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识别英格兰体重和 BMI 变化风险较高的成年人:一项使用电子健康记录的纵向、大规模、基于人群的队列研究。

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.

机构信息

Institute of Health Informatics, University College London, London, UK; Health Data Research UK, University College London, London, UK.

Institute of Health Informatics, University College London, London, UK; Health Data Research UK, University College London, London, UK.

出版信息

Lancet Diabetes Endocrinol. 2021 Oct;9(10):681-694. doi: 10.1016/S2213-8587(21)00207-2. Epub 2021 Sep 2.

Abstract

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% 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.

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.

FUNDING

The British Hearth Foundation, Health Data Research UK, the UK Medical Research Council, and the National Institute for Health Research.

摘要

背景

目标明确的肥胖预防政策将得益于识别出体重增长风险最高的人群。然而,我们并不清楚成年年龄、性别、种族、地理位置和社会剥夺程度等因素对体重增加的相对重要性。我们旨在利用电子健康记录(EHR)来识别体重和 BMI 变化的高风险人群。

方法

在这项基于人群的纵向队列研究中,我们使用了来自英格兰 400 家初级保健机构(通过临床实践研究数据链接,CALIBER 计划获取)的链接 EHR 数据。合格的参与者年龄在 18-74 岁之间,在普通诊所注册,在有资格获得至少 1 年随访时间的链接数据期间,BMI 和体重测量值记录在 1998 年 1 月 1 日至 2016 年 6 月 30 日之间。我们计算了 1、5 和 10 年内 BMI 的纵向变化,并研究了体重指数类别(体重不足、正常体重、超重、肥胖 1 类和 2 类和严重肥胖[3 类])之间的绝对风险和优势比(OR)的转变,这是由世界卫生组织定义的。使用逻辑回归分析估计人口因素与 BMI 转变的关系,调整了基线 BMI、心血管疾病家族史、利尿剂使用和现患慢性疾病。

结果

我们在研究中纳入了 2092260 名符合条件的个体,他们有超过 900 万次 BMI 测量值。年轻的成年年龄是 1、5 和 10 年随访时体重增加的最强风险因素。与最年长的年龄组(65-74 岁)相比,最年轻的年龄组(18-24 岁)的成年人具有最高的 OR(4.22 [95%CI 3.86-4.62])和最高的绝对风险(37%比 24%),在 10 年内从正常体重转变为超重或肥胖。同样,在基线时超重或肥胖的最年轻年龄组成年人也面临着最高的风险,向更高的 BMI 类别转变;OR 4.60(4.06-5.22)和绝对风险(42%比 18%)从超重转变为 1 类和 2 类肥胖,以及 OR 5.87(5.23-6.59)和绝对风险(22%比 5%)从 1 类和 2 类肥胖转变为 3 类肥胖。其他人口因素与这些转变的关系则不那么密切;例如,与生活在最贫困和最贫困地区的人相比,从正常体重到超重或肥胖的转变的 OR 为 1.23(1.18-1.27),男性为 1.12(1.08-1.16),黑人与白人相比为 1.13(1.04-1.24)。我们提供了一个开放访问的在线风险计算器,并呈现了 1 年、5 年和 10 年随访期间的高分辨率肥胖风险图表。

解释

需要进行彻底的政策转变,重点关注体重增长风险最高的人群(即 18-24 岁的年轻人),以进行个体和人群层面的肥胖预防及其对健康和医疗保健的长期影响。

资助

英国心脏基金会、英国健康数据研究署、英国医学研究理事会和英国国家卫生研究院。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7ea/8440227/15c56987481c/gr1.jpg

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