A recursive partitioning approach to investigating correlates of self-rated health: The CARDIA Study.

Autor: Nayak S; Department of Public Health and Policy, The Whelan Building, Quadrangle, The University of Liverpool, Liverpool L69 3GB, UK., Hubbard A; School of Public Health, The University of California, Berkeley, CA 94720, USA., Sidney S; Kaiser Permanente Northern California Division of Research, 2000 Broadway, Oakland, CA 94612, USA., Syme SL; School of Public Health, The University of California, Berkeley, CA 94720, USA.
Jazyk: angličtina
Zdroj: SSM - population health [SSM Popul Health] 2017 Dec 15; Vol. 4, pp. 178-188. Date of Electronic Publication: 2017 Dec 15 (Print Publication: 2018).
DOI: 10.1016/j.ssmph.2017.12.002
Abstrakt: Self-rated health (SRH) is an independent predictor of mortality; studies have investigated correlates of SRH to explain this predictive capability. However, the interplay of a broad array of factors that influence health status may not be adequately captured with parametric multivariate regression. This study investigated associations between several health determinants and SRH using recursive partitioning methods. This non-parametric analytic approach aimed to reflect the social-ecological model of health, emphasizing relationships between multiple health determinants, including biological, behavioral, and from social/physical environments. The study sample of 3648 men and women was drawn from the year 15 (2000-2001) data collection of the CARDIA Study, USA, in order to study a young adult sample. Classification tree analysis identified 15 distinct, mutually exclusive, subgroups (eight with a larger proportion of individuals with higher SRH, and seven with a larger proportion of lower SRH), and multi-domain risk and protective factors associated with subgroup membership. Health determinant profiles were not uniform between subgroups, even for those with similar health status. The subgroup with the largest proportion of higher SRH was characterized by several protective factors, whilst that with the largest proportion of lower SRH, with several negative risk factors; certain factors were associated with both higher and lower SRH subgroups. In the full sample, physical activity, education and income were highest ranked by variable importance (random forests analysis) in association with SRH. This exploratory study demonstrates the utility of recursive partitioning methods in studying the joint impact of multiple health determinants. The findings indicate that factors do not affect SRH in the same way across the whole sample. Multiple factors from different domains, and with varying relative importance, are associated with SRH in different subgroups. This has implications for developing and prioritizing appropriate interventions to target conditions and factors that improve self-rated health status.
Databáze: MEDLINE