OBJECTIVES: The objective of this study was to determine the relative contribution of modifiable risk factors (physical activity, smoking, and alcohol consumption) to inter-subject variation in erectile dysfunction (ED). METHODS: The Boston Area Community Health (BACH) Survey used a multistage stratified random sample to recruit 2301 men age 30-79 years from the city of Boston between 2002 and 2005. ED was assessed using the 5-item International Index of Erectile Function (IIEF-5). Multiple linear regression models and R(2) were used to determine the proportion of the variance explained by modifiable risk factors. RESULTS: In unadjusted analyses, lifestyle factors accounted for 12.2% of the inter-subject variability in IIEF-5 scores, comparable to the proportion explained by comorbid conditions (14.7%) and socioeconomic status (9%). Lifestyle factors were also significantly associated with age, comorbid conditions and socioeconomic status (SES). A multivariate model including all covariates associated with ED explained 29% of the variance, with lifestyle factors accounting for 0.9% over and above all other covariates in the model. Analyses repeated in a subgroup of 1215 men without comorbid conditions show lifestyle factors accounting for 2.5% of the variance after accounting for all other variables in the model. CONCLUSIONS: Results of the present study demonstrate the contribution of modifiable lifestyle factors to the prevalence of ED. These results suggest a role for behavior modification in the prevention of ED. Copyright 2009. Published by Elsevier Inc.
OBJECTIVES: The objective of this study was to determine the relative contribution of modifiable risk factors (physical activity, smoking, and alcohol consumption) to inter-subject variation in erectile dysfunction (ED). METHODS: The Boston Area Community Health (BACH) Survey used a multistage stratified random sample to recruit 2301 men age 30-79 years from the city of Boston between 2002 and 2005. ED was assessed using the 5-item International Index of Erectile Function (IIEF-5). Multiple linear regression models and R(2) were used to determine the proportion of the variance explained by modifiable risk factors. RESULTS: In unadjusted analyses, lifestyle factors accounted for 12.2% of the inter-subject variability in IIEF-5 scores, comparable to the proportion explained by comorbid conditions (14.7%) and socioeconomic status (9%). Lifestyle factors were also significantly associated with age, comorbid conditions and socioeconomic status (SES). A multivariate model including all covariates associated with ED explained 29% of the variance, with lifestyle factors accounting for 0.9% over and above all other covariates in the model. Analyses repeated in a subgroup of 1215 men without comorbid conditions show lifestyle factors accounting for 2.5% of the variance after accounting for all other variables in the model. CONCLUSIONS: Results of the present study demonstrate the contribution of modifiable lifestyle factors to the prevalence of ED. These results suggest a role for behavior modification in the prevention of ED. Copyright 2009. Published by Elsevier Inc.
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