Information de reference pour ce titreAccession Number: | 00000605-201705020-00003.
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Author: | Yu, Edward MS; Ley, Sylvia H. PhD, RD; Manson, JoAnn E. MD, DrPH; Willett, Walter MD, DrPH; Satija, Ambika ScD; Hu, Frank B. MD, PhD, MPH; Stokes, Andrew PhD
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Institution: | From Harvard T.H. Chan School of Public Health, Brigham and Women's Hospital, Harvard Medical School, and Boston University School of Public Health, Boston, Massachusetts.
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Title: | |
Source: | Annals of Internal Medicine. 166(9):613-620, May 2, 2017.
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Abstract: | Background: The relationship between body mass index (BMI) and mortality is controversial.
Objective: To investigate the relationship between maximum BMI over 16 years and subsequent mortality.
Design: 3 prospective cohort studies.
Setting: Nurses' Health Study I and II and Health Professionals Follow-Up Study.
Participants: 225 072 men and women with 32 571 deaths observed over a mean of 12.3 years of follow-up.
Measurements: Maximum BMI over 16 years of weight history and all-cause and cause-specific mortality.
Results: Maximum BMIs in the overweight (25.0 to 29.9 kg/m2) (multivariate hazard ratio [HR], 1.06 [95% CI, 1.03 to 1.08]), obese I (30.0 to 34.9 kg/m2) (HR, 1.24 [CI, 1.20 to 1.29]), and obese II (>=35.0 kg/m2) (HR, 1.73 [CI, 1.66 to 1.80]) categories were associated with increases in risk for all-cause death. The pattern of excess risk with a maximum BMI above normal weight was maintained across strata defined by smoking status, sex, and age, but the excess was greatest among those younger than 70 years and never-smokers. In contrast, a significant inverse association between overweight and mortality (HR, 0.96 [CI, 0.94 to 0.99]) was observed when BMI was defined using a single baseline measurement. Maximum overweight was also associated with increased cause-specific mortality, including death from cardiovascular disease and coronary heart disease.
Limitation: Residual confounding and misclassification.
Conclusion: The paradoxical association between overweight and mortality is reversed in analyses incorporating weight history. Maximum BMI may be a useful metric to minimize reverse causation bias associated with a single baseline BMI assessment.
Primary Funding Source: National Institutes of Health.
(C) 2017 American College of Physicians
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Language: | English.
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Document Type: | Original Research.
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Journal Subset: | Clinical Medicine.
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ISSN: | 0003-4819
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NLM Journal Code: | 0372351, 5a6
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