Epidemiological associations between obesity, metabolism and disease risk: are body mass index and waist-hip ratio all you need?

IF 3.8 2区 医学 Q1 ENDOCRINOLOGY & METABOLISM
Ville-Petteri Mäkinen, Siyu Zhao, Andrei Ihanus, Tuulia Tynkkynen, Mika Ala-Korpela
{"title":"Epidemiological associations between obesity, metabolism and disease risk: are body mass index and waist-hip ratio all you need?","authors":"Ville-Petteri Mäkinen, Siyu Zhao, Andrei Ihanus, Tuulia Tynkkynen, Mika Ala-Korpela","doi":"10.1038/s41366-025-01895-2","DOIUrl":null,"url":null,"abstract":"<p><strong>Background/objectives: </strong>Tracking excess adiposity at population scale is essential for managing the obesity pandemic in human populations. New formulas based on weight, height, waist and hip measurements have been suggested as better alternatives to the classic body mass index and waist-hip ratio, but the lack of systematic benchmarking on how these formulas reflect adiposity, metabolic dysfunction and clinical sequelae causes confusion on how to best monitor the health of populations.</p><p><strong>Subjects/methods: </strong>Participants from the Northern Finland Birth Cohort 1966 were included based on data availability at the 46-year visit (2511 women and 1908 men). Cross-sectional sex-adjusted Spearman correlations with clinical biomarkers and serum and urine NMR metabolomics were calculated for body mass index (BMI), waist-hip ratio (WHR), waist-height ratio (WHER), abdominal volume index, body adiposity index, body roundness index, body shape index, conicity index and impedance-based body fat. UK biobank participants were selected based on available data at initial visit (244,947 women and 205,949 men). Prevalent and incident cases of type 2 diabetes, hypertension, liver disease and heart disease were ascertained through register linkage. Prevalent cases were predicted from adiposity measures by age- and sex-adjusted logistic regression and incident cases by age- and sex-adjusted Cox regression.</p><p><strong>Results: </strong>Adiposity measures were highly collinear and exhibited low biomolecular specificity. BMI and WHR together captured almost all body shape information related to cardiometabolic diseases. For instance, the c-statistic of the BMI & WHR model for diabetes (0.8012; CI95: 0.7963, 0.8061) was near the theoretical maximum of 0.8047. Diabetes was also predicted by WHER (0.7951; CI95: 0.7903, 0.8000). Other adiposity measures showed equal or worse prediction accuracy. This pattern repeated across multiple disease diagnoses.</p><p><strong>Conclusions: </strong>We did not observe sufficient benefits from the more recent body adiposity formulas over body mass index, waist-hip or waist-height ratio to warrant their widespread application in cardiometabolic epidemiology.</p>","PeriodicalId":14183,"journal":{"name":"International Journal of Obesity","volume":" ","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Obesity","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41366-025-01895-2","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0

Abstract

Background/objectives: Tracking excess adiposity at population scale is essential for managing the obesity pandemic in human populations. New formulas based on weight, height, waist and hip measurements have been suggested as better alternatives to the classic body mass index and waist-hip ratio, but the lack of systematic benchmarking on how these formulas reflect adiposity, metabolic dysfunction and clinical sequelae causes confusion on how to best monitor the health of populations.

Subjects/methods: Participants from the Northern Finland Birth Cohort 1966 were included based on data availability at the 46-year visit (2511 women and 1908 men). Cross-sectional sex-adjusted Spearman correlations with clinical biomarkers and serum and urine NMR metabolomics were calculated for body mass index (BMI), waist-hip ratio (WHR), waist-height ratio (WHER), abdominal volume index, body adiposity index, body roundness index, body shape index, conicity index and impedance-based body fat. UK biobank participants were selected based on available data at initial visit (244,947 women and 205,949 men). Prevalent and incident cases of type 2 diabetes, hypertension, liver disease and heart disease were ascertained through register linkage. Prevalent cases were predicted from adiposity measures by age- and sex-adjusted logistic regression and incident cases by age- and sex-adjusted Cox regression.

Results: Adiposity measures were highly collinear and exhibited low biomolecular specificity. BMI and WHR together captured almost all body shape information related to cardiometabolic diseases. For instance, the c-statistic of the BMI & WHR model for diabetes (0.8012; CI95: 0.7963, 0.8061) was near the theoretical maximum of 0.8047. Diabetes was also predicted by WHER (0.7951; CI95: 0.7903, 0.8000). Other adiposity measures showed equal or worse prediction accuracy. This pattern repeated across multiple disease diagnoses.

Conclusions: We did not observe sufficient benefits from the more recent body adiposity formulas over body mass index, waist-hip or waist-height ratio to warrant their widespread application in cardiometabolic epidemiology.

肥胖、新陈代谢和疾病风险之间的流行病学联系:体重指数和腰臀比就是你所需要的吗?
背景/目的:在人群规模上追踪过度肥胖对于控制人群中的肥胖大流行至关重要。有人建议,基于体重、身高、腰围和臀围测量的新公式可以更好地替代传统的体重指数和腰臀比,但由于缺乏系统的基准,这些公式如何反映肥胖、代谢功能障碍和临床后遗症,导致人们对如何最好地监测人群健康感到困惑。对象/方法:根据46年随访期间的可用数据,纳入了1966年芬兰北部出生队列的参与者(2511名女性和1908名男性)。计算体重指数(BMI)、腰臀比(WHR)、腰高比(WHER)、腹体积指数、体脂指数、体圆度指数、体型指数、圆度指数和基于阻抗的体脂,与临床生物标志物以及血清和尿液核磁共振代谢组学进行性别调整的横断面Spearman相关性。英国生物银行的参与者是根据首次访问时的可用数据选择的(244947名女性和205949名男性)。通过登记联系法确定2型糖尿病、高血压、肝病和心脏病的患病率和发病率。通过年龄和性别调整的logistic回归预测肥胖测量的流行病例,通过年龄和性别调整的Cox回归预测发病率。结果:肥胖测量高度共线,表现出低生物分子特异性。BMI和WHR一起捕获了几乎所有与心脏代谢疾病相关的体型信息。例如,糖尿病BMI & WHR模型的c统计量(0.8012;CI95: 0.7963, 0.8061)接近理论最大值0.8047。WHER也预测糖尿病(0.7951;CI95: 0.7903, 0.8000)。其他测量肥胖的方法显示出相同或更差的预测准确性。这种模式在多种疾病诊断中重复出现。结论:我们没有观察到最近的身体肥胖公式对身体质量指数、腰臀比或腰高比有足够的好处,以保证它们在心脏代谢流行病学中的广泛应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
International Journal of Obesity
International Journal of Obesity 医学-内分泌学与代谢
CiteScore
10.00
自引率
2.00%
发文量
221
审稿时长
3 months
期刊介绍: The International Journal of Obesity is a multi-disciplinary forum for research describing basic, clinical and applied studies in biochemistry, physiology, genetics and nutrition, molecular, metabolic, psychological and epidemiological aspects of obesity and related disorders. We publish a range of content types including original research articles, technical reports, reviews, correspondence and brief communications that elaborate on significant advances in the field and cover topical issues.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信