Antai and Moradi the mother at the time of the second birth (Rahman et al. 1996). Moreover, we found that high birth order after short birth interval was associated with increased risks of under-5 deaths, an expected finding shown by other studies (Makepeace and Pal 2006). Preceding birth intervals of 36–59 months have been shown to be optimal for reducing the risk of neonatal mortality (Conde-Agudelo et al. 2006; Rutstein 2005). In addition, birth-to- pregnancy intervals of ≤ 18 months have been associated with the highest risk of neonatal mortality (which reflects a birth-to-birth inter- val of < 27 months), with the lowest risks esti- mated for children with birth-to-pregnancy intervals of ≥ 27 months (or birth intervals of > 35 months) (Marston 2006). Our results indicated that low SEP (pri- mary education or less, unemployment, and being in the poorest wealth quintile) was positively associated with under-5 deaths. This finding is corroborated by those of other urban studies (Giashuddin et al. 2009; Raphael et al. 2003; Schulz et al. 2008; Singh and Kogan 2007; Songsore 2000). Ultimately, it is the multiplicity of socioeconomic factors at both the individual and community levels that shape the survival chances of children in urban environments. A number of limitations need to be considered in relation to this study. First, defining neighborhoods according to admin- istratively defined boundaries may not always reflect meaningful neighborhood boundaries, especially for area-based measures that char- acterize the availability of neighborhood socio- economic characteristics. Such measures may be particularly sensitive to whether people live near neighborhood boundaries (Macintyre et al. 1993). The effect of this nondifferen- tial misclassification of individuals into an inappropriate administrative boundary can generate information biases and reduce the validity of analyses. Second, indices in general are difficult to construct and validate and tend to mask variation in the characteristics that contribute to a score when two or more areas have the same score (Pickett and Pearl 2001). The strengths of this study are also worth mentioning. First, neighborhood-level socio- economic characteristics are much more highly correlated than are individual-level socioeconomic factors; hence, the risk of mis- specifying the neighborhood-level effect is minimal (Pickett and Pearl 2001). Second, the development of composite indices enable easy handling of several highly correlated neighborhood-level variables and improves statistical efficiency and simplifies the presen- tation of results. Using several single neigh- borhood-level measures separately to reflect a single underlying concept such as urban SEP introduces the risk of collinearity and cumber- some results, a point emphasized by previous 882 studies (Pickett and Pearl 2001). Third, the DHS surveys are nationally representative and allow for generalization of the results across the country (Fotso 2006). Fourth, variables in the DHS surveys are defined similarly across countries, and results are therefore compa- rable across countries (de Walque 2006). Fifth, the advantages of using administrative boundaries are the possibility of comparing any set of data on the same geographic frame, or of presenting complex data in a simple way. Last, further inclusion of individual-level characteristics to the model may have resulted in reduced strength of the association with area disadvantage. Policy implications. Several policy impli- cations are therefore inherent from our find- ings. First, there is a need for accessible and relevant data to better describe and quantify relationships between health outcomes and the urban environment. Second, because most disadvantaged urban neighborhoods are char- acterized by significant levels of inequality, we do not necessarily support a policy that concentrates only on the most deprived areas of low- and middle-income countries such as Nigeria, because interventions resulting from policies that focus solely on priority areas risk excluding a major proportion of mothers and children who might otherwise have benefited from resulting interventions and widening such inequalities. Hence, there is a need to focus on inequality-reduction measures. Third, there is a need for policies to promote the optimal birth interval of 36–59 months, which has been repeatedly observed to reduce risk of neonatal or child mortality (Setty- Venugopal 2002), or a birth-to-pregnancy interval of 24 months (Marston 2006). Conclusion We found that urban-area disadvantage was independently associated with the risk of under-5 deaths even after controlling for individual child- and mother-level demo- graphic and socioeconomic characteristics. The existence of significant risk of under-5 deaths at both the individual and community levels underscores the need not only to tailor interventions aiming at the community level (the disadvantaged neighborhoods) but also to focus strategies implemented at the indi- vidual level. Community- or neighborhood- level strategies could aim to counter adverse environmental conditions of deprived areas, such as the sustainable development of urban household amenities and community infra- structure, improved water supply, improved maternal literacy, education, and employ- ment, and other neighborhood socioeco- nomic upliftment strategies in these deprived communities. Increased relative risks associ- ated with first births and high-order births after short preceding birth interval emphasizes the need for strategies that promote optimal birth-to-birth intervals and enhanced health- seeking behavior of mothers in these disad- vantaged areas, especially young uneducated mothers. Significant variation among com- munities found in this study stresses the need for further studies on possible unmeasured community-level determinants of under-5 mortality in disadvantaged urban areas. c ectinor In Table 2, the variance values were incor- rect in the manuscript originally published online. They have been corrected here. Ref Rencs Adepoju A. 2004. Feminisation of poverty in Nigerian cities: insights from focus group discussions and participatory poverty assessment. Afr Popul Stud 19:141–154. African Population and Health Research Center. 2002. 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