Exploring Skin Pigmentation Adaptation: A Systematic Review on the Vitamin D Adaptation Hypothesis.

Understanding the genetic adaptations that occurred as humans migrated out of Africa to higher latitudes helps explain on a population-wide level how UV radiation (UVR) exposure will have varying consequences and benefits in patients of different skin pigmentations. It has been hypothesized that the need for efficient vitamin D synthesis was the primary driver for the skin-lightening process that evolutionarily occurred as humans migrated to higher latitudes. This review analyzes the level of support for the hypothesis that skin lightening occurred to enable adequate vitamin D synthesis in populations that migrated to areas with less UVR. Our literature search supported the hypothesis that through natural selection and intricate genetic adaptations, humans who migrated to areas with lower levels of UVR underwent a skin-lightening process to avoid the consequences of vitamin D deficiency. Our review includes an analysis of migration patterns out of Africa and how these affected pigmentation genes that are found in certain ethnic populations can be used to better understand this critical adaptation process when counseling patients on the need for sun protection.

Applications and Best Practices for Geospatial Analysis Research in Dermatology.

Dermatologic diseases often exhibit distinct geographic patterns, underscoring the significant role of regional environmental, genetic, and sociocultural factors in driving their prevalence and manifestations. Geographic information and geospatial analysis enable researchers to investigate the spatial distribution of adverse health outcomes and their relationship with socioeconomic and environmental risk factors that are inherently geographic. Health geographers and spatial epidemiologists have developed numerous geospatial analytical tools to collect, process, visualize, and analyze geographic data. These tools help provide vital spatial context to the comprehension of the underlying dynamics behind health outcomes. By identifying areas with high rates of dermatologic disease and areas with barriers to access to quality dermatologic care, findings from studies utilizing geospatial analysis can inform the design and targeting of policy and intervention to help improve dermatologic healthcare outcomes and promote health equity. This article emphasizes the significance of geospatial data and analysis in dermatology research. We explore the common processes in data acquisition, harmonization, and geospatial analytics while conducting spatially and dermatologically relevant research. The article also highlights the practical application of geospatial analysis through instances drawn from the dermatology literature.

Risk factors for pediatric intoxications in the prehospital setting. A geospatial survey.

Background: Socioeconomic factors and the COVID-19 pandemic influence children's physical and mental health. We aimed to investigate the association between a census tract's median household income [MHI in United States Dollars ($)] and pediatric intoxications in Rhode Island, the smallest state in the United States of America. Geographical hotspots, as well as interactions with the COVID-19 pandemic, should be identified. Methods: This study is a retrospective analysis of ambulance calls for pediatric (<18 years) intoxication in Rhode Island between March 1st, 2018, and February 28th, 2022. March 1st, 2020 was considered the beginning of the COVID-19 pandemic. Prehospital data were joined with information from the United States Census Bureau. The census tracts' case counts and MHI were examined using Poisson regression. Geographical clusters were identified with the Global Moran's I and local indicators of spatial association tests in ArcGIS Pro (Esri Corporation, Redlands, CA). Results: Inclusion criteria were met by 208 incidents (48% female, median age 16 (IQR 15 to 17) years). The regression model showed a 0.6% increase (IRR 1.006, 95% CI [1.002, 1.01], p = 0.003) in pediatric intoxications for every $ 1,000 increase in MHI. Interaction analysis showed that the effect of MHI was less pronounced during the pandemic (IRR 0.98, 95% CI [0.964, 0.997], p = 0.02). Thirty-four (14%) of the 244 census tracts contributed to geographical clusters, which changed after the onset of the pandemic. Conclusion: Higher median household income could be a risk factor for pediatric intoxications. Geographical hotspots changed with the pandemic.

Socioeconomic Risk Factors for Pediatric Out-of-hospital Cardiac Arrest: A Statewide Analysis.

