P-0013 - Investigating potential associations between O3 exposure and lipid profiles: A longitudinal study of older adults in Beijing
Abstract Control Number
2003
Abstract Body
Background: Little information exists on the lipidemic effects of ozone exposure. Few studies have focused on the different patterns of the association among older adults population, and little attention has been given to comprehensive lipid indices when evaluating the effect of O3 exposure on the metabolism. Methods: We conducted a longitudinal study involving 201 older adults in Beijing, China between 2016-2018. A mixed regression model was applied with random effects to investigate the relationship between O3 and lipid profiles. Results: O3 exposure positively correlated with TC, LDL-C, CRI-I, CRI-II and AC at short-term and medium-term exposure periods. The largest increases in TC, LDL-C, CRI-I and CRI-II were found in the 28-days moving average indicating accumulative effects over prolonged exposure period. A 10μg/m3 increase of O3 at the 28-days moving average was associated with a significant increase of 3.9% (95% CI: 1.0, 6.9) in TC, 8.2% (95% CI: 4.2, 12.4) in LDL-C, 4.8% (95% CI: 1.1, 8.5) in CRI-I and 7.0% (95% CI: 2.7, 11.5) in CRI-II. Stratification by health status and characteristics revealed different patterns of lipid changes among older adults, lipid status, age, sex and BMI may modify the relationship between O3 exposure and lipid profiles. Conclusions: Our findings suggest that short-term and medium-term O3 exposure is associated with lipid profiles abnormalities among the older adults. Evidence also suggests there are patterns within population which differ according to both health status and demographic characteristics.
P-0014 - Cognitive impact of polluted landscape and its neural basis: Evidence based on an Event-related Potential study
Abstract Control Number
2019
Abstract Body
Background Abundant studies suggest that long-term exposure to air pollution such as particulate matter (PM) can impair cognitive functions. Systemic and brain inflammation induced by pollutants are recognized as the major cause. Recently, new evidence emerged that even “mild” exposure to air pollution, for instance the visual impact of air pollutants can influence mental health and cognitive performance. Such effect is hard to capture but may lead to lowered productivity in daily life. Methods We utilized the event-related potential (ERP) technique to prove the existence of cognitive impact caused by polluted landscape. Thirty-two undergraduate students from Nanjing, China participated the experiment. A dot-probe task was designed as follows. Two horizontal or two vertical dots were presented at the left or right visual field. This target was preceded by a cue (i.e., clean or polluted pictures) at either the target location (valid trials) or at the opposite location (invalid trials). Participants were asked to respond to the target (vertical or horizontal) as soon and accurate as possible. We hypothesized invalid trials and trials cued by polluted pictures would cause participants longer reaction time. Meanwhile, averaged electroencephalogram signals, i.e. the event-related potential, of four trial types (clean-valid, polluted-valid, clean-invalid, polluted-invalid) were extracted to reveal the underlying neural cognitive basis. Results There is a significant positive effect of invalidation, pollution and their interactions on response time, which means visual impact of pollution distracts attention and slows decision-making process. ERP data shows a frontal negativity for pollution trials after 1600-2000ms cue onset. This may serve as the neural basis of how human brain reacts to polluted landscapes. Conclusions To our knowledge, this is the first study adopting ERP technique to investigate the cognitive impact of visual impact caused by air pollution. The findings call for attention to this subtle phenomenon especially in developing countries.
P-0015 - Outdoor Air Quality and Antibiogram Characteristics of Bacterial Isolates of Akure City Abattoirs, Nigeria
Abstract Control Number
2025
Abstract Body
Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:\"Table Normal\"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:\"\"; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:\"Calibri\",\"sans-serif\"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} Air sampling of Onyearugbulem and FUTA abattoirs was carried out to evaluate their quality. Air sampling was done using the open-settling method on general and selective agar media of the gutter, sleeping bench, slaughtering floor dumpsite, slaughtering table and roof of the abattoirs. Using standard methods, Presumptive identification of the bacterial isolates was carried out. An array of ten (10) conventional antibiotics was used to assay the antibiotic susceptibility characteristics of the bacterial isolates. Multiple antibiotic sensitivity index (MARI) was determined for isolated bacteria. At Onyearugbulem abattoir, the total Escherichia coli count ranged from 3.6×10 cfu/ml from the gutter and slaughtering table to 6.5×10 cfu/ml from the slaughtering floor, while the total bacterial count ranged from 1.34×102 cfu/ml from dumpsite to 2.55×102 cfu/ml from the gutter, the total coliform count ranged from 2.8×10 cfu/ml from slaughtering floor to 4.1×10 cfu/ml from sleeping bench. Several bacteria were presumptively isolated. These include: Micrococcus sp., Bacillus sp., Staphylococcus aureus, Escherichia coli, Proteus sp., Enterobacter aerogenes and Aeromonas sp. Ciprofloxacin (10 µg) had an inhibitory effect on all the Gram positive bacterial isolates with the highest inhibitory activity on S. aureus at 24.00 mm, and the Gram negative bacteria with the highest inhibitory activity on E. coli at 21.00 mm. Micrococcus sp. had the highest MARI of 0.8. These findings reveal the presence of multiple-antibiotic resistant bacteria in Onyearugbulem and FUTA abattoirs’ atmosphere. There is therefore need for routine environmental sanitation of the slaughterhouses.
