Table 7.

Current challenges and suggested future directions for DHS data used in HAP and health studies.

Challenges	Suggestions (Survey Planning and Implementation/Policy/Research)	Priority to Implement	Difficulty to Implement
Data on the degree of exposure to smoke from cooking fuels collected using questionnaire, which is likely to be less accurate than other methods of exposure assessment.	DHS and other household surveys could implement more robust methods (e.g., biological monitoring, personal sampling and micro-environmental area-based sampling) in a smaller, representative sub-sample.	High	Medium
DHS collects a single (main) fuel item used for cooking, but households use multiple fuel items (fuel stacking) for cooking, and for other purposes (e.g., heating and lighting).	Modifying the DHS questionnaire in a way that it can capture multiple responses on the types of fuel used for cooking and for other purposes would be beneficial, including more granular estimates of exposure to cooking-derived pollutant (either categorical or continuous, from models and/or measurements).	High	Low
Included studies did not control for some potentially important ambient air pollutants (e.g., particulate matter, NO2, O3 and CO).	Existing public domain, global spatial exposure datasets (e.g., those used in the GBD and other studies) could be linked to geocoded DHS data, which would reduce the need for individual researchers to seek out the data and complete this linkage themselves.	Medium	Low
Most of the outcomes, except child nutritional status and a few birth weight outcomes, were based on self-report and prone to recall bias or have unclear validity.	Though it is very challenging, and unlikely to be achieved in the near future, a shift to collecting more objectively determined outcomes, either measured directly or through linkage with non-DHS administrative data, would enable a larger range and higher quality of analyses.	High	High
The included studies collectively suggest that missing data on cooking fuel and associated information (e.g., location of the kitchen and stove ventilation) can be make analyses problematic.	Explore implications of missing exposure data on health analyses and compare the utility of different imputation or prediction-based methods to deal with missingness.	High	Low