INTRODUCTION: Economic hardship is a major threat to children's health, implying that pediatric out-of-hospital cardiac arrest (pOHCA) might be promoted by lower incomes and child poverty. To target resources, it is helpful to identify geographical hotspots. Rhode Island is the smallest state by area in the United States of America. It has one million inhabitants and is comparable to many larger cities worldwide. We aimed to investigate the possible associations of pOHCA with economic factors and the coronavirus 2019 (COVID-19) pandemic. Our goal was to identify high-risk areas and evaluate whether the COVID-19 pandemic had an influence on delays in prehospital care. METHODS: We analyzed all pOHCA cases (patients <18 years of age) in Rhode Island between March 1, 2018-February 28, 2022. We performed Poisson regression with pOHCA as dependent and economic risk factors (median household income [MHI] and child poverty rate from the US Census Bureau) as well as the COVID-19 pandemic as independent variables. Hotspots were identified using local indicators of spatial association (LISA) statistics. We used linear regression to assess the association of emergency nedical services-related times with economic risk factors and COVID-19. RESULTS: A total of 51 cases met our inclusion criteria. Lower MHIs (incidence-rate ratio [IRR]) 0.99 per $1,000 MHI; P=0.01) and higher child poverty rates (IRR 1.02 per percent; P=0.02) were significantly associated with higher numbers of ambulance calls due to pOHCA. The pandemic did not have a significant influence (IRR 1.1; P=0.7). LISA identified 12 census tracts as hotspots (P<0.01). The pandemic was not associated with delays in prehospital care. CONCLUSION: Lower median household income and higher child poverty rate are associated with higher numbers of pediatric out-of-hospital cardiac arrest.

Increases in Ambulance Call Volume Are an Early Warning Sign of Major COVID-19 Surges in Children.

Background: Infectious diseases, including COVID-19, have a severe impact on child health globally. We investigated whether emergency medical service (EMS) calls are a bellwether for future COVID-19 caseloads. We elaborated on geographical hotspots and socioeconomic risk factors. Methods: All EMS calls for suspected infectious disease in the pediatric population (under 18 years of age) in Rhode Island between 1 March 2018 and 28 February 2022 were included in this quasi-experimental ecological study. The first of March 2020 was the beginning of the COVID-19 pandemic. We used the 2020 census tract and the most recent COVID-19 data. We investigated associations between pediatric EMS calls and positive COVID-19 tests with time series analysis and identified geographical clusters using local indicators of spatial association. Economic risk factors were examined using Poisson regression. Results: We included 980 pediatric ambulance calls. Calls during the omicron wave were significantly associated with increases in positive COVID-19 tests one week later (p < 0.001). Lower median household income (IRR 0.99, 95% CI [0.99, 0.99]; p < 0.001) and a higher child poverty rate (IRR 1.02, 95% CI [1.02, 1.02]; p < 0.001) were associated with increased EMS calls. Neighborhood hotspots changed over time. Conclusion: Ambulance calls might be a predictor for major surges of COVID-19 in children.

Healthcare accessibility in preconflict Syria: a comparative spatial analysis.

INTRODUCTION: There is scarce information about the allocation of health resources in Syria. Pre-existing inequalities were further intensified after the 2011 conflict which displaced over 50% of the population. This study provides an analysis of health inequalities in Syria focusing on spatial access to public hospitals and employs data from 2010, just prior to the outbreak of conflict. Establishing a preconflict snapshot of the health system could serve as a helpful baseline assessment for future studies to measure the impact of the conflict on the health system. Such information could also offer systematic data to guide postconflict reconstruction efforts. METHODS: We compared two methods to quantify the inpatient bed access: provider to population ratio (PPR) and two-step floating catchment area (2SFCA) method. We compared PPR calculated at the governorate level with population weighted 2SFCA score calculated at a resolution of 2 km by 2 km. We then aggregated at the governorate level, tested multiple catchment sizes and calculated Gini coefficient for each governorate. RESULTS: We found high inequality in access to public hospitals across and within governorates, especially in the north and eastern regions, where all governorates ranked in the lowest two quintiles using both PPR and 2SFCA. Relatively small governorates in the west and the south had higher spatial access and less inequality. Testing variability in catchment size showed that even at 125 km catchment, 65% of the country had accessibility below national average. CONCLUSION: Methodologically, the use of 2SFCA provided more nuanced insights about hospital bed allocation than PPR. 2SFCA was able to account for the cross-boundary effect and road network quality. Realistic representation of health accessibility is possible in data-scarce settings such as Syria and could be adapted to assess health access inequalities in conflict and postconflict settings.