evaluation of mortality data collected from population censuses
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Evaluation of Mortality Data Collected from Population Censuses. United Nations Statistics Division. Outline of the presentation. 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 - PowerPoint PPT PresentationTRANSCRIPT
United Nations Sub-Regional Workshop on Census Data EvaluationPhnom Penh, Cambodia, 14-17 November 2011
Evaluation of Mortality Data Collected from Population Censuses
United Nations Statistics Division
United Nations Sub-Regional Workshop on Census Data EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 November 2011
Some basics about life table (1)
Age (x) nMx nqx lx nLx ex
0 0.005774 0.00579 100000 99707 79.1561
1 0.000284 0.001134 99581 398184 78.4879
5 9.32E-05 0.000466 99511 497465 74.5417
10 0.000166 0.000831 99475 497260 69.5677
… … … … … …
55 0.007521 0.036913 93619 462988 26.9352
60 0.011885 0.057709 91576 449140 22.4803
65 0.021682 0.102837 88080 429485 18.2733
70 0.037063 0.1696 83714 407728 14.096
75 0.059397 0.258588 79377 383688 9.72956
80 0.10245 0.407803 74098 354340 5.24461
85+ 0.179314 1 67638 34275 0.50674
United Nations Sub-Regional Workshop on Census Data EvaluationPhnom Penh, Cambodia, 14-17 November 2011
Some basics about life table (2)
nMx = period mortality rate = nxandxagedalivepersonsofnumberaverage
nxageandxagebetweendieddeaths
#
nqx = proportion of those people reaching their xth birthday who die before their (x+n)th birthday
lx = number of person who live to their xth 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 EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 November 2011
Survival of children ever born- Tabulation example, Turkey 2000
Source: Tabulated using data from United Nations Demographic Yearbook
Age Women Total CEB Total CSProportion of
deceased children
15 - 19 3518257 294628 281296 0.045
20 - 24 3263432 2078364 1991445 0.042
25 - 29 2918825 4522719 4312404 0.047
30 - 34 2457285 5700038 5395143 0.053
35 - 39 2400808 7036619 6563946 0.067
40 - 44 1985225 6707033 6131544 0.086
45 - 49 1658012 6394157 5722904 0.105
United Nations Sub-Regional Workshop on Census Data EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 November 2011
Survival of children ever born: Brass-type estimates (2)
Age group of mother in years Age group index Proportion of children dead approximates
15-19 1 q(1)
20-24 2 q(2)
25-29 3 q(3)
30-34 4 q(5)
35-39 5 q(10)
40-44 6 q(15)
45-49 7 q(20)
50-54 8 q(25)
55-59 9 q(30)
Empirical findings about child mortality
United Nations Sub-Regional Workshop on Census Data EvaluationPhnom Penh, Cambodia, 14-17 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): 109-128.
United Nations Sub-Regional Workshop on Census Data EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 November 2011
Survival of children ever born: Brass-type estimates (10)Turkey example again
q(5), Turkey 2000 census
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0.1
2000199919971995199319901987
United Nations Sub-Regional Workshop on Census Data EvaluationPhnom Penh, Cambodia, 14-17 November 2011
Survival of children ever born: Brass-type estimates (11)Comparison of multiple sources
q(5), Turkey
0.045
0.055
0.065
0.075
0.085
0.095
0.105
0.115
year
2000 census Brass 1990 census Brass
1998 TDHS 2003 DHS
United Nations Sub-Regional Workshop on Census Data EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 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 1st or 2nd 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 EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 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
Proportion of deceased children, Turkey
00.020.040.060.08
0.10.120.140.160.18
15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49
Age of mother
1990 census 1998 DHS 2000 census 2003 DHS
United Nations Sub-Regional Workshop on Census Data EvaluationPhnom Penh, Cambodia, 14-17 November 2011
Survival of children ever born – quality assessment (6) A rapid assessment: Burundi, 1990 census: CS and CEB data
Age Total women Average CEB Average CS CS/CEB
15 + 1483895 3.82 2.93 0.77
15 - 19 250329 0.07 0.07 0.89
20 - 24 229655 1.02 0.86 0.84
25 - 29 214467 2.75 2.28 0.83
30 - 34 187348 4.49 3.63 0.81
35 - 39 135551 5.62 4.51 0.80
40 - 44 97537 6.10 4.85 0.80
45 - 49 75526 6.23 4.89 0.79
50 - 54 76100 6.21 4.70 0.76
55 - 59 50817 6.22 4.58 0.74
60 - 64 53775 6.12 4.28 0.70
65 + 110062 6.07 3.82 0.63
Unknown 2728 4.47 3.37 0.76
Source: Graph produced based on data collected by the United Nations Demographic Yearbook
United Nations Sub-Regional Workshop on Census Data EvaluationPhnom Penh, Cambodia, 14-17 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 30-34 age group: the proportion of deceased among all children born to mother of 30-34 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
- 1990 census estimates of under-5 child mortality = 190 per 1000 for 1983
- UN Pop Division estimates for the period 1980-1985: 196 per 1000
- Slightly underestimates
Method: Rapid Assessment of Census Data on Children Born and Surviving, Griffith Feeney, 2009. http://www.demographer.com/rapid-assessment-of-ceb-and-cs-data/
United Nations Sub-Regional Workshop on Census Data EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 November 2011
Survival of children ever born – quality assessment (9) Existing external sources
- UN population division (World Population Prospect)
- UNICEF child mortality website (www.childmortality.org)
United Nations Sub-Regional Workshop on Census Data EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 November 2011
Household deaths in the last 12 months – adult mortality (4):Comparing age-specific death rates
Age specific death rate, Madagascar, Male
0
2
4
6
8
10
12
14
16
15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49
Age
Male, 1993 census Male, 1992 DHS Male, 1997 DHS
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 EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 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 EvaluationPhnom Penh, Cambodia, 14-17 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