Socio-economic patterning of cardiometabolic risk factors in rural and peri-urban India: Andhra Pradesh children and parents study (APCAPS)
Aim To assess the prevalence of cardiometabolic risk factors by socio-economic position (SEP) in rural and peri-urban Indian population. Subjects and methods Cross-sectional survey of 3,948 adults (1,154 households) from Telangana (2010–2012) was conducted to collect questionnaire-based data, physic...
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Published in | Journal of public health Vol. 23; no. 3; pp. 129 - 136 |
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Main Authors | , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.06.2015
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
ISSN | 2198-1833 1613-2238 |
DOI | 10.1007/s10389-015-0662-y |
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Abstract | Aim
To assess the prevalence of cardiometabolic risk factors by socio-economic position (SEP) in rural and peri-urban Indian population.
Subjects and methods
Cross-sectional survey of 3,948 adults (1,154 households) from Telangana (2010–2012) was conducted to collect questionnaire-based data, physical measurements and fasting blood samples. We compared the prevalence of risk factors and their clustering by SEP adjusting for age using the Mantel Hansel test.
Results
Men and women with no education had higher prevalence of increased waist circumference (men: 8 vs. 6.4 %,
P
< 0.001; women: 20.9 vs. 12.0 %,
P
= 0.01), waist-hip ratio (men: 46.5 vs. 25.8 %,
P
= 0.003; women: 58.8 vs. 29.2 %,
P
= 0.04) and regular alcohol intake (61.7 vs. 32.5 %,
P
< 0.001; women: 25.7 vs. 3.8 %,
P
< 0.001) than educated participants. Unskilled participants had higher prevalence of regular alcohol intake (men: 57.7 vs. 38.7 %,
P
= 0.001; women: 28.3 vs. 7.3 %,
P
< 0.001). In contrast, participants with a higher standard of living index had higher prevalence of diabetes (top third vs. bottom third: men 5.2 vs. 3.5 %,
P
= 0.004; women 5.5 vs. 2.4 %,
P
= 0.003), hyperinsulinemia (men 29.5 vs. 16.3 %,
P
= 0.002; women 31.1 vs. 14.3 %,
P
< 0.001), obesity (men 23.3 vs. 10.6 %,
P
< 0.001; women 25.9 vs. 12.8 %,
P
< 0.001), and raised LDL (men 16.8 vs. 11.4 %,
P
= 0.001; women 21.3 vs. 14.0 %,
P
< 0.001).
Conclusions
Cardiometabolic risk factors are common in rural India but do not show a consistent association with SEP except for higher prevalence of smoking and regular alcohol intake in lower SEP group. Strategies to address the growing burden of cardiometabolic diseases in urbanizing rural India should be assessed for their potential impact on social inequalities in health. |
---|---|
AbstractList | Aim
To assess the prevalence of cardiometabolic risk factors by socio-economic position (SEP) in rural and peri-urban Indian population.
Subjects and methods
Cross-sectional survey of 3,948 adults (1,154 households) from Telangana (2010–2012) was conducted to collect questionnaire-based data, physical measurements and fasting blood samples. We compared the prevalence of risk factors and their clustering by SEP adjusting for age using the Mantel Hansel test.
Results
Men and women with no education had higher prevalence of increased waist circumference (men: 8 vs. 6.4 %,
P
< 0.001; women: 20.9 vs. 12.0 %,
P
= 0.01), waist-hip ratio (men: 46.5 vs. 25.8 %,
P
= 0.003; women: 58.8 vs. 29.2 %,
P
= 0.04) and regular alcohol intake (61.7 vs. 32.5 %,
P
< 0.001; women: 25.7 vs. 3.8 %,
P
< 0.001) than educated participants. Unskilled participants had higher prevalence of regular alcohol intake (men: 57.7 vs. 38.7 %,
P
= 0.001; women: 28.3 vs. 7.3 %,
P
< 0.001). In contrast, participants with a higher standard of living index had higher prevalence of diabetes (top third vs. bottom third: men 5.2 vs. 3.5 %,
P
= 0.004; women 5.5 vs. 2.4 %,
P
= 0.003), hyperinsulinemia (men 29.5 vs. 16.3 %,
P
= 0.002; women 31.1 vs. 14.3 %,
P
< 0.001), obesity (men 23.3 vs. 10.6 %,
P
< 0.001; women 25.9 vs. 12.8 %,
P
< 0.001), and raised LDL (men 16.8 vs. 11.4 %,
P
= 0.001; women 21.3 vs. 14.0 %,
P
< 0.001).
