PURPOSE: To examine behavioral patterns and sociodemographic predictors of diet, inactivity, and tobacco use among a diverse sample of residents from low-income housing developments. DESIGN: In this cross-sectional survey study, households and residents were randomly selected using multistage cluster sampling. Setting . The study was conducted in 20 low-income housing developments in the Boston, Massachusetts, metropolitan area. SUBJECTS: Subjects were 828 residents who completed the survey (response rate = 49.3%). Forty-one percent of participants were Hispanic and 38% were non-Hispanic Black. Measures . Outcomes measured were diet, inactivity, and tobacco use. Predictors measured were age, race/ethnicity, gender, education, country in which the subject was born, language spoken, and financial hardship. Analysis . Logistic regression analyses were conducted to examine the association of three health behaviors with sociodemographic factors. RESULTS: Age, gender, language spoken, and financial hardship showed significant relationships with all three behaviors. For example, those who reported less financial hardship (odds ratio [OR] = 1.75) were more likely to eat healthier. Residents who spoke no English, or at least one language in addition to English, were significantly more likely to report healthier eating (OR = 2.78 and 3.30, respectively) than those who spoke English only. Men were significantly more likely to report less healthy eating (OR = 0.65) than were women. Similar trends emerged for inactivity and tobacco use. CONCLUSION: Effective health promotion interventions in low-income housing developments that leverage protective factors while addressing risk factors have the potential to reduce income-related health disparities in these concentrated resource-deprived neighborhoods.
PURPOSE: To examine behavioral patterns and sociodemographic predictors of diet, inactivity, and tobacco use among a diverse sample of residents from low-income housing developments. DESIGN: In this cross-sectional survey study, households and residents were randomly selected using multistage cluster sampling. Setting . The study was conducted in 20 low-income housing developments in the Boston, Massachusetts, metropolitan area. SUBJECTS: Subjects were 828 residents who completed the survey (response rate = 49.3%). Forty-one percent of participants were Hispanic and 38% were non-Hispanic Black. Measures . Outcomes measured were diet, inactivity, and tobacco use. Predictors measured were age, race/ethnicity, gender, education, country in which the subject was born, language spoken, and financial hardship. Analysis . Logistic regression analyses were conducted to examine the association of three health behaviors with sociodemographic factors. RESULTS: Age, gender, language spoken, and financial hardship showed significant relationships with all three behaviors. For example, those who reported less financial hardship (odds ratio [OR] = 1.75) were more likely to eat healthier. Residents who spoke no English, or at least one language in addition to English, were significantly more likely to report healthier eating (OR = 2.78 and 3.30, respectively) than those who spoke English only. Men were significantly more likely to report less healthy eating (OR = 0.65) than were women. Similar trends emerged for inactivity and tobacco use. CONCLUSION: Effective health promotion interventions in low-income housing developments that leverage protective factors while addressing risk factors have the potential to reduce income-related health disparities in these concentrated resource-deprived neighborhoods.
Entities:
Keywords:
African Americans; Health Behavior; Health Promotion; Health focus: fitness/physical activity, nutrition, and smoking control; Immigrants; Low-Income Population; Manuscript format: research; Outcome measure: behavioral; Prevention Research; Public Housing; Research purpose: modeling/relationship testing; Setting: local community; Study design: nonexperimental; Target population age: adults; Target population circumstances: education/income level, geographic location, and race/ethnicity
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