Diagram-based Analysis of Causal Systems (DACS): elucidating inter-relationships between determinants of acute lower respiratory infections among children in sub-Saharan Africa

Multidimensional energy poverty and acute respiratory infection in children under 5 years of age: evidence from 22 low-income and middle-income countries

BACKGROUND

In low-income and middle-income countries (LMICs), energy poverty has predominantly been studied from the unidimensional perspective of indoor air pollution. Acute respiratory infection (ARI) in children under 5 years of age is the most important disease associated with indoor air pollution attributable to solid fuel use in LMICs. This study aimed to extend the existing knowledge on the association between energy poverty and ARI among children under 5 years of age in LMICs, by adopting a multidimensional perspective.

METHODS

Using Demographic and Health Surveys from 22 LMICs, data from 483 088 children were analysed (mean age 2.00 years (SD 1.41); 51.3% male). Energy poverty was measured using the Multidimensional Energy Poverty Index (MEPI) (range 0-1), which comprises five dimensions of essential energy services. Binary logistic regression models were conducted to study the association between MEPI and ARI, adjusting for child, maternal, household and environmental characteristics.

RESULTS

A 0.1 increase in MEPI score was associated with greater odds of ARI (aOR 1.05; 95% CI 1.04 to 1.07). Likewise, MEPI indicators using biomass for cooking (aOR 1.15; 95% CI 1.07 to 1.23) and lack of access to electricity (aOR 1.17; 95% CI 1.10 to 1.26), entertainment/education appliances (aOR 1.07; 95% CI 1.02 to 1.13) and household appliances (aOR 1.12; 95% CI 1.04 to 1.21) were associated with greater odds of ARI.

CONCLUSION

Multidimensional energy poverty was associated with greater odds of ARI in children under 5 years of age living in 22 LMICs. Hence, our findings justify the design and implementation of interventions that address energy poverty from a multidimensional perspective, integrating energy affordability and accessibility.

The effect of occupational exposure to welding fumes on trachea, bronchus and lung cancer: A systematic review and meta-analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury

BACKGROUND

The World Health Organization (WHO) and the International Labour Organization (ILO) are the producers of the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury (WHO/ILO Joint Estimates). Welding fumes have been classified as carcinogenic to humans (Group 1) by the WHO International Agency for Research on Cancer (IARC) in IARC Monograph 118; this assessment found sufficient evidence from studies in humans that welding fumes are a cause of lung cancer. In this article, we present a systematic review and meta-analysis of parameters for estimating the number of deaths and disability-adjusted life years from trachea, bronchus, and lung cancer attributable to occupational exposure to welding fumes, to inform the development of WHO/ILO Joint Estimates on this burden of disease (if considered feasible).

OBJECTIVES

We aimed to systematically review and meta-analyse estimates of the effect of any (or high) occupational exposure to welding fumes, compared with no (or low) occupational exposure to welding fumes, on trachea, bronchus, and lung cancer (three outcomes: prevalence, incidence, and mortality).

DATA SOURCES

We developed and published a protocol, applying the Navigation Guide as an organizing systematic review framework where feasible. We searched electronic databases for potentially relevant records from published and unpublished studies, including Medline, EMBASE, Web of Science, CENTRAL and CISDOC. We also searched grey literature databases, Internet search engines, and organizational websites; hand-searched reference lists of previous systematic reviews; and consulted additional experts.

STUDY ELIGIBILITY AND CRITERIA

We included working-age (≥15 years) workers in the formal and informal economy in any Member State of WHO and/or ILO but excluded children (<15 years) and unpaid domestic workers. We included randomized controlled trials, cohort studies, case-control studies, and other non-randomized intervention studies with an estimate of the effect of any (or high) occupational exposure to welding fumes, compared with occupational exposure to no (or low) welding fumes, on trachea, bronchus, and lung cancer (prevalence, incidence, and mortality).

