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Indoor air pollution from solid fuels and hypertension: A systematic review and meta-analysis
Journal Pre-proof Indoor air pollution from solid fuels and hypertension: A systematic review and metaanalysis Lanyu Li, Aiming Yang, Xiaotao He, Jiangtao Liu, Yueling Ma, Jingping Niu, Bin Luo PII:
S0269-7491(19)34812-2
DOI:
https://doi.org/10.1016/j.envpol.2020.113914
Reference:
ENPO 113914
To appear in:
Environmental Pollution
Received Date: 25 August 2019 Revised Date:
29 December 2019
Accepted Date: 2 January 2020
Please cite this article as: Li, L., Yang, A., He, X., Liu, J., Ma, Y., Niu, J., Luo, B., Indoor air pollution from solid fuels and hypertension: A systematic review and meta-analysis, Environmental Pollution (2020), doi: https://doi.org/10.1016/j.envpol.2020.113914. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier Ltd.
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Indoor Air Pollution from Solid Fuels and Hypertension: A
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Systematic Review and Meta-Analysis
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Lanyu Lia#; Aiming Yangc#; Xiaotao Hea; Jiangtao Liua; Yueling Maa; Jingping,
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Niua; Bin Luoa, b*
5
a
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Lanzhou University, Lanzhou, Gansu 730000, People’s Republic of China
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b
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Republic of China
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c
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Institute of Occupational Health and Environmental Health, School of Public Health,
Shanghai Key Laboratory of Meteorology and health, Shanghai 200030, People’s
Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong,
Hong Kong SAR, People’s Republic of China
11 12 13 14 15 16 17 18 19 20
*
Correspondence to Bin Luo: Institute of Occupational Health and Environmental
Health, School of Public Health, Lanzhou University, 199 Donggang West Road, Lanzhou, 730000, China. E-mail address: [email protected] (B.Luo) #
Lanyu Li and Aiming Yang contributed equally to this work. 1
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Abstract
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Cardiovascular diseases (CVD) are leading global health issue. More studies
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have linked indoor air pollution from solid fuel usage to hypertension risk, a leading
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risk factor for CVD. We conducted a systematic review and meta-analysis of
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observational studies assessing the relationship of indoor air pollution from solid fuel
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with hypertension risk. Using a protocol standardized a priori, two independent
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reviewers searched PubMed, the Cochrane Library, Ovid MEDLINE, Web of Science
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and EMBASE for available studies published before Dec.1, 2019. A random effects
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model was used to analyze the pooled results. Out of 3740 articles, 47 were reviewed
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in depth and 11 contributing to this meta-analysis. The use of household solid fuel
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was significantly associated with an increased risk of hypertension (OR = 1.52 , 95%
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CI = 1.26 to 1.85 ). The smoking-controlled group (OR = 2.38, 95% CI = 1.58 to 3.60)
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had greater effect size of hypertension than the uncontrolled group (OR = 1.11, 95%
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CI = 1.10 to 1.11). These findings implicated that indoor air pollution from solid fuel
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may be an important risk factor for hypertension.
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Key Words: Solid Fuel; Indoor Air Pollution; Hypertension; Meta-analysis; Review
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2
Introduction
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Hypertension is the leading global risk factor for cardiovascular diseases,
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affecting more than one billion individuals and causing an estimated 9.4 million
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deaths each year.1 Recent study showed an increasing trend in prevalence of
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hypertension over time with an estimated 1.56 billion people in 2025.2 Besides some
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well-established risk factors for hypertension, such as diet, smoking and physical
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activity, the role of environmental factors, particularly air pollution, had gained
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considerable attention worldwide.3,4 A nation-wide cohort study in China observed
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2.3% of the hypertension cases were attributed to fine particulate matter (PM2.5)
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exposure in adults.5 Meta-analysis also observed the significant associations of both
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long- and short-term exposures to outdoor air pollutants with increased risk of
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hypertension.6
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Besides outdoor air pollution, indoor air pollution is a leading cause of
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disability-adjusted life years in Southeast Asia and globally.7 About half of the world’s
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population depends on solid fuel including coal or biomass fuel for cooking and
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heating. In China, almost half of families use solid fuel for cooking. Burning solid
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fuel generates substantial emissions of health-damaging pollutants, including
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particulate matter (mainly PM2.5), carbon monoxide (CO), organic carbon and
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polycyclic aromatic hydrocarbons (PAHs). Coal-burning, the most significant
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contributors to ambient PM2.5, was responsible for 40% of population-weighted PM2.5
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in China in 2013.8 Solid fuel combustion, the major sources of indoor air pollution,
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causes an estimated 4.5% of the global burden of disease.9 Increasing studies reported
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that indoor air pollution exposure from household solid fuels combustion was
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associated with increased risk of hypertension.10 Indoor air pollution due to the use of
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solid fuels significantly increases the likelihood of being diagnosed with
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cardiovascular diseases including heart disease and hypertension in China.11 Biomass
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users also had higher particulate pollution in kitchen than liquefied petroleum gas
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users and caused higher prevalence of hypertension.12 So far, although increasing 3
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studies have investigated the association of indoor air pollution from solid fuel with
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hypertension risk, however, the conclusion is inconsistent partly owing to the different
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participants and fuel types. Additionally, systematic review and meta-analytical
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assessment of observational studies have not directly evaluated the role of indoor air
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pollution from solid fuel burning in the hypertension development.
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We therefore performed a systematic review and meta-analysis of available
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observational studies investigating the association between indoor air pollution from
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solid fuel burning and hypertension risk.
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Methods
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The design, implementation, analysis, and reporting of our meta-analysis were
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performed in accordance with the Meta-analysis of Observational Studies in
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Epidemiology (MOOSE) protocol.13 The protocol of this study was registered on
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International Prospective Register of Systematic Reviews, PROSPERO (registration
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number: CRD42019134027).
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Search Strategy
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We searched PubMed, the Cochrane Library, Ovid MEDLINE, Web of Science
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and EMBASE databases in terms of “high blood pressure”, “hypertensive disease”,
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“hypertension”, “indoor air pollution”, “household air pollution”, “solid fuel”,
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“biomass”, “coal”,
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publications in English and published before Dec.1, 2019 were included for review.
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Table 1 showed the specific search strategy in the PubMed database.
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and “wood”, using Boolean logic searching methods. All
Selection Criteria
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Hypertension was defined as: 1) systolic blood pressure (SBP) ≥ 140 mmHg
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and/or diastolic blood pressure (DBP) ≥ 90 mmHg;14 2) self-reported diagnosis by 4
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physician; 3) current anti-hypertensive medication use or anti-hypertensive therapy.
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Solid fuel was defined as coal, wood, charcoal, dung or crop residues.15
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Articles were considered for inclusion in the systematic review if they (1) were
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original, peer-reviewed population studies (2) reported odds ratios (ORs) and 95%
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confidence intervals (CIs) of hypertension by solid fuel smoke, or they could be
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calculated by original data. (3) published in English. Articles were excluded if they
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were: (1) review articles; (2) case reports or letter to the editor; (3) studies in vitro
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or animal studies; (4) studies involving only occupational exposure or blood
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pressure; (5) not published in English.
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To ensure the correct identification of eligible studies, we used a two-step
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selection process: two independent investigators (authors J.L. and Y.M.) conducted an
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initial screening of all titles and/or abstracts, and the full text of each potentially
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relevant article was then evaluated.
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Data Extraction and Quality Assessment
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Data were extracted using a standardized data collection form. Two investigators
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(L.L. and X.H.) independently extracted detailed information from each included
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article. Any discrepancies were resolved through group discussion. We extracted the
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following information from each publication: first author, publication year, study
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country, participants, study type, fuel type, hypertension definition, sample size,
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ORs, 95% CIs and addressed confounders. We extracted adjusted ORs firstly. If ORs
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or 95% CIs were not given directly in the included article, we would calculate the
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specific results through original data. In addition, all eligible ORs reported from one
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article were extracted and used as an independent set of data to perform all the
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subsequent statistical analysis.
