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The weak potential of using the sole outdoor concentrations to represent personal exposure to PM2.5 is confirmed by the literature; therefore, it is important to account for a person's movements over time when estimating the short-term personal air pollution exposure within different microenvironments (MEs). This study is an example of applying an assessment method of the exposure to PM2.5 in different microenvironments at different temporal scales. A low-cost particle counter (the Dylos 1700) was used; its performance was validated in comparison with equivalent instruments such the SidePak AM520 Personal Aerosol Monitor (R2 = 0.89). This validation also provided a function to convert measured particle number concentrations (PNCs) into calculated particle mass concentrations. The 150 profiles that was collected on a minute-by-minute basis regarding PM2.5 concentration from December 2018 to May 2021 highlight the influence of individual activities and contextual factors on the air quality, so that Lebanon's annual PM2.5 mean (24.2 µg/m3) is 142% higher than the World Health Organization (WHO) annual mean guideline (10 µg/m3). Winter is the most polluted period due to the increased application of space heating devices. Additionally, the occurrence of dusty winds during the spring period leads to the elevated levels of dispersed PM2.5. Simultaneously, the rural zones are more polluted than urban ones due to the usage of more traditional heating equipment, in addition to the usage of chemical products like pesticides and fertilizers in agricultural activities in such areas. Furthermore, the (outdoor-indoor-transport) MEs indicate that the transport and indoor MEs have similar levels of suspended fine particulates, while outdoor MEs are less polluted. Studies based on the personal exposure to PM2.5 were generally applied on specific and limited places such as schools, workplaces, or residences. The study aims to shed light on the modern method in an attempt to estimate the personal exposure to PM2.5 and to inspire similar studies to achieve the maximum efficiency.

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PURPOSE OF REVIEW: Even though the burden of disease attributable to air pollution is high in the Eastern Mediterranean Region (EMR), the number of studies linking environmental exposures to negative health outcomes remains scarce and limited in scope. This review aims to assess the literature on exposure to air pollutants and perinatal health in the EMR and to explain the potential of epigenetics in exploring the processes behind adverse birth outcomes. RECENT FINDINGS: In the last three decades, hundreds of studies and publications tackled the health effects of air pollution on birth outcomes and early life development, but only a small number of these studies was conducted in the EMR. The existing literature is concentrated in specific geographic locations and is focused on a limited number of exposures and outcomes. Main limitations include inconsistent and poorly funded air quality monitoring, inappropriate study designs, imprecise and/or unreliable assessments of exposures, and outcomes. Even though the studies establish associations between air pollutants and adverse birth outcomes, the mechanisms through which these processes take place are yet to be fully understood. A likely candidate to explain these processes is epigenetics; however, epigenetics research on the impact of air pollution in EMR is still in its infancy. This review highlights the need for future research examining perinatal health and air pollutants, especially the epigenetic processes that underlie the adverse birth outcomes, to better understand them and to develop effective recommendations and intervention strategies.

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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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OBJECTIVES: The primary objective was to evaluate the association between weather variables and joint pain in patients with chronic rheumatic diseases (CRD: rheumatoid arthritis (RA), osteoarthritis (OA), and spondyloarthritis (SpA)). A secondary objective was to study the impact of air pollution indicators on CRD pain. METHOD: The study is prospective, correlational, with time-series analysis. Patients with CRD, living in a predefined catchment area, filled their level of pain daily using a 0-10 numerical scale (NS), for 1 year. Weather (temperature, relative humidity (H), atmospheric pressure (P)) and air pollution indicators (particulate matters (PM10, PM2.5), nitrogen dioxide (NO2), and ozone (O3)) were recorded daily using monitoring systems positioned in the same area. Association between pain and weather and air pollution indicators was studied using Pearson's correlation. Time-series analysis methodology was applied to determine the temporal relationship between pain and indicators. RESULTS: The study included 94 patients, 82% reported they were weather-sensitive. Pain variation was similar across diseases over a year. Pain was associated negatively with temperature, H, and O3, and positively with P and NO2. However, the strength of correlation was moderate; temperature explained 22% of pain variance. A drop of 10°C in temperature corresponded to an increase of 0.5 points in pain NS. Also, there was a significant interaction among environmental factors. In time-series analysis, temperature and NO2 remained independently associated with pain. CONCLUSIONS: The perception of joint pain in patients with CRD was correlated with weather and air pollution. The strength of association was moderate and independent of underlying disease. Key Points •Weather variation was moderately correlated with joint pain in chronic rheumatic diseases, with an inverse association with temperature, humidity, and O3. • Air pollution indicators, mainly nitrogen dioxide and ozone, were correlated with joint pain; particulate matters were also correlated but to a lesser extent. • The influence of these environmental factors was independent of the type of rheumatic disease, thus raising the hypothesis of their impact on pain perception mechanisms.

