United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Evaluation of Mortality Data Collected from Population Censuses United Nations Statistics Division

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Some basics about life table For two items that can be used to obtain mortality statistics in census: -Survival of children ever born -Deaths in the household We discuss -Information collected -Possible quality issues related to each question -Methods of data evaluation using examples Outline of the presentation

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Some basics about life table (1) Age (x)nMxnqxlxnLxex E ………………

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Some basics about life table (2) nMx = period mortality rate = nqx = proportion of those people reaching their x th birthday who die before their (x+n) th birthday lx = number of person who live to their x th birthday nLx = number of person-years lived between exact ages x and x+n ex = life expectancy at age x (the average number of years which people have left to live when they are at age x)

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Model life tables Created to estimate demographic parameters for countries with limited data Built on empirical studies of age-specific mortality patterns in the past Two groups of model life tables: Coale-Demeny: based on European populations North, South, East and west European models United Nations: For developing countries Latin American, Chilean, South Asian, Far Eastern, General Some basics about life table (3)

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Mortality statistics from population census – Introduction A group of questions can be used to obtain mortality data in a census Two distinctions: a)Level and trend of mortality vs age pattern of mortality Survival of children ever born: level and trend of mortality Household deaths: age pattern of mortality: b)Deaths of younger persons vs. deaths of adults Younger persons: survival of children ever born Adults: household deaths All approaches are to supplement death registration data, not to replace it.

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Have been used for the past 50 years to collect data on infant and child mortality For every woman the following information are collected: a) the total number of female children she has borne in her lifetime. b) the total number of male children she has borne in her lifetime. c) the number of female children who are surviving d) the number of male children who are surviving Survival of children ever born – information collected

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born – Use of Ever born – Surviving = Children deceased Children deceased / Ever born = Proportion deceased Life table measures of infant, child and young adult mortality may be derived from the proportion of deceased.

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born - Tabulation example, Turkey 2000 Source: Tabulated using data from United Nations Demographic Yearbook AgeWomenTotal CEBTotal CS Proportion of deceased children

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Data are used to estimate level and trend of mortality for about 20 years prior to a census or survey. Survival of children ever born – Brass type estimates (1)

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born: Brass-type estimates (2) Age group of mother in yearsAge group index Proportion of children dead approximates q(1) q(2) q(3) q(5) q(10) q(15) q(20) q(25) q(30) Empirical findings about child mortality

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born - Brass-type estimates (3) -Approximation -q values referring to different time period before census -q(1): more recent estimates; q(20) – earlier estimates (Feeney, 1980) -Under-five mortality is used more often: more robust than infant mortality -However if comparing estimates with civil registration, may use infant mortality rate Empirical findings about child mortality Feeney 1980: Estimating infant mortality trends from child survivorship data, Population Studies 34(1):

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born: Brass-type estimates (4) -Under-five mortality -Most commonly used -more robust than infant mortality -Upward biases from reports of younger women, usually inaccurate -More powerful results (Brass type) came from multiple data sources Empirical findings about child mortality

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born: Brass-type estimates (5) An example of MortPak CEBCS output

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born: Brass-type estimates (5) An example of MortPak CEBCS output (cont.)

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born: Brass-type estimates (6) How to identify the right mortality model - graphical Source: Step by step guide to the estimation of child mortality, 1990, United Nations

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born: Brass-type estimates (7) How to identify the right mortality model – graphical Source: Step by step guide to the estimation of child mortality, 1990, United Nations

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born: Brass-type estimates (8) Illustration of the relationship of mother’s age and timing of the under-5 mortality estimates Source: Step by step guide to the estimation of child mortality, 1990, United Nations Bangladesh, 1974 Retrospective Survey of Fertility and Mortality

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born: Brass-type estimates (9) q(5) more robust than q(1) Source: Step by step guide to the estimation of child mortality, 1990, United Nations Infant and under-five mortality, Bangladesh

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born: Brass-type estimates (10) Turkey example again

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born: Brass-type estimates (11) Comparison of multiple sources

