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Background: Over the past decades, childhood overweight has increased in many African countries. We examined the relationship between sedentary behaviour, moderate-to-vigorous physical activity (MVPA), and body composition in South African primary schoolchildren living in peri-urban settings. Methods: MVPA was measured via 7-day accelerometry and body composition via bioelectrical impedance analysis in 1090 learners (49.2% girls, M age = 8.3 ± 1.4 years). The relationships between MVPA and sedentary behaviour with the various body composition indicators (body fat and fat-free mass [total, truncal, arms, and legs], bone mass, muscle mass, and body water) were tested with mixed linear regressions. Results: The prevalence of overweight and obesity was 9.8% and 6.6%, respectively; 77.1% of the children engaged in ≥60 min of MVPA/day. Girls were more likely to be overweight/obese, to accumulate less than 60 min of MVPA/day, and had significantly higher relative body fat than boys ( p s < 0.001). Lower MVPA was associated with a higher likelihood of being overweight/obese, higher relative body fat, and lower relative fat-free mass, bone mass, muscle mass, and body water ( p s < 0.001). For lower sedentary behaviour, the associations with body composition pointed in the opposite direction. Conclusions: In this South African setting, girls are a particularly relevant target group for future physical activity interventions to prevent overweight/obesity-related non-communicable diseases in later life.

Background: The health effect of air pollution is rarely quantified in Africa, and this is evident in global systematic reviews and multi-city studies which only includes South Africa., Methods: A time-series analysis was conducted on daily mortality (cardiovascular (CVD) and respiratory diseases (RD)) and air pollution from 2006-2015 for the city of Cape Town. We fitted single- and multi-pollutant models to test the independent effects of particulate matter (PM 10 ), nitrogen dioxide (NO 2 ), sulphur dioxide (SO 2 ) and ozone (O 3 ) from co-pollutants., Results: daily average concentrations per interquartile range (IQR) increase of 16.4 µg/m 3 PM 10 , 10.7 µg/m 3 NO 2 , 6 µg/m 3 SO 2 and 15.6 µg/m 3 O 3 lag 0-1 were positively associated with CVD, with an increased risk of 2.4% (95% CI: 0.9-3.9%), 2.2 (95% CI: 0.4-4.1%), 1.4% (95% CI: 0-2.8%) and 2.5% (95% CI: 0.2-4.8%), respectively. For RD, only NO 2 showed a significant positive association with a 4.5% (95% CI: 1.4-7.6%) increase per IQR. In multi-pollutant models, associations of NO 2 with RD remained unchanged when adjusted for PM 10 and SO 2 but was weakened for O 3 . In CVD, O 3 estimates were insensitive to other pollutants showing an increased risk. Interestingly, CVD and RD lag structures of PM 10 , showed significant acute effect with evidence of mortality displacement., Conclusion: The findings suggest that air pollution is associated with mortality, and exposure to PM 10 advances the death of frail population.

