A, Himali JJ, Kelly-Hayes M, Debette S, et al. Parental occurrence of stroke and risk of stroke in their children: The Framingham study. Circulation 2010;121:1304-12.  Back to cited text no. 17
    
18.
Pourasgari M, Mohamadkhani A. Heritability for stroke: Essential for taking family history. Caspian J Intern Med 2020;11:237-43.  Back to cited text no. 18
    
19.
Kamel H, Okin PM, Elkind MS, Iadecola C. Atrial fibrillation and mechanisms of stroke: Time for a new model. Stroke 2016;47:895-900.  Back to cited text no. 19
    
20.
Nayak AR, Badar SR, Lande N, Kawle AP, Kabra DP, Chandak NH, et al. Prediction of outcome in diabetic acute ischemic stroke patients: A hospital-based pilot study report. Ann Neurosci 2016;23:199-208.  Back to cited text no. 20
    
21.
Willey JZ, Moon YP, Sacco RL, Greenlee H, Diaz KM, Wright CB, et al. Physical inactivity is a strong risk factor for stroke in the oldest old: Findings from a multi-ethnic population (the Northern Manhattan Study). Int J Stroke 2017;12:197-200.  Back to cited text no. 21
    
22.
Howard VJ, McDonnell MN. Physical activity in primary stroke prevention: Just do it! Stroke 2015;46:1735-9.  Back to cited text no. 22
    
23.
Oesch L, Tatlisumak T, Arnold M, Sarikaya H. Obesity paradox in stroke – Myth or reality? A systematic review. PLoS One 2017;12:e0171334.  Back to cited text no. 23
    
24.
Reeves MJ, Bushnell CD, Howard G, Gargano JW, Duncan PW, Lynch G, et al. Sex differences in stroke: Epidemiology, clinical presentation, medical care, and outcomes. Lancet Neurol 2008;7:915-26.  Back to cited text no. 24
    
25.
Banerjee TK, Das SK. Fifty years of stroke researches in India. Ann Indian Acad Neurol 2016;19:1-8.  Back to cited text no. 25
[PUBMED]  [Full text]  
26.
Jackson CA, Sudlow CL, Mishra GD. Education, sex and risk of stroke: A prospective cohort study in New South Wales, Australia. BMJ Open 2018;8:e024070.  Back to cited text no. 26
    
27.
Wang S, Shen B, Wu M, Chen C, Wang J. Effects of socioeconomic status on risk of ischemic stroke: A case-control study in the Guangzhou population. BMC Public Health 2019;19:648.  Back to cited text no. 27
    


    Figures

  [Figure 1]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

Top
 
 
  Search
 
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

 
  In this article
    Abstract
   Introduction
    Materials and Me...
   Results
   Discussion
   Conclusion
    References
    Article Figures
    Article Tables

 Article Access Statistics
    Viewed310    
    Printed4    
    Emailed0    
    PDF Downloaded80    
    Comments [Add]    

Recommend this journal