Daikwon Han

Industrialized communities along the U.S. Gulf Coast face persistent respiratory health inequities that are shaped by cumulative environmental exposures an

Arsenic and atrazine are two water contaminants of high public health concern in Iowa. The occurrence of arsenic and atrazine in drinking water from Iowa’s private wells and public water systems was investigated over several decades. In this study, the percentages of detection and violation of regulations were compared over region, season, and water source, and factors affecting the detection and concentration of arsenic and atrazine were analyzed using a mixed-effects model. Atrazine contamination in drinking water was found to vary by region, depending on agricultural usage patterns and hydrogeological features. The annual median atrazine levels of all public water systems were below the drinking water standard of 3 ppb in 2001–2014. Around 40% of public water systems contained arsenic at levels > 1 ppb in 2014, with 13.8% containing arsenic at levels of 5–10 ppb and 2.6% exceeding 10 ppb. This unexpected result highlights the ongoing public health threat posed by arsenic in drinking water in Iowa, emphasizing the need for continued monitoring and mitigation efforts to reduce exposure and associated health risks. Additionally, an atrazine metabolite, desethylatrazine, should be monitored to obtain a complete account of atrazine exposure and possible health effects.

By 2050, one in five Americans will be 65 years and older. The growing proportion of older adults in the U.S. population has implications for many aspects of health including disaster preparedness. This study assessed correlates of disaster preparedness among community-dwelling minority older adults and explored unique differences for African American and Hispanic older adults. An electronic survey was disseminated to older minority adults 55+, between November 2020 and January 2021 (n = 522). An empirical framework was used to contextualize 12 disaster-related activities into survival and planning actions. Multivariate logistic regression models were stratified by race/ethnicity to examine the correlates of survival and planning actions in African American and Hispanic older adults, separately. We found that approximately 6 in 10 older minority adults did not perceive themselves to be disaster prepared. Medicare coverage was positively associated with survival and planning actions. Income level and prior experience with disaster were related to survival actions in the African American population. In conclusion, recognizing the gaps in disaster-preparedness in elderly minority communities can inform culturally sensitive interventions to improve disaster preparedness and recovery.

While COVID-19 vaccines have been available since December 2020 and efforts have been made to vaccinate the maximum population, a large number of people are continuing to be hesitant, prolonging the pandemic in the US. While most previous studies investigated social, economic, and demographic variables that are associated with COVID-19 vaccine hesitancy, we added ecological and technological variables to better understand the spatial variations of vaccine rates in the contiguous United States using spatial regression and geographically weighted regression (GWR) models. We aim to identify spatially varying social, ecological, and technological factors that are associated with COVID-19 vaccination rates, which can aid in identifying and strengthening the public health system and vaccination programs that can eventually facilitate and overcome vaccination hesitancy. We found six statistically significant predictors; two predictors, % Republican voters (r = 0.507, p < .001) and % Black population (r = −0.360, p < .001) were negatively correlated with the vaccination rates, whereas four remaining predictors, % Population with college degree (r = 0.229, p < 001), NRI Score (r = 0.131, p < .001), % Population with broadband access (r = 0.020, p < 001), and Health facilities per 10 000 population (r = 0.424, p < 001) were positively correlated with the vaccination rates at the county level. GWR results show spatially varying relationships between vaccination rate and explanatory variables, indicating the need for regional-specific public health policy. To achieve widespread vaccination, addressing social, ecological, and technological factors will be essential. We draw particular attention to the spatial variances even among positively and negatively associated factors. This research also calls for a reexamination of existing practices, including vaccination communication and other public health policies, local and national public health organizations, telecommunications agents, and mobilization of resources by the public and private sectors.

