A mapping review of epidemiological evidence on outdoor air pollution and human health in Bangladesh

A mapping review of epidemiological evidence on outdoor air pollution and human health in Bangladesh | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review A mapping review of epidemiological evidence on outdoor air pollution and human health in Bangladesh Abdullah Al Nayeem, Taznim Ara Khanm This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9121173/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Epidemiological evidence on the health effects of outdoor air pollution remains limited in low-income countries, particularly in Bangladesh. This study aims to systematically map the existing epidemiological evidence on the association between outdoor air pollution and human health outcomes in Bangladesh. Methods This mapping review followed established methodological guidelines for health science evidence mapping and was reported in accordance with the PRISMA. Literature searches were conducted in PubMed and Web of Science from database inception to 15 January 2026, using the Population-Exposure-Outcome (PEO) framework. Studies examining exposure to outdoor air pollution within epidemiological designs and conducted in Bangladesh were included. Results Of the 567 records identified, 11 studies met the inclusion criteria. The earliest eligible study was published in 2017, with no clear increasing publication trend through January 2026. Most studies were based on Dhaka city. PM 2.5 ( particles that are 2.5 microns or less in diameter) was the most frequently assessed exposure, while cardiovascular and respiratory diseases were the most commonly reported health outcomes. Study populations included pregnant women, children, and adults. Cross-sectional and ecological designs predominated. Conclusion Most included studies examined short-term effects and consistently reported adverse health outcomes associated with PM 2.5 exposure. This mapping review highlights the limited but growing evidence base on outdoor air pollution and health in Bangladesh and may inform policy development, targeted public health interventions, and research funding priorities. Health Effects Air Pollution Bangladesh mapping review Epidemiological evidence Figures Figure 1 Figure 2 1. Introduction Outdoor air pollution is a major modifiable risk factor for a wide range of respiratory, cardiovascular, and other health conditions, contributing to an estimated 8.1 million deaths globally in 2021 [ 1 ]. Key ambient pollutants include particulate matter (PM), ground-level ozone (O 3 ), carbon monoxide (CO), sulfur dioxide (SO 2 ), and nitrogen dioxide (NO 2 ), with fine particulate matter (PM 2.5 , aerodynamic diameter ≤ 2.5 µm) receiving the greatest attention due to its strong association with adverse health outcomes. Recent years have witnessed substantial growth in research on the health effects of air pollution. A meta-analysis of 799 original epidemiological studies, predominantly conducted in Asia, Europe, and North America have reported that 95.2% of research demonstrated significant associations between air pollution and various health outcomes [ 2 ]. However, these findings cannot be fully generalized to low-income countries (LICs), where socioeconomic conditions, baseline health status, and exposure patterns differ substantially. Globally, LICs bear a disproportionate burden of air pollution, particularly from PM 2.5 , yet high-quality epidemiological evidence from these regions remains limited [ 3 ]. This gap is evident in South Asian countries, especially in Bangladesh. Despite being consistently ranked among the most polluted countries worldwide, the health impacts of air pollution in Bangladesh are poorly characterized. PM 2.5 concentrations in the country have risen markedly between 2000 and 2020 across all 64 major cities, ranging from 55.1 to 159.4 µg/m³ in winter season which is 11 to 32 times higher than the World Health Organization Air Quality Guideline (annual mean ≤ 5 µg/m³) and 4 to 11 times above the Bangladesh National Ambient Air Quality Standard (annual mean ≤ 15 µg/m³) [ 4 ]. While numerous studies have assessed PM 2.5 exposure, source apportionment, and chemical composition using both ground-based monitoring and remote sensing, robust epidemiological evidence on population health impacts in Bangladesh remains scarce [ 5 ]. Therefore, to better understand the evolution of research in this field, it is essential to examine the characteristics of existing studies and the primary health outcomes associated with exposure to various air pollutants. In Bangladesh, no prior systematic synthesis of epidemiological evidence on air pollution exists. Mapping such evidence are critical to identify research gaps, inform future epidemiological studies, and guide evidence-based policy formulation and implementation. Mapping reviews are a valuable research tool for categorizing and visualizing existing literature, highlighting knowledge gaps, and directing further research efforts [ 6 ]. Accordingly, the aim of this paper is to systematically map and describe the characteristics of epidemiological studies investigating outdoor air pollution and related health outcomes in Bangladesh. 2. Methods 2.1 Guidelines A systematic mapping review is one of the fourteen recognized review types within the broader family of systematic review research [ 7 ]. Unlike systematic reviews, mapping reviews do not typically include a formal quality appraisal of individual studies. Nevertheless, they play a critical role in identifying research trends, knowledge gaps, and evidence clusters, thereby informing future research directions, guiding funding priorities, and supporting evidence-based policymaking [ 8 ]. This review approach has been widely adopted in health sciences, where it is particularly useful for synthesizing large and heterogeneous bodies of literature [ 9 ]. Accordingly, this study employed a systematic mapping review to visualize and summarize the existing epidemiological evidence on the relationship between outdoor air pollution and human health in Bangladesh. The review followed a structured methodological framework consisting of three key stages including gathering, selection, and data extraction [ 7 , 9 ]. 2.2 Data sources and search strategy The literature search was conducted using the PubMed and Web of Science databases, as these platforms are widely recognized and extensively used by researchers for health-related studies. The search was restricted to publications written in the English language. In PubMed, both Title/Abstract fields and Medical Subject Headings (MeSH) terms were employed during keyword development to ensure comprehensive coverage of relevant studies. The final search was completed on 15 January 2026. This review followed the PEO framework (Population, Exposure, Outcome) to structure the search strategy and guide study identification. Detailed descriptions of the key concepts and corresponding search terms are presented in S. Table 1 . 2.3 Eligibility Criteria Several general criteria were applied to screen articles for inclusion in this review. First, all included studies were required to be peer-reviewed and to employ epidemiological study designs with quantitative analyses. Studies investigating short- or long-term health outcomes associated with exposure to outdoor air pollution, regardless of pollutant type, were eligible for inclusion. All epidemiological study designs were considered. In contrast, systematic review articles addressing this topic were excluded. Studies focusing on indoor or household air pollution, as well as those examining industrial occupational exposure, were also excluded. Furthermore, multi-country study with pooled estimates were not taken into account. Additionally, studies centred on air pollution monitoring or health risk assessment using hazard quotient (HQ) approaches, without direct epidemiological health outcome analyses, were excluded. A comprehensive description of the inclusion and exclusion criteria is provided in S. Table 2 . 