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. 2024 Mar 4;7(3):e243062.
doi: 10.1001/jamanetworkopen.2024.3062.

Long-Term Body Mass Index Variability and Adverse Cardiovascular Outcomes

Zakaria Almuwaqqat  1   2 , Qin Hui  1   3 , Chang Liu  3 , Jin J Zhou  4   5 , Benjamin F Voight  6   7 , Yuk-Lam Ho  8 , Daniel C Posner  8 , Jason L Vassy  8   9 , J Michael Gaziano  8   10 , Kelly Cho  8   9 , Peter W F Wilson  1   2 , Yan V Sun  1   2   3
Affiliations

Long-Term Body Mass Index Variability and Adverse Cardiovascular Outcomes

Zakaria Almuwaqqat et al. JAMA Netw Open. .

Abstract

Importance: Body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) is a commonly used estimate of obesity, which is a complex trait affected by genetic and lifestyle factors. Marked weight gain and loss could be associated with adverse biological processes.

Objective: To evaluate the association between BMI variability and incident cardiovascular disease (CVD) events in 2 distinct cohorts.

Design, setting, and participants: This cohort study used data from the Million Veteran Program (MVP) between 2011 and 2018 and participants in the UK Biobank (UKB) enrolled between 2006 and 2010. Participants were followed up for a median of 3.8 (5th-95th percentile, 3.5) years. Participants with baseline CVD or cancer were excluded. Data were analyzed from September 2022 and September 2023.

Exposure: BMI variability was calculated by the retrospective SD and coefficient of variation (CV) using multiple clinical BMI measurements up to the baseline.

Main outcomes and measures: The main outcome was incident composite CVD events (incident nonfatal myocardial infarction, acute ischemic stroke, and cardiovascular death), assessed using Cox proportional hazards modeling after adjustment for CVD risk factors, including age, sex, mean BMI, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, smoking status, diabetes status, and statin use. Secondary analysis assessed whether associations were dependent on the polygenic score of BMI.

Results: Among 92 363 US veterans in the MVP cohort (81 675 [88%] male; mean [SD] age, 56.7 [14.1] years), there were 9695 Hispanic participants, 22 488 non-Hispanic Black participants, and 60 180 non-Hispanic White participants. A total of 4811 composite CVD events were observed from 2011 to 2018. The CV of BMI was associated with 16% higher risk for composite CVD across all groups (hazard ratio [HR], 1.16; 95% CI, 1.13-1.19). These associations were unchanged among subgroups and after adjustment for the polygenic score of BMI. The UKB cohort included 65 047 individuals (mean [SD] age, 57.30 (7.77) years; 38 065 [59%] female) and had 6934 composite CVD events. Each 1-SD increase in BMI variability in the UKB cohort was associated with 8% increased risk of cardiovascular death (HR, 1.08; 95% CI, 1.04-1.11).

Conclusions and relevance: This cohort study found that among US veterans, higher BMI variability was a significant risk marker associated with adverse cardiovascular events independent of mean BMI across major racial and ethnic groups. Results were consistent in the UKB for the cardiovascular death end point. Further studies should investigate the phenotype of high BMI variability.

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Conflict of interest statement

Conflict of Interest Disclosures: None reported.

Figures

Figure 1.
Figure 1.. Participant Inclusion Flowchart
Figure 2.
Figure 2.. Subgroup Analysis of the Associations Between Body Mass Index (BMI) Variability and Adverse Cardiovascular Events by Different Groups
BMI is calculated as weight in kilograms divided by height in meters squared. HR indicates hazard ratio.
See this image and copyright information in PMC

References

    1. Tsao CW, Aday AW, Almarzooq ZI, et al. . Heart disease and stroke statistics—2022 update: a report from the American Heart Association. Circulation. 2022;145(8):e153-e639. doi:10.1161/CIR.0000000000001052 - DOI - PubMed
    1. Powell-Wiley TM, Poirier P, Burke LE, et al. ; American Heart Association Council on Lifestyle and Cardiometabolic Health; Council on Cardiovascular and Stroke Nursing; Council on Clinical Cardiology; Council on Epidemiology and Prevention; and Stroke Council . Obesity and cardiovascular disease: a scientific statement from the American Heart Association. Circulation. 2021;143(21):e984-e1010. doi:10.1161/CIR.0000000000000973 - DOI - PMC - PubMed
    1. Gu D, He J, Duan X, et al. . Body weight and mortality among men and women in China. JAMA. 2006;295(7):776-783. doi:10.1001/jama.295.7.776 - DOI - PubMed
    1. Aune D, Sen A, Prasad M, et al. . BMI and all cause mortality: systematic review and non-linear dose-response meta-analysis of 230 cohort studies with 3.74 million deaths among 30.3 million participants. BMJ. 2016;353:i2156. doi:10.1136/bmj.i2156 - DOI - PMC - PubMed
    1. Lee DH, Steffes MW, Gross M, et al. . Differential associations of weight dynamics with coronary artery calcium versus common carotid artery intima-media thickness: the CARDIA Study. Am J Epidemiol. 2010;172(2):180-189. doi:10.1093/aje/kwq093 - DOI - PMC - PubMed

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