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. 2024 Oct 18;31(2):89–97. doi: 10.1097/MCP.0000000000001126

Household air pollution and respiratory health in Africa: persistent risk and unchanged health burdens

Nkosana Jafta a, Busisiwe Shezi a,b, Minenhle Buthelezi a, Shamiso Muteti-Fana a,c, Rajen N Naidoo a
PMCID: PMC11789611  PMID: 39410863

Abstract

Purpose of review

Despite evidence emerging from the Global Burden of Disease studies that biomass use and household air pollution are declining globally, with important positive health impacts for households in low- and middle-income countries, these trends have not been equally documented in African countries. This review describes the state of household air pollution exposure and its relationship with respiratory disease in Africa.

Recent findings

African studies on this topic are limited, and generally focus on respiratory infections. Most evidence emerge from models based on the Global Burden of Disease data, and from limited individual epidemiological studies across the continent. More than 80% of the African population is exposed to household air pollution. Women and children continue to bear the substantial burden of exposure. Evidence from limited exposure-response studies strongly points to household air pollution being the major driver of acute and chronic respiratory diseases on the continent.

Summary

Respiratory infections, particularly in children, and other chronic respiratory diseases, are strongly attributable to household air pollution. Elimination of such exposures through interventions such as cleaner fuels and preferably, electricity, is critical to improving respiratory health on the continent.

Keywords: Africa, children and women, cooking fuels, household air pollution, respiratory diseases

INTRODUCTION

Household air pollution (HAP) is a major risk factor for respiratory health outcomes in low- and middle-income countries (LMICs) generally, and in Africa in particular [1,2]. According to the World Health Organization (WHO), approximately 3.2 million deaths were attributable to exposure to HAP in 2020 [3]. Among these deaths, about one-fifth were due to lower respiratory infections and chronic obstructive pulmonary disease (COPD) respectively, whereas 6% resulted from lung cancer [3,4].

The major source of HAP, especially in low socio-economic homes in LMICs, is the combustion and emissions from solid fuels such as wood, crop waste, charcoal, and dung [5]. According to the 2022 Energy Progress Report from the International Energy Agency in partnership with the United Nations, World Bank and WHO, 2.1 billion people still cook using solid fuels [5]. Projections indicate that by 2030, 31% of the global population, including over a billion people in sub-Saharan Africa (SSA) will still rely on polluting fuels [6]. This widespread reliance on solid fuels raises concerns about whether Sustainable Development Goal 7, which aims to ensure access to affordable, reliable, sustainable, and modern energy for all, will be fulfilled by 2030.

The sources of HAP emit smoke that contains a range of pollutants, including particulate matter, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), carbon dioxide (CO2), heavy metals and volatile organic compounds (VOCs) [7]. Exposure to these pollutants triggers several acute responses with pulmonary consequences. For instance, they can impair the airways, induce acute neutrophilia and lymphocytosis, activate redox-sensitive signalling pathways in pulmonary cells, and initiate oxidative stress [8–10]. Some pollutants, such as SO2, are water soluble and absorbed in the upper respiratory tract, while the less soluble components, such as O3 and NO2, can penetrate deeper into the distal airways and gas exchange regions. Fine particles, such as PM2.5, may reach the lower respiratory tract (LRT). When the LRT is exposed to fine particles, leukocytes and epithelial cells release cytokines and chemokines that trigger inflammation, activate fibroblasts involved in tissue remodelling, and increase the secretion of signalling molecules like Ca2+. Over time, these effects can contribute to the development of serious respiratory diseases, including asthma, lower respiratory infections, lung cancer, and COPD [10].

Systematic reviews, meta-analytic studies and examination of the Global Burden of Disease have provided repeated evidence for the risks of biomass fuel use for adverse health outcomes. A meta-analysis of 116 studies convincingly showed that gas use as an energy source, when compared to biomass use, significantly lowered the risk of a range of respiratory outcomes, and transitioning to electricity from gas improved outcomes for pneumonia and COPD, globally [11▪▪]. The analysis of the Global Burden of Disease data of 2021 provides evidence of globally declining risk attributable to HAP over the period 1990 to 2021, due to reduced use of biomass fuels [12▪▪], however, the risk in Africa remains high.

African countries face a rise in respiratory diseases and accounts for more than half of the world's unelectrified population and nearly a quarter of people without access to clean cooking fuels [13]. Women and children bear a disproportionate burden of exposure to HAP due to gender-based domestic roles [14–16]. 

Box 1.