STUDY APPRAISAL AND SYNTHESIS METHODS

At least two review authors independently screened titles and abstracts against the eligibility criteria at a first review stage and full texts of potentially eligible records at a second stage, followed by extraction of data from qualifying studies. If studies reported odds ratios, these were converted to risk ratios (RRs). We combined all RRs using random-effects meta-analysis. Two or more review authors assessed the risk of bias, quality of evidence, and strength of evidence, using the Navigation Guide tools and approaches adapted to this project. Subgroup (e.g., by WHO region and sex) and sensitivity analyses (e.g., studies judged to be of "high"/"probably high" risk of bias compared with "low"/"probably low" risk of bias) were conducted.

RESULTS

Forty-one records from 40 studies (29 case control studies and 11 cohort studies) met the inclusion criteria, comprising over 1,265,512 participants (≥22,761 females) in 21 countries in three WHO regions (Region of the Americas, European Region, and Western Pacific Region). The exposure and outcome were generally assessed by job title or self-report, and medical or administrative records, respectively. Across included studies, risk of bias was overall generally probably low/low, with risk judged high or probably high for several studies in the domains for misclassification bias and confounding. Our search identified no evidence on the outcome of having trachea, bronchus, and lung cancer (prevalence). Compared with no (or low) occupational exposure to welding fumes, any (or high) occupational exposure to welding fumes increased the risk of acquiring trachea, bronchus, and lung cancer (incidence) by an estimated 48 % (RR 1.48, 95 % confidence interval [CI] 1.29-1.70, 23 studies, 57,931 participants, I² 24 %; moderate quality of evidence). Compared with no (or low) occupational exposure to welding fumes, any (or high) occupational exposure to welding fumes increased the risk dying from trachea, bronchus, and lung cancer (mortality) by an estimated 27 % (RR 1.27, 95 % CI 1.04-1.56, 3 studies, 8,686 participants, I² 0 %; low quality of evidence). Our subgroup analyses found no evidence for difference by WHO region and sex. Sensitivity analyses supported the main analyses.

CONCLUSIONS

Overall, for incidence and mortality of trachea, bronchus, and lung cancer, we judged the existing body of evidence for human data as "sufficient evidence of harmfulness" and "limited evidence of harmfulness", respectively. Occupational exposure to welding fumes increased the risk of acquiring and dying from trachea, bronchus, and lung cancer. Producing estimates for the burden of trachea, bronchus, and lung cancer attributable to any (or high) occupational exposure to welding fumes appears evidence-based, and the pooled effect estimates presented in this systematic review could be used as input data for the WHO/ILO Joint Estimates. PROTOCOL IDENTIFIER: https://doi.org/10.1016/j.envint.2020.106089.

The effect of occupational exposure to welding fumes on trachea, bronchus and lung cancer: A protocol for a systematic review and meta-analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury

BACKGROUND

The World Health Organization (WHO) and the International Labour Organization (ILO) are developing joint estimates of the work-related burden of disease and injury (WHO/ILO Joint Estimates), with contributions from a large network of experts. Welding fumes have been classified as carcinogenic to humans (Group 1) by the International Agency for Research on Cancer (IARC); this assessment found sufficient evidence from studies in humans that welding fumes are a cause of lung cancer. In this article, we present the protocol for a systematic review of parameters for estimating the number of deaths and disability-adjusted life years from trachea, bronchus and lung cancer attributable to occupational exposure to welding fumes, to inform the development of the WHO/ILO Joint Estimates.

OBJECTIVES

We aim to systematically review and meta-analyse estimates of the effect of occupational exposure to welding fumes on trachea, bronchus and lung cancer, applying the Navigation Guide systematic review methodology as an organizing framework.

DATA SOURCES

We will search electronic bibliographic databases for potentially relevant records from published and unpublished studies, including Medline, EMBASE, Web of Science, and CISDOC. We will also search electronic grey literature databases, Internet search engines and organizational websites; hand search reference list of previous systematic reviews and included study records; and consult additional experts.

