Dickerson et al. BMC Public Health 2011, 11:926 http://www.biomedcentral.com/1471-2458/11/926 (BMI >= 40.0 kg/m2) [2]. While obesity has increased substantially over the past decade, the increase in obese class III, also known as “morbid obesity,” has increased at twice the rate of lower obese classifications [6]. Research indicates morbidly obese individuals suffer from serious co-morbidities with nearly half (48%) diag- nosed with hypertension, 29% diagnosed with diabetes, and 25% diagnosed with heart failure [7]. Treating many of these conditions is difficult because morbidly obese individuals are often physically unable to avail them- selves of modern diagnostic medicine because of their size, especially when attempting to be treated for cardio- vascular diseases [8]. It is therefore understandable that mortality rates of hospitalized morbidly obese indivi- duals are increasing and are highest among those with the highest BMI [7]. These findings provide context to research indicating healthcare expenditures for the mor- bidly obese are 47% greater than for the obese class I population [9]. There are many causes for increasing rates of obesity. Among these risk factors are sedentary behaviors [10]. Even though engaging in positive physical activity (PA) habits such as exercise, individuals who simultaneously engage in sedentary behaviors (e.g., such as extended hours watching television or sitting in an office or car) can still experience negative health consequences [11]. Research indicates only 3% of waking hours are currently spent on exercise while 58% are spent engaging in sedentary beha- viors such as sitting or lying down [10]. Based on these findings, researchers have argued sedentary behaviors should be considered an independent set of risk factors [12] related to both all-cause and cardiovascular disease mortality [13]. Among sedentary behaviors, extended peri- ods watching television has been uniquely linked to increasing rates of obesity [14]. Even when adjusted for socio-demographics, co-morbidities, and family history, each 1 h per day increase in time spent watching television has been positively associated with increased risk of all- cause mortality and cardiovascular mortality [15]. It is important to recognize the role PA (e.g., exercise) can play in mitigating negative health outcomes. PA has been linked with lower risk of heart disease and certain cancers, and has also been identified as an effective tool in addressing obesity [16]. The current federal guidelines for PA recommend 150 min per week of moderate intensity activity or 75 min per week of vigorous inten- sity activity [17]. Despite these recommendations, how- ever, there is an inverse relationship between BMI and the likelihood of exercising [18]. This represents a key challenge for healthcare providers to address. The research identified above is demonstrative of growing literature linking sedentary behaviors, physical inactivity, and obesity. However, what is less emphasized in the literature is the relationship of these variables to Page 2 of 10 individuals of differing levels of obesity. The purpose of our study is to examine whether there is a homogenous effect between sedentary behaviors, PA, socio-demo- graphic variables and BMI classification. This research question is important to policymakers as it may assist in targeting interventions to certain BMI classifications, and in return maximize the use of financial resources to address obesity. Methods Brazos valley health assessment (BVHA) The 2010 BVHA (n = 3,964) was conducted and funded by the Center for Community Health Development at the Texas A&M Health Science Center, School of Rural Pub- lic Health [19]. In conjunction with community health partners, a voluntary questionnaire was disseminated to assess community health status and opportunities for health improvement in the Brazos Valley, an eight county region in central Texas [19]. Data were collected using a random sampling of households. The recruitment specia- list solicited the head of household according to the adult with the next coming birthday in order to eliminate bias. Based on the head of household’s eligibility and consent to participate, a survey instrument was mailed to them. Only one survey instrument per household was collected. The instrument was 32 pages containing items from vali- dated sources such as the Center for Disease Control and Prevention’s National Health and Nutrition Examination Survey (NHANES) and Behavioral Risk Factor Surveil- lance System (BRFSS) [19-21]. Sample Respondents who self-reported being diagnosed by their healthcare provider with a disease or medical condition associated with obesity were included in our study (n = 2,840). These diseases or medical conditions were: hypertension, heart failure, high cholesterol, angina, heart attack, stroke, diabetes, asthma, and chronic obstructive pulmonary disorder. Respondents who self- reported severe impairment such as loss of hearing or eyesight, a loss of limb(s), and respondents not reporting data to calculate a BMI or reporting data resulting in a BMI classification of underweight were excluded from the sample (n = 859). This exclusionary criteria was used because several of the variables in the study (e.g., watching television and PA) involved the use of physical faculties and the investigators were unaware of the degree such physical impairments would naturally impede participation in these activities, potentially resulting in biased study results. Dependent variable The dependent variable was BMI classification. All sam- ple respondents self-reported their height and weight,