Sreeramareddy et al. BMC Public Health 2011, 11:403 http://www.biomedcentral.com/1471-2458/11/403 Discussion The results from our analysis suggest that use of bio- mass cooking fuels is associated with child’s birth weight and size at birth. The children born in households using high pollution fuels had significantly lower birth weight than those children born in households using low pollu- tion fuels. The association between use of high pollution fuels and size at birth was independent of child’s gender, birth order, mother’s education and nutritional status, even after adjustment. The association did not remain significant after adding socio-economic factors in the final model. The results of our analysis about the association between type of cooking fuel and LBW are consistent with previous reports from rural Guatemala, Pakistan, Zimbabwe and Southern India [19-22]. The only differ- ence of our results from previous studies is the possibi- lity of residual confounding effect of household wealth index. The effect of type of fuel on LBW may have been masked by wealth index in the final regression model. Wealth index being a composite measure of cumulative living standard is computed based on 41 items including type of fuel used in households. Therefore we did not find any association in the final regression model. One reason for such an effect may be due to correlation between wealth index and type of fuel (r = 0.664), urban/rural residence and type of fuel used (r = 0.54), which could not be controlled for in the modelling. However, the influence of other variables well known to cause LBW remained significant during multivariable modelling. These consistent associations of primary exposure variable and the covariates should be discussed in the light of various epidemiological study designs and other criteria necessary to establish causal links. LBW was associated with maternal smoking in studies from Southern India and Pakistan [19,22]; mother’s age in studies from Pakistan and Guatemala [19,21]; birth order/parity in studies from Guatemala and Zimbabwe [20,21], and BMI in studies from Zimbabwe and Paki- stan [19,20]. Though all the variables were not tested in all the studies and the degree of adjustment varied across studies remarkably, the association has remained consistent. In our analysis, birth weight was associated urban/rural residence and literacy. Such associations may be due interactions between socio-economic factors as discussed above. The study from Guatemala used a non-representative sample with predominantly hospital deliveries [21]. The study from Pakistan had a population-based historical cohort allowing to test for temporal sequence i.e. use of wood fuel preceding the birth of LBW baby [19]. The report from Zimbabwe used birth weight information from recall and health card and had selection bias as Page 8 of 10 mentioned earlier i.e. birth weights were not available for babies from a disproportionately high number of households using high pollution fuels [20]. In Zimbab- wean study, selection bias arising from these differentials in birth weight information may have lead to underesti- mation of actual effect size for the association. Maternal self-reports of birth weight during health interviews are not accurate and have a propensity for over-estimation [27]. When a sensitivity analysis was carried out overes- timation of birth weight had lead to attenuation of effect size in the study from Zimbabwe [23]. The study from Southern India used a cohort design and did not adjust for nutritional factors in their analysis but tested the exposure to second hand tobacco smoke (SHTS) [22]. However, very few of the earlier studies have used direct methods for measurement of indoor air pollution from burning biomass fuels. Evidence for association between ETS and LBW [6,7] from the systematic reviews and similarity of pollutants in ETS and biomass smoke [8,17] is a sufficient proof for the hypothesis tested in our study. Studies measuring ambient air pollutants like sulphur dioxide, carbon monoxide and PM10 have also shown that these pollutants are associated with decreased birth weight [28-30]. The association is also supported by biological plausibility from animal studies. It has been has shown that when rabbits were exposed to 90 ppm of CO, 8-9% of COHb was produced and there was 11% reduction in mean birth weight [31]. Stu- dies have also demonstrated that air pollutants can bring about changes in alveolar macrophage load [18], cross the alveolar-capillary barrier and penetrate deep into the lungs [32]. Like any other epidemiological study, our study has certain strengths and limitations. The strength of our analysis was using a large nationally representative sam- ple. Additionally, using size at birth as proxy for birth weight gave us a bigger sample and increase in statistical power for our results. We examined the effect of mater- nal smoking, maternal BMI and haemoglobin levels on size at birth. However, our results should be interpreted with caution against the inherent limitations of cross-sec- tional design and secondary data analysis. The main lim- itations are lack of temporality of association due to cross-sectional design, and possible misclassification of both exposure and outcome assessment. Due to cross- sectional design of DHS, it was not possible to ascertain if exposure (type of fuel use) occurred prior to the out- come (size of baby at birth) or vice versa. Another main limitation was misclassification bias of both exposure and outcome. For the information about type of fuel used, we relied on one question in the DHS questionnaire. Infor- mation about multiple fuel use, temporal changes (time trend) in fuel use, duration of fuel used were not assessed