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Chu L, Chen K, Di Q, Crowley S, Dubrow R. Associations between short-term exposure to PM 2.5, NO 2 and O 3 pollution and kidney-related conditions and the role of temperature-adjustment specification: A case-crossover study in New York state. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 328:121629. [PMID: 37054868 DOI: 10.1016/j.envpol.2023.121629] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 03/24/2023] [Accepted: 04/11/2023] [Indexed: 05/09/2023]
Abstract
Epidemiologic evidence on the relationship between air pollution and kidney disease remains inconclusive. We evaluated associations between short-term exposure to PM2.5, NO2 and O3 and unplanned hospital visits for seven kidney-related conditions (acute kidney failure [AKF], urolithiasis, glomerular diseases [GD], renal tubulo-interstitial diseases, chronic kidney disease, dysnatremia, and volume depletion; n = 1,209,934) in New York State (2007-2016). We applied a case-crossover design with conditional logistic regression, controlling for temperature, dew point temperature, wind speed, and solar radiation. We used a three-pollutant model at lag 0-5 days of exposure as our main model. We also assessed the influence of model adjustment using different specifications of temperature by comparing seven temperature metrics (e.g., dry-bulb temperature, heat index) and five intraday temperature measures (e.g., daily mean, daily minimum, nighttime mean), according to model performance and association magnitudes between air pollutants and kidney-related conditions. In our main models, we adjusted for daytime mean outdoor wet-bulb globe temperature, which showed good model performance across all kidney-related conditions. We observed the odds ratios (ORs) for 5 μg/m3 increase in daily mean PM2.5 to be 1.013 (95% confidence interval [CI]: 1.001, 1.025) for AKF, 1.107 (95% CI: 1.018, 1.203) for GD, and 1.027 (95% CI: 1.015, 1.038) for volume depletion; and the OR for 5 ppb increase in daily 1-hour maximum NO2 to be 1.014 (95% CI; 1.008, 1.021) for AKF. We observed no associations with daily 8-hour maximum O3 exposure. Association estimates varied by adjustment for different intraday temperature measures: estimates adjusted for measures with poorer model performance resulted in the greatest deviation from estimates adjusted for daytime mean, especially for AKF and volume depletion. Our findings indicate that short-term exposure to PM2.5 and NO2 is a risk factor for specific kidney-related conditions and underscore the need for careful adjustment of temperature in air pollution epidemiologic studies.
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Affiliation(s)
- Lingzhi Chu
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA; Yale Center on Climate Change and Health, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA.
| | - Kai Chen
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA; Yale Center on Climate Change and Health, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA
| | - Qian Di
- Vanke School of Public Health, Tsinghua University, Beijing, 100084, China
| | - Susan Crowley
- Department of Medicine (Nephrology), Yale University School of Medicine, New Haven, CT, 06520, USA; Veterans Administration Health Care System of Connecticut, West Haven, CT, 06516, USA
| | - Robert Dubrow
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA; Yale Center on Climate Change and Health, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA
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Concentration–Response Functions as an Essence of the Results from Lags. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19138116. [PMID: 35805772 PMCID: PMC9265718 DOI: 10.3390/ijerph19138116] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 06/21/2022] [Accepted: 06/29/2022] [Indexed: 02/04/2023]
Abstract
Among various aspects of environmental epidemiology, one is to assess the relationships between ambient air pollution and health outcomes. The goal of this work is to estimate the associations in the form of the parametric concentration–response functions (C-RF). Various forms of the C-RFs are proposed in this short-term health effect study. Emergency department (ED) visits for all respiratory health problems are analyzed as an illustrative example. A case-crossover (CC) technique is applied as a study design. Daily cases are organized as daily counts by the same day of the week in one common month. A conditional Poisson regression is used in the constructed statistical models. Temperature and relative humidity are included in the statistical models in the form of natural splines. Ground-level ozone concentration is considered an exposure. Ozone concentration values are transformed and submitted to the statistical models. The parameters of the transformation are determined by using the goodness of fit criterion. Counts of ED visits are analyzed in relation to a sequence of lagged exposure to ozone. The C-RF shapes are constructed for each individual lag. In a final step, the set of the estimated C-RF shapes is used to create a pooled C-RF shape. The results are positive and statistically significant for nine lagged exposures, from 0 to 8 days. The following relative risks (RR) were estimated from the constructed C-RFs at 30 ppb concentration of ozone: RR = 1.0531 (95% confidence interval: 1.0231, 1.0718), 1.0462 (1.0253, 1.0677), and 1.0387, (1.0240, 1.0531), realizing the CC method, CC method + transformation, and CC method + flexible transformation, respectively. The pooled C-RF shape gives a summary of the associations between ED visits for respiratory conditions and ambient ozone. The estimated shapes indicate lower air health effects than the standard CC methods. Among three considered statistical models, the CC method + flexible transformation is the most appropriate to use according to the goodness of fit criterion.
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Szyszkowicz M, Lukina A, Dinu T. Urban Air Pollution and Emergency Department Visits for Neoplasms and Outcomes of Blood Forming and Metabolic Systems. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19095603. [PMID: 35564996 PMCID: PMC9105125 DOI: 10.3390/ijerph19095603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 04/30/2022] [Accepted: 05/03/2022] [Indexed: 11/25/2022]
Abstract
This study focused on investigating possible associations between exposure to urban air pollution and the number of emergency department (ED) visits for various health outcomes. The outcomes were grouped into four chapters of the International Classification of Diseases Tenth Revision (ICD-10) system (i.e., Chapter II-IV: “Neoplasms”, “Diseases of the blood”, “Endocrine, nutritional and metabolic diseases”, and XVIII: “Symptoms, signs and abnormal clinical and laboratory findings“). The data were collected for the city of Toronto, Canada, (2004–2015, 4292 days). Four gaseous air pollutants (carbon monoxide (CO), nitrogen dioxide (NO2), ground level ozone (O3), and sulfur dioxide (SO2)) and fine particulate matter (PM2.5), and two calculated air quality health indexes (AQHI) based on Toronto were used. The statistical models were constructed by applying the conditional Poisson regression. The exposure was assessed over a maximum of 15 days (time lags 0–14 days). An analysis was performed with the following strata: sex, age, and seasons. Relative risks (RR) and their 95% confidence intervals (95%CI) were estimated for an increase in concentration by a one interquartile range (IQR). For the AQHI (composed of NO2, O3, and PM2.5), IQR = 1, the estimations for lag 1 and all patients, are RR = 1.023 (95%CI: 1.008, 1.038), 1.026 (1.012, 1.040), 1.013 (1.003, 1.024), and 1.007 (1.003, 1.010) for Chapters II–IV and XVIII, respectively. The results show that in the four large, analyzed health groups, the impact of air quality mainly occurs over a short period (from current day to a maximum of 3 days after exposure).
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Affiliation(s)
- Mieczysław Szyszkowicz
- Environmental Health Science & Research Bureau, Health Canada, Ottawa, ON K1A 0K9, Canada;
- Correspondence: or
| | - Anna Lukina
- Environmental Health Science & Research Bureau, Health Canada, Ottawa, ON K1A 0K9, Canada;
| | - Tatiana Dinu
- Water and Air Quality Bureau, Health Canada, Ottawa, ON K1A 0K9, Canada;
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