Previous studies of Indoor Air Pollution have identified several potential determinants of exposure to indoor air pollution: fuel type, time spent in cooking, cooking location, structural characteristics of houses, and household ventilation practices (opening of windows and doors, etc.). All of these factors are important in Bangladeshi households, which exhibit significant diversity in cooking fuels, stove types, cooking locations, and ventilation characteristics of houses. Discussion with local experts revealed widespread use of gas, electricity, kerosene, firewood, cow dung, rice husks, straw, jute sticks, bagasse and sawdust as fuel; four cooking locations (separate-attached, separate-detached, outside/ open, single room dwelling – no separate kitchen); and thatch, tin, mud and brick as common structural materials of houses.
These data on respirable airborne particulates (PM10) collected in a large number of Bangladeshi households.were used to analyze the implications for indoor air pollution, drawing on new monitoring data for Concentrations of 300 ug/m3 or greater are common in our sample, implying widespread exposure to a serious health hazard.
Kind of Data
Sample survey data [ssd]
Version 0.1: The data files used in this documentation have been converted to Stata from Excel format. When converting the datasets, variable names have been created using the questions number and “q” as prefix.
Data collected using district survey questionnaire has been reshaped using “IAP-DistrictSurveyDataReshape.do” program which is provided as external resource. Both the original "IAP-DistrictSurveyData" and the reshaped data files are uploaded to this documentation.
The survey covered urban and peri-urban areas of Narshingdi in Dhaka region.
Producers and sponsors
The World Bank
For the World Bank research, a stratified sample in urban and peri-urban areas of Narshingdi in Dhaka region was selected to incorporate representative variations in fuel use, cooking arrangements and structural characteristics that affect ventilation. (The term "peri-urban" has been used to describe areas proximate to Dhaka, but the sample includes many rural farmhouseholds.) The households were separated into groups defined by cooking fuel, kitchen type and location, and construction material. Then households were selected independently from each group. The stratification had been designed for cell values large enough to test fuel and ventilation effects on indoor air pollution, and was not intended to represent all Bangladeshi households.
The sample size was 250+, given cost constraints.
Extrapolation and Exposure Reconstruction:
Since the determinants of indoor air pollution were analyzed using a stratified sample of urban and peri-urban households in the Dhaka region, the sample was not intended to represent all Bangladeshi households. In order to assess the broader implications, a representative household survey was conducted in seven districts in six geographical regions: Rangpur in the Northwest, Sylhet in the Northeast, Rajshahi and Jessore in the West, Dhaka, Faridpur and Kishoreganj in the Center, and Cox's Bazar in the Southeast. Information on all potential determinants of indoor air pollution (determinants found significant in the regression analysis) was collected in this survey. In addition, all members of the households were questioned regarding their time activity pattern: average hours spent in the cooking area, living areas, and outdoors in a typical day to get an idea about exposure
Dates of Data Collection
Data Collection Mode
Data Collection Notes
Monitoring of Indoor Air:
At each household, PM10 concentrations in the cooking and living areas were monitored for a 24 hour period during 2003 - 2004. Two devices were used for monitoring indoor air:
1) A real-time monitoring instrument, the Thermo Electric Personal DataRAM (pDR-1000) (http://www.thermo.com/eThermo/CMA/PDFs/Product/productPDF_18492.pdf)
2) A 24-hour instrument, the Airmetrics MiniVol Portable Air Sampler (http://www.airmetrics.com/products/minivol/index.html).
The pDR-1000 uses a light scattering photometer (nephelometer) to measure airborne particle concentrations. The operative principle is real-time measurement of light scattered by aerosols, integrated over as wide a range of angles as possible. This instrument operated continuously for 24-hour periods, recording PM10 concentrations at 2-minute intervals. The Airmetrics MiniVol Portable Air Sampler, on the other hand, is a more conventional device that samples ambient air for 24 hours. The MiniVols were generally programmed to draw air at 5 liters/minute through PM10 particle size separators. The particles were caught on the filters, and the filters were weighed pre and post exposure with a precisely-calibrated microbalance at Airmetrics, Inc. The readings of pD-RAM and MiniVol air sampler provide a detailed record of indoor air pollution concentration in each household.
A short questionnaire was administered to each household on the same day to obtain information on socio-economic characteristics of the household members, fuel type, fuel quantity, stove location, cooking time, numbers of people cooked for, duration of fire after cooking, the use of iron, mud, thatch and concrete for construction of the house and kitchen, the placement and size of windows, doors and ventilation spaces between walls and roofs, ventilation practices such as opening doors and windows after cooking, smoking practices, and the use of lanterns and mosquito coils.
Regression Analysis to Explore the Determinants of IAP:
A regression analysis for the households with monitored information of indoor air was conducted to explore the determinants of indoor air pollution. Households' PM10 concentrations were regressed on fuels used during the monitored day, cooking time, duration of fire after cooking, numbers of people cooked for, stove location, the use of iron, mud, thatch and concrete for construction of the house and kitchen, the placement and size of windows, doors and ventilation spaces between walls and roofs, ventilation practices such as opening doors and windows after cooking, smoking practices, and the use of lanterns and mosquito coils. Among these variables, a small set were found to significantly affect household PM10 concentrations: fuel type, stove locations, building materials, and opening doors and windows after cooking.