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Abstract Background There is limited evidence regarding the modifying effects of parents’ age at childbirth on the relationship between air pollution and obesity in plateau areas. This study aimed to explore the association between particulate matter (PM) and child obesity, specifically investigating whether parents’ age at childbirth could modify this relationship in the Tibetan plateau, China. Methods Satellite-based random forest models were used to estimate the concentrations of PM2.5 (particulate matter with aerodynamic diameters ≤ 2.5 μm), PMc (particulate matter with aerodynamic diameters between 2.5 μm and 10 μm), and PM10 (particulate matter with aerodynamic diameters ≤ 10 μm). Linear and logistic regression models were employed to assess associations between PM exposure and obesity indicators, and effect estimates of PM across different particle sizes were compared. Results The study comprised 2,015 children under five years old. Postnatal exposure to PM was positively associated with overweight and obesity (OWO), waist-to-hip ratio (WHR) and body mass index (BMI). Among these pollutants, PM10 exhibited the strongest association with BMI and OWO, whereas PMc showed the strongest association with WHR. An interquartile range (IQR) increase in PM2.5 (5.67 µg/m3), PMc (5.25 µg/m3), and PM10 (11.06 µg/m3) was positively associated with OWO (odd ratio [OR] for PM2.5 = 1.52, 95% confidence interval [CI] for PM2.5 = 1.24 to 1.85; OR for PMc = 1.50, 95% CI for PMc = 1.19 to 1.88; OR for PM10 = 1.56, 95% CI for PM10 = 1.25 to 1.96), respectively. Stratified analysis by parents’ age at childbirth indicated that the effects of PM on obesity indicators were more pronounced in the advanced age group. Conclusions Long-term exposure to PM was positively associated with OWO, WHR, and BMI. Our findings also underscore the importance of examining the effects of ambient PM exposure on OWO, particularly in parents of advanced age at childbirth.

Abstract Objective: To assess urban–rural disparities in the association between long-term exposure to high altitude and malnutrition among children under 5 years old. Design: A three-stage, stratified, cluster sampling was used to randomly select eligible individuals from July to October 2020. The data of participants, including demographic characteristics, altitude of residence, and nutritional status, were collected via questionnaire and physical examination. Setting: Tibet, China. Participants: Children under 5 years old in Tibet. Results: Totally, 1975 children under 5 years old were included in this study. We found that an additional 1000 m increase in altitude was associated with decreased Z-scores of height-for-age (β = –0·23, 95 % CI: –0·38, –0·08), Z-scores of weight-for-age (β = –0·24, 95 % CI: –0·39, –0·10). The OR for stunting and underweight were 2·03 (95 % CI: 1·51 to 2·73) and 2·04 (95 % CI: 1·38 to 3·02) per 1000 m increase in altitude, respectively; and OR increased rapidly at an altitude above 3500 m. The effects of long-term exposure to high altitudes on the prevalence of underweight in rural children were higher than that in urban children (P < 0·05). Conclusions: High-altitude exposure is tightly associated with malnutrition among children under 5 years old. Improving children’s nutrition is urgently needed in areas above 3500 m, especially in rural ones.

Background There is limited evidence on association between air pollutants and hospital admissions, hospital cost and length of stay (LOS) among patients with diabetes mellitus (DM) and comorbid respiratory diseases (RD), especially in low- and middle-income countries (LMICs) with low levels of air pollution. Methods Daily data on RD-DM patients were collected in Panzhihua from 2016 to 2020. A generalised additive model (GAM) was used to explore the effect of air pollutants on daily hospital admissions, LOS and hospital cost. Attributable risk was employed to estimate RD-DM's burden due to exceeding air pollution exposure, using both 0 microgrammes per cubic metre (μg/m3) and WHO's 2021 air quality guidelines as reference. Results For each 10 ug/m3 increase of particles with an aerodynamic diameter <2.5 micron (≥m) (PM2.5), particles with an aerodynamic diameter <10 ≥m (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3), the admissions of RD-DM patients increased by 7.25% (95% CI = 4.26 to 10.33), 5.59% (95% CI = 3.79 to 7.42), 10.10% (95% CI = 7.29 to 12.98), 12.33% (95% CI = 8.82 to 15.95) and -2.99% (95% CI = -4.08 to -1.90); per 1 milligramme per cubic metre (mg/m3) increase of carbon monoxide (CO) corresponded to a 25.77% (95% CI = 17.88 to 34.19) increment for admissions of RD-DM patients. For LOS and hospital cost, the six air pollutants showed similar effect. Given 0 μg/m3 as the reference, NO2 showed the maximum attributable fraction of 32.68% (95% CI = 25.12 to 39.42%), corresponding to an avoidable burden of 5661 (95% CI = 3611 to 5860) patients with RD-DM. Conclusions There is an association between PM2.5, PM10, SO2, NO2, and CO with increased hospital admissions, LOS and hospital cost in patients with RD-DM. Disease burden of RD-DM may be improved by formulating policies related to air pollutants exposure reduction, especially in LMICs with low levels of air pollution. [ABSTRACT FROM AUTHOR]

Background The evidence regarding the relationship between postnatal exposure of air pollution and child malnutrition indicators, as well as the corresponding urban-rural disparities, is limited, especially in low-pollution area of low- and middle-income countries (LMICs). Therefore, our aim was to contrast the effect estimates of varying ambient particulate matter (PM) on malnutrition indicators between urban and rural areas in Tibet, China. Methods Six malnutrition indicators were evaluated in this study, namely, Z-scores of height for age (HFA), Z-scores of weight for age (WFA), Z-scores of weight for height (WFH), stunting, underweight, and wasting. Exposure to particles with an aerodynamic diameter ≤2.5 micron (μm) (PM2.5), particles with an aerodynamic diameter ≤10 μm (PM10) and particles with an aerodynamic diameter between 2.5 and 10 μm (PMc) was estimated using satellite-based random forest models. Linear regression and logistic regression models were used to assess the associations between PM and the above malnutrition indicators. Furthermore, the effect estimates of different PM were contrasted between urban and rural areas. Results A total of 2511 children under five years old were included in this study. We found long-term exposure to PM2.5, PMc, and PM10 was associated with an increased risk of stunting and a decreased risk of underweight. Of these air pollutants, PMc had the strongest association for Z-scores of HFA and stunting, while PM2.5 had the strongest association for underweight. The results showed that the odds ratio (OR) for stunting were 1.36 (95% confidence interval (CI)=1.06 to 1.75) per interquartile range (IQR) microgrammes per cubic metre (μg/m3) increase in PM2.5, 1.80 (95% CI=1.30 to 2.50) per IQR μg/m3 increase in PMc and 1.55 (95% CI=1.17 to 2.05) per IQR μg/m3 increase in PM10. The concentrations of PM were higher in urban areas, and the effects of PM on malnutrition indicators among urban children were higher than those of rural children. Conclusions Our results suggested that PM exposure might be an important trigger of child malnutrition. Further prospective researches are needed to provide important scientific literature for understanding child malnutrition risk concerning postnatal exposure of air pollutants and formulating synthetically social and environmental policies for malnutrition prevention. [ABSTRACT FROM AUTHOR]