Jake Turicchi , Ruairi O'Driscoll , Graham Horgan , Cristiana Duarte , Inês Santos , Jorge Encantado , Antonio L. Palmeira , Sofus C. Larsen , Jack K. Olsen , Berit L. Heitmann , R. James Stubbs
{"title":"Body weight variability is not associated with changes in risk factors for cardiometabolic disease","authors":"Jake Turicchi , Ruairi O'Driscoll , Graham Horgan , Cristiana Duarte , Inês Santos , Jorge Encantado , Antonio L. Palmeira , Sofus C. Larsen , Jack K. Olsen , Berit L. Heitmann , R. James Stubbs","doi":"10.1016/j.ijchy.2020.100045","DOIUrl":null,"url":null,"abstract":"<div><h3>Context</h3><p>Weight loss is known to improve health, however the influence of variability in body weight around the overall trajectory on these outcomes is unknown. Few studies have measured body weight frequently enough to accurately estimate the variability component.</p></div><div><h3>Objective</h3><p>To investigate the association of 12-month weight variability and concurrent weight change with changes in health markers and body composition.</p></div><div><h3>Methods</h3><p>This study was a secondary analysis of the NoHoW trial, a 2 × 2 factorial randomised controlled trial promoting evidence-based behaviour change for weight loss maintenance. Outcome measurements related to cardiometabolic health and body composition were taken at 0, 6 and 12 months. Participants were provided with Wi-Fi connected smart scales (Fitbit Aria 2) and asked to self-weigh regularly over this period. Associations of weight variability and weight change with change in outcomes were investigated using multiple linear regression with multiple levels of adjustment in 955 participants.</p></div><div><h3>Results</h3><p>Twelve models were generated for each health marker. Associations between weight variability and changes in health markers were inconsistent between models and showed no evidence of a consistent relationship, with all effects explaining <1% of the outcome, and most 0%. Weight loss was consistently associated with improvements in health and body composition, with the greatest effects seen in percent body fat (R<sup>2</sup> = 10.4–11.1%) followed by changes in diastolic (4.2–4.7%) and systolic (3–4%) blood pressure.</p></div><div><h3>Conclusion</h3><p>Over 12-months, weight variability was not consistently associated with any measure of cardiometabolic health or body composition, however weight loss consistently improved all outcomes.</p></div><div><h3>Trial registration number</h3><p>ISRCTN88405328.</p></div>","PeriodicalId":36839,"journal":{"name":"International Journal of Cardiology: Hypertension","volume":"6 ","pages":"Article 100045"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.ijchy.2020.100045","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Cardiology: Hypertension","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590086220300227","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 7
Abstract
Context
Weight loss is known to improve health, however the influence of variability in body weight around the overall trajectory on these outcomes is unknown. Few studies have measured body weight frequently enough to accurately estimate the variability component.
Objective
To investigate the association of 12-month weight variability and concurrent weight change with changes in health markers and body composition.
Methods
This study was a secondary analysis of the NoHoW trial, a 2 × 2 factorial randomised controlled trial promoting evidence-based behaviour change for weight loss maintenance. Outcome measurements related to cardiometabolic health and body composition were taken at 0, 6 and 12 months. Participants were provided with Wi-Fi connected smart scales (Fitbit Aria 2) and asked to self-weigh regularly over this period. Associations of weight variability and weight change with change in outcomes were investigated using multiple linear regression with multiple levels of adjustment in 955 participants.
Results
Twelve models were generated for each health marker. Associations between weight variability and changes in health markers were inconsistent between models and showed no evidence of a consistent relationship, with all effects explaining <1% of the outcome, and most 0%. Weight loss was consistently associated with improvements in health and body composition, with the greatest effects seen in percent body fat (R2 = 10.4–11.1%) followed by changes in diastolic (4.2–4.7%) and systolic (3–4%) blood pressure.
Conclusion
Over 12-months, weight variability was not consistently associated with any measure of cardiometabolic health or body composition, however weight loss consistently improved all outcomes.