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Social inequalities in biomarkers of cardiovascular risk in adolescence
Elizabeth Goodman1, Bruce S McEwen, Bin Huang
1Heller School for Social Policy and Management, Brandeis University MS 35, 415 South Street, Waltham, MA 02453-9110, USA. goodman@brandeis.edu
Objective:
Cardiovascular disease, which begins early in life but often is not manifest until adulthood, is the nation's leading cause of mortality. Social inequalities in cardiovascular disease are pervasive, yet the process by which they accrue is poorly understood. The objective of this study was to explore the associations between socioeconomic status, a range of biomarkers reflective of cardiovascular risks, and a cumulative physiological risk score among adolescents.
Methods:
Non-Hispanic black and white high school students (N = 758) in a suburban Midwestern public school district had a physical examination to measure height, weight, and waist circumference and a fasting morning blood sample drawn to assess cortisol, insulin, glucose, glycosylated hemoglobin, fibrinogen, low-density lipoprotein (LDL) and high-density lipoprotein (HDL) cholesterol, and triglycerides. A cumulative risk score was created from these physiological measures and waist circumference. Information on parent education and household income was obtained from a parent in a separate survey. Generalized estimating equation models were used to assess the association of parent education to the risks and the cumulative risk score adjusting for age, gender, and race.
Results:
Lower parent education was associated with higher insulin, higher glucose, greater insulin resistance, higher LDL cholesterol, lower HDL cholesterol, higher waist circumference, and higher body mass index (p <.05 for all), but not cortisol, fibrinogen, glycosylated hemoglobin, or triglycerides in adjusted analyses. Cumulative risk scores ranged from 0 to 7 and were highly skewed; the median risk score was 1. A total of 7.4% had risk scores of 4 or more. Lower parent education was also associated with higher cumulative risk score (p <.001) and this association was maintained after adjustment for body mass index. Risk scores were highest, on average, among those with insulin levels greater than 1 standard deviation above the mean (mean risk score = 3.2, standard error = 0.18, median = 3).
Conclusion:
Lower parent education is associated with multiple metabolic risks and cumulative risk in adolescents, suggesting that there is a strong intergenerational transfer of education's influence on cardiovascular health. Our data imply that regulation of insulin may be a key factor underlying the influence of lower parent education on cardiovascular health early in the life course.
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