Comparison of respiratory health impacts associated with wood and charcoal biomass fuels: A population-based analysis of 475,000 children from 30 low-and middle-income countries

International Journal of Environmental Research and Public Health, Volume 18, No. 17, Year 2021

Interpretation

Background: The World Health Organisation reported that 45% of global acute respiratory infection (ARI) deaths in children under five years are attributable to household air pollution, which has been recognised to be strongly associated with solid biomass fuel usage in domestic settings. The introduction of legislative restrictions for charcoal production or purchase can result in unintended consequences, such as reversion to more polluting biomass fuels such as wood; which may increase health and environmental harms. However, there remains a paucity of evidence concerning the relative health risks between wood and charcoal. This study compares the risk of respiratory symptoms, ARI, and severe ARI among children aged under five years living in wood and charcoal fuel households across 30 low-and middle-income countries. Methods: Data from children (N = 475,089) residing in wood or charcoal cooking households were extracted from multiple population-based Demographic and Health Survey databases (DHS) (N = 30 countries). Outcome measures were obtained from a maternal report of respiratory symptoms (cough, shortness of breath and fever) occurring in the two weeks prior to the survey date, generating a composite measure of ARI (cough and shortness of breath) and severe ARI (cough, shortness of breath and fever). Multivariable logistic regression analyses were implemented, with adjustment at individual, household, regional and country level for relevant demographic, social, and health-related confounding factors. Results: Increased odds ratios of fever (AOR: 1.07; 95% CI: 1.02–1.12) were observed among children living in wood cooking households compared to the use of charcoal. However, no association was observed with shortness of breath (AOR: 1.03; 95% CI: 0.96–1.10), cough (AOR: 0.99; 95% CI: 0.95–1.04), ARI (AOR: 1.03; 95% CI: 0.96–1.11) or severe ARI (AOR: 1.07; 95% CI: 0.99–1.17). Within rural areas, only shortness of breath was observed to be associated with wood cooking (AOR: 1.08; 95% CI: 1.01–1.15). However, an increased odds ratio of ARI was observed in Asian (AOR: 1.25; 95% CI: 1.04–1.51) and East African countries (AOR: 1.11; 95% CI: 1.01–1.22) only. Conclusion: Our population-based observational data indicates that in Asia and East Africa there is a greater risk of ARI among children aged under 5 years living in wood compared to charcoal cooking households. These findings have major implications for understanding the existing health impacts of wood-based biomass fuel usage and may be of relevance to settings where charcoal fuel restrictions are under consideration. A cross-sectional study across 30 LMIC countries was conducted using data obtained from the most recently available national population-based Demographic and Health Survey (DHS) [31], with LMIC status defined using the Development Assistance Committee (DAC) list 2020 [32]. Criteria for country inclusion included: (i) DHS survey data available from within the last 10 years, (ii) presence of wood and charcoal cooking fuel use (iii) presence of the outcome variables of interest (Appendix A: Figure A1). Each country followed the same two-stage stratified DHS sampling methodology with proportionate random sampling and standardised questionnaires with fieldwork supported by United States Agency for International Development (USAID). Eligible participants were identified through the residential household survey and included ever-married (has been married at least once in their life) women aged 15–49 years and men aged 15–59 years, who resided in the household the night before the survey [33]. Non-response households at the time of data collection and those with institutional living arrangements (e.g., boarding schools, police camps, army barracks, and hospitals) were excluded. All countries followed the standard core questionnaire from Phases VI, VII, and VIII of the DHS Program model, with country-specific modifications to non-core questions to reflect the population and health issues most relevant to that country. USAID standardises and provides training to government agencies and health authorities to complete surveys, with internal training and