A multiscale analysis of social and spatial determinants of cancer and noncancer hazards from on-road air pollution in Texas.

Evidence on environmental justice studies linking adverse health effects and on-roadair pollution showing spatial nonstationarity is limited.This study uses cancer and noncancer risk estimates from on-road sources of hazardous air pollutants modeled by the National-Scale Air Toxics Assessment (NATA) at the census tract (N = 5265) level and sociodemographic variables from U.S. Census Bureau to examine the nonstationarity spatial relationship by comparing aspatial and spatial regression modelsglobal ordinary least squares, spatial error model, geographically weighted regression, and multiscale geographically weighted regression. At first glance, census tracts within the highest quartile of cancer and noncancer risks were clustered in the major urban areas. Spatial regression indicates that cancer and non-cancer risk were associated with census tract level percentages of Black, Indigenous, and People of Color (BIPOC). These findings can serve as geospatial guidance for intervening in the processes that drive socio-spatial disparity in air pollution exposure.

Racial/Ethnic Heterogeneity and Rural-Urban Disparity of COVID-19 Case Fatality Ratio in the USA: a Negative Binomial and GIS-Based Analysis.

The 2019 coronavirus disease (COVID-19) has exacerbated inequality in the United States of America (USA). Black, indigenous, and people of color (BIPOC) are disproportionately affected by the pandemic. This study examines determinants of COVID-19 case fatality ratio (CFR) based on publicly sourced data from January 1 to December 18, 2020, and sociodemographic and rural-urban continuum data from the US Census Bureau. Nonspatial negative binomial Poisson regression and geographically weighted Poisson regression were applied to estimate the global and local relationships between the CFR and predictors-rural-urban continuum, political inclination, and race/ethnicity in 2407 rural counties. The mean COVID-19 CFR among rural counties was 1.79 (standard deviation (SD) = 1.07; 95% CI 1.73-1.84) higher than the total US counties (M = 1.69, SD = 1.18; 95% CI: 1.65-1.73). Based on the global NB model, CFR was positively associated with counties classified as "completely rural" (incidence rate ratio (IRR) = 1.24; 95% CI: 1.12-1.39) and "mostly rural" (IRR = 1.26; 95% CI: 1.15-1.38) relative to "mostly urban" counties. Nonspatial regression indicates that COVID-19 CFR increases by a factor of 8.62, 5.87, 2.61, and 1.36 for one unit increase in county-level percent Blacks, Hispanics, American Indians, and Asian/Pacific Islanders, respectively. Local spatial regression shows CFR was significantly higher in rural counties with a higher share of BIPOC in the Northeast and Midwest regions, and political inclination predicted COVID-19 CFR in rural counties in the Midwest region. In conclusion, spatial and racial/ethnic disparities exist for COVID-19 CFR across the US rural counties, and findings from this study have implications for public health.

Housing conditions as predictors of common childhood illness: Evidence from Nigeria Demographic and Health Surveys, 2008-2018.

Several studies have examined the impacts of water, sanitation, hygiene, and general housing conditions on childhood health in developing countries. However, up-to-date knowledge and change pattern in common childhood illness prevalence over time are scarce in Nigeria. To contribute toward meeting the Sustainable Development Goals three and six, we used pooled data (N = 94,053) from the Nigeria Demographic Health Surveys from 2008 to 2018 to examine the trend and determinants of four childhood illnesses: diarrhea, fever, cough, and respiratory infection. Multivariate logistic regression was used to estimate the determinants of the four health outcomes. Our results indicate that between 2008 and 2018, the prevalence of childhood diarrhea, cough, and fever slowly declined. However, there was a drastic decline in childhood-related respiratory illness. Housing conditions, sanitation facilities, and water sources were significantly associated with childhood illness based on the logistic regression analysis. Based on our findings, we recommend general improvement in housing conditions that can eradicate childhood cough, fever, and respiratory infections.

Geographical patterns and effects of human and mechanical factors on road traffic crashes in Nigeria.