STUDY ELIGIBILITY AND CRITERIA

We will include working-age (≥15 years) workers in the formal and informal economy in any Member State of WHO and/or ILO but exclude children (<15 years) and unpaid domestic workers. The eligible risk factor will be occupational exposure to welding fumes, measured directly or indirectly (i.e., through proxy of relevant occupation, work task, job-exposure matrix, expert judgment or self-report). The eligible outcomes will be trachea, bronchus and lung cancer. We will include randomized controlled trials, cohort studies, case-control studies and other non-randomized intervention studies with an estimate of the relative effect of any occupational exposure to welding fumes on the prevalence of, incidence of or mortality from trachea, bronchus and lung cancer, compared with the theoretical minimum risk exposure level of no occupational exposure to welding fumes.

STUDY APPRAISAL AND SYNTHESIS METHODS

At least two review authors will independently screen titles and abstracts against the eligibility criteria at a first stage and full texts of potentially eligible records at a second stage, followed by extraction of data from qualifying studies. Two or more review authors will assess risk of bias and the quality of evidence, using the Navigation Guide tool or approach. If feasible, we will combine relative risks using meta-analysis. We will report results using the preferred reporting items for systematic reviews and meta-analyses guidelines (PRISMA).

Water, sanitation and hygiene risk factors for the transmission of cholera in a changing climate: using a systematic review to develop a causal process diagram

Cholera is a severe diarrhoeal disease affecting vulnerable communities. A long-term solution to cholera transmission is improved access to and uptake of water, sanitation and hygiene (WASH). Climate change threatens WASH. A systematic review and meta-analysis determined five overarching WASH factors incorporating 17 specific WASH factors associated with cholera transmission, focussing upon community cases. Eight WASH factors showed lower odds and six showed higher odds for cholera transmission. These results were combined with findings in the climate change and WASH literature, to propose a health impact pathway illustrating potential routes through which climate change dynamics (e.g. drought, flooding) impact on WASH and cholera transmission. A causal process diagram visualising links between climate change dynamics, WASH factors, and cholera transmission was developed. Climate change dynamics can potentially affect multiple WASH factors (e.g. drought-induced reductions in handwashing and rainwater use). Multiple climate change dynamics can influence WASH factors (e.g. flooding and sea-level rise affect piped water usage). The influence of climate change dynamics on WASH factors can be negative or positive for cholera transmission (e.g. drought could increase pathogen desiccation but reduce rainwater harvesting). Identifying risk pathways helps policymakers focus on cholera risk mitigation, now and in the future.

Household air pollution profiles associated with persistent childhood cough in urban Uganda

BACKGROUND

Most household air pollution (HAP) interventions in developing countries of sub-Saharan Africa have focused on a single source, such as replacing polluting cooking sources with cleaner burning cooking stoves. Such interventions, however, have resulted in insufficient reductions in HAP levels and respiratory health risks in children. In this study we determined how multiple HAP combustion sources and exposure-mitigation factors in the home environment influence child respiratory health alone and in combination.

METHODS

We carried out a case-control study to determine associations between multiple indicators of HAP and persistent cough among children (<15 years of age) seeking care at three primary-care clinics in Kampala, Uganda. HAP indicators included self-report of combustion sources inside the home (e.g., stove type, fuel type, and smoking); housing characteristics and cooking practices that mitigate HAP exposure (e.g., use of windows, location of cooking, location of children during cooking) and perceptions of neighborhood air quality. To explore joint associations between indicators of HAP, we applied a Bayesian clustering technique (Bayesian profile regression) to identify HAP indicator profiles most strongly associated with persistent cough in children.

RESULTS

Most HAP indicators demonstrated significant positive bivariate associations with persistent cough among children, including fuel-type (kerosene), the number of hours burning solid fuels, use of polluting fuels (kerosene or candles) for lighting the home, tobacco smoking indoors, cooking indoors, cooking with children indoors, lack of windows in the cooking area, and not opening windows while cooking. Bayesian cluster analysis revealed 11 clusters of HAP indicator profiles. Compared to a reference cluster that was representative of the underlying study population cough prevalence, three clusters with profiles characterized by highly adverse HAP indicators resulted in ORs of 1.72 (95% credible interval: 1.15, 2.60), 4.74 (2.88, 8.0), and 8.6 (3.9, 23.9). Conversely, at least two clusters of HAP indicator-profiles were protective compared to the reference cluster, despite the fact that these protective HAP indicator profiles used solid fuels for cooking in combination with an unimproved stove (cooking was performed predominantly outdoors in these protective clusters).

