Ethylene oxide emissions and incident breast cancer and non-Hodgkin lymphoma in a US cohort.

BACKGROUND: Ethylene oxide (EtO) is a carcinogenic gas used in chemical production and to sterilize medical equipment that has been linked to risk of breast and lymphohematopoietic cancers in a small number of occupational studies. We investigated the relationship between environmental EtO exposure and risk of these cancers. METHODS: Using the US Environmental Protection Agency's Toxics Release Inventory, we estimated historical exposures for National Institutes of Health-AARP Diet and Health Study participants enrolled in 1995-1996. We constructed 2 metrics at 3, 5, and 10 km: 1) distance between residences and EtO-emitting facilities, weighted by the proportion of time the home was downwind of each facility, and 2) distance-weighted, wind direction-adjusted average airborne emissions index (AEI=∑[lbs EtO/km2]). We estimated risk (hazard ratio [HR], 95% confidence interval [CI]) of incident breast cancer (in situ and invasive) among postmenopausal women (n = 173 670) overall and by tumor estrogen receptor status and non-Hodgkin lymphoma in the full cohort (n = 451 945). RESULTS: We observed an increased risk of breast cancer associated with EtO-emitting facilities within 10 km (HR[≤10vs>10] = 1.05, 95% CI = 1.00 to 1.10) that appeared stronger for in situ (HR[≤10vs>10] = 1.13, 95% CI = 1.00 to 1.27) than invasive (HR[≤10vs>10] = 1.03, 95% CI = 0.97 to 1.09) disease. Risk of breast cancer in situ was also increased in the top AEI quartiles, and associations weakened with larger distances (HR[Q4vs0] = 1.60, 95% CI = 0.98 to 2.61; HR[Q4vs0] = 1.28, 95% CI = 0.92 to 1.79; HR[Q4vs0] = 1.25, 95% CI = 1.02 to 1.53 at 3, 5, and 10 km, respectively). No differences in breast cancer risk were observed by estrogen receptor status. We found no clear pattern of increased non-Hodgkin lymphoma risk. CONCLUSIONS: A novel potential association between EtO emissions and risk of in situ, but not invasive, breast cancer warrants additional evaluation.

Burkitt lymphoma risk shows geographic and temporal associations with Plasmodium falciparum infections in Uganda, Tanzania, and Kenya.

Endemic Burkitt lymphoma (eBL) is a pediatric cancer coendemic with malaria in sub-Saharan Africa, suggesting an etiological link between them. However, previous cross-sectional studies of limited geographic areas have not found a convincing association. We used spatially detailed data from the Epidemiology of Burkitt Lymphoma in East African Children and Minors (EMBLEM) study to assess this relationship. EMBLEM is a case-control study of eBL from 2010 through 2016 in six regions of Kenya, Uganda, and Tanzania. To measure the intensity of exposure to the malaria parasite, Plasmodium falciparum, among children in these regions, we used high-resolution spatial data from the Malaria Atlas Project to estimate the annual number of P. falciparum infections from 2000 through 2016 for each of 49 districts within the study region. Cumulative P. falciparum exposure, calculated as the sum of annual infections by birth cohort, varied widely, with a median of 47 estimated infections per child by age 10, ranging from 4 to 315 infections. eBL incidence increased 39% for each 100 additional lifetime P. falciparum infections (95% CI: 6.10 to 81.04%) with the risk peaking among children aged 5 to 11 and declining thereafter. Alternative models using estimated annual P. falciparum infections 0 to 10 y before eBL onset were inconclusive, suggesting that eBL risk is a function of cumulative rather than recent cross-sectional exposure. Our findings provide population-level evidence that eBL is a phenotype related to heavy lifetime exposure to P. falciparum malaria and support emphasizing the link between malaria and eBL.

Geographic Patterns in U.S. Lung Cancer Mortality and Cigarette Smoking.