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Quality assessment was performed according to the Agency for Healthcare
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Research and Quality (AHRQ).16 Evaluation of cross-sectional study standard
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including 11 items, with "YES" and "NO" and "UNCLEAR" answer.17 An item was 5
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scored “1” if it answered “YES”; the item was scored “0” if it answered “NO” or
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“UNCLEAR”. Article quality was rated as three levels: low quality = 0-3; moderate
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quality = 4-7; high quality = 8-11.18
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Statistical Analysis
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The ORs and 95% CIs were used as the common measure of association across
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studies. The natural log of OR, 95% CIs, and standard error (SE) were used to
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estimate the pooled effect size of all studies. The heterogeneity of the included studies
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was assessed by using the Q statistic and I2 statistic.19 If the result of heterogeneity
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test turned out to be significant, the DerSimonian and Laird random effects model
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was used to calculate the summary statistics. The causes leading to heterogeneity
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were analyzed further, and the subgroup analysis and meta regression of heterogeneity
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caused by these causes was used to calculate the combined statistics.
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Funnel plots and the Egger’s test were used to assess publication bias.20,21 If there
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was publication bias, Duval and Tweedie trim and fill procedure would be used to
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calculate the estimated effect size after considering publication bias.22
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In addition, we also conducted sensitivity analysis by excluding each single
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study and rerunning the statistical analysis to examine the robustness of the pooled
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estimates. All statistical analyses were performed by Stata software (version 11.0;
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Stata Corp, College Station, TX, USA). All tests were two tailed and statistical
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significance was defined as P < 0.05.
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Results
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Study Characteristics
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Of 3740 articles identified (623 in PubMed, 575 in Ovid MEDLINE, 1471 in
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EMBASE, 95 in the Cochrane Library and 976 in Web of Science), we excluded
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duplicates and studies that did not fulfill the inclusion criteria (Fig. 1). We finally
6
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included 11 studies (12 reports) in this meta-analysis.12,23-32 Each study was extracted
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one OR and its 95% CIs except the study conducted by Neupane et al.26‐‐‐
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Table 2 summarized the general characteristics of these included studies. Seven
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papers only studied women,12,23-27,32 while four studies included both women and
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men.28-31 All studies were carried out in developing countries, which included China
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(n=2), India (n=2), Peru (n=2), Honduras (n=1), Nigeria (n=1), Nepal (n=1),
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Pakistan (n=1) and ten resource-poor countries (n=1). All studies were published after
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2010, and the sample size ranged from 147 to 77,605 with a total of 101,262
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participants. Six study measured personal air pollution, while five studies did not
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measure directly. However, the data of solid fuel usage in all studies were collected by
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self-reported. Eight studies reported biomass, while three studies reported mixed solid
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fuel.
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Table 2 presented the quality scores of individual study. The highest score was 9,
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and the lowest score was 4. Three studies were of high quality and eight studies were
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of moderate quality. No article was of low quality and the mean quality score was
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6.18.
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The overall pooled effect of solid fuel use and hypertension
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The heterogeneity among these studies was statistically significant (I2 = 90.7%, P
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= 0.000), so we applied the random effects model. The overall pooled effect of all
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studies showed that the use of household solid fuel was significantly associated with
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an increased risk of hypertension (OR=1.52, 95% CI = 1.26 to 1.85). Fig. 2 showed
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the forest plot for the results among all included studies.
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Subgroup Analysis
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Heterogeneity among studies existed in numerous factors such as studied
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countries, participant characteristics, sample size, air pollutants measurements and
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adjusted variables including smoking. To explore the sources of heterogeneity, we
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further conducted subgroup analysis. The subgroup meta-analyses did not reveal the 7
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inconsistent results compared to the results from overall meta-analyse, and the
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heterogeneity was not effectively decreased in most subgroups (Supplemental Table
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1).
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The smoking-controlled groups, only included no-smoking or adjusted smoking
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population, contributed 45.14% to the pooled effect size, while the uncontrolled
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groups contributed 54.86% to the pooled effect size. The random pooled effect sizes
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(ORs) for the smoking-controlled- and uncontrolled- groups were 2.38 (95% CI =
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1.58 to 3.60) and 1.11 (95% CI = 1.10 to 1.11), respectively (Fig. 3). The difference
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between two subgroups was significant from meta-regression (P=0.006) , suggesting
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that smoking may be an important source of heterogeneity.
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Fig. 4 showed the subgroup meta-analysis for different kinds of fuel types.
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Mixed solid fuel contributed 44.06% to the pooled effect size of hypertension, while
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single biomass contributed 55.94%. The effect size of single biomass (OR= 1.63, 95%
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CI = 0.99 to 2.69) was greater than mixed solid fuel (OR= 1.27, 95% CI = 1.06 to
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1.51). However, the association between single biomass and hypertension was not
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statistically significant. Fig.5 presented subgroup meta-analysis for sample size. We
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found that the effect size of group 1 (≥ 500) and group 2 (< 500) was 1.45 (95% CI =
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1.18 to 1.79) and 1.62 (95% CI = 0.83 to 3.16), respectively.
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Sensitivity Analysis and Publication Bias
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In sensitivity analysis, all results were generally robust. Omitting a single study
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did not substantially alter the association magnitude and significance of the primary
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results. (Fig. 6). The pooled effect estimate (OR = 1.52, 95% CI = 1.26 to 1.85) for
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hypertension and solid fuel was statistically significant. The pooled effect estimate
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still became statistically significant after excluding the study one by one.
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The asymmetry was revealed by the shape of funnel plot in Fig. 7. However,
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based on the Egger’s test (P > |t| = 0.096) and the Duval and Tweedie trim and fill
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procedure, there was no a wide-scale indication of publication bias. 8
Discussion
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Solid fuel burning generates a great number of air pollutants, which may
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promote the induction of hypertension. In this systematic review and meta-analysis,
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we comprehensively evaluated the association between indoor air pollution from solid
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fuel and hypertension risk and found a positive association of increased indoor air
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pollution from solid fuel with hypertension risk. To our knowledge, this is the first
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study pooling evidences to recognize the association between indoor air pollution
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from solid fuel and hypertension through meta-analysis.
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Previous studies on the association between indoor air pollution from solid fuel
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burning and hypertension are rather inconsistent. Among 12 reports (11 studies )
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included in this study, 6 reports observed positive association of indoor air pollution
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from solid fuel burning with hypertension risk, whereas, 6 reports did not find the
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statistically significant association. After systematic evaluation of previous
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observational studies investigating the association between indoor air pollution from
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solid fuel burning and hypertension risk, our results showed a positive association,
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indicating that the solid fuel use may be a potential risk factor for hypertension.
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During combustion, solid fuel produces a large number of air pollutants such as
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particulate matter, volatile organic chemicals, sulfur dioxide (SO2) and nitrogen oxide
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(NOx).33 Previous study observed households using solid fuels for heating and
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cooking had twice higher average personal exposure PM2.5 value than using electric
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power in rural Guanzhong Plain, China.34 A study also reported that burning solid
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fuels for cooking and heating resulted in high levels of NO2 and SO2.35 These indoor
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air pollutants could induce the systemic inflammation, oxidative stress and vascular
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function impairment, and then promote the happening of hypertension and
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atherosclerosis.36,37
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We also observe the fuel type may be a critical factor in inducing hypertension.
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Expose to indoor air pollution from biomass fuel had an increased risk of
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hypertension compared with mixed solid fuel (biomass and coal) (OR: 1.63 vs. 1.27). 9
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However, the association between single biomass and hypertension risk was also not
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statistically significant. Biomass fuels refer to firewood, dung and sawdust etc, which
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are distinguished from coal. Different fuels have different burning efficiency, and
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would generate different contents of air pollution, which decided their different effect
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size on hypertension. A study conducted in China also found that biomass (wood,
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tobacco stems, corncobs etc.) burning resulted in higher personal PM2.5
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concentrations than coal in a rural region of China.38 However, studies reported higher
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level of heavy metal and PAHs in PM during coal burning, the exposure of which
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were related to the increase of hypertension and many other diseases like lung
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cancer.39 It is possible that the air pollutants from coal burning may also contribute to
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increased risk of hypertension, but the study concerning single coal burning is not
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available. Hence, future study concerning the hypertension effect of single coal
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burning will be needed to clarify the comparison between biomass and coal.
