Dataset Information

Sex Differences in the Association Between Measures of General and Central Adiposity and the Risk of Myocardial Infarction: Results From the UK Biobank.

ABSTRACT:

Background

There are substantial differences in the distribution of adipose tissue between women and men. We assessed the sex-specific relationships and their differences between measures of general and central adiposity and the risk of incident myocardial infarction (MI).

Methods and results

Between 2006 and 2010, the UK Biobank recruited over 500 000 participants aged 40 to 69 years across the United Kingdom. During 7 years of follow-up, 5710 cases of MI (28% women) were recorded among 265 988 women and 213 622 men without a history of cardiovascular disease at baseline. Cox regression models yielded adjusted hazard ratios for MI associated with body mass index, waist circumference, waist-to-hip ratio, and waist-to-height ratio. There was an approximate log-linear relationship between measures of general and central adiposity and the risk of MI in both sexes. A 1-SD higher in body mass index, waist circumference, waist-to-hip ratio, and waist-to-height ratio, respectively, were associated with hazard ratios (confidence intervals) for MI of 1.22 (1.17; 1.28), 1.35 (1.28; 1.42), 1.49 (1.39; 1.59), and 1.34 (1.27; 1.40) in women and of 1.28 (1.23; 1.32), 1.28 (1.23; 1.33), 1.36 (1.30; 1.43), and 1.33 (1.28; 1.38) in men. The corresponding women-to-men ratios of hazard ratios were 0.96 (0.91; 1.02), 1.07 (1.00; 1.14), 1.15 (1.06; 1.24), and 1.03 (0.97; 1.09).

Conclusions

Although general and central adiposity measures each have profound deleterious effects on the risk of MI in both sexes, a higher waist circumference and waist-to-hip ratio conferred a greater excess risk of MI in women than in men. Waist-to-hip ratio was more strongly associated with the risk of MI than body mass index in both sexes, especially in women.

SUBMITTER: Peters SAE

PROVIDER: S-EPMC5866342 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Publications

Sex Differences in the Association Between Measures of General and Central Adiposity and the Risk of Myocardial Infarction: Results From the UK Biobank.

Peters Sanne A E SAE Bots Sophie H SH Woodward Mark M

Journal of the American Heart Association 20180228 5

<h4>Background</h4>There are substantial differences in the distribution of adipose tissue between women and men. We assessed the sex-specific relationships and their differences between measures of general and central adiposity and the risk of incident myocardial infarction (MI).<h4>Methods and results</h4>Between 2006 and 2010, the UK Biobank recruited over 500 000 participants aged 40 to 69 years across the United Kingdom. During 7 years of follow-up, 5710 cases of MI (28% women) were recorde ...[more]

PMID: 29490971

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Project description:BackgroundThe direct effects of general adiposity (body mass index (BMI)) and central adiposity (waist-to-hip-ratio (WHR)) on circulating lipoproteins, lipids, and metabolites are unknown.MethodsWe used new metabolic data from UK Biobank (N=109,532, a five-fold higher N over previous studies). EDTA-plasma was used to quantify 249 traits with nuclear-magnetic-resonance spectroscopy including subclass-specific lipoprotein concentrations and lipid content, plus pre-glycemic and inflammatory metabolites. We used univariable and multivariable two-stage least-squares regression models with genetic risk scores for BMI and WHR as instruments to estimate total (unadjusted) and direct (mutually-adjusted) effects of BMI and WHR on metabolic traits; plus effects on statin use and interaction by sex, statin use, and age (proxy for medication use).FindingsHigher BMI decreased apolipoprotein B and low-density lipoprotein cholesterol (LDL-C) before and after WHR-adjustment, whilst BMI increased triglycerides only before WHR-adjustment. These effects of WHR were larger and BMI-independent. Direct effects differed markedly by sex, e.g., triglycerides increased only with BMI among men, and only with WHR among women. Adiposity measures increased statin use and showed metabolic effects which differed by statin use and age. Among the youngest (38-53y, statins-5%), BMI and WHR (per-SD) increased LDL-C (total effects: 0.04-SD, 95%CI=-0.01,0.08 and 0.10-SD, 95%CI=0.02,0.17 respectively), but only WHR directly. Among the oldest (63-73y, statins-29%), BMI and WHR directly lowered LDL-C (-0.19-SD, 95%CI=-0.27,-0.11 and -0.05-SD, 95%CI=-0.16,0.06 respectively).InterpretationExcess adiposity likely raises atherogenic lipid and metabolite levels exclusively via adiposity stored centrally, particularly among women. Apparent effects of adiposity on lowering LDL-C are likely explained by an effect of adiposity on statin use.FundingUK Medical Research Council; British Heart Foundation; Novo Nordisk; National Institute for Health Research; Wellcome Trust; Cancer Research UK.

Project description:Personality is a strong determinant for several health-related behaviours and has been linked to the development of cardiovascular diseases. However, the reports of personality's mediating role have been inconsistent with no data available from large population-based cohorts. The study aimed to create proxies for the Big Five personality traits, extraversion, agreeableness, conscientiousness, openness and neuroticism, to examine the longitudinal relationship between personality and myocardial infarction in the UK Biobank. The study sample comprised of 484,205 participants (55% female, 45% male, mean age 56.4 ± 8.1 years) from UK Biobank cohort with a mean follow-up of 7 years. The personality proxies sociability, warmth, diligence, curiosity and nervousness were created using self-reported data on psychological factors, mental health and social support, to match the facets of the Big Five traits. As neuroticism is the only Big Five personality trait available in the UK Biobank, it was included to validate the personality proxies. Myocardial infarction outcome information was collected from hospital records, death registries or was self-reported. Logistic regression and Cox proportional hazard regression were used to estimate odds ratio (OR) and hazard ratios (HR), respectively with 95% confidence intervals (CI) adjusted for demographics (age, sex, socioeconomic status, ethnicity), health-related factors (BMI, diabetes, systolic and diastolic blood pressure) and lifestyle factors (alcohol intake, smoking, and moderate-to-vigorous physical activity). Diligence was found to be significantly associated with lower prevalent myocardial infarction [OR: 0.87; (CI 0.84-0.89)] and lower incident myocardial infarction [HR: 0.88; (CI 0.85-0.92)]. Sociability was also protective against prevalent [OR: 0.89; (CI 0.87-0.92)] and incident [HR: 0.90; (CI 0.87-0.93)] myocardial infarction. Conversely, nervousness inferred a higher risk for both prevalent [OR: 1.10; (CI 1.08-1.12)] and incident [HR: 1.07; (CI 1.04-1.09)] myocardial infarction during follow-up. Sex-stratified analyses revealed that nervousness significantly increases the risk for incident myocardial infarction among women [HR: 1.13; (CI 1.08-1.19)] compared to men [HR: 1.05; (CI 1.02-1.08)]. By using our created proxies, we were able to investigate the impact of personality on the development of myocardial infarction. Persons with higher levels of diligence and sociability mimicking predominantly conscientiousness and extraversion personalities respectively are less likely to experience myocardial infarction, while personalities predominantly characterised by nervousness pose higher risk for developing myocardial infarction. These initial findings invite further validation of the use of the personality proxies in UK Biobank cohort.

Dataset Information

Sex Differences in the Association Between Measures of General and Central Adiposity and the Risk of Myocardial Infarction: Results From the UK Biobank.

Background

Methods and results

Conclusions

Publications

Sex Differences in the Association Between Measures of General and Central Adiposity and the Risk of Myocardial Infarction: Results From the UK Biobank.

Similar Datasets

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