Maternal smoking during pregnancy increases the risk of gut microbiome-associated childhood overweight and obesity.

Childhood obesity is linked to maternal smoking during pregnancy. Gut microbiota may partially mediate this association and could be potential targets for intervention; however, its role is understudied. We included 1,592 infants from the Canadian Healthy Infants Longitudinal Development Cohort. Data on environmental exposure and lifestyle factors were collected prenatally and throughout the first three years. Weight outcomes were measured at one and three years of age. Stool samples collected at 3 and 12 months were analyzed by sequencing the V4 region of 16S rRNA to profile microbial compositions and magnetic resonance spectroscopy to quantify the metabolites. We showed that quitting smoking during pregnancy did not lower the risk of offspring being overweight. However, exclusive breastfeeding until the third month of age may alleviate these risks. We also reported that maternal smoking during pregnancy significantly increased Firmicutes abundance and diversity. We further revealed that Firmicutes diversity mediates the elevated risk of childhood overweight and obesity linked to maternal prenatal smoking. This effect possibly occurs through excessive microbial butyrate production. These findings add to the evidence that women should quit smoking before their pregnancies to prevent microbiome-mediated childhood overweight and obesity risk, and indicate the potential obesogenic role of excessive butyrate production in early life.

Examining the influence of built environment on sleep disruption.

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 (PM2.5, 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.

GlobeCorr: interactive globe-based visualization for correlation datasets.

Motivation: Increasingly complex omics datasets are being generated, along with associated diverse categories of metadata (environmental, clinical, etc.). Looking at the correlation between these variables can be critical to identify potential confounding factors and novel relationships. To date, some correlation globe software has been developed to aid investigations; however, they lack secure, dynamic visualization capability. Results: GlobeCorr.ca is a web-based application designed to provide user-friendly, interactive visualization and analysis of correlation datasets. Users load tabular data listing pairwise variables and their correlation values, and GlobeCorr creates a dynamic visualization using ribbons to represent positive and negative correlations, optionally grouped by domain/category (such as microbiome taxa against other metadata). GlobeCorr runs securely (locally on a user's computer) and provides a simple method for users to visualize and summarize complex datasets. This tool is applicable to a wide range of disciplines and domains of interest, including the bioinformatics/microbiome and metadata examples provided within. Availability and Implementation: See https://GlobeCorr.ca; Code provided under an open source MIT license: https://github.com/brinkmanlab/globecorr.

Early Life Antimicrobial Exposure: Impact on Clostridioides difficile Colonization in Infants.

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.

Projected Impact of Weight Gain During the COVID-19 Pandemic on the Future Burden of Cancer in Canada.

The COVID-19 pandemic and resulting public health measures have had significant impacts on daily life, including shifts in health behaviours which contribute to weight gain and may increase subsequent risk of chronic diseases such as cancer. Using OncoSim, a web-based microsimulation tool, we estimated the future burden of cancer in Canada by incorporating data on unintentional weight gain among adults during the first year of the COVID-19 pandemic. Population impact measures were estimated until 2042, assuming a 12-year latency period. We estimated 14,194 excess cancer cases and 5,324 excess cancer deaths by 2042 due to COVID-19 related weight gain. Particularly large impacts were estimated for endometrial and breast cancer among women, with 2,983 and 2,151 excess cases by 2042. For men, 1,700 excess colorectal cases and 1,188 excess kidney cancer cases were projected by 2042. Changes in health behavior during the COVID-19 pandemic are likely to have significant and long-lasting impacts on cancer burden. These projections highlight the immediate need for investment into the development and implementation of effective cancer prevention strategies.

Assessing secondhand and thirdhand tobacco smoke exposure in Canadian infants using questionnaires, biomarkers, and machine learning.

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.

Association of use of cleaning products with respiratory health in a Canadian birth cohort.

BACKGROUND: Comprehensive longitudinal studies are important for understanding the complex risk factors, pathways, exposures and interactions that lead to the development and persistence of asthma. We aimed to examine associations between use of household cleaning products in early life and childhood respiratory and allergic disease using data from the Canadian Healthy Infant Longitudinal Development (CHILD) Cohort Study. METHODS: We summed responses from parental questionnaires that indicated the frequency of use of 26 household cleaning products in the homes of 2022 children from this birth cohort when they were 3-4 months of age to create a cumulative Frequency of Use Score (FUS). We used multivariable logistic regression models to assess whether frequent compared with less frequent use was associated with recurrent wheeze, atopy or asthma diagnosis, as defined by the questionnaire and clinical assessments at age 3 years. Data were collected between 2008 and 2015. RESULTS: Children in homes with a higher frequency of use of cleaning products in infancy, as determined by an interquartile range increase, had higher odds of recurrent wheeze (adjusted odds ratio [OR] 1.35, 95% confidence interval [CI] 1.11-1.64), recurrent wheeze with atopy (adjusted OR 1.49, 95% CI 1.02-2.16) and asthma diagnosis (adjusted OR 1.37, 95% CI 1.09-1.70), but no increase in the odds of atopy at age 3 years (adjusted OR 1.14, 95% CI 0.96-1.35). Compared with the lowest tertile of FUS exposure, infants in the highest tertile had higher odds of acquiring asthma. Stratification of the results showed that females had higher ORs than males for all outcomes, although the p values for this sex difference did not reach statistical significance. INTERPRETATION: Frequent use of household cleaning products in early life was associated with an increased risk for childhood wheeze and asthma but not atopy at age 3 years. Our findings add to the understanding of how early life exposures to cleaning products may be associated with the development of allergic airway disease and help to identify household behaviours as a potential area for intervention.