Acute respiratory infections (ARIs) kill 0.94 million children under five years of age annually [1]. The burden of ARIs in developing countries is considerably higher than that in developed countries [2]. In India in 2010, 24% of the total deaths among children under five was due to ARIs [3]. In terms of incidence, 151 million new ARI cases occur annually among children under five in developing countries [4-6]. Many of these result in the death of young children. For example, in India, about 0.16 million male children and 0.21 million female children below the age of five died due to ARIs in 2005 [7]. Recent estimates suggest that about 0.41 million young children died of ARIs in India in 2010 [3].

Research on the subject indicates that indoor air pollution (IAP) from the use of solid fuels for cooking/heating is one of the important risk factors of ARIs [7-11]. Exposure is particularly high among women and young children, who spend most of their time near the domestic hearth [12]. According to WHO [1], nearly half of the deaths among children due to ARIs is because of IAP. Recent data from India suggests that the use of solid fuels was responsible for 20% of the total deaths among children in the age group, 1–4 years [13]. According to IIPS & ORC Macro [14], only 4% of the children living in households using electricity/LPG had ARI symptoms compared to 7% of the children belonging to households using animal dung as fuel [14].

An important factor while examining the role of IAP in causing health risks is the permeability or ventilation in the dwelling [15-18]. A study carried out by Dasgupta, Huq [17] in Bangladesh showed that ventilation such as roof and wall permeability reduced the average household pollution level greatly. Akunne, Louis [15] also found an association between permeability and impact of IAP. On the other hand, Pitt, Rosenzweig [19] concluded that improving ventilation by increasing the permeability of roofs and walls had no significant effect on health. The study by Gajate-Garrido [20] could not establish the benefits of higher permeability in the dwelling. The issue of the use of hazardous fuel and permeability of dwelling is particularly important in India because, of the 247 million Indian households, about 173 million use solid fuels such as firewood, crop residual, cow dung and cake coal/charcoal. Of these 173 million households, 75 million do not have a separate kitchen [21].

A number of Indian studies have reported an association between IAP caused by cooking fuel and risk of ARIs among children under the age of five [8,10,11,22-27]. Notably, majority of these studies are based on cross-sectional data, and hence these studies fail to develop any causal relationship between IAP caused by cooking fuel and risk of ARIs. None of the Indian studies have included roof and wall permeability in the analysis. Moreover, the impact of IAP on ARIs is also likely to depend on the number of other women (like aunt, grandmothers, etc.) present in the household. Pitt, Rosenzweig [19] argued that the presence of other women in the household is likely to reduce young children’s exposure to IAP. Mothers with young children are likely to spend less time close to the stove if other women like grandmothers or aunts are present in the house [19]. It is important to mention that none of the Indian studies have included the presence of other women in their statistical models.

Our study complements and augments existing literature by examining the impact of IAP from the use of solid fuels for cooking on the incidence of life-threatening respiratory illnesses (LTRI) using panel data. The panel structure of the data allows our analysis to capture the dynamic nature of the household and community level variables, isolate the effect of omitted variables, reduce collinearity among exposure variables and provide robust causal effect of exposure variable on the outcome variable. We also account for the permeability of the dwelling and the presence of other women in the house while examining the impact of use of solid fuels for cooking on the incidence of LTRI.

Data and methods

Data

We use data from the first and second rounds of the Young Lives Study (YLS), which was conducted in the state of Andhra Pradesh in India during 2002 and 2006–07. Young Lives is an international longitudinal study investigating the changing nature of childhood poverty. About 12000 children are being followed in four countries: Ethiopia, Peru, Vietnam and India (Andhra Pradesh). Each country has two cohorts: younger cohort and older cohort to be followed over a period of 15 years. The younger cohort consists of about 2000 children born in 2001–2002 and the older cohort consists of about 1000 children born in 1994–1995 [28,29]. The YLS is conducted every three/four years to collect data on a range of indicators related to the growth and development of children [28-30].

A multistage sampling design was adopted in YLS. In the first stage, two districts were selected from each of the three geographic regions (Coastal, Rayalseema and Telangana) of the state of Andhra Pradesh. In the second stage, 19 (15 from rural areas and 4 from urban areas) sentinel sites (administrative blocks or ‘mandals’) were selected from the six selected districts. In addition, one sentinel site was selected from the urban slums of the city of Hyderabad. In the third stage, villages were selected from rural sentinel sites and wards were selected from urban sites. All the households with a one year old child (born in 2001–2002) or an eight year old child (born in 1994–95) in the selected villages and wards were included in YLS. Overall, 2011 households (with 2011 children) in the younger cohort (born in 2001–2002) and 1008 households (with 1008 children) in the older cohort (born in 1994–95) were included in the first round of YLS, which was conducted in 2002 (for details of YLS sampling design, see [6,28,29]. As the objective of this study is to analyze the impact of the use of solid fuels on the incidence of LTRI in children under six years, we include only the younger cohort (born in 2001–02) in the analysis. This is again a reason for using only the first two rounds of YLS that is, 2002 and 2006–07 in the analysis.