Conclusions
Cardiometabolic risk factors are common in rural India but do not show a consistent association with SEP except for higher prevalence of smoking and regular alcohol intake in lower SEP group. Strategies to address the growing burden of cardiometabolic diseases in urbanizing rural India should be assessed for their potential impact on social inequalities in health. To assess the prevalence of cardiometabolic risk factors by socio-economic position (SEP) in rural and peri-urban Indian population. Cross-sectional survey of 3,948 adults (1,154 households) from Telangana (2010-2012) was conducted to collect questionnaire-based data, physical measurements and fasting blood samples. We compared the prevalence of risk factors and their clustering by SEP adjusting for age using the Mantel Hansel test. Men and women with no education had higher prevalence of increased waist circumference (men: 8 vs. 6.4 %, < 0.001; women: 20.9 vs. 12.0 %, = 0.01), waist-hip ratio (men: 46.5 vs. 25.8 %, = 0.003; women: 58.8 vs. 29.2 %, = 0.04) and regular alcohol intake (61.7 vs. 32.5 %, < 0.001; women: 25.7 vs. 3.8 %, < 0.001) than educated participants. Unskilled participants had higher prevalence of regular alcohol intake (men: 57.7 vs. 38.7 %, = 0.001; women: 28.3 vs. 7.3 %, < 0.001). In contrast, participants with a higher standard of living index had higher prevalence of diabetes (top third vs. bottom third: men 5.2 vs. 3.5 %, = 0.004; women 5.5 vs. 2.4 %, = 0.003), hyperinsulinemia (men 29.5 vs. 16.3 %, = 0.002; women 31.1 vs. 14.3 %, < 0.001), obesity (men 23.3 vs. 10.6 %, < 0.001; women 25.9 vs. 12.8 %, < 0.001), and raised LDL (men 16.8 vs. 11.4 %, = 0.001; women 21.3 vs. 14.0 %, < 0.001). Cardiometabolic risk factors are common in rural India but do not show a consistent association with SEP except for higher prevalence of smoking and regular alcohol intake in lower SEP group. Strategies to address the growing burden of cardiometabolic diseases in urbanizing rural India should be assessed for their potential impact on social inequalities in health. To assess the prevalence of cardiometabolic risk factors by socio-economic position (SEP) in rural and peri-urban Indian population. Cross-sectional survey of 3,948 adults (1,154 households) from Telangana (2010-2012) was conducted to collect questionnaire-based data, physical measurements and fasting blood samples. We compared the prevalence of risk factors and their clustering by SEP adjusting for age using the Mantel Hansel test. Men and women with no education had higher prevalence of increased waist circumference (men: 8 vs. 6.4 %, P<0.001; women: 20.9 vs. 12.0 %, P=0.01), waist-hip ratio (men: 46.5 vs. 25.8 %, P=0.003; women: 58.8 vs. 29.2 %, P=0.04) and regular alcohol intake (61.7 vs. 32.5 %, P<0.001; women: 25.7 vs. 3.8 %, P<0.001) than educated participants. Unskilled participants had higher prevalence of regular alcohol intake (men: 57.7 vs. 38.7 %, P=0.001; women: 28.3 vs. 7.3 %, P<0.001). In contrast, participants with a higher standard of living index had higher prevalence of diabetes (top third vs. bottom third: men 5.2 vs. 3.5 %, P=0.004; women 5.5 vs. 2.4 %, P=0.003), hyperinsulinemia (men 29.5 vs. 16.3 %, P=0.002; women 31.1 vs. 14.3 %, P<0.001), obesity (men 23.3 vs. 10.6 %, P<0.001; women 25.9 vs. 12.8 %, P<0.001), and raised LDL (men 16.8 vs. 11.4 %, P=0.001; women 21.3 vs. 14.0 %, P<0.001). Cardiometabolic risk factors are common in rural India but do not show a consistent association with SEP except for higher prevalence of smoking and regular alcohol intake in lower SEP group. Strategies to address the growing burden of cardiometabolic diseases in urbanizing rural India should be assessed for their potential impact on social inequalities in health. |
Author | Kumar, Aniket Gupta, Vipin Smith, George Davey Prabhakaran, Poornima Krishna, K. V. Radha Gupta, Ruby Millett, Christopher Bhogadi, Santhi Reddy, K. Srinath Prabhakaran, D. Kinra, Sanjay Ben-Shlomo, Yoav Ebrahim, Shah Walia, Gagandeep Kaur Aggarwal, Aastha |
