Abstract

Background: The factors influencing the oral microbiome during childhood and adolescence remain under-explored at the population level. Furthermore, details on how the oral microbiome differs with age, varies between individuals of different ethnicities, or is associated with socioeconomic factors and diet in children and adolescents are almost entirely unknown. Saliva samples and detailed demographic, health, diet and socioeconomic data were collected from children and adolescents that attended the Ontario Science Centre (Toronto, Canada) and were enrolled in the Spit for Science cohort. We characterised the bacterial microbiota of 4812 samples using 16S rRNA gene sequencing to make this the largest population cohort of the paediatric oral microbiome to date.

Results: Exploration of limited participant genotyping information and more than 50 variables encompassing the demographics, health, diet, socioeconomic status and living environment of participants revealed that almost all of the investigated variables were associated with overall community structure and/or the abundance of specific bacterial genera. However, most of these associations were modest (R² < 0.01) and the correlation between genetic relatedness and salivary bacteriome similarity was weak (R² = -0.014), while the strongest determinants of oral bacteriome composition were shared family/household environment (R² = 0.61 in the subset of participants from multi-child households), age (R² = 0.014) and ethnicity (R² = 0.01). We show that older children and adolescents have higher richness but lower evenness than younger children, suggesting that their oral bacteriome changes as they are exposed to more influences outside the home, and that the oral bacteriome is more consistent with more core taxa among children and adolescents than adults. We also find that diet variables related to the frequency of sugar consumption have the largest impact on the oral bacteriome of children and adolescents, and that microbial differences attributed to ethnicity and diet are likely intertwined.

Conclusions: This study provides an atlas of the demographic, health and lifestyle factors that are associated with the salivary bacteriome of children and adolescents. These findings highlight the complex interplay between social, environmental, and biological factors in shaping the developing oral microbiome and underscore the importance of inclusive, demographically diverse cohorts in microbiome research. This presents a reference for the variables that are important to account for in paediatric oral microbiome studies.

Citation

Wright, R.J., DeClercq, V., Burton, C.L. et al. Population-based characterisation of child and adolescent oral bacterial microbiomes. Microbiome��(2026). 

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This scoping review will examine epidemiologic studies assessing associations between ambient air pollution exposure and neurodevelopmental disorder symptoms for three childhood neurodevelopmental disorders: ADHD, ASD, and OCD. It will also characterize the modifying roles of socioeconomic and neighbourhood characteristics.

This protocol has been registered with Open Science Foundation: .

Background

Neurodevelopmental disorders in children and adolescents

There is established evidence for the interaction between childhood neurodevelopmental disorders (NDDs) and genetic, social, and environmental factors (1–5). Attention Deficit Hyperactivity Disorder (ADHD; prevalence 5-11%), Autism Spectrum Disorder (ASD; 1-3%), and Obsessive-Compulsive Disorder (OCD; 0.5-2%) are among the most common NDDs, affecting children and adolescents globally (6). Childhood NDDs are often co-occurrent with other NDDs (homotypic comorbidity) and with additional psychiatric pathologies (heterotypic comorbidity) such as anxiety and mood disorders (6).

Measuring the mental health burden in children and young people requires looking beyond clinical samples to dimensional symptom scores from population-based cohorts (7). Symptom rating scales implemented in community-based samples capture children who meet threshold criteria for an NDD but have not received a formal diagnosis given various healthcare disparities related to low income, race/ethnicity, etc. (8)

Note on OCD classification: In DSM-5, OCD is classified under “Obsessive-Compulsive and Related Disorders” rather than the Neurodevelopmental Disorders chapter. Its inclusion in this review is justified by its childhood onset, high co-occurrence with ADHD and ASD, and its established use as a neurodevelopmental outcome in the environmental epidemiology literature (5).

Environmental exposures and neurodevelopmental outcomes

Air pollution is a significant and increasing global risk factor for children and youth (9). Several ambient environmental exposures are associated with ADHD, ASD, and OCD incidence, acting as either risk or protective factors depending on exposure level and timing (10–14). Prenatal and early-life PM2.5 exposure is reported in multiple cohort studies to raise ASD risk and impair cognitive development (11,15). NO2, a marker of traffic-related pollution, is linked to psychomotor delays and attention difficulties in children (13). Children with greater greenspace access score lower on NDD symptom measures including OCD, plausibly because greenspace reduces pollutant exposure, supports physical activity, and lowers physiological stress (14,16,17).

Most of this evidence concerns clinical diagnosis rather than dimensional symptom severity, with some exceptions (18,19). Prior systematic reviews and meta-analyses have predominantly treated ASD or ADHD diagnosis as a binary outcome, rather than examining scale scores that capture sub-threshold and severity variation (10). Most prior reviews have also been confined to a single NDD and a single exposure type, which limits understanding of multi-exposure effects and cross-diagnostic patterns. Clarifying how environmental exposures shape NDD trait severity, rather than diagnosis incidence, could directly inform community intervention priorities and strengthen the case for urban environmental standards protective of child neurodevelopment.

