Article

Socioeconomic Position and the Metabolic Syndrome in Early, Middle, and Late Life: Evidence from NHANES 1999-2002

Department of Psychiatry, McGill University, Montréal, Quebec, Canada
Annals of Epidemiology (Impact Factor: 2.15). 10/2007; 17(10):782-90. DOI: 10.1016/j.annepidem.2007.05.003
Source: PubMed

ABSTRACT To evaluate whether there is an association between socioeconomic position (SEP) and the metabolic syndrome at various ages, including adolescent, middle-aged and older participants in gender-specific analyses.
Participants were from the 1999-2002 National Health and Nutrition Examination Survey. SEP was measured by income and years of education. Metabolic syndrome was measured in adults using the American Heart Association guidelines and in adolescents using methods based on national reference data. Cross-sectional multivariable-adjusted logistic regression analyses were performed.
In women aged 25 to 45 and 46 to 65 years, income below the poverty line (poverty income ratio [PIR] less than one) was associated with higher odds of metabolic syndrome compared with PIR greater than 3 (odds ratio [OR] = 4.90; 95% confidence interval (CI) = 2.24, 10.71, and OR = 2.54; CI = 1.38, 4.67, for the respective age groups) after adjustment for age, race/ethnicity, and menopause. Similar findings were observed for educational attainment. In adolescents, older adults (aged >65 years), and males, income and education were not related to the metabolic syndrome.
This report demonstrates that SEP is associated with the metabolic syndrome in females aged 25 to 65 years and is less strongly associated in males, adolescents, or older participants. These findings provide physiologic mechanistic evidence linking SEP to risk for coronary heart disease.

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    • "Several studies have shown that low socioeconomic status (SES), with factors such as low income, low educational status, low occupational status and ethnicity, is associated with impaired health and increased morbidity [1] [2] [3]. For example, low SES is associated with severe chronic and comorbid diseases [4], and low SES in childhood is associated with high body mass index in adult life and, thus, mortality [5]. "
    • "These studies raise the possibility that SEP may influence biomarkers in gender-specific ways and through gender-specific pathways. A range of methodological issues threaten the quality of the findings reported from these studies, including: limited measures of SEP, such as dichotomous measure of education and income (Muennig, Sohler et al. 2007); a small number of biological outcomes; a large proportion of missing information on socioeconomic variables particularly income (Loucks, Rehkopf et al. 2007; Pekkanen, Tuomilehto et al. 1995; Seeman, Merkin et al. 2008)) and biomarkers (Loucks, Rehkopf et al. 2007); and, selective samples of work environments (Brunner, Wunsch et al. 2001; De Vogli, Brunner et al. 2007; Heslop, Smith et al. 2001; Ishizaki, Yamada et al. 1999)). In addition, many of the studies dichotomised the biomarkers as below or above a certain threshold as abnormal (e.g. "
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    ABSTRACT: Socio-economic gradients in cardiovascular disease (CVD) and diabetes have been found throughout the developed world and there is some evidence to suggest that these gradients may be steeper for women. Research on social gradients in biological risk factors for CVD and diabetes has received less attention and we do not know the extent to which gradients in biomarkers vary for men and women. We examined the associations between two indicators of socio-economic position (education and household income) and biomarkers of diabetes and cardiovascular disease (CVD) for men and women in a national, population-based study of 11,247 Australian adults. Multi-level linear regression was used to assess associations between education and income and glucose tolerance, dyslipidaemia, blood pressure (BP) and waist circumference before and after adjustment for behaviours (diet, smoking, physical activity, TV viewing time, and alcohol use). Measures of glucose tolerance included fasting plasma glucose and insulin and the results of a glucose tolerance test (2 h glucose) with higher levels of each indicating poorer glucose tolerance. Triglycerides and High Density Lipoprotein (HDL) Cholesterol were used as measures of dyslipidaemia with higher levels of the former and lower levels of the later being associated with CVD risk. Lower education and low income were associated with higher levels of fasting insulin, triglycerides and waist circumference in women. Women with low education had higher systolic and diastolic BP and low income women had higher 2 h glucose and lower HDL cholesterol. With only one exception (low income and systolic BP), all of these estimates were reduced by more than 20% when behavioural risk factors were included. Men with lower education had higher fasting plasma glucose, 2 h glucose, waist circumference and systolic BP and, with the exception of waist circumference, all of these estimates were reduced when health behaviours were included in the models. While low income was associated with higher levels of 2-h glucose and triglycerides it was also associated with better biomarker profiles including lower insulin, waist circumference and diastolic BP. We conclude that low socio-economic position is more consistently associated with a worse profile of biomarkers for CVD and diabetes for women.
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