2.4 Data Extraction and Analysis The purpose of the data extraction was to systematically capture and summarize key characteristics of the included studies, rather than to synthesize effect estimates or assess study quality, consistent with the objectives of a systematic mapping review. Paper were extracted into an excel spreadsheet. For the analysis and discussion of the results, the following information was extracted from each included study: author(s), year of publication, study location, study design, study period, population characteristics, sample size, source of health data, type of outdoor air pollutants assessed, exposure assessment methods, statistical methods, health outcomes examined, time scale of exposure (short-term or long-term), and key epidemiological findings. Developing the research questions (RQs) is one of the key methodological aspects of systematic mapping review [ 10 ]. Hence, the questions of this mapping review are: RQ1. What is the temporal and spatial distribution of epidemiological studies on air pollution and health in Bangladesh? RQ2. What air pollutants and health outcomes have been investigated in these studies? RQ3. What are the main methodological characteristics of these studies (study design, exposure assessment methods, health data sources)? RQ4. What associations between air pollutants and health outcomes reported in the existing epidemiological literatures? 3. Results 3.1 Literature Search A total of 758 records were identified through database searching including 306 from PubMed and 452 from the Web of Science. After removing the duplicates, 567 unique articles remained and were screened based on their titles and abstracts according to predefined inclusion criteria. Following the screening process, 43 articles were deemed eligible for full text assessment. After applying the exclusion criteria to the full-text articles, 11 studies finally included in the mapping review (Fig. 1 ). 3.2 Research Question 1: Temporal and spatial distribution of epidemiological studies The earliest study included in this review was published in 2017. Overall, no consistent temporal trend in publication volume was observed. The highest number of publications (n = 3) appeared in 2023, followed by two publications each in 2019 and 2025. Only one study was published in 2017, 2021, and early 2026, respectively (Fig. 2 ). Among the total of 11 studies reviewed, the majority (n = 8) were conducted in the Dhaka region, while only three studies used nationally representative data. 3.3 Research Question 2: Investigated health outcomes and air pollutants Of the 11 articles included in this review, nine focused specifically on particulate matter air pollution in Bangladesh, while two studies examined criteria air pollutants to assess the health impacts of air pollution. Across these studies, five broad categories of health outcomes were investigated. Respiratory outcomes were the most frequently examined, including chronic obstructive pulmonary disease (COPD), lung function impairment, and asthma. Cardiovascular disease (CVD) outcomes represented the second most commonly studied category; however, these analyses were limited to all-cause cardiovascular morbidity and mortality rather than cause-specific CVD outcomes. In the birth and pregnancy category, outcomes such as low birth weight and preterm birth were evaluated. Child growth and nutritional outcomes, including stunting and wasting, were assessed in one study. Additionally, one study examined metabolic outcomes, focusing on diabetes among adults. Table 1 Investigated health outcomes and air pollutants category Health Outcomes Particulate Matter Criteria air pollutants Cardiovascular Mortality and Morbidity 3 - Acute and Chronic Respiratory 4 - Birth and Pregnancy - 2 Child Growth and Nutrition 1 - Metabolic 1 - 3.4 Research Question 3: main methodological characteristics The study populations of reviewed evidence demonstrated considerable heterogeneity, encompassing pregnant women (particularly focusing on low birth weight and preterm birth), children, adults, and, in some cases, individuals across all age groups (Table 2 ). In terms of methodological approaches, most studies employed either cross-sectional or ecological designs, with a smaller number using quasi-experimental, time-series, case-crossover, or retrospective designs. Exposure assessment methods varied, with researchers using both ground-level monitoring systems and satellite-based measurements to estimate air pollutant concentrations. Notably, the majority of Dhaka based studies relied on clinical data obtained from specialized hospitals and national health institutes, whereas nationwide studies predominantly used large-scale survey or modelled datasets. Table 2 Methodological characteristics of selected publications Author Location Population Study design Exposure measure Health data sources Brooks et al., (2023) [ 11 ] Mirzapur, Dhaka Adults and Children Quasi-experimental Low cost ground sensors Household survey Goyal and Canning (2017) [ 12 ] Nationwide Pregnant Women Cross sectional Satellite DHS Khan et al., (2019) [ 13 ] Dhaka Emergency Room Visits Case-crossover CAMS National Institute of Cardiovascular Diseases, Dhaka Nahian et al., (2023) [ 14 ] Dhaka Pregnant Women Cross sectional Air Quality Index (AQI) Child Health Training Institute, Dhaka Nayeem and Islam (2025) [ 5 ] Dhaka Not Specified Ecological CAMS Medical college Hospitals in Dhaka Partha et al., (2025) [ 15 ] Nationwide Pregnant Women Ecological Satellite Global Burden of Disease 2019 ;Poverty Mapping of the World version 2.01 Rahman et al., (2021) [ 16 ] Dhaka All ages Ecological time-series CAMS National Institute of Cardiovascular Diseases, Dhaka Rahman et al., (2022) [ 17 ] Dhaka All category (0 to 50 + years) Ecological time-series CAMS National Institute of Chest Diseases and Hospital (NICDH) Rana et al., (2026) [ 18 ] Nationwide Adults Retrospective study Satellite and CAMS DHS Saira et al., (2019) [ 19 ] Dhaka School Children (9–16 years) Cross sectional Ground monitor Spirometry Measure Sherris et al., (2021) [ 20 ] Dhaka Children less than five years of age Ecological time-series Ground Monitor icddrb surveillance data Notes : CAMS = Continuous Air Monitoring Station ; DHS = Demographic Health Survey 3.5 Research Question 4: Associations between air pollutants and health outcomes Across the reviewed studies, exposure to PM 2.5 consistently showed adverse effects on multiple health outcomes in Bangladesh (Table 3 ). Higher PM 2.5 levels were linked to substantially increased odds of COPD and respiratory symptoms among adults, greater respiratory emergency visits, reduced lung function indicators and a modest rise in pneumonia incidence following short-term exposure. Cardiovascular impacts were similarly pronounced, with PM 2.5 associated with higher risks of CVD mortality, increased emergency room visits, elevated hospitalizations and deaths at short time lags. Adverse birth outcomes were also evident, with air pollution linked to substantial numbers of preterm births nationally, as well as increased risks of low birth weight and prematurity. Additionally, long-term PM 2.5 exposure elevated the risk of stunting among children and was associated with a higher incidence of diabetes in adults, particularly those with obesity. Table 3 Summary results of effects of air pollution on human health Study Outcome Results Acute and Chronic Respiratory Brooks et al., (2023) [ 11 ] Respiratory Higher PM 2.5 was associated with 2.23 times higher odds of COPD (95% CI: 1.15–4.33) and 4.2 times higher odds of respiratory symptoms (95% CI: 2.7–6.8) among adults. Rahman et al., (2022) [ 17 ] Respiratory Emergency visit A 10-µg/m³ increase in PM2.5 was associated with a 0.84% rise in respiratory emergency department visits (95% CI: 0.33% − 1.35%). Saira et al., (2019) [ 19 ] Lung Function An inverse association was observed, with both peak expiratory flow (PEF) and forced expiratory volume in 1 second (FEV₁) decreasing as PM 2.5 levels increased. Sherris et al., (2021) [ 20 ] Upper respiratory infection Total PM 2.5 mass was associated with a modest increase in pneumonia incidence, with a peak effect two days after exposure (rate ratio = 1.032; 95% CI: 1.008–1056). Cardiovascular Mortality and Morbidity Nayeem and Islam (2025) [ 5 ] CVD deaths A 10 µg/m³ increase in PM 2.5 concentration was associated with a 3.1% increase in CVD mortality at lag 0 (95% CI: 1.1% − 5.2%). Khan et al., (2019) [ 13 ] CVD Emergency Room visit An IQR increase (103 µg/m3) in PM 2.5 at lag 3 was