Environmental health survey for children residing near mining areas in South Gobi, Mongolia.

BACKGROUND: We evaluated the level and factors of heavy metal exposure to children residing in the Togttsetsii, Khanbogd, and Bayandalai soums of South Gobi province, Mongolia. METHODS: A total of 118 children aged 9-12 years were surveyed, and the level of heavy metal exposure in their bodies was investigated. Exposure was investigated by measuring concentrations of heavy metals such as cadmium, lead, and mercury in the blood; mercury concentration in the hair; and total arsenic in the urine. RESULTS: Blood cadmium concentration had geometric averages of 0.16 µg/L in the children from Bayandalai, 0.15 µg/L Tsogttsetsii, and 0.16 µg/L Khanbogd. Blood lead concentration showed a relatively higher geometric average of 7.42 µg/dL in the children from Bayandalai compared to 4.78 µg/dL and 5.15 µg/dL in those from Tsogttsetsii and Khanbogd, respectively. While blood mercury concentration was the highest in the children from Bayandalai, with a value of 0.38 µg/L, those from Tsogttsetsii and Khanbogd had similar concentrations of 0.29 µg/L and 0.29 µg/L, respectively. Hair mercury concentration was the highest in the children from Bayandalai, with a value of 78 µg/g, a particularly significant difference, with a concentration of 0.50 µg/g in those from Khanbogd. Urine arsenic concentration was the highest in the children from Khanbogd, with a value of 36.93 µg/L; it was 26.11 µg/L in those from Bayandalai and 23.89 µg/L in those from Tsogttsetsii. CONCLUSIONS: The high blood lead concentration of children in Bayandalai was judged to be due to other factors in addition to mine exposure; the reason why blood and hair mercury concentration was higher in children from Bayandalai may have been due to exposure to many small-scale gold mines in the area. In the case of Khanbogd, it was estimated that the high arsenic level in urine was caused by the effect of mines.

Coal smoke, gestational cadmium exposure, and fetal growth.

BACKGROUND: Gestational cadmium exposure may impair fetal growth. Coal smoke has largely been unexplored as a source of cadmium exposure. We investigated the relationship between gestational cadmium exposure and fetal growth, and assessed coal smoke as a potential source of airborne cadmium, among non-smoking pregnant women in Ulaanbaatar, Mongolia, where coal combustion in home heating stoves is a major source of outdoor and indoor air pollution. METHODS: This observational study was nested within the Ulaanbaatar Gestation and Air Pollution Research (UGAAR) study, a randomized controlled trial of portable high efficiency particulate air (HEPA) filter air cleaner use during pregnancy, fetal growth, and early childhood development. We measured third trimester blood cadmium concentrations in 374 out of 465 participants who had a live birth. We used multiple linear and logistic regression to assess the relationships between log2-transformed maternal blood cadmium concentrations and birth weight, length, head circumference, ponderal index, low birth weight, small for gestational age, and preterm birth in crude and adjusted models. We also evaluated the relationships between log2-transformed blood cadmium concentrations and the density of coal-burning stoves within 5000 m of each participant's apartment as a proxy of coal smoke emissions from home heating stoves. RESULTS: The median (25th,75th percentile) blood cadmium concentration was 0.20 (0.15, 0.29) µg/L. A doubling of blood cadmium was associated with a 95 g (95% CI: 34, 155 g) reduction in birth weight in adjusted models. An interquartile range increase in coal stove density (from 3.4 to 4.9 gers/hectare) surrounding participants' apartments was associated with a 12.2% (95% CI: 0.3, 25.6%) increase in blood cadmium concentrations. CONCLUSIONS: Gestational cadmium exposure was associated with reduced birth weight. In settings where coal is a widely used fuel, cadmium may play a role in the putative association between air pollution and impaired fetal growth.

Evaluation of random forest regression and multiple linear regression for predicting indoor fine particulate matter concentrations in a highly polluted city.

