Abstract

SummaryBackgroundTargeted obesity prevention policies would benefit from the identification of population groups with the highest risk of weight gain. The relative importance of adult age, sex, ethnicity, geographical region, and degree of social deprivation on weight gain is not known. We aimed to identify high-risk groups for changes in weight and BMI using electronic health records (EHR).MethodsIn this longitudinal, population-based cohort study we used linked EHR data from 400 primary care practices (via the Clinical Practice Research Datalink) in England, accessed via the CALIBER programme. Eligible participants were aged 18–74 years, were registered at a general practice clinic, and had BMI and weight measurements recorded between Jan 1, 1998, and June 30, 2016, during the period when they had eligible linked data with at least 1 year of follow-up time. We calculated longitudinal changes in BMI over 1, 5, and 10 years, and investigated the absolute risk and odds ratios (ORs) of transitioning between BMI categories (underweight, normal weight, overweight, obesity class 1 and 2, and severe obesity [class 3]), as defined by WHO. The associations of demographic factors with BMI transitions were estimated by use of logistic regression analysis, adjusting for baseline BMI, family history of cardiovascular disease, use of diuretics, and prevalent chronic conditions.FindingsWe included 2 092 260 eligible individuals with more than 9 million BMI measurements in our study. Young adult age was the strongest risk factor for weight gain at 1, 5, and 10 years of follow-up. Compared with the oldest age group (65–74 years), adults in the youngest age group (18–24 years) had the highest OR (4·22 [95% CI 3·86–4·62]) and greatest absolute risk (37% vs 24%) of transitioning from normal weight to overweight or obesity at 10 years. Likewise, adults in the youngest age group with overweight or obesity at baseline were also at highest risk to transition to a higher BMI category; OR 4·60 (4·06–5·22) and absolute risk (42% vs 18%) of transitioning from overweight to class 1 and 2 obesity, and OR 5·87 (5·23–6·59) and absolute risk (22% vs 5%) of transitioning from class 1 and 2 obesity to class 3 obesity. Other demographic factors were consistently less strongly associated with these transitions; for example, the OR of transitioning from normal weight to overweight or obesity in people living in the most socially deprived versus least deprived areas was 1·23 (1·18–1·27), for men versus women was 1·12 (1·08–1·16), and for Black individuals versus White individuals was 1·13 (1·04–1·24). We provide an open access online risk calculator, and present high-resolution obesity risk charts over a 1-year, 5-year, and 10-year follow-up period.InterpretationA radical shift in policy is required to focus on individuals at the highest risk of weight gain (ie, young adults aged 18–24 years) for individual-level and population-level prevention of obesity and its long-term consequences for health and health care.FundingThe British Hearth Foundation, Health Data Research UK, the UK Medical Research Council, and the National Institute for Health Research.

Highlights

  • Adult obesity prevention policies, which are largely untargeted, have had limited success globally,[1,2] and the high prevalence of obesity is predicted to increase substantially over the decade.[3,4] Population-wide approaches to obesity prevention could be complemented by new targeted approaches if population groups with the highest risk of weight gain could be identified using readily available information in national public health systems.[1]

  • We identified 2 396 540 individuals with linked electronic health records (EHR) data and at least one BMI measurement recorded between 1998 and 2016 in England, of whom 2 092 260 individuals aged [18–74] years with at least one valid BMI measurement were included in the analysis

  • We found that the association between Index of Multiple Deprivation (IMD) and transition to a higher BMI category was even more pronounced among individuals in the [18,19,20,21,22,23,24] years age group compared with older age groups

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Summary

Introduction

Adult obesity prevention policies, which are largely untargeted, have had limited success globally,[1,2] and the high prevalence of obesity is predicted to increase substantially over the decade.[3,4] Population-wide approaches to obesity prevention could be complemented by new targeted approaches if population groups with the highest risk of weight gain could be identified using readily available information in national public health systems.[1]. Articles and Biostatistics, School of Public Health, Imperial College. London, UK (K Tsilidis PhD); Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece (K Tsilidis); Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece (Prof P Lagiou PhD, L Wen PhD); Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA (Prof P Lagiou); Hellenic Health. Foundation, Athens, Greece (G Misirli PhD); Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College. London, UK (Prof R L Batterham); MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK (Prof N Wareham PhD, Prof C Langenberg PhD); Computational Medicine, Berlin Institute of Health, Charité–University Medicine Berlin, Berlin, Germany (Prof C Langenberg)

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