Although evidence suggests that successive climate disasters are on the rise, few studies have documented the disproportionate impacts on communities of color. Through the unique lens of successive disaster events (Hurricane Harvey and Winter Storm Uri) coupled with the COVID-19 pandemic, we assessed disaster exposure in minority communities in Harris County, Texas. A mixed methods approach employing qualitative and quantitative designs was used to examine the relationships between successive disasters (and the role of climate change), population geography, race, and health disparities-related outcomes. This study identified four communities in the greater Houston area with predominantly non-Hispanic African American residents. We used data chronicling the local community and environment to build base maps and conducted spatial analyses using Geographic Information System (GIS) mapping. We complemented these data with focus groups to assess participants’ experiences in disaster planning and recovery, as well as community resilience. Thematic analysis was used to identify key patterns. Across all four communities, we observed significant Hurricane Harvey flooding and significantly greater exposure to 10 of the 11 COVID-19 risk factors examined, compared to the rest of the county. Spatial analyses reveal higher disease burden, greater social vulnerability, and significantly higher community-level risk factors for both pandemics and disaster events in the four communities, compared to all other communities in Harris County. Two themes emerged from thematic data analysis: (1) Prior disaster exposure prepared minority populations in Harris County to better handle subsequent disaster suggesting enhanced disaster resilience, and (2) social connectedness was key to disaster resiliency. Long-standing disparities make people of color at greater risk for social vulnerability. Addressing climate change offers the potential to alleviate these health disparities.

Introduction and Aims: This study examined whether the introduction of a large number of off‐premise alcohol outlets into a city over a brief period of time could affect rates of violent crime.Design and Methods: The study analysed annual counts of violent crime across 172 US Census block groups in Lubbock, Texas from 2006 through 2011. Spatial Poisson models related annual violent crime counts within each block group to off‐premise and on‐premise alcohol outlets active during this time period as well as neighbourhood socio‐demographic characteristics. The effects of alcohol outlets were assessed both within block groups and across adjacent block groups.Results: On‐premise outlets had a small, significant positive association with violence within a given block group. A similar well‐supported local effect for off‐premise outlets was not found. However, the spatially lagged effect for off‐sale premises was well‐supported, indicating that greater densities of these outlets were related to greater rates of violent crime in adjacent areas.Discussion and Conclusions: While these analyses confirmed a previous time‐series analysis in finding no city‐wide effect of the increase in off‐premise outlets, they do suggest that such outlets in a local area may be related to violence in nearby geographic areas. They indicate the importance of examining neighbourhood‐specific effects of alcohol outlets on violence in addition to the city‐wide effects. They also present further evidence supporting the need to examine the differential effects of on‐sale and off‐sale premises.

It is well known that the conventional, automated geocoding method based on self-reported residential addresses has many issues. We developed a smartphone-assisted aerial image-based method, which uses the Google Maps application programming interface as a spatial data collection tool during the birth registration process. In this pilot study, we have tested whether the smartphone-assisted method provides more accurate geographic information than the automated geocoding method in the scenario when both methods can get the address geocodes. We randomly selected 100 well-geocoded addresses among women who gave birth in Alachua county, Florida in 2012. We compared geocodes generated from three geocoding methods: i) the smartphone-assisted aerial image-based method; ii) the conventional, automated geocoding method; and iii) the global positioning system (GPS). We used the GPS data as the reference method. The automated geocoding method yielded positional errors larger than 100 m among 29.3% of addresses, while all addresses geocoded by the smartphoneassisted method had errors less than 100 m. The positional errors of the automated geocoding method were greater for apartment/condominiums compared with other dwellings and also for rural addresses compared with urban ones. We conclude that the smartphone-assisted method is a promising method for perspective spatial data collection by improving positional accuracy.

Heavy industrialization has resulted in the contamination of soil by metals from anthropogenic sources in Anniston, Alabama. This situation calls for increased public awareness of the soil contamination issue and better knowledge of the main factors contributing to the potential sources contaminating residential soil. The purpose of this spatial epidemiology research is to describe the effects of physical factors on the concentration of lead (Pb) in soil in Anniston AL, and to determine the socioeconomic and demographic characteristics of those residing in areas with higher soil contamination. Spatial regression models are used to account for spatial dependencies using these explanatory variables. After accounting for covariates and multicollinearity, results of the analysis indicate that lead concentration in soils varies markedly in the vicinity of a specific foundry (Foundry A), and that proximity to railroads explained a significant amount of spatial variation in soil lead concentration. Moreover, elevated soil lead levels were identified as a concern in industrial sites, neighborhoods with a high density of old housing, a high percentage of African American population, and a low percent of occupied housing units. The use of spatial modelling allows for better identification of significant factors that are correlated with soil lead concentrations.