Associations Between Household and Neighbourhood Socioeconomic Status and Systolic Blood Pressure Among Urban South African Adolescents

Abstract

SummaryFactors resulting in high risk for cardiovascular disease have been well studied in high income countries, but have been less well researched in low/middle income countries. This is despite robust theoretical evidence of environmental transitions in such countries which could result in biological adaptations that lead to increased hypertension and cardiovascular disease risk. Data from the South African Birth to Twenty cohort, Bone Health sub-sample (n=358, 47% female), were used to model associations between household socioeconomic status (SES) in infancy, household/neighbourhood SES at age 16 years, and systolic blood pressure (multivariate linear regression) and risk for systolic pre-hypertension (binary logistic regression). Bivariate analyses revealed household/neighbourhood SES measures that were significantly associated with increased systolic blood pressure. These significant associations included improved household sanitation in infancy/16 years, caregiver owning the house in infancy and being in a higher tertile (higher SES) of indices measuring school problems/environment or neighbourhood services/problems/crime at 16 years of age. Multivariate analyses adjusted for sex, maternal age, birth weight, parity, smoking, term birth, height/body mass index at 16 years. In adjusted analyses, only one SES variable remained significant for females: those in the middle tertile of the crime prevention index had higher systolic blood pressure (β=3.52, SE=1.61) compared with the highest tertile (i.e. those with the highest crime prevention). In adjusted analyses, no SES variables were significantly associated with the systolic blood pressure of boys, or with the risk of systolic pre-hypertension in either sex. The lack of association between SES and systolic blood pressure/systolic pre-hypertension at age 16 years is consistent with other studies showing an equalization of adolescent health inequalities. Further testing of the association between SES and systolic blood pressure would be recommended in adulthood to see whether the lack of association persists.

Metrics in Urban Health: Current Developments and Future Prospects

“…The major concern was to determine social inequalities in health in urban areas across race/ethnic, socioeconomic, gender, or migrant groups. The health issues considered are diverse, including child health, mental health, obesity, physical activity, HIV, and substance abuse (4,9,12,34,59,66). At the same time, the emphasis on NCDs was stronger than in the case of the built environment, especially on mental health.…”

In urban South Africa, 16 year old adolescents experience greater health equality than children

“…Furthermore, the second components for any of the indices were hard to interpret in a theory driven approach to construction because they included both positive and negative values and there was no clear substantive reason that could be found for the variables that were assigned negative values versus positive values in any of the indices. Further details about the composition and fit of the neighbourhood indices have previously been reported (Griffiths et al, 2012). Neighbourhood indices created were; (1) neighbourhood economic index, (2) neighbourhood need for more services and facilities index, (3) neighbourhood problem index, (4) neighbourhood crime prevention index, and (5) neighbourhood social support and happiness index.…”

Urban South African Adolescents' Perceptions of Their Neighborhood Socio-Economic Environments: The Birth to Twenty Plus Cohort Study

“…within their neighborhoods. The neighborhood SES indices created in this study have also been used and related to health issues such as systolic blood pressure and anthropometric measures (Griffiths et al 2012;2013).…”

“…These were built on indices developed by Griffiths et al (2012) (see Table 1). There is a debate around the use of indices for measuring SES over individual SES variables (Sheppard et al 2009).…”