Obesity and mortality in the Lipid Research Clinics Program Follow-up Study. 1990

T Wilcosky, and J Hyde, and J J Anderson, and S Bangdiwala, and B Duncan
Department of Epidemiology, School of Public Health, University of North Carolina, Chapel Hill 27514.

Using data from the Lipid Research Clinics Program for 1972-1983, the study presented here examined weight history and two indices of obesity: the body mass index (BMI) and the triceps skinfold (TSF) thickness. Cox regression analyses with and without adjustment for cardiovascular disease risk factors revealed a significant (p less than 0.05) quadratic association between BMI and all-causes mortality among men, but not women, after an average 8.4 years of follow-up; mortality was relatively high at both extremes of the BMI distribution. The association was stronger among smokers compared with nonsmokers, and it was apparent among male normotensives, but not hypertensives. All TSF-mortality associations and BMI associations with cancer and coronary heart disease mortality were weak and nonsignificant. Among men, per cent weight change in adulthood showed a significant inverse association with all-causes and cancer mortality. Because BMI and weight history were significantly associated with mortality after adjustment for other risk factors, they appear to be independent predictors of mortality among men.

UI MeSH Term Description Entries
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D009765 Obesity A status with BODY WEIGHT that is grossly above the recommended standards, usually due to accumulation of excess FATS in the body. The standards may vary with age, sex, genetic or cultural background. In the BODY MASS INDEX, a BMI greater than 30.0 kg/m2 is considered obese, and a BMI greater than 40.0 kg/m2 is considered morbidly obese (MORBID OBESITY).
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D001786 Blood Glucose Glucose in blood. Blood Sugar,Glucose, Blood,Sugar, Blood
D001794 Blood Pressure PRESSURE of the BLOOD on the ARTERIES and other BLOOD VESSELS. Systolic Pressure,Diastolic Pressure,Pulse Pressure,Pressure, Blood,Pressure, Diastolic,Pressure, Pulse,Pressure, Systolic,Pressures, Systolic
D001835 Body Weight The mass or quantity of heaviness of an individual. It is expressed by units of pounds or kilograms. Body Weights,Weight, Body,Weights, Body
D003327 Coronary Disease An imbalance between myocardial functional requirements and the capacity of the CORONARY VESSELS to supply sufficient blood flow. It is a form of MYOCARDIAL ISCHEMIA (insufficient blood supply to the heart muscle) caused by a decreased capacity of the coronary vessels. Coronary Heart Disease,Coronary Diseases,Coronary Heart Diseases,Disease, Coronary,Disease, Coronary Heart,Diseases, Coronary,Diseases, Coronary Heart,Heart Disease, Coronary,Heart Diseases, Coronary
D005260 Female Females
D005500 Follow-Up Studies Studies in which individuals or populations are followed to assess the outcome of exposures, procedures, or effects of a characteristic, e.g., occurrence of disease. Followup Studies,Follow Up Studies,Follow-Up Study,Followup Study,Studies, Follow-Up,Studies, Followup,Study, Follow-Up,Study, Followup

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