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BACKGROUND: Recent studies investigating the health effects of air pollution have proven an existing impact around and below international air quality guidelines and standards. These studies were based on accessible data from official registers managed by public authorities. The protocol followed in BAPHE project is described; its benefits and disadvantages are presented and discussed in this paper. METHODS: Based on the review of several international studies we developed a custom made approach in BAPHE (Beirut Air Pollution and Health Effects) project in order to analyze the short term health effects of air pollution taking into consideration the lack of data availability from official sources. RESULTS: PM2.5 and PM10 concentrations were measured in Beirut for the period starting from the 1(st) of January 2012 to the 31(st) of December 2012. The annual average concentrations of PM10 and PM2.5 exceeded WHO's annual average limits by 150 % and 200 %, respectively. Health data for 11,567 individuals were collected over 12 months. A variation of hospital admission causes was observed by age categories and gender. CONCLUSIONS: This article presents a simple protocol and the descriptive results of its application in the frame of an eco-epidemiological study in Lebanon. We believe that this work is not only important on a local scale, but it could be helpful for environmental epidemiological studies in other countries.

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High levels of major outdoor air pollutants have been documented in Lebanon, but their health effects remain unknown. The Beirut Air Pollution and Health Effects study aimed to determine the relationship between short-term variations in ambient concentrations of particulate matter (PM10 and PM2.5) and emergency hospital admissions in the city of Beirut, and whether susceptible groups are more greatly affected. An autoregressive Poisson model was used to evaluate the association between daily concentrations of particulate matter and respiratory and cardiovascular emergency hospital admissions after controlling for confounders. All variables were measured during 1 year from January 2012 to December 2012. Relative risks of admissions for respiratory and cardiovascular diseases were calculated for an increase in 10 µg.m(-3) of pollutant concentrations. Total respiratory admissions were significantly associated with the levels of PM10 (1.012 [95% CI 1.004-1.02]) per 10 µg.m(-3) rise in daily mean pollutant concentration for PM10 and 1.016 [95% CI 1.000-1.032] for PM2.5 on the same day. With regard to susceptible groups, total respiratory admissions were associated with PM2.5 and PM10 within the same day in children (relative risk (RR), 1.013 and 1.014; 95% confidence interval, 0.985-1.042 and 1.000-1.029 for PM2.5 and PM10, respectively). Moreover, a nearly significant association was found between particles and total circulatory admissions for adults and elderly groups in the same day. These results are similar to other international studies. Therefore, air pollution control is expected to reduce the number of admissions of these diseases in Lebanon.

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This study reports for the first time a time series analysis of daily urban air pollutant levels (CO, NO, NO2, O3, PM10, and SO2) in Beirut, Lebanon. The study examines data obtained between September 2005 and July 2006, and their descriptive analysis shows long-term variations of daily levels of air pollution concentrations. Strong persistence of these daily levels is identified in the time series using an autocorrelation function, except for SO2. Time series of standardized residual values (SRVs) are also calculated to compare fluctuations of the time series with different levels. Time series plots of the SRVs indicate that NO and NO2 had similar temporal fluctuations. However, NO2 and O3 had opposite temporal fluctuations, attributable to weather conditions and the accumulation of vehicular emissions. The effects of both desert dust storms and airborne particulate matter resulting from the Lebanon War in July 2006 are also discernible in the SRV plots.

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