Estimation of Under-5 Mortality by Wealth Quintile Fengqing Chao1, Danzhen You2, Jon Pedersen3, Lucia Hug2, Leontine Alkema4 1(Email: ephchf@nus.edu.sg), Saw Swee Hock School of Public Health, National University of Singapore. 2Division of Data, Research and Policy, UNICEF. 3Fafo Institute of Applied International Studies, Fafo. 4Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst. Poster 11833, Poster Session P3 – Data, Methods, and Professionalization, Population Association of America, Apr 27th 2017, Chicago Introduction Objective ▶Estimate the levels and trends of under-5 mortality rate (U5MR; probability of dying before age 5) by wealth quintile across countries from 1990 to 2015; ▶Estimate the relation between ratios of quintile-speciﬁc U5MR and the national-level U5MR (all quintiles combined); ▶Implement a reproducible statistical model; Wealth Quintiles ▶Refer to 5 equal-size birth groups with diﬀerent levels of socioeconomic status according to the wealth index assigned to each household; ▶1st wealth quintile = the poorest group; 5th wealth quintile = the richest group. Wealth Index ▶Computed based on selected questions asked in the Demographic Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS); ▶Indicator variables: any item that will reﬂect economic status: ▶Type of ﬂooring (dirt/cement/parquet)? Type of toilet (bush/ﬂush)? Has electricity? Number of members per sleeping room? etc. ▶Use principal component analysis (PCA) to assign the indicator weights, and get the weighted sum as the wealth index. Data Data Types # surveys DHS direct 208 MICS direct 17 MICS indirect 66 total 291 Table: Database for modeling. ‘Direct’: full birth history data. ‘Indirect’: summary birth history data. ▶95 countries with DHS and/or MICS survey data; ▶Each survey has 1 data point for each quintile; ▶Range of reference year: 1987 – 2011. Results 1985 1995 2005 2015 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Wealth Quintile Group 1 Quintile−specific / Total U5MR Country estimate Global expected 1985 1995 2005 2015 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Wealth Quintile Group 2 1985 1995 2005 2015 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Wealth Quintile Group 3 1985 1995 2005 2015 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Wealth Quintile Group 4 1985 1995 2005 2015 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Wealth Quintile Group 5 1985 1995 2005 2015 50 100 150 200 U5MR (deaths per 1000 livebirth) quintile−specific total 1985 1995 2005 2015 50 100 150 200 1985 1995 2005 2015 50 100 150 200 1985 1995 2005 2015 50 100 150 200 1985 1995 2005 2015 50 100 150 200 India 1985 1995 2005 2015 0.7 0.8 0.9 1.0 1.1 1.2 1.3 Wealth Quintile Group 1 Quintile−specific / Total U5MR Country estimate Global expected 1985 1995 2005 2015 0.7 0.8 0.9 1.0 1.1 1.2 1.3 Wealth Quintile Group 2 1985 1995 2005 2015 0.7 0.8 0.9 1.0 1.1 1.2 1.3 Wealth Quintile Group 3 1985 1995 2005 2015 0.7 0.8 0.9 1.0 1.1 1.2 1.3 Wealth Quintile Group 4 1985 1995 2005 2015 0.7 0.8 0.9 1.0 1.1 1.2 1.3 Wealth Quintile Group 5 1985 1995 2005 2015 100 150 200 250 300 U5MR (deaths per 1000 livebirth) quintile−specific total 1985 1995 2005 2015 100 150 200 250 300 1985 1995 2005 2015 100 150 200 250 300 1985 1995 2005 2015 100 150 200 250 300 1985 1995 2005 2015 100 150 200 250 300 Chad Model estimates and 90% CI for India and Chad. Row 1: ratio of wealth quintile-speciﬁc to national-level U5MR. Row 2: wealth quintile-speciﬁc and national-level U5MR. 0 20 40 60 80 1.0 1.5 2.0 2.5 3.0 Difference between U5MRQ1 and U5MRQ5 Ratio of U5MRQ1 to U5MRQ5 CMR CIV GHA HTI MWI MDA NAM NIC PRY ALB AZE BLZ BEN ERI GIN PSE TJK THA AFG ARM BLR BDI COL COG GAB GEO GUY MKD MDV MRT SRB SWZ SYR TUN UKR UZB ZMB AGO BGD BTN BOL BFA KHM CAF TCD COM COD DOM EGY GNQ ETH GMB GTM GNB HND IND IDN IRQ KEN KGZ LAO LSO LBR MDG MLI MNG MAR MOZ NPL NER NGA PAK PHL RWA STP SEN SLE SOM ZAF SSD SDN SUR TZA TLS TGO UGA VUT VNM YEM ZWE BRA JOR KAZ PER TUR G G G G G G South Asia CEE/CIS Sub−Saharan Africa Latin America and the Caribbean East Asia an