Background: Cigarette smoking is causally linked to renal cell carcinoma (RCC). However, associations for individual RCC histologies are not well described. Newly available data on tobacco use from population-based cancer registries allow characterization of associations with individual RCC types. Methods: We analyzed data for 30,282 RCC cases from 8 states that collected tobacco use information for a National Program of Cancer Registry project. We compared the prevalence and adjusted prevalence ratios (aPR) of cigarette smoking (current vs. never, former vs. never) among individuals diagnosed between 2011 and 2016 with clear cell RCC, papillary RCC, chromophobe RCC, renal collecting duct/medullary carcinoma, cyst-associated RCC, and unclassified RCC. Results: Of 30,282 patients with RCC, 50.2% were current or former cigarette smokers. By histology, proportions of current or formers smokers ranged from 38% in patients with chromophobe carcinoma to 61.9% in those with collecting duct/medullary carcinoma. The aPRs (with the most common histology, clear cell RCC, as referent group) for current and former cigarette smoking among chromophobe RCC cases (4.9% of our analytic sample) were 0.58 [95% confidence interval (CI), 0.50–0.67] and 0.88 (95% CI, 0.81–0.95), respectively. Other aPRs were slightly increased (papillary RCC and unclassified RCC, current smoking only), slightly decreased (unclassified RCC, former smoking only), or not significantly different from 1.0 (collecting duct/medullary carcinoma and cyst-associated RCC). Conclusions: Compared with other RCC histologic types, chromophobe RCC has a weaker (if any) association with smoking. Impact: This study shows the value of population-based cancer registries’ collection of smoking data, especially for epidemiologic investigation of rare cancers.

Background: Endocrine disrupting chemical (EDC) exposure is ubiquitous. EDC exposure during critical windows of development may interfere with the body's endocrine system, affecting growth. Previous human studies have examined one EDC at a time in relation to infant growth. By studying mixtures, the human experience can be better approximated. Aims: We investigated the association of prenatal exposure to persistent EDCs (per- and polyfluoroalkyl substances (PFAS), polychlorinated biphenyls (PCBs), and organochlorine pesticides (OCPs)) as mixtures with postnatal body size among female offspring. Subjects: We used a sub-sample of the Avon Longitudinal Study of Parents and Children (N = 425), based in the United Kingdom. Study design: We quantified 52 EDCs in maternal serum collected during pregnancy. We used Bayesian kernel machine regression with a random intercept to examine the association of prenatal concentrations of EDC mixtures with longitudinal postnatal body size measures for each EDC class separately (PFAS, PCBs, and OCPs) and for all three classes combined. Outcome measures: Weight and height measures at 0, 2, 9, and 19 months were obtained by health professionals as part of routine child health surveillance. Results: The mixture representing all three classes combined (31 chemicals) (n = 301) was inversely associated with postnatal body size. Holding all EDCs in the 31-chemical mixture at the 75th percentile compared to the 50th percentile was associated with 0.15 lower weight-for-age z-score (95% credible interval −0.26, −0.03). Weak inverse associations were also seen for height-for-age and body mass index-for-age scores. Conclusions: These results suggest that prenatal exposure to mixtures of persistent EDCs may affect postnatal body size.

Background: Bicycling is an important form of physical activity in populations. Research assessing the effect of infrastructure on bicycling with high-resolution smartphone data is emerging in several places, but it remains limited in low-bicycling US settings, including the Southeastern US. The Atlanta area has been expanding its bicycle infrastructure, including off-street paved trails such as the Atlanta BeltLine and some protected bike lanes. Methods: Using the generalized synthetic-control method, we estimated effects of five groups of off-street paved trails and protected bike lanes on bicycle ridership in their corresponding areas. To measure bicycling, we used 2 years (October 1, 2016 to September 30, 2018) of monthly Strava data in Atlanta's urban core along with data from 15 on-the-ground counters to adjust for spatiotemporal variation in app use. Results: Considering all infrastructure as one joint intervention, an estimated 1.10 (95% confidence interval [CI]: 0.99, 1.18) times more bicycle-distance was ridden than would have been expected in the same areas had the infrastructure not been built, when defining treatment areas by the narrower of two definitions (defined in text). The Atlanta BeltLine Westside Trail and Proctor Creek Greenway had especially strong effect estimates, e.g., ratios of 1.45 (95% CI: 1.12, 1.86) and 1.55 (1.10, 2.14) under each treatment-area definition, respectively. We estimated that other infrastructure had weaker positive or no effects on bicycle-distance ridden. Conclusions: This study advances research on the topic because of its setting in the US Southeast, simultaneous assessment of several infrastructure groups, and data-driven approach to estimating effects. See video abstract at, http://links.lww.com/EDE/B936.