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In this study, we also found that smoking-controlled group had an increased risk
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of hypertension than uncontrolled group. The effect of solid fuel on hypertension may
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be underestimated among smoking populations as the passive cigarette smoking
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exposure is significantly associated with hypertension in female never-smokers.40
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Tobacco smoking (including passive smoking) may be an important confounding
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factor in evaluating the association between indoor air pollution from solid fuel and
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hypertension risk.
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This meta-analysis showed indoor air pollution from solid fuel is an important
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risk factor for hypertension, implicating hypertension risk reduction by reducing
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primary air pollutant emission from residential fuel combustion. Other studies that
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adoption of gas fuels (liquid petroleum gas, natural gas) also showed c clear benefit
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significant indoor air pollutant reduction, nearly 96% for targeted pollutants,41 and
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even applying of improved stoves was a potential method to reduce household air
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pollution in developing countries.42 Therefore, more efforts should be made to the
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promotion of improved stoves and other locally appropriate methods to reduce the
10
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exposure of solid fuel smoke, until everyone can access to cleaner fuels
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conveniently.43
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Our study included available observational studies and comprehensively
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evaluated the association between indoor air pollution from solid fuel burning and
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hypertension risk. Several limitations need to be considered when interpreting these
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findings. Firstly, there were significant amount of heterogeneity concerning relation
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of indoor air pollution among solid fuel burning to hypertension risk, although
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heterogeneities were substantially reduced by using subgroup analysis. Secondly,
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there is no data from unpublished negative studies. We have collected all the
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published studies, and the Duval & Tweedie trim and fill procedure indicated there
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did not exist wide-scale publication bias. Thirdly, we did not conduct dose-response
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relationship and further perform the subgroup analysis by hypertension measurements
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between indoor air pollution form solid fuel burning and hypertension risk as limited
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studies. Therefore, future studies should focus on dose-response relationship between
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solid fuel burning-based indoor air pollution and hypertension, and consider the effect
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of solid fuel smoke components and the measurement characteristics on hypertension.
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In conclusion, this meta-analysis implicated indoor air pollution from solid fuel
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is a potential risk factor for hypertension. It is crucial to reduce indoor air pollution
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from solid fuel by using cleaner fuel or improved biomass stove.
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Acknowledgements
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We acknowledge Dr. Xiaowei Ren for statistical method guide.
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Sources of Funding
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This work was supported by grants from the National Natural Science
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Foundation of China (4187050043), the foundation of the Ministry of Education Key
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Laboratory of Cell Activities and Stress Adaptations, Lanzhou University, China
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(lzujbky-2018-kb05).
11
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Conflicts of interest
292 293
The authors declare no conflict of interest.
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35. Seow WJ, Downward GS, Wei H, Rothman N, Reiss B, Xu J et al.. Indoor concentrations of
412
nitrogen dioxide and sulfur dioxide from burning solid fuels for cooking and heating in Yunnan Province,
413
China. INDOOR AIR 2016; 26(5): 776-783.
414 415
36. Brook RD, Franklin B, Cascio W, Hong Y, Howard G, Lipsett M et al.. Air pollution and
416
cardiovascular disease: a statement for healthcare professionals from the Expert Panel on Population and
417
Prevention Science of the American Heart Association. CIRCULATION 2004; 109(21): 2655-2671.
14
418 419
37. VAZIRI N. Causal link between oxidative stress, inflammation, and hypertension. 2008.
420 421
38. Hu W, Downward GS, Reiss B, Xu J, Bassig BA, Hosgood III HD et al.. Personal and indoor PM2.
422
5 exposure from burning solid fuels in vented and unvented stoves in a rural region of China with a high
423
incidence of lung cancer. ENVIRON SCI TECHNOL 2014; 48(15): 8456-8464.
424 425
39. Lu S, Tan Z, Liu P, Zhao H, Liu D, Yu S et al.. Single particle aerosol mass spectrometry of coal
426
combustion particles associated with high lung cancer rates in Xuanwei and Fuyuan, China.
427
CHEMOSPHERE 2017; 186: 278-286.
428 429
40. Park YS, Lee C, Kim Y, Ahn CM, Kim JO, Park J et al.. Association between secondhand smoke
430
exposure and hypertension in never smokers: a cross-sectional survey using data from Korean National
431
Health and Nutritional Examination Survey V, 2010
432 433
41. Shen G. Quantification of emission reduction potentials of primary air pollutants from residential
434
solid fuel combustion by adopting cleaner fuels in China. J Environ Sci (China) 2015; 37: 1-7.
435 436
42. Smith KR. Indoor air pollution in developing countries: recommendations for research. INDOOR
437
AIR 2002; 12(3): 198-207.
438 439
43. Mehta S, Shahpar C. The health benefits of interventions to reduce indoor air pollution from solid
440
fuel use: a cost-effectiveness analysis. ENERGY SUSTAIN DEV 2004; 8(3): 53-59.
2012. BMJ OPEN 2018; 8(5): e21217.
441 442 443 444 445 446 447 448 449 450 451 452 453 454
Table 1. Search strategy in PubMed 15
Search strategy 1
“Indoor air pollution” [Title/Abstract]
2
“Household air pollution” [Title/Abstract]
3
“Solid fuel” [Title/Abstract]
4
“Biomass” [Title/Abstract]
5
“Coal” [Title/Abstract]
6
“Wood” [Title/Abstract]
7
“Air pollution, indoor” [Mesh]
8
1 OR 2 OR 3 OR 4 OR 5 OR 6 OR 7
9
“Hypertension” [Title/Abstract]
10
“High blood pressure” [Title/Abstract]
11
“Hypertensive disease” [Title/Abstract]
12
“Hypertension” [Mesh]
13
9 OR 10 OR 11 OR 12
14
8 AND 13
16
Table 2. Characteristics of the included publications
455 First Author
Publication Country of year
Study
Participants
Study Type
Fuel Type
Hypertension Definition
Sample Size
Air Pollutant
OR (95% CIs)
AHRQ SCORE
Addressed Confounders
74 traditional Young
2019
Honduras
women using stoves
CS
biomass
SBP≥ 140 mmHg,
stoves 73
DBP ≥90 mmHg
cleaner-burning Justa stoves
Dutta
2011
India
no-smoking women
CS
biomass, SBP ≥140 mmHg, LPG
DBP ≥90 mmHg
Mean personal and kitchen
1.20 (0.35-4.12)*
6
Sex
3.38 (2.07-5.53)*
5
Sex, smoking
24-hour PM2.5
244 biomass,
PM10 and PM2.5
236 LPG
in cooking areas
Sex, age, weight, education, occupation,
Ofori
2018
Nigeria adult women CS
biomass
SBP ≥140 mmHg,
249 biomass,
DBP ≥90 mmHg
140 no-biomass
Indoor PM2.5 in a subset of
kitchen ventilation, hours per day spent 1.23 (0.73-2.07)
9
households
cooking, alcohol consumption,fasting blood glucose, total cholesterol, triglycerides, HDL and LDL cholesterol.
Albania, Arkua
2018
Armenia, etc.
