Dataset Information

Does a physical activity supportive environment ameliorate or exacerbate socioeconomic inequities in incident coronary heart disease?

ABSTRACT:

Background

Efforts to reduce socioeconomic inequities in cardiovascular disease include interventions to change the built environment. We aimed to explore whether socioeconomic inequities in coronary heart disease (CHD) incidence are ameliorated or exacerbated in environments supportive of physical activity (PA).

Methods

We used data from the Reasons for Geographic and Racial Differences in Stroke study, which recruited US residents aged 45 or older between 2003 and 2007. Our analyses included participants at risk for incident CHD (n=20 808), followed until 31 December 2014. We categorised household income and treated it as ordinal: (1) US$75 000+, (2) US$35 000-US$74 000, (3) US$20 000-US$34 000 and (4) ResultsWe found a 25% (95% CI 1.17% to 1.34%) increased hazard of CHD per 1-category decrease in household income category. Adjusting for PA-supportive environments slightly reduced this association (HR=1.24). The income-CHD association was strongest in areas without walking destinations (HR=1.57), an interaction which reached statistical significance in analyses among men. In contrast, the income-CHD association showed a trend towards being strongest in areas with the highest percentage of green land cover.

Conclusions

Indicators of a PA supportive environment show divergent trends to modify socioeconomic inequities in CHD . Built environment interventions should measure the effect on socioeconomic inequities.

SUBMITTER: Gullon P

PROVIDER: S-EPMC8200362 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Does a physical activity supportive environment ameliorate or exacerbate socioeconomic inequities in incident coronary heart disease?

Gullon Pedro P Bilal Usama U Hirsch Jana A JA Rundle Andrew G AG Judd Suzanne S Safford Monika M MM Lovasi Gina S GS

Journal of epidemiology and community health 20201214 7

<h4>Background</h4>Efforts to reduce socioeconomic inequities in cardiovascular disease include interventions to change the built environment. We aimed to explore whether socioeconomic inequities in coronary heart disease (CHD) incidence are ameliorated or exacerbated in environments supportive of physical activity (PA).<h4>Methods</h4>We used data from the Reasons for Geographic and Racial Differences in Stroke study, which recruited US residents aged 45 or older between 2003 and 2007. Our anal ...[more]

PMID: 33318134

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Project description:Aims/hypothesisSleep duration is a risk factor for incident diabetes mellitus and CHD. The primary aim of the present study was to investigate, in sex-specific analyses, the role of incident diabetes as the possible biological mechanism for the reported association between short/long sleep duration and incident CHD. Considering that diabetes is a major risk factor for CHD, we hypothesised that any association with sleep duration would not hold for cases of incident CHD occurring before incident diabetes ('non-diabetes CHD') but would hold true for cases of incident CHD following incident diabetes ('diabetes-CHD').MethodsA total of 6966 men and 9378 women aged 45-73 years from the Malmö Diet Cancer Study, a population-based, prospective cohort, who had answered questions on habitual sleep duration and did not have a history of prevalent diabetes or CHD were included in the analyses. Incident cases of diabetes and CHD were identified using national registers. Sex-specific Cox proportional hazards regression models were stratified by BMI and adjusted for known covariates of diabetes and CHD.ResultsMean follow-up times for incident diabetes (n = 1137/1016 [men/women]), incident CHD (n = 1170/578), non-diabetes CHD (n = 1016/501) and diabetes-CHD (n = 154/77) were 14.2-15.2 years for men, and 15.8-16.5 years for women. In men, short sleep duration (< 6 h) was associated with incident diabetes (HR 1.35, 95% CI 1.01, 1.80), CHD (HR 1.41, 95% CI 1.06, 1.89) and diabetes-CHD (HR 2.34, 95% CI 1.20, 4.55). Short sleep duration was not associated with incident non-diabetes CHD (HR 1.35, 95% CI 0.98, 1.87). Long sleep duration (≥ 9 h) was associated with incident diabetes (HR 1.37, 95% CI 1.03, 1.83), CHD (HR 1.33, 95% CI 1.01, 1.75) and diabetes-CHD (HR 2.10, 95% CI 1.11, 4.00). Long sleep duration was not associated with incident non-diabetes CHD (HR 1.33, 95% CI 0.98, 1.80). In women, short sleep duration was associated with incident diabetes (HR 1.53, 95% CI 1.16, 2.01), CHD (HR 1.46, 95% CI 1.03, 2.07) and diabetes-CHD (HR 2.88, 95% CI 1.37, 6.08). Short sleep duration was not associated with incident non-diabetes CHD (HR 1.29, 95% CI 0.86, 1.93).Conclusions/interpretationThe associations between sleep duration and incident CHD directly reflect the associations between sleep duration and incident diabetes. Incident diabetes may thus be the explanatory mechanism for the association between short and long sleep duration and incident CHD.