BACKGROUND: Despite the success of smoking cessation campaigns, lung cancer remains the leading cause of cancer death in the U.S. Variations in smoking behavior and lung cancer mortality are evident by sex and region. METHODS: Applying geospatial methods to lung cancer mortality data from the National Vital Statistics System and county-level estimates of smoking prevalences from the NCI's Small Area Estimates of Cancer-Related Measures, we evaluated patterns in lung cancer mortality rates (2005-2018) in relation to patterns in ever cigarette smoking prevalences (1997-2003). RESULTS: Overall, ever smoking spatial patterns were generally associated with lung cancer mortality rates, which were elevated in the Appalachian region and lower in the West for both sexes. However, we also observed geographic variation in mortality rates that is not explained by smoking. Using Lee's L statistic for assessing bivariate spatial association, we identified counties where the ever smoking prevalence was low and lung cancer rates were high. We observed a significant cluster of counties (n = 25; P values ranging from 0.001 to 0.04) with low ever smoking prevalence and high mortality rates among females around the Mississippi River region south of St. Louis, Missouri and a similar and smaller cluster among males in Western Mississippi (n = 12; P values ranging from 0.002 to 0.03) that has not been previously described. CONCLUSIONS: Our analyses identified U.S. counties where factors other than smoking may be driving lung cancer mortality. IMPACT: These novel findings highlight areas where investigation of environmental and other risk factors for lung cancer is needed.

Urinary nitrate and sodium in a high-risk area for upper gastrointestinal cancers: Golestan Cohort Study☆.

BACKGROUND: The epidemiological evidence regarding the carcinogenicity of nitrate and sodium in drinking water is limited, partly because measuring the exposure at the individual level is complex. Most studies have used nitrate in water supplies as a proxy for individual exposure, but dietary intakes and other factors may contribute to the exposure. The present study investigates the factors associated with urinary nitrate and sodium in a high-risk area for esophageal and gastric cancers. METHODS: For this cross-sectional study, we used data and samples collected in 2004-2008 during the enrollment phase of the Golestan Cohort Study from a random sample of 349 participants (300 individuals from 24 rural villages and 49 from the city of Gonbad), stratified by average water nitrate in their district, the source of drinking water, and the usual dietary intake of nitrate and sodium. Nitrate, sodium, and creatinine were measured in a spot urine sample collected at the time of interview. We used the provincial cancer registry data to calculate the cumulative incidence rates of esophageal and gastric cancers for each location through June 1, 2020, and used weighted partial Pearson correlation to compare the incidence rates with median urinary nitrate and sodium in each village or the city. RESULTS: Among 349 participants (mean age±SD: 50.7 ± 8.6 years), about half (n = 170) used groundwater for drinking, and the use of groundwater was significantly more common in high-elevation locations (75.8%). The geometric mean of the creatinine-corrected urinary nitrate concentration was 68.3 mg/g cr (95%CI: 64.6,72.3), and the corresponding geometric mean for urinary sodium was 150.0 mmoL/g cr (95%CI: 139.6,161.1). After adjusting for confounders, urinary nitrate was associated with being a woman, drinking groundwater, and living in high-elevation locations, but not with estimated dietary intake. Urinary sodium concentration was significantly associated with monthly precipitation at the time of sampling but not with elevation or drinking water source. There were significant positive correlations between both median urinary nitrate and sodium in each location and esophageal cancer incidence rates adjusted for sex and age (r = 0.65 and r = 0.58, respectively, p < 0.01), but not with gastric cancer incidence. CONCLUSION: In a rural population at high risk for esophageal and gastric cancers, nitrate excretion was associated with living at a higher elevation and using groundwater for drinking. The associations between nitrate and sodium excretion with esophageal cancer incidence warrant future investigation.

A National Map of NCI-Designated Cancer Center Catchment Areas on the 50th Anniversary of the Cancer Centers Program.