Age, body mass index, ethnicity, women aged 15–49
CS
2015
Nepal
clean fuel DBP ≥90 mmHg
77605
No direct measurement
1.07 (0.99-1.16)
4
education, occupation, wealth index, rural/urban, location, and month of interview.
female ≥ Neupane
solid fuel, SBP ≥140 mmHg
50 years (a)
CS
firewood, SBP ≥140 mmHg, 115 wood, 107 biogas
DBP ≥90 mmHg
biogas
female aged
185 wood, 112
30-50 (b)
biogas
17
24-h kitchen CO 3.13 (1.41-7.14)*
0.60 (0.27-1.33)*
5
Smoking, kitchen characteristics, ventilation and additional fuel use
SBP ≥140 Dutta
2012
India
never-smoki ng women
CS
Biomass, LPG
635 biomass,
PM10 and PM2.5
452 LPG
in cooking areas
SBP ≥140 mmHg,
11013 ever ,
No direct
DBP ≥90 mmHg
3055 never
measurement
mmHg DBP ≥90
3.41 (2.44-4.76)*
4
Smoking, sex
mmHg
Lee
Yan
2012
2016
shanghai, Adults ≥ 18 China
China
years
Adults ≥ 18 years
CS
CS
solid fuels
solid fuel, SBP ≥140 mmHg, 1725 solid , 2869 clean fuel DBP ≥90 mmHg
SBP ≥140 mmHg, Burroughs Peña
2015
Puno,
Adults ≥ 35
Peru
years
CS
biomass
DBP ≥90 mmHg or self-reported diagnosis
Caravedo
2014
Puno,
Adults ≥ 35
Peru
years
self-reported CS
biomass history or current medication use
clean
No direct measurement
Age, gender, education level, smoking, 1.91 (1.58-2.30)
9
SHS, pack-years, BMI, waist circumference
1.11 (1.11-1.12)
9
Age, vascular disease history, pregnant
Age, sex, BMI, height, wealth index, 509 daily biomass , 495 no-daily
No direct measurement
categories of education years, presence 3.5 (1.7-7.0)
4
or absence of depressive symptoms, pack-years of smoking, alcohol abuse, and low physical activity
275 biomass ,
Indoor PM2.5
244 clean
and CO
0.51 (0.19-1.30)*
7
1.0 (0.8 to 1.4)
6
SBP ≥140 mmHg, Fatmi
2019
Sindh, Pakistan
Women 40 years
≥ CS
biomass
DBP ≥90 mmHg; 436 biomass, regular use of
414 non-biomass
medication
18
No direct measurement
Age, sex, household assets and current nutrition
456
CS, cross-sectional study; LPG, liquefied petroleum gas; BMI, body mass index ; HDL, high density lipoprotein; LDL, low density lipoprotein
457
*The study did not offer ORs directly and they were calculated by original data.
458
19
459 460
Fig. 1. A flow chart of screening studies on the association of hypertension and solid
461
fuel
462 463 464 465 466
20
%
Study ID
OR (95% CI)
Weight
Burroughs Pena 2015
3.50 (1.70, 7.00)
5.01
Dutta 2012
3.41 (2.44, 4.76)
10.56
Dutta 2011
3.38 (2.07, 5.53)
7.71
Neupane 2015a
3.13 (1.41, 7.14)
4.13
Lee 2012
1.91 (1.58, 2.30)
13.49
Ofori 2018
1.23 (0.73, 2.07)
7.26
Young 2019
1.20 (0.35, 4.12)
2.11
Yan 2016
1.11 (1.11, 1.12)
15.48
Arkua 2018
1.07 (0.99, 1.16)
15.09
Neupane 2015b
0.60 (0.27, 1.33)
4.24
Caravedo 2014
0.50 (0.20, 1.30)
3.26
Fatmi 2019
1.00 (0.80, 1.40)
11.67
Overall (I-squared = 90.7%, p = 0.000)
1.52 (1.26, 1.85)
100.00
NOTE: Weights are from random effects analysis .14
1
7.14
467 468 469
Fig. 2. Individual study odd ratio (95% CI) for the association between solid fuel use and
hypertension risk.
470 471 472
21
Study
%
ID
OR (95% CI)
Weight
Burroughs Pena 2015
3.50 (1.70, 7.00)
5.01
Dutta 2012
3.41 (2.44, 4.76)
10.56
Dutta 2011
3.38 (2.07, 5.53)
7.71
Neupane 2015a
3.13 (1.41, 7.14)
4.13
Lee 2012
1.91 (1.58, 2.30)
13.49
Neupane 2015b
0.60 (0.27, 1.33)
4.24
Subtotal (I-squared = 79.3%, p = 0.000)
2.38 (1.58, 3.60)
45.14
Ofori 2018
1.23 (0.73, 2.07)
7.26
Young 2019
1.20 (0.35, 4.12)
2.11
Yan 2016
1.11 (1.11, 1.12)
15.48
Arkua 2018
1.07 (0.99, 1.16)
15.09
Caravedo 2014
0.50 (0.20, 1.30)
3.26
Fatmi 2019
1.00 (0.80, 1.40)
11.67
Subtotal (I-squared = 0.0%, p = 0.525)
1.11 (1.10, 1.11)
54.86
1.52 (1.26, 1.85)
100.00
Controlled
. Uncontrolled
. Overall (I-squared = 90.7%, p = 0.000) NOTE: Weights are from random effects analysis .14
1
7.14
473 474
Fig. 3. Individual study odd ratio (95% CI) for the association between solid fuel use
475
and hypertension risk by smoking
476
22
Study
%
ID
OR (95% CI)
Weight
Burroughs Pena 2015
3.50 (1.70, 7.00)
5.01
Dutta 2012
3.41 (2.44, 4.76)
10.56
Dutta 2011
3.38 (2.07, 5.53)
7.71
Neupane 2015a
3.13 (1.41, 7.14)
4.13
Ofori 2018
1.23 (0.73, 2.07)
7.26
Young 2019
1.20 (0.35, 4.12)
2.11
Neupane 2015b
0.60 (0.27, 1.33)
4.24
Caravedo 2014
0.50 (0.20, 1.30)
3.26
Fatmi 2019
1.00 (0.80, 1.40)
11.67
Subtotal (I-squared = 86.4%, p = 0.000)
1.63 (0.99, 2.69)
55.94
Lee 2012
1.91 (1.58, 2.30)
13.49
Yan 2016
1.11 (1.11, 1.12)
15.48
Arkua 2018
1.07 (0.99, 1.16)
15.09
Subtotal (I-squared = 93.9%, p = 0.000)
1.27 (1.06, 1.51)
44.06
1.52 (1.26, 1.85)
100.00
Biomass
. Solid fuel
. Overall (I-squared = 90.7%, p = 0.000) NOTE: Weights are from random effects analysis .14
1
7.14
477 478
Fig. 4. Individual study odd ratio (95% CI) for the association between solid fuel use
479
and hypertension risk by fuel type
23
%
Study OR (95% CI)
Weight
Burroughs Pena 2015
3.50 (1.70, 7.00)
5.01
Dutta 2012
3.41 (2.44, 4.76)
10.56
Lee 2012
1.91 (1.58, 2.30)
13.49
Yan 2016
1.11 (1.11, 1.12)
15.48
Arkua 2018
1.07 (0.99, 1.16)
15.09
Caravedo 2014
0.50 (0.20, 1.30)
3.26
Fatmi 2019
1.00 (0.80, 1.40)
11.67
Subtotal (I-squared = 93.3%, p = 0.000)
1.45 (1.18, 1.79)
74.56
Dutta 2011
3.38 (2.07, 5.53)
7.71
Neupane 2015a
3.13 (1.41, 7.14)
4.13
Ofori 2018
1.23 (0.73, 2.07)
7.26
Young 2019
1.20 (0.35, 4.12)
2.11
Neupane 2015b
0.60 (0.27, 1.33)
4.24
Subtotal (I-squared = 77.6%, p = 0.001)
1.62 (0.83, 3.16)
25.44
1.52 (1.26, 1.85)
100.00
ID
≥500
. <500
. Overall (I-squared = 90.7%, p = 0.000) NOTE: Weights are from random effects analysis .14
1
7.14
480 481
Fig. 5. Individual study odd ratio (95% CI) for the association between solid fuel use
482
and hypertension risk adjusted by sample size
483 484
24
Meta-analysis random-effects estimates (exponential form) Study ommited Burroughs Pena 2015 Dutta 2012 Dutta 2011 Neupane 2015a Lee 2012 Ofori 2018 Young 2019 Yan 2016 Arkua 2018 Neupane 2015b Caravedo 2014 Fatmi 2019 1.15
1.26
1.52
1.85
485 486
Fig. 6. Sensitivity Analysis of included studies
487 488 489 490 491 492 493 494 495 496
25
2.25
Funnel plot with pseudo 95% confidence limits 0
Filled funnel plot with pseudo 95% confidence limits
s.e. of lnO R .4 .2
2
th e ta , fille d
1
.6
0
1
2
3
4
-1 0
OR
.2
.4 s.e. of: theta, filled
497 498 499
Fig. 7. Funnel plot and filled funnel plot of included studies
500 501 502 503 504 505 506
26
.6
Highlights: The association between indoor air pollution from solid fuel usage and risk of hypertension was systemically reviewed.
