Background: As smoking prevalence has decreased in Canada, particularly during pregnancy and around children, and technological improvements have lowered detection limits, the use of traditional tobacco smoke biomarkers in infant populations requires re-evaluation. Objective: We evaluated concentrations of urinary nicotine biomarkers, cotinine and trans-3’-hydroxycotinine (3HC), and questionnaire responses. We used machine learning and prediction modeling to understand sources of tobacco smoke exposure for infants from the CHILD Cohort Study. Methods: Multivariable linear regression models, chosen through a combination of conceptual and data-driven strategies including random forest regression, assessed the ability of questionnaires to predict variation in urinary cotinine and 3HC concentrations of 2017 3-month-old infants. Results: Although only 2% of mothers reported smoking prior to and throughout their pregnancy, cotinine and 3HC were detected in 76 and 89% of the infants’ urine (n = 2017). Questionnaire-based models explained 31 and 41% of the variance in cotinine and 3HC levels, respectively. Observed concentrations suggest 0.25 and 0.50 ng/mL as cut-points in cotinine and 3HC to characterize SHS exposure. This cut-point suggests that 23.5% of infants had moderate or regular smoke exposure. Significance: Though most people make efforts to reduce exposure to their infants, parents do not appear to consider the pervasiveness and persistence of secondhand and thirdhand smoke. More than half of the variation in urinary cotinine and 3HC in infants could not be predicted with modeling. The pervasiveness of thirdhand smoke, the potential for dermal and oral routes of nicotine exposure, along with changes in public perceptions of smoking exposure and risk warrant further exploration.

Background: Modifying aspects of the built environment may be an effective strategy for population-level improvements to sleep. However, few comprehensive evaluations of built environment and sleep have been completed. Methods: We conducted a cross-sectional study among participants of the British Columbia Generations Project (BCGP) who self-reported sleep duration (n = 28,385). Geospatial measures of light-at-night (LAN), greenness, air pollution (PM_2.5, NO₂, SO₂), and road proximity were linked to participant baseline residential postal codes. Logistic regression models, adjusted for age and sex, were used to estimate the association between these factors and self-reported sleep duration (<7 vs. ≥7 hours). Results: Interquartile range (IQR) increases in LAN intensity, greenness, and SO₂ were associated with 1.04-fold increased (95% CI = 1.02, 1.07), 0.95-fold decreased (95% CI = 0.91, 0.98), and 1.07-fold increased (95% CI = 1.03, 1.11) odds, respectively, of reporting insufficient sleep (i.e., <7 hours per night). Living <100 m from a main roadway was associated with a 1.09-fold greater odds of insufficient sleep (95% CI = 1.02, 1.17). Results were unchanged when examining all factors together within a single regression model. In stratified analyses, associations with SO₂ were stronger among those with lower reported annual household incomes and those living in more urban areas. Conclusions: BCGP’s rich data enabled a comprehensive evaluation of the built environment, revealing multiple factors as potentially modifiable determinants of sleep disruption. In addition to longitudinal evaluations, future studies should pay careful attention to the role of social disparities in sleep health.

The relationship between antibiotic use and Clostridioides difficile (C. difficile) has been well established in adults and older children but remains unclear and is yet to be fully examined in infant populations. This study aimed to determine the separate and cumulative impact from antibiotics and household cleaning products on C. difficile colonization in infants. This study included 1429 infants at 3–4 months of age and 1728 infants at 12 months of age from the Canadian Healthy Infant Longitudinal Development (CHILD) birth cohort. The levels of infant antimicrobial exposure were obtained from hospital birth charts and standardized questionnaires. Infant gut microbiota was characterized by Illumina 16S ribosomal ribonucleic acid (rRNA) gene sequencing. Analysis of C. difficile was performed using a quantitative polymerase chain reaction (qPCR). Overall, C. difficile colonized 31% and 46% of infants at 3–4 months and 12 months, respectively. At 3–4 months, C. difficile colonization was significantly higher in infants exposed to both antibiotics and higher (above average) usage of household cleaning products (adjusted odds ratio (aOR) 1.50, 95% CI 1.03–2.17; p = 0.032) than in infants who had the least antimicrobial exposure. This higher colonization persisted up to 12 months of age. Our study suggests that cumulative exposure to systemic antibiotics and higher usage of household cleaning products facilitates C. difficile colonization in infants. Further research is needed to understand the future health impacts.

Outdoor artificial light at night (ALAN) may increase breast cancer risk by suppressing melatonin secretion, an effect influenced by light intensity and wavelength. We evaluated the association of multiple ALAN measures with breast cancer risk. We pooled data from two cohort studies (baseline: 2009-2016; n = 24,793 female participants, 674 breast cancer cases). ALAN exposures at residential addresses were estimated using images taken from the International Space Station (2011-2013; ∼30-meter spatial resolution). Measures included average visual radiance (i.e., brightness), average melatonin suppression index (MSI), which quantifies the extent to which light suppresses melatonin, and their product (average impact MSI). Cox proportional hazards regression, adjusted for breast cancer risk factors and built environment features, was used to generate hazard ratios with 95 % confidence intervals (CI) for the associations between ALAN and breast cancer incidence. We also explored associations with breast cancer subtypes (invasive ductal, luminal A, postmenopausal) and among participants self-reporting light entering their rooms while sleeping. No statistically significant associations were observed in the overall study population. Among women reporting light entering their rooms, statistically significant associations of average impact MSI with breast cancer risk, overall and across each subtype, were observed. For example, those in the highest versus lowest tertile of average impact MSI had a 1.53-fold increased hazard of overall breast cancer (95 % CI: 1.18-1.98). Our findings suggest that outdoor ALAN is associated with increased risk of breast cancer and that both intensity and wavelength of light should be considered when evaluating ALAN exposures.

While hundreds of germline genetic variants have been associated with breast cancer risk, the mechanisms underlying the impacts of most of these variants on breast cancer remain uncertain. Metabolomics may offer valuable insights into the mechanisms underlying genetic risks of breast cancer. Among 143 cancer-free female participants, we used linear regression analyses to explore associations between the genetic risk of breast cancer, as determined by a previously developed polygenic risk score (PRS) that included 266 single-nucleotide polymorphisms (SNPs), and 223 measures of metabolites obtained from blood samples using nuclear magnetic resonance (NMR). A false discovery rate of 10% was applied to account for multiple comparisons. PRS was statistically significantly associated with 45 metabolite measures. These were primarily measures of very low-density lipoproteins (VLDLs) and high-density lipoproteins (HDLs), including triglycerides, cholesterol, and phospholipids. For example, the strongest effect was observed with the percent ratio of medium VLDL triglycerides to total lipids (0.53 unit increase in mean-standardized ln-transformed percent ratio per unit increase in PRS; q = 0.1). While larger-scale studies are needed to confirm these results, this exploratory study presents biologically plausible findings that are consistent with previously reported associations between lipids and breast cancer risk. If confirmed, these lipids could be targeted for lifestyle and pharmaceutical interventions among women at increased genetic risk of breast cancer.

Environmental Health Perspectives is an Open Access journal published by the National Institute of Environmental Health Sciences. Environmental Health Perspectives is an Open Access journal published by the National Institute of Environmental Health Sciences.