Previous studies have indicated that outdoor light at night (LAN) is associated with a higher prevalence of overweight or obesity in adults. However, the association of LAN levels with overweight or obesity in children is still unknown. This study utilized data from the Seven Northeastern Cities study, which included 47,990 school-aged children and adolescents (ages 6–18 years). Outdoor LAN levels were measured using satellite imaging data. Weight and height were used to calculate age-sex-specific body mass index (BMI) Z-scores based on the World Health Organization (WHO) growth standards. Overweight status and obesity were defined using the Chinese standard. Information regarding socioeconomic status, sleep-related characteristics, and obesogenic factors were obtained using a questionnaire. A generalized linear mixed model examined the associations of outdoor LAN levels (in quartiles) with the outcomes of interest. Compared to children in the lowest quartile of outdoor LAN levels, children exposed to higher outdoor LAN levels had larger BMI Z-scores and higher odds of being overweight (including obesity) or obese, with the largest estimates in the third quartile [BMI Z-score: β = 0.26, 95% CI: 0.18–0.33; overweight (including obesity): OR = 1.40, 95% CI: 1.25–1.56; obesity: OR = 1.46, 95% CI: 1.29–1.65]. There was a significant sex difference (Pᵢₙₜₑᵣₐcₜᵢₒₙ<0.001) in the association of outdoor LAN levels with BMI Z-scores, and the association was stronger in males. Results remained robust following multiple sensitivity analyses and the adjustment of sleep-related characteristics, obesogenic factors, and environmental exposures. Our findings suggest that higher outdoor LAN levels are associated with larger BMI Z-scores and greater odds of overweight (including obesity) and obesity in school-aged children and adolescents. Further, the association between outdoor LAN levels and BMI Z-scores is stronger in males. Future studies with exposure assessments that consider both outdoor and indoor LAN exposures are needed.

Ambient particles with aerodynamic diameter <0.1 μm (PM₀.₁) have been suggested to have significant health impact. However, studies on the association between long-term PM₀.₁ exposure and human blood lipid metabolism are still limited. This study was aimed to evaluate such association based on multiple lipid biomarkers and dyslipidemia indicators. We matched the 2006–2009 average PM₀.₁ concentration simulated using the neural-network model following the WRF-Chem model with the clinical and questionnaire data of 15,477 adults randomly recruited from 33 communities in Northeast China in 2009. After controlling for social demographic and behavior confounders, we assessed the association of PM₀.₁ concentration with multiple lipid biomarkers and dyslipidemia indicators using generalized linear mixed-effect models. Effect modification by various social demographic and behavior factors was examined. We found that each interquartile range increase in PM₀.₁ concentration was associated with a 5.75 (95% Confidence interval, 3.24–8.25) mg/dl and a 6.05 (2.85–9.25) mg/dl increase in the serum level of total cholesterol and LDL-C, respectively. This increment was also associated with an odds ratio of 1.25 (1.10–1.42) for overall dyslipidemias, 1.41 (1.16, 1.73) for hypercholesterolemia, and 1.90 (1.39, 2.61) for hyperbetalipoproteinemia. Additionally, we found generally greater effect estimates among the younger participants and those with lower income or with certain behaviors such as high-fat diet. The deleterious effect of long-term PM₀.₁ exposure on lipid metabolism may make it an important toxic chemical to be targeted by future preventive strategies.

This international scale study measured the prevalence of indoor microplastics (MPs) in deposited dust in 108 homes from 29 countries over a 1-month period. Dust borne MPs shape, colour, and length were determined using microscopy and the composition measured using μFTIR. Human health exposure and risk was assessed along with residential factors associated with MPs via a participant questionnaire. Samples were categorised according to each country's gross national income (GNI). Synthetic polymers dominated in low income (LI) (39%) and high income (HI) (46%) while natural fibres were the most prevalent in medium income (MI) (43%) countries. Composition and statistical analysis showed that the main sources of MPs and dust were predominantly from indoor sources. Across all GNI countries, greater vacuuming frequency was associated with lower MPs loading. High income country samples returned higher proportions of polyamides and polyester fibres, whereas in LI countries polyurethane was the most prominent MPs fibre. Exposure modelling showed infants (0–2 years) were exposed to the highest MPs dose through inhalation (4.5 × 10⁻⁵ ± 3 × 10⁻⁵) and ingestion (3.24 × 10⁻² ± 3.14 × 10⁻²) mg/kg-Bw/day. Health risk analysis of constituent monomers of polymers indicates cancer incidence was estimated at 4.1–8.7 per million persons across age groups. This study's analysis showed socio-economic factors and age were dominant variables in determining dose and associated health outcomes of MPs in household dust.