P-0016 - Bayesian Predictive Modeling of Household Air Pollution Concentrations for 25,000 Rural Households across 8 Countries in the PURE-AIR Study
Abstract Control Number
2198
Abstract Body
Background/Aim: Global quantitative estimation of household air pollution (HAP) exposure is critical for assessing associated health impacts. Previous global HAP modeling studies have aggregated published measurements, which can introduce bias by combining data from various study protocols.
Methods: The Prospective Urban and Rural Epidemiology (PURE)-AIR study, one of the largest HAP measurement studies to-date, included 48-hour fine particulate matter (PM2.5) kitchen concentrations in a stratified-sample (2,541 households) proportional to primary cooking fuel type across 120 rural communities within eight countries (Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania, Zimbabwe). Additionally, survey data captured detailed information on household cooking characteristics/behaviors. Random forest modeling was used to rank predictors of measured PM2.5 concentrations. Selected factors and weakly informative priors from a previous global model using PM2.5 measurements available in the WHO Global HAP database were included in a Bayesian hierarchical predictive model of PM2.5 concentrations. Model performance was assessed via leave-one-out cross-validation. The chosen model was then applied to 26,197 households in the eight countries, with available survey data but no PM2.5 monitoring.
Results: Primary cooking fuel type, heating fuel type, roofing material, primary drinking water source, household size, household income and kitchen ventilation (windows) were the most important predictors of household PM2.5 concentrations; an R2 of 0.49 and mean absolute error of 49 μg/m3 resulted from the Bayesian model. Modeled global average 48-hour PM2.5 concentrations among households using gas as a primary cooking fuel (46 μg/m3; 95%CI:[32,64]) were lower than those using coal (68 μg/m3; 95%CI:[37,124]), wood (72 μg/m3; 95%CI:[65,80]), grass/shrubs (81 μg/m3; 95%CI:[45,147]) and animal dung (98 μg/m3; 95%CI:[50,194]).
Conclusions: HAP monitoring in a strategic sub-sample of households alongside detailed survey data collection provides a feasible, multinational quantitative assessment of HAP exposure. Improved global estimates of PM2.5 concentrations can be used to improve risk assessment models and epidemiological analyses of HAP.
Methods: The Prospective Urban and Rural Epidemiology (PURE)-AIR study, one of the largest HAP measurement studies to-date, included 48-hour fine particulate matter (PM2.5) kitchen concentrations in a stratified-sample (2,541 households) proportional to primary cooking fuel type across 120 rural communities within eight countries (Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania, Zimbabwe). Additionally, survey data captured detailed information on household cooking characteristics/behaviors. Random forest modeling was used to rank predictors of measured PM2.5 concentrations. Selected factors and weakly informative priors from a previous global model using PM2.5 measurements available in the WHO Global HAP database were included in a Bayesian hierarchical predictive model of PM2.5 concentrations. Model performance was assessed via leave-one-out cross-validation. The chosen model was then applied to 26,197 households in the eight countries, with available survey data but no PM2.5 monitoring.
Results: Primary cooking fuel type, heating fuel type, roofing material, primary drinking water source, household size, household income and kitchen ventilation (windows) were the most important predictors of household PM2.5 concentrations; an R2 of 0.49 and mean absolute error of 49 μg/m3 resulted from the Bayesian model. Modeled global average 48-hour PM2.5 concentrations among households using gas as a primary cooking fuel (46 μg/m3; 95%CI:[32,64]) were lower than those using coal (68 μg/m3; 95%CI:[37,124]), wood (72 μg/m3; 95%CI:[65,80]), grass/shrubs (81 μg/m3; 95%CI:[45,147]) and animal dung (98 μg/m3; 95%CI:[50,194]).