supervision of local data collectors and data entry. The questionnaire is translated into the main language(s) for each country and validated on approximately 100–200 households. Data for this current analysis were obtained from (i) household dataset containing situational and household characteristics; (ii) woman’s dataset containing maternal characteristics; (iii) children’s dataset containing health and individual characteristics. All primary data collection has ethical approval from the relevant government authority within each country, with all data being anonymised and aggregated for DHS online data archive [31]. The archive is publicly available and authorisation for data access has been gained for this study. The wealth index provided by DHS is calculated through principal component analysis, including cooking fuel as an indicator variable [34], therefore to prevent effect underestimation due to circularity, a modified wealth index was calculated [35] following the DHS provided guide [36] using SPSS [37], to calculate a modified wealth index. The new wealth index included indicator variables for the source of drinking water, house construction material (wall, roof and floor), toilet facility and assets. The assets included vary by country [37] and have been documented in Appendix B: Table A1. The wealth index was then ranked by household to provide tertiles of wealth. Maternal respondents were asked to report the presence of respiratory symptoms (shortness of breath, cough and fever) during the two weeks prior to the survey among all children under the age of five years living in their household. Respiratory symptoms were modelled as binary outcomes (yes, no), included short rapid breaths or difficulty breathing, cough, and fever. These respiratory symptoms were used to form the composite measures for ARI (both shortness of breath and cough [38]), and severe ARI (each of shortness of breath, cough, and fever [39,40,41]). Composite measures for ARI and severe ARI were then modelled as binary (yes, no) outcomes. Cooking fuel use was recorded from self-report for each household that undertook cooking activities. Fuels were categorised as “Cleaner fuels” (electricity, LPG, natural gas, biogas) and “Solid biomass fuels and kerosene” (kerosene, coal/lignite, charcoal, wood, straw/shrubs/grass, agricultural crop, animal dung). Wood and charcoal cooking household fuels were extracted and modelled as a binary variable. Individual child characteristics included child’s age (0–11, 12–23, 24–35, 36–48, 48–59 months), sex (male, female), mode of delivery (caesarean, vaginal), birth order (first, not first born), breastfeeding status (ever, never), vitamin A supplementation in the last 6 months (yes, no), iron supplementation (yes, no). Maternal characteristics included age of mother (15–24, 25–35, 36–49 years), mother’s highest attained educational level (none, primary, secondary/higher). Household characteristics included: number of household members (≤6, >6), household smoking (yes, no), cooking location (indoor, outdoor), and modified wealth index (lowest, low, middle, high, highest) [34]. Situational variables included geographical region of residence and area of residence (rural, urban). All co-variates were modelled as categorical variables. Data that were identified to be missing at random with less than 50% missing data [42,43] underwent multiple imputations of 50 iterations [44,45], at a country level, using the MICE package [46] in R studio [47]. Using R studio [47], descriptive statistics were tabulated with the number of cases (n), and percentage (%) for categorical outcome variables within the combined dataset. The association between the health outcome variables and exposure to HAP was assessed using a multivariable logistic regression using the Survey package [48] in R to account for the sampling strategy. Adjusted odds ratios (AOR) and 95% confidence intervals (95% CI) for each country were obtained and presented on a forest plot, with a summary result for the combined dataset. Additional exploratory analyses of a subset of countries were undertaken, incorporating breastfeeding, birthweight, and household smoking, which were missing or incomplete in a number of countries. Stratified analyses were undertaken to investigate the association in rural and urban settings, indoor and outdoor cooking status, geographic location and before or after 2014 (mid-time point of included studies), separately.