Rice and vegetables cultivated in naturally arsenic (As) endemic areas are the substantial source of As body loading for persons using safe drinking water. However, tracing As intake, particularly from rice and vegetables by biomarker analysis, has been poorly addressed. This field investigation was conducted to trace the As transfer pathway and measure health risk associated with consuming As enriched rice and vegetables. Purposively selected 100 farmers from five sub-districts of Chandpur, Bangladesh fulfilling specific requirements constituted the subjects of this study. A total of 100 Irrigation water, soils, rice, and vegetable samples were collected from those farmers’ who donated scalp hair. Socio-demographic and food consumption data were collected face to face through questionnaire administration. The mean As level in irrigation water, soils, rice, vegetables, and scalp hairs exceeded the acceptable limit, while As content was significant at 0.1%, 5%, 0.1%, 1%, and 0.1% probability levels, respectively, in all five locations. Arsenic in scalp hair is significantly (p ≤ 0.01) correlated with that in rice and vegetables. The bioconcentration factor (BCF) for rice and vegetables is less than one and significant at a 1% probability level. The average daily intake (ADI) is higher than the RfD limit for As. Both grains and vegetables have an HQ (hazard quotient) > 1. Maximum incremental lifetime cancer risk (ILCR) showed 2.8 per 100 people and 1.6 per 1000 people are at considerable and threshold risk, respectively. However, proteinaceous and nutritious food consumption might have kept the participants asymptomatic. The PCA analysis showed that the first principle component (PC1) explains 91.1% of the total variance dominated by As in irrigation water, grain, and vegetables. The dendrogram shows greater variations in similarity in rice and vegetables As, while the latter has been found to contribute more to human body loading compared to grain As.

Limited attention has been given to the presence of MPs in the atmospheric environment, particularly in indoor environments where people spend about 90% of their time. This study quantitatively assesses the prevalence, source and type of MPs in Australian homes with the goal of evaluating human health exposure potential. Thirty-two airborne indoor deposited dust samples were collected in glass Petri dishes from Sydney (Australia) homes, over a one-month period in 2019. Participants completed a questionnaire on their household characteristics. Samples were analysed using a stereomicroscope, a fluorescent microscope and micro-Fourier transform infrared (FTIR) spectroscopy for their colour, size, shape and composition. Inhalation and ingestion rates were modelled using US EPA exposure factors. Microplastic fibre deposition rates ranged from 22 to 6169 fibres/m²/day. Deposited dust comprised 99% fibres. The highest proportion of fibres (19%) were 200–400 μm in length. The majority were natural (42%); 18% were transformed natural-based fibres; and 39% were petrochemical based. A significant difference was observed between the deposition rate and the main floor covering (p-value <0.05). Polyethylene, polyester, polyamide, polyacrylic, and polystyrene fibres were found in higher abundance in homes with carpet as the main floor covering. Where carpet was absent, polyvinyl fibres were the most dominant petrochemical fibre type, indicating the role of flooring materials (e.g. wood varnishes) in determining MP composition. Vacuum cleaner use was significantly related to MP deposition rates (p-value <0.05). MP ingestion rates peaked at 6.1 mg/kg-Bw/year for ages 1–6, falling to a minimum of 0.5 mg/kg-Bw/year in >20 years age group. Mean inhaled MP weight and count was determined to be 0.2±0.07 mg/kg-Bw/year and 12891±4472 fibres/year. Greatest inhalation intake rates were for the <0.5-yr age group, at 0.31 mg/kg-Bw/year. The study data reveal that MPs are prevalent in Australian homes and that the greatest risk of exposure resides with young children. Notwithstanding the limited number of global studies and the different methods used to measure MPs, this study indicates Australian deposition and inhalation rates are at the lower end of the exposure spectrum.

