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Table 1 Variables available in the information systems and availability period

From: Combination of conditional cash transfer program and environmental health interventions reduces child mortality: an ecological study of Brazilian municipalities

Variables Data source/information system Period
Deaths for diarrheaa (A00 – A04 and A06 – A09)b and for malnutrition (E40 – E46)b and number of children under the age of five Mortality Information System (SIM) / Informatics Department of the Unified Health System (SUS) (DATASUS) Years 2006 to 2016
Beneficiary families of the Bolsa Família Program (PBF) Social Information Matrix (MIS) / Information Evaluation and Management Service (SAGI) Years 2006 to 2016
Average size of beneficiary families MIS / SAGI Years 2007 and 2010
Families eligible for the Bolsa Família Program (PBF) MIS / SAGI Years 2006 to 2016
Number of households with coverage for water and sanitation services and number of municipal households CENSO / IBGE Years 2000 and 2010c
Population exposed to solid waste collection and total municipal population CENSO / IBGE Years 2000 and 2010c
Per capita monthly income CENSO/IBGE Years 2000 and 2010c
Proportion of individuals without basic literacy among the population aged 15 and over CENSO / IBGE Years 2000 and 2010c
Urbanization rate IBGE Years 2000 and 2010c
Population served by primary care related to the Family Health Strategy (FHS) and total municipal population Primary Care Information System (SIAB) / DATASUS Years 2006 to 2016
  1. aOnly categories related to deaths due to diarrhea were also chosen, which were also classified as Diseases Related to Inadequate Environmental Sanitation (DRSAI) [46]. bInternational Statistical Classification Codes for Diseases and Health-Related Problems - 10th revision (CID-10). cFor variables with information only for the years related to the censuses, 2000 and 2010, interpolation (2006 to 2009) and linear extrapolation (2011 to 2016) methods were applied. For the income variable, due to its non-linear behavior [47], the variation of municipal Gross Domestic Product was used to predict the variation of municipal income and after this procedure, their values were corrected according to the Consumer Price Index Broad (IPCA)