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1.
BMC Pulm Med ; 21(1): 139, 2021 Apr 27.
Article in English | MEDLINE | ID: mdl-33906617

ABSTRACT

BACKGROUND: Millions of Americans are living in food deserts in the United States, however the role of the local food environment on COPD has not been studied. The aim of this study is to determine the association between food deserts and COPD-related outcomes. METHOD: In this cross-sectional analysis we linked data collected from SPIROMICS (SubPopulations and InteRmediate Outcome Measures in COPD Study) between 2010 and 2015 and food desert data, defined as an underserved area that lacks access to affordable healthy foods, from the Food Access Research Atlas. COPD outcomes include percentage of predicted forced expiratory volume in one second (FEV1%), St. George's Respiratory Questionnaire (SGRQ), COPD Assessment Test (CAT), 6-min walk distance test (6MWD), exacerbations, and air trapping. We used generalized linear mixed models to evaluate the association between living in food deserts and respiratory outcomes, adjusting for age, gender, race, education, income, marital status, BMI, smoking status, pack years, and urban status RESULTS: Among 2713 participants, 22% lived in food deserts. Participants living in food deserts were less likely to be white and more likely to have a lower income than those who did not live in food deserts. In the adjusted model controlling for demographics and individual income, living in food deserts was associated lower FEV1% (ß = - 2.51, P = 0.046), higher air trapping (ß = 2.47, P = 0.008), worse SGRQ (ß = 3.48, P = 0.001) and CAT (ß = 1.20, P = 0.003) scores, and 56% greater odds of severe exacerbations (P = 0.004). Results were consistent when looking at food access alone, regardless of whether participants lived in low income areas. CONCLUSIONS: Findings suggest an independent association between food desert and food access alone with COPD outcomes. Health program planning may benefit from addressing disparities in access to food.


Subject(s)
Food , Pulmonary Disease, Chronic Obstructive , Aged , Cross-Sectional Studies , Female , Humans , Male , Middle Aged
2.
BMC Pulm Med ; 20(1): 63, 2020 Mar 14.
Article in English | MEDLINE | ID: mdl-32171269

ABSTRACT

BACKGROUND: Asthma is one of the conditions that contributes to the global burden of respiratory diseases and has been previously associated with diet intake. The goal of this study was to determine the relationship between diet, assessed by a developed score, and asthma in Peruvian children. METHODS: This study was a cross sectional analysis nested within an unmatched case-control study of children in two peri-urban communities of Lima, Peru. We evaluated 767 children and adolescents (573 with asthma, 194 controls) between 9 and 19 years. Diet was assessed using a food frequency questionnaire (FFQ), with food groups classified as "healthy" or "unhealthy". Asthma control, Lung function and atopy were assessed by Asthma Control Test, Spirometry and InmunoCAP 250 test, respectively. RESULTS: Mean age of participants was 13.8 years (SD 2.6). Mean diet score was 5 (SD 1.23; range 2-8). Healthy Diet Score was associated with asthma status [OR 0.83, 95% CI (0.72, 0.95), p = 0.009] in adjusted analysis. Thus, participants with higher HDS, had lower odds of asthma. In sensitivity analyses, when adjusting for atopy, results did not change significantly. [OR 0.85, 95% CI (0.72, 0.99); p = 0.04]. No association between the HDS and asthma control, FEV1, nor FeNO were observed. Atopy did not modify the association between diet and asthma outcomes. CONCLUSIONS: In our study cohort, better diet quality was associated with lower odds of asthma, but was not associated with asthma control. Diet modification may be a potential intervention to impact the increasing prevalence of this disease.


Subject(s)
Asthma/epidemiology , Diet, Healthy/statistics & numerical data , Hypersensitivity, Immediate/epidemiology , Adolescent , Asthma/physiopathology , Case-Control Studies , Child , Cross-Sectional Studies , Female , Forced Expiratory Volume , Humans , Linear Models , Logistic Models , Male , Multivariate Analysis , Peru/epidemiology , Prevalence , Risk Factors , Spirometry
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