Evidence map›Paper›PMID 37963153›Full record

ArticlePloS one2023

Descriptive regression tree analysis of intersecting predictors of adult self-rated health: Does gender matter? A cross-sectional study of Canadian adults.

Afshin Vafaei, Jocelyn M Stewart, Susan P Phillips

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Afshin VafaeiSchool of Health Studies, Western University, London, ON, Canada.ORCID 0000-0002-3605-409X
Jocelyn M StewartDepartment of Family Medicine, Queen's University, Kingston, ON, Canada.
Susan P PhillipsDepartment of Public Health Sciences, Queen's University, Kingston, ON, Canada.

Funding

CIHR 161787
6 · The paper itself

Abstract

backgroundWhile self-rated health (SRH) is a well-validated indicator, its alignment with objective health is inconsistent, particularly among women and older adults. This may reflect group-based differences in characteristics considered when rating health. Using a combination of SRH and satisfaction with health (SH) could capture lived realities for all, thus enabling a more accurate search for predictors of subjective health. With the combined measure of SRH and SH as the outcome we explore a range of characteristics that predict high SRH/SH compared with predictors of a low rating for either SRH or SH.

methodsData were from the Canadian General Social Survey 2016 which includes participants 15 years of age and older. We performed classification and regression tree (CRT) analyses to identify the best combination of socioeconomic, behavioural, and mental health predictors of good SRH and health satisfaction.

resultsAlmost 85% of the population rated their health as good; however, 19% of those had low SH. Conversely, about 20% of those reporting poor SRH were, none-the-less, satisfied. CRT identified healthy eating, absence of a psychological disability, no work disability from long-term illness, and high resilience as the main predictors of good SRH/SH. Living with a spouse or children, higher social class and healthy behaviours also aligned with high scores in both self-perceived health measures. Sex was not a predictor.

conclusionsCombining SRH and SH eliminated sex as a predictor of subjective health, and identified characteristics, particularly resilience, that align with high health and well-being and that are malleable.

Indexed as

Health StatusMental HealthAgedCanadaChildCross-Sectional StudiesFemaleHumansSocial Class

Identifiers

PMID37963153
PMCPMC10645330

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.