Human biomonitoring has become a pivotal tool for supporting chemicals' policies. It provides information on real-life human exposures and is increasingly used to prioritize chemicals of health concern and to evaluate the success of chemical policies. Europe has launched the ambitious REACH program in 2007 to improve the protection of human health and the environment. In October 2020 the EU commission published its new chemicals strategy for sustainability towards a toxic-free environment. The European Parliament called upon the commission to collect human biomonitoring data to support chemical's risk assessment and risk management. This manuscript describes the organization of the first HBM4EU-aligned studies that obtain comparable human biomonitoring (HBM) data of European citizens to monitor their internal exposure to environmental chemicals. The HBM4EU-aligned studies build on existing HBM capacity in Europe by aligning national or regional HBM studies. The HBM4EU-aligned studies focus on three age groups: children, teenagers, and adults. The participants are recruited between 2014 and 2021 in 11 to 12 primary sampling units that are geographically distributed across Europe. Urine samples are collected in all age groups, and blood samples are collected in children and teenagers. Auxiliary information on socio-demographics, lifestyle, health status, environment, and diet is collected using questionnaires. In total, biological samples from 3137 children aged 6-12 years are collected for the analysis of biomarkers for phthalates, HEXAMOLL ® DINCH, and flame retardants. Samples from 2950 teenagers aged 12-18 years are collected for the analysis of biomarkers for phthalates, Hexamoll ® DINCH, and per- and polyfluoroalkyl substances (PFASs), and samples from 3522 adults aged 20-39 years are collected for the analysis of cadmium, bisphenols, and metabolites of polyaromatic hydrocarbons (PAHs). The children's group consists of 50.4% boys and 49.5% girls, of which 44.1% live in cities, 29.0% live in towns/suburbs, and 26.8% live in rural areas. The teenagers' group includes 50.6% girls and 49.4% boys, with 37.7% of residents in cities, 31.2% in towns/suburbs, and 30.2% in rural areas. The adult group consists of 52.6% women and 47.4% men, 71.9% live in cities, 14.2% in towns/suburbs, and only 13.4% live in rural areas. The study population approaches the characteristics of the general European population based on age-matched EUROSTAT EU-28, 2017 data; however, individuals who obtained no to lower educational level (ISCED 0-2) are underrepresented. The data on internal human exposure to priority chemicals from this unique cohort will provide a baseline for Europe's strategy towards a non-toxic environment and challenges and recommendations to improve the sampling frame for future EU-wide HBM surveys are discussed.

Background/aim: In sub-Sahara Africa, few studies have investigated the short-term association between hospital admissions and ambient air pollution. Therefore, this study explored the association between multiple air pollutants and hospital admissions in Cape Town, South Africa., Methods: Generalized additive quasi-Poisson models were used within a distributed lag linear modelling framework to estimate the cumulative effects of PM 10 , NO 2 , and SO 2 up to a lag of 21 days. We further conducted multi-pollutant models and stratified our analysis by age group, sex, and season., Results: The overall relative risk (95% confidence interval (CI)) for PM 10 , NO 2 , and SO 2 at lag 0-1 for hospital admissions due to respiratory disease (RD) were 1.9% (0.5-3.2%), 2.3% (0.6-4%), and 1.1% (-0.2-2.4%), respectively. For cardiovascular disease (CVD), these values were 2.1% (0.6-3.5%), 1% (-0.8-2.8%), and -0.3% (-1.6-1.1%), respectively, per inter-quartile range increase of 12 µg/m 3 for PM 10 , 7.3 µg/m 3 for NO 2 , and 3.6 µg/m 3 for SO 2 . The overall cumulative risks for RD per IQR increase in PM 10 and NO 2 for children were 2% (0.2-3.9%) and 3.1% (0.7-5.6%), respectively., Conclusion: We found robust associations of daily respiratory disease hospital admissions with daily PM 10 and NO 2 concentrations. Associations were strongest among children and warm season for RD.

This survey investigates the cross-sectional association between nighttime road, rail and aircraft noise exposure and the probability to be highly sleep disturbed (%HSD), as measured by self-report in postal and online questionnaires. As part of the Swiss SiRENE study, a total of 5592 survey participants in the entire country were selected based on a stratified random sample of their dwelling. Self-reported sleep disturbance was measured using an ICBEN-style 5-point verbal scale. The survey was carried out in four waves at different times of the year. Source-specific noise exposure was calculated for several façade points for each dwelling. After adjustment for potential confounders, all three noise sources showed a statistically significant association between the nighttime noise level LNight at the most exposed façade point and the probability to report high sleep disturbance, as determined by logistic regression. The association was strongest for aircraft noise and weakest for road traffic noise. We a priori studied the role of a range of effect modifiers, including the "eventfulness" of noise exposure, expressed as the Intermittency Ratio (IR) metric, bedroom window position, bedroom orientation towards the closest street, access to a quiet side of the dwelling, degree of urbanization, sleep timing factors (bedtime and sleep duration), sleep medication intake, survey season and night air temperature. While bedroom orientation exhibited a strong moderating effect, with an Leq-equivalent of nearly 20 dB if the bedroom faces away from the nearest street, the LNight-%HSD associations were not affected by bedroom window position, sleep timing factors, survey season, or temperature., Competing Interests: The authors declare no conflicts of interest.