significantly associated with a 12% (RR: 1.12; 95% CI: 1.01–1.23) increase in CVD emergency room visits. Rahman et al., (2021) [ 16 ] All cause CVD mortality and morbidity A 10-µg/m³ increase in PM 2.5 was associated with higher risks of cardiovascular emergency visits [0.27%, (0.07% − 0.47%)], hospitalizations [0.32% (0.08% to 0.55%)] at lag-0, and deaths [0.87%, (0.27% − 1.47%)] at lag-1. Birth and Pregnancy Partha et al., (2025) [ 15 ] Preterm Birth CO, O3, PM 2.5 , SO2, and NO 2 exposure combinedly caused 0.18–0.20 million preterm births yearly in Bangladesh. Nahian et al., (2023) [ 14 ] Low Birith Weight, Prematurity For every 10,000 AQI value increase in cumulative exposure, low birth weight and preterm birth increased by 4% and 2%, respectively. Child Growth and Nutrition Goyal and Canning (2017) [ 12 ] Stunting Relative risks of stunting was 1.074 (95% CI: 1.014–1.138), 1.150 (95% CI: 1.069–1.237), and 1.132 (95% CI: 1.031–1.243) across the second, third, and fourth quartiles of PM 2.5 exposure, respectively. Metabolic Rana et al., (2026) [ 18 ] Diabetes A 10 µg/m 3 increase in 3-year average PM 2.5 concentration (with a 1-year lag) was associated with a 10% higher risk of diabetes with a stronger effect observed among individuals with obesity. 4. Discussions This study represents the first mapping review synthesizing epidemiological evidence on the health impacts of outdoor air pollution in Bangladesh. A total of 11 epidemiological studies were identified through searches in PubMed and Web of Science. The earliest available study was published in 2017, with no consistent trend in publication frequency over time. Most studies were Dhaka-centric, reflecting a substantial geographic imbalance in the evidence. PM 2.5 was the most commonly examined pollutant, and respiratory and cardiovascular health outcomes were the most frequently investigated across the included studies. Nearly all studies reported adverse associations between air pollution exposure and human health, though the majority focused on short-term effects. In terms of methodological design, cross-sectional and ecological studies predominated. Compared with other South Asian countries, Bangladesh has far fewer epidemiological studies on air pollution and health [ 21 ]. Although global research in this field is growing rapidly, Bangladesh-specific evidence remains limited. Nevertheless, the findings from existing Bangladeshi studies are generally consistent with global patterns. A few multi-country longitudinal studies that included Bangladesh were not part of this review because they reported pooled or regional associations rather than Bangladesh-specific estimates. For example, a multi-country prospective cohort study including Bangladesh found that a 10 µg/m³ increase in PM 2.5 was associated with increased risks of cardiovascular events (hazard ratio 1.05 [95% CI 1.03–1.07]), myocardial infarction (1.03 [1.00–1.05]), stroke (1.07 [1.04–1.10]), and cardiovascular mortality (1.03 [1.00–1.05]) [ 22 ]. Similarly, an analysis of Demographic and Health Surveys from India, Pakistan, and Bangladesh (1998–2016) showed that each 10 µg/m³ increment in PM2.5 increased the odds of pregnancy loss (OR 1.03 [95% CI 1.02–1.05]) [ 23 ]. These broader findings align with the evidence observed in the Bangladeshi studies included in this review. Despite these contributions, several important gaps have been identified in the current evidence. First, most studies relied on cross-sectional and ecological designs. While these provide useful snapshots of population-level or individual-level associations, they cannot establish temporal relationships or causality. The lack of longitudinal and cohort studies limits understanding of how long-term exposure to air pollution contributes to the development of chronic diseases over time. This is particularly relevant in Bangladesh, where rapid urbanization, industrial growth, and high population density may result in cumulative exposure effects that short-term studies cannot capture. Second, almost all studies are conducted in urban centres, particularly Dhaka, limiting the generalizability of findings. Populations in other district cities, suburban areas, and rural regions are also exposed to significant outdoor air pollution from traffic, brick kilns, and biomass burning [ 24 ]. Assessing the health impacts across these diverse settings is crucial for developing national interventions. Third, investigations of vulnerable populations remain very limited. Most studies focus on the general population, with few examining children, the elderly, or individuals with pre-existing conditions. Notably, there are no studies assessing occupationally exposed groups such as outdoor workers, traffic police personnel, or street vendors, who are likely to experience higher levels of exposure and associated health risks. Fourth, the range of health outcomes examined is narrow. The majority of studies focus on cardiovascular and respiratory conditions, whereas global research increasingly documents associations between air pollution and broader outcomes, including DNA methylation, mental health disorders, neurodevelopmental effects, dementia, and autism spectrum disorder (ASD) [ 25 – 27 ]. Expanding the spectrum of outcomes studied in Bangladesh would provide a more comprehensive understanding of the population-level burden of pollution. Finally, there is a critical need to investigate long-term effects of air pollution on morbidity and mortality, particularly for chronic diseases. Evidence on long-term impacts is essential to inform public health policy, guide preventive strategies, and allocate resources effectively to reduce the burden of air pollution in Bangladesh. Without such evidence, policymakers and health professionals lack the information necessary to implement targeted interventions that protect vulnerable populations and mitigate adverse health effects. The limited epidemiological evidence on air pollution and health in Bangladesh likely reflects structural and systemic constraints rather than a lack of scientific interest. First, Bangladesh does not have a nationally integrated disease surveillance system capable of linking environmental exposure data with individual-level demographic and social information [ 28 ]. In addition, the country lacks a complete and reliable death registration system. Policymakers therefore have limited access to accurate cause-of-death data for evidence-based decision-making. Studies show that only about 17% of adult deaths are registered in the civil registration system, and fewer than 36% are reported within the legally required timeframe [ 29 , 30 ]. Although the Directorate General of Health Services (DGHS) collects hospital data, these records are typically aggregated and not consistently available across district-level hospitals, particularly outside major cities [ 5 ]. This makes it difficult to estimate population-level morbidity and mortality attributable to air pollution. Air quality monitoring is another major constraint. In most district towns, only one continuous air quality monitoring station operates. A single station cannot provide spatially detailed exposure estimates representative of individual-level exposure, which are necessary for most epidemiological study designs beyond ecological analyses. Eventually, limited domestic research funding and reliance on international collaborations restrict both the number and scope of studies that can be conducted. Addressing these upstream barriers by strengthening civil registration systems, expanding ambient monitoring networks across 64 districts, and investing in epidemiological capacity building is therefore just as important as calling for more research. This mapping review will guide the government of Bangladesh in tracking existing interventions and supporting targeted health initiatives. Most importantly, it may assist the government and international agencies in prioritizing funding for health research in Bangladesh. This study will also facilitate policymakers and future researchers in identifying areas where evidence is robust and where further investigation is needed. However, this review has several limitations. First, the search was limited to only two databases, PubMed and Web of Science, which may have resulted in the exclusion of relevant