AI Digest

Study Justification:

The study aimed to investigate the respiratory health impacts associated with wood and charcoal biomass fuels in low- and middle-income countries. This research was justified by the World Health Organisation’s report that 45% of global acute respiratory infection deaths in children under five years old are caused by household air pollution, which is strongly linked to the use of solid biomass fuels. The study aimed to fill the gap in knowledge regarding the relative health risks between wood and charcoal fuels.

Highlights:

– The study analyzed data from 475,000 children living in wood or charcoal cooking households across 30 low- and middle-income countries.
– The study found that children living in wood cooking households had increased odds of fever compared to those using charcoal.
– However, there was no significant association between wood or charcoal fuel use and shortness of breath, cough, acute respiratory infection (ARI), or severe ARI.
– In rural areas, wood cooking was associated with an increased odds ratio of shortness of breath.
– Asian and East African countries showed an increased odds ratio of ARI among children living in wood cooking households.
– These findings have important implications for understanding the health impacts of wood-based biomass fuel usage, especially in regions considering charcoal fuel restrictions.

Recommendations:

Based on the study findings, the following recommendations can be made:

1. Implement targeted interventions to reduce the risk of fever among children living in wood cooking households.
2. Develop and promote cleaner cooking technologies and fuels to reduce the overall burden of respiratory symptoms and ARI in low- and middle-income countries.
3. Conduct further research to understand the specific factors contributing to the increased odds of ARI in Asian and East African countries.

Key Role Players:

To address the recommendations, the involvement of the following key role players is crucial:

1. Government agencies and health authorities: They can implement policies and regulations to promote cleaner cooking technologies and fuels.
2. Non-governmental organizations (NGOs) and international development agencies: They can provide support and resources for the implementation of interventions and programs.
3. Research institutions and scientists: They can conduct further studies to explore the underlying factors and develop effective interventions.

Cost Items for Planning Recommendations:

While the actual cost may vary depending on the specific context, the following cost items should be considered in planning the recommendations:

1. Research funding: To support further studies and data collection.
2. Development and distribution of cleaner cooking technologies: This includes the cost of research, design, production, and dissemination of improved cookstoves and fuels.
3. Training and capacity building: To educate communities and individuals on the proper use of cleaner cooking technologies and fuels.
4. Monitoring and evaluation: To assess the effectiveness and impact of interventions and programs.
5. Advocacy and awareness campaigns: To promote behavior change and raise awareness about the health risks associated with biomass fuels and the benefits of cleaner alternatives.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is relatively strong, but there are some areas for improvement. The study design is a cross-sectional study across 30 low- and middle-income countries, which provides a large sample size and diverse population. The data was obtained from national population-based Demographic and Health Survey databases, which adds to the reliability of the findings. The study used multivariable logistic regression analyses to adjust for confounding factors. However, the study is observational in nature, which limits the ability to establish causation. Additionally, the abstract does not provide information on potential limitations or biases in the study. To improve the evidence, future studies could consider conducting randomized controlled trials or longitudinal studies to establish causal relationships. It would also be beneficial to address potential limitations and biases in the study, such as selection bias or measurement error.