Road traffic crashes (RTCs) remain an issue of global concern particularly in Nigeria where over 80 percent of these crashes are accounted by human and mechanical factors (HM). Many geographic studies on RTCs, fatality and injury have largely focused on the spatial clustering and associative analysis of risk factors; with little known about the relative contribution of HM factors within the spatial context. Hence, this study applied a spatial approach to the effect of HM factors on RTCs, fatality and injury across the regions of Nigeria. The data for this study were obtained from the National Bureau of Statistics for the year 2017-2019 and were analysed using spatial analysis techniques such as Global Moran's I and spatial regression model. There was evidence of geographic clustering of RTCs, fatality and injury in Nigeria. On one hand, route violation and sleeping on steering were significant predictors in southern Nigeria while tyre burst was significant at the national level, in the north and rural areas. The use of mobile phone while driving was a significant predictor at the national level. On the other hand, overloading was associated with RTCs and injuries at the national level and northern Nigeria. Speed violation was a prominent risk factor across the country. The study, based on observed regional differentials, argues that extant laws and regulations on traffic safety should be strictly enforced to curtail RTCs in the country.

Regional variation and demographic factors associated with knowledge of malaria risk and prevention strategies among pregnant women in Nigeria.

Pregnant women and children are the most vulnerable populations for malaria infection. Yet, knowledge of risk, and preventive measures are poor among this population. Using the 2015 Nigeria Malaria Indicator Survey, we applied logit link function to estimate the associations of wealth status, educational attainment, and region of residence with malaria risk knowledge and prevention strategies (using a treated mosquito net and malaria drugs) among 739 Nigerian pregnant women aged 15-49 years. Urban women who had obtained a secondary school education (Adjusted odds ratio [aOR] = 2.12; 95% confidence interval [CI] 1.09-4) or higher (aOR = 8.31; 95% CI 3.2-22) had more knowledge of malaria risk. Urban women in the South-West (aOR = 5.02; [CI] 2.02-12.50) and South-East (aOR = 2.68; 95% CI 1.19-6.06) were more likely to use treated mosquito nets during pregnancy. Women in the urban South-West (aOR = 4.04; 95% CI 1.5-11) were more likely to use malaria drugs during pregnancy than those in the North-Central. A wide regional disparity in the knowledge of malaria risks and use of preventive measures exists. Thus, promoting equal access to malaria preventive measures as well as improving knowledge about malaria transmission by mosquitoes should be considered as essential components of ongoing malaria control and elimination efforts in Nigeria.

Geographic analysis of road accident severity index in Nigeria.

Before 2030, deaths from road traffic accidents (RTAs) will surpass cerebrovascular disease, tuberculosis, and HIV/AIDS. Yet, there is little knowledge on the geographic distribution of RTA severity in Nigeria. Accident Severity Index is the proportion of deaths that result from a road accident. This study analysed the geographic pattern of RTA severity based on the data retrieved from Federal Road Safety Corps (FRSC). The study predicted a two-year data from a historic road accident data using exponential smoothing technique. To determine spatial autocorrelation, global and local indicators of spatial association were implemented in a geographic information system. Results show significant clusters of high RTA severity among states in the northeast and the northwest of Nigeria. Hence, the findings are discussed from two perspectives: Road traffic law compliance and poor emergency response. Conclusion, the severity of RTA is high in the northern states of Nigeria, hence, RTA remains a public health concern.

Using GIS to detect cluster and spatial disparity in maternal health indicators: a need for social health interventions.

Maternal mortality remains a serious global health concern. Although global efforts have produced some encouraging results in some World Health Organization's health regions, disparities persist within many countries. Additionally, in many developing countries, inadequate documentation of various health events including maternal mortality and morbidity, make it difficult to determine the true extent of the problem. Maternal health indicators are therefore proxies used in estimating health status in developing countries. Using geospatial and geovisualization techniques, this study examines district level disparities in two maternal health indicators in Ghana antenatal care (ANC) visits and skilled birth attendance (SBA). The results reveal districts with complete lack of access to higher health care professionals and others with underutilization of antenatal services. The findings provide important input for targeting location-specific public health and maternal health interventions.