Conclusions: HAP monitoring in a strategic sub-sample of households alongside detailed survey data collection provides a feasible, multinational quantitative assessment of HAP exposure. Improved global estimates of PM2.5 concentrations can be used to improve risk assessment models and epidemiological analyses of HAP.
P-0017 - Particulate matter air pollution, neighborhood socio-economic status, and leukocyte telomere length
Abstract Control Number
2199
Abstract Body
Background: Telomeres cap and protect chromosomes from degradation and risk factors for telomere attrition include aging and environmental factors. Although exposure to some air pollutants and neighborhood socio-economic factors (nSES) have been associated with telomere length, evidence of associations between exposure to particulate matter (PM) air pollution, nSES, and the interaction between the two in relation to telomere length is limited and inconclusive. Our objective was to examine the associations between exposure to short-, intermediate-, and long-term (1-, 3-, and 12-month) exposure to different size fractions of PM (<2.5 microns [PM2.5], 2.5-10 microns [PM10-2.5], and <10 microns [PM10]) and nSES at blood draw, and leukocyte telomere length.
Methods: We used generalized linear regression models to examine the associations between each of the PM exposure metrics, nSES, and z-scores of log-transformed telomere length in 10,212 female participants of the nationwide Nurses’ Health Study, after adjusting for demographics and telomere attrition risk factors. Using participants’ address history, we applied spatio-temporal prediction models to estimate monthly PM exposures.
Results: In adjusted models, PM2.5 exposure per 10 μg/m3 increase was not associated with relative telomere length: 1-month exposure: β: 0.01, standard error (SE): 0.01, p: 0.40; 3-month exposure: β: 0.01, SE: 0.01, p: 0.37; 12-month exposure: β: 0.01, SE: 0.01, p: 0.34. Results for exposure to PM10-2.5, and PM10 were similar. nSES at blood draw was also not associated with telomere length: β: -0.001, SE: 0.001, p: 0.28. We observed no multiplicative interactions between 1-, 3-, and 12-month PM exposures and nSES.
Conclusions: In this study of U.S. women, short-, intermediate-, and long-term PM exposures were not associated with telomere attrition for any size fraction of PM; nSES was also not associated with telomere length. Additionally, we observed no interactions between PM exposures and nSES in association with telomere length.
Methods: We used generalized linear regression models to examine the associations between each of the PM exposure metrics, nSES, and z-scores of log-transformed telomere length in 10,212 female participants of the nationwide Nurses’ Health Study, after adjusting for demographics and telomere attrition risk factors. Using participants’ address history, we applied spatio-temporal prediction models to estimate monthly PM exposures.
Results: In adjusted models, PM2.5 exposure per 10 μg/m3 increase was not associated with relative telomere length: 1-month exposure: β: 0.01, standard error (SE): 0.01, p: 0.40; 3-month exposure: β: 0.01, SE: 0.01, p: 0.37; 12-month exposure: β: 0.01, SE: 0.01, p: 0.34. Results for exposure to PM10-2.5, and PM10 were similar. nSES at blood draw was also not associated with telomere length: β: -0.001, SE: 0.001, p: 0.28. We observed no multiplicative interactions between 1-, 3-, and 12-month PM exposures and nSES.
Conclusions: In this study of U.S. women, short-, intermediate-, and long-term PM exposures were not associated with telomere attrition for any size fraction of PM; nSES was also not associated with telomere length. Additionally, we observed no interactions between PM exposures and nSES in association with telomere length.
