Effect of Social Vulnerability on Cocaine-Related Mortality Rates in U.S. Counties.

Cocaine-related mortality rates have risen sharply since 2013 and social vulnerability is a crucial indicator for drug-related mortality rates. Therefore, the purpose of this study was to investigate the relationship between social vulnerability and cocaine-related mortality rates in U.S. counties. The Data were collected from the CDC WONDER, CDC's Social Vulnerability Index (CDC's SVI), and American Community Survey (ACS). The Data were analyzed by spatial autoregression models. According to present results, first, counties with social vulnerability (socioeconomic) were positively related to higher rates of cocaine overdose death (spatial lag: B = 0.323, p < .05; spatial error: B = 0.513, p < .01). Second, counties with social vulnerability (minority status & language) were negatively related to higher rates of cocaine overdose death (spatial lag: B = -0.233, p < .05). Third, counties with social vulnerability (housing type & transportation) were positively related to higher rates of cocaine overdose death (spatial lag: B = 0.413, p < .001; spatial error: B = 0.378, p < .001). In conclusion, the spread of cocaine overdose on U.S. counties with social vulnerabilities demonstrated a disproportionate burden of cocaine-related mortality.

A spatial analysis of the association between social vulnerability and the cumulative number of confirmed deaths from COVID-19 in United States counties through November 14, 2020.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) is classified as a natural hazard, and social vulnerability describes the susceptibility of social groups to potential damages from natural hazards. Therefore, the objective of this study was to examine the association between social vulnerability and the cumulative number of confirmed COVID-19 deaths (per 100,000) in 3,141 United States counties. METHODS: The cumulative number of COVID-19 deaths was obtained from USA Facts. Variables related to social vulnerability were obtained from the Centers for Disease Control and Prevention Social Vulnerability Index and the 2018 5-Year American Community Survey. Data were analyzed using spatial autoregression models. RESULTS: Lowest income and educational level, as well as high proportions of single parent households, mobile home residents, and people without health insurance were positively associated with a high cumulative number of COVID-19 deaths. CONCLUSION: In conclusion, there are regional differences in the cumulative number of COVID-19 deaths in United States counties, which are affected by various social vulnerabilities. Hence, these findings underscore the need to take social vulnerability into account when planning interventions to reduce COVID-19 deaths.

Gender Difference in the Association Between E-Cigarette Use and Depression among US Adults.

OBJECTIVES: The objective of this study was to determine the association between e-cigarette use and depression and examine how this association is different by gender among US adults. METHODS: Data from the 2017 Behavioral Risk Factor Surveillance System and Selected Metropolitan/Micropolitan Area Risk Trends was used, and included 174,351 of 230,875 US adults aged 18 years and older. Data were analyzed using the multivariate logistic regression models. RESULTS: After adjusting for age, race, education, income, marital status, employment status, smoking status, and physical activity, firstly, "current daily e-cigarette users" (AOR = 2.487, p < 0.001), "current non-daily e-cigarette users" (AOR = 1.623, p < 0.001), and "former e-cigarette users" (AOR = 1.573, p < 0.001) were associated with increased odds of depression compared with "never e-cigarette users." Secondly, women were associated with increased odds of depression compared with men (AOR = 1.797, p < 0.001). Finally, male "current daily e-cigarette users" (AOR = 1.366, p < 0.01) were associated with increased odds of depression compared with female "never e-cigarette users." CONCLUSION: Thus, even though women tend to be more vulnerable to depression compared with men, e-cigarette use was positively associated with depression among both men and women.

A spatial analysis of the effect of neighborhood contexts on cumulative number of confirmed cases of COVID-19 in U.S. Counties through October 20 2020.

