Title
Association between socioeconomic status and health behaviour change before and after non-communicable disease diagnoses: a multicohort study
Date Issued
01 August 2022
Access level
open access
Resource Type
journal article
Author(s)
Wang D.
Dai X.
Mishra S.R.
Lim C.C.W.
Gakidou E.
Xu X.
Publisher(s)
Elsevier Ltd
Abstract
Background: Behavioural risk factors of non-communicable diseases (NCDs) are socially patterned. However, the direction and the extent to which socioeconomic status (SES) influences behaviour changes before and after the diagnosis of NCDs is not clearly understood. We aimed to investigate the influence of SES on behaviour changes (physical inactivity and smoking) before and after the diagnosis of major NCDs. Methods: In this multicohort study, we pooled individual-level data from six prospective cohort studies across 17 countries. We included participants who were diagnosed with either diabetes, cardiovascular disease, chronic lung disease, or cancer after recruitment. Participants were surveyed every 2 years. Education and total household wealth were used to construct SES. We measured behaviour changes as whether or not participants continued or initiated physical inactivity or smoking after NCD diagnosis. We used multivariable logistic regression models to estimate odds ratios (ORs), prevalence ratios (PRs), and 95% CIs for the associations between SES and continuation or initiation of unfavourable behaviours. Findings: We included 8107 individuals recruited between March, 2002, and January, 2016. Over the 4-year period before and after NCD diagnosis, 886 (60·4%) of 1466 individuals continued physical inactivity and 1018 (68·8%) of 1480 participants continued smoking; 1047 (15·8%) of 6641 participants with physical activity before diagnosis initiated physical inactivity after diagnosis and 132 (2·0%) of 6627 non-smokers before diagnosis initiated smoking after diagnosis. Compared with participants with high SES, those with low SES were more likely to continue physical inactivity (244 [70·3%] of 347 vs 23 [50.0%] of 46; PR 1·41 [95% CI 1·05–1·99]; OR 2·28 [1·18–4·41]), continue smoking (214 [75·4%] of 284 vs 39 [60·9%] of 64; PR 1·27 [1·03–1·59]; OR 2·08 [1·14–3·80]), but also to initiate physical inactivity (188 [26·1%] of 720 vs 47 [7·4%] of 639; PR 3·59 [2·58–4·85]; OR 4·31 [3·02 – 6·14]). Interpretation: Low SES was associated with continuing or initiating physical inactivity and continuing smoking after NCD diagnosis. Reducing socioeconomic inequality in health behaviour changes should be prioritised and integrated into NCD-prevention programmes. Funding: Zhejiang University and Fundamental Research Funds for the Central Universities.
Start page
e670
End page
e682
Volume
7
Issue
8
Language
English
OCDE Knowledge area
Ciencias médicas, Ciencias de la salud
Scopus EID
2-s2.0-85134987282
PubMed ID
Source
The Lancet Public Health
ISSN of the container
24682667
Sponsor(s)
RMC-L is supported by a Wellcome Trust International Training Fellowship (Wellcome Trust 214185/Z/18/Z). This study was funded by Zhejiang University (Zhejiang, China) and Fundamental Research Funds for the Central Universities. We thank all team members who have contributed to the HRS, ELSA, SHARE CRELES, and KLoSA. We thank the China Center for Economic Research, the National School of Development of Peking University, for providing the CHARLS data. Our analysis used data or information from the Harmonized HRS, ELSA, SHARE, and CHARLS datasets and codebooks developed by the Gateway to Global Aging Data. The development was funded by the US National Institute on Aging (R01 AG030153, RC2 AG036619, and 1R03AG043052). The HRS is sponsored by the National Institute on Aging (NIA U01AG009740) and is conducted by the University of Michigan. Funding for the ELSA is provided by the National Institute of Aging [2RO1AG7644-01A1 and 2RO1AG017644] and a consortium of UK Government departments coordinated by the Office for National Statistics. The SHARE data collection has been funded by the European Commission, through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812), FP7 (SHARE-PREP: GA 211909, SHARE-LEAP: GA 227822, SHARE M4: GA 261982, DASISH: GA 283646), and Horizon 2020 (SHARE-DEV3: GA 676536, SHARE-COHESION: GA 870628, SERISS: GA 654221, SSHOC: GA 823782), and by DG Employment, Social Affairs and Inclusion (VS 2015/0195, VS 2016/0135, VS 2018/0285, VS 2019/0332, and VS 2020/0313). Additional funding from the German Ministry of Education and Research, the Max Planck Society for the Advancement of Science, the US National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, OGHA_04-064, HHSN271201300071C, and RAG052527A) and from various national funding sources is gratefully acknowledged (see https://www.share-project.org). The CRELES project is a longitudinal study by the University of Costa Rica's Centro Centroamericano de Población and Instituto de Investigaciones en Salud, in collaboration with the University of California at Berkeley. KLoSA is organised by the Korea Employment Information Service (KEIS). CHARLS is supported by the Behavioral And Social Research division of the National Institute on Aging of the National Institute of Health (1-R21-AG031372-01, 1-R01-AG037031-01, and 3-R01AG037031-03S1); the Natural Science Foundation of China (70773002, 70910107022, and 71130002), the World Bank (7145915 and 7159234), and is conducted by Peking University.
Sources of information: Directorio de Producción Científica Scopus