Abstract

A cross-sectional study across 30 LMIC countries was conducted using data obtained from the most recently available national population-based Demographic and Health Survey (DHS) [31], with LMIC status defined using the Development Assistance Committee (DAC) list 2020 [32]. Criteria for country inclusion included: (i) DHS survey data available from within the last 10 years, (ii) presence of wood and charcoal cooking fuel use (iii) presence of the outcome variables of interest (Appendix A: Figure A1). Each country followed the same two-stage stratified DHS sampling methodology with proportionate random sampling and standardised questionnaires with fieldwork supported by United States Agency for International Development (USAID). Eligible participants were identified through the residential household survey and included ever-married (has been married at least once in their life) women aged 15–49 years and men aged 15–59 years, who resided in the household the night before the survey [33]. Non-response households at the time of data collection and those with institutional living arrangements (e.g., boarding schools, police camps, army barracks, and hospitals) were excluded. All countries followed the standard core questionnaire from Phases VI, VII, and VIII of the DHS Program model, with country-specific modifications to non-core questions to reflect the population and health issues most relevant to that country. USAID standardises and provides training to government agencies and health authorities to complete surveys, with internal training and supervision of local data collectors and data entry. The questionnaire is translated into the main language(s) for each country and validated on approximately 100–200 households. Data for this current analysis were obtained from (i) household dataset containing situational and household characteristics; (ii) woman’s dataset containing maternal characteristics; (iii) children’s dataset containing health and individual characteristics. All primary data collection has ethical approval from the relevant government authority within each country, with all data being anonymised and aggregated for DHS online data archive [31]. The archive is publicly available and authorisation for data access has been gained for this study. The wealth index provided by DHS is calculated through principal component analysis, including cooking fuel as an indicator variable [34], therefore to prevent effect underestimation due to circularity, a modified wealth index was calculated [35] following the DHS provided guide [36] using SPSS [37], to calculate a modified wealth index. The new wealth index included indicator variables for the source of drinking water, house construction material (wall, roof and floor), toilet facility and assets. The assets included vary by country [37] and have been documented in Appendix B: Table A1. The wealth index was then ranked by household to provide tertiles of wealth. Maternal respondents were asked to report the presence of respiratory symptoms (shortness of breath, cough and fever) during the two weeks prior to the survey among all children under the age of five years living in their household. Respiratory symptoms were modelled as binary outcomes (yes, no), included short rapid breaths or difficulty breathing, cough, and fever. These respiratory symptoms were used to form the composite measures for ARI (both shortness of breath and cough [38]), and severe ARI (each of shortness of breath, cough, and fever [39,40,41]). Composite measures for ARI and severe ARI were then modelled as binary (yes, no) outcomes. Cooking fuel use was recorded from self-report for each household that undertook cooking activities. Fuels were categorised as “Cleaner fuels” (electricity, LPG, natural gas, biogas) and “Solid biomass fuels and kerosene” (kerosene, coal/lignite, charcoal, wood, straw/shrubs/grass, agricultural crop, animal dung). Wood and charcoal cooking household fuels were extracted and modelled as a binary variable. Individual child characteristics included child’s age (0–11, 12–23, 24–35, 36–48, 48–59 months), sex (male, female), mode of delivery (caesarean, vaginal), birth order (first, not first born), breastfeeding status (ever, never), vitamin A supplementation in the last 6 months (yes, no), iron supplementation (yes, no). Maternal characteristics included age of mother (15–24, 25–35, 36–49 years), mother’s highest attained educational level (none, primary, secondary/higher). Household characteristics included: number of household members (≤6, >6), household smoking (yes, no), cooking location (indoor, outdoor), and modified wealth index (lowest, low, middle, high, highest) [34]. Situational variables included geographical region of residence and area of residence (rural, urban). All co-variates were modelled as categorical variables. Data that were identified to be missing at random with less than 50% missing data [42,43] underwent multiple imputations of 50 iterations [44,45], at a country level, using the MICE package [46] in R studio [47]. Using R studio [47], descriptive statistics were tabulated with the number of cases (n), and percentage (%) for categorical outcome variables within the combined dataset. The association between the health outcome variables and exposure to HAP was assessed using a multivariable logistic regression using the Survey package [48] in R to account for the sampling strategy. Adjusted odds ratios (AOR) and 95% confidence intervals (95% CI) for each country were obtained and presented on a forest plot, with a summary result for the combined dataset. Additional exploratory analyses of a subset of countries were undertaken, incorporating breastfeeding, birthweight, and household smoking, which were missing or incomplete in a number of countries. Stratified analyses were undertaken to investigate the association in rural and urban settings, indoor and outdoor cooking status, geographic location and before or after 2014 (mid-time point of included studies), separately.

Materials

N/A

Innovations

Based on the provided description, here are some potential innovations that could improve access to maternal health:

1. Clean Cooking Solutions: Develop and promote cleaner cooking technologies that reduce household air pollution, such as improved cookstoves or clean fuels like LPG (liquefied petroleum gas) or biogas. These technologies can help reduce the respiratory health risks associated with wood and charcoal biomass fuels.

2. Education and Awareness Campaigns: Implement educational programs and awareness campaigns to educate communities about the health risks of using wood and charcoal fuels for cooking. This can help increase knowledge about alternative cooking options and promote behavior change towards cleaner fuels.

3. Policy Interventions: Advocate for policy interventions that promote the use of cleaner cooking technologies and discourage the use of wood and charcoal fuels. This can include regulations on the production and purchase of charcoal, as well as incentives or subsidies for cleaner cooking solutions.

4. Access to Affordable Clean Fuels: Improve access to affordable clean fuels, such as LPG or biogas, especially in low- and middle-income countries. This can be achieved through partnerships with governments, NGOs, and private sector organizations to establish distribution networks and reduce the cost of clean fuels.

5. Maternal Health Clinics: Integrate maternal health services with clean cooking interventions by providing information and resources on cleaner cooking technologies during antenatal and postnatal care visits. This can help ensure that pregnant women and new mothers are aware of the health risks and have access to alternative cooking options.

6. Research and Data Collection: Conduct further research and data collection on the health impacts of different cooking fuels, particularly in specific regions or communities. This can help inform targeted interventions and policies to improve maternal health outcomes.

It is important to note that these recommendations are based on the information provided and may need to be tailored to specific contexts and local needs.

