PT - JOURNAL ARTICLE AU - Honor Bixby AU - James E Bennett AU - Ayaga A Bawah AU - Raphael E Arku AU - Samuel K Annim AU - Jacqueline D Anum AU - Samilia E Mintah AU - Alexandra M Schmidt AU - Charles Agyei-Asabere AU - Brian E Robinson AU - Alicia Cavanaugh AU - Samuel Agyei-Mensah AU - George Owusu AU - Majid Ezzati AU - Jill Baumgartner TI - Quantifying within-city inequalities in child mortality across neighbourhoods in Accra, Ghana: a Bayesian spatial analysis AID - 10.1136/bmjopen-2021-054030 DP - 2022 Jan 01 TA - BMJ Open PG - e054030 VI - 12 IP - 1 4099 - http://bmjopen.bmj.com/content/12/1/e054030.short 4100 - http://bmjopen.bmj.com/content/12/1/e054030.full SO - BMJ Open2022 Jan 01; 12 AB - Objective Countries in sub-Saharan Africa suffer the highest rates of child mortality worldwide. Urban areas tend to have lower mortality than rural areas, but these comparisons likely mask large within-city inequalities. We aimed to estimate rates of under-five mortality (U5M) at the neighbourhood level for Ghana’s Greater Accra Metropolitan Area (GAMA) and measure the extent of intraurban inequalities.Methods We accessed data on >700 000 women aged 25–49 years living in GAMA using the most recent Ghana census (2010). We summarised counts of child births and deaths by five-year age group of women and neighbourhood (n=406) and applied indirect demographic methods to convert the summaries to yearly probabilities of death before age five years. We fitted a Bayesian spatiotemporal model to the neighbourhood U5M probabilities to obtain estimates for the year 2010 and examined their correlations with indicators of neighbourhood living and socioeconomic conditions.Results U5M varied almost five-fold across neighbourhoods in GAMA in 2010, ranging from 28 (95% credible interval (CrI) 8 to 63) to 138 (95% CrI 111 to 167) deaths per 1000 live births. U5M was highest in neighbourhoods of the central urban core and industrial areas, with an average of 95 deaths per 1000 live births across these neighbourhoods. Peri-urban neighbourhoods performed better, on average, but rates varied more across neighbourhoods compared with neighbourhoods in the central urban areas. U5M was negatively correlated with multiple indicators of improved living and socioeconomic conditions among peri-urban neighbourhoods. Among urban neighbourhoods, correlations with these factors were weaker or, in some cases, reversed, including with median household consumption and women’s schooling.Conclusion Reducing child mortality in high-burden urban neighbourhoods in GAMA, where a substantial portion of the urban population resides, should be prioritised as part of continued efforts to meet the Sustainable Development Goal national target of less than 25 deaths per 1000 live births.Data are available in a public, open access repository. Data may be obtained from a third party and are not publicly available. Estimates of neighbourhood U5M will be made available at http://equitablehealthycities.org/data-download/. The full microdata of the 2010 Ghana Population and Housing Census are with the Ghana Statistical Service and are not publicly available. Data from a random 10% sample of households enumerated in the 2010 Population and Housing census are publicly available and can be downloaded from Ghana Statistical Services online data catalogue (https://www2.statsghana.gov.gh/nada/index.php/catalog/51).