Project description:ImportanceAmerican Indian communities experience a high burden of coronary heart disease (CHD). Strategies are needed to identify individuals at risk and implement preventive interventions.ObjectiveTo investigate the association of blood DNA methylation (DNAm) with incident CHD using a large number of methylation sites (cytosine-phosphate-guanine [CpG]) in a single model.Design, setting, and participantsThis prospective study, including a discovery cohort (the Strong Heart Study [SHS]) and 4 additional cohorts (the Women's Health Initiative [WHI], the Framingham Heart Study [FHS], the Atherosclerosis Risk in Communities Study ([ARIC]-Black, and ARIC-White), evaluated 12 American Indian communities in 4 US states; African American women, Hispanic women, and White women throughout the US; White men and White women from Massachusetts; and Black men and women and White men and women from 4 US communities. A total of 2321 men and women (mean [SD] follow-up, 19.1 [9.2] years) were included in the SHS, 1874 women (mean [SD] follow-up, 15.8 [5.9] years) in the WHI, 2128 men and women (mean [SD] follow-up, 7.7 [1.8] years) in the FHS, 2114 men and women (mean [SD] follow-up, 20.9 [7.2] years) in the ARIC-Black, and 931 men and women (mean [SD] follow-up, 20.9 [7.2] years) in the ARIC-White. Data were collected from May 1989 to December 2018 and analyzed from February 2019 to May 2021.ExposureBlood DNA methylation.Main outcome and measureUsing a high-dimensional time-to-event elastic-net model for the association of 407 224 CpG sites with incident CHD in the SHS (749 events), this study selected the differentially methylated CpG positions (DMPs) selected in the SHS and evaluated them in the WHI (531 events), FHS (143 events), ARIC-Black (350 events), and ARIC-White (121 events) cohorts.ResultsThe median (IQR) age of participants in SHS was 55 (49-62) years, and 1359 participants (58.6%) were women. Elastic-net models selected 505 DMPs associated with incident CHD in the SHS beyond established risk factors, center, blood cell counts, and genetic principal components. Among those DMPs, 33 were commonly selected in 3 or 4 of the other cohorts and the pooled hazard ratios from the standard Cox models were significant at P < .05 for 10 of the DMPs. For example, the hazard ratio (95% CI) for CHD comparing the 90th and 10th percentiles of differentially methylated CpGs was 0.86 (0.78-0.95) for cg16604233 (tagged to COL11A2) and 1.23 (1.08-1.39) for cg09926486 (tagged to FRMD5). Some of the DMPs were consistent in the direction of the association; others showed associations in opposite directions across cohorts. Untargeted independent elastic-net models of CHD showed distinct DMPs, genes, and network of genes in the 5 cohorts.Conclusions and relevanceIn this multi-cohort study, blood-based DNAm findings supported an association between a complex blood epigenomic signature and CHD that was largely different across populations.

Project description:ObjectiveTo investigate socioeconomic inequities in the intervention and evaluation process of the GoActive school-based physical activity intervention and demonstrate a novel approach to evaluating intervention-related inequalities.DesignExploratory post-hoc secondary data analysis of trial data.SettingThe GoActive trial was run in secondary schools across Cambridgeshire and Essex (UK), between September 2016 and July 2018.Participants13-14 years old adolescents (n=2838, 16 schools).MethodsSocioeconomic inequities across six stages in the intervention and evaluation process were evaluated: (1) provision of and access to resources; (2) intervention uptake; (3) intervention effectiveness (accelerometer-assessed moderate-to-vigorous physical activity (MVPA)); (4) long-term compliance; (5) response in evaluation; and (6) impact on health. Data from self-report and objective measures were analysed by individual-level and school-level socioeconomic position (SEP) using a combination of classical hypothesis tests and multilevel regression modelling.ResultsStage: (1) There was no difference in the provision of physical activity resources by school-level SEP (eg, quality of facilities (0-3), low=2.6 (0.5); high=2.5 (0.4). (2) Students of low-SEP engaged significantly less with the intervention (eg, website access: low=37.2%; middle=45.4%; high=47.0%; p=0.001). (3) There was a positive intervention effect on MVPA in adolescents of low-SEP (3.13 min/day, 95% CI -1.27 to 7.54, but not middle/high (-1.49; 95% CI -6.54 to 3.57). (4) At 10 months post-intervention, this difference increased (low SEP: 4.90; 95% CI 0.09 to 9.70; middle/high SEP: -2.76; 95% CI -6.78 to 1.26). (5) There was greater non-compliance to evaluation measures among adolescents of low-SEP (eg, % accelerometer compliance (low vs high): baseline: 88.4 vs 92.5; post-intervention: 61.6 vs 69.2; follow-up: 54.5 vs 70.2. (6) The intervention effect on body mass index (BMI) z-score was more favourable in adolescents of low-SEP (low SEP: -0.10; 95% CI -0.19 to 0.00; middle/high: 0.03; 95% CI -0.05 to 0.12).ConclusionsThese analyses suggest the GoActive intervention had a more favourable positive effect on MVPA and BMI in adolescents of low-SEP, despite lower intervention engagement. However, differential response to evaluation measures may have biassed these conclusions. We demonstrate a novel way of evaluating inequities within young people's physical activity intervention evaluations.Trial registration numberISRCTN31583496.

Dataset Information

Does a physical activity supportive environment ameliorate or exacerbate socioeconomic inequities in incident coronary heart disease?

Background

Methods

Conclusions

Publications

Does a physical activity supportive environment ameliorate or exacerbate socioeconomic inequities in incident coronary heart disease?

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