Michael D Wirth1, Christine E Blake2, James R Hébert3, Xuemei Sui4, Steven N Blair4. 1. South Carolina Statewide Cancer Prevention and Control Program, Arnold School of Public Health, University of South Carolina. 2. Department of Health Promotion, Education, and Behavior, Arnold School of Public Health, University of South Carolina. 3. South Carolina Statewide Cancer Prevention and Control Program, University of South Carolina, Arnold School of Public Health. 4. Department of Exercise Science, Arnold School of Public Health, University of South Carolina.
Abstract
OBJECTIVE: Weight dissatisfaction, defined as discordance between actual and goal weight, may be associated with increased risk for several obesity-related comorbidities. The purpose of the study was to examine the association between weight dissatisfaction and risk of developing Type 2 diabetes. METHOD: This longitudinal study used data from 9,584 adults enrolled in the Aerobics Center Longitudinal Study. Key variables included multiple measures of measured weight, self-reported goal weight, and incident diabetes. Weight dissatisfaction was defined as being above the median of measured weight minus goal weight. Cox proportional hazards regression estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for diabetes incidence by weight dissatisfaction. RESULTS: HRs for time until diabetes diagnosis revealed that family history of diabetes (HR = 1.46, 95% CI [1.13, 1.90]), age (HR = 1.03, 95% CI [1.02, 1.04]), and weight dissatisfaction (HR = 1.83, 95% CI [1.50, 2.25]) at baseline were statistically significant predictors. Longitudinally, higher risk was observed in individuals who either stayed dissatisfied (HR = 2.98, 95% CI [1.98, 4.48]) or became dissatisfied (HR = 1.51, 95% CI [0.79, 2.89]), compared with those who stayed satisfied. After additional adjustment for BMI, the elevated HR for those who remained dissatisfied compared with those who remained satisfied persisted (HR = 2.85, 95% CI [1.89, 4.31]). CONCLUSIONS: Weight dissatisfaction, regardless of BMI, represents a potentially important psychophysiological modifier of the relationships between BMI and risk of Type 2 diabetes, and warrants greater attention in future studies of chronic disease risk.
OBJECTIVE: Weight dissatisfaction, defined as discordance between actual and goal weight, may be associated with increased risk for several obesity-related comorbidities. The purpose of the study was to examine the association between weight dissatisfaction and risk of developing Type 2 diabetes. METHOD: This longitudinal study used data from 9,584 adults enrolled in the Aerobics Center Longitudinal Study. Key variables included multiple measures of measured weight, self-reported goal weight, and incident diabetes. Weight dissatisfaction was defined as being above the median of measured weight minus goal weight. Cox proportional hazards regression estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for diabetes incidence by weight dissatisfaction. RESULTS: HRs for time until diabetes diagnosis revealed that family history of diabetes (HR = 1.46, 95% CI [1.13, 1.90]), age (HR = 1.03, 95% CI [1.02, 1.04]), and weight dissatisfaction (HR = 1.83, 95% CI [1.50, 2.25]) at baseline were statistically significant predictors. Longitudinally, higher risk was observed in individuals who either stayed dissatisfied (HR = 2.98, 95% CI [1.98, 4.48]) or became dissatisfied (HR = 1.51, 95% CI [0.79, 2.89]), compared with those who stayed satisfied. After additional adjustment for BMI, the elevated HR for those who remained dissatisfied compared with those who remained satisfied persisted (HR = 2.85, 95% CI [1.89, 4.31]). CONCLUSIONS: Weight dissatisfaction, regardless of BMI, represents a potentially important psychophysiological modifier of the relationships between BMI and risk of Type 2 diabetes, and warrants greater attention in future studies of chronic disease risk.
Authors: Cynthia L Ogden; Margaret D Carroll; Lester R Curtin; Margaret A McDowell; Carolyn J Tabak; Katherine M Flegal Journal: JAMA Date: 2006-04-05 Impact factor: 56.272
Authors: Jennifer L Kuk; Chris I Ardern; Timothy S Church; James R Hebert; Xuemei Sui; Steven N Blair Journal: Am J Epidemiol Date: 2009-06-22 Impact factor: 4.897