Background: Recent reports suggest that alcohol use may have a protective effect on obesity. This study explores association between obesity and alcohol consumption in the non-smoking U.S. adult population.Methods: We analyzed data on a total of 8,236 respondents who participated in the Third National Health and Nutrition Examination Survey. Body mass index (weight-kg/height-m²) was derived from measured height and weight data and categorized into: normal weight, overweight, and obese. Alcohol consumption was measured using following measures: history of drinking, binge drinking, quantity of drinks/day, frequency of drinking, and average volume of drinks/week.Results: Mean body mass index in this sample of non-smokers was 26.4 (95% CI: 26.1, 26.7). Approximately 46% of respondents were classified as current drinkers. Current drinkers had lower odds of obesity (Adjusted odds ratio = 0.73, 95% CI: 0.55, 0.97) as compared to non-drinkers. The odds of overweight and obesity were significantly greater among binge drinkers and those consuming four or more drinks/day. However, those who reported drinking one or two drinks per day had 0.46 (95% CI: 0.34, 0.62) and 0.59 (95% CI: 0.41, 0.86) times the odds of obesity, respectively. Similarly, the odds of obesity were significantly lower among those who reported drinking frequently and consuming less than five drinks per week. The association between overweight and other alcohol measures was less pronounced.Conclusion: The results suggest further exploring the possible role of moderate alcohol drinking in controlling body weight in adults.

Purpose: There are growing signs that the COVID‐19 virus has started to spread to rural areas and can impact the rural health care system that is already stretched and lacks resources. To aid in the legislative decision process and proper channelizing of resources, we estimated and compared the county‐level change in prevalence rates of COVID‐19 by rural‐urban status over 3 weeks. Additionally, we identified hotspots based on estimated prevalence rates.Methods: We used crowdsourced data on COVID‐19 and linked them to county‐level demographics, smoking rates, and chronic diseases. We fitted a Bayesian hierarchical spatiotemporal model using the Markov Chain Monte Carlo algorithm in R‐studio. We mapped the estimated prevalence rates using ArcGIS 10.8, and identified hotspots using Gettis‐Ord local statistics.Findings: In the rural counties, the mean prevalence of COVID‐19 increased from 3.6 per 100,000 population to 43.6 per 100,000 within 3 weeks from April 3 to April 22, 2020. In the urban counties, the median prevalence of COVID‐19 increased from 10.1 per 100,000 population to 107.6 per 100,000 within the same period. The COVID‐19 adjusted prevalence rates in rural counties were substantially elevated in counties with higher black populations, smoking rates, and obesity rates. Counties with high rates of people aged 25‐49 years had increased COVID‐19 prevalence rates.Conclusions: Our findings show a rapid spread of COVID‐19 across urban and rural areas in 21 days. Studies based on quality data are needed to explain further the role of social determinants of health on COVID‐19 prevalence.

The prevalence of asthma has been on the increase in the USA and worldwide. To understand the worsening epidemiological trends of asthma, this study analysed the data from the third National Health and Nutrition Examination Survey (NHANES III) to determine the prevalence and risk factors for asthma and wheezing among US adults.This analysis used data from 18,825 US adults aged ≥20 yrs who had participated in the NHANES III project. After excluding subjects with physician­diagnosed emphysema, a total of 18,393 subjects were included in the final analysis.The prevalence of current asthma (asthma) was 4.5% and the prevalence of wheezing in the previous 12 months (wheezing) was 16.4%. Mexican­Americans exhibited the lowest prevalence of asthma when compared with other race/ethnic groups. Multiple logistic regression analysis showed that Mexican­Americans were less likely to report asthma when compared to non­Hispanic whites. Low education level, female sex, current and past smoking status, pet ownership, lifetime diagnosis of physician­diagnosed hay fever and obesity were all significantly associated with asthma and/or wheezing. No significant effect of indoor air pollutants, as derived from the use of household heating/cooking appliances, on asthma and wheezing was observed in this study.In conclusion, this study observed racial/ethnic differences in the prevalence of asthma and wheezing and identified several important risk factors that may contribute to development and/or exacerbation of asthma and wheezing. Contrary to earlier reports, the proxy measures of indoor air pollution used in this study were not found to be associated with increased risk of asthma and wheezing.