Indoor air pollution from solid fuel is an important risk factor for hypertension.
Smoking is an important confounding factor for evaluating the association of indoor air pollution from solid fuel with hypertension risk.
Declaration of interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
S0269-7491(19)34812-2
DOI:
https://doi.org/10.1016/j.envpol.2020.113914
Reference:
ENPO 113914
To appear in:
Environmental Pollution
Received Date: 25 August 2019 Revised Date:
29 December 2019
Accepted Date: 2 January 2020
Please cite this article as: Li, L., Yang, A., He, X., Liu, J., Ma, Y., Niu, J., Luo, B., Indoor air pollution from solid fuels and hypertension: A systematic review and meta-analysis, Environmental Pollution (2020), doi: https://doi.org/10.1016/j.envpol.2020.113914. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier Ltd.
1
Indoor Air Pollution from Solid Fuels and Hypertension: A
2
Systematic Review and Meta-Analysis
3
Lanyu Lia#; Aiming Yangc#; Xiaotao Hea; Jiangtao Liua; Yueling Maa; Jingping,
4
Niua; Bin Luoa, b*
5
a
6
Lanzhou University, Lanzhou, Gansu 730000, People’s Republic of China
7
b
8
Republic of China
9
c
10
Institute of Occupational Health and Environmental Health, School of Public Health,
Shanghai Key Laboratory of Meteorology and health, Shanghai 200030, People’s
Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong,
Hong Kong SAR, People’s Republic of China
11 12 13 14 15 16 17 18 19 20
*
Correspondence to Bin Luo: Institute of Occupational Health and Environmental
Health, School of Public Health, Lanzhou University, 199 Donggang West Road, Lanzhou, 730000, China. E-mail address: [email protected] (B.Luo) #
Lanyu Li and Aiming Yang contributed equally to this work. 1
21
Abstract
22
Cardiovascular diseases (CVD) are leading global health issue. More studies
23
have linked indoor air pollution from solid fuel usage to hypertension risk, a leading
24
risk factor for CVD. We conducted a systematic review and meta-analysis of
25
observational studies assessing the relationship of indoor air pollution from solid fuel
26
with hypertension risk. Using a protocol standardized a priori, two independent
27
reviewers searched PubMed, the Cochrane Library, Ovid MEDLINE, Web of Science
28
and EMBASE for available studies published before Dec.1, 2019. A random effects
29
model was used to analyze the pooled results. Out of 3740 articles, 47 were reviewed
30
in depth and 11 contributing to this meta-analysis. The use of household solid fuel
31
was significantly associated with an increased risk of hypertension (OR = 1.52 , 95%
32
CI = 1.26 to 1.85 ). The smoking-controlled group (OR = 2.38, 95% CI = 1.58 to 3.60)
33
had greater effect size of hypertension than the uncontrolled group (OR = 1.11, 95%
34
CI = 1.10 to 1.11). These findings implicated that indoor air pollution from solid fuel
35
may be an important risk factor for hypertension.
36
Key Words: Solid Fuel; Indoor Air Pollution; Hypertension; Meta-analysis; Review
37 38 39 40 41 42 43
44
45
46
2
Introduction
47 48
Hypertension is the leading global risk factor for cardiovascular diseases,
49
affecting more than one billion individuals and causing an estimated 9.4 million
50
deaths each year.1 Recent study showed an increasing trend in prevalence of
51
hypertension over time with an estimated 1.56 billion people in 2025.2 Besides some
52
well-established risk factors for hypertension, such as diet, smoking and physical
53
activity, the role of environmental factors, particularly air pollution, had gained
54
considerable attention worldwide.3,4 A nation-wide cohort study in China observed
55
2.3% of the hypertension cases were attributed to fine particulate matter (PM2.5)
56
exposure in adults.5 Meta-analysis also observed the significant associations of both
57
long- and short-term exposures to outdoor air pollutants with increased risk of
58
hypertension.6
59
Besides outdoor air pollution, indoor air pollution is a leading cause of
60
disability-adjusted life years in Southeast Asia and globally.7 About half of the world’s
61
population depends on solid fuel including coal or biomass fuel for cooking and
62
heating. In China, almost half of families use solid fuel for cooking. Burning solid
63
fuel generates substantial emissions of health-damaging pollutants, including
64
particulate matter (mainly PM2.5), carbon monoxide (CO), organic carbon and
65
polycyclic aromatic hydrocarbons (PAHs). Coal-burning, the most significant
66
contributors to ambient PM2.5, was responsible for 40% of population-weighted PM2.5
67
in China in 2013.8 Solid fuel combustion, the major sources of indoor air pollution,
68
causes an estimated 4.5% of the global burden of disease.9 Increasing studies reported
69
that indoor air pollution exposure from household solid fuels combustion was
70
associated with increased risk of hypertension.10 Indoor air pollution due to the use of
71
solid fuels significantly increases the likelihood of being diagnosed with
72
cardiovascular diseases including heart disease and hypertension in China.11 Biomass
73
users also had higher particulate pollution in kitchen than liquefied petroleum gas
74
users and caused higher prevalence of hypertension.12 So far, although increasing 3
75
studies have investigated the association of indoor air pollution from solid fuel with
76
hypertension risk, however, the conclusion is inconsistent partly owing to the different
77
participants and fuel types. Additionally, systematic review and meta-analytical
78
assessment of observational studies have not directly evaluated the role of indoor air
79
pollution from solid fuel burning in the hypertension development.
80
We therefore performed a systematic review and meta-analysis of available
81
observational studies investigating the association between indoor air pollution from
82
solid fuel burning and hypertension risk.
83
Methods
84 85
The design, implementation, analysis, and reporting of our meta-analysis were
86
performed in accordance with the Meta-analysis of Observational Studies in
87
Epidemiology (MOOSE) protocol.13 The protocol of this study was registered on
88
International Prospective Register of Systematic Reviews, PROSPERO (registration
89
number: CRD42019134027).
90
Search Strategy
91
We searched PubMed, the Cochrane Library, Ovid MEDLINE, Web of Science
92
and EMBASE databases in terms of “high blood pressure”, “hypertensive disease”,
93
“hypertension”, “indoor air pollution”, “household air pollution”, “solid fuel”,
94
“biomass”, “coal”,
95
publications in English and published before Dec.1, 2019 were included for review.
96
Table 1 showed the specific search strategy in the PubMed database.
97
and “wood”, using Boolean logic searching methods. All
Selection Criteria
98
Hypertension was defined as: 1) systolic blood pressure (SBP) ≥ 140 mmHg
99
and/or diastolic blood pressure (DBP) ≥ 90 mmHg;14 2) self-reported diagnosis by 4
100
physician; 3) current anti-hypertensive medication use or anti-hypertensive therapy.
101
Solid fuel was defined as coal, wood, charcoal, dung or crop residues.15
102
Articles were considered for inclusion in the systematic review if they (1) were
103
original, peer-reviewed population studies (2) reported odds ratios (ORs) and 95%
104
confidence intervals (CIs) of hypertension by solid fuel smoke, or they could be
105
calculated by original data. (3) published in English. Articles were excluded if they
106
were: (1) review articles; (2) case reports or letter to the editor; (3) studies in vitro
107
or animal studies; (4) studies involving only occupational exposure or blood
108
pressure; (5) not published in English.
