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      Association of BMI with overall and cause-specific mortality: a population-based cohort study of 3·6 million adults in the UK

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          Summary

          Background

          BMI is known to be strongly associated with all-cause mortality, but few studies have been large enough to reliably examine associations between BMI and a comprehensive range of cause-specific mortality outcomes.

          Methods

          In this population-based cohort study, we used UK primary care data from the Clinical Practice Research Datalink (CPRD) linked to national mortality registration data and fitted adjusted Cox regression models to examine associations between BMI and all-cause mortality, and between BMI and a comprehensive range of cause-specific mortality outcomes (recorded by International Classification of Diseases, 10th revision [ICD-10] codes). We included all individuals with BMI data collected at age 16 years and older and with subsequent follow-up time available. Follow-up began at whichever was the latest of: start of CPRD research-standard follow up, the 5-year anniversary of the first BMI record, or on Jan 1, 1998 (start date for death registration data); follow-up ended at death or on March 8, 2016. Fully adjusted models were stratified by sex and adjusted for baseline age, smoking, alcohol use, diabetes, index of multiple deprivation, and calendar period. Models were fitted in both never-smokers only and the full study population. We also did an extensive range of sensitivity analyses. The expected age of death for men and women aged 40 years at baseline, by BMI category, was estimated from a Poisson model including BMI, age, and sex.

          Findings

          3 632 674 people were included in the full study population; the following results are from the analysis of never-smokers, which comprised 1 969 648 people and 188 057 deaths. BMI had a J-shaped association with overall mortality; the estimated hazard ratio per 5 kg/m 2 increase in BMI was 0·81 (95% CI 0·80–0·82) below 25 kg/m 2 and 1·21 (1·20–1·22) above this point. BMI was associated with all cause of death categories except for transport-related accidents, but the shape of the association varied. Most causes, including cancer, cardiovascular diseases, and respiratory diseases, had a J-shaped association with BMI, with lowest risk occurring in the range 21–25 kg/m 2. For mental and behavioural, neurological, and accidental (non-transport-related) causes, BMI was inversely associated with mortality up to 24–27 kg/m 2, with little association at higher BMIs; for deaths from self-harm or interpersonal violence, an inverse linear association was observed. Associations between BMI and mortality were stronger at younger ages than at older ages, and the BMI associated with lowest mortality risk was higher in older individuals than in younger individuals. Compared with individuals of healthy weight (BMI 18·5–24·9 kg/m 2), life expectancy from age 40 years was 4·2 years shorter in obese (BMI ≥30·0 kg/m 2) men and 3·5 years shorter in obese women, and 4·3 years shorter in underweight (BMI <18·5 kg/m 2) men and 4·5 years shorter in underweight women. When smokers were included in analyses, results for most causes of death were broadly similar, although marginally stronger associations were seen among people with lower BMI, suggesting slight residual confounding by smoking.

          Interpretation

          BMI had J-shaped associations with overall mortality and most specific causes of death; for mental and behavioural, neurological, and external causes, lower BMI was associated with increased mortality risk.

          Funding

          Wellcome Trust.

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          Most cited references13

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          Impact of Cardiorespiratory Fitness on All-Cause and Disease-Specific Mortality: Advances Since 2009

          Cardiorespiratory fitness (CRF) has been one of the most widely examined physiological variables, particularly as it relates to functional capacity and human performance. Over the past three decades, CRF has emerged as a strong, independent predictor of all-cause and disease-specific mortality. The evidence supporting the prognostic use of CRF is so powerful that the American Heart Association recently advocated for the routine assessment of CRF as a clinical vital sign. Interestingly, the continuity of evidence of the inverse relationship between CRF and mortality over the past decade exists despite a wide variation of methods used to assess CRF in these studies, ranging from the gold-standard method of directly measured maximal oxygen uptake (VO2max) during cardiopulmonary exercise testing to estimation from exercise tests and non-exercise prediction equations. This review highlights new knowledge and the primary advances since 2009, with specific reference to the impact variations in CRF have on all-cause and disease-specific mortality.
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            What is the difference between missing completely at random and missing at random?

            The terminology describing missingness mechanisms is confusing. In particular the meaning of ‘missing at random’ is often misunderstood, leading researchers faced with missing data problems away from multiple imputation, a method with considerable advantages. The purpose of this article is to clarify how ‘missing at random’ differs from ‘missing completely at random’ via an imagined dialogue between a clinical researcher and statistician.
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              Body-mass index and cancer mortality in the Asia-Pacific Cohort Studies Collaboration: pooled analyses of 424,519 participants.

              Excess bodyweight is an established risk factor for several types of cancer, but there are sparse data from Asian populations, where the proportion of overweight and obese individuals is increasing rapidly and adiposity can be substantially greater for the same body-mass index (BMI) compared with people from Western populations. We examined associations of adult BMI with cancer mortality (overall and for 20 cancer sites) in geographic populations from Asia and from Australia and New Zealand (ANZ), within the Asia-Pacific Cohort Studies Collaboration, by use of Cox regression analysis. Pooled data from 39 cohorts (recruitment 1961-99, median follow-up 4 years) were analysed for 424,519 participants (77% Asian; 41% female; mean recruitment age 48 years) with individual data on BMI. After excluding those with follow-up of less than 3 years, 4872 cancer deaths occurred in 401,215 participants. Hazard ratios for cancer sites with increased mortality risk in obese (BMI > or = 30 kg/m(2)) compared with normal weight participants (BMI 18.5-24.9 kg/m(2)) were: 1.21 (95% CI 1.09-1.36) for all-cause cancer (excluding lung and upper aerodigestive tract), 1.50 (1.13-1.99) for colon, 1.68 (1.06-2.67) for rectum, 1.63 (1.13-2.35) for breast in women 60 years or older, 2.62 (1.57-4.37) for ovary, 4.21 (1.89-9.39) for cervix, 1.45 (0.97-2.19) for prostate, and 1.66 (1.03-2.68) for leukaemia (all after left censoring at 3 years). The increased risk associated with a 5-unit increase in BMI for those with BMI of 18.5 kg/m(2) or higher was 1.09 (95% CI 1.04-1.14) for all cancers (excluding lung and upper aerodigestive tract). There was little evidence of regional differences in relative risk of cancer with higher BMI, apart from cancers of the oropharynx and larynx, where the association was inverse in ANZ and absent in Asia. Overweight and obese individuals in populations across the Asia-Pacific region have a significantly increased risk of mortality from cancer. Strategies to prevent individuals from becoming overweight and obese in Asia are needed to reduce the burden of cancer that is expected if the obesity epidemic continues. National Health and Medical Research Council of Australia, Health Research Council of New Zealand, and Pfizer Inc. 2010 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                Journal
                Lancet Diabetes Endocrinol
                Lancet Diabetes Endocrinol
                The Lancet. Diabetes & Endocrinology
                The Lancet, Diabetes & Endocrinology
                2213-8587
                2213-8595
                1 December 2018
                December 2018
                : 6
                : 12
                : 944-953
                Affiliations
                [a ]Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
                [b ]Department of Community Medicine, The Arctic University of Norway, Tromsø, Norway
                Author notes
                [* ]Correspondence to: Dr Krishnan Bhaskaran, London School of Hygiene & Tropical Medicine, London WC1E 7T, UK krishnan.bhaskaran@ 123456lshtm.ac.uk
                Article
                S2213-8587(18)30288-2
                10.1016/S2213-8587(18)30288-2
                6249991
                30389323
                dde9e623-93ec-47b3-a61a-3948a8f05985
                © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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