studies indexed in other databases such as Scopus, Embase, or regional databases. Second, the review included only peer-reviewed journal articles published in English, which may have excluded relevant studies published in other languages, particularly Bangla, thereby introducing potential language bias. Third, the review focused only on peer-reviewed literature and did not include grey literature such as government reports, NGO publications, policy documents, and technical reports from international organizations, which may contain important information on health research activities in Bangladesh. Finally, as this study was a mapping review, it primarily aimed to describe the distribution of available evidence rather than assess the methodological quality or risk of bias of the included studies. Declarations Funding The author declare that no funds, grants, or other support were received during the preparation of this manuscript. Data Availability Not Applicable. Consent for publication Not applicable. Clinical trial number Not Applicable. Contributions Design, Conceptualization, PRISMA and draft: AA Nayeem; PRISMA cross check and draft edit: MTA Khanm. Ethical statement Ethical approval was not required. Declaration of competing interest Not Applicable. References Health Effects Institute. State of Global Air Report 2024 | Special Report.Boston, MA: Health Effects Institute. https://www.stateofglobalair.org/resources/archived/state-global-air-report-2024 . Accessed 1 Mar 2026. Sun Z, Zhu D. 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Bull World Health Organ. 2019;97:637–41. https://doi.org/10.2471/BLT.18.219162 . Tahsina T, Iqbal A, Rahman AE, Chowdhury SK, Chowdhury AI, Billah SM et al. Birth and Death Notifications for Improving Civil Registration and Vital Statistics in Bangladesh: Pilot Exploratory Study. JMIR Public Health Surveill. 2022;8(8):e25735 https://publichealth.jmir.org/2022/8/e25735 . 2022. https://doi.org/10.2196/25735 Haider MR, Rahman MM, Islam F, Khan MM. Association of Low Birthweight and Indoor Air Pollution: Biomass Fuel Use in Bangladesh. J Health Pollut. 2016;6:18–25. https://doi.org/10.5696/2156-9614-6-11.18 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 10 Apr, 2026 Reviewers agreed at journal 07 Apr, 2026 Reviewers invited by journal 05 Apr, 2026 Editor invited by journal 31 Mar, 2026 Editor assigned by journal 30 Mar, 2026 Submission checks completed at journal 28 Mar, 2026 First submitted to journal 28 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9121173","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":623647230,"identity":"7b3b2731-f4df-49b2-93e8-e99a8af03505","order_by":0,"name":"Abdullah Al Nayeem","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYHAD/ocPPgApNnbitfAwG84AaWEmQQubNA+IJqTFnP2M4YOPOQxy5hK5h41tfm2T52NmYPwAFMEJLHtyjA1nbmMwtpyRl/g4t++2YRszA7MkUAQnMDiQYybNu40hccOZA8bGuT23GYFa2Jh58Wk5/8b8999tDPVALWbSlj237QlruZFjxsy4jSHB4HiPmTTDj9uJRGh5VizZu03CcMPxtmTD3obbyW3MjM34/XI+eeOHn9ts5A0OMx988OPPbdv57c0HP3zEo4WBgcMASEhA2IxtYLIBn3ogYH+AxPlDQPEoGAWjYBSMSAAA7yVRQ8m1TzwAAAAASUVORK5CYII=","orcid":"","institution":"Stamford University Bangladesh","correspondingAuthor":true,"prefix":"","firstName":"Abdullah","middleName":"Al","lastName":"Nayeem","suffix":""},{"id":623647231,"identity":"71d7d7c6-00c3-478f-aa23-94dfc0d8babb","order_by":1,"name":"Taznim Ara Khanm","email":"","orcid":"","institution":"Stamford University Bangladesh","correspondingAuthor":false,"prefix":"","firstName":"Taznim","middleName":"Ara","lastName":"Khanm","suffix":""}],"badges":[],"createdAt":"2026-03-14 09:09:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9121173/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9121173/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107514986,"identity":"c64c4dbd-4d5b-445a-a172-eb1d5c57881b","added_by":"auto","created_at":"2026-04-22 08:27:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":326009,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA diagram illustrating the study search and selection process\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9121173/v1/794e1b0f556ec742c3c5f4c1.png"},{"id":107515213,"identity":"f33ec333-92e1-41bc-845f-9a8cefba8c33","added_by":"auto","created_at":"2026-04-22 08:28:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":8863,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of published articles per year on effects of air pollution on health.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9121173/v1/85a84fb2541bf8488623783b.png"},{"id":107515437,"identity":"4e7aab09-f3e4-4ea9-962b-5dd935dc79e4","added_by":"auto","created_at":"2026-04-22 08:28:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":783885,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9121173/v1/b3daf993-908e-46d8-b304-54cf7dcec609.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A mapping review of epidemiological evidence on outdoor air pollution and human health in Bangladesh","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eOutdoor air pollution is a major modifiable risk factor for a wide range of respiratory, cardiovascular, and other health conditions, contributing to an estimated 8.1\u0026nbsp;million deaths globally in 2021 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Key ambient pollutants include particulate matter (PM), ground-level ozone (O\u003csub\u003e3\u003c/sub\u003e), carbon monoxide (CO), sulfur dioxide (SO\u003csub\u003e2\u003c/sub\u003e), and nitrogen dioxide (NO\u003csub\u003e2\u003c/sub\u003e), with fine particulate matter (PM\u003csub\u003e2.5\u003c/sub\u003e, aerodynamic diameter\u0026thinsp;\u0026le;\u0026thinsp;2.5 \u0026micro;m) receiving the greatest attention due to its strong association with adverse health outcomes. Recent years have witnessed substantial growth in research on the health effects of air pollution. A meta-analysis of 799 original epidemiological studies, predominantly conducted in Asia, Europe, and North America have reported that 95.2% of research demonstrated significant associations between air pollution and various health outcomes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, these findings cannot be fully generalized to low-income countries (LICs), where socioeconomic conditions, baseline health status, and exposure patterns differ substantially. Globally, LICs bear a disproportionate burden of air pollution, particularly from PM\u003csub\u003e2.5\u003c/sub\u003e, yet high-quality epidemiological evidence from these regions remains limited [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis gap is evident in South Asian countries, especially in Bangladesh. Despite being consistently ranked among the most polluted countries worldwide, the health impacts of air pollution in Bangladesh are poorly characterized. PM\u003csub\u003e2.5\u003c/sub\u003e concentrations in the country have risen markedly between 2000 and 2020 across all 64 major cities, ranging from 55.1 to 159.4 \u0026micro;g/m\u0026sup3; in winter season which is 11 to 32 times higher than the World Health Organization Air Quality Guideline (annual mean\u0026thinsp;\u0026le;\u0026thinsp;5 \u0026micro;g/m\u0026sup3;) and 4 to 11 times above the Bangladesh National Ambient Air Quality Standard (annual mean\u0026thinsp;\u0026le;\u0026thinsp;15 \u0026micro;g/m\u0026sup3;) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. While numerous studies have assessed PM\u003csub\u003e2.5\u003c/sub\u003e exposure, source apportionment, and chemical composition using both ground-based monitoring and remote sensing, robust epidemiological evidence on population health impacts in Bangladesh remains scarce [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTherefore, to better understand the evolution of research in this field, it is essential to examine the characteristics of existing studies and the primary health outcomes associated with exposure to various air pollutants. In Bangladesh, no prior systematic synthesis of epidemiological evidence on air pollution exists. Mapping such evidence are critical to identify research gaps, inform future epidemiological studies, and guide evidence-based policy formulation and implementation. Mapping reviews are a valuable research tool for categorizing and visualizing existing literature, highlighting knowledge gaps, and directing further research efforts [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Accordingly, the aim of this paper is to systematically map and describe the characteristics of epidemiological studies investigating outdoor air pollution and related health outcomes in Bangladesh.