P-0018 - Determinants of exposure to ultrafine particles (PUF) and black carbon (BC) inside Parisian taxi vehicles: the PUF-TAXI project
Abstract Control Number
2248
Abstract Body
Background In the last decades, traffic related air pollutants (TRAP) have decreased in response to the implementation of stricter emission standards and to new technologies in automobile fleet. Despite these improvements, taxi drivers remain highly exposed to TRAP due to their proximity to the “traffic source” and the significant amount of time spent in traffic. Thus, we aimed to identify the determinants of Parisian taxi drivers’ exposure to ultrafine particles (UFP) and black carbon (BC), pollutants of recent interest, inside their vehicles.MethodsIn this cross-sectional study, we studied 499 trips conducted by 50 Parisian taxi drivers from PUF-TAXI project. UFP and BC were measured inside taxis by Diffusion Size Classifier Miniature® and microAeth® AE51, respectively, for 9 hours during normal service. Data on vehicles and trips characteristics were collected by questionnaires and face to face interviews. Associations between pollutants levels and their determinants were analyzed using Generalized Estimating Equations (GEE) model adjusting for potential confounders. ResultsUFP (32.3 ± 37.5 pt/cm3) and BC (3.3 ± 2.3 μg/m³) mean concentrations per trip inside taxi vehicles were moderately correlated (r= 0.3, p <0.001). The analyses showed that levels of UFP and BC inside taxi vehicles were greatly influenced by ventilation settings. The use of air-conditioning (A/C) with closed windows reduced UFP and BC by 53% and 19%, respectively. However, maximum air protection was obtained when both A/C and air recirculation were on. Vehicles speed, trips destinations were also significant determinants of in-taxis UFP and BC levels. In addition, the variability of BC levels inside taxis depended significantly on ambient air pollution, humidity and trip duration.ConclusionsOur results suggest that exposure to UFP and BC inside vehicles can be reduced significantly through simple preventative measures likely to be adopted by professional drivers as well as by all commuters.
P-0019 - Vale of Tears: The Dangerous Health Effects of Tear Gas Used in the Hong Kong Pro-Democracy Movement
Abstract Control Number
2278
Abstract Body
Background
Throughout the second half of 2019, the use of tear gas by the Hong Kong Police Force on protesting crowds has yielded much debate. Previous international studies have recognised the significant and pervasive health effects of tear gas.
Methods
Researchers at the Citizens’ Press Conference, a citizen-initiated broadcast platform, collected 17766 valid responses from their large-scale online survey on the participants’ roles in the Hong Kong pro-democracy movement, the locations of their homes and workplaces, and any adverse symptoms suffered from tear gas exposure.
Results
Severe medical symptoms induced directly by tear gas, some of which unseen in previous studies elsewhere, have been recorded. Results from our structural equation modelling analysis show significant associations between the respondents’ symptom scores and their roles in protests, the number of geographical districts in which they have come into direct contact with tear gas, a gender bias, and the amount and types of protective gear used (albeit a measure of their involvement in street protests and on the frontline). The respondents’ roles in protests and the gender bias are also significantly correlated with their symptom scores for indirect exposures to tear gas, i.e. when they are not actively participating in protests.
Conclusions
Our findings suggest that adverse medical symptoms from tear gas exposure are pervasive across both protesting and non-protesting demographics, and specific susceptible subpopulations of note have been identified. Inter-district spread of irritants originating from areas where episodes of tear gas overuse by the police have occurred has also been denoted in our results. Future modelling studies of the geographical flow of tear gas chemicals and subsequent analyses on the health risk this brings to residents should be pursued for a fuller understanding of the whole picture of the adverse effects of tear gas on the health of the Hong Kong population.
Throughout the second half of 2019, the use of tear gas by the Hong Kong Police Force on protesting crowds has yielded much debate. Previous international studies have recognised the significant and pervasive health effects of tear gas.
Methods
Researchers at the Citizens’ Press Conference, a citizen-initiated broadcast platform, collected 17766 valid responses from their large-scale online survey on the participants’ roles in the Hong Kong pro-democracy movement, the locations of their homes and workplaces, and any adverse symptoms suffered from tear gas exposure.
Results
Severe medical symptoms induced directly by tear gas, some of which unseen in previous studies elsewhere, have been recorded. Results from our structural equation modelling analysis show significant associations between the respondents’ symptom scores and their roles in protests, the number of geographical districts in which they have come into direct contact with tear gas, a gender bias, and the amount and types of protective gear used (albeit a measure of their involvement in street protests and on the frontline). The respondents’ roles in protests and the gender bias are also significantly correlated with their symptom scores for indirect exposures to tear gas, i.e. when they are not actively participating in protests.
Conclusions
Our findings suggest that adverse medical symptoms from tear gas exposure are pervasive across both protesting and non-protesting demographics, and specific susceptible subpopulations of note have been identified. Inter-district spread of irritants originating from areas where episodes of tear gas overuse by the police have occurred has also been denoted in our results. Future modelling studies of the geographical flow of tear gas chemicals and subsequent analyses on the health risk this brings to residents should be pursued for a fuller understanding of the whole picture of the adverse effects of tear gas on the health of the Hong Kong population.
