Identifying adults at high-risk for change in weight and BMI in England: a longitudinal, large-scale, population-based cohort study using electronic health records

Katsoulis, M. et al | 2021 | Identifying adults at high-risk for change in weight and BMI in England: a longitudinal, large-scale, population-based cohort study using electronic health records | The Lancet Diabetes & Endocrinology | https://doi.org/10.1016/S2213-8587(21)00207-2

The researchers behind this paper use electronic health records of over 2 million people to address four research objectives:

(1) to test the extent to which temporal trends in mean BMI changes between 1998 and 2016 are replicated between EHRs and survey methods

 (2) to compare the extent and distribution of BMI changes across age groups and BMI categories

(3) to estimate the associations between age, sex, degree of social deprivation, ethnicity, and geographical region with transitions across BMI categories

(4) to produce a risk calculator (both online and in chart-form), showing how these risk factors combine to identify groups at a high risk of transitioning to higher BMI categories.

Their findings show that young adults (aged 18–24 years) had a markedly greater risk for transitioning to higher BMI categories than did older age groups (ie, those aged 65–74 years). Compared with age, the researchers found smaller additional contributions to the risk of BMI change, including being male, living in socially deprived neighbourhoods, and being from a Black ethnic background. . The authors provide the first estimates of the risks of transitioning between underweight, normal weight, overweight, and obesity BMI categories at 1, 5, and 10 years (risk charts and an online tool). They also show the value of using longitudinal population-based EHRs to identify and monitor specific population groups at risk of weight gain (Source: Katsoulis et al, 2021).

Summary

Background

Targeted 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).

Methods

In 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.

Findings

We 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 per cent  CI 3·86–4·62]) and greatest absolute risk (37 per cent vs 24 per cent ) 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 per cent  vs 18 per cent ) of transitioning from overweight to class 1 and 2 obesity, and OR 5·87 (5·23–6·59) and absolute risk (22 per cent  vs 5 per cent ) 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.

Interpretation

A 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.

Identifying adults at high-risk for change in weight and BMI in England: a longitudinal, large-scale, population-based cohort study using electronic health records

Diabetes: BMI cut-offs designed to trigger action are too high for some ethnic populations

The findings of a study published in The Lancet Diabetes & Endocrinology indicate that there should be revisions of ethnicity-specific BMI cutoffs to ensure that minority ethnic populations are provided with appropriate clinical surveillance to optimise the prevention, early diagnosis, and timely management of type 2 diabetes.

Summary

Background

National and global recommendations for BMI cutoffs to trigger action to prevent obesity-related complications like type 2 diabetes among non-White populations are questionable. We aimed to prospectively identify ethnicity-specific BMI cutoffs for obesity based on the risk of type 2 diabetes that are risk-equivalent to the BMI cutoff for obesity among White populations (≥30 kg/m2).

Methods

In this population-based cohort study, we used electronic health records across primary care (Clinical Practice Research Datalink) linked to secondary care records (Hospital Episodes Statistics) from a network of general practitioner practices in England. Eligible participants were aged 18 years or older, without any past or current diagnosis of type 2 diabetes, had a BMI of 15·0–50·0 kg/m2 and complete ethnicity data, were registered with a general practitioner practice in England at any point between Sept 1, 1990, and Dec 1, 2018, and had at least 1 year of follow-up data. Patients with type 2 diabetes were identified by use of a CALIBER phenotyping algorithm. Self-reported ethnicity was collapsed into five main categories. Age-adjusted and sex-adjusted negative binomial regression models, with fractional polynomials for BMI, were fitted with incident type 2 diabetes and ethnicity data.

Findings

1 472 819 people were included in our study, of whom 1 333 816 (90·6%) were White, 75 956 (5·2%) were south Asian, 49 349 (3·4%) were Black, 10 934 (0·7%) were Chinese, and 2764 (0·2%) were Arab. After a median follow-up of 6·5 years (IQR 3·2–11·2), 97 823 (6·6%) of 1 472 819 individuals were diagnosed with type 2 diabetes. For the equivalent age-adjusted and sex-adjusted incidence of type 2 diabetes at a BMI of 30·0 kg/m2 in White populations, the BMI cutoffs were 23·9 kg/m2 (95% CI 23·6–24·0) in south Asian populations, 28·1 kg/m2 (28·0–28·4) in Black populations, 26·9 kg/m2 (26·7–27·2) in Chinese populations, and 26·6 kg/m2 (26·5–27·0) in Arab populations.