AI Innovations Description

The study described in the provided text aims to compare the respiratory health impacts associated with wood and charcoal biomass fuels in low- and middle-income countries. The study analyzed data from 475,000 children living in wood or charcoal cooking households across 30 countries. The outcome measures included respiratory symptoms such as cough, shortness of breath, and fever, as well as acute respiratory infections (ARI) and severe ARI.

The study found that children living in wood cooking households had increased odds of fever compared to those using charcoal as fuel. However, there was no significant association between wood fuel use and shortness of breath, cough, ARI, or severe ARI. In rural areas, only shortness of breath was associated with wood cooking. Additionally, an increased odds ratio of ARI was observed in Asian and East African countries.

Based on these findings, the study suggests that there is a greater risk of ARI among children under 5 years old living in wood cooking households compared to charcoal cooking households in Asia and East Africa. These findings have important implications for understanding the health impacts of wood-based biomass fuel usage and may be relevant to settings where charcoal fuel restrictions are being considered.

In terms of recommendations for developing innovations to improve access to maternal health, it is important to consider the findings of this study. One possible recommendation could be to promote the use of cleaner fuels, such as electricity, LPG, natural gas, or biogas, in households where wood or charcoal is currently used for cooking. This could help reduce the respiratory health risks associated with solid biomass fuel usage. Additionally, efforts could be made to raise awareness about the health impacts of wood-based biomass fuel usage and provide education on alternative cooking methods and fuels.

Furthermore, it may be beneficial to explore and support initiatives that aim to improve access to cleaner cooking technologies and fuels in low- and middle-income countries. This could involve collaborations with local communities, governments, and international organizations to develop and implement sustainable solutions that address the specific needs and challenges of each region.

Overall, the findings of this study highlight the importance of addressing household air pollution and its impact on maternal and child health. By promoting the use of cleaner fuels and improving access to alternative cooking technologies, it is possible to reduce the respiratory health risks associated with solid biomass fuel usage and improve maternal health outcomes.

AI Innovations Methodology

The methodology used in this study involved conducting a cross-sectional analysis across 30 low- and middle-income countries (LMICs) using data obtained from national population-based Demographic and Health Surveys (DHS). The criteria for country inclusion included the availability of DHS survey data within the last 10 years, the presence of wood and charcoal cooking fuel use, and the presence of the outcome variables of interest.

The surveys followed a two-stage stratified sampling methodology with proportionate random sampling. Eligible participants were ever-married women aged 15-49 years and men aged 15-59 years who resided in the household the night before the survey. Non-response households and those with institutional living arrangements were excluded.

The surveys used standard questionnaires with country-specific modifications to reflect the population and health issues relevant to each country. The data collected included information on household characteristics, maternal characteristics, and individual child characteristics. The wealth index provided by DHS was used, and a modified wealth index was calculated to prevent circularity.

The outcome measures of interest were respiratory symptoms (shortness of breath, cough, and fever) reported by maternal respondents for children under the age of five years. These symptoms were used to form composite measures for acute respiratory infection (ARI) and severe ARI. Cooking fuel use was recorded from self-report, and wood and charcoal cooking households were modeled as a binary variable.

Multivariable logistic regression analyses were conducted to assess the association between health outcomes and exposure to household air pollution (HAP) from wood and charcoal cooking. The analyses were adjusted for relevant demographic, social, and health-related confounding factors at individual, household, regional, and country levels.

Descriptive statistics were tabulated, and adjusted odds ratios (AOR) and 95% confidence intervals (CI) were obtained for each country. Additional exploratory analyses were conducted to investigate associations in different settings and time periods.

Overall, this methodology allowed for a comprehensive analysis of the impact of wood and charcoal cooking fuels on respiratory health outcomes in children across multiple LMICs. The findings have important implications for understanding the health risks associated with different biomass fuel usage and can inform policies and interventions aimed at improving respiratory health in these settings.

Authors & Co-Authors

Statistics:

Citations: 6

Authors: 8

Identifiers:

DOI: 10.3390/ijerph18179305

ISSN: 16617827

Research Areas:

Environmental, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Social Determinants

Study Countries:

Multi-Countries

Study Design:

Case-Control Study, Cross Sectional Study, Exploratory Study, Grounded Theory

Study Approach:

Quantitative

Participants Gender:

Male & Female