Box 1

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no caption available

EXPOSURE TO HOUSEHOLD AIR POLLUTION

HAP is caused by emissions during the combustion of solid and fossil fuels, including wood, coal, crop residues, cow dung, kerosene, etc. as energy sources for cooking and heating in households [3,17]. Because of the varied constituents of HAP pollutants, careful characterizing of HAP exposure provides a better understanding of its impacts on health. In epidemiological studies, HAP has been characterized by reporting the source of pollution through the use of questionnaires which help to untangle the complex use of fuel sources and its interaction with other household factors [17–21]. More precise exposure characterization includes measuring pollutants and chemical speciation of emissions [17,22]. These objective methods of quantifying HAP in epidemiological studies become useful in determining the exposure-response relationships [18].

SSA is the only region in the world where HAP has not significantly decreased (Fig. 1) [17,23]. Approximately 80% of the population in SSA was exposed to HAP in 2020, although in some countries this is as low as 6% (Fig. 2) [17,18]. This exposure burden is experienced particularly by children and women because of the latter's household tasks such as cooking and child-caring [24]. The risk ranking of HAP between 1990 and 2019 for children of 9 years and younger has not changed despite an overall decline across other age groups [25].

FIGURE 1.

FIGURE 1

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Changes in population exposure in different regions of the world exposed to household air pollution from solid cooking fuel (reproduced from Health Effects Institute. 2024. State of Global Air Report 2024. Special Report. Boston, MA: Health Effects Institute).

FIGURE 2.

FIGURE 2

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Percentage of the population using solid fuels for cooking in countries across Africa (reproduced from Health Effects Institute. 2022. State of Air Quality and Health Impacts in Africa – a report from the State of Global Air Initiative. Boston, MA: Health Effects Institute).

Particulate matter (PM) concentrations produced by biomass fuel combustion during cooking and heating can exceed the WHO standard for indoor air PM by orders of magnitude, reaching more than 3000 ug/m3[26,27]. Interventions employed to address exposure to high HAP such as substitution of improved and better ventilated cook stoves have not been able to decrease the PM concentrations significantly. Elimination of biomass as an energy source is the intervention of choice [23,26]. This transition to cleaner fuels such as electricity and gas is slow across the continent [23].

RESPIRATORY HEALTH AMONG AT-RISK SUB-POPULATIONS

Respiratory diseases such as respiratory tract infections, tuberculosis (TB), asthma, COPD, and lung cancer remain a major public health issue in Africa [25]

In 2021, the incidence rate of respiratory infections in children under five in Africa was 7642 per 100 000, which is much higher than the average global incidence rates of 5941 per 100 000 for the same age group [4]. Studies using 2014 to 2020 demographic health survey datasets of 25 African countries found an average prevalence of respiratory illnesses to be 4.6% (ranging from 1% in Cameroon to 9.8% in Uganda) in the under 5 age group children [28▪▪,29]. The prevalence of childhood pneumonia varied in East African countries with pooled country prevalence across multiple studies ranging from 22% to 64.3% [30].

Pulmonary tuberculosis control and eradication in Africa is a monumental task with national tuberculosis prevalence surveys across 12 African countries indicating that about 14% (range 11–21%) of individuals had a positive TB symptom screen and/or an abnormal chest radiograph [31–33].

Although globally, chronic respiratory diseases showed an age standardized decline from 1990 until 2019, the mortality rate and disability-adjusted life years (DALYs) remained at high levels in SSA, ranging from 27.9 to 56.9 deaths and 831 to 1505 DALYs per 100 000 population, across the various SSA countries [34▪▪]. The prevalence of asthma among urban African children exceeds 20% in some parts of the continent [35–37], significantly higher than the global average of 9.1% [38].

In 2019, the worldwide prevalence of COPD in the 30–79 year age group, was estimated to be 10.3% (391.9 million people), with approximately 29.6 million Africans affected [39]. Prevalence varied across the African continent: as low as 2% in Uganda, ranging from 4% to 25% across South Africa, Nigeria, Malawi, and Cape Verde, and 17.5% in Tanzania [40–42], with one study reporting a pooled prevalence of chronic airflow obstruction of 8% in SSA [43]. The global burden of COPD is projected to rise by 23% by 2050, with higher increases in LMICs and among women.

HOUSEHOLD AIR POLLUTION EXPOSURE RELATED RESPIRATORY OUTCOMES

The evidence of HAP association with different respiratory outcomes has been well established globally [1,34▪▪,44,45], as well as in low and middle-income countries [46▪▪]. A meta-analysis from studies across 123 countries globally showed a significantly increased relative risk (RR) of HAP with asthma [RR = 1.2, 95% confidence interval (CI) 1.1–1.4], chronic obstructive pulmonary disease (1.7, 1.5–1·9), acute respiratory infection in adults (1.5, 1.2–1.9) and children (1.4, 1.3–1.5), lung cancer (1.7, 1.4–2.0), and tuberculosis (1.3, 1.1–1.5) and respiratory mortality (1.2, 1.18–1.20) [1].

Exposure-outcome studies within African countries have either tended toward cross-sectional studies of modest sample sizes or have made use of large national demographic and health surveys using interview-based proxy measures for both exposure and outcome [47,48,49▪,50,51▪]. However, using the GBD estimates, household air pollution from solid fuels remains the highest ranked risk factor for chronic respiratory diseases for the majority of SSA [34▪▪]

Recent data confirmed associations between biomass fuels and exacerbations of obstructive lung diseases such as asthma and COPD [2,52]. Acute respiratory infections, particularly lower respiratory tract infections, remain an important contributor to the overall burden of disease, particularly among children on the African continent [53]. Against this context, African studies, in recent years have tended to focus on attempting to understand whether environmental pollution increases the risk for this key outcome.

Respiratory infections and symptoms

Based on the 2019 Global Burden of Disease studies, household PM2.5 pollution was associated with varying age-standardized DALYs of lower respiratory tract infections across African regions, with a low estimate in North Africa and Western Asia of 107.04 (62.95–162.17), compared to SSA, ranging from a low of 352.12 (196.38–554.55) in the southern sub-region to a high of 1589.51 (1068.1–2245.57) in the western sub-region [45]. There has been an annual decline in estimates of approximately 4% per year since 1990, attributed to the reduction in HAP [45].

Despite this decline, epidemiological studies from African countries have shown increased estimates of risk. Cooking using one or more biomass fuels [adjusted odds ratio (aOR): 1.44, 95% CI: 1.21, 1.92] such as wood (aOR: 1.10, 95% CI: 0.79, 1.53), animal dung (aOR: 1.54, 95% CI: 1.02, 2.33), and charcoal (aOR: 4.35, 95% CI: 1.63, 11.6) was associated with childhood and adult acute respiratory infection in African countries when compared to cooking with clean fuel, including electricity [22,54,55]. Significantly reduced risk of childhood lower acute respiratory infection was seen in households with improved cookstoves when compared to traditional cookstoves (aOR: 0.43, 95% CI: 0.28, 0.67) [55].

The range of studies that analysed data collected through national Demographic and Health Surveys (DHS) in SSA countries showed that various markers of poor household air quality, such as solid or unclean fuel type use, resulted in an increased risk in childhood acute respiratory infections, with adjusted odds ratios ranging from 1.36 (95% CI: 1.11–1.66) in Uganda [47] to 3.47 (95% CI, 1.31–9.21) in Tanzania [50], while a report using the Ethiopian DHS data showed that biomass fuel use was associated with spatial variations in acute respiratory infections in childhood [51▪]. These findings were replicated in West Africa but were not statistically significant: Ivory Coast: aOR: 1.29 (95% CI: 0.72–2.30), Senegal: aOR: 1.39 (95% CI: 0.94–2.05) and Togo: aOR: 1.15 (95% CI: 0.67–1.95) [48]. The attributable fraction of polluting fuels for acute respiratory infections, across 25 countries, including over 250 000 children under 5 years of age, was 16% [28▪▪].

Several systematic reviews with meta-analyses have shown pooled estimates of increased risk of pneumonia in children under the age of five from exposure to HAP broadly or other specific markers of poor indoor air (fuel type use etc.), with odds ratios ranging from 2.6 (95% CI: 2.05–3.3) and 2.5 (95% CI: 1.7–3.7 in Ethiopia to 1.53 (95% CI: 1.3–1.8) across the studies in East Africa [30,56,57].

Studies which have attempted to objectively measure pollutants to describe HAP have described increased pollutant-related dose-response risks. In one Kenyan study, the risk of having more than five episodes of childhood acute respiratory infection increased 10-fold (RR = 10, 98% CI 3.3 to 30) when exposed to PM of more than 50 μg/m3[58]. In another Kenyan study, 12-month cumulative lagged PM2.5 exposure showed elevated risk for childhood acute infection in the four to 12 months prior, with clear dose-response relationships (aOR: 1.02, 95% CI: 1.01–1.04) [59].

The Ghana Randomized Air Pollution and Health Study (GRAPHS) investigated antenatal and postnatal exposure to carbon monoxide (CO) and its risk for pneumonia. CO exposure during 34–39 weeks’ gestation was positively associated with severe pneumonia risk in the first year of life. Each parts per million (ppm) increase in antenatal CO exposure was associated with an increased risk for pneumonia (RR = 1.10; 95% CI, 1.04–1.16) and severe pneumonia (RR = 1.15; 95% CI, 1.03–1.28) in the first year of life. An increased risk (RR = 1.06; 95% CI, 0.99–1.13) was also seen for postnatal CO exposure [60▪,61].

Asthma and lung function

Unlike respiratory infection outcomes, African studies of obstructive airway diseases in the period under review, were limited. Among Kenyan school children selected from an informal and formal community respectively, the prevalence of reported wheeze was greater in the informal community (9.5% vs. 6.4%, P < 0.007) with higher indoor PM, compared to the formal communities, but no significant increase in estimated per unit increase with PM was noted. Doctor-diagnosed asthma was higher in the formal community. Pollution-related lung function did not vary between communities [62▪].

Asthma has been significantly associated with the use of crop residues (aOR: 3.81, 95% CI: 1.05, 13.8) and wood (aOR: 4.95, 95% CI: 2.10, 11.7) for cooking compared to those using cleaner fuels in Ethiopia [63]. In South Africa, asthma symptom scores were positively associated with lagged indoor sources of PM2.5 concentrations [lag day 1 (aOR: 1.02; 95% CI: 1.00, 1.04), lag day 4 (aOR: 1.03; 95% CI: 1.02, 1.05), and 5-day average lagged of PM2.5 (aOR: 1.05; 95% CI: 1.01, 1.08)] (submitted paper: Buthelezi et al., unpublished data).

Among a sample of Congolese women, wood (aOR: 2.6, 95% CI 1.7; 5.9) and charcoal users (aOR: 2.9, 95% CI 1.4; 10.7), compared to electricity users, were at risk of developing airflow obstruction. Lung function parameters were significantly lower across wood and charcoal users than electricity users [64].

Among low and middle-income countries in the Prospective Urban and Rural Epidemiology (PURE) study, the use of solid fuel in comparison with clean fuels was associated with lower FEV1 of −17 : 5 ml (95% CI: −32 : 7, −2 : 3) and FVC of −14 : 4 ml (95% CI: −32 : 0, 3.2). However, for SSA countries within PURE (South Africa/Tanzania/Zimbabwe), the differences in FEV1 [−0.8 ml (−65.3, 63.7)] and FVC [−16.3 (−85.7, 53.1)] were not statistically significant [46▪▪].

An interesting advance in lung function assessment has been the use of impulse oscillometry among children exposed to HAP, with studies reporting findings from Ghana (the previously described GRAPHS) and Nigeria. Among 2-year-old children in Nigeria, postnatal PM2.5 exposures were associated with higher airway reactance, suggesting poorer lung function [65]. Similarly, 4-year-old children exposed to open-fire stoves showed poorer lung function compared to those using improved biomass stoves and liquid petroleum gas stoves [66▪▪].

Interstitial lung diseases

“Domestically acquired particulate lung disease” (hut lung) was first coined by Gold and colleagues in 2000 when presenting a case of an elderly woman presenting with features typical of pneumoconiosis with no history of occupational exposures, but a long history of indoor wood burning [67]. There have been limited epidemiological studies investigating this outcome, and since then only a few further case studies have been reported, with two of these among African emigrants [68,69]. Although likely to be a prevalent condition among households exposed to solid biomass fuels, epidemiological investigation among poorer communities in Africa, where easy access to radiography for diagnosing interstitial lung disease is challenging, the extent of “hut lung” may not be fully understood.

The varied estimates of risk for different outcomes, using different measures of exposure in different sub-populations in African countries, are presented in Fig. 3. The range of exposure/outcome measures limits direct comparisons across studies but provides a sense of the risk experienced by those exposed to HAP in Africa (Fig. 3).

FIGURE 3.

FIGURE 3

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Forest plot of studies on household air pollution and respiratory health outcomes stratified by respiratory outcomes.

CONCLUSION

HAP-related respiratory disorders may be on the decline globally as a result of reduced use of biomass fuels. This trend may not be typical for African countries generally because of the ongoing dependence on polluting fuels. While analysis of large datasets, pooled estimates from meta-analysis or modelling approaches such as the Global Burden of Disease suggests a high prevalence of HAP-related adverse respiratory outcomes in Africa, these studies maybe under-estimating the true burden because of the general lack of good exposure data and health surveillance data, or of large epidemiological studies on the continent.

However, the evidence for a causal relationship from global estimates is without doubt, therefore interventions that address elimination or a significant reduction of exposure is key to reduce the burden of respiratory diseases in Africa. Women and children in SSA bear the highest burden of exposure to HAP influencing maternal and child mortality and morbidity rates. The costs of the burden of HAP-related respiratory disorders to the health systems within a country is likely to outweigh investments in cleaner sources of energy on the continent.

Acknowledgements

None.

Financial support and sponsorship

None.

Conflicts of interest

There are no conflicts of interest.

REFERENCES AND RECOMMENDED READING

Papers of particular interest, published within the annual period of review, have been highlighted as:

  • ▪ of special interest

  • ▪▪ of outstanding interest

REFERENCES

  • 1.Lee KK, Bing R, Kiang J, et al. Adverse health effects associated with household air pollution: a systematic review, meta-analysis, and burden estimation study. Lancet Global Health 2020; 8:e1427–e1434. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Pathak U, Gupta NC, Suri JC. Risk of COPD due to indoor air pollution from biomass cooking fuel: a systematic review and meta-analysis. Int J Environ Health Res 2020; 30:75–88. [DOI] [PubMed] [Google Scholar]
  • 3. WHO. Household air pollution. 2023. Available at: https://www.who.int/news-room/fact-sheets/detail/household-air-pollution-and-health [Accessed 5 September 2024]. [Google Scholar]
  • 4.Bender RG, Sirota SB, Swetschinski LR, et al. Global, regional, and national incidence and mortality burden of non-COVID-19 lower respiratory infections and aetiologies, 1990–2021: a systematic analysis from the Global Burden of Disease Study 2021. Lancet Infect Dis 2024; 24:974–1002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. IEA I, UNSD, World Bank, WHO Tracking SDG 7: The energy progress report. 2022. Available at: https://trackingsdg7.esmap.org/downloads [Accessed 5 September 2024]. [Google Scholar]
  • 6.Stoner O, Lewis J, Martínez IL, et al. Household cooking fuel estimates at global and country level for 1990 to 2030. Nat Commun 2021; 12:5793. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. USEPA. Introduction to indoor air quality. 2024. Available at: https://www.epa.gov/indoor-air-quality-iaq/introduction-indoor-air-quality [Accessed 5 September 2024]. [Google Scholar]
  • 8.Glencross DA, Ho TR, Camina N, et al. Air pollution and its effects on the immune system. Free Rad Biol Med 2020; 151:56–68. [DOI] [PubMed] [Google Scholar]
  • 9.Mudway IS, Kelly FJ, Holgate ST. Oxidative stress in air pollution research. Free Radic Biol Med 2020; 151:2–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Al-Rekabi Z, Dondi C, Faruqui N, et al. Uncovering the cytotoxic effects of air pollution with multimodal imaging of in vitro respiratory models. Roy Soc Open Sci 2023; 10:221426. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11▪▪.Puzzolo E, Fleeman N, Lorenzetti F, et al. Estimated health effects from domestic use of gaseous fuels for cooking and heating in high-income, middle-income, and low-income countries: a systematic review and meta-analyses. Lancet Respir Med 2024; 12:281–293. [DOI] [PubMed] [Google Scholar]; Performing a systematic review and meta-analysis of 116 studies, this manuscript provides strong evidence for the adverse respiratory effects of polluting fuels, and varying risk across dirty fuels, gas and electricity. Comparisons across high-, middle- and low-income countries highlights the burden faced by African countries.
  • 12▪▪.Brauer M, Roth GA, Aravkin AY, et al. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet 2024; 403:2162–2203. [DOI] [PMC free article] [PubMed] [Google Scholar]; Using the powerful tools available to analyse the Global Burden of Disease data, this study shows the declining global risk for biomass usage, but at the same time provides evidence for slower rates of decline in Africa, and the high burden faced in African countries, particularly sub-Saharan Africa.
  • 13.National Institute for Health and Care Research (NIHR). CLEAN-Air Africa: addressing the disease burden from household air pollution. UK: National Institute for Health and Care Research; 2024. [Google Scholar]
  • 14.Gakidou E, Afshin A. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet 2017; 390:1345–1422. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Soriano JB, Kendrick PJ, Paulson KR. Prevalence and attributable health burden of chronic respiratory diseases, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet Respir Med 2020; 8:585–596. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Dai X, Dharmage SC, Lodge CJ. The relationship of early-life household air pollution with childhood asthma and lung function. Eur Respir Rev 2022; 31:220020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Health Effects Institute. State of air quality and health impacts in Africa – a report from the State of Global Air Initiative. Boston, MA: Health Effects Institute; 2022. [Google Scholar]
  • 18.HEI. Health effects institute. state of global air report 2024. Special report. Boston, MA: Health Effects Institute; 2024. [Google Scholar]
  • 19.Lam NL, Goel V, Blasdel M, et al. Reduction potentials for particulate emissions from household energy in India. Environ Res Lett 2023; 18:054009. [Google Scholar]
  • 20.Orina F, Amukoye E, Bowyer C, et al. Household carbon monoxide (CO) concentrations in a large African city: an unquantified public health burden? Environ Pollut 2024; 351:124054. [DOI] [PubMed] [Google Scholar]
  • 21.Zhu K, Kawyn MN, Kordas K, et al. Assessing exposure to household air pollution in children under five: a scoping review. Environ Pollut 2022; 311:119917. [DOI] [PubMed] [Google Scholar]
  • 22.Addisu A, Getahun T, Deti M, et al. Association of acute respiratory infections with indoor air pollution from biomass fuel exposure among under-five children in Jimma Town, Southwestern Ethiopia. J Environ Public Health 2021. 7112548. 10.1155/2021/7112548 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. IEA, IRENA, UNSD, World Bank, WHO. Tracking SDG 7: the energy progress report. World Bank, Washington DC. 2024. Available at: https://trackingsdg7.esmap.org/downloads [Accessed 5 September 2024]. [Google Scholar]
  • 24.Okello G, Devereux G, Semple S. Women and girls in resource poor countries experience much greater exposure to household air pollutants than men: results from Uganda and Ethiopia. Environ Int 2018; 119:429–437. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.GBD 2019 Chronic Respiratory Diseases Collaborators. Global burden of chronic respiratory diseases and risk factors, 1990–2019: an update from the Global Burden of Disease Study 2019. eClinicalMedicine 2023; 59:101936. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Sharma D, Jain S. Impact of intervention of biomass cookstove technologies and kitchen characteristics on indoor air quality and human exposure in rural settings of India. Environ Int 2019; 123:240–255. [DOI] [PubMed] [Google Scholar]
  • 27. World Health Organization. WHO global air quality guidelines: particulate matter (PM2. 5 and PM10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide. World Health Organization; 2021. [PubMed] [Google Scholar]
  • 28▪▪.Ahmed KY, Dadi AF, Kibret GD, et al. Population modifiable risk factors associated with under-5 acute respiratory tract infections and diarrhoea in 25 countries in sub-Saharan Africa (2014–2021): an analysis of data from demographic and health surveys. eClinicalMedicine 2024; 68:102444. [DOI] [PMC free article] [PubMed] [Google Scholar]; Using the data from the national Demographic Health Surveys over seven years (2014–2021), in 25 African countries, including over 250 000 children in the analyses, this represents an extremely comprehensive assessment of the risk factors for the respiratory health of children under five in sub-Saharan Africa. Almost 16% of acute respiratory infections were attributable to polluting fuels.
  • 29.Uttajug A, Ueda K, Seposo X, Francis MF. Association between extreme rainfall and acute respiratory infection among children under-5 years in sub-Saharan Africa: an analysis of Demographic and Health Survey data, 2006–2020. BMJ Open 2023; 13:e071874. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Beletew B, Bimerew M, Mengesha A, et al. Prevalence of pneumonia and its associated factors among under-five children in East Africa: a systematic review and meta-analysis. BMC Pediatr 2020; 20:254. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Law I, Floyd K. National tuberculosis prevalence surveys in Africa, 2008–2016: an overview of results and lessons learned. Trop Med Int Health 2020; 25:1308–1327. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Atkins S, Heimo L, Carter DJ, et al. The socioeconomic impact of tuberculosis on children and adolescents: a scoping review and conceptual framework. BMC Public Health 2022; 22:2153. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33. World Health Organization. Fourth WHO consultation on the translation of tuberculosis research into global policy guidelines: meeting report, 2024. World Health Organization; 2024. [Google Scholar]
  • 34▪▪.Momtazmanesh S, Moghaddam SS, Ghamari SH, et al. Global burden of chronic respiratory diseases and risk factors, 1990–2019: an update from the Global Burden of Disease Study 2019. EClinicalMedicine 2023; 59:101936. [DOI] [PMC free article] [PubMed] [Google Scholar]; This study, using the Global Burden of Disease 2019 data provides the most updated estimates of respiratory disease burden globally and in Africa. In addition, it provides evidence that while declines are seen in disease burden globally, this is less so for regions in Africa, and that household air pollution is the leading risk factor for respiratory outcomes for most in sub-Saharan Africa.
  • 35.Mphahlele R, Lesosky M, Masekela R. Prevalence, severity and risk factors for asthma in school-going adolescents in KwaZulu Natal, South Africa. BMJ Open Respir Res 2023; 10:e001498. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Navuluri N, Lagat D, Egger JR, et al. Asthma, airflow obstruction, and eosinophilic airway inflammation prevalence in Western Kenya: a population-based cross-sectional study. Int J Public Health 2023; 68:1606030. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Oluwole O, Arinola GO, Huo D, Olopade CO. Household biomass fuel use, asthma symptoms severity, and asthma underdiagnosis in rural schoolchildren in Nigeria: a cross-sectional observational study. BMC Pulm Med 2017; 17:3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Rutter C, Silverwood R, Pérez Fernández V, et al. The global burden of asthma. Int J Tuberc Lung Dis 2022; 26:20–23. [PubMed] [Google Scholar]
  • 39.Adeloye D, Song P, Zhu Y, et al. Global, regional, and national prevalence of, and risk factors for, chronic obstructive pulmonary disease (COPD) in 2019: a systematic review and modelling analysis. Lancet Respir Med 2022; 10:447–458. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Magitta NF, Madas SJ, Apte KK, et al. Prevalence and characteristics of COPD among residents in an urban informal settlement in Dar es Salaam, Tanzania. 2019; PREPRINT (Version 1). Available at: Research Square 10.21203/rs.2.15525/v1. [DOI] [Google Scholar]
  • 41.North CM, Kakuhikire B, Vořechovská D. Prevalence and correlates of chronic obstructive pulmonary disease and chronic respiratory symptoms in rural southwestern Uganda: a cross-sectional, population-based study. J Global Health 2019; 9:010434. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Rossaki FM, Hurst JR, van Gemert F, et al. Strategies for the prevention, diagnosis and treatment of COPD in low-and middle-income countries: the importance of primary care. Expert Rev Respir Med 2021; 15:1563–1577. [DOI] [PubMed] [Google Scholar]
  • 43.Amaral AF, Patel J, Kato BS, et al. Airflow obstruction and use of solid fuels for cooking or heating. BOLD (Burden of Obstructive Lung Disease) results. Am J Respir Crit Care Med 2018; 197:595–610. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Nassikas NJ, McCormack MC, Ewart G, et al. Indoor air sources of outdoor air pollution: health consequences, policy, and recommendations: an official American Thoracic Society Workshop Report. Ann Am Thorac Soc 2024; 21:365–376. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Hu J, Zhou R, Ding R, et al. Effect of PM2.5 air pollution on the global burden of lower respiratory infections, 1990–2019: A systematic analysis from the Global Burden of Disease Study 2019. J Hazard Mater 2023; 459:132215. [DOI] [PubMed] [Google Scholar]
  • 46▪▪.Wang Y, Duong M, Brauer M, et al. Household air pollution and adult lung function change, respiratory disease, and mortality across eleven low-and middle-income countries from the PURE study. Environ Health Perspect 2023; 131:047015. [DOI] [PMC free article] [PubMed] [Google Scholar]; This is one of the few studies that have conducted household pollutant-lung function dose response studies, with reports of data from Africa. Although showing a pollutant-related decline in lung function, these were not statistically significant for the African countries, but suggested that a risk may be present.
  • 47.Woolley KE, Bagambe T, Singh A, et al. Investigating the association between wood and charcoal domestic cooking, respiratory symptoms and acute respiratory infections among children aged under 5 years in uganda: a cross-sectional analysis of the 2016 demographic and health survey. Int J Environ Res Public Health 2020; 17:3974. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Daffe ML, Thiam S, Bah F, et al. Household level of air pollution and its impact on the occurrence of acute respiratory illness among children under five: secondary analysis of demographic and health survey in West Africa. BMC Public Health 2022; 22:2327. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49▪.Amadu I, Seidu AA, Mohammed A, et al. Assessing the combined effect of household cooking fuel and urbanicity on acute respiratory symptoms among under-five years in sub-Saharan Africa. Heliyon 2023; 9:e16546. [DOI] [PMC free article] [PubMed] [Google Scholar]; Although using crude outcome measures (cough and rapid breathing in the past two weeks) from national Demographic Health Surveys across 31 African countries, data from over 320 000 children provided evidence for the use of unclean fuels increasing the risk for these outcomes.
  • 50.Shayo FK, Bintabara D. Household air pollution from cooking fuels increases the risk of under-fives acute respiratory infection: evidence from population-based cross-sectional surveys in Tanzania. Ann Glob Health 2022; 88:46. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51▪.Tesfaye SH, Seboka BT, Sisay D. Spatial patterns and spatially-varying factors associated with childhood acute respiratory infection: data from Ethiopian demographic and health surveys (2005, 2011, and 2016). BMC Infect Dis 2023; 23:293. [DOI] [PMC free article] [PubMed] [Google Scholar]; Using data from the country's Demographic Health Surveys over three periods, with reported cough and rapid breathing as outcome measures, data from 31 500 children under the age of five, indicated an increased risk with biomass fuel use for cooking.
