Sreeramareddy et al. BMC Public Health 2011, 11:403 http://www.biomedcentral.com/1471-2458/11/403 and School of Public health, University of Alabama at Birmingham. The interviewers informed the participants that participation in the survey was voluntary and assured them that information provided will be kept confidential. Following this an informed consent was obtained from each participant. Outcome variable The main outcome measure used was child’s birth weight. For each birth during the preceding five years, mothers were asked about birth weight. Mothers were asked, “Was your baby weighed at birth?” If the response was ‘yes’, they were further questioned, “How much did your baby weigh?” If mother possessed a health card, she was asked to show it and birth weight was recorded. For those mothers who did not possess a health card, birth weight was recorded according to mother’s recall. Mothers were also asked to classify ‘size of the baby’ at birth into of following five categories: ‘very large’, ‘larger than average’, ‘average’,’ smaller than average’, and ‘very small’. We pooled these categories to form a binary vari- able as ‘greater than or equal to average size’ and ‘less than average size’ at birth corresponding to normal birth weight (≥2500 grams) and low birth weight (birth weight < 2500 grams) respectively. Births with missing informa- tion about size at birth and multiple births (6.7%) were excluded from our analysis. In a similar study based on Zimbabwe DHS, the authors have acknowledged about bias arising from a disproportionately high number of babies from households using biomass fuels being not weighed at birth as compared to the households using cleaner fuel [20]. We observed a similar pattern in our data also. Nearly 60% of the births included for our ana- lysis did not have information about birth weight either from mother’s recall or health card, whereas for ‘size at birth’ missing information was only 4.5%. This precluded us from using information about birth weight as outcome variable) from health card and/or mother’s recall. There- fore size at birth was used as a proxy for birth weight to classify children as low birth weight and normal birth weight. This gave us a bigger sample size of 47,139 births to be included in the final analysis Exposure variables The standard DHS used eleven fold classification of cooking fuels used in the house. The specific question asked was, “What type of fuel does your household mainly use?” For our analysis, the main cooking fuel used was grouped into one of the two categories. These two categories were namely; high pollution fuels (wood, straw, animal dung, and crop residues, kerosene, coal and charcoal), and low pollution fuels (electricity, liquid petroleum gas, natural gas and biogas). Page 3 of 10 Other predictor variables The DHS also collected information about smoking habits of the individuals in households, and tested hae- moglobin level for women. Mothers were asked, “Do you currently smoke cigarettes?” The effect of exposure to biomass fuels on birth weight may be confounded by fac- tors like tobacco smoking and nutritional status of mother. Therefore, we adjusted for body mass index (BMI) as an indicator for nutritional status of mothers [25] and haemoglobin level of mothers along with biolo- gical and socio-demographic factors. Blood haemoglobin level, height and weight measurements were obtained by the interviewer at the time of interview. Blood haemoglo- bin level was measured using a portable HemoCue sys- tem which is feasible to operate in field setting. HemoCue system uses a drop of blood taken by finger prick. Blood was drawn into a cuvette and inserted into a portable, battery-operated instrument which gives a digi- tal reading of haemoglobin concentration. Haemoglobin measurements were adjusted for altitude. The respon- dents were informed about the results of haemoglobin testing. As an indicator of nutritional status, maternal BMI was calculated using height and weight. During the interview, maternal demographic information about age at interview, age at the time of each birth, gender of the child, birth order, highest level of education attained, reli- gion practiced, rural or urban area of residence, and level of household wealth was also obtained. Maternal educa- tion was classified as no formal education, primary edu- cation, secondary education, or higher education. Mother’s religion was classified as Hindu, Muslim, Chris- tian, Buddhist/Neo-Buddhist, or other. Urban or rural area of residence was defined as a mega city, large city, small city, large town, small town, or rural area. Wealth Index which is a relative index of household wealth was calculated based on a standard set of household assets as observed by the interviewer, ownership of consumer items and dwelling characteristics. The individuals were ranked on the basis of their household score and divided into quintiles where one is the poorest 20% of the house- holds and five is the wealthiest 20% of the households. Statistical analyses We did an exploratory analysis of birth weight of the child obtained from health card and mother’s recall. We compared the mean birth weight between two fuel type categories i.e. high pollution and low pollution fuels using independent samples t-test. To test the concor- dance between birth weight of child (from recall and health card) and size at birth we used Somer’s D test. The outcome variable was size at birth dichotomized into normal birth weight and low birth weight. For bivariate analysis of categorical variables we used chi