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Guidelines\u003c/h2\u003e \u003cp\u003eA systematic mapping review is one of the fourteen recognized review types within the broader family of systematic review research [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Unlike systematic reviews, mapping reviews do not typically include a formal quality appraisal of individual studies. Nevertheless, they play a critical role in identifying research trends, knowledge gaps, and evidence clusters, thereby informing future research directions, guiding funding priorities, and supporting evidence-based policymaking [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This review approach has been widely adopted in health sciences, where it is particularly useful for synthesizing large and heterogeneous bodies of literature [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Accordingly, this study employed a systematic mapping review to visualize and summarize the existing epidemiological evidence on the relationship between outdoor air pollution and human health in Bangladesh. The review followed a structured methodological framework consisting of three key stages including gathering, selection, and data extraction [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Data sources and search strategy\u003c/h2\u003e \u003cp\u003eThe literature search was conducted using the PubMed and Web of Science databases, as these platforms are widely recognized and extensively used by researchers for health-related studies. The search was restricted to publications written in the English language. In PubMed, both Title/Abstract fields and Medical Subject Headings (MeSH) terms were employed during keyword development to ensure comprehensive coverage of relevant studies. The final search was completed on 15 January 2026. This review followed the PEO framework (Population, Exposure, Outcome) to structure the search strategy and guide study identification. Detailed descriptions of the key concepts and corresponding search terms are presented in S. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Eligibility Criteria\u003c/h2\u003e \u003cp\u003eSeveral general criteria were applied to screen articles for inclusion in this review. First, all included studies were required to be peer-reviewed and to employ epidemiological study designs with quantitative analyses. Studies investigating short- or long-term health outcomes associated with exposure to outdoor air pollution, regardless of pollutant type, were eligible for inclusion. All epidemiological study designs were considered. In contrast, systematic review articles addressing this topic were excluded. Studies focusing on indoor or household air pollution, as well as those examining industrial occupational exposure, were also excluded. Furthermore, multi-country study with pooled estimates were not taken into account. Additionally, studies centred on air pollution monitoring or health risk assessment using hazard quotient (HQ) approaches, without direct epidemiological health outcome analyses, were excluded. A comprehensive description of the inclusion and exclusion criteria is provided in S. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data Extraction and Analysis\u003c/h2\u003e \u003cp\u003eThe purpose of the data extraction was to systematically capture and summarize key characteristics of the included studies, rather than to synthesize effect estimates or assess study quality, consistent with the objectives of a systematic mapping review. Paper were extracted into an excel spreadsheet. For the analysis and discussion of the results, the following information was extracted from each included study: author(s), year of publication, study location, study design, study period, population characteristics, sample size, source of health data, type of outdoor air pollutants assessed, exposure assessment methods, statistical methods, health outcomes examined, time scale of exposure (short-term or long-term), and key epidemiological findings.\u003c/p\u003e \u003cp\u003eDeveloping the research questions (RQs) is one of the key methodological aspects of systematic mapping review [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Hence, the questions of this mapping review are:\u003c/p\u003e \u003cp\u003e \u003cb\u003eRQ1.\u003c/b\u003e What is the temporal and spatial distribution of epidemiological studies on air pollution and health in Bangladesh?\u003c/p\u003e \u003cp\u003e \u003cb\u003eRQ2.\u003c/b\u003e What air pollutants and health outcomes have been investigated in these studies?\u003c/p\u003e \u003cp\u003e \u003cb\u003eRQ3.\u003c/b\u003e What are the main methodological characteristics of these studies (study design, exposure assessment methods, health data sources)?\u003c/p\u003e \u003cp\u003e \u003cb\u003eRQ4.\u003c/b\u003e What associations between air pollutants and health outcomes reported in the existing epidemiological literatures?\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Literature Search\u003c/h2\u003e \u003cp\u003eA total of 758 records were identified through database searching including 306 from PubMed and 452 from the Web of Science. After removing the duplicates, 567 unique articles remained and were screened based on their titles and abstracts according to predefined inclusion criteria. Following the screening process, 43 articles were deemed eligible for full text assessment. After applying the exclusion criteria to the full-text articles, 11 studies finally included in the mapping review (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Research Question 1: Temporal and spatial distribution of epidemiological studies\u003c/h2\u003e \u003cp\u003eThe earliest study included in this review was published in 2017. Overall, no consistent temporal trend in publication volume was observed. The highest number of publications (n\u0026thinsp;=\u0026thinsp;3) appeared in 2023, followed by two publications each in 2019 and 2025. Only one study was published in 2017, 2021, and early 2026, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Among the total of 11 studies reviewed, the majority (n\u0026thinsp;=\u0026thinsp;8) were conducted in the Dhaka region, while only three studies used nationally representative data.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Research Question 2: Investigated health outcomes and air pollutants\u003c/h2\u003e \u003cp\u003eOf the 11 articles included in this review, nine focused specifically on particulate matter air pollution in Bangladesh, while two studies examined criteria air pollutants to assess the health impacts of air pollution. Across these studies, five broad categories of health outcomes were investigated. Respiratory outcomes were the most frequently examined, including chronic obstructive pulmonary disease (COPD), lung function impairment, and asthma. Cardiovascular disease (CVD) outcomes represented the second most commonly studied category; however, these analyses were limited to all-cause cardiovascular morbidity and mortality rather than cause-specific CVD outcomes. In the birth and pregnancy category, outcomes such as low birth weight and preterm birth were evaluated. Child growth and nutritional outcomes, including stunting and wasting, were assessed in one study. Additionally, one study examined metabolic outcomes, focusing on diabetes among adults.