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Background: Transgenerational epigenetic risks associated with complex health outcomes, such as autism spectrum disorder (ASD), have attracted increasing attention. Transgenerational environmental risk exposures with potential for epigenetic effects can be effectively identified using space-time clustering. Specifically applied to ancestors of individuals with disease outcomes, space-time clustering characterized for vulnerable developmental stages of growth can provide a measure of relative risk for disease outcomes in descendants. Objectives: (1) Identify space-time clusters of ancestors with a descendent with a clinical ASD diagnosis and matched controls. (2) Identify developmental windows of ancestors with the highest relative risk for ASD in descendants. (3) Identify how the relative risk may vary through the maternal or paternal line. Methods: Family pedigrees linked to residential locations of ASD cases in Utah have been used to identify space-time clusters of ancestors. Control family pedigrees of none-cases based on age and sex have been matched to cases 2:1. The data have been categorized by maternal or paternal lineage at birth, childhood, and adolescence. A total of 3957 children, both parents, and maternal and paternal grandparents were identified. Bernoulli space-time binomial relative risk (RR) scan statistic was used to identify clusters. Monte Carlo simulation was used for statistical significance testing. Results: Twenty statistically significant clusters were identified. Thirteen increased RR (> 1.0) space-time clusters were identified from the maternal and paternal lines at a p-value < 0.05. The paternal grandparents carry the greatest RR (2.86–2.96) during birth and childhood in the 1950's–1960, which represent the smallest size clusters, and occur in urban areas. Additionally, seven statistically significant clusters with RR < 1 were relatively large in area, covering more rural areas of the state. Conclusion: This study has identified statistically significant space-time clusters during critical developmental windows that are associated with ASD risk in descendants. The geographic space and time clusters family pedigrees with over 3 + generations, which we refer to as a person's geographic legacy, is a powerful tool for studying transgenerational effects that may be epigenetic in nature. Our novel use of space-time clustering can be applied to any disease where family pedigree data is available. [ABSTRACT FROM AUTHOR]

Type 1 Diabetes (T1D) poses an increasing threat to public health, as incidence rates continue to rise globally. However, the etiology of T1D is still poorly understood, especially from the perspective of geography. The objective of this research is to examine the incidence of T1D among youth and to identify high-risk clusters and their association with socio-demographic and geographic variables. The study area was the entire state of Utah and included youth with T1D from birth to 19 years of age from 1998 to 2015 (n = 4161). Spatial clustering was measured both globally and locally using the Moran's I statistic and spatial scan statistic. Ordinary least squares (OLS) regression was used to measure the association of high-risk clusters with certain risk factors at the Census Block Group (CBG) level. The mean age at diagnosis was 9.3 years old. The mean incidence rate was 25.67 per 100,000 person-years (95% CI, 24.57–26.75). The incidence rate increased by 14%, from 23.94 per100,000 person-years in 1998 to 27.98 per 100,000 person-years in 2015, with an annual increase of 0.80%. The results of the spatial scan statistic found 42 high-risk clusters throughout the state. OLS regression analysis found a significant association with median household income, population density, and latitude. This study provides evidence that incidence rates of T1D are increasing annually in the state of Utah and that significant geographic high-risk clusters are associated with socio-demographic and geographic factors. • Determines incidence rates for Type 1 Diabetes among youth in Utah, U.S.A. • Identifies spatial hotspots of Type 1 Diabetes at the Census Block Group level. • Measures association of incidence rates with socio-demographic risk factors. • Measures association of incidence rates with geographic risk factors. [ABSTRACT FROM AUTHOR]

Introduction: Limited or uncertain availability of nutritionally adequate and safe foods affects the health of individuals. Because of its association with chronic health conditions, addressing food insecurity may improve health outcomes and decrease health-related costs. This study explores whether and how information seeking as captured by calls made to United Way 2-1-1 can be used to identify food-insecure areas and information deserts-communities with low proportions of residents accessing government food resources but with high rates of 2-1-1 calls for emergency food resources., Methods: Details regarding calls made to United Way of Salt Lake 2-1-1 for emergency food resources between 2014 and 2018 (n=63,221) were analyzed in 2019. Using GIS methods, areas with the highest number of calls for emergency food resources (hot spots) were identified; multinomial logistic regression was used to identify community-level sociodemographic predictors of food insecurity., Results: Areas with a smaller proportion of the population aged <18 years, more female householders, and more African Americans are associated with higher odds of being food-insecure., Conclusions: Patterns of information seeking about emergency food resources suggest that, despite statewide access to federal means-tested food programs, significant food needs remain. This novel approach in food insecurity research can help public health officials and health systems address an important social determinant of health by identifying areas vulnerable to food insecurity. In addition, this work may be useful in benchmarking food needs, information seeking, and replicating analyses where similar data are available., (Copyright © 2020 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)