BACKGROUND: In 1971, the National Cancer Act created a process to recognize the leadership, facilities, and research efforts at cancer centers throughout the United States. Toward this goal, each NCI-designated cancer center defines and describes a catchment area to which they tailor specific scientific and community engagement activities. METHODS: The geographically defined catchment areas of 63 NCI-designated comprehensive and clinical cancer centers are collated and presented visually. In addition, the NCI-designated cancer center catchment areas are geographically linked with publicly available data sources to aggregate sociodemographic and epidemiologic characteristics across the NCI Cancer Centers Program. RESULTS: The national map portrays the size, shape, and locations for 63 catchment areas of the 71 NCI-designated cancer centers. The findings illustrate the geographic extent of the NCI Cancer Centers Program during the 50th anniversary of the National Cancer Act. CONCLUSIONS: NCI-designated cancer centers occupy a prominent role in the cancer control ecosystem and continue to perform research to address the burden of cancer among their local communities. The strength of the NCI Cancer Centers Program is partly defined by the scope, quality, and impact of community outreach and engagement activities in the catchment areas. IMPACT: The collation and geographic presentation of the distinct, but complementary, NCI-designated cancer center catchment areas are intended to support future research and community outreach activities among NCI-designated cancer centers. See related commentary by Vadaparampil and Tiro, p. 952.

Invited Commentary: Predicting Incidence Rates of Rare Cancers-Adding Epidemiologic and Spatial Contexts.

There are unique challenges to identifying causes of and developing strategies for prevention of rare cancers, driven by the difficulty in estimating incidence, prevalence, and survival due to small case numbers. Using a Poisson modeling approach, Salmerón et al. (Am J Epidemiol. 2022;191(3):487-498) built upon their previous work to estimate incidence rates of rare cancers in Europe using a Bayesian framework, establishing a uniform prior for a measure of variability for country-specific incidence rates. They offer a methodology with potential transferability to other settings with similar cancer surveillance infrastructure. However, the approach does not consider the spatiotemporal correlation of rare cancer case counts and other, potentially more appropriate nonnormal probability distributions. In this commentary, we discuss the implications of future work from cancer epidemiology and spatial epidemiology perspectives. We describe the possibility of developing prediction models tailored to each type of rare cancer; incorporating the spatial heterogeneity in at-risk populations, surveillance coverage, and risk factors in these predictions; and considering a modeling framework with which to address the inherent spatiotemporal components of these data. We note that extension of this methodology to estimate subcountry rates at provincial, state, or smaller geographic levels would be useful but would pose additional statistical challenges.

Ingestion of Nitrate and Nitrite and Risk of Stomach and Other Digestive System Cancers in the Iowa Women's Health Study.

Nitrate and nitrite are precursors in the endogenous formation of N-nitroso compounds (NOC) which are potent animal carcinogens for the organs of the digestive system. We evaluated dietary intakes of nitrate and nitrite, as well as nitrate ingestion from drinking water (public drinking water supplies (PWS)), in relation to the incidence (1986-2014) of cancers of the esophagus (n = 36), stomach (n = 84), small intestine (n = 32), liver (n = 31), gallbladder (n = 66), and bile duct (n = 58) in the Iowa Women's Health Study (42,000 women aged from 50 to 75 in 1986). Dietary nitrate and nitrite were estimated using a food frequency questionnaire and a database of nitrate and nitrite levels in foods. Historical nitrate measurements from PWS were linked to the enrollment address by duration. We used Cox regression to compute hazard ratios (HR) and 95% confidence intervals (CI) for exposure quartiles (Q), tertiles (T), or medians, depending on the number of cancer cases. In adjusted models, nitrite intake from processed meats was associated with an increased risk of stomach cancer (HRQ4vsQ1 = 2.2, CI: 1.2-4.3). A high intake of total dietary nitrite was inversely associated with gallbladder cancer (HRQ4vsQ1 = 0.3, CI: 0.1-0.96), driven by an inverse association with plant sources of nitrite (HRQ4vsQ1 = 0.3, CI: 0.1-0.9). Additionally, small intestine cancer was inversely associated with a high intake of animal nitrite (HRT3vsT1 = 0.2, CI: 0.1-0.7). There were no other dietary associations. Nitrate concentrations in PWS (average, years ≥ 1/2 the maximum contaminant level) were not associated with cancer incidence. Our findings for stomach cancer are consistent with prior dietary studies, and we are the first to evaluate nitrate and nitrite ingestion for certain gastrointestinal cancers.

sparrpowR: a flexible R package to estimate statistical power to identify spatial clustering of two groups and its application.