BACKGROUND: Indoor and outdoor fine particulate matter (PM2.5) are both leading risk factors for death and disease, but making indoor measurements is often infeasible for large study populations. METHODS: We developed models to predict indoor PM2.5 concentrations for pregnant women who were part of a randomized controlled trial of portable air cleaners in Ulaanbaatar, Mongolia. We used multiple linear regression (MLR) and random forest regression (RFR) to model indoor PM2.5 concentrations with 447 independent 7-day PM2.5 measurements and 87 potential predictor variables obtained from outdoor monitoring data, questionnaires, home assessments, and geographic data sets. We also developed blended models that combined the MLR and RFR approaches. All models were evaluated in a 10-fold cross-validation. RESULTS: The predictors in the MLR model were season, outdoor PM2.5 concentration, the number of air cleaners deployed, and the density of gers (traditional felt-lined yurts) surrounding the apartments. MLR and RFR had similar performance in cross-validation (R2 = 50.2%, R2 = 48.9% respectively). The blended MLR model that included RFR predictions had the best performance (cross validation R2 = 81.5%). Intervention status alone explained only 6.0% of the variation in indoor PM2.5 concentrations. CONCLUSIONS: We predicted a moderate amount of variation in indoor PM2.5 concentrations using easily obtained predictor variables and the models explained substantially more variation than intervention status alone. While RFR shows promise for modelling indoor concentrations, our results highlight the importance of out-of-sample validation when evaluating model performance. We also demonstrate the improved performance of blended MLR/RFR models in predicting indoor air pollution.

The effect of portable HEPA filter air cleaner use during pregnancy on fetal growth: The UGAAR randomized controlled trial.

BACKGROUND: Fine particulate matter (PM2.5) exposure may impair fetal growth. AIMS/OBJECTIVES: Our aim was to assess the effect of portable high efficiency particulate air (HEPA) filter air cleaner use during pregnancy on fetal growth. METHODS: The Ulaanbaatar Gestation and Air Pollution Research (UGAAR) study is a single-blind randomized controlled trial conducted in Ulaanbaatar, Mongolia. Non-smoking pregnant women recruited at ≤18 weeks gestation were randomized to an intervention (1-2 air cleaners in homes from early pregnancy until childbirth) or control (no air cleaners) group. Participants were not blinded to their intervention status. Demographic, health, and birth outcome data were obtained via questionnaires and clinic records. We used unadjusted linear and logistic regression and time-to-event analysis to evaluate the intervention. Our primary outcome was birth weight. Secondary outcomes were gestational age-adjusted birth weight, birth length, head circumference, gestational age at birth, and small for gestational age. The study is registered at ClinicalTrials.gov (NCT01741051). RESULTS: We recruited 540 participants (272 control and 268 intervention) from January 9, 2014 to May 1, 2015. There were 465 live births and 28 losses to follow up. We previously reported a 29% (95% CI: 21, 37%) reduction in indoor PM2.5 concentrations with portable HEPA filter air cleaner use. The median (25th, 75th percentile) birth weights for control and intervention participants were 3450 g (3150, 3800 g) and 3550 g (3200, 3800 g), respectively (p = 0.34). The intervention was not associated with birth weight (18 g; 95% CI: -84, 120 g), but in a pre-specified subgroup analysis of 429 term births the intervention was associated with an 85 g (95% CI: 3, 167 g) increase in mean birth weight. CONCLUSIONS: HEPA filter air cleaner use in a high pollution setting was associated with greater birth weight only among babies born at term.

The effect of portable HEPA filter air cleaners on indoor PM2.5 concentrations and second hand tobacco smoke exposure among pregnant women in Ulaanbaatar, Mongolia: The UGAAR randomized controlled trial.

BACKGROUND: Portable HEPA filter air cleaners can reduce indoor fine particulate matter (PM2.5), but their use has not been adequately evaluated in high pollution settings. We assessed air cleaner effectiveness in reducing indoor residential PM2.5 and second hand smoke (SHS) exposures among non-smoking pregnant women in Ulaanbaatar, Mongolia. METHODS: We randomized 540 participants to an intervention group receiving 1 or 2 HEPA filter air cleaners or a control group receiving no air cleaners. We followed 259 intervention and 253 control participants to the end of pregnancy. We measured one-week indoor residential PM2.5 concentrations in early (~11weeks gestation) and late (~31weeks gestation) pregnancy and collected outdoor PM2.5 data from centrally-located government monitors. We assessed blood cadmium in late pregnancy. Hair nicotine was quantified in a subset (n=125) to evaluate blood cadmium as a biomarker of SHS exposure. We evaluated air cleaner effectiveness using mixed effects and multiple linear regression models and used stratified models and interaction terms to evaluate potential modifiers of effectiveness. RESULTS: The overall geometric mean (GM) one-week outdoor PM2.5 concentration was 47.9µg/m3 (95% CI: 44.6, 51.6µg/m3), with highest concentrations in winter (118.0µg/m3; 110.4, 126.2µg/m3). One-week indoor and outdoor PM2.5 concentrations were correlated (r=0.69). Indoor PM2.5 concentrations were 29% (21, 37%) lower in intervention versus control apartments, with GMs of 17.3µg/m3 (15.8, 18.8µg/m3) and 24.5µg/m3 (22.2, 27.0µg/m3), respectively. Air cleaner effectiveness was greater when air cleaners were first deployed (40%; 31, 48%) than after approximately five months of use (15%; 0, 27%). Blood cadmium concentrations were 14% (4, 23%) lower among intervention participants, likely due to reduced SHS exposure. CONCLUSIONS: Portable HEPA filter air cleaners can lower indoor PM2.5 concentrations and SHS exposures in highly polluted settings.

