Di Disent ntang ngli ling ng S Sex-Di -Different ntials ls i - - PowerPoint PPT Presentation
Di Disent ntang ngli ling ng S Sex-Di -Different ntials ls i in De n Death R h Registration & n & Mortali lity E y Estima mates: : Preli limi mina nary F y Find nding ngs f from M m Morocco & & K Kuwait
Statistics Division, Economic and Social Commission for Western Asia United Nations Expert Group Meeting on Methodology for and Lessons Learned from CRVS Assessments Population Division, DESA, United Nations 3 November, 2016
2
Romesh Silva – UN DESA EGM, New York.
3 Source: Eastern Mediterranean Regional Office, World Health Organization, 2013.
Romesh Silva – UN DESA EGM, New York.
4
20 40 60 80 100 20 40 60 80 100 Under−five Mortality Rate Death Registration Completeness (%)
BAH EGY IRQ JOR KUW LBN MOR OMN QTR SAU PAL SDN SYR TUN UAE YEM
50 100 150 200 250 20 40 60 80 100 Adult Mortality Rate (45q15) Death Registration Completeness (%)
BAH EGY IRQ JOR KUW LBN MOR OMN QTR SAU PAL SDN SYR TUN UAE YEM
Romesh Silva – UN DESA EGM, New York.
5
Egypt Iraq Jordan Kuwait Lebanon Libya Morocco Oman Qatar Saudi Arabia Sudan Syria Tunisia United Arab Emirates Yemen Bahrain Palestine
Source: United Nations, Department of Economic and Social Affairs, Population Dicvision (2013), World Population Prospects: The 2012 Revision
Mortality Data Source for WPP 2012 Vital Registration Derived from Child Mortality Estimates Survey Data Indirect Estimates from Population Census
Romesh Silva – UN DESA EGM, New York.
6
7
To assess completeness and quality of recent death
Completeness: Proportion of all deaths (b/w ages 15-59) that were
Quality: whether the age, sex, geographic, temporal patterns in the
Understand current deficiencies in death registration as a first
Romesh Silva – UN DESA EGM, New York.
8
Reporting
ng b bias d due t to t termi mino nolo logical d l differenc nces
Reporting
ng b bias d due t to s social d l desirabili lity y
Misali
lignme nment nt b between r n referenc nce p popula lations ns
Large s
sampli ling ng e errors
Strong
ng a assumptions ns: : [1]
[1] closed population, [2] completeness of
recording of deaths is constant by age, [3] the completeness of recording of population is constant by age, & [4] error-free age reporting
Non-negligible uncertainty intervals (Murray et al., PLoSMed-2013)
4. 4.
Labor i
int ntens nsive & & T Techni hnically c lly cha halle lleng nging ng
Romesh Silva – UN DESA EGM, New York.
9
national populations:
population growth rates, the observed birth rate and the observed death rate to estimate the relative coverage of the population censuses along with the relative coverage of the death registration process.
future cohort deaths to the current cohort’s population size as a means to assessing the completeness of the death registration process during the intercensal time period.
available data to adjust the raw data followed by application of the SEG method to the GGB-adjusted data.
Romesh Silva – UN DESA EGM, New York.
10
national populations:
population growth rates, the observed birth rate and the observed death rate to estimate the relative coverage of the population censuses along with the relative coverage of the death registration process.
future cohort deaths to the current cohort’s population size as a means to assessing the completeness of the death registration process during the intercensal time period.
available data to adjust the raw data followed by application of the SEG method to the GGB-adjusted data.
Romesh Silva – UN DESA EGM, New York.
11
Romesh Silva – UN DESA EGM, New York.
12
0.0 0.5 1.0 1.5 2.0
Morocco
Age Group Age Ratio
5−9 10−14 15−19 20−24 25−29 30−34 35−39 40−44 45−49 50−54 55−59 60−64 65−69 70−74
Male Median Min Max Female Median Min Max
0.0 0.5 1.0 1.5 2.0
Kuwait
Age Group
5−9 10−14 15−19 20−24 25−29 30−34 35−39 40−44 45−49 50−54 55−59 60−64 65−69 70−74
Male Median Min Max Female Median Min Max
Romesh Silva – UN DESA EGM, New York.
13
100 200 300 400 500 600
Morocco
Age Group Sex Ratio (Males per 100 Females)
0−4 5−9 10−14 15−19 20−24 25−29 30−34 35−39 40−44 45−49 50−54 55−59 60−64 65−69 70−74 75−79 80+
Median Min Max
100 200 300 400 500 600
Kuwait
Age Group
0−4 5−9 10−14 15−19 20−24 25−29 30−34 35−39 40−44 45−49 50−54 55−59 60−64 65−69 70−74 75−79 80+
Median Min Max
Romesh Silva – UN DESA EGM, New York.