BACKGROUND: Cancer epidemiology studies require sufficient power to assess spatial relationships between exposures and cancer incidence accurately. However, methods for power calculations of spatial statistics are complicated and underdeveloped, and therefore underutilized by investigators. The spatial relative risk function, a cluster detection technique that detects spatial clusters of point-level data for two groups (e.g., cancer cases and controls, two exposure groups), is a commonly used spatial statistic but does not have a readily available power calculation for study design. RESULTS: We developed sparrpowR as an open-source R package to estimate the statistical power of the spatial relative risk function. sparrpowR generates simulated data applying user-defined parameters (e.g., sample size, locations) to detect spatial clusters with high statistical power. We present applications of sparrpowR that perform a power calculation for a study designed to detect a spatial cluster of incident cancer in relation to a point source of numerous environmental emissions. The conducted power calculations demonstrate the functionality and utility of sparrpowR to calculate the local power for spatial cluster detection. CONCLUSIONS: sparrpowR improves the current capacity of investigators to calculate the statistical power of spatial clusters, which assists in designing more efficient studies. This newly developed R package addresses a critically underdeveloped gap in cancer epidemiology by estimating statistical power for a common spatial cluster detection technique.

Spatial Heterogeneity in Positional Errors: A Comparison of Two Residential Geocoding Efforts in the Agricultural Health Study.

Geocoding is a powerful tool for environmental exposure assessments that rely on spatial databases. Geocoding processes, locators, and reference datasets have improved over time; however, improvements have not been well-characterized. Enrollment addresses for the Agricultural Health Study, a cohort of pesticide applicators and their spouses in Iowa (IA) and North Carolina (NC), were geocoded in 2012-2016 and then again in 2019. We calculated distances between geocodes in the two periods. For a subset, we computed positional errors using "gold standard" rooftop coordinates (IA; N = 3566) or Global Positioning Systems (GPS) (IA and NC; N = 1258) and compared errors between periods. We used linear regression to model the change in positional error between time periods (improvement) by rural status and population density, and we used spatial relative risk functions to identify areas with significant improvement. Median improvement between time periods in IA was 41 m (interquartile range, IQR: -2 to 168) and 9 m (IQR: -80 to 133) based on rooftop coordinates and GPS, respectively. Median improvement in NC was 42 m (IQR: -1 to 109 m) based on GPS. Positional error was greater in rural and low-density areas compared to in towns and more densely populated areas. Areas of significant improvement in accuracy were identified and mapped across both states. Our findings underscore the importance of evaluating determinants and spatial distributions of errors in geocodes used in environmental epidemiology studies.

Parasite competition hidden by correlated coinfection: using surveys and experiments to understand parasite interactions.

Within most free-living species exists a cryptic community of interacting parasites. By combining multiscale field data with manipulative experiments, we evaluated patterns of parasite coinfection in amphibian hosts and their underlying mechanisms. Surveys of 86 wetlands and 1273 hosts revealed positive correlations between two pathogenic trematodes (Ribeiroia ondatrae and Echinostoma trivolvis) both between wetlands and within individual hosts. In infection and coinfection experiments, Ribeiroia caused greater pathology than Echinostoma, including high host mortality (24%) and severe limb malformations (75%). No interactive effects were noted for host pathology, but both parasites decreased the per capita persistence of one another by 17-36%. Thus, in spite of consistently positive associations from field data, these parasites negatively affected the persistence of one another, likely via cross immunity (apparent competition). These findings underscore the danger of inferring parasite interactions from coinfection patterns and emphasize the potential disconnect between within-host processes (e.g., competition) and between-host processes (e.g., exposure and transmission). Here, correlated coinfections likely resulted from similarities in the parasites' host requirements and heterogeneity in host susceptibility or exposure. Understanding complex interactions among parasites depends critically on the scale under consideration, highlighting the importance of combining coinfection field studies with mechanistic experiments.