Sampling errors and design effects from 48 nationally representative surveys conducted under the Demographic and Health Surveys Program for a large number of variables concerning fertility, family planning, fertility intentions, child health and mortality etc. are analysed for the total sample, and for urban-rural domains, sub-national regions and various demographic and socio-economic subclasses. The effect of sample weights on sampling errors is examined, as well as the effect of clustering of children in a sample of women who are the actual respondents in DHS surveys. Modelling of design effect for geographic domains, for subclasses that are defined in terms of individual characteristics, and for differences between subclasses is offered. At the country level, overall design effect (the ratio of actual to simple random sampling standard error) averaged over all variables and countries is around 1.5. Variation among countries is high, but less so than among variables. Urban-rural and regional differentials in design effects are small, and can be attributed to the fact that similar sample designs and cluster sizes were used across those domains within each country. Design effects for estimates over other subclasses are smaller, and tend towards 1.0 for small subclasses and differences, apart from the effect of sample weights which tends to persist undiminished across variables and subclasses