OBJECTIVES: To compare the estimates of Prevalence Ratio (PR) and Odds Ratios (OR) as effect measures in the analysis of cross sectional data for obese individuals suffering with chronic comorbid conditions.  METHODS: Medical Expenditure Panel Survey data files from 2005-2007 was utilized for the analysis. Obese adults were defined as individuals with age ≥ 20 years and having a BMI ≥ 30. Prevalence ratios were estimated from logistic regressions by dividing predicted prevalence estimates of comorbidities among obese individuals to the predicted prevalence of comorbidities in non-obese individuals after adjusting for socio-demographic factors. Ninety-five percent boot-strapped confidence intervals were generated around the prevalence ratios. Odds ratios were generated by using the ‘Survey Logistic’ syntax in SAS after adjusting for the same socio-demographic factors. RESULTS: Both odds ratios and prevalence ratios indicate that obese individuals have a greater burden of chronic conditions in United States. Obese individuals had the greatest odds of having hypertension and osteoarthritis followed by coronary heart disease, diabetes and dyslipidemia. Prevalence ratios were highest for diabetes, followed by hypertension, osteoarthritis and dyslipidemia. Odds ratios were almost always greater than the prevalence ratios for all chronic conditions. The confidence intervals derived around odds ratios were also wider than the confidence intervals around the prevalence ratios.   CONCLUSIONS: The relative importance of obesity upon different disease conditions differed depending on whether PR or OR were estimated. This study along with previous literature shows that odds ratios may be overestimating the true effect of a disease condition on the prevalence of a comorbid disease. Although it is easier to derive odds ratios, prevalence ratios may be more realistic estimates of the true public health burden. Thus prevalence ratios should ideally be used as effect measures instead of odds ratios especially for commonly occurring disease conditions.