Sreeramareddy et al. BMC Public Health 2011, 11:403 http://www.biomedcentral.com/1471-2458/11/403 square test. We carried out the analyses using SAS soft- ware (Cray, North Carolina). In addition to type of fuel used, other (independent) variables considered were child factors (gender, and birth order), maternal factors (anaemia, BMI, age at childbirth, smoking, education) and socio-demographic factors (religion, wealth index, urban/rural residence). We tested for the possibility of collinearity between predictor variables. In a correlation matrix, BMI versus haemoglobin level and wealth index versus type of cooking fuel were paired and Pearson’s correlation coefficients were calculated to rule out mul- ticollinearity. Multilevel modelling was done to adjust for cluster sampling (cluster as primary sampling unit used in DHS). Three multivariable regression analysis models were built using SURVEYLOGISTIC procedure in SAS system (version 8.02) [26]. During statistical modelling, certain factors known to confound the results were adjusted. Adjusted odds ratios (AOR) and their 95% confidence intervals (95% CI) were calculated. A p-value less than 0.05 was considered as significant. Results Sample distribution A total of 124, 385 women participants reported 56, 438 births during the previous five years. The final sample analysed was 47,139 most recent singleton births. The main types of fuel used by the households were as fol- lows: electricity (267, 0.6%), liquid petroleum gas (12333, 26.2%), biogas(174, 0.4%), kerosene (1708, 3.6%), coal & lignite (786, 1.7%), charcoal (286, 0.6%), wood (24049, 51%), straw/shrubs/grass (1807, 3.8%), agricul- tural crop ( 1226, 2.6%), and animal dung ( 4503, 9.6%). Birth weight of the child was available for only 19,270 (41%) births. Of these, birth weights for 3113 children were available from child health card (18.4% were LBW) and for 16,157 children from mother’s recall (20.5% were LBW). Overall mean birth weight was 2846.5 grams (SD = 684.6). The children born in households using high pollution fuels were 73 grams lighter than the children born in households using low pollution fuels (mean birth weights; 2883.8 grams versus 2810.7 grams). This difference was statistically significant (p < 0.001). The adjusted (for wealth index) mean difference was 39.9 grams (SD = 13.4). The distribution of birth weights of most recent births according to type of fuel used in the households, mothers’ education, and type of residence is shown in Table 1. For 6.6% of the babies, birth weight was avail- able from health card and for 34.3% of the babies; birth weight was recorded from mother’s recall. Babies who were not weighed at birth were more likely to be from households using high pollution fuels as compared to households using low pollution fuels (66.87% versus 18.81%). A similar pattern was observed according to Page 4 of 10 the type of residence, i.e. rural versus urban: 68.1% ver- sus 31.3%. Additionally, babies who were not weighed at birth were more likely to be born to mothers who had lesser education. Mothers had a tendency of reporting the size at birth as ‘average’ since about 57% of the babies was reported as ‘average size’ (table 2). The dis- tribution of five categories of size at birth between households using high pollution fuels and low pollution fuels was statistically significant (p < 0.001). We used the test of association (Somer’s D) for con- cordance between birth weight of child (from mother’s recall and health card) and size at birth (table 3). Out of 3889 babies who were reported as weighing less than 2500 grams, 2066 (53.1%) were perceived by mothers as less than average size at birth. Similarly, out of 15,389 babies who were reported as weighing 2500 grams or more, 13,990 (90.9%) babies were perceived by mothers as average or more than average size at birth. These numbers suggest that mother’s perception about size at birth was reasonably reliable. Univariate analysis The results of univariate analysis for type of fuel and other control variables with low birth weight i.e. the effect of cooking fuel, tobacco smoke, biological factors and other variables on low birth weight are shown in table 4. Mothers from households using high pollution fuels were 1.4 (OR 1.41, 95% CI 1.27, 1.55) times more likely to give birth to a low birth weight baby as com- pared to those using cleaner fuels. Mothers who reported to be smoking were 1.4 times (OR 1.43, 95% CI 1.11, 1.86) more likely to give birth to a LBW baby as com- pared to those who did not reported to be smoking dur- ing the time of survey. Female babies (OR 1.13, 95% CI 1.07, 1.20) and babies of higher birth order (OR 0.89, 95% CI 0.83, 0.96) were less likely to be LBW. Among maternal factors, lower haemoglobin level, lower educa- tional status, and lower BMI increased the risk for child being LBW. Similarly children born in rural areas and those belonging to families with lower wealth index were at increased risk of being LBW. Multivariable analysis We checked for collinearity between BMI and maternal haemoglobin level and there was no correlation (r = 0.04). A strong collinearity was present (r = 0.664) between wealth index and type of cooking fuel. Table 5 shows the results of the multivariable models. We devel- oped three models by including child factors (model-1), maternal factors (model-2) and socio-demographic fac- tors (model-3), one by one to the main exposure vari- able i.e. type of cooking fuel, to control for the effect of these variables on the association between exposure to biomass fuel smoke and birth weight. In model-1, when