Evidence map›Paper›PMID 29854903›Full record

ArticleSSM - population health2018

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

Shilpa Nayak, Alan Hubbard, Stephen Sidney, S Leonard Syme

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Article in SSM - population health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Shilpa NayakDepartment of Public Health and Policy, The Whelan Building, Quadrangle, The University of Liverpool, Liverpool L69 3GB, UK.
Alan HubbardSchool of Public Health, The University of California, Berkeley, CA 94720, USA.
Stephen SidneyKaiser Permanente Northern California Division of Research, 2000 Broadway, Oakland, CA 94612, USA.
S Leonard SymeSchool of Public Health, The University of California, Berkeley, CA 94720, USA.

Funding

NHLBI NIH HHS HHSN268200900041CNHLBI NIH HHS HHSN268201300025CNHLBI NIH HHS HHSN268201300026CNHLBI NIH HHS HHSN268201300027CNHLBI NIH HHS HHSN268201300028CNHLBI NIH HHS HHSN268201300029C
6 · The paper itself

Abstract

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.

Indexed as

Classification tree analysisHealth determinantsRandom forestsRecursive partitioning methodsSelf-rated health

Identifiers

PMID29854903
PMCPMC5976867

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.