COVID-19 has become a nationwide public health crisis in the United States and the number of COVID-19 cases is different by U.S. counties. Also, previous studies have reported that neighborhood contexts have an influence on health outcomes. Therefore, the objective of this study was to examine the association between neighborhood contexts and cumulative number of confirmed COVID-19 cases (per 100,000) in U.S. counties. Cumulative number of COVID-19 cases gained from USA FACTS and variables related to neighborhood contexts gained from the 2018 5-Year American Community Survey at the county level. Data were analyzed using spatial autoregressive models. According to the present results, firstly, larger population, high poverty rate, higher % of bachelor's degree, higher % of no health insurance, higher employment rate, higher % of manufacturing jobs, higher % of primary industry jobs, higher % of commute by drove alone, higher % of foreign born, higher % of Hispanic, and higher % of Black are positively associated with higher cumulative number of COVID-19 cases. Secondly, higher income, higher % of cash assistance recipient, higher % of SNAP recipient, higher unemployment rate, higher % of commute by walked, higher % of Asian, and higher % of senior citizen are negatively associated with higher cumulative number of COVID-19 cases. In conclusion, there exist geographical differences in cumulative number of COVID-19 cases in U.S. counties, which is influenced by various neighborhood contexts. Hence, these findings emphasize the need to take various neighborhood contexts into account when planning COVID-19 prevention.

Gender Difference in Longitudinal Social and Personal Factors Related to Frequency of Alcohol Consumption of South Korean Adults: A Fixed-Effects Model.

The purpose of this study was to examine the longitudinal social and personal factors related to frequency of alcohol consumption by South Korean adults focused on comparisons between men and women. Data came from the 2005-2016 Korea Welfare Panel Study. A fixed-effects model was used to examine the longitudinal correlations between dependent and independent variables. According to the present results, first, life satisfaction except for health satisfaction and marital status were not associated with alcohol consumption patterns by men. On the other hand, higher frequency of alcohol consumption by women was negatively associated with various life satisfaction variables and being married. Second, income levels were positively associated with higher frequency of alcohol consumption by men, whereas income levels were not associated with alcohol consumption by women. Finally, being employed was positively associated with higher frequency of alcohol consumption by both men and women. In conclusion, there were gender differences in how alcohol consumption was influenced by various sociocultural and life satisfaction factors in South Korea.

Multilevel Analysis of Socio-Demographic Disparities in Adulthood Obesity Across the United States Geographic Regions.

OBJECTIVES: The objective of this study was to examine the socio-demographic disparities in obesity among US adults across 130 metropolitan and micropolitan statistical areas. METHODS: This study used data from the 2015 Behavioral Risk Factor Surveillance System and Selected Metropolitan/Micropolitan Area Risk Trend of 159,827 US adults aged 18 years and older. Data were analyzed using the multilevel linear regression models. RESULTS: According to individual level analyses, socio-demographic disparities in obesity exist in the United States. Individuals with low socioeconomic status were associated with a higher body mass index. The participants from the Midwest United States tend to have higher body mass index than those who from the South. According to metropolitan and micropolitan statistical area level analyses, secondly, there were significant differences in obesity status between different areas and the relation of obesity with 5 socio-demographic factors varied across different areas. According to geospatial mapping analyses, even though obesity status by metropolitan and micropolitan statistical area level has improved overtime, differences in body mass index between United States regions are increasing from 2007 to 2015. CONCLUSION: Socio-demographic and regional disparities in obesity status persist among US adults. Hence, these findings underscore the need to take socio-environmental factors into account when planning obesity prevention on vulnerable populations and areas.

Time to First Cigarette and Self-Reported Health Among US Adult Smokers.

BACKGROUND: Numerous studies have reported that shorter time to first cigarette (TTFC) is linked to elevated risk for smoking-related morbidity. However, little is known about the influence of early TTFC on self-reported health among current smokers. Hence, the objective of this study was to examine the association between TTFC and self-reported health among US adult smokers. METHODS: Data came from the 2012-2013 National Adult Tobacco Survey (NATS). Current smokers aged 18 years and older (N = 3323) were categorized into 2 groups based on TTFC: ≤ 5 minutes (n = 1066) and >5 minutes (n = 2257). Propensity score matching (PSM) was used to control selection bias. RESULTS: After adjusting for sociodemographic and smoking behavior factors, current smokers with early TTFC had higher odds for poor health in comparison with current smokers with late TTFC in the prematching (adjusted odds ratio [AOR] = 1.65; 95% confidence interval [CI] = 1.31-2.08) and postmatching (AOR = 1.60; 95% CI = 1.22-2.09) samples. CONCLUSIONS: In conclusion, smokers with early TTFC were associated with increased risk of poor health in the United States. To reduce early TTFC, elaborate efforts are needed to educate people about harms of early TTFC and benefits of stopping early TTFC.