Objectives Work-related asthma (WRA) is an important public health problem affecting one quarter of adults with asthma. Although cleaning substances are routinely used in hospitals, few studies have addressed their potential adverse respiratory health effects on healthcare professionals (HCPs). This study attempts to identify relationship between work-related exposure to cleaning-related chemicals and development of WRA among HCPs. Methods Of 5600 HCPs surveyed, 3650 responded to a validated questionnaire about their occupation, asthma diagnosis, variability of asthma symptoms at and away from work, and exposure to individual cleaning substances. Workplace asthma was defined as a categorical variable with four mutually exclusive categories: work-related asthma symptoms (WRAS), work-exacerbated asthma (WEA), occupational asthma (OA) and none. Multivariable logistic regression analysis was used to evaluate the association between self-reported use of cleaning substances and asthma outcomes among HCPs. Results Prevalences of WRAS, WEA and OA were 3.3%, 1.1% and 0.8%, respectively. The prevalence estimates were generally higher among female than male HCPs. The odds of WRAS and WEA increased in a dose-dependent manner for exposure in the longest job to cleaning agents and disinfectants/sterilants, respectively. For exposure in any job, the odds of WRAS were significantly elevated for both factor 1 (bleach, cleaners/abrasives, toilet cleaners, detergents and ammonia) and factor 2 (glutaraldehyde/ortho-phtaldehyde, chloramines and ethylene oxide). Significantly elevated odds of WEA were observed for exposure to bleach, factor 2 and formalin/formaldehyde. Exposure to chloramines was significantly associated with an almost fivefold elevated odds of OA. Conclusions HCPs are at risk of developing WRA from exposure to cleaning substances.

Rationale: Recent U.S. data suggest an increased risk of work-related asthma among health care workers, yet only a few specific determinants have been elucidated. Objectives: To evaluate associations of asthma prevalence with occupational exposures in a cross-sectional survey of health care professionals. Methods: A detailed questionnaire was mailed to a random sample (n = 5,600) of all Texas physicians, nurses, respiratory therapists, and occupational therapists with active licenses in 2003. Information on asthma symptoms and nonoccupational asthma risk factors obtained from the questionnaire was linked to occupational exposures derived through an industry-specific job-exposure matrix. Measurements: There were two a priori defined outcomes: (1) physician-diagnosed asthma with onset after entry into health care (“reported asthma”) and (2) “bronchial hyperresponsiveness–related symptoms,” defined through an 8-item symptom-based predictor. Main Results: Overall response rate was 66%. The final study population consisted of 862 physicians, 941 nurses, 968 occupational therapists, and 879 respiratory therapists (n = 3,650). Reported asthma was associated with medical instrument cleaning (odds ratio [OR], 2.22; 95% confidence interval [CI], 1.34–3.67), general cleaning (OR, 2.02; 95% CI, 1.20–3.40), use of powdered latex gloves between 1992 and 2000 (OR, 2.17; 95% CI, 1.27–3.73), and administration of aerosolized medications (OR, 1.72; 95% CI, 1.05–2.83). The risk associated with latex glove use was not apparent after 2000. Bronchial hyperresponsiveness–related symptoms were associated with general cleaning (OR, 1.63; 95% CI, 1.21–2.19), aerosolized medication administration (OR, 1.40; 95% CI, 1.06–1.84), use of adhesives on patients (OR, 1.65; 95% CI, 1.22–2.24), and exposure to a chemical spill (OR, 2.02; 95% CI, 1.28–3.21). Conclusions: The contribution of occupational exposures to asthma in health care professionals is not trivial, meriting both implementation of appropriate controls and further study.