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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 (ß = -0·23, 95 % CI: -0·38, -0·08), Z-scores of weight-for-age (ß = -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.
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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.
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Poluentes Atmosféricos , Transtornos da Nutrição Infantil , Desnutrição , Criança , Humanos , Pré-Escolar , Material Particulado/toxicidade , Estudos Transversais , Magreza/epidemiologia , Desnutrição/epidemiologia , China/epidemiologia , Poluentes Atmosféricos/toxicidade , Transtornos do Crescimento/epidemiologiaRESUMO
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 (µm) (PM2.5), particles with an aerodynamic diameter <10 µm (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.
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Poluentes Atmosféricos , Poluição do Ar , Diabetes Mellitus , Doenças Respiratórias , Humanos , Tempo de Internação , Dióxido de Nitrogênio/análise , Custos Hospitalares , Poluição do Ar/efeitos adversos , Poluentes Atmosféricos/efeitos adversos , Poluentes Atmosféricos/análise , Diabetes Mellitus/epidemiologia , China/epidemiologia , Material Particulado/efeitos adversos , Material Particulado/análise , Hospitais , Doenças Respiratórias/epidemiologiaRESUMO
Background: The associations of ambient air pollution with hospital admissions (HAs) for overall and specific causes of cardiovascular diseases (CVDs), as well as related morbidity and economic burdens remain understudied, especially in low-pollution areas of low- and middle-income countries (LMICs). We evaluated the short-term effects of exposure to PM2.5 (particles with an aerodynamic diameter ≤2.5 µm), PM10 (particles with an aerodynamic diameter ≤10 µm), and SO2 (sulfur dioxide) on HAs for CVDs in Panzhihua, China, during 2016-2020, and calculated corresponding attributable risks and economic burden. Methods: We used a generalized additive model (GAM) while controlling for time trends, meteorological conditions, holidays, and days of the week to estimate the associations. The cost of illness (COI) method was adopted to further assess corresponding hospitalization costs and productivity losses. Results: A total of 27 660 HAs for CVDs were included in this study. PM10 and SO2 were significantly associated with elevated risks of CVDs hospitalizations. Each 10 µg/m3 increase in PM10 and SO2 at lag06 corresponded to an increase of 2.48% (95% confidence interval (CI) = 0.92%-4.06%), and 5.50% (95% CI = 3.09%-7.97%) in risk of HAs for CVDs, respectively. The risk estimates of PM10 and SO2 on CVD hospitalizations were generally robust after adjustment for other pollutants in two-pollutant models. We found stronger associations between air pollution (PM10 and SO2) and CVDs in cool seasons than in warm seasons. For specific causes of CVDs, significant associations of PM10 and SO2 exposure with cerebrovascular disease and ischaemic heart disease were observed. Using 0 µg/m3 as the reference concentrations, 11.91% (95%CI = 4.64%-18.56%) and 15.71% (95%CI = 9.30%-21.60%) of HAs for CVDs could be attributable to PM10 and SO2, respectively. During the study period, PM10 and SO2 brought 144.34 million Yuan economic losses for overall CVDs, accounting for 0.028% of local GDP. Conclusions: Our results suggest that PM10 and SO2 exposure might be an important trigger of HAs for CVDs and accounted for substantial morbidity and economic burden.