Rationale and justification for a scoping review

This review examines studies assessing associations between environmental exposures and NDD trait scores, and characterizes the modifying roles of social, neighbourhood, and genetic factors (20). Given the heterogeneity of NDD outcome measures, exposure types, and study designs in this area, a scoping review is more appropriate than a systematic review or meta-analysis. It maps evidence across multiple exposures and NDD outcomes without requiring pooling of effect estimates from incompatible measurement scales.

Prior meta-analyses have typically been restricted to a single exposure-outcome pair: Shang et al. (2020) for NO2 and psychomotor development; Lin et al. (2022) for particulate matter and NDDs; Alter et al. (2024) for PM2.5 and IQ (2–4). The present review takes a broader mapping approach to characterize the breadth of measurement approaches across multiple exposures (environmental and social) and NDD types, and to identify evidence gaps and research priorities.

The format is also appropriate because the use of psychometric outcomes in environmental NDD research is still emerging. A scoping review lays the groundwork for subsequent systematic reviews with more precisely defined questions.

Prior reviews

Current systematic and scoping reviews in this area examine studies that measure only the incidence rate or clinical diagnosis of NDDs in relation to environmental exposures (2–4,10–12,21–23). From an initial search of systematic and scoping reviews in December 2025, a search of PROSPERO, MEDLINE, the Cochrane Database of Systematic Reviews, and JBI Evidence Synthesis was conducted. No current or in-progress scoping reviews or systematic reviews were identified that specifically address trait scores and NDD symptoms for childhood NDDs in relation to multiple environmental and social exposures.

Gao et. al. (2025) conducted an umbrella review of environmental pollutant exposure and neurodevelopmental outcomes, including collection of assessment criteria or tools used (10). However, this review didn’t provide a discussion of included studies or the relationship between NDD symptoms and environmental exposures.

Numerous reviews have examined individual neurodevelopmental disorders or specific environmental exposures, but most focus on clinical incidence for a single NDD and do not address symptom severity or multi-morbidity. Prior reviews also rarely examine multiple environmental and social exposures and simultaneously. This review addresses both gaps.

Primary research question(s) 

The objective of this review is to map epidemiologic studies that assess the associations between ambient air pollution and neighbourhood environmental exposures (ambient air pollution and greenspace) and neurodevelopmental disorders (ADHD, ASD, and OCD) symptoms in children and adolescents, and to characterize the modifying roles of neighbourhood-level socioeconomic characteristics.

The following questions operationalize the review objective and guide the inclusion criteria and data extraction:

1. What validated ADHD, ASD, and OCD-related behavioural and/or cognitive measures have been used to (Concept) in children and adolescents aged 0-18 years (Population) exposed to ambient air pollution or greenspace, across any geographic setting (Context)?
2. What types of environmental exposures (PM2.5, PM10, NO2, O3, SO2, greenspace, and other ambient exposures) and what exposure measurement methods (ground monitoring, satellite-derived estimates, land-use regression, NDVI) have been employed in included studies?
3. 3) What socioeconomic and neighbourhood-level characteristics have been examined as potential modifiers of the exposure-NDD symptom score relationship?

Secondary research question(s) 

1. What exposure windows (prenatal, early childhood, school-age, cumulative) have been examined, and how have studies operationalized these windows?
2. What evidence gaps exist regarding multi-exposure designs, under-studied NDD types, and under-represented populations or geographic settings?

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Robyn Wright, Vanessa DeClercq, Christie Burton, Nicole Roslin, Alex Chan, Paul Arnold, Paul Peters, Russell Schachar, Jennifer Crosbie, Morgan Langille

Abstract

The factors influencing the oral microbiome during childhood and adolescence remain under-explored at the population level. We characterised the saliva microbiomes of 4,812 children aged 5-18 years within the Spit for Science cohort collected at the Ontario Science Centre (Toronto, Canada), making this the largest population cohort of the paediatric oral microbiome to date. Exploration of participant genotyping and more than 50 variables encompassing the demographics, health, diet, socioeconomic status and living environment of participants revealed that almost all of the investigated variables were associated with overall community structure and/or the abundance of specific bacterial genera. However, most of these associations were modest, while the strongest determinants of oral microbiome composition were shared household environment, age, and ethnicity. We further show that the oral microbiome is more consistent with more core taxa among children than adults, and that microbial differences attributed to ethnicity and diet are likely intertwined. These findings highlight the complex interplay between social, environmental, and biological factors in shaping the developing oral microbiome. This underscores the importance of inclusive, demographically diverse cohorts in microbiome research and presents a reference for the variables that are important to account for in paediatric oral microbiome studies.

Download at Research Square: .

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Dissanayake A, Dupuis A, Burton CL, Soreni N, Peters PA, Gajaria A, Arnold P, Crosbie J, & R Schachar. (2024) “Racial/Ethnic Disparities in Youth Mental Health Traits and Diagnoses within a Community-based Sample.” Canadian Journal of Psychiatry. .

