scholarly journals Inter- and independent effects of region and race/ethnicity on variety of fruit and vegetable consumption in the USA: 2011 Behavioral Risk Factor Surveillance System (BRFSS)

2015 ◽  
Vol 19 (1) ◽  
pp. 104-113 ◽  
Author(s):  
Nicole Tichenor ◽  
Zach Conrad
Keyword(s):  
Surveillance System ◽  
Vegetable Consumption ◽  
Fruit And Vegetable Consumption ◽  
Behavioral Risk ◽  
Fruit And Vegetable ◽  
Behavioral Risk Factor ◽  
Behavioral Risk Factor Surveillance ◽  
Risk Factor Surveillance ◽  
The Usa ◽  
Race Ethnicity

AbstractObjective(i) To estimate the independent and combined effects of race/ethnicity and region on the variety of fruits and vegetables consumed in the USA in 2011; and (ii) to assess whether and to what extent race/ethnicity and region may synergistically influence variety of fruit and vegetable consumption.DesignCross-sectional analysis. Multivariate logistic regression predicted the likelihood of meeting fruit and vegetable variety indicators independently and in combination for each race/ethnicity and region. Interaction effects models were used to test for interaction effects between race/ethnicity and region on fruit and vegetable variety.SettingThe 2011 Behavioral Risk Factor Surveillance System (BRFSS).SubjectsThe sample consisted of 275 864 adult respondents.ResultsFewer than half of respondents consumed fruit and all vegetable subcategories at least once weekly. The adjusted likelihood of meeting fruit and vegetable variety indicators varied significantly by race/ethnicity and region (P<0·05). Significant interactions between race/ethnicity and region were found for at least once weekly consumption of beans, orange vegetables, all vegetables, and fruit and all vegetables (P<0·05).ConclusionsOur results reinforce previous findings that the variety of vegetable consumption is lacking and is particularly evident among some population subgroups, such as non-Hispanic blacks in the Midwest USA, who may benefit from targeted dietary interventions.

scholarly journals Risk Factors for COVID-19-associated hospitalization: COVID-19-Associated Hospitalization Surveillance Network and Behavioral Risk Factor Surveillance System

2020 ◽  
Author(s):  
Jean Y. Ko ◽  
Melissa L. Danielson ◽  
Machell Town ◽  
Gordana Derado ◽  
Kurt J. Greenland ◽  
...  
Keyword(s):  
Surveillance System ◽  
Severe Obesity ◽  
Medical Condition ◽  
Behavioral Risk ◽  
Behavioral Risk Factor ◽  
Surveillance Network ◽  
Behavioral Risk Factor Surveillance ◽  
Risk Factor Surveillance ◽  
Race Ethnicity ◽  
Underlying Medical Condition

Background: Identification of risk factors for COVID-19-associated hospitalization is needed to guide prevention and clinical care. Objective: To examine if age, sex, race/ethnicity, and underlying medical conditions is independently associated with COVID-19-associated hospitalizations. Design: Cross-sectional. Setting: 70 counties within 12 states participating in the Coronavirus Disease 2019-Associated Hospitalization Surveillance Network (COVID-NET) and a population-based sample of non-hospitalized adults residing in the COVID-NET catchment area from the Behavioral Risk Factor Surveillance System. Participants: U.S. community-dwelling adults (≥18 years) with laboratory-confirmed COVID-19-associated hospitalizations, March 1- June 23, 2020. Measurements: Adjusted rate ratios (aRR) of hospitalization by age, sex, race/ethnicity and underlying medical conditions (hypertension, coronary artery disease, history of stroke, diabetes, obesity [BMI ≥30 kg/m2], severe obesity [BMI≥40 kg/m2], chronic kidney disease, asthma, and chronic obstructive pulmonary disease). Results: Our sample included 5,416 adults with COVID-19-associated hospitalizations. Adults with (versus without) severe obesity (aRR:4.4; 95%CI: 3.4, 5.7), chronic kidney disease (aRR:4.0; 95%CI: 3.0, 5.2), diabetes (aRR:3.2; 95%CI: 2.5, 4.1), obesity (aRR:2.9; 95%CI: 2.3, 3.5), hypertension (aRR:2.8; 95%CI: 2.3, 3.4), and asthma (aRR:1.4; 95%CI: 1.1, 1.7) had higher rates of hospitalization, after adjusting for age, sex, and race/ethnicity. In models adjusting for the presence of an individual underlying medical condition, higher hospitalization rates were observed for adults ≥65 years, 45-64 years (versus 18-44 years), males (versus females), and non-Hispanic black and other race/ethnicities (versus non-Hispanic whites). Limitations: Interim analysis limited to hospitalizations with underlying medical condition data. Conclusion: Our findings elucidate groups with higher hospitalization risk that may benefit from targeted preventive and therapeutic interventions.

scholarly journals Risk Factors for Coronavirus Disease 2019 (COVID-19)–Associated Hospitalization: COVID-19–Associated Hospitalization Surveillance Network and Behavioral Risk Factor Surveillance System

2020 ◽  
Author(s):  
Jean Y Ko ◽  
Melissa L Danielson ◽  
Machell Town ◽  
Gordana Derado ◽  
Kurt J Greenlund ◽  
...  
Keyword(s):  
Risk Factors ◽  
Surveillance System ◽  
Severe Obesity ◽  
Behavioral Risk ◽  
Behavioral Risk Factor ◽  
Surveillance Network ◽  
Hospitalization Rates ◽  
Behavioral Risk Factor Surveillance ◽  
Risk Factor Surveillance ◽  
Race Ethnicity

Abstract Background Data on risk factors for coronavirus disease 2019 (COVID-19)–associated hospitalization are needed to guide prevention efforts and clinical care. We sought to identify factors independently associated with COVID-19–associated hospitalizations. Methods Community-dwelling adults (aged ≥18 years) in the United States hospitalized with laboratory-confirmed COVID-19 during 1 March–23 June 2020 were identified from the COVID-19–Associated Hospitalization Surveillance Network (COVID-NET), a multistate surveillance system. To calculate hospitalization rates by age, sex, and race/ethnicity strata, COVID-NET data served as the numerator and Behavioral Risk Factor Surveillance System estimates served as the population denominator for characteristics of interest. Underlying medical conditions examined included hypertension, coronary artery disease, history of stroke, diabetes, obesity, severe obesity, chronic kidney disease, asthma, and chronic obstructive pulmonary disease. Generalized Poisson regression models were used to calculate adjusted rate ratios (aRRs) for hospitalization. Results Among 5416 adults, hospitalization rates (all reported as aRR [95% confidence interval]) were higher among those with ≥3 underlying conditions (vs without) (5.0 [3.9–6.3]), severe obesity (4.4 [3.4–5.7]), chronic kidney disease (4.0 [3.0–5.2]), diabetes (3.2 [2.5–4.1]), obesity (2.9 [2.3–3.5]), hypertension (2.8 [2.3–3.4]), and asthma (1.4 [1.1–1.7]), after adjusting for age, sex, and race/ethnicity. Adjusting for the presence of an individual underlying medical condition, higher hospitalization rates were observed for adults aged ≥65 or 45–64 years (vs 18–44 years), males (vs females), and non-Hispanic black and other race/ethnicities (vs non-Hispanic whites). Conclusions Our findings elucidate groups with higher hospitalization risk that may benefit from targeted preventive and therapeutic interventions.

Sign in / Sign up

Export Citation Format

Share Document