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 A few notes about Brass type estimates Almost smooth due to modeling If see rough and unsmooth data, indicates quality issues The last increase of q(5) does not mean increasing mortality, but rather biases generated from mother of young age groups (15-19) There is violation of assumptions about age patterns in the method, i.e., child death depends on children’s age only. But children born to very young mothers tend to be disadvantaged

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Experience has shown that it is possible to get high quality responses to this kind of questions in any data collection exercise, including censuses. If both CEB and CS are understated, some cancellation of errors will occur. But in practice, reporting of CS is more likely to be complete than reporting of CEB => calculated proportions of deceased children are likely to be too low. Survival of children ever born – quality (1)

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Other influences on the accuracy of estimates derived from these data: Assumptions about the age pattern of mortality: mortality of child relies only on their own age (which will fail at young age of mothers, i.e., the 1 st or 2 nd age groups of mothers) In the ideal case, data on CEB and CS will be available from two or more data collection exercises, at different points in time. This will allow comparison, providing a powerful test of the quality of the estimates. Survival of children ever born – quality (2)

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born – quality assessment (1) -Initial assessment: -Any missing values in children surviving data? -Missing values for any relevant variables: age of mother, sex of those who died -Plausibility of data -Children survival data; age distribution -Distribution of women with socio-economic characteristics

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born – quality assessment (2) “… systematic failure in data collection…” Source: Estimation of mortality using the South African Census 2001 data, Dorrington, Moultrie and Timæus, Centre of Actuarial Research, University of Cape Town, 2001 Example: missing or implausible values of CEB and CS data

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born – quality assessment (5) Comparing age patterns of proportion deceased children Source: Graph produced based on data collected by the United Nations Demographic Yearbook and Measure DHS country report

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born – quality assessment (6) A rapid assessment: Burundi, 1990 census: CS and CEB data AgeTotal womenAverage CEBAverage CSCS/CEB Unknown Source: Graph produced based on data collected by the United Nations Demographic Yearbook

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born – quality assessment (7) A rapid assessment of CEB and CS data - (1-0.81)=0.19 for the age group: the proportion of deceased among all children born to mother of years of age ≈ q(5), the proportion of children born who die before their 5th birthday 7 years prior to census -Compare with other estimates, e.g., UN Population Division estimates of under-5 mortality census estimates of under-5 child mortality = 190 per 1000 for UN Pop Division estimates for the period : 196 per Slightly underestimates Method : Rapid Assessment of Census Data on Children Born and Surviving, Griffith Feeney,

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born – quality assessment (8) Comparing with UN Population Division under-five mortality estimates Source: World Population Prospects: The 2010 Revision

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Survival of children ever born – quality assessment (9) Existing external sources -UN population division (World Population Prospect) -UNICEF child mortality website (

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Household deaths in the last 12 months – adult mortality (1) - Direct estimates of current death rates can be obtained, however, with substantial errors -Under-reporting, especially for child deaths and older age deaths -Reference period errors in reporting of deaths (versus the usual 12 months reference period) -Death question omitted by interviewers -Household breaking up due to the death of a senior household member -Age-heaping and age exaggeration -The method is mainly used for adult mortality

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Household deaths in the last 12 months – adult mortality (2) Initial assessment Tabulation of enumerated deaths with associated variables, e.g., year/month of death Quality of age reporting for the deceased

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Household deaths in the last 12 months – adult mortality (4): Comparing age-specific death rates Source: Graph produced based on data collected by the United Nations Demographic Yearbook and Measure DHS country report

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Household deaths in the last 12 months – adult mortality (3) Assessment: death distribution methods General Growth Balance (GGB), assumes constant coverage of household deaths and population across all ages (this would not work for children deaths) Negligible migration Stable population (constant births and deaths) Accurate reporting of age for both population and deaths Synthetic Extinct Generations method (SEG), assumes All the above, except for stable population assumption was relaxed in later version Constant coverage of population across time (may be relaxed if use a “combined GGB-SEG approach”)

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Household deaths in the last 12 months – adult mortality (4) Assessment: example of GGB method

United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Household deaths in the last 12 months – adult mortality (5) Assessment: example of GGB method f: slope of the fitted line (1/f)*100% = 41.2%  only 41.2% of the deaths were being reported