P-0020 - Assessment of multipollutant ambient air composition on type 2 diabetes mellitus using machine learning.
Abstract Control Number
2335
Abstract Body
Type 2 diabetes mellitus (DM) is a complex multifactorial disease affecting over 30 million people in the United States (9.4% of the population). The last two decades have seen an increasing volume of research on the effects of air pollution (AP) on numerous health outcomes, including DM, with varied results. To address this, we employed an unsupervised ML algorithm, k-means clustering, to assess multiple AP components, which may show interactions between the constituents on health that traditional regression models don’t capture.K-means was performed on 53,284 observations collected by the US Environmental Protection Agency during 2003-2012 and downloaded from their website. The following are the AP constituents used for partitioning: carbon monoxide (CO), nitrogen oxide (NO), nitrogen dioxide (NO2), ozone (O3), sulfur dioxide (SO2), particulate matter with a diameter of 10µm or less and 2.5µm or less (PM10 and PM2.5, respectively). Change in annual DM incidence, data from the US Center for Disease Control and Prevention, was calculated by subtracting annual DM incidence from the following year for each US county, then matched to AP by year. The k-means analysis resulted in six clusters. The change in annual DM incidence was statistically different in all but two clusters. The cluster with the greatest change in DM incidence (0.19 per 1000) also had the highest concentrations of CO, NO, NO2, PM10, and PM2.5. Additionally, the mean SO2 level was greater than twice the mean SO2 for all observations. The cluster with the largest decrease in DM incidence (-0.19 per 1000) also had the lowest levels of CO, NO, NO2, PM10, PM2.5, and SO2. Using an unsupervised k-means algorithm, we showed multiple AP components were related to increased incidence of DM even when average concentrations were below the National Ambient Air Quality Standards.
P-0021 - Long-term particulate matter 2.5 exposure, insulin resistance and type 2 diabetes risk in Mexican adults: results from GEA study.
Abstract Control Number
2370
Abstract Body
Background/Aim. Type two diabetes mellitus (T2DM) is a leading cause of morbidity and mortality in Mexico. The aim of this study was to examine associations between particulate matter 2.5 (PM2.5) exposure and T2DM risk.Methods. This study comprised 1478 individuals belonging to the Genetics of Atherosclerotic Mexican Study (GEA) in Mexico City. Type 2 diabetes mellitus was defined by the American Diabetes Association criteria and insulin resistance (IR) was considered when the HOMA-IR (Homeostatic Model Assessment of Insulin Resistance) values were more than 75 percentile. PM2.5 concentrations for long-term periods (1 to 9 years) were assigned by inverse distance weighted (IDW) of data from air quality monitors. Linear regression models or logistic regression models were employed to assess long-term PM2.5 exposure and continuous variables (HOMA-IR or glycosylated hemoglobin [Hb1Ac]) or binary outcomes (T2DM or IR ), respectively. All models were adjusted for age, sex, body mass index, socioeconomic status, marital status, smoking, physical activity and total calories intake. Results. The prevalence of T2DM was 13.2% and for IR was 57.9%. PM2.5 exposure at year 1, 3, and 5 years before the baseline visit were significantly associated with higher HOMA-IR and IR. Each 10 ug/m3 of PM2.5 at year 1 was associated with 16% (95% CI: 1.01-1.33) higher odds of IR, and year 5 with 20% (95%CI: 1.05-1.36) higher odds of IR. Each 10 ug/m3 PM2.5 increased at year 2 (0.4% [95% CI: 0.04-0.74]) and 7 (0.5% [95% CI: 0.14-0.80]) were associated with increased HbA1c. Finally, no significant associations were observed between PM2.5 exposure at any time point and type 2 diabetes mellitus risk. Conclusions. The association between long-term exposure to PM2.5 and insulin resistance is relevant in the context of high obesity rate and poor glycemic control characteristic of Mexican adults.