Ambient air pollution is a leading environmental risk factor and its broad spectrum of adverse health effects includes a decrease in lung function. Socioeconomic status (SES) is known to be associated with both air pollution exposure and respiratory function. This study assesses the role of SES either as confounder or effect modifier of the association between ambient air pollution and lung function. Cross-sectional data from three European multicenter adult cohorts were pooled to assess factors associated with lung function, including annual means of home outdoor NO 2 . Pre-bronchodilator lung function was measured according to the ATS-criteria. Multiple mixed linear models with random intercepts for study areas were used. Three different factors (education, occupation and neighborhood unemployment rate) were considered to represent SES. NO 2 exposure was negatively associated with lung function. Occupation and neighborhood unemployment rates were not associated with lung function. However, the inclusion of the SES-variable education improved the models and the air pollution-lung function associations got slightly stronger. NO 2 associations with lung function were not substantially modified by SES-variables. In this multicenter European study we could show that SES plays a role as a confounder in the association of ambient NO 2 exposure with lung function.

A high body mass (BMI) index has repeatedly been associated with non-atopic asthma, but the biological mechanism linking obesity to asthma is still poorly understood. We aimed to test the hypothesis that inflammation and/or innate immunity plays a role in the obesity-asthma link. DNA methylome was measured in blood samples of 61 non-atopic participants with asthma and 146 non-atopic participants without asthma (non-smokers for at least 10 years) taking part in the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA) study. Modification by DNA methylation of the association of BMI or BMI change over 10 years with adult-onset asthma was examined at each CpG site and differentially methylated region. Pathway enrichment tests were conducted for genes in a priori curated inflammatory pathways and the NLRP3-IL1B-IL17 axis. The latter was chosen on the basis of previous work in mice. Inflammatory pathways including glucocorticoid/PPAR signaling ( p = 0.0023), MAPK signaling ( p = 0.013), NF-κB signaling ( p = 0.031), and PI3K/AKT signaling ( p = 0.031) were enriched for the effect modification of BMI, while NLRP3-IL1B-IL17 axis was enriched for the effect modification of BMI change over 10 years ( p = 0.046). DNA methylation measured in peripheral blood is consistent with inflammation as a link between BMI and adult-onset asthma and with the NLRP3-IL1B-IL17 axis as a link between BMI change over 10 years and adult-onset asthma in non-atopic participants.

Obesity-related conditions impose a considerable and growing burden on low- and middle-income countries, including South Africa. We aimed to assess the effect of twice a 10-week multidimensional, school-based physical activity intervention on children's health in Port Elizabeth, South Africa. A cluster-randomised controlled trial was implemented from February 2015 to May 2016 in grade 4 classes in eight disadvantaged primary schools. Interventions consisted of physical education lessons, moving-to-music classes, in-class activity breaks and school infrastructure enhancement to promote physical activity. Primary outcomes included cardiorespiratory fitness, body mass index (BMI) and skinfold thickness. Explanatory variables were socioeconomic status, self-reported physical activity, stunting, anaemia and parasite infections. Complete data were available from 746 children. A significantly lower increase in the mean BMI Z-score (estimate of difference in mean change: -0.17; 95% confidence interval (CI): -0.24 to -0.09; p < 0.001) and reduced increase in the mean skinfold thickness (difference in mean change: -1.06; 95% CI: -1.83 to -0.29; p = 0.007) was observed in intervention schools. No significant group difference occurred in the mean change of cardiorespiratory fitness ( p > 0.05). These findings show that a multidimensional, school-based physical activity intervention can reduce the increase in specific cardiovascular risk factors. However, a longer and more intensive intervention might be necessary to improve cardiorespiratory fitness.

