Analyzing Health Equity Using Household Survey Data Lecture 3 Health Outcome #1: Child Survival “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy.
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Analyzing Health Equity Using Household Survey Data Lecture 3 Health Outcome #1: Child Survival “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity Child mortality • Infant mortality rate (IMR) – no. of deaths in the first year of life per 1000 live births • Under-five mortality rate (U5MR) – no. of deaths in first 5 years per 1000 live births “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity Data for estimation of child mortality • Vital registration statistics often incomplete, unreliable or not linked to socioeconomic status data • IMR & U5MR estimated from fertility histories in survey data – Complete fertility history – dates of all births/child deaths to woman of fertile age – Incomplete fertility history – no. children born to woman and no. still alive • Complete fertility history requires more data but less assumptions and gives standard errors • Incomplete fertility history requires less data but must impose a model life table and does not give standard errors “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity Computing survival time from complete fertility histories • Create a variable to indicate the interview date (intrvdate2) • Create a vbl to indicate the date-of-birth of each child (dob) • From intrvdate2 and dob, compute the age each child would be at interview if alive (hypagedays) • Choose a reference period for births – 5 or 10 years before interview date – and select on hypagedays accordingly • Create a vbl to indicate vital status of each child (dead) • From hypagedays, dead and date of death compute the survival time of each child until death or interview (timeyears) “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity Estimating mortality rates • From hypagedays, dead and timeyears, a life table can be estimated • In Stata, ltable timeyears dead if hypageyrs <=10 , int(.5) gr “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity Life Table, Vietnam 1988–98 Interval 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 Total 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 Deaths 5316 5008 4832 4644 4450 4237 4049 3809 3582 3347 3063 2742 2480 2214 1926 1626 1303 972 623 324 1 114 15 12 4 15 0 13 0 4 0 7 0 3 0 3 0 0 0 1 0 0 Lost Survival 194 161 176 190 198 188 227 227 231 284 314 262 263 288 297 323 331 349 298 323 1 0.9782 0.9752 0.9727 0.9719 0.9685 0.9685 0.9653 0.9653 0.9642 0.9642 0.9619 0.9619 0.9606 0.9606 0.9590 0.9590 0.9590 0.9590 0.9570 0.9570 0.9570 Error 0.0020 0.0022 0.0023 0.0023 0.0025 0.0025 0.0026 0.0026 0.0027 0.0027 0.0028 0.0028 0.0029 0.0029 0.0030 0.0030 0.0030 0.0030 0.0036 0.0036 0.0036 [95% Conf. Int.] 0.9738 0.9706 0.9679 0.9670 0.9633 0.9633 0.9598 0.9598 0.9586 0.9586 0.9560 0.9560 0.9546 0.9546 0.9527 0.9527 0.9527 0.9527 0.9493 0.9493 0.9493 0.9818 0.9791 0.9768 0.9760 0.9730 0.9730 0.9701 0.9701 0.9690 0.9690 0.9670 0.9670 0.9659 0.9659 0.9645 0.9645 0.9645 0.9645 0.9636 0.9636 0.9636 “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity .98 .97 .96 .95 Proportion Surviving Survival Function with 95 Percent Confidence Intervals, Vietnam 1988–98 0 2 4 6 timeyears 8 10 “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity Indirect mortality estimation from incomplete fertility histories • Incomplete fertility histories give the no. of kids born to each woman and the no. surviving • A model life table is then superimposed on these data to estimate mortality rates • The latter step can be done using QFIVE • QFIVE requires, for each of 7 age groups: # women, # kids born, # kids surviving “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity QFIVE’s Reproduction of Input Data for South Africa 1 INPUT DATA FOR S Africa BOTH SEXES ENUMERATION DATE: JUN 1993 --------Age Group of Women --------15-19 20-24 25-29 30-34 35-39 40-44 45-49 --------Number of Women --------2034. 2063. 1683. 1479. 1250. 1099. 853. --------Number of Children Ever Born --------312. 1608. 2841. 3948. 4294. 4391. 3734. --------Number of Children Surviving --------290. 1469. 2554. 3490. 3744. 3794. 3186. MEAN AGE AT MATERNITY WAS NOT GIVEN. THE DEFAULT VALUE OF 27.0 WILL BE USED. “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity Indirect Estimates of Child Mortality, South Africa COALE-DEMENY: NORTH SOUTH EAST WEST ------------------------------------------------------------------------------------------------ -------------------AGE OF REFERENCE REFERENCE REFERENCE REFERENCE WOMAN DATE q DATE q DATE q DATE q ------------------------------------------------------------------------------------------------------------- ------INFANT MORTALITY RATE: q(1) 15-19 20-24 25-29 30-34 35-39 40-44 45-49 1992.2 1991.0 1989.3 1987.4 1985.2 1982.8 1980.0 .065 .069 .071 .074 .075 .073 .071 1992.2 1991.0 1989.2 1987.2 1984.9 1982.3 1979.2 .063 .076 .081 .087 .091 .092 .092 1992.2 1990.9 1989.1 1987.0 1984.7 1982.1 1978.9 .070 .079 .085 .092 .097 .097 .097 1992.2 1990.9 1989.2 1987.1 1984.9 1982.4 1979.5 .068 .075 .079 .084 .086 .085 .084 ------------------------------------------------------------------------------------------------ -------------------PROBABILITY OF DYING BETWEEN AGES 1 AND 5: 15-19 20-24 25-29 30-34 35-39 40-44 45-49 1992.2 1991.0 1989.3 1987.4 1985.2 1982.8 1980.0 .039 .042 .043 .046 .047 .045 .043 q 4 1 1992.2 1991.0 1989.2 1987.2 1984.9 1982.3 1979.2 .018 .026 .031 .036 .040 .041 .041 1992.2 1990.9 1989.1 1987.0 1984.7 1982.1 1978.9 .018 .022 .025 .029 .031 .031 .031 1992.2 1990.9 1989.2 1987.1 1984.9 1982.4 1979.5 .027 .031 .034 .038 .039 .039 .038 --------------------------------------------------------------------------------------------------- ----------------PROBABILITY OF DYING BY AGE 5: 15-19 20-24 25-29 30-34 35-39 40-44 45-49 1992.2 1991.0 1989.3 1987.4 1985.2 1982.8 1980.0 q(5) .101 .108 .111 .116 .119 .115 .112 1992.2 1991.0 1989.2 1987.2 1984.9 1982.3 1979.2 .079 .100 .109 .120 .128 .128 .130 1992.2 1990.9 1989.1 1987.0 1984.7 1982.1 1978.9 .086 .099 .108 .118 .124 .125 .125 1992.2 1990.9 1989.2 1987.1 1984.9 1 982.4 1979.5 .093 .104 .110 .118 .122 .121 .119 ======================================================================================= ============================== NOTE: A q VALUE OF .999 DENOTES VALUE BELOW A LEVEL 1 MODEL LIFE TABLE " .000 " ABOVE A LEVEL 25 " “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity Indirect Estimates of U5MR using alternative model life tables, South Africa 0.14 0.12 0.10 North South East West U5MR 0.08 0.06 0.04 0.02 0.00 1978 1980 1982 1984 1986 1988 1990 1992 1994 “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity