Characterising variability and predictors of infant mortality in urban settings: findings from 286 Latin American cities.
Ana F Ortigoza, José A Tapia Granados, J Jaime Miranda, Marcio Alazraqui, Diana Higuera, Georgina Villamonte, Amélia Augusta de Lima Friche, Tonatiuh Barrientos Gutierrez, Ana V Diez Roux
Author Information
Ana F Ortigoza: Urban Health Collaborative, Drexel University, Philadelphia, Pennsylvania, USA afo25@drexel.edu. ORCID
José A Tapia Granados: History and Political Science, Drexel University, Philadelphia, Pennsylvania, USA. ORCID
J Jaime Miranda: CRONICAS Centre of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru. ORCID
Marcio Alazraqui: Instituto de Salud Colectiva, Universidad Nacional de Lanus, Lanus, Argentina.
Diana Higuera: Escuela de Medicina, Universidad de Los Andes, Bogota, Colombia.
Georgina Villamonte: CRONICAS Centre of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru.
Amélia Augusta de Lima Friche: School of Medicine, Universidade Federal de Minas Gerais Faculdade de Medicina, Belo Horizonte, Brazil.
Tonatiuh Barrientos Gutierrez: Instituto Nacional de Salud Publica, Mexico DF, Mexico.
Ana V Diez Roux: Urban Health Collaborative, Drexel University, Philadelphia, Pennsylvania, USA.
BACKGROUND: Urbanisation in Latin America (LA) is heterogeneous and could have varying implications for infant mortality (IM). Identifying city factors related to IM can help design policies that promote infant health in cities. METHODS: We quantified variability in infant mortality rates (IMR) across cities and examined associations between urban characteristics and IMR in a cross-sectional design. We estimated IMR for the period 2014-2016 using vital registration for 286 cities above 100 000 people in eight countries. Using national censuses, we calculated population size, growth and three socioeconomic scores reflecting living conditions, service provision and population educational attainment. We included mass transit availability of bus rapid transit and subway. Using Poisson multilevel regression, we estimated the per cent difference in IMR for a one SD (1SD) difference in city-level predictors. RESULTS: Of the 286 cities, 130 had <250 000 inhabitants and 5 had >5 million. Overall IMR was 11.2 deaths/1000 live births. 57% of the total IMR variability across cities was within countries. Higher population growth, better living conditions, better service provision and mass transit availability were associated with 6.0% (95% CI -8.3 to 3.7%), 14.1% (95% CI -18.6 to -9.2), 11.4% (95% CI -16.1 to -6.4) and 6.6% (95% CI -9.2 to -3.9) lower IMR, respectively. Greater population size was associated with higher IMR. No association was observed for population-level educational attainment in the overall sample. CONCLUSION: Improving living conditions, service provision and public transportation in cities may have a positive impact on reducing IMR in LA cities.