Allergic diseases have been one of the leading causes of chronic disorders in the United States. Animal studies have suggested that exposures to perchlorate, nitrate, and thiocyanate could induce allergic inflammation. However, the associations have not been examined among general populations. Here, we investigated data of 7030 participants aged ≥6 years from the National Health and Nutritional Examination Survey (NHANES) 2005–2006. Urinary levels of perchlorate, nitrate, and thiocyanate were measured by ion chromatography combined with electrospray tandem mass spectrometry. Information on allergic symptoms (hay fever, allergy, rash, sneeze, wheeze, eczema, and current asthma) was collected by questionnaire. Allergic sensitization was defined by a concentration ≥150 kU/L for total immunoglobulin E (IgE) levels. The associations were estimated using multivariate-adjusted logistic regression models. A positive association was observed for urinary nitrate and eczema (p < 0.001 for the trend). Compared with quartile 1 (lowest quartile), the odds ratios of eczema with 95% confidence intervals [ORs (95% CIs)] from quartiles 2 to 4 were 1.72 (95% CI, 1.41, 2.09), 1.94 (1.53, 2.47) and 2.10 (1.49, 2.97) for urinary nitrate. In addition, urinary thiocyanate was positively related to sneeze (ORQ₄ ᵥₛ. Q₁: 1.25, 95% CI: 1.01, 1.55; p = 0.015 for the trend). However, urinary perchlorate was not correlated with any allergic-related outcome. Additionally, the associations were different among subgroups in a four-level polytomous model. Thus, our results suggested that exposures to nitrate and thiocyanate may be associated with allergic symptoms. Further investigations are warranted to concentrate on the practical strategies to monitor exposure levels and the latent mechanisms of the relationship between exposure and allergy.

The prevalence of allergic diseases in Australian children is high, but few studies have assessed the potential role of outdoor air pollution in allergic sensitization. We investigated the association between outdoor air pollution and the prevalence of aeroallergen sensitization in a national cross-sectional study of Australian children aged 7–11 years. Children were recruited from 55 participating schools in 12 Australian cities during 2007–2008. Parents completed a detailed (70-item) questionnaire. Outdoor nitrogen dioxide (NO₂), as a proxy for exposure to traffic-related emissions, was estimated using measurements from regulatory monitors near each school and a national land-use regression (LUR) model. Three averaging periods were assessed, using information on duration of residence at the address, including lifetime, previous (lifetime, excluding the last year), and recent (the last year only). The LUR model was used as an additional source of recent exposure estimates at school and home addresses. Skin prick tests (SPTs) were performed to measure sensitization to eight common aeroallergens. Multilevel logistic regression estimated the association between NO₂ and sensitization (by individual allergens, indoor and outdoor allergens, and all allergens combined), after adjustment for individual- and area-level covariates. In total, 2226 children had a completed questionnaire and SPT. The prevalence of sensitization to any allergen was 44.4%. Sensitization to house dust mites (HDMs) was the most common (36.1%), while sensitization to Aspergillus was the least common (3.4%). Measured mean (±s.d.) NO₂ exposure was between 9 (±2.9) ppb and 9.5 (±3.2) ppb, depending on the averaging period. An IQR (4 ppb) increase in measured previous NO₂ exposure was associated with greater odds of sensitization to HDMs (OR: 1.21, 95% CI: 1.01–1.43, P = 0.035). We found evidence of an association between relatively low outdoor NO₂ concentrations and sensitization to HDMs, but not other aeroallergens, in Australian children aged 7–11 years.