CONCLUSIONS

In addition to cooking fuel and type of cook stove, multiple HAP indicators were strongly associated with persistent cough in children. Bayesian profile regression revealed that the combination of HAP sources and HAP exposure-mitigating factors was driving risk of adverse cough associations in children, rather than any single HAP source at the home.

Dynamic modeling approaches to characterize the functioning of health systems: A systematic review of the literature

Universal Health Coverage (UHC) is one of the targets for the United Nations Sustainable Development Goal 3. The impetus for UHC has led to an increased demand for time-sensitive tools to enhance our knowledge of how health systems function and to evaluate impact of system interventions. We define the field of "health system modeling" (HSM) as an area of research where dynamic mathematical models can be designed in order to describe, predict, and quantitatively capture the functioning of health systems. HSM can be used to explore the dynamic relationships among different system components, including organizational design, financing and other resources (such as investments in resources and supply chain management systems) - what we call "inputs" - on access, coverage, and quality of care - what we call "outputs", toward improved health system "outcomes", namely increased levels and fairer distributions of population health and financial risk protection. We undertook a systematic review to identify the existing approaches used in HSM. We identified "systems thinking" - a conceptual and qualitative description of the critical interactions within a health system - as an important underlying precursor to HSM, and collated a critical collection of such articles. We then reviewed and categorized articles from two schools of thoughts: "system dynamics" (SD)" and "susceptible-infected-recovered-plus" (SIR+). SD emphasizes the notion of accumulations of stocks in the system, inflows and outflows, and causal feedback structure to predict intended and unintended consequences of policy interventions. The SIR + models link a typical disease transmission model with another that captures certain aspects of the system that impact the outcomes of the main model. These existing methods provide critical insights in informing the design of HSM, and provide a departure point to extend this research agenda. We highlight the opportunity to advance modeling methods to further understand the dynamics between health system inputs and outputs.

Towards a taxonomy of logic models in systematic reviews and health technology assessments: A priori, staged, and iterative approaches

The complexity associated with how interventions result-or fail to result-in outcomes and how context matters is increasingly recognised. Logic models provide an important tool for handling complexity, with contrasting uses in programme evaluation and evidence synthesis. To reconcile these, we developed an approach that combines the strengths of both traditions, propose a taxonomy of logic models, and provide guidance on how to choose between approaches and types of logic models in systematic reviews and health technology assessments (HTA). The taxonomy distinguishes 3 approaches (a priori, staged, and iterative) and 2 types (systems-based and process-orientated) of logic models. An a priori logic model is specified at the start of the systematic review/HTA and remains unchanged. With a staged logic model, the reviewer prespecifies several points, at which major data inputs require a subsequent version. An iterative logic model is continuously modified throughout the systematic review/HTA process. System-based logic models describe the system, in which the interaction between participants, intervention, and context takes place; process-orientated models display the causal pathways leading from the intervention to multiple outcomes. The proposed taxonomy of logic models offers an improved understanding of the advantages and limitations of logic models across the spectrum from a priori to fully iterative approaches. Choice of logic model should be informed by scope of evidence synthesis, presence/absence of clearly defined population, intervention, comparison, outcome (PICO) elements, and feasibility considerations. Applications across distinct interventions and methodological approaches will deliver good practice case studies and offer further insights on the choice and implementation of logic modelling approaches.

Systems science and systems thinking for public health: a systematic review of the field

OBJECTIVES

This paper reports on findings from a systematic review designed to investigate the state of systems science research in public health. The objectives were to: (1) explore how systems methodologies are being applied within public health and (2) identify fruitful areas of activity.

DESIGN

A systematic review was conducted from existing literature that draws on or uses systems science (in its various forms) and relates to key public health areas of action and concern, including tobacco, alcohol, obesity and the social determinants of health.