Introduction The Centers for Disease Control and Prevention’s Controlling Childhood Asthma and Reducing Emergencies initiative aims to prevent 500,000 emergency department (ED) visits and hospitalizations within 5 years among children with asthma through implementation of evidence-based interventions and policies. Methods are needed for calculating the anticipated effects of planned asthma programs and the estimated effects of existing asthma programs. We describe and illustrate a method of using results from randomized control trials (RCTs) to estimate changes in rates of adverse asthma events (AAEs) that result from expanding access to asthma interventions. Methods We use counterfactual arguments to justify a formula for the expected number of AAEs prevented by a given intervention. This formula employs a current rate of AAEs, a measure of the increase in access to the intervention, and the rate ratio estimated in an RCT. Results We justified a formula for estimating the effect of expanding access to asthma interventions. For example, if 20% of patients with asthma in a community with 20,540 annual asthma-related ED visits were offered asthma self-management education, ED visits would decrease by an estimated 1,643; and annual hospitalizations would decrease from 2,639 to 617. Conclusion Our method draws on the best available evidence from RCTs to estimate effects on rates of AAEs in the community of interest that result from expanding access to asthma interventions.

We systematically evaluated studies published through May 2014 in which investigators assessed the dose-response relationship between serum levels of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and the occurrence of diabetes mellitus (DM), and we investigated the extent and sources of interstudy heterogeneity. The dose-response relationship between serum TCDD and DM across studies was examined using 2 dependent variables: an exposure level–specific proportion of persons with DM and a corresponding natural log-transformed ratio measure of the association between TCDD and DM. Regression slopes for each dependent variable were obtained for each study and included in a random-effects meta-analysis. Sensitivity analyses were used to assess the influence of inclusion and exclusion decisions, and sources of heterogeneity were explored using meta-regression models and a series of subanalyses. None of the summary estimates in the main models or in the sensitivity analyses indicated a statistically significant association. We found a pronounced dichotomy: a positive dose-response in cross-sectional studies of populations with low-level TCDD exposures (serum concentrations <10 pg/g lipid) and heterogeneous, but on balance null, results for prospective studies of persons with high prediagnosis TCDD body burdens. Considering the discrepancy of results for low current versus high past TCDD levels, the available data do not indicate that increasing TCDD exposure is associated with an increased risk of DM.

Food consumption, particularly of animal-based products, is considered the most important contributor to persistent endocrine disrupting chemical (EDC) exposure. This study aims to describe the association between maternal diet during pregnancy and exposure to persistent EDCs using dietary pattern analysis. This study is based on subsamples of the Avon Longitudinal Study of Parents and Children (ALSPAC) (N=422) and the Norwegian Mother, Father, and Child Cohort Study (MoBa) (N=276) which uses data from the Medical Birth Registry of Norway (MBRN). Women in both studies completed food frequency questionnaires (FFQs) during pregnancy, from which consumption data were categorized into 38 aggregated food groups. Maternal blood samples were collected during pregnancy and concentrations of perfluoroalkyl substances (PFAS), polychlorinated biphenyls (PCBs), and organochlorine pesticides (OCPs) in serum/plasma were measured. Dietary patterns were identified using reduced rank regression, with blood EDC concentrations as response variables. Within ALSPAC, all patterns (PFAS, PCB, and OCP) were characterized by high consumption of meat, poultry, white fish, and biscuits. In MoBa, high consumption of sausages and burgers (representing processed meats), pasta, and chocolate bars characterized PCB and OCP dietary patterns, while high consumption of cheese characterized the PFAS pattern. Across both cohorts, PFAS patterns were characterized by high consumption of cheese, PCB patterns by high consumption of rice, and OCP patterns by poultry. Dietary patterns explained between 8 and 20% of the variation in serum EDC concentrations, with explained variance being the highest for PCBs in both cohorts. In conclusion, dietary patterns high in animal-based products appear to be associated with persistent EDC concentrations among pregnant women. Diet explains more variation in PCB concentrations than for other persistent EDC classes.

Introduction: Transgender and gender diverse people often face discrimination and may experience disproportionate emotional distress that leads to suicide attempts. Therefore, it is essential to estimate the frequency and potential determinants of suicide attempts among transgender and gender diverse individuals. Methods: Longitudinal data on 6,327 transgender and gender diverse individuals enrolled in 3 integrated healthcare systems were analyzed to assess suicide attempt rates. Incidence was compared between transmasculine and transfeminine people by age and race/ethnicity and according to mental health status at baseline. Cox proportional hazards models examined rates and predictors of suicide attempts during follow-up. Data were collected in 2016, and analyses were conducted in 2019. Results: During follow-up, 4.8% of transmasculine and 3.0% of transfeminine patients had at least 1 suicide attempt. Suicide attempt rates were more than 7 times higher among patients aged <18 years than among those aged >45 years, more than 3 times higher among patients with previous history of suicide ideation or suicide attempts than among those with no such history, and 2–5 times higher among those with 1–2 mental health diagnoses and more than 2 mental health diagnoses at baseline than among those with none. Conclusions: Among transgender and gender diverse individuals, younger people, people with previous suicidal ideation or attempts, and people with multiple mental health diagnoses are at a higher risk for suicide attempts. Future research should examine the impact of gender-affirming healthcare use on the risk of suicide attempts and identify targets for suicide prevention interventions among transgender and gender diverse people in clinical settings.