Population-based linkage of patient-level information opens new strategies for dental research to identify unknown correlations of diseases, prognostic factors, novel treatment concepts and evaluate healthcare systems. As clinical trials have become more complex and inefficient, register-based controlled (clinical) trials (RC(C)T) are a promising approach in dental research. RC(C)Ts provide comprehensive information on hard-to-reach populations, allow observations with minimal loss to follow-up, but require large sample sizes with generating high level of external validity. Collecting data is only valuable if this is done systematically according to harmonized and inter-linkable standards involving a universally accepted general patient consent. Secure data anonymization is crucial, but potential re-identification of individuals poses several challenges. Population-based linkage of big data is a game changer for epidemiological surveys in Public Health and will play a predominant role in future dental research by influencing healthcare services, research, education, biotechnology, insurance, social policy and governmental affairs.

Identifying correlates of sedentary behaviour across all levels of the ecological model and understanding their interrelations is a promising method to plan effective interventions. The present study examined whether the objectively assessed and the perceived neighbourhood are associated with children&rsquo;s sedentary behaviour time (SBT). A comprehensive set of factors at different levels of influence across the ecological model were taken into account and analysed for mediating and modifying effects. Analyses were based on 1306 children and adolescents (6⁻16 years) participating in the population-based SOPHYA-study. Accelerometers were used to assess SBT, the perceived environment was examined by a validated parental questionnaire, and objective environmental data were allocated using GIS (ArcMap 10.2, Esri, Redlands, CA, USA) for each family&rsquo;s residential address. A high perceived safety was associated with less SBT. Boys, those whose residential neighbourhood was characterized by dead ends in urban areas, a low main street density in the neighbourhood of children and greenness were less likely to exhibit SBT. The association of the objective environment with the respective parental perceptions was low and no significant mediating effect was found for the perceived environment. We conclude for land-use planning to reduce sedentary behaviour objective environments should be complemented with efforts to increase parental sense of security.

Traffic noise has been linked to diabetes, with limited understanding of its mechanisms. We hypothesize that night-time road traffic noise (RTN) may impair glucose homeostasis through circadian rhythm disturbances. We prospectively investigated the relationship between residential night-time RTN and subsequent eight-year change in glycosylated hemoglobin (ΔHbA1c) in 3350 participants of the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA), adjusting for diabetes risk factors and air pollution levels. Annual average RTN (Lnight) was assigned to participants in 2001 using validated Swiss noise models. HbA1c was measured in 2002 and 2011 using liquid chromatography. We applied mixed linear models to explore RTN-ΔHbA1c association and its modification by a genetic risk score of six common circadian-related MTNR1B variants (MGRS). A 10 dB difference in RTN was associated with a 0.02% (0.003-0.04%) increase in mean ΔHbA 1c in 2142 non-movers. RTN-ΔHbA1c association was modified by MGRS among diabetic participants ( P interaction = 0.001). A similar trend in non-diabetic participants was non-significant. Among the single variants, we observed strongest interactions with rs10830963, an acknowledged diabetes risk variant also implicated in melatonin profile dysregulation. Night-time RTN may impair glycemic control, especially in diabetic individuals, through circadian rhythm disturbances. Experimental sleep studies are needed to test whether noise control may help individuals to attain optimal glycemic levels., Competing Interests: The authors declare no competing interests. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

