Sentence examples for obesity sample from inspiring English sources
c = Sociodemographic information for the obesity sample represents the clinical sample of severely obese children (n = 106) used for comparisons across disease categories, given the unavailability of sociodemographic information for the obese and overweight community samples.
The obesity sample (n = 63) utilized for HRQOL comparisons across the disease clusters was derived from a community sample classified as obese according to Body Mass Index (BMI) cut points [ 27].
The discrepant findings between those and our studies might be attributable to differences of the criteria adopted for the definition of the metabolic syndrome or obesity, sample size, and methodological limitations.
In addition, another study also mentioned that the amounts of Bifidobacterium and Ruminococcus decreased in obesity samples [ 38].
In another study, amounts of Archaea and Methanobacteriales were positively correlated with obesity [ 37], and their amounts in obesity samples decreased or disappeared after gastric bypass surgery.
By combing the differential expression profiles from multiple datasets and the NOT2D network, the top 5 scoring active modules were identified in the obesity samples as well as in T2D.
In fact, there are a whole slew of academic articles that employ faulty logic (many of which cite this article to make their own claim on lesbian obesity), small sample sizes, inept research questions, and arguably homophobic and fat-phobic hypotheses, in an attempt to prove that lesbians are an overweight and obese population, and that we have BMIs higher than the average heterosexual woman.
The differences can be explained on the basis of BMI and WHR cutoffs used to categorize obesity, ethnicity, sample size, and behavioral and environmental factors.
In our sample, obesity and central obesity were relatively common (∼20%), as would be expected for a posttransitional urban population such as that of Santiago, Chile.
Associations between PM2.5 and CRP were consistently, and often significantly, elevated among the 8 individuals with diabetes (26 repeated samples), 14 individuals with obesity (41 repeated samples), and 4 individuals with concurrent diabetes, obesity, and hypertension (14 repeated samples).