Author_xml | – sequence: 1 givenname: Vipin surname: Gupta fullname: Gupta, Vipin email: udaiig@gmail.com organization: Department of Anthropology, University of Delhi – sequence: 2 givenname: Christopher surname: Millett fullname: Millett, Christopher organization: Faculty of Medicine, School of Public Health, Imperial College London, Public Health Foundation of India – sequence: 3 givenname: Gagandeep Kaur surname: Walia fullname: Walia, Gagandeep Kaur organization: Public Health Foundation of India – sequence: 4 givenname: Sanjay surname: Kinra fullname: Kinra, Sanjay organization: Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine – sequence: 5 givenname: Aastha surname: Aggarwal fullname: Aggarwal, Aastha organization: Public Health Foundation of India – sequence: 6 givenname: Poornima surname: Prabhakaran fullname: Prabhakaran, Poornima organization: Public Health Foundation of India – sequence: 7 givenname: Santhi surname: Bhogadi fullname: Bhogadi, Santhi organization: Public Health Foundation of India – sequence: 8 givenname: Aniket surname: Kumar fullname: Kumar, Aniket organization: Public Health Foundation of India – sequence: 9 givenname: Ruby surname: Gupta fullname: Gupta, Ruby organization: Public Health Foundation of India – sequence: 10 givenname: D. surname: Prabhakaran fullname: Prabhakaran, D. organization: Public Health Foundation of India, Centre for Chronic Disease Control – sequence: 11 givenname: K. Srinath surname: Reddy fullname: Reddy, K. Srinath organization: Public Health Foundation of India – sequence: 12 givenname: George Davey surname: Smith fullname: Smith, George Davey organization: MRC Integrative Epidemiology Unit, University of Bristol – sequence: 13 givenname: Yoav surname: Ben-Shlomo fullname: Ben-Shlomo, Yoav organization: School of Social and Community Medicine, University of Bristol – sequence: 14 givenname: K. V. Radha surname: Krishna fullname: Krishna, K. V. Radha organization: Indian Council for Medical Research, National Institute of Nutrition – sequence: 15 givenname: Shah surname: Ebrahim fullname: Ebrahim, Shah organization: Public Health Foundation of India, Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/26000232$$D View this record in MEDLINE/PubMed |
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CitedBy_id | crossref_primary_10_1016_j_numecd_2016_08_001 crossref_primary_10_1371_journal_pone_0271169 crossref_primary_10_1007_s11814_016_0221_4 crossref_primary_10_1186_s12913_024_11560_5 crossref_primary_10_1007_s13410_022_01133_9 crossref_primary_10_1016_j_envint_2019_105108 |
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Keywords | Status Metabolic disease Socioeconomic position Cardiovascular Risk factors |
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To assess the prevalence of cardiometabolic risk factors by socio-economic position (SEP) in rural and peri-urban Indian population.
Subjects and methods... To assess the prevalence of cardiometabolic risk factors by socio-economic position (SEP) in rural and peri-urban Indian population. Cross-sectional survey of... To assess the prevalence of cardiometabolic risk factors by socio-economic position (SEP) in rural and peri-urban Indian population. Cross-sectional survey of... |
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SubjectTerms | Cardiovascular disease Economics Epidemiology Health Promotion and Disease Prevention Health risks Households Medicine Medicine & Public Health Original Original Article Public Health Risk factors Rural areas Socioeconomic factors Socioeconomics Standard of living Urban areas |
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Title | Socio-economic patterning of cardiometabolic risk factors in rural and peri-urban India: Andhra Pradesh children and parents study (APCAPS) |
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