Assuntos
Hematocolpia , Retenção Urinária , Feminino , Humanos , Hímen , Retenção Urinária/etiologiaRESUMO
OBJECTIVE: Examine associations between food insecurity and multiple demographic, socioeconomic, acculturation, social risk factor, and food access variables. DESIGN: Data are from Sinai Community Health Survey 2.0, a cross-sectional, population-based probability survey of adults. SETTING: Ten selected community areas in Chicago. PARTICIPANTS: Adults aged 18 years and over who completed the Household Food Security Scale (HFSS) portion of the survey were included in the analysis (nâ¯=â¯1,041). MAIN OUTCOME MEASURES: Food insecurity as defined by the HFSS was the dependent variable. Independent variables included multiple demographic, socioeconomic, acculturation, social risk factor, and food access variables. ANALYSIS: Multivariate logistic regression, along with a manual backward selection process, was used to examine predictors of food insecurity. A P of .05 was used to determine statistical significance. RESULTS: Respondents reporting English as their primary language (odds ratio [OR]â¯=â¯0.31; Pâ¯=â¯.002) had significantly lower odds of experiencing food insecurity. Respondents who reported feeling lonely (ORâ¯=â¯1.86; Pâ¯=â¯.024) had significantly higher odds of experiencing food insecurity. Emergency food use (ORâ¯=â¯3.89; Pâ¯=â¯.001) and food stamp benefit receipt (ORâ¯=â¯2.79; Pâ¯=â¯.001) were also associated with food insecurity. Race/ethnicity demonstrated a strong relationship with food insecurity in early models, but this relationship appeared to be mediated by language and social risk factors. In the final adjusted model, most demographic and socioeconomic variables, including race/ethnicity, gender, and education were not significantly associated with food insecurity. CONCLUSIONS AND IMPLICATIONS: The burden of food insecurity was not shared equally across populations. This analysis sheds light on significant predictors of food insecurity in several diverse communities in Chicago. Findings can help inform tailored interventions by guiding food assistance programs to those most in need.