4.7 Article

Systolic Blood Pressure, Socioeconomic Status, and Biobehavioral Risk Factors in a Nationally Representative US Young Adult Sample

Journal

HYPERTENSION
Volume 58, Issue 2, Pages 161-U85

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1161/HYPERTENSIONAHA.111.171272

Keywords

systolic blood pressure; socioeconomic status; education; income; body mass index; biobehavioral risk

Funding

  1. Eunice Kennedy Shriver National Institute of Child Health and Human Development [P01 HD31921]
  2. National Heart, Lung and Blood Institute [P01 HL36587]

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In the National Longitudinal Study of Adolescent Health, a US longitudinal study of >15 000 young adults, we examined the extent to which socioeconomic status is linked to systolic blood pressure (SBP) and whether biobehavioral risk factors mediate the association. More than 62% of the participants had SBP >120 mm Hg and 12% had SBP >140 mm Hg. More than 66% were classified as at least overweight (body mass index >25 kg/m(2)), with >36% meeting criteria for at least class I obesity (body mass index >30 kg/m(2)). Multivariate models showed that higher household income and being married were independently associated with lower SBP. Higher body mass index, greater waist circumference, smoking, and higher alcohol intake were each independently associated with higher SBP. Meditational analyses suggested that higher education level was associated with lower SBP by way of lower body mass, smaller waist circumference, and lower resting heart rate. When these indirect effects were accounted for, education was not significantly associated with SBP. In contrast, household income remained associated with SBP even with control for all of the covariates. Results reinforce current public health concerns about rates of obesity and high blood pressure among young adults and suggest that disparities in education level and household income may play an important role in the observed decrements in health. Identifying modifiable mechanisms that link socioeconomic status to SBP using data from a large representative sample may improve risk stratification and guide the development of effective interventions. (Hypertension. 2011;58:161-166.). Online Data Supplement

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