  • 52.Zhang X, Zhu X, Wang X, et al. Association of exposure to biomass fuels with occurrence of chronic obstructive pulmonary disease in rural Western China: a real-world nested case-control study. Int J Chron Obstruct Pulmon Dis 2023; 18:2207–2224. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Reiner RC, Welgan CA, Casey DC, et al. Identifying residual hotspots and mapping lower respiratory infection morbidity and mortality in African children from 2000 to 2017. Nat Microbiol 2019; 4:2310–2318. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Nsoh M, Mankollo BO, Ebongue M, et al. Acute respiratory infection related to air pollution in Bamenda, North West Region of Cameroon. Pan Afr Med J 2019; 32:99. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Adane MM, Alene GD, Mereta ST, Wanyonyi KL. Prevalence and risk factors of acute lower respiratory infection among children living in biomass fuel using households: a community-based cross-sectional study in Northwest Ethiopia. BMC Public Health 2020; 20:363. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Enyew HD, Mereta ST, Hailu AB. Biomass fuel use and acute respiratory infection among children younger than 5 years in Ethiopia: a systematic review and meta-analysis. Public Health 2021; 193:29–40. [DOI] [PubMed] [Google Scholar]
  • 57.Alamneh YM, Adane F. Magnitude and predictors of pneumonia among under-five children in Ethiopia: a systematic review and meta-analysis. J Environ Public Health 2020; 2020:1606783. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Mwitari J, Simiyu W, Kiogora S, et al. Relationship between household air pollution of particulate matter and acute respiratory infections among young children in central Kenya. IOSR J Environ Sci Toxicol Food Technol 2021; 15:54–69. [Google Scholar]
  • 59.Larson PS, Espira L, Glenn BE, et al. Long-term PM2.5 exposure is associated with symptoms of acute respiratory infections among children under five years of age in Kenya, 2014. Int J Environ Res Public Health 2022; 19:2525. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60▪.Kaali S, Jack DW, Mujtaba MN, et al. Identifying sensitive windows of prenatal household air pollution on birth weight and infant pneumonia risk to inform future interventions. Environ Int 2023; 178:108062. [DOI] [PMC free article] [PubMed] [Google Scholar]; This manuscript reports on the Ghanian birth cohort (GRAPHS), and is novel in its exposure characterization across pregnancy and shows the increased risk for pneumonia in infants following antenatal exposure to carbon monoxide.
  • 61.Kinney PL, Asante KP, Lee AG, et al. Prenatal and postnatal household air pollution exposures and pneumonia risk: evidence from the Ghana Randomized Air Pollution and Health Study. Chest 2021; 160:1634–1644. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62▪.Meme H, Amukoye E, Bowyer C, et al. Asthma symptoms, spirometry and air pollution exposure in schoolchildren in an informal settlement and an affluent area of Nairobi, Kenya. Thorax 2023; 78:1118–1125. [DOI] [PMC free article] [PubMed] [Google Scholar]; Over 2000 Kenyan children performed spirometry and personal sampling for particulate matter from informal and formal communities. Household air pollution from a variety of sources contributed to adverse respiratory outcomes, some independent of community.
  • 63.Abebe Y, Ali A, Kumie A, et al. Determinants of asthma in Ethiopia: age and sex matched case control study with special reference to household fuel exposure and housing characteristics. Asthma Res Pract 2021; 7:14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.Mbelambela EP, Muchanga SMJ, Villanueva AF, et al. Biomass energy, particulate matter (PM2.5), and the prevalence of chronic obstructive pulmonary disease (COPD) among Congolese women living near of a cement plant, in Kongo Central Province. Environ Sci Pollut Res 2020; 27:40706–40714. [DOI] [PubMed] [Google Scholar]
  • 65.Dutta A, Alaka M, Ibigbami T, et al. Impact of prenatal and postnatal household air pollution exposure on lung function of 2-year old Nigerian children by oscillometry. Sci Total Environ 2021; 755:143419. [DOI] [PubMed] [Google Scholar]
  • 66▪▪.Agyapong PD, Jack D, Kaali S, et al. Household air pollution and child lung function: the Ghana Randomized Air Pollution and Health Study. Am J Respir Crit Care Med 2024; 209:716–726. [DOI] [PMC free article] [PubMed] [Google Scholar]; Another of the GRAPHS reports, reporting on the use of novel techniques to describe small airways disease among children associated with different types of fuel use in Accra, Ghana in the antenatal period. The study found that children exposed to open-fire stoves had decreased lung function compared to those using improved biomass stoves and liquid petroleum gas stoves.
  • 67.Gold JA, Jagirdar J, Hay JG, et al. Hut lung. A domestically acquired particulate lung disease. Medicine (Baltimore) 2000; 79:310–317. [DOI] [PubMed] [Google Scholar]
  • 68.Saad A, Cao K, Rumbak M. Should hut lung be called domestically acquired particulate lung disease or domestically acquired pneumoconiosis? Respir Med Case Rep 2017; 23:74–76. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69.Klaaver M, Kars AH, Maat AP, den Bakker MA. Pseudomediastinal fibrosis caused by massive lymphadenopathy in domestically acquired particulate lung disease. Ann Diagn Pathol 2008; 12:118–121. [DOI] [PubMed] [Google Scholar]

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