Effects of Different Types of Smoking Cessation Treatments for South Korean Adult Smokers without an Intention to Quit.

BACKGROUND: While there are many different ways to quit smoking, current methods are not equally successful. The objective of this study was to analyze the effects of different types of stop smoking treatment for South Korean adult smokers without an intention to quit. METHODS: This cross-sectional study used data of 14,174 adults (age 19 years and over) from the Korea national health and nutrition examination survey (2007-2012) who have experience of smoking. The data were analyzed using multiple logistic regression. RESULTS: According to multiple logistic regression analysis, the education and counseling plus prescription drug group (OR = 14.831, 95% CI = 1.256 to 175.136) and education and counseling plus NRT group (OR = 3.060, 95% CI = 1.971 to 4.748) were associated with increased odds of quitting success compared to the no intervention group. Second, the education and counseling group was associated with increased odds of quitting success compared to the no intervention group (OR = 4.944, 95% CI = 3.463 to 7.058). Third, education and counseling plus NRT (OR = 0.325, 95% CI = 0.161 to 0.657) and NRT alone (OR = 0.322, 95% CI = 0.175 to 0.593) were associated with decreased odds of quitting success compared to the group using prescription drug only. CONCLUSION: These findings suggest that an approach utilizing education and counseling plus prescription drugs is the most successful type of stop smoking treatment for South Korean adult smokers without an intention to quit.

E-cigarette Use and Smoking Cessation Among South Korean Adult Smokers: A Propensity Score-Matching Approach.

Research on the efficacy of e-cigarette use as a smoking cessation tool has yielded inconclusive results. Hence, the objective of this study was to identify the relationship between e-cigarette use and smoking cessation among South Korean adult smokers. This study used data from the sixth Korea National Health and Nutrition Examination Survey (2013-2015) of 2965 adult smokers aged 19 years and older. As statistical analysis methods, data were analyzed using the χ2 test and multiple logistic regression. Propensity score matching (PSM) was applied to control selection bias, and sociodemographic and smoking-linked factors were used as covariates in PSM. According to the multiple logistic regression analysis, adult smokers who had not used e-cigarettes were more likely to attempt to quit smoking than those who had used e-cigarettes in the prematching (OR = 1.58; 95% CI = 1.18-2.12) and postmatching (OR = 1.62; 95% CI = 1.08-2.44) samples. Thus, this study suggests that e-cigarette use among South Korean adult smokers was not related to smoking cessation.

Analysis of the Relationship between Sleep Duration and Body Mass Index in a South Korean Adult Population: A Propensity Score Matching Approach.

BACKGROUND: One-third of the present adults in South Korea are obese, and previous studies have demonstrated that sleep duration is considered a risk factor for obesity. Hence, I assessed the relationship between sleep duration and body mass index in a South Korean adult population. METHODS: This cross-sectional study consists of a representative sample of 4,218 South Korean adults (20-64 years) who participated in the sixth Korea National Health and Nutrition Examination Survey (2015). As statistical analysis methods, data were analyzed using chi-square test and multiple logistic regression. Propensity score matching (PSM) was applied to control selection bias, and obesity-related factors were used as covariates in PSM. RESULTS: According to the multiple logistic regression analysis, people who sleep for more than seven hours a day were less likely to be obese than those who sleep for less than seven hours a day in the pre-match (OR = 0.75, 95%CI = 0.65-0.88) and post-match (OR = 0.77, 95%CI = 0.65-0.90) samples. CONCLUSIONS: This finding suggests that South Korean adults who reported sleeping more than 7 hours a day were linked to decreased body mass index. Hence, the proper amount of sleep is necessary to reduce the prevalence of obesity in this population.