Patterns of indoor radon concentrations, radon-hazard potential, and radon testing on a small geographic scale in Utah.

INTRODUCTION: Currently, there are no publicly-available estimates of indoor radon concentration at scales smaller than the county. Radon-hazard potential soil maps that reflect underlying geologic factors can be created at small geographic scale and linked to residential and census data. We determined the association between residential radon tests and high radon-hazard potential soil at the residential and block group levels using a large Utah-based dataset. We also identified characteristics of block groups with limited tests in the dataset. METHODS: We geocoded a dataset of residential radon tests obtained from 2001 to 2017 by a statewide educational program. We linked each location to maps of radon-hazard potential soil, the Environmental Protection Agency's (EPA) county radon zones. We also calculated the number of tests conducted in each block group and linked block groups to demographic data from the 2020 United States census. Log-linear and logistic models identified the association between residential home test results and 1) radon-hazard potential soil of each residence, 2) percent of residences on high radon-hazard potential soils in block groups, and 3) EPA's radon zones. We compared demographic characteristics among block groups with ≥5 or <5 residential tests in our dataset. RESULTS: Approximately 42% of homes in the dataset tested ≥4 pCi/L. We found significant positive associations for residential radon test results with 1) residential location on high radon-hazard potential soil and 2) block groups with >0% of residences on high radon-hazard potential soil. EPA radon zones were not associated with residential test results. Block groups with <5 tests had higher than the statewide median percentage of Hispanic residents (OR = 2.46, 95% CI = 1.89-3.21) and were located in rural counties. DISCUSSION: Radon-hazard potential soil has a significant association with residential home radon tests. More efforts are needed to improve radon testing in block groups that are rural and have greater percentages of racial minorities.

Relationship between distance of referring facilities and haemoglobin change in children in Malawi.

BACKGROUND: Anaemia is a significant cause of mortality in children in sub-Saharan Africa where blood transfusion is often available only at referral hospitals. Understanding the pattern of referrals by health facilities is essential to identify the delays that affect child survival. AIM: To determine if there was a correlation between change in haemoglobin (Hb) level and distance from referring facilities to Kamuzu Central Hospital (KCH) in Malawi, and whether distance affected mortality rates. METHODS: This was a retrospective cohort study of 2259 children referred to KCH whose Hb was measured at the referring facility or at KCH. Maps were created using ArcGIS® software. The relationship between distance from KCH and change in Hb was assessed by χ2 analysis and multiple linear regression with SAS© software. RESULTS: The majority of children were referred by health facilities in the Lilongwe District. When categorised as Hb <4, 4-6 or >6 g/dL, 87.0% of children remained in the same category during transfer. There was no significant relationship between Hb drop and distance from KCH. Distance from KCH was not a significant predictor of Hb level at KCH or Hb change. However, mortality rates were significantly higher in facilities that were 10-50 km from KCH than in those which were <10 km away. CONCLUSIONS: Using distance as a proxy for time, this suggests that referring facilities are transferring children sufficiently quickly to avert significant reductions in Hb. Despite this, there is a need to identify the factors that influence the decision to transfer anaemic children.

Early life exposures associated with risk of small intestinal neuroendocrine tumors.

Small intestinal neuroendocrine tumors (SINT) are rare with incidence increasing over the past 40 years. The purpose of this work is to examine the role of environmental exposures in the rise of SINT incidence using the Utah Population Database, a resource of linked records including life events, cancer diagnoses and residential histories. SINT cases born in Utah were identified through the Utah Cancer Registry with: diagnosis years of 1948 to 2014 and age at diagnosis of 23 to 88 years. Controls were matched to cases 10:1 based on sex, birth year and residence time in Utah. Cases and controls were geocoded to their birth locale. An isotonic spatial scan statistic was used to test for the occurrence and location(s) of SINT clusters. Potential environmental exposures and economic conditions in the birth locales at the time of the birth (1883-1982) were generated using historical references. Conditional logistic regression was used to estimate odd ratios. We report a spatial cluster central to historic coal mining communities, associated with a 2.86 relative risk (p = 0.016) of SINT. Aspatial analyses of industry and mining exposures further suggest elevated risk for early life exposure near areas involved in the construction industry (OR 1.98 p = 0.024). Other exposures approached significance including coal, uranium and hard rock mining during the earliest period (1883-1929) when safety from exposures was not considered. We do observe a lower risk (OR 0.58 p = 0.033) associated with individuals born in rural areas in the most recent period (1945-1982). Environmental exposures early in life, especially those from industries such as mining, may confer an elevated risk of SINT.

Spatial clusters of cancer incidence: analyzing 1940 census data linked to 1966-2017 cancer records.

PURPOSE: A life course perspective to cancer incidence is important for understanding effects of the environment during early life on later cancer risk. We assessed spatial clusters of cancer incidence based on early life location defined as 1940 US Census Enumeration District (ED). METHODS: A cohort of 260,585 individuals aged 0-40 years in 1940 was selected. Individuals were followed from 1940 to cancer diagnosis, death, or last residence in Utah. We geocoded ED centroids in Utah for the 1940 Census. Spatial scan statistics with purely spatial elliptic scanning window were used to identify spatial clusters of EDs with excess cancer rates across 26 cancer types, assuming a discrete Poisson model. RESULTS: Cancer was diagnosed in 66,904 (25.67%) individuals during follow-up across 892 EDs. Average follow-up was 50.9 years. We detected 15 clusters of excess risk for bladder, breast, cervix, colon, lung, melanoma, oral, ovary, prostate, and soft tissue cancers. An urban area had dense overlap of multiple cancer types, including two EDs at increased risk for five cancer types each. CONCLUSIONS: Early environments may contribute to cancer risk later in life. Life course perspectives applied to the study of cancer incidence can provide insights for increasing understanding of cancer etiology.

Contrasting regional and national mechanisms for predicting elevated arsenic in private wells across the United States using classification and regression trees.

Arsenic contamination in groundwater is a public health and environmental concern in the United States (U.S.) particularly where monitoring is not required under the Safe Water Drinking Act. Previous studies suggest the influence of regional mechanisms for arsenic mobilization into groundwater; however, no study has examined how influencing parameters change at a continental scale spanning multiple regions. We herein examine covariates for groundwater in the western, central and eastern U.S. regions representing mechanisms associated with arsenic concentrations exceeding the U.S. Environmental Protection Agency maximum contamination level (MCL) of 10 parts per billion (ppb). Statistically significant covariates were identified via classification and regression tree (CART) analysis, and included hydrometeorological and groundwater chemical parameters. The CART analyses were performed at two scales: national and regional; for which three physiographic regions located in the western (Payette Section and the Snake River Plain), central (Osage Plains of the Central Lowlands), and eastern (Embayed Section of the Coastal Plains) U.S. were examined. Validity of each of the three regional CART models was indicated by values >85% for the area under the receiver-operating characteristic curve. Aridity (precipitation minus potential evapotranspiration) was identified as the primary covariate associated with elevated arsenic at the national scale. At the regional scale, aridity and pH were the major covariates in the arid to semi-arid (western) region; whereas dissolved iron (taken to represent chemically reducing conditions) and pH were major covariates in the temperate (eastern) region, although additional important covariates emerged, including elevated phosphate. Analysis in the central U.S. region indicated that elevated arsenic concentrations were driven by a mixture of those observed in the western and eastern regions.