ArticleInternational journal of epidemiology2013
Within-person variability in calculated risk factors: comparing the aetiological association of adiposity ratios with risk of coronary heart disease.
Article in International journal of epidemiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 5 of them syntheses that pooled it.
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Who cites it
9 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Blood pressure and risk of venous thromboembolism: a cohort analysis of 5.5 million UK adults and Mendelian randomization studies.Cardiovascular research · 2023Pooled it
- Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction: An Individual-Participant-Data Meta-Analysis.American journal of epidemiology · 2017Pooled it
- Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents.Lancet (London, England) · 2016 · on this mapPooled it
- Usual Blood Pressure and Risk of New-Onset Diabetes: Evidence From 4.1 Million Adults and a Meta-Analysis of Prospective Studies.Journal of the American College of Cardiology · 2015Pooled it
- Usual blood pressure, peripheral arterial disease, and vascular risk: cohort study of 4.2 million adults.BMJ (Clinical research ed.) · 2015Pooled it
- Independent relevance of adiposity measures to coronary heart disease risk among 0.5 million adults in UK Biobank.International journal of epidemiology · 2023Article
- Cross-sectional associations between central and general adiposity with albuminuria: observations from 400,000 people in UK Biobank.International journal of obesity (2005) · 2020Article
- J-shaped relationship between habitual coffee consumption and 10-year (2002-2012) cardiovascular disease incidence: methodological issues.European journal of nutrition · 2017Article
- Usual blood pressure, atrial fibrillation and vascular risk: evidence from 4.3 million adults.International journal of epidemiology · 2017Article
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Authors and funding
4 authors.
Funding
Abstract
backgroundWithin-person variability in measured values of a risk factor can bias its association with disease. We investigated the extent of regression dilution bias in calculated variables and its implications for comparing the aetiological associations of risk factors.
methodsUsing a numerical illustration and repeats from 42,300 individuals (12 cohorts), we estimated regression dilution ratios (RDRs) in calculated risk factors [body-mass index (BMI), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR)] and in their components (height, weight, waist circumference, and hip circumference), assuming the long-term average exposure to be of interest. Error-corrected hazard ratios (HRs) for risk of coronary heart disease (CHD) were compared across adiposity measures per standard-deviation (SD) change in: (i) baseline and (ii) error-corrected levels.
resultsRDRs in calculated risk factors depend strongly on the RDRs, correlation, and comparative distributions of the components of these risk factors. For measures of adiposity, the RDR was lower for WHR [RDR: 0.72 (95% confidence interval 0.65-0.80)] than for either of its components [waist circumference: 0.87 (0.85-0.90); hip circumference: 0.90 (0.86-0.93) or for BMI: 0.96 (0.93-0.98) and WHtR: 0.87 (0.85-0.90)], predominantly because of the stronger correlation and more similar distributions observed between waist circumference and hip circumference than between height and weight or between waist circumference and height. Error-corrected HRs for BMI, waist circumference, WHR, and WHtR, were respectively 1.24, 1.30, 1.44, and 1.32 per SD change in baseline levels of these variables, and 1.24, 1.27, 1.35, and 1.30 per SD change in error-corrected levels.
conclusionsThe extent of within-person variability relative to between-person variability in calculated risk factors can be considerably larger (or smaller) than in its components. Aetiological associations of risk factors should be compared through the use of error-corrected HRs per SD change in error-corrected levels of these risk factors.
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