P-0022 - Short-term exposure to indoor PM2.5 on depressive symptoms: Ko-CHENS Mom study
Abstract Control Number
2399
Abstract Body
Background/Aim The results of previous studies evaluating the associations between short-term PM exposure and depressive symptoms were inconsistent. However, no studies have evaluated on the relationship between indoor particulate matters and depressive symptoms in housewives. Most housewives spend a lot of time at home and do housework, which can generate indoor particulate matter, such as cleaning and cooking. Therefore, we investigated the impact of short-term exposure to indoor PM on depressive symptoms among Korean housewives in Ko-CHENS Mom study. Methods We recruited a total of 306 housewives (from January 2018 to February 2020) in Seoul and Ulsan, Republic of Korea. The indoor PM concentrations of each participant were measured by sensors for consecutive 7-days before completing health questionnaire. In addition, indoor PM concentration, two days before completing health questionnaire, was measured by gravimetric analysis. The Korean version of Center for Epidemiologic Studies Depression Scale (KCES-D) was used to evaluate depressive symptom during the study. The CES-D cut-off score was 16 or higher. We analyzed the association between indoor PM and CES-D by logistic regression adjusting for BMI, income level, education level, regions, smoking status, job status, time of stay at home and meteorological data (daily mean temperature and relative humidity). Results A total of 138 housewives included in this study. The average (SD) indoor PM2.5 and PM10 concentrations was 27.6 (17.4) μg/m3 and 43.8 (23.9) μg/m3. 26 (18.8%) out of total housewives were a CES-D score of 16 or higher. The 10 μg/m3 increase in concentration of indoor PM2.5 (OR=1.42, 95% CI: 1.06, 1.88) measured by gravimetric analysis was statistically associated with in CES-D. Exposure-response curve was used to capture linear relationship between indoor PM and depressive symptom. Conclusion Our study has found evidence that short-term exposure to indoor PM2.5 levels is related to the depressive symptoms in housewives.
P-0023 - Disease vulnerability and PAH biomonitoring in urban population exposed to air-borne particulate matter
Abstract Control Number
2405
Abstract Body
This study was conducted in urban area of Rawalpindi city with an aim to analyze population exposure to particulate matter (PM) and Polycyclic Aromatic Hydrocarbons (PAHs) in relation to their vulnerability for diseases. Biomonitoring study using serum naphthalene, pyrene and urinary 1-hydroxyprene was also conducted to quantify PAH exposure. The health risks based on self-reported health status was also noted using a questionnaire. Results of HPLC based serum analysis showed that mean concentration of blood naphthalene was 106 μg L-1 which had significant correlation with cigarette smoking (r=0.49; p<0.01). However, pyrene body burden (mean 19.18 μg L-1) appeared to be a significant predictor of urinary 1-hydroxyprene pyrene (69.9 μmol mol-1 creatinine). Among people associated with petroleum related occupations, there was fairly high significant effect of daily work-hours and job duration on serum pyrene levels. Urban population exposed to 6 hour per day or more had significantly high prevalence of physical disorders (OR=2.79, 95% CI=1.28-6.09). Neurasthenic symptoms were found in 65% of the subjects and were associated with years of involvement in job. Ten years or more occupational work at petrol pumps attributed substantial development of neurasthenic effects (OR=2.80, 95% CI=1.23-6.34). We conclude that subjects associating disturbances in physical and neurological behavior with petrol related occupation rated their overall health and functional capacity significantly poorer than that of urban area general population. A direct relationship between exposure to PM with population illness was observed especially during winter. To promote health of occupational groups, reduction in work hours and provision of masks and gloves could be introduced as health interventions.
P-0024 - Clinical outcomes associated with long-term exposure to airborne particulate pollution in kidney transplant recipients
Abstract Control Number
2490
Abstract Body
We aimed to evaluate the relationship of 10-μm particulate matter (PM10) with the risk of graft failure, mortality, and decline of graft function in kidney transplant recipients (KTRs). Air pollutant data were obtained from the Korean National Institute of Environmental Research and linked to those of 1,532 KTRs who underwent kidney transplantation in tertiary hospital from 2001 to 2015. Survival models were used to evaluate the association of PM10 concentrations and the risk of death-censored graft failure (DCGF), all-cause mortality, and biopsy-proven rejection (BPR) over a median follow-up of 6.31 years. The annual average PM10 exposure after KT was 27.1 ± 8.0 μg/m3. Based on the 5-year baseline exposure, a 1-μg/m3 increase in PM10 concentration was associated with increased risk of DCGF and BPR. All-cause mortality was significantly associated with 5-year average PM10 concentrations before the event in fully adjusted models. Long-term PM10 exposure has a significant association with respect to the risk of BPR, DCGF, and all-cause mortality.