Dawda Jawara, Craig M Krebsbach, Manasa Venkatesh, Jacqueline A Murtha, Bret M Hanlon, Kate V Lauer, Lily N Stalter, Luke M Funk
{"title":"美国体重趋势:对美国国立卫生研究院合作数据集的纵向分析。","authors":"Dawda Jawara, Craig M Krebsbach, Manasa Venkatesh, Jacqueline A Murtha, Bret M Hanlon, Kate V Lauer, Lily N Stalter, Luke M Funk","doi":"10.1038/s41366-024-01661-w","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Obesity is a major public health challenge in the U.S. Existing datasets utilized for calculating obesity prevalence, such as the National Health and Nutrition Examination Survey (NHANES) and Behavioral Risk Factor Surveillance System (BRFSS), have limitations. Our objective was to analyze weight trends in the U.S. using a nationally representative dataset that incorporates longitudinal electronic health record data.</p><p><strong>Methods: </strong>Using the National Institutes of Health All of Us Research Program (AoU) dataset, we identified patients aged 18-70 years old who had at least two height and weight measurements within a 5-year period from 2008 to 2021. Baseline and most recent BMI values were used to calculate total body weight (%TBW) changes. %TBW change predictors were determined using multivariable linear regression.</p><p><strong>Results: </strong>We included 30,862 patients (mean age 48.9 [ ± 12.6] years; 60.5% female). At the 5-year follow-up, the prevalences of obesity and severe obesity were 37.4% and 20.7%, respectively. The frequency of patients with normal weight or overweight BMI who gained ≥5% TBW at follow-up was 37.8% and 33.1%, respectively. Nearly 24% of the cohort lost ≥ 5% TBW, and 6.5% with severe obesity lost weight to achieve a BMI < 30 kg/m<sup>2</sup>. In adjusted analyses, male sex (-1.10%, 95% CI [-1.36, -0.85]), non-Hispanic Asian race/ethnicity (-1.69% [-2.44, -0.94]), and type 2 diabetes (-1.58% [-1.95, -1.22]) were associated with weight loss, while obstructive sleep apnea (1.80% [1.40, 2.19]) was associated with weight gain.</p><p><strong>Conclusions: </strong>This evaluation of an NIH-partnered dataset suggests that patients are continuing to gain weight in the U.S. AoU represents a unique tool for obesity prediction, prevention, and treatment given its longitudinal nature and unique behavioral and genetic data.</p>","PeriodicalId":14183,"journal":{"name":"International Journal of Obesity","volume":null,"pages":null},"PeriodicalIF":4.2000,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"U.S. weight trends: a longitudinal analysis of an NIH-partnered dataset.\",\"authors\":\"Dawda Jawara, Craig M Krebsbach, Manasa Venkatesh, Jacqueline A Murtha, Bret M Hanlon, Kate V Lauer, Lily N Stalter, Luke M Funk\",\"doi\":\"10.1038/s41366-024-01661-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Obesity is a major public health challenge in the U.S. Existing datasets utilized for calculating obesity prevalence, such as the National Health and Nutrition Examination Survey (NHANES) and Behavioral Risk Factor Surveillance System (BRFSS), have limitations. Our objective was to analyze weight trends in the U.S. using a nationally representative dataset that incorporates longitudinal electronic health record data.</p><p><strong>Methods: </strong>Using the National Institutes of Health All of Us Research Program (AoU) dataset, we identified patients aged 18-70 years old who had at least two height and weight measurements within a 5-year period from 2008 to 2021. Baseline and most recent BMI values were used to calculate total body weight (%TBW) changes. %TBW change predictors were determined using multivariable linear regression.</p><p><strong>Results: </strong>We included 30,862 patients (mean age 48.9 [ ± 12.6] years; 60.5% female). At the 5-year follow-up, the prevalences of obesity and severe obesity were 37.4% and 20.7%, respectively. The frequency of patients with normal weight or overweight BMI who gained ≥5% TBW at follow-up was 37.8% and 33.1%, respectively. Nearly 24% of the cohort lost ≥ 5% TBW, and 6.5% with severe obesity lost weight to achieve a BMI < 30 kg/m<sup>2</sup>. In adjusted analyses, male sex (-1.10%, 95% CI [-1.36, -0.85]), non-Hispanic Asian race/ethnicity (-1.69% [-2.44, -0.94]), and type 2 diabetes (-1.58% [-1.95, -1.22]) were associated with weight loss, while obstructive sleep apnea (1.80% [1.40, 2.19]) was associated with weight gain.</p><p><strong>Conclusions: </strong>This evaluation of an NIH-partnered dataset suggests that patients are continuing to gain weight in the U.S. AoU represents a unique tool for obesity prediction, prevention, and treatment given its longitudinal nature and unique behavioral and genetic data.</p>\",\"PeriodicalId\":14183,\"journal\":{\"name\":\"International Journal of Obesity\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-10-29\",\"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/s41366-024-01661-w\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Obesity","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41366-024-01661-w","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
U.S. weight trends: a longitudinal analysis of an NIH-partnered dataset.
Background: Obesity is a major public health challenge in the U.S. Existing datasets utilized for calculating obesity prevalence, such as the National Health and Nutrition Examination Survey (NHANES) and Behavioral Risk Factor Surveillance System (BRFSS), have limitations. Our objective was to analyze weight trends in the U.S. using a nationally representative dataset that incorporates longitudinal electronic health record data.
Methods: Using the National Institutes of Health All of Us Research Program (AoU) dataset, we identified patients aged 18-70 years old who had at least two height and weight measurements within a 5-year period from 2008 to 2021. Baseline and most recent BMI values were used to calculate total body weight (%TBW) changes. %TBW change predictors were determined using multivariable linear regression.
Results: We included 30,862 patients (mean age 48.9 [ ± 12.6] years; 60.5% female). At the 5-year follow-up, the prevalences of obesity and severe obesity were 37.4% and 20.7%, respectively. The frequency of patients with normal weight or overweight BMI who gained ≥5% TBW at follow-up was 37.8% and 33.1%, respectively. Nearly 24% of the cohort lost ≥ 5% TBW, and 6.5% with severe obesity lost weight to achieve a BMI < 30 kg/m2. In adjusted analyses, male sex (-1.10%, 95% CI [-1.36, -0.85]), non-Hispanic Asian race/ethnicity (-1.69% [-2.44, -0.94]), and type 2 diabetes (-1.58% [-1.95, -1.22]) were associated with weight loss, while obstructive sleep apnea (1.80% [1.40, 2.19]) was associated with weight gain.
Conclusions: This evaluation of an NIH-partnered dataset suggests that patients are continuing to gain weight in the U.S. AoU represents a unique tool for obesity prediction, prevention, and treatment given its longitudinal nature and unique behavioral and genetic data.
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.