The second round took place between late 2006 and early 2007 and included 1950 children in the younger cohort. The attrition rate between the two rounds was about 3% [31]. While the pooled analysis presented in this paper is based on observations on 3961 children, the panel analysis is based on 1950 children.

Outcome variable

The outcome variable of interest is the incidence of LTRI. Both rounds of YLS asked mothers two questions related to life threatening illnesses:

1. In the (reference period), has the child had any serious illnesses or injuries when you really thought he/she might die? (Yes/No/Don’t Know) 2. What were the illnesses or injuries?

If the mother reported pneumonia, severe cough, asthma, acute respiratory problems and high fever in response to the second question, then we coded LTRI as ‘1’ and otherwise‘0’. Hence, LTRI is a binary indicator variable, which takes value ‘0’ when no episode of LTRI occurred and ‘1’ otherwise. By using LTRI instead of minor illnesses, we were able to exclude seasonal health problems in our analysis.

Independent variable

The independent variable of interest in the present study is the presence of indoor air pollution from the use of solid fuel for cooking. The survey gathered information on the main type of fuel used for cooking. Cooking fuels like wood, charcoal, coal and cow dung were coded as solid fuels. Electricity, gas and kerosene were coded as other cooking fuels (or cleaner fuels). The United States Environmental Protection Agency’s Standard for the 24-hour average of PM 10 is 150 ug/m3 [32]. Since kerosene has emission levels (PM 10 134 ug/m3) below the recommended standard [17], we included kerosene in the category of ‘other cooking fuel’.

Other key variables

The other key variables included age of the child (in months), sex of the child (female; male), wall permeability (non-permeable; permeable), roof permeability (non-permeable; permeable), child’s nutritional status (Height-for-age z-score > = − 2SD; Height-for-age z-score < −2SD), wealth index (poorest; poorer; middle; richer; richest), presence of other women at home (no/yes), household crowding (<3 persons per room; > = 3 persons per room), and the interactions of cooking fuel with wall permeability, roof permeability and sex of the child.

If the wall of the house was made of matting, wood/branches, cement bag, fibreboard/chipboard or stone, it was classified as permeable. Walls made of any other material were classified as non-permeable. If the roof was constructed of straw/thatch, tiles/slates, wood/plank or galvanised iron, it was classified as permeable. Roofs made of other materials were classified as non-permeable.

The child’s nutritional status was measured using height-for-age z-score. Children whose height-for-age z-score was below minus two standard deviations from the median of the reference population were considered short for their age or stunted. Such children are also considered chronically malnourished [14].

We also generated a wealth index based on household assets (including radio, refrigerator, bicycle, television, motorbike/scooter, car, pump, sewing machine, mobile, phone, landline telephone, fan, almirah, clock, table, chair, sofa, bedsheet and animals), household quality (including wall, roof and floor) and services (including electricity, drinking water, toilet facility) using principle components analysis. The generated index was then coded into five categories. Based on the wealth index, the lowest 20% of the households were coded as the poorest, the next 20% as poorer, and so on.

A number of other socioeconomic, demographic and residence related variables affect the health of children [11]. Accordingly, we controlled for number of siblings below five years of age, mother’s schooling (0–4 years; 5–9 years; 9+ years), mother’s working status (not working; agricultural work; other work), schooling of household head (0–4 years; 5–9 years; 9+ years), religion of household head (Hindu; Muslim; others), caste of household head (Scheduled Caste/Scheduled Tribes; other backward caste; others), household’s size, income shocks (no/yes), residence (rural/urban), exposure to outdoor air pollution (no/yes), percentage of literate mothers in the community, and ecological zone (others/inland plane) as control variables in the statistical models.

Income shocks refer to the loss of job or source of income that significantly decreased the economic welfare of the household. Income shocks at the household level were assessed by the answers to the following question asked in the two rounds of YLS:

‘In the last four years has the household suffered loss of job/source of income/family enterprise? (Yes/No)’.

The respondents were asked to report the ecological zone to which they belonged. The ecological zone is a pre-coded variable with four categories (inland plane, coastal plane, rain forest, and hill). Since 78 of the 98 communities included in YLS belonged to the ‘inland plane’, we coded the ecological zone into two categories (inland plane and others). Direct questions were asked in YLS to assess the exposure of the communities to outdoor air pollution from garbage burning, industrial activity and transportation. This information was used to create the variable, ‘exposure to outdoor air pollution’. If the community was exposed to any of the three afore-mentioned sources, ‘exposure to outdoor air pollution’ was coded as ‘1’ and otherwise, ‘0’.