109
To ensure the correct identification of eligible studies, we used a two-step
110
selection process: two independent investigators (authors J.L. and Y.M.) conducted an
111
initial screening of all titles and/or abstracts, and the full text of each potentially
112
relevant article was then evaluated.
113
Data Extraction and Quality Assessment
114
Data were extracted using a standardized data collection form. Two investigators
115
(L.L. and X.H.) independently extracted detailed information from each included
116
article. Any discrepancies were resolved through group discussion. We extracted the
117
following information from each publication: first author, publication year, study
118
country, participants, study type, fuel type, hypertension definition, sample size,
119
ORs, 95% CIs and addressed confounders. We extracted adjusted ORs firstly. If ORs
120
or 95% CIs were not given directly in the included article, we would calculate the
121
specific results through original data. In addition, all eligible ORs reported from one
122
article were extracted and used as an independent set of data to perform all the
123
subsequent statistical analysis.
124
Quality assessment was performed according to the Agency for Healthcare
125
Research and Quality (AHRQ).16 Evaluation of cross-sectional study standard
126
including 11 items, with "YES" and "NO" and "UNCLEAR" answer.17 An item was 5
127
scored “1” if it answered “YES”; the item was scored “0” if it answered “NO” or
128
“UNCLEAR”. Article quality was rated as three levels: low quality = 0-3; moderate
129
quality = 4-7; high quality = 8-11.18
130
Statistical Analysis
131
The ORs and 95% CIs were used as the common measure of association across
132
studies. The natural log of OR, 95% CIs, and standard error (SE) were used to
133
estimate the pooled effect size of all studies. The heterogeneity of the included studies
134
was assessed by using the Q statistic and I2 statistic.19 If the result of heterogeneity
135
test turned out to be significant, the DerSimonian and Laird random effects model
136
was used to calculate the summary statistics. The causes leading to heterogeneity
137
were analyzed further, and the subgroup analysis and meta regression of heterogeneity
138
caused by these causes was used to calculate the combined statistics.
139
Funnel plots and the Egger’s test were used to assess publication bias.20,21 If there
140
was publication bias, Duval and Tweedie trim and fill procedure would be used to
141
calculate the estimated effect size after considering publication bias.22
142
In addition, we also conducted sensitivity analysis by excluding each single
143
study and rerunning the statistical analysis to examine the robustness of the pooled
144
estimates. All statistical analyses were performed by Stata software (version 11.0;
145
Stata Corp, College Station, TX, USA). All tests were two tailed and statistical
146
significance was defined as P < 0.05.
147
Results
148 149
Study Characteristics
150
Of 3740 articles identified (623 in PubMed, 575 in Ovid MEDLINE, 1471 in
151
EMBASE, 95 in the Cochrane Library and 976 in Web of Science), we excluded
152
duplicates and studies that did not fulfill the inclusion criteria (Fig. 1). We finally
6
153
included 11 studies (12 reports) in this meta-analysis.12,23-32 Each study was extracted
154
one OR and its 95% CIs except the study conducted by Neupane et al.26‐‐‐
155
Table 2 summarized the general characteristics of these included studies. Seven
156
papers only studied women,12,23-27,32 while four studies included both women and
157
men.28-31 All studies were carried out in developing countries, which included China
158
(n=2), India (n=2), Peru (n=2), Honduras (n=1), Nigeria (n=1), Nepal (n=1),
159
Pakistan (n=1) and ten resource-poor countries (n=1). All studies were published after
160
2010, and the sample size ranged from 147 to 77,605 with a total of 101,262
161
participants. Six study measured personal air pollution, while five studies did not
162
measure directly. However, the data of solid fuel usage in all studies were collected by
163
self-reported. Eight studies reported biomass, while three studies reported mixed solid
164
fuel.
165
Table 2 presented the quality scores of individual study. The highest score was 9,
166
and the lowest score was 4. Three studies were of high quality and eight studies were
167
of moderate quality. No article was of low quality and the mean quality score was
168
6.18.
169
The overall pooled effect of solid fuel use and hypertension
170
The heterogeneity among these studies was statistically significant (I2 = 90.7%, P
171
= 0.000), so we applied the random effects model. The overall pooled effect of all
172
studies showed that the use of household solid fuel was significantly associated with
173
an increased risk of hypertension (OR=1.52, 95% CI = 1.26 to 1.85). Fig. 2 showed
174
the forest plot for the results among all included studies.
175
Subgroup Analysis
176
Heterogeneity among studies existed in numerous factors such as studied
177
countries, participant characteristics, sample size, air pollutants measurements and
178
adjusted variables including smoking. To explore the sources of heterogeneity, we
179
further conducted subgroup analysis. The subgroup meta-analyses did not reveal the 7
180
inconsistent results compared to the results from overall meta-analyse, and the
181
heterogeneity was not effectively decreased in most subgroups (Supplemental Table
182
1).
183
The smoking-controlled groups, only included no-smoking or adjusted smoking
184
population, contributed 45.14% to the pooled effect size, while the uncontrolled
185
groups contributed 54.86% to the pooled effect size. The random pooled effect sizes
186
(ORs) for the smoking-controlled- and uncontrolled- groups were 2.38 (95% CI =
187
1.58 to 3.60) and 1.11 (95% CI = 1.10 to 1.11), respectively (Fig. 3). The difference
188
between two subgroups was significant from meta-regression (P=0.006) , suggesting
189
that smoking may be an important source of heterogeneity.
190
Fig. 4 showed the subgroup meta-analysis for different kinds of fuel types.
191
Mixed solid fuel contributed 44.06% to the pooled effect size of hypertension, while
192
single biomass contributed 55.94%. The effect size of single biomass (OR= 1.63, 95%
193
CI = 0.99 to 2.69) was greater than mixed solid fuel (OR= 1.27, 95% CI = 1.06 to
194
1.51). However, the association between single biomass and hypertension was not
195
statistically significant. Fig.5 presented subgroup meta-analysis for sample size. We
196
found that the effect size of group 1 (≥ 500) and group 2 (< 500) was 1.45 (95% CI =
197
1.18 to 1.79) and 1.62 (95% CI = 0.83 to 3.16), respectively.
198
Sensitivity Analysis and Publication Bias
199
In sensitivity analysis, all results were generally robust. Omitting a single study
200
did not substantially alter the association magnitude and significance of the primary
201
results. (Fig. 6). The pooled effect estimate (OR = 1.52, 95% CI = 1.26 to 1.85) for
202
hypertension and solid fuel was statistically significant. The pooled effect estimate
203
still became statistically significant after excluding the study one by one.
204
The asymmetry was revealed by the shape of funnel plot in Fig. 7. However,
205
based on the Egger’s test (P > |t| = 0.096) and the Duval and Tweedie trim and fill
206
procedure, there was no a wide-scale indication of publication bias. 8
Discussion
207 208
Solid fuel burning generates a great number of air pollutants, which may
209
promote the induction of hypertension. In this systematic review and meta-analysis,
210
we comprehensively evaluated the association between indoor air pollution from solid
211
fuel and hypertension risk and found a positive association of increased indoor air
212
pollution from solid fuel with hypertension risk. To our knowledge, this is the first
213
study pooling evidences to recognize the association between indoor air pollution
214
from solid fuel and hypertension through meta-analysis.
215
Previous studies on the association between indoor air pollution from solid fuel
216
burning and hypertension are rather inconsistent. Among 12 reports (11 studies )
217
included in this study, 6 reports observed positive association of indoor air pollution
218
from solid fuel burning with hypertension risk, whereas, 6 reports did not find the
219
statistically significant association. After systematic evaluation of previous
220
observational studies investigating the association between indoor air pollution from
221
solid fuel burning and hypertension risk, our results showed a positive association,
222
indicating that the solid fuel use may be a potential risk factor for hypertension.