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInvestigated health outcomes and air pollutants category\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth Outcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticulate Matter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCriteria air pollutants\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular Mortality and Morbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute and Chronic Respiratory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth and Pregnancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChild Growth and Nutrition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetabolic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Research Question 3: main methodological characteristics\u003c/h2\u003e \u003cp\u003eThe study populations of reviewed evidence demonstrated considerable heterogeneity, encompassing pregnant women (particularly focusing on low birth weight and preterm birth), children, adults, and, in some cases, individuals across all age groups (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In terms of methodological approaches, most studies employed either cross-sectional or ecological designs, with a smaller number using quasi-experimental, time-series, case-crossover, or retrospective designs. Exposure assessment methods varied, with researchers using both ground-level monitoring systems and satellite-based measurements to estimate air pollutant concentrations. Notably, the majority of Dhaka based studies relied on clinical data obtained from specialized hospitals and national health institutes, whereas nationwide studies predominantly used large-scale survey or modelled datasets.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMethodological characteristics of selected publications\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStudy design\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExposure measure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHealth data sources\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrooks et al., (2023) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMirzapur, Dhaka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdults and Children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQuasi-experimental\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLow cost ground sensors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHousehold survey\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGoyal and Canning (2017) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNationwide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePregnant Women\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCross sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSatellite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDHS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKhan et al., (2019) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDhaka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEmergency Room Visits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCase-crossover\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCAMS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNational Institute of Cardiovascular Diseases, Dhaka\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNahian et al., (2023) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDhaka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePregnant Women\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCross sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAir Quality Index (AQI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eChild Health Training Institute, Dhaka\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNayeem and Islam (2025) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDhaka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot Specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEcological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCAMS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMedical college Hospitals in Dhaka\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePartha et al., (2025) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNationwide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePregnant Women\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEcological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSatellite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGlobal Burden of Disease 2019 ;Poverty Mapping of the World version 2.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRahman et al., (2021) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDhaka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAll ages\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEcological time-series\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCAMS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNational Institute of Cardiovascular Diseases, Dhaka\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRahman et al., (2022) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDhaka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAll category (0 to 50\u0026thinsp;+\u0026thinsp;years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEcological time-series\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCAMS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNational Institute of Chest Diseases and Hospital (NICDH)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRana et al., (2026) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNationwide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRetrospective study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSatellite and CAMS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDHS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSaira et al., (2019) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDhaka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSchool Children (9\u0026ndash;16 years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCross sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGround monitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpirometry Measure\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSherris et al., (2021) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDhaka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChildren less than five years of age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEcological time-series\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGround Monitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eicddrb surveillance data\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNotes : CAMS\u0026thinsp;=\u0026thinsp;Continuous Air Monitoring Station ; DHS\u0026thinsp;=\u0026thinsp;Demographic Health Survey\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Research Question 4: Associations between air pollutants and health outcomes\u003c/h2\u003e \u003cp\u003eAcross the reviewed studies, exposure to PM\u003csub\u003e2.5\u003c/sub\u003e consistently showed adverse effects on multiple health outcomes in Bangladesh (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Higher PM\u003csub\u003e2.5\u003c/sub\u003e levels were linked to substantially increased odds of COPD and respiratory symptoms among adults, greater respiratory emergency visits, reduced lung function indicators and a modest rise in pneumonia incidence following short-term exposure. Cardiovascular impacts were similarly pronounced, with PM\u003csub\u003e2.5\u003c/sub\u003e associated with higher risks of CVD mortality, increased emergency room visits, elevated hospitalizations and deaths at short time lags. Adverse birth outcomes were also evident, with air pollution linked to substantial numbers of preterm births nationally, as well as increased risks of low birth weight and prematurity. Additionally, long-term PM\u003csub\u003e2.5\u003c/sub\u003e exposure elevated the risk of stunting among children and was associated with a higher incidence of diabetes in adults, particularly those with obesity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary results of effects of air pollution on human health\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eResults\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAcute and Chronic Respiratory\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrooks et al., (2023) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRespiratory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigher PM\u003csub\u003e2.5\u003c/sub\u003e was associated with 2.23 times higher odds of COPD (95% CI: 1.15\u0026ndash;4.33) and 4.2 times higher odds of respiratory symptoms (95% CI: 2.7\u0026ndash;6.8) among adults.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRahman et al., (2022) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRespiratory Emergency visit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA 10-\u0026micro;g/m\u0026sup3; increase in PM2.5 was associated with a 0.84% rise in respiratory emergency department visits (95% CI: 0.33% \u0026minus;\u0026thinsp;1.35%).