Full paper Ethnicity-specific BMI cutoffs for obesity based on type 2 diabetes risk in England: a population-based cohort study available from The Lancet Diabetes & Endocrinology

See also:

BMJ Diabetes: BMI cut-offs designed to trigger action are too high for some ethnic populations, say researchers

Associations between body-mass index and COVID-19 severity in 6·9 million people in England: a prospective, community-based, cohort study

Gao, M. et al | 2021| Associations between body-mass index and COVID-19 severity in 6·9 million people in England: a prospective, community-based, cohort study | The Lancet Diabetes & Endocrinology | DOI: https://doi.org/10.1016/S2213-8587(21)00089-9

The authors of this paper, report the results of a large, representative community-based cohort study of 6·9 million people in England, UK, to thoroughly characterise the association between BMI and severe COVID-19 outcomes and to explore interactions with demographic characteristics and other known risk factors.

Their findings suggest that the hazard ratio of severe outcomes from COVID-19 (i.e. admission to hospital, admission to ICU, or death) increase progressively above a BMI of 23 kg/m2, which is not attributable to excess risks of related diseases such as type 2 diabetes. We found that BMI is a greater risk factor for younger people (aged 20 to 39 years) than for older people (more than or equal to 80 years), and for Black people than for White people.

Summary

Background

Obesity is a major risk factor for adverse outcomes after infection with SARS-CoV-2. We aimed to examine this association, including interactions with demographic and behavioural characteristics, type 2 diabetes, and other health conditions.

Methods

In this prospective, community-based, cohort study, we used de-identified patient-level data from the QResearch database of general practices in England, UK. We extracted data for patients aged 20 years and older who were registered at a practice eligible for inclusion in the QResearch database between Jan 24, 2020 (date of the first recorded infection in the UK) and April 30, 2020, and with available data on BMI. Data extracted included demographic, clinical, clinical values linked with Public Health England’s database of positive SARS-CoV-2 test results, and death certificates from the Office of National Statistics. Outcomes, as a proxy measure of severe COVID-19, were admission to hospital, admission to an intensive care unit (ICU), and death due to COVID-19. We used Cox proportional hazard models to estimate the risk of severe COVID-19, sequentially adjusting for demographic characteristics, behavioural factors, and comorbidities.

Findings

Among 6 910 695 eligible individuals (mean BMI 26·78 kg/m2 [SD 5·59]), 13 503 (0·20%) were admitted to hospital, 1601 (0·02 per cent ) to an ICU, and 5479 (0·08 per cent) died after a positive test for SARS-CoV-2. We found J-shaped associations between BMI and admission to hospital due to COVID-19 (adjusted hazard ratio [HR] per kg/m2 from the nadir at BMI of 23 kg/m2 of 1·05 [95 per cent CI 1·05–1·05]) and death (1·04 [1·04–1·05]), and a linear association across the whole BMI range with ICU admission (1·10 [1·09–1·10]). We found a significant interaction between BMI and age and ethnicity, with higher HR per kg/m2 above BMI 23 kg/m2 for younger people (adjusted HR per kg/m2 above BMI 23 kg/m2 for hospital admission 1·09 [95% CI 1·08–1·10] in 20–39 years age group vs 80–100 years group 1·01 [1·00–1·02]) and Black people than White people (1·07 [1·06–1·08] vs 1·04 [1·04–1·05]). The risk of admission to hospital and ICU due to COVID-19 associated with unit increase in BMI was slightly lower in people with type 2 diabetes, hypertension, and cardiovascular disease than in those without these morbidities.

Interpretation

At a BMI of more than 23 kg/m2, we found a linear increase in risk of severe COVID-19 leading to admission to hospital and death, and a linear increase in admission to an ICU across the whole BMI range, which is not attributable to excess risks of related diseases. The relative risk due to increasing BMI is particularly notable people younger than 40 years and of Black ethnicity.

Paper available from The Lancet Diabetes & Endocrinology