Abstract

Objective

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Exposure to outdoor concentrations of fine particulate matter is considered a leading global health concern, largely based on estimates of excess deaths using information integrating exposure and risk from several particle sources (outdoor and indoor air pollution and passive/active smoking). Such integration requires strong assumptions about equal toxicity per total inhaled dose. We relax these assumptions to build risk models examining exposure and risk information restricted to cohort studies of outdoor air pollution, now covering much of the global concentration range. Our estimates are severalfold larger than previous calculations, suggesting that outdoor particulate air pollution is an even more important population health risk factor than previously thought.

Burnett RT, Chen H, Szyszkowicz M, … Peters PA, … et al. (2018) “Global Mortality and Long-Term Ambient Exposure to Fine Particulate Matter: A New Relative Risk Estimator.” Proceedings of the National Academy of Sciences USA. 115(38): 9592-9597.

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The post Surveillance of cancer risks for firefighters, police, and armed forces among men in a Canadian census cohort appeared first on Determinants.

This is another article in a large series of papers done using the 1991 Canadian Census Health and Environment Cohort (CanCHEC), making use of the linkage to the Canadian Cancer Database (1969-2010). This series, some of which are profiled on our lab website, examines cancer risks by occupation and industry. This research is led by from the and the .

Abstract

As there are no well‐established modifiable risk factors for prostate cancer, further evidence is needed on possible factors such as occupation. Our study uses one of the largest Canadian worker cohorts to examine occupation, industry, and prostate cancer and to assess patterns of prostate cancer rates. The Canadian Census Health and Environment Cohort (CanCHEC) was established by linking the 1991 Canadian Census Cohort to the Canadian Cancer Database (1969–2010), Canadian Mortality Database (1991–2011), and Tax Summary Files (1981–2011). A total of 37,695 prostate cancer cases were identified in men aged 25–74 based on age at diagnosis. Cox proportional hazards models were used to estimate hazards ratios and 95% confidence intervals. In men aged 25–74 years, elevated risks were observed in the following occupations: senior management (HR = 1.12, 95% CI: 1.04–1.20); office and administration (HR = 1.19, 95% CI: 1.11–1.27); finance services (HR = 1.09, 95% CI: 1.04–1.14); education (HR = 1.05, 95% CI: 1.00–1.11); agriculture and farm management (HR = 1.12, 95% CI: 1.06–1.17); farm work (HR = 1.11, 95% CI: 1.01–1.21); construction managers (HR = 1.07, 95% CI: 1.01–1.14); firefighting (HR = 1.17, 95% CI: 1.01–1.36); and police work (HR = 1.22, 95% CI: 1.09–1.36). Decreased risks were observed across other construction and transportation occupations. Results by industry were consistent with occupation results. Associations were identified for white‐collar, agriculture, protective services, construction, and transportation occupations. These findings emphasize the need for further study of job‐related exposures and the potential influence of nonoccupational factors such as screening practices. ()

Citation

Sritharan J, MacLeod J, Harris S, Cole DC, Harris A, Tjepkema M, Peters PA, & PA Demers. (2018). “Prostate cancer surveillance by occupation and industry: the Canadian Census Health and Environment Cohort (CanCHEC).” Cancer Medicine. 7(4): 1468-1478.

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The post Sedentary work and the risks of colon and rectal cancer by anatomical sub-site in the Canadian census health and environment cohort (CanCHEC) appeared first on Determinants.

A New Method to Jointly Estimate the Mortality Risk of Long-Term Exposure to Fine Particulate Matter and its Components

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Most studies on the association between exposure to fine particulate matter (PM_2.5) and mortality have considered only total concentration of PM_2.5 or individual components of PM_2.5, and not the combined effects of concentration and particulate composition. We sought to develop a method to estimate the risk of death from long-term exposure to PM_2.5 and the distribution of its components, namely: sulphate, nitrate, ammonium, organic mass, black carbon, and mineral dust. We decomposed PM_2.5 exposure into the sum of total concentration and the proportion of each component. We estimated the risk of death due to exposure using a cohort of ~2.4 million Canadians who were followed for vital status over 16 years. Modelling the concentration of PM_2.5 with the distribution of the proportions of components together was a superior predictor for mortality than either total PM_2.5 concentration alone, or all component concentrations modelled together. Our new approach has the advantage of characterizing the toxicity of the atmosphere in its entirety. This is required to fully understand the health benefits associated with strategies to improve air quality that may result in complex changes not only in PM_2.5 concentration, but also in the distribution of particle components.

Dan L. Crouse, Sajeev Philip, Aaron van Donkelaar, Randall V. Martin, Barry Jessiman, Paul A. Peters, Scott Weichenthal, Jeffrey R. Brook, Bryan Hubbell & Richard T. Burnett

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