14
Romesh Silva – UN DESA EGM, New York.
15
16
0.5 1.0 1.5
Death registration completeness by age, male
c_5Nx aNx 15−19 25−29 35−39 45−49 55−59 65−69 75−79
aNx
−2 −1 1 −3 −2 −1 1
Observed vs. Fitted Logits, male
Ys(x) Y(x)
0.05 0.10 0.15
Smoothed vs. Adjusted Mortality Rates, male
Adjusted m_x Smoothed m_x 5−9 15−19 25−29 35−39 45−49 55−59 65−69 75−79 85+
0.5 1.0 1.5
Death registration completeness by age, female
c_5Nx aNx 15−19 25−29 35−39 45−49 55−59 65−69 75−79
aNx
−2 −1 1 −3 −2 −1 1
Observed vs. Fitted Logits, female
Ys(x) Y(x)
0.05 0.10 0.15
Smoothed vs. Adjusted Mortality Rates, female
Adjusted m_x Smoothed m_x 5−9 15−19 25−29 35−39 45−49 55−59 65−69 75−79 85+
17
0.2 0.4 0.6 0.8 1.0 1.2
Death registration completeness by age, male
c_5Nx aNx 15−19 25−29 35−39 45−49 55−59 65−69 75−79
aNx
−2 −1 1 −3 −2 −1 1
Observed vs. Fitted Logits, male
Ys(x) Y(x)
0.05 0.10 0.15 0.20
Smoothed vs. Adjusted Mortality Rates, male
Adjusted m_x Smoothed m_x 5−9 15−19 25−29 35−39 45−49 55−59 65−69 75−79 85+
0.2 0.4 0.6 0.8 1.0 1.2
Death registration completeness by age, female
c_5Nx aNx 15−19 25−29 35−39 45−49 55−59 65−69 75−79
aNx
−2 −1 1 −3 −2 −1 1
Observed vs. Fitted Logits, female
Ys(x) Y(x)
0.05 0.10 0.15 0.20
Smoothed vs. Adjusted Mortality Rates, female
Adjusted m_x Smoothed m_x 5−9 15−19 25−29 35−39 45−49 55−59 65−69 75−79 85+
18
19
20
21 Comparison Table of Adult Mortality Estimates (45q15) by Sex derived using the Adjusted SEG Method and those published in WPP, 2012
Romesh Silva – UN DESA EGM, New York.
22
Limited insight from application of DDMs
Published DR data only available for nationals (~1/3 of resident
population)
DDMs sensitive to reporting errors/bias given small pop size
Notable sex differential in DR completeness
Likely a rural phenomenon, but need internal migration data
Subjective-choice of age-trim Effects of assumption violations
Romesh Silva – UN DESA EGM, New York.
23 Ku
Kuwait: investigate the nature of census enumeration & examine sex-specific CoD data
Quantitative Study:
Evaluate Cause-of-Death (CoD) data from death register
small-scale record linkage study focused on young adult ages – linkable data source?
Mo
Morocco cco: investigate the nature of sex differentials in death registration in urban areas vs. rural areas
Quantitative Studies:
Replicate analysis using 2004 & 2014 Census data (and intercensal registration data)
Disaggregate by urban/rural (Census-2014 included migration questions)
Small-scale record linkage study – linking HH deaths in last 12-months (Census-2004) and registered deaths Qualitative Study: Incentives for DR (by sex)
Ethnographic work to understand patrilineal inheritance tradition and impact of recent changes to Moroccan Family Code
Relationship b/w Burial permit process in urban/rural areas and DR completeness sex-differences
Regiona
nal:
Expand completeness assessments beyond Morocco, Kuwait, Egypt, Bahrain
Application of DDMs in Jordan, Tunisia, Oman(?), Sudan
Develop small-scale record-linkage studies [Egypt, Jordan, Palestine] Coordination with 2020 Pop Census Round & HH survey programs
Inclusion of “HH deaths in last 12 months” question or kin-survival modules;
Inclusion of migration questions à for study of subnational variation Romesh Silva – UN DESA EGM, New York.
24
Romesh Silva, Ph.D. Demographic and Social Statistics Section Economic and Social Commission for Western Asia United Nations
Email: silva22@un.org Tel: +961-1-278-727 Twitter: @Romesh_Silva
Romesh Silva – UN DESA EGM, New York.