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSaira et al., (2019) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLung Function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAn inverse association was observed, with both peak expiratory flow (PEF) and forced expiratory volume in 1 second (FEV₁) decreasing as PM\u003csub\u003e2.5\u003c/sub\u003e levels increased.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSherris et al., (2021) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUpper respiratory infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal PM\u003csub\u003e2.5\u003c/sub\u003e mass was associated with a modest increase in pneumonia incidence, with a peak effect two days after exposure (rate ratio\u0026thinsp;=\u0026thinsp;1.032; 95% CI: 1.008\u0026ndash;1056).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCardiovascular Mortality and Morbidity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNayeem and Islam (2025) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCVD deaths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA 10 \u0026micro;g/m\u0026sup3; increase in PM\u003csub\u003e2.5\u003c/sub\u003e\u0026nbsp;concentration was associated with a 3.1% increase in CVD mortality at lag 0 (95% CI: 1.1% \u0026minus;\u0026thinsp;5.2%).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKhan et al., (2019) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCVD Emergency Room visit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAn IQR increase (103 \u0026micro;g/m3) in PM\u003csub\u003e2.5\u003c/sub\u003e at lag 3 was significantly associated with a 12% (RR: 1.12; 95% CI: 1.01\u0026ndash;1.23) increase in CVD emergency room visits.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRahman et al., (2021) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll cause CVD mortality and morbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA 10-\u0026micro;g/m\u0026sup3; increase in PM\u003csub\u003e2.5\u003c/sub\u003e was associated with higher risks of cardiovascular emergency visits [0.27%, (0.07% \u0026minus;\u0026thinsp;0.47%)], hospitalizations [0.32% (0.08% to 0.55%)] at lag-0, and deaths [0.87%, (0.27% \u0026minus;\u0026thinsp;1.47%)] at lag-1.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBirth and Pregnancy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePartha et al., (2025) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePreterm Birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCO, O3, PM\u003csub\u003e2.5\u003c/sub\u003e, SO2, and NO\u003csub\u003e2\u003c/sub\u003e exposure combinedly caused 0.18\u0026ndash;0.20\u0026nbsp;million preterm births yearly in Bangladesh.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNahian et al., (2023) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow Birith Weight, Prematurity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFor every 10,000 AQI value increase in cumulative exposure, low birth weight and preterm birth increased by 4% and 2%, respectively.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild Growth and Nutrition\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGoyal and Canning (2017) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStunting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRelative risks of stunting was 1.074 (95% CI: 1.014\u0026ndash;1.138), 1.150 (95% CI: 1.069\u0026ndash;1.237), and 1.132 (95% CI: 1.031\u0026ndash;1.243) across the second, third, and fourth quartiles of PM\u003csub\u003e2.5\u003c/sub\u003e exposure, respectively.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMetabolic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRana et al., (2026) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA 10\u0026nbsp;\u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e\u0026nbsp;increase in 3-year average PM\u003csub\u003e2.5\u003c/sub\u003e\u0026nbsp;concentration (with a 1-year lag) was associated with a 10% higher risk of diabetes with a stronger effect observed among individuals with obesity.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussions","content":"\u003cp\u003eThis study represents the first mapping review synthesizing epidemiological evidence on the health impacts of outdoor air pollution in Bangladesh. A total of 11 epidemiological studies were identified through searches in PubMed and Web of Science. The earliest available study was published in 2017, with no consistent trend in publication frequency over time. Most studies were Dhaka-centric, reflecting a substantial geographic imbalance in the evidence. PM\u003csub\u003e2.5\u003c/sub\u003e was the most commonly examined pollutant, and respiratory and cardiovascular health outcomes were the most frequently investigated across the included studies. Nearly all studies reported adverse associations between air pollution exposure and human health, though the majority focused on short-term effects. In terms of methodological design, cross-sectional and ecological studies predominated.\u003c/p\u003e \u003cp\u003eCompared with other South Asian countries, Bangladesh has far fewer epidemiological studies on air pollution and health [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Although global research in this field is growing rapidly, Bangladesh-specific evidence remains limited. Nevertheless, the findings from existing Bangladeshi studies are generally consistent with global patterns. A few multi-country longitudinal studies that included Bangladesh were not part of this review because they reported pooled or regional associations rather than Bangladesh-specific estimates. For example, a multi-country prospective cohort study including Bangladesh found that a 10 \u0026micro;g/m\u0026sup3; increase in PM\u003csub\u003e2.5\u003c/sub\u003e was associated with increased risks of cardiovascular events (hazard ratio 1.05 [95% CI 1.03\u0026ndash;1.07]), myocardial infarction (1.03 [1.00\u0026ndash;1.05]), stroke (1.07 [1.04\u0026ndash;1.10]), and cardiovascular mortality (1.03 [1.00\u0026ndash;1.05]) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Similarly, an analysis of Demographic and Health Surveys from India, Pakistan, and Bangladesh (1998\u0026ndash;2016) showed that each 10 \u0026micro;g/m\u0026sup3; increment in PM2.5 increased the odds of pregnancy loss (OR 1.03 [95% CI 1.02\u0026ndash;1.05]) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These broader findings align with the evidence observed in the Bangladeshi studies included in this review.\u003c/p\u003e \u003cp\u003eDespite these contributions, several important gaps have been identified in the current evidence. First, most studies relied on cross-sectional and ecological designs. While these provide useful snapshots of population-level or individual-level associations, they cannot establish temporal relationships or causality. The lack of longitudinal and cohort studies limits understanding of how long-term exposure to air pollution contributes to the development of chronic diseases over time. This is particularly relevant in Bangladesh, where rapid urbanization, industrial growth, and high population density may result in cumulative exposure effects that short-term studies cannot capture. Second, almost all studies are conducted in urban centres, particularly Dhaka, limiting the generalizability of findings. Populations in other district cities, suburban areas, and rural regions are also exposed to significant outdoor air pollution from traffic, brick kilns, and biomass burning [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Assessing the health impacts across these diverse settings is crucial for developing national interventions. Third, investigations of vulnerable populations remain very limited. Most studies focus on the general population, with few examining children, the elderly, or individuals with pre-existing conditions. Notably, there are no studies assessing occupationally exposed groups such as outdoor workers, traffic police personnel, or street vendors, who are likely to experience higher levels of exposure and associated health risks. Fourth, the range of health outcomes examined is narrow. The majority of studies focus on cardiovascular and respiratory conditions, whereas global research increasingly documents associations between air pollution and broader outcomes, including DNA methylation, mental health disorders, neurodevelopmental effects, dementia, and autism spectrum disorder (ASD) [\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Expanding the spectrum of outcomes studied in Bangladesh would provide a more comprehensive understanding of the population-level burden of pollution. Finally, there is a critical need to investigate long-term effects of air pollution on morbidity and mortality, particularly for chronic diseases. Evidence on long-term impacts is essential to inform public health policy, guide preventive strategies, and allocate resources effectively to reduce the burden of air pollution in Bangladesh. Without such evidence, policymakers and health professionals lack the information necessary to implement targeted interventions that protect vulnerable populations and mitigate adverse health effects.