Analysis
This research reviewed the relationship amongst the frequency away from carrying excess fat (founded changeable) and put of quarters (main explanatory changeable) changing for carrying excess fat chance factors along with decades, sex, degree, work reputation, marital status, and you will everyday use of SSBs . Even more study browsed sex differences by-place out of quarters. Detailed analysis projected market, behavioural, and contextual functions of the try and Pearson’s \(x\) 2 evaluating were utilized to decide differences between communities. Loads available with each questionnaire were used to help you estimate frequency out-of being obese in order to make up prospective nonresponse bias and alternatives opportunities. Brand new prevalence from obesity are estimated by place of quarters (i.e., New york, the country of Colombia, and you will head Colombian urban centers) and by sex. Personal survey loads on ENSIN was associate of the Colombia inhabitants based on the 2005 Colombia Federal Census . Loads on Ny CHS had been associate of the Nyc adult society from the sex, race/ethnicity, age, cellular telephone style of and you may borough from house according to the 2015 Western People Survey .
Unadjusted and you will bivariate regressions were used to explore the fresh relationships between being obese and various correlates. The series out-of regression patterns (parallel designs having obesity as the outcome) can be follows. Design step one compared immigrant Colombians living in Ny in the place of nonimmigrant Colombians surviving in their house nation. Model dos checked the connection between carrying excess fat and place away from house, evaluating immigrant Colombians located in New york versus nonimmigrant Colombians staying in fundamental Colombian locations only in order to discuss distinctions unique so you can staying in an urban context. Designs 3 and you will cuatro understood sex-certain contacts anywhere between obesity and place out-of household. All patterns adjusted to possess years, sex, studies level, employment standing, relationship reputation, and each day SSB application.
Analyses had been did having fun with SAS Enterprise Book (version eight.1) and you can SAS-callable SUDAAN (adaptation eleven.0, Lookup Triangle Institute, Cary, NC) to adjust for complex examples, taking into account clustering of data, services of your studies structure, decide to try weights, and you can shed research. Results are shown because Pr using their respective 95% depend on periods (95% CI). Advertising depicted the fresh new proportion away from predict odds determined regarding weighted multivariable logistic regression designs, utilising the PREDMARG and PRED_EFF statements into the SUDAAN . All mathematical examination was basically one or two-sided at a significance amount of less than 0.05.
Results
Obesity was defined as BMI ? 30 kg/m 2 (yes/no) for the analysis. BMI was calculated from self-reported height and weight in the NYC CHS and measured height and weight in the ENSIN. Country of origin was self-reported in NYC CHS (i.e., Where were you born? Please tell me the country) and was used to identify Colombian immigrants living in NYC. In addition to the adult population of Colombians residing in their home country, area of residence was used in the ENSIN survey to categorize Colombians that lived in the four main cities in the country (i.e., Bogota, Medellin, Barranquilla and Cali) for urban comparisons with the NYC sample. Age at time of survey was categorized as 18–39, 40–59, and 60 years or over. Education was classified as less than high school, some college, and college graduate. Employment was categorized as formally employed (i.e., full-time or part-time), self-employed, and unemployed (i.e., this variable excludes individuals who are not in the labor force because they are students, homemakers, retired or unable to work). Marital status was dichotomized as married or living together versus divorced, widowed, separated or never married. Frequency of SSB consumption per day was captured in both surveys and was dichotomized as none or
Carrying excess fat prevalence
Numbers step one and you may 2 show new weighted prevalence out-of being obese into the the entire try and you will inside sex teams by place regarding house. The prevalence out-of obesity certainly Colombian immigrants located in Nyc (twenty-five.5%; 95% CI 20.5, 30.2) try rather high than the nonimmigrant Colombians living in their home nation (18.9%; 95% CI 18.5, 19.4) and also in an element of the towns and cities (19.1%; 95% CI 18.0, 19.8). There have been together with distinctions by sex for some teams. Colombian immigrant dudes surviving in New conhecer mulheres Moldavo york (twenty five.0%; 95% CI 17.3, 34.7) got a considerably higher prevalence out-of carrying excess fat than the nonimmigrant Colombian dudes nation-wide (14.5%; 95% CI thirteen.9, fifteen.2) plus part of the locations (15.8%; 95% CI fourteen.2, 16.8). not, there were no tall differences among Colombian immigrant women living in Nyc (twenty five.8%; 95% CI 19.six, 33.1) compared to the nonimmigrant Colombian female living around the Colombia (22.7%; 95% CI 22.0, 23.4) or in the main urban centers (21.7%; 95% CI 20.3, 23.2).