223
During combustion, solid fuel produces a large number of air pollutants such as
224
particulate matter, volatile organic chemicals, sulfur dioxide (SO2) and nitrogen oxide
225
(NOx).33 Previous study observed households using solid fuels for heating and
226
cooking had twice higher average personal exposure PM2.5 value than using electric
227
power in rural Guanzhong Plain, China.34 A study also reported that burning solid
228
fuels for cooking and heating resulted in high levels of NO2 and SO2.35 These indoor
229
air pollutants could induce the systemic inflammation, oxidative stress and vascular
230
function impairment, and then promote the happening of hypertension and
231
atherosclerosis.36,37
232
We also observe the fuel type may be a critical factor in inducing hypertension.
233
Expose to indoor air pollution from biomass fuel had an increased risk of
234
hypertension compared with mixed solid fuel (biomass and coal) (OR: 1.63 vs. 1.27). 9
235
However, the association between single biomass and hypertension risk was also not
236
statistically significant. Biomass fuels refer to firewood, dung and sawdust etc, which
237
are distinguished from coal. Different fuels have different burning efficiency, and
238
would generate different contents of air pollution, which decided their different effect
239
size on hypertension. A study conducted in China also found that biomass (wood,
240
tobacco stems, corncobs etc.) burning resulted in higher personal PM2.5
241
concentrations than coal in a rural region of China.38 However, studies reported higher
242
level of heavy metal and PAHs in PM during coal burning, the exposure of which
243
were related to the increase of hypertension and many other diseases like lung
244
cancer.39 It is possible that the air pollutants from coal burning may also contribute to
245
increased risk of hypertension, but the study concerning single coal burning is not
246
available. Hence, future study concerning the hypertension effect of single coal
247
burning will be needed to clarify the comparison between biomass and coal.
248
In this study, we also found that smoking-controlled group had an increased risk
249
of hypertension than uncontrolled group. The effect of solid fuel on hypertension may
250
be underestimated among smoking populations as the passive cigarette smoking
251
exposure is significantly associated with hypertension in female never-smokers.40
252
Tobacco smoking (including passive smoking) may be an important confounding
253
factor in evaluating the association between indoor air pollution from solid fuel and
254
hypertension risk.
255
This meta-analysis showed indoor air pollution from solid fuel is an important
256
risk factor for hypertension, implicating hypertension risk reduction by reducing
257
primary air pollutant emission from residential fuel combustion. Other studies that
258
adoption of gas fuels (liquid petroleum gas, natural gas) also showed c clear benefit
259
significant indoor air pollutant reduction, nearly 96% for targeted pollutants,41 and
260
even applying of improved stoves was a potential method to reduce household air
261
pollution in developing countries.42 Therefore, more efforts should be made to the
262
promotion of improved stoves and other locally appropriate methods to reduce the
10
263
exposure of solid fuel smoke, until everyone can access to cleaner fuels
264
conveniently.43
265
Our study included available observational studies and comprehensively
266
evaluated the association between indoor air pollution from solid fuel burning and
267
hypertension risk. Several limitations need to be considered when interpreting these
268
findings. Firstly, there were significant amount of heterogeneity concerning relation
269
of indoor air pollution among solid fuel burning to hypertension risk, although
270
heterogeneities were substantially reduced by using subgroup analysis. Secondly,
271
there is no data from unpublished negative studies. We have collected all the
272
published studies, and the Duval & Tweedie trim and fill procedure indicated there
273
did not exist wide-scale publication bias. Thirdly, we did not conduct dose-response
274
relationship and further perform the subgroup analysis by hypertension measurements
275
between indoor air pollution form solid fuel burning and hypertension risk as limited
276
studies. Therefore, future studies should focus on dose-response relationship between
277
solid fuel burning-based indoor air pollution and hypertension, and consider the effect
278
of solid fuel smoke components and the measurement characteristics on hypertension.
279
In conclusion, this meta-analysis implicated indoor air pollution from solid fuel
280
is a potential risk factor for hypertension. It is crucial to reduce indoor air pollution
281
from solid fuel by using cleaner fuel or improved biomass stove.
282
Acknowledgements
283 284
We acknowledge Dr. Xiaowei Ren for statistical method guide.
285
Sources of Funding
286 287
This work was supported by grants from the National Natural Science
288
Foundation of China (4187050043), the foundation of the Ministry of Education Key
289
Laboratory of Cell Activities and Stress Adaptations, Lanzhou University, China
290
(lzujbky-2018-kb05).
11
291
Conflicts of interest
292 293
The authors declare no conflict of interest.
294 295
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296
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Table 1. Search strategy in PubMed 15
Search strategy 1
“Indoor air pollution” [Title/Abstract]
2
“Household air pollution” [Title/Abstract]
3
“Solid fuel” [Title/Abstract]
4
“Biomass” [Title/Abstract]
5
“Coal” [Title/Abstract]
6
“Wood” [Title/Abstract]
7
“Air pollution, indoor” [Mesh]
8
1 OR 2 OR 3 OR 4 OR 5 OR 6 OR 7
9
“Hypertension” [Title/Abstract]
10
“High blood pressure” [Title/Abstract]
11
“Hypertensive disease” [Title/Abstract]
12
“Hypertension” [Mesh]
13
9 OR 10 OR 11 OR 12
14
8 AND 13
16
Table 2. Characteristics of the included publications
455 First Author
Publication Country of year
Study
Participants
Study Type
Fuel Type
Hypertension Definition
Sample Size
Air Pollutant
OR (95% CIs)
AHRQ SCORE
Addressed Confounders
74 traditional Young
2019
Honduras
women using stoves
CS
biomass
SBP≥ 140 mmHg,
stoves 73
DBP ≥90 mmHg
cleaner-burning Justa stoves
Dutta
2011
India
no-smoking women
CS
biomass, SBP ≥140 mmHg, LPG
DBP ≥90 mmHg
Mean personal and kitchen
1.20 (0.35-4.12)*
6
Sex
3.38 (2.07-5.53)*
5
Sex, smoking
24-hour PM2.5
244 biomass,
PM10 and PM2.5
236 LPG
in cooking areas
Sex, age, weight, education, occupation,
Ofori
2018
Nigeria adult women CS
biomass
SBP ≥140 mmHg,
249 biomass,
DBP ≥90 mmHg
140 no-biomass
Indoor PM2.5 in a subset of
kitchen ventilation, hours per day spent 1.23 (0.73-2.07)
9
households
cooking, alcohol consumption,fasting blood glucose, total cholesterol, triglycerides, HDL and LDL cholesterol.
Albania, Arkua
2018
Armenia, etc.
Age, body mass index, ethnicity, women aged 15–49
CS
2015
Nepal
clean fuel DBP ≥90 mmHg
77605
No direct measurement
1.07 (0.99-1.16)
4
education, occupation, wealth index, rural/urban, location, and month of interview.
female ≥ Neupane
solid fuel, SBP ≥140 mmHg
50 years (a)
CS
firewood, SBP ≥140 mmHg, 115 wood, 107 biogas
DBP ≥90 mmHg
biogas
female aged
185 wood, 112
30-50 (b)
biogas
17
24-h kitchen CO 3.13 (1.41-7.14)*
0.60 (0.27-1.33)*
5
Smoking, kitchen characteristics, ventilation and additional fuel use
SBP ≥140 Dutta
2012
India
never-smoki ng women
CS
Biomass, LPG
635 biomass,
PM10 and PM2.5
452 LPG
in cooking areas
SBP ≥140 mmHg,
11013 ever ,
No direct
DBP ≥90 mmHg
3055 never
measurement
mmHg DBP ≥90
3.41 (2.44-4.76)*
4
Smoking, sex
mmHg
Lee
Yan
2012
2016
shanghai, Adults ≥ 18 China
China
years
Adults ≥ 18 years
CS
CS
solid fuels
solid fuel, SBP ≥140 mmHg, 1725 solid , 2869 clean fuel DBP ≥90 mmHg
SBP ≥140 mmHg, Burroughs Peña
2015
Puno,
Adults ≥ 35
Peru
years
CS
biomass
DBP ≥90 mmHg or self-reported diagnosis
Caravedo
2014
Puno,
Adults ≥ 35
Peru
years
self-reported CS
biomass history or current medication use
clean
No direct measurement
Age, gender, education level, smoking, 1.91 (1.58-2.30)
9
SHS, pack-years, BMI, waist circumference
1.11 (1.11-1.12)
9
Age, vascular disease history, pregnant
Age, sex, BMI, height, wealth index, 509 daily biomass , 495 no-daily
No direct measurement
categories of education years, presence 3.5 (1.7-7.0)
4
or absence of depressive symptoms, pack-years of smoking, alcohol abuse, and low physical activity
275 biomass ,
Indoor PM2.5
244 clean
and CO
0.51 (0.19-1.30)*
7
1.0 (0.8 to 1.4)
6
SBP ≥140 mmHg, Fatmi
2019
Sindh, Pakistan
Women 40 years
≥ CS
biomass
DBP ≥90 mmHg; 436 biomass, regular use of
414 non-biomass
medication
18
No direct measurement
Age, sex, household assets and current nutrition
456
CS, cross-sectional study; LPG, liquefied petroleum gas; BMI, body mass index ; HDL, high density lipoprotein; LDL, low density lipoprotein
457
*The study did not offer ORs directly and they were calculated by original data.
