Beirut Air Pollution and Health Effects - BAPHE study protocol and objectives

Nakhlé, Myriam Mrad; Farah, Wehbeh; Ziadé, Nelly; Abboud, Maher; Coussa-Koniski, Marie-Louise; Annesi‐Maesano, Isabella

doi:10.4081/mrm.2015.295

Cited by 4 publications

(5 citation statements)

References 25 publications

(31 reference statements)

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“…Studies have shown that annual ambient average levels of particulate (PM 2.5 , PM 10 ) and NO 2 exceeded the air quality guidelines of the World Health Organization (WHO) (30.3 vs 10 μg m −3 , 51.3 vs 20 μg m −3 , and 53 vs 40 μg m −3 , respectively). 12,13 Also, vehicular traffic accounts for 27.1% of the total carbon dioxide (CO 2 ) emissions-which is 1.4 times higher than the world average of the total energy consumed by the road sector. 1 Air pollution in Lebanon is an environmental burden and a major source of concern to public health.…”

Section: Introductionmentioning

confidence: 99%

Cross‐sectional study of in‐vehicle exposure to ultrafine particles and black carbon inside Lebanese taxicabs

et al. 2020

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Taxi drivers' exposure to traffic-related air pollutants inside their vehicles has been reported in different countries but not yet in Lebanon. Thus, we conducted a crosssectional study on 20 Lebanese taxi drivers to (1) assess their exposure to ultrafine particles (UFP) and black carbon (BC) inside their vehicles and (2) identify determinants of this exposure. UFP and BC were measured using Diffusion Size Classifier Miniature ® and microAeth ® Model AE51, respectively, for 5 hours. Data on characteristics of vehicles and trips were collected by face-to-face interviews. Associations between pollutant levels and their determinants were analyzed by multiple linear regression. The mean of UFP count (35.2 ± 17.6 x 10 3 particles cm-3) and BC (5.2 ± 1.9 μg m-3) concentrations in-taxis was higher in the morning measurements compared with those in the afternoon measurements. UFP count increased in-taxis by 60% for every 10 minutes spent in blocked traffic and by 84% starting from two trips with smokers compared to trips without smokers. Conversely, UFP count decreased by 30% for every 10 minutes under both airconditioning and air recirculation mode with windows closed. BC was not affected by any of these factors. Our findings suggest easy ways to reduce UFP exposure inside vehicles for all commuters.

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Section: Introductionmentioning

confidence: 99%

Cross‐sectional study of in‐vehicle exposure to ultrafine particles and black carbon inside Lebanese taxicabs

et al. 2020

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“…The city of Beirut was chosen because of the availability of air pollution data. 36 The selected hospitals were chosen due to their proximity to pollutant measuring stations, the presence of an ED and their reception of large volumes of patients. The data sample was selected from a larger database collected for the Beirut Air Pollution and Health Effects (BAPHE) study performed by Nakhlé et al 36…”

Section: Sample Selectionmentioning

confidence: 99%

“…The data collection process is described in detail by Nakhlé et al in another study. 36 The data was collected using Microsoft Excel, inspected by the principal investigator, and validated by two senior physicians/epidemiologists.…”

Section: Data Collectionmentioning

confidence: 99%

Establishing a Sorting Protocol for Healthcare Databases

Ghabi¹,

Farah²,

Abboud³

et al. 2021

Journal of Public Health Research

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Background: Health information records in many countries, especially developing countries, are still paper based. Compared to electronic systems, paper-based systems are disadvantageous in terms of data storage and data extraction. Given the importance of health records for epidemiological studies, guidelines for effective data cleaning and sorting are essential. They are, however, largely absent from the literature. The following paper discusses the process by which an algorithm was developed for the cleaning and sorting of a database generated from emergency department records in Lebanon.Design and methods: Demographic and health related information were extracted from the emergency department records of three hospitals in Beirut. Appropriate categories were selected for data categorization. For health information, disease categories and codes were selected according to the International Classification of Disease 10th Edition.Results: A total of 16,537 entries were collected. Demographic information was categorized into groups for future epidemiological studies. Analysis of the health information led to the creation of a sorting algorithm which was then used to categorize and code the health data. Several counts were then performed to represent and visualize the data numerically and graphically.Conclusions: The article describes the current state of health information records in Lebanon and the associated disadvantages of a paper-based system in terms of storage and data extraction. Furthermore, the article describes the algorithm by which health information was sorted and categorized to allow for future data analysis using paper records.

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“…A convenience sample of 3 hospitals with emergency departments located in densely populated areas in the city of Beirut was chosen. The city of Beirut was chosen because of the availability of air pollutant level monitoring performed in previous research studies [26]. The selected hospitals, Hotel Dieu de France (HDF), Saint Georges University Medical Center (SGHUMC) and Makassed Hospital, were chosen based on their location close to where pollutant monitoring was performed, the presence of an ED and their reception of large volumes of patients.…”

Section: Sample Selectionmentioning

confidence: 99%

“…From each record, the following information was collected by trained hospital residents: patient's age, sex, date of presentation, chief complaint, differential diagnosis, final diagnosis, medications, and the name of the treating physician. This process is explained in detail in Nakhle et al's study entitled Beirut Air Pollution and Health Effects-BAPHE study protocol and objectives [26]. The data was then entered into Microsoft Excel, inspected by the principal investigator, and validated by two senior physicians/epidemiologists who were part of the research team.…”

Section: Data Collectionmentioning

confidence: 99%

Establishing A Sorting Protocol for The Data Cleaning of Health Record Databases for Eco-Epidemiological Studies: The Case of Beirut

Ghabi

Farah

Abboud

et al. 2019

Preprint

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Background Health information records in many countries, especially developing countries, still rely on a paper-based system which, when compared to electronic systems, are disadvantageous in terms of storage and data extraction. Given the importance of health records as a data resource for epidemiological studies, guidelines for systematic data cleaning and sorting are essential, yet are largely absent in the literature. This paper discusses the process by which an electronic database was generated from emergency department registers in Lebanon and the data subsequently cleaned, sorted, and categorized.Methods Demographic and health complaint-related information was extracted from emergency department registers of a convenience sample of seven hospitals in Beirut. Appropriate categories were selected for data categorization. For health-complaint related information, disease categories and codes were selected according to the International Classification of Disease 10th Edition.Results A total of 16,537 entries were collected. Demographic information was categorized into appropriate categories and groups as required for future epidemiological studies. Analysis of the health information allowed for the creation of a sorting algorithm which then used to categorize and code the heath data. Several counts were then performed to represent and visualize the data numerically and graphically to aid in data interpretation.Conclusions The article describes the current state of health information records in Lebanon and the associated disadvantages of a paper-based system in terms of storage and data extraction and subsequent analysis. Furthermore, the article describes the algorithm by which health information was sorted and categorized to allow for future data analysis using paper records.

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Beirut Air Pollution and Health Effects - BAPHE study protocol and objectives

Cited by 4 publications

References 25 publications

Cross‐sectional study of in‐vehicle exposure to ultrafine particles and black carbon inside Lebanese taxicabs

Cross‐sectional study of in‐vehicle exposure to ultrafine particles and black carbon inside Lebanese taxicabs

Establishing a Sorting Protocol for Healthcare Databases

Establishing A Sorting Protocol for The Data Cleaning of Health Record Databases for Eco-Epidemiological Studies: The Case of Beirut

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