DATA ANALYSIS

117 articles were included in the review. An inductive qualitative content analysis was used for data extraction. The following were systematically extracted from the articles: approach, methodology, transparency, strengths and weaknesses. These were then organised according to theme (ie, commonalities between studies within each category), in order to provide an overview of the state of the field as a whole. The assessment of data quality was intrinsic to the goals of the review itself, and therefore, was carried out as part of the analysis.

RESULTS

4 categories of research were identified from the review, ranging from editorial and commentary pieces to complex system dynamic modelling. Our analysis of each of these categories of research highlighted areas of potential for systems science to strengthen public health efforts, while also revealing a number of limitations in the dynamic systems modelling being carried out in public health.

CONCLUSIONS

There is a great deal of interest in how the application of systems concepts and approach might aid public health. Our analysis suggests that soft systems modelling techniques are likely to be the most useful addition to public health, and align well with current debate around knowledge transfer and policy. However, the full range of systems methodologies is yet to be engaged with by public health researchers.

Cooking and season as risk factors for acute lower respiratory infections in African children: a cross-sectional multi-country analysis

Background

Acute lower respiratory infections (ALRI) are a leading cause of death among African children under five. A significant proportion of these are attributable to household air pollution from solid fuel use.

Methods

We assessed the relationship between cooking practices and ALRI in pooled datasets of Demographic and Health Surveys conducted between 2000 and 2011 in countries of sub-Saharan Africa. The impacts of main cooking fuel, cooking location and stove ventilation were examined in 18 (n = 56,437), 9 (n = 23,139) and 6 countries (n = 14,561) respectively. We used a causal diagram and multivariable logistic mixed models to assess the influence of covariates at individual, regional and national levels.

Results

Main cooking fuel had a statistically significant impact on ALRI risk (p<0.0001), with season acting as an effect modifier (p = 0.034). During the rainy season, relative to clean fuels, the odds of suffering from ALRI were raised for kerosene (OR 1.64; CI: 0.99, 2.71), coal and charcoal (OR 1.54; CI: 1.21, 1.97), wood (OR 1.20; CI: 0.95, 1.51) and lower-grade biomass fuels (OR 1.49; CI: 0.93, 2.35). In contrast, during the dry season the corresponding odds were reduced for kerosene (OR 1.23; CI: 0.77, 1.95), coal and charcoal (OR 1.35; CI: 1.06, 1.72) and lower-grade biomass fuels (OR 1.07; CI: 0.69, 1.66) but increased for wood (OR 1.32; CI: 1.04, 1.66). Cooking location also emerged as a season-dependent statistically significant (p = 0.0070) determinant of ALRI, in particular cooking indoors without a separate kitchen during the rainy season (OR 1.80; CI: 1.30, 2.50). Due to infrequent use in Africa we could, however, not demonstrate an effect of stove ventilation.

Conclusions

We found differential and season-dependent risks for different types of solid fuels and kerosene as well as cooking location on child ALRI. Future household air pollution studies should consider potential effect modification of cooking fuel by season.

Causal diagrams in systems epidemiology

Methods of diagrammatic modelling have been greatly developed in the past two decades. Outside the context of infectious diseases, systematic use of diagrams in epidemiology has been mainly confined to the analysis of a single link: that between a disease outcome and its proximal determinant(s). Transmitted causes ("causes of causes") tend not to be systematically analysed.

The infectious disease epidemiology modelling tradition models the human population in its environment, typically with the exposure-health relationship and the determinants of exposure being considered at individual and group/ecological levels, respectively. Some properties of the resulting systems are quite general, and are seen in unrelated contexts such as biochemical pathways. Confining analysis to a single link misses the opportunity to discover such properties.

The structure of a causal diagram is derived from knowledge about how the world works, as well as from statistical evidence. A single diagram can be used to characterise a whole research area, not just a single analysis - although this depends on the degree of consistency of the causal relationships between different populations - and can therefore be used to integrate multiple datasets.

Additional advantages of system-wide models include: the use of instrumental variables - now emerging as an important technique in epidemiology in the context of mendelian randomisation, but under-used in the exploitation of "natural experiments"; the explicit use of change models, which have advantages with respect to inferring causation; and in the detection and elucidation of feedback.