\u003c/p\u003e \u003cp\u003eThe limited epidemiological evidence on air pollution and health in Bangladesh likely reflects structural and systemic constraints rather than a lack of scientific interest. First, Bangladesh does not have a nationally integrated disease surveillance system capable of linking environmental exposure data with individual-level demographic and social information [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In addition, the country lacks a complete and reliable death registration system. Policymakers therefore have limited access to accurate cause-of-death data for evidence-based decision-making. Studies show that only about 17% of adult deaths are registered in the civil registration system, and fewer than 36% are reported within the legally required timeframe [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Although the Directorate General of Health Services (DGHS) collects hospital data, these records are typically aggregated and not consistently available across district-level hospitals, particularly outside major cities [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This makes it difficult to estimate population-level morbidity and mortality attributable to air pollution. Air quality monitoring is another major constraint. In most district towns, only one continuous air quality monitoring station operates. A single station cannot provide spatially detailed exposure estimates representative of individual-level exposure, which are necessary for most epidemiological study designs beyond ecological analyses. Eventually, limited domestic research funding and reliance on international collaborations restrict both the number and scope of studies that can be conducted. Addressing these upstream barriers by strengthening civil registration systems, expanding ambient monitoring networks across 64 districts, and investing in epidemiological capacity building is therefore just as important as calling for more research.\u003c/p\u003e \u003cp\u003eThis mapping review will guide the government of Bangladesh in tracking existing interventions and supporting targeted health initiatives. Most importantly, it may assist the government and international agencies in prioritizing funding for health research in Bangladesh. This study will also facilitate policymakers and future researchers in identifying areas where evidence is robust and where further investigation is needed. However, this review has several limitations. First, the search was limited to only two databases, PubMed and Web of Science, which may have resulted in the exclusion of relevant studies indexed in other databases such as Scopus, Embase, or regional databases. Second, the review included only peer-reviewed journal articles published in English, which may have excluded relevant studies published in other languages, particularly Bangla, thereby introducing potential language bias. Third, the review focused only on peer-reviewed literature and did not include grey literature such as government reports, NGO publications, policy documents, and technical reports from international organizations, which may contain important information on health research activities in Bangladesh. Finally, as this study was a mapping review, it primarily aimed to describe the distribution of available evidence rather than assess the methodological quality or risk of bias of the included studies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDesign, Conceptualization, PRISMA and draft: AA Nayeem; PRISMA cross check and draft edit: MTA Khanm.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHealth Effects Institute. 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J Health Pollut. 2016;6:18\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5696/2156-9614-6-11.18\u003c/span\u003e\u003cspan address=\"10.5696/2156-9614-6-11.18\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":true,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Health Effects, Air Pollution, Bangladesh, mapping review, Epidemiological evidence","lastPublishedDoi":"10.21203/rs.3.rs-9121173/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9121173/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEpidemiological evidence on the health effects of outdoor air pollution remains limited in low-income countries, particularly in Bangladesh. This study aims to systematically map the existing epidemiological evidence on the association between outdoor air pollution and human health outcomes in Bangladesh.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis mapping review followed established methodological guidelines for health science evidence mapping and was reported in accordance with the PRISMA. Literature searches were conducted in PubMed and Web of Science from database inception to 15 January 2026, using the Population-Exposure-Outcome (PEO) framework. Studies examining exposure to outdoor air pollution within epidemiological designs and conducted in Bangladesh were included.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the 567 records identified, 11 studies met the inclusion criteria. The earliest eligible study was published in 2017, with no clear increasing publication trend through January 2026. Most studies were based on Dhaka city. PM\u003csub\u003e2.5\u003c/sub\u003e ( particles that are 2.5 microns or less in diameter) was the most frequently assessed exposure, while cardiovascular and respiratory diseases were the most commonly reported health outcomes. Study populations included pregnant women, children, and adults. Cross-sectional and ecological designs predominated.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eMost included studies examined short-term effects and consistently reported adverse health outcomes associated with PM\u003csub\u003e2.5\u003c/sub\u003e exposure. This mapping review highlights the limited but growing evidence base on outdoor air pollution and health in Bangladesh and may inform policy development, targeted public health interventions, and research funding priorities.\u003c/p\u003e","manuscriptTitle":"A mapping review of epidemiological evidence on outdoor air pollution and human health in Bangladesh","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-22 08:26:19","doi":"10.21203/rs.3.rs-9121173/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"314784308149369349103677214144874548399","date":"2026-04-10T05:18:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"208499753508300695644644637263812625096","date":"2026-04-07T14:51:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-05T12:38:27+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-31T16:20:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-30T06:31:36+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-28T13:02:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Public Health","date":"2026-03-28T12:57:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"96694b86-b6eb-4634-aa09-ded2968ce2a6","owner":[],"postedDate":"April 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T08:26:20+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-22 08:26:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9121173","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9121173","identity":"rs-9121173","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}