In low- and middle-income countries, noise exposure and its negative health effects have been little explored. The present study aimed to assess the noise exposure situation in adults living in informal settings in the Western Cape Province, South Africa. We conducted continuous one-week outdoor noise measurements at 134 homes in four different areas. These data were used to develop a land use regression (LUR) model to predict A-weighted day-evening-night equivalent sound levels (L den ) from geographic information system (GIS) variables. Mean noise exposure during day (6:00-18:00) was 60.0 A-weighted decibels (dB(A)) (interquartile range 56.9-62.9 dB(A)), during night (22:00-6:00) 52.9 dB(A) (49.3-55.8 dB(A)) and average L den was 63.0 dB(A) (60.1-66.5 dB(A)). Main predictors of the LUR model were related to road traffic and household density. Model performance was low (adjusted R 2 = 0.130) suggesting that other influences than those represented in the geographic predictors are relevant for noise exposure. This is one of the few studies on the noise exposure situation in low- and middle-income countries. It demonstrates that noise exposure levels are high in these settings., Competing Interests: The authors declare no conflict of interest.

The type of noise annoyance scale and aspects of its presentation such as response format or location within a questionnaire and other contextual factors may affect self-reported noise annoyance. By means of a balanced experimental design, the effect of type of annoyance question and corresponding scale (5-point verbal vs. 11-point numerical ICBEN (International Commission on Biological Effects of Noise) scale), presentation order of scale points (ascending vs. descending), question location (early vs. late within the questionnaire), and survey season (autumn vs. spring) on reported road traffic noise annoyance was investigated in a postal survey with a stratified random sample of 2386 Swiss residents. Our results showed that early appearance of annoyance questions was significantly associated with higher annoyance scores. Questionnaires filled out in autumn were associated with a significantly higher annoyance rating than in the springtime. No effect was found for the order of response alternatives. Standardized average annoyance scores were slightly higher using the 11-point numerical scale whereas the percentage of highly annoyed respondents was higher based on the 5-point scale, using common cutoff points. In conclusion, placement and presentation of annoyance questions within a questionnaire, as well as the time of the year a survey is carried out, have small but demonstrable effects on the degree of self-reported noise annoyance., Competing Interests: The authors declare no conflicts of interest.

The aim of this study is to investigate the relationships between road traffic noise exposure, annoyance caused by different noise sources and validated health indicators in a cohort of 1375 adults from the region of Basel, Switzerland. Road traffic noise exposure for each study participant was determined using modelling, and annoyance from various noise sources was inquired by means of a four-point Likert scale. Regression parameters from multivariable regression models for the von Zerssen score of somatic symptoms (point symptom score increase per annoyance category) showed strongest associations with annoyance from industry noise (2.36, 95% CI: 1.54, 3.17), neighbour noise (1.62, 95% CI: 1.17, 2.06) and road traffic noise (1.53, 95% CI: 1.09, 1.96). Increase in modelled noise exposure by 10 dB(A) resulted in a von Zerssen symptom score increase of 0.47 (95% CI: -0.01, 0.95) units. Subsequent structural equation modelling revealed that the association between physical noise exposure and health-related quality of life (HRQOL) is strongly mediated by annoyance and sleep disturbance. This study elucidates the complex interplay of different factors for the association between physical noise exposure and HRQOL.

We simulated commuter routes and long-term exposure to traffic-related air pollution during commute in a representative population sample in Basel (Switzerland), and evaluated three air pollution models with different spatial resolution for estimating commute exposures to nitrogen dioxide (NO2) as a marker of long-term exposure to traffic-related air pollution. Our approach includes spatially and temporally resolved data on actual commuter routes, travel modes and three air pollution models. Annual mean NO2 commuter exposures were similar between models. However, we found more within-city and within-subject variability in annual mean (±SD) NO2 commuter exposure with a high resolution dispersion model (40 ± 7 µg m(-3), range: 21-61) than with a dispersion model with a lower resolution (39 ± 5 µg m(-3); range: 24-51), and a land use regression model (41 ± 5 µg m(-3); range: 24-54). Highest median cumulative exposures were calculated along motorized transport and bicycle routes, and the lowest for walking. For estimating commuter exposure within a city and being interested also in small-scale variability between roads, a model with a high resolution is recommended. For larger scale epidemiological health assessment studies, models with a coarser spatial resolution are likely sufficient, especially when study areas include suburban and rural areas.