Air pollution is a global threat to public health, especially when considering susceptible populations, such as children. A better understanding of determinants of exposure could help epidemiologists in refining exposure assessment methods, and policy makers in identifying effective mitigation interventions. Through a participatory approach, 73 and 89 schoolchildren were involved in a two-season personal exposure monitoring campaign of equivalent black carbon (EBC) in Milan, Italy. GPS devices, time-activity diaries and a questionnaire were used to collect personal information. Exposure to EBC was 1.3 ± 1.5 μg/m³ and 3.9 ± 3.3 μg/m³ (mean ± sd) during the warm and the cold season, respectively. The highest peaks of exposure were detected during the home-to-school commute. Children received most of their daily dose at school and home (82%), but the highest dose/time intensity was related to transportation and outdoor environments. Linear mixed-effect models showed that meteorological variables were the most influencing predictors of personal exposure and inhaled dose, especially in the cold season. The total time spent in a car, duration of the home-to-school commute, and smoking habits of parents were important predictors as well. Our findings suggest that seasonality, time-activity and mobility patterns play an important role in explaining exposure patterns. Furthermore, by highlighting the contribution of traffic rush hours, transport-related microenvironments and traffic-related predictors, our study suggests that acting on a local scale could be an effective way of lowering personal exposure to EBC and inhaled dose of children in the city of Milan.

Lead (Pb) exposure is known to affect the health of children while soil Pb is an important contributor to human Pb exposure. To analyze the effects of both environmental and other factors, especially total and bioaccessible Pb in neighborhood soil, on school-aged urban children’s blood lead level (BLL), 75 children (6–11 years old) were recruited from an industry city in eastern China for BLL measurement and questionnaire survey. Soil samples were collected from their living neighborhoods and measured for total and bioaccessible Pb. The mean BLL was 4.82 μg dL⁻¹, with 42 out of 75 children having BLL exceeding the international guideline of 5 μg dL⁻¹. Low Pb contamination was observed in soil with total Pb ranging from 12.5 to 271 mg kg⁻¹ (mean 34.3 mg kg⁻¹). Based on the in vitro Solubility Bioaccessibility Research Consortium (SBRC) gastric fluid extraction, bioaccessible Pb in soil ranged from 0.40 to 79.1 mg kg⁻¹ (mean 7.58 mg kg⁻¹) with Pb bioaccessibility ranging from 1.74 to 68.1 (mean 19.9%). When BLL was correlated with total Pb in soil, insignificant linear relationship was observed (P > 0.05, correlation coefficient 95%CI = −0.047–0.40, R² = 0.07). However, when BLL was correlated with soil bioaccessible Pb or Pb bioaccessibility, much stronger linear relationships were observed (P < 0.01, correlation coefficient 95%CI = 0.28–0.64, R² = 0.16–0.20), suggesting that bioaccessible Pb was a much stronger predictor of BLL. In addition, strong associations were also observed between BLL and social factors such as house decoration, residence time, and personal habits, suggesting that both soil Pb contamination and social factors play important roles in elevating BLL for city children.

In the study, personal PM₂.₅ exposures and their source contributions were characterized for 159 subjects living in the Beijing Metropolitan area. The exposures and sources were examined as functions of residential location, season, vocation, cigarette smoking, and time spent outdoors. Sampling was performed for two categories of volunteers, guards and students, that lived in urban and suburban areas of Beijing. Samples were collected using portable PM₂.₅ monitors during summer and winter. Exposure measurements were supplemented with a questionnaire that tracked personal activity and time spent in microenvironments that may have impacted exposures. Simultaneously, ambient PM₂.₅ data were obtained from national network stations located at the Gucheng and Huairouzhen sites. These data were used as a comparison against the personal PM₂.₅ exposures and produced poor correlations between personal and ambient PM₂.₅. These results demonstrate that individual behavior strongly affects personal PM₂.₅ exposure. Six primary sources of personal PM₂.₅ exposure were determined using a positive matrix factorization (PMF) source apportionment model. These sources included Roadway Transport Source, Soil/Dust Source, Industrial/Combustion Source, Secondary Inorganic Source, Cd Source, and Household Heating Source. Averaged across all subjects and seasons, the highest source contribution was Secondary Inorganic Source (24.8% ± 32.6%, AVG ± STD), whereas the largest primary ambient source was determined to be Roadway Transport (20.9% ± 13.6%). Subjects were classified according to the questionnaire and were used to help understand the relationship between personal activity and source contribution to PM₂.₅ exposure. In general, primary ambient sources showed only significant spatial and seasonal differences, while secondary sources differed significantly between populations with different personal behavior. In particular, Cd source was found to be related to smoking exposure and was the most unpredictable source, with significant differences between populations of different sites, vocations, smoking exposures, and outdoor time.