Outbound medical tourism from Mongolia: a qualitative examination of proposed domestic health system and policy responses to this trend.

BACKGROUND: Medical tourism is the practice of traveling across international boundaries in order to access medical care. Residents of low-to-middle income countries with strained or inadequate health systems have long traveled to other countries in order to access procedures not available in their home countries and to take advantage of higher quality care elsewhere. In Mongolia, for example, residents are traveling to China, Japan, Thailand, South Korea, and other countries for care. As a result of this practice, there are concerns that travel abroad from Mongolia and other countries risks impoverishing patients and their families. METHODS: In this paper, we present findings from 15 interviews with Mongolian medical tourism stakeholders about the impacts of, causes of, and responses to outbound medical tourism. These findings were developed using a case study methodology that also relied on tours of health care facilities and informal discussions with citizens and other stakeholders during April, 2012. RESULTS: Based on these findings, health policy changes are needed to address the outflow of Mongolian medical tourists. Key areas for reform include increasing funding for the Mongolian health system and enhancing the efficient use of these funds, improving training opportunities and incentives for health workers, altering the local culture of care to be more supportive of patients, and addressing concerns of corruption and favouritism in the health system. CONCLUSIONS: While these findings are specific to the Mongolian health system, other low-to-middle income countries experiencing outbound medical tourism will benefit from consideration of how these findings apply to their own contexts. As medical tourism is increasing in visibility globally, continued research on its impacts and context-specific policy responses are needed.

An assessment of air pollution and its attributable mortality in Ulaanbaatar, Mongolia.

Epidemiologic studies have consistently reported associations between outdoor fine particulate matter (PM2.5) air pollution and adverse health effects. Although Asia bears the majority of the public health burden from air pollution, few epidemiologic studies have been conducted outside of North America and Europe due in part to challenges in population exposure assessment. We assessed the feasibility of two current exposure assessment techniques, land use regression (LUR) modeling and mobile monitoring, and estimated the mortality attributable to air pollution in Ulaanbaatar, Mongolia. We developed LUR models for predicting wintertime spatial patterns of NO2 and SO2 based on 2-week passive Ogawa measurements at 37 locations and freely available geographic predictors. The models explained 74% and 78% of the variance in NO2 and SO2, respectively. Land cover characteristics derived from satellite images were useful predictors of both pollutants. Mobile PM2.5 monitoring with an integrating nephelometer also showed promise, capturing substantial spatial variation in PM2.5 concentrations. The spatial patterns in SO2 and PM, seasonal and diurnal patterns in PM2.5, and high wintertime PM2.5/PM10 ratios were consistent with a major impact from coal and wood combustion in the city's low-income traditional housing (ger) areas. The annual average concentration of PM2.5 measured at a centrally located government monitoring site was 75 µg/m3 or more than seven times the World Health Organization's PM2.5 air quality guideline, driven by a wintertime average concentration of 148 µg/m3. PM2.5 concentrations measured in a traditional housing area were higher, with a wintertime mean PM2.5 concentration of 250 µg/m3. We conservatively estimated that 29% (95% CI, 12-43%) of cardiopulmonary deaths and 40% (95% CI, 17-56%) of lung cancer deaths in the city are attributable to outdoor air pollution. These deaths correspond to nearly 10% of the city's total mortality, with estimates ranging to more than 13% of mortality under less conservative model assumptions. LUR models and mobile monitoring can be successfully implemented in developing country cities, thus cost-effectively improving exposure assessment for epidemiology and risk assessment. Air pollution represents a major threat to public health in Ulaanbaatar, Mongolia, and reducing home heating emissions in traditional housing areas should be the primary focus of air pollution control efforts.