Nighttime light exposure may increase cancer risk by disrupting the circadian system. However, there is no well-established survey method for measuring ambient light. In the Cancer Prevention Study-3, 732 men and women answered a light survey based on seven environments. The light environment in the past year was assessed twice, one year apart, and four one-week diaries were collected between the annual surveys. A total of 170 participants wore a meter to measure photopic illuminance and circadian stimulus (CS). Illuminance and CS values were estimated for lighting environments from measured values and evaluated with a cross validation approach. The kappas for self-reported light environment comparing the two annual surveys were 0.61 on workdays and 0.49 on non-workdays. Kappas comparing the annual survey to weekly diaries were 0.71 and 0.57 for work and non-workdays, respectively. Agreement was highest for reporting of darkness (95.3%), non-residential light (86.5%), and household light (75.6%) on workdays. Measured illuminance and CS identified three peaks of light (darkness, indoor lighting, and outdoor daytime light). Estimated illuminance and CS were correlated with the measured values overall (r = 0.77 and r = 0.67, respectively) but were less correlated within each light environment (r = 0.23–0.43). The survey has good validity to assess ambient light for studies of human health.

Objective: Asthma carries a high burden of disease for residents of Puerto Rico. We conducted this study to better understand asthma-related healthcare use and to examine potential asthma triggers. Methods: We characterized asthma-related healthcare use in 2013 by demographics, region, and date using outpatient, hospital, and emergency department (ED) insurance claims with a primary diagnostic ICD-9-CM code of 493.XX. We examined environmental asthma triggers, including outdoor allergens (i.e., mold and pollen), particulate pollution, and influenza-like illness. Analyses included descriptive statistics and Poisson time-series regression. Results: During 2013, there were 550,655 medical asthma claims reported to the Puerto Rico Healthcare Utilization database, representing 148 asthma claims/1,000 persons; 71% of asthma claims were outpatient visits, 19% were hospitalizations, and 10% were ED visits. Females (63%), children aged ≤9 years (77% among children), and adults aged ≥45 years (80% among adults) had the majority of asthma claims. Among health regions, Caguas had the highest asthma claim-rate at 142/1,000 persons (overall health region claim-rate = 108). Environmental exposures varied across the year and demonstrated seasonal patterns. Metro health region regression models showed positive associations between increases in mold and particulate matter <10 microns in diameter (PM10) and outpatient asthma claims. Conclusions: This study provides information about patterns of asthma-related healthcare use across Puerto Rico. Increases in mold and PM10 were associated with increases in asthma claims. Targeting educational interventions on exposure awareness and reduction techniques, especially to persons with higher asthma-related healthcare use, can support asthma control activities in public health and clinical settings.

Introduction: Advances in the development of high-resolution metabolomics (HRM) have provided new opportunities for their use in characterizing exposures to environmental air pollutants and air pollution-related disease etiologies. Exposure assessment studies have considered blood, breath, and saliva as biological matrices suitable for measuring responses to air pollution exposures. The current study examines comparability among these three matrices using HRM and explores their potential for measuring mobile-source air toxics. Methods: Four participants provided saliva, exhaled breath concentrate (EBC), and plasma before and after a 2 h road traffic exposure. Samples were analyzed on a Thermo Scientific QExactive MS system in positive electrospray ionization mode and resolution of 70 000 full-width at half-maximum with C18 chromatography. Data were processed using an apLCMS and xMSanalyzer on the R statistical platform. Results: The analysis yielded 7110, 6019, and 7747 reproducible features in plasma, EBC, and saliva, respectively. Correlations were moderate-to-strong (R = 0.41-0.80) across all pairwise comparisons of feature intensity within profiles, with the strongest between EBC and saliva. The associations of mean intensities between matrix pairs were positive and significant, controlling for subject and sampling time effects. Six out of 20 features shared in all three matrices putatively matched a list of known mobile-source air toxics. Conclusions: Plasma, saliva, and EBC have largely comparable metabolic profiles measurable through HRM. These matrices have the potential to be used in identification and measurement of exposures to mobile-source air toxics, though further, targeted study is needed.