458
19
459 460
Fig. 1. A flow chart of screening studies on the association of hypertension and solid
461
fuel
462 463 464 465 466
20
%
Study ID
OR (95% CI)
Weight
Burroughs Pena 2015
3.50 (1.70, 7.00)
5.01
Dutta 2012
3.41 (2.44, 4.76)
10.56
Dutta 2011
3.38 (2.07, 5.53)
7.71
Neupane 2015a
3.13 (1.41, 7.14)
4.13
Lee 2012
1.91 (1.58, 2.30)
13.49
Ofori 2018
1.23 (0.73, 2.07)
7.26
Young 2019
1.20 (0.35, 4.12)
2.11
Yan 2016
1.11 (1.11, 1.12)
15.48
Arkua 2018
1.07 (0.99, 1.16)
15.09
Neupane 2015b
0.60 (0.27, 1.33)
4.24
Caravedo 2014
0.50 (0.20, 1.30)
3.26
Fatmi 2019
1.00 (0.80, 1.40)
11.67
Overall (I-squared = 90.7%, p = 0.000)
1.52 (1.26, 1.85)
100.00
NOTE: Weights are from random effects analysis .14
1
7.14
467 468 469
Fig. 2. Individual study odd ratio (95% CI) for the association between solid fuel use and
hypertension risk.
470 471 472
21
Study
%
ID
OR (95% CI)
Weight
Burroughs Pena 2015
3.50 (1.70, 7.00)
5.01
Dutta 2012
3.41 (2.44, 4.76)
10.56
Dutta 2011
3.38 (2.07, 5.53)
7.71
Neupane 2015a
3.13 (1.41, 7.14)
4.13
Lee 2012
1.91 (1.58, 2.30)
13.49
Neupane 2015b
0.60 (0.27, 1.33)
4.24
Subtotal (I-squared = 79.3%, p = 0.000)
2.38 (1.58, 3.60)
45.14
Ofori 2018
1.23 (0.73, 2.07)
7.26
Young 2019
1.20 (0.35, 4.12)
2.11
Yan 2016
1.11 (1.11, 1.12)
15.48
Arkua 2018
1.07 (0.99, 1.16)
15.09
Caravedo 2014
0.50 (0.20, 1.30)
3.26
Fatmi 2019
1.00 (0.80, 1.40)
11.67
Subtotal (I-squared = 0.0%, p = 0.525)
1.11 (1.10, 1.11)
54.86
1.52 (1.26, 1.85)
100.00
Controlled
. Uncontrolled
. Overall (I-squared = 90.7%, p = 0.000) NOTE: Weights are from random effects analysis .14
1
7.14
473 474
Fig. 3. Individual study odd ratio (95% CI) for the association between solid fuel use
475
and hypertension risk by smoking
476
22
Study
%
ID
OR (95% CI)
Weight
Burroughs Pena 2015
3.50 (1.70, 7.00)
5.01
Dutta 2012
3.41 (2.44, 4.76)
10.56
Dutta 2011
3.38 (2.07, 5.53)
7.71
Neupane 2015a
3.13 (1.41, 7.14)
4.13
Ofori 2018
1.23 (0.73, 2.07)
7.26
Young 2019
1.20 (0.35, 4.12)
2.11
Neupane 2015b
0.60 (0.27, 1.33)
4.24
Caravedo 2014
0.50 (0.20, 1.30)
3.26
Fatmi 2019
1.00 (0.80, 1.40)
11.67
Subtotal (I-squared = 86.4%, p = 0.000)
1.63 (0.99, 2.69)
55.94
Lee 2012
1.91 (1.58, 2.30)
13.49
Yan 2016
1.11 (1.11, 1.12)
15.48
Arkua 2018
1.07 (0.99, 1.16)
15.09
Subtotal (I-squared = 93.9%, p = 0.000)
1.27 (1.06, 1.51)
44.06
1.52 (1.26, 1.85)
100.00
Biomass
. Solid fuel
. Overall (I-squared = 90.7%, p = 0.000) NOTE: Weights are from random effects analysis .14
1
7.14
477 478
Fig. 4. Individual study odd ratio (95% CI) for the association between solid fuel use
479
and hypertension risk by fuel type
23
%
Study OR (95% CI)
Weight
Burroughs Pena 2015
3.50 (1.70, 7.00)
5.01
Dutta 2012
3.41 (2.44, 4.76)
10.56
Lee 2012
1.91 (1.58, 2.30)
13.49
Yan 2016
1.11 (1.11, 1.12)
15.48
Arkua 2018
1.07 (0.99, 1.16)
15.09
Caravedo 2014
0.50 (0.20, 1.30)
3.26
Fatmi 2019
1.00 (0.80, 1.40)
11.67
Subtotal (I-squared = 93.3%, p = 0.000)
1.45 (1.18, 1.79)
74.56
Dutta 2011
3.38 (2.07, 5.53)
7.71
Neupane 2015a
3.13 (1.41, 7.14)
4.13
Ofori 2018
1.23 (0.73, 2.07)
7.26
Young 2019
1.20 (0.35, 4.12)
2.11
Neupane 2015b
0.60 (0.27, 1.33)
4.24
Subtotal (I-squared = 77.6%, p = 0.001)
1.62 (0.83, 3.16)
25.44
1.52 (1.26, 1.85)
100.00
ID
≥500
. <500
. Overall (I-squared = 90.7%, p = 0.000) NOTE: Weights are from random effects analysis .14
1
7.14
480 481
Fig. 5. Individual study odd ratio (95% CI) for the association between solid fuel use
482
and hypertension risk adjusted by sample size
483 484
24
Meta-analysis random-effects estimates (exponential form) Study ommited Burroughs Pena 2015 Dutta 2012 Dutta 2011 Neupane 2015a Lee 2012 Ofori 2018 Young 2019 Yan 2016 Arkua 2018 Neupane 2015b Caravedo 2014 Fatmi 2019 1.15
1.26
1.52
1.85
485 486
Fig. 6. Sensitivity Analysis of included studies
487 488 489 490 491 492 493 494 495 496
25
2.25
Funnel plot with pseudo 95% confidence limits 0
Filled funnel plot with pseudo 95% confidence limits
s.e. of lnO R .4 .2
2
th e ta , fille d
1
.6
0
1
2
3
4
-1 0
OR
.2
.4 s.e. of: theta, filled
497 498 499
Fig. 7. Funnel plot and filled funnel plot of included studies
500 501 502 503 504 505 506
26
.6
Highlights: The association between indoor air pollution from solid fuel usage and risk of hypertension was systemically reviewed.
Indoor air pollution from solid fuel is an important risk factor for hypertension.
Smoking is an important confounding factor for evaluating the association of indoor air pollution from solid fuel with hypertension risk.
Declaration of interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: