The role of health-related behavioural factors in accounting for inequalities in coronary heart disease risk by education and area deprivation: prospective study of 1.2 million UK women

Floud, Sarah; Balkwill, Angela; Moser, Kath; Reeves, Gillian; Green, Jane; Beral, Valerie; Cairns, Benjamin J.

doi:10.1186/s12916-016-0687-2

Cited by 38 publications

(34 citation statements)

References 49 publications

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“…More recent studies focusing on the mediation of the association between education and CHD showed that 21–57% of the effect was accounted for behavioral and biological risk factors 10 , 18 , 20 . These and other studies pointed to smoking, BMI, hypertension, PA, lipid profile, and diabetes as mediators of the association between education and CVD incidence 10 , 11 , 13 , 15 , 16 , 20 , 24 , 26 .…”

Section: Discussionmentioning

confidence: 67%

The association between education and cardiovascular disease incidence is mediated by hypertension, diabetes, and body mass index

Dégano

Marrugat

Grau

et al. 2017

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Education and cardiovascular disease (CVD) are inversely associated but the mediating factors have not been totally elucidated. Our aim was to analyze the mediating role of modifiable risk factors. Cohort study using the REGICOR population cohorts. Participants without previous CVD were included (n = 9226). Marginal structural models were used to analyze the association between education and CVD incidence at 6 years of follow-up. Mediation by modifiable risk factors (diabetes, dyslipidemia, hypertension, smoking, body mass index, and physical activity) was assessed using the counterfactual framework. Participants with a university degree had a CVD incidence hazard ratio (HR) of 0.51 (95% confidence interval (CI) = 0.30, 0.85), compared to those with primary or lower education. Only hypertension, BMI, and diabetes mediated the association between education and CVD incidence, accounting for 26% of the association (13.9, 6.9, and 5.2%, respectively). Sensitivity analyses showed that hypertension was the strongest mediator (average causal mediation effect [95% CI] = increase of 2170 days free of CVD events [711, 4520]). The association between education and CVD incidence is partially mediated by hypertension, BMI, and diabetes. Interventions to decrease the prevalence of these risk factors could contribute to diminish the CVD inequalities associated with educational level.

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Section: Discussionmentioning

confidence: 67%

The association between education and cardiovascular disease incidence is mediated by hypertension, diabetes, and body mass index

Dégano

Marrugat

Grau

et al. 2017

Sci Rep

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“…Person-years were calculated from the date the baseline questionnaire was completed to first hospital record of any stroke (ICD codes I60–I64), death, emigration, or March 31, 2015 (the latest date when complete information was available), whichever was earliest. Time in study was the underlying time variable, and analyses were stratified by year of birth (1930 or before, 1931 to 1949 in single years, 1950 or later) and of completion of the baseline questionnaire (2000 or before, 2001, 2002, 2003, 2004 or later) and adjusted for region of residence (10 geographical areas in the United Kingdom), socioeconomic status (5 levels of the Townsend index 10 ), educational attainment (tertiary, secondary/technical, no formal qualifications 11 ), and when appropriate for smoking (never, past, current <5, 5–9, 10–14, 15–19, 20–24, ≥25 cigarettes/d), alcohol consumption (none, ≤6, 7–14, ≥15 drinks/wk), body mass index (<25, 25–29.9, ≥30 kg/m 2 ), physical activity (thirds of excess metabolic equivalents), and menopausal hormone therapy (never, past, current). For adjustment variables, missing values were assigned to an unknown category and represented <5% of the data in every variable.…”

Section: Methodsmentioning

confidence: 99%

Differences in risk factors for 3 types of stroke

et al. 2018

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Objective To compare associations of behavioral and related factors for incident subarachnoid hemorrhage and intracerebral hemorrhage and ischemic stroke. MethodsA total of 712,433 Million Women Study participants without prior stroke, heart disease, or cancer reported behavioral and related factors at baseline (1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007) and were followed up by record linkage to national hospital admission and death databases. Cox regression yielded adjusted relative risks (RRs) by type of stroke. Heterogeneity was assessed with χ 2 tests. When appropriate, meta-analyses were done of published prospective studies. ResultsAfter 12.9 (SD 2.6) years of follow-up, 8,128 women had an incident ischemic stroke, 2,032 had intracerebral hemorrhage, and 1,536 had subarachnoid hemorrhage. In women with diabetes mellitus, the risk of ischemic stroke was substantially increased (RR 2.01, 95% confidence interval [CI] 1.84-2.20), risk of intracerebral hemorrhage was increased slightly (RR 1.31, 95% CI 1.04-1.65), but risk of subarachnoid hemorrhage was reduced (RR 0.43, 95% CI 0.26-0.69) (heterogeneity by stroke type, p < 0.0001). Stroke incidence was greater in women who rated their health as poor/fair compared to those who rated their health as excellent/good (RR 1.36, 95% CI 1.30-1.42). Among 565,850 women who rated their heath as excellent/good, current smokers were at an increased risk of all 3 stroke types, (although greater for subarachnoid hemorrhage [≥15 cigarettes/d vs never smoker, RR 4.75, 95% CI 4.12-5.47] than for intracerebral hemorrhage [RR 2.30, or ischemic stroke [RR 2.50, 95% CI 2.29-2.72]; heterogeneity p < 0.0001). Obesity was associated with an increased risk of ischemic stroke and a decreased risk of hemorrhagic stroke (heterogeneity p < 0.0001). Metaanalyses confirmed the associations and the heterogeneity across the 3 types of stroke. ConclusionClassic risk factors for stroke have considerably different effects on the 3 main pathologic types of stroke.

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“…To ensure that analyses compared dementia detection rates in women who were as similar as possible in all other respects, all analyses were routinely stratified by single year of birth (≤1930, 1931…1949, 1950 and later) and by calendar year at recruitment (1996,1997,1998,1999,2000,2001 and later) or, for the diet analyses, at the 3-year resurvey. All analyses were also adjusted for other factors at recruitment: region of residence at baseline (Scotland and 9 areas in England representing NHS Regional Heath Authorities); education (no qualifications, any qualification) 21 ; area deprivation (tertiles based on the Townsend Index 22 ); height (<155, 155-164, 165+ cm); smoking (never, past, current <10, 10-19, 20+ cigarettes per day); alcohol consumption (0, <7, 7-14, 15+ drinks per week); and use of menopausal hormones (never, past, current).…”

Section: Statistical Analysesmentioning

confidence: 99%

Body mass index, diet, physical inactivity, and the incidence of dementia in 1 million UK women

et al. 2020

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ObjectiveTo help determine whether midlife obesity is a cause of dementia and whether low body mass index (BMI), low caloric intake, and physical inactivity are causes or merely consequences of the gradual onset of dementia by recording these factors early in a large 20-year prospective study and relating them to dementia detection rates separately during follow-up periods of <5, 5 to 9, 10 to 14, and 15+ years.MethodsA total of 1,136,846 UK women, mean age 56 (SD 5) years, were recruited in 1996 to 2001 and asked about height, weight, caloric intake, and inactivity. They were followed up until 2017 by electronic linkage to National Health Service records, detecting hospital admissions with mention of dementia. Cox regression yielded adjusted rate ratios (RRs) for first dementia detection during particular follow-up periods.ResultsFifteen years after the baseline survey, only 1% were lost to follow-up, and 89% remained alive with no detected dementia, of whom 18,695 had dementia detected later, at a mean age of 77 (SD 4) years. Dementia detection during years 15+ was associated with baseline obesity (BMI 30+ vs 20–24 kg/m2: RR 1.21, 95% confidence interval 1.16–1.26, p < 0.0001) but not clearly with low BMI, low caloric intake, or inactivity at baseline. The latter 3 factors were associated with increased dementia rates during the first decade, but these associations weakened substantially over time, approaching null after 15 years.ConclusionsMidlife obesity may well be a cause of dementia. In contrast, behavioral changes due to preclinical disease could largely or wholly account for associations of low BMI, low caloric intake, and inactivity with dementia detection during the first decade of follow-up.

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The role of health-related behavioural factors in accounting for inequalities in coronary heart disease risk by education and area deprivation: prospective study of 1.2 million UK women

Cited by 38 publications

References 49 publications

The association between education and cardiovascular disease incidence is mediated by hypertension, diabetes, and body mass index

The association between education and cardiovascular disease incidence is mediated by hypertension, diabetes, and body mass index

Differences in risk factors for 3 types of stroke

Body mass index, diet, physical inactivity, and the incidence of dementia in 1 million UK women

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