Transcript Maternal mortality

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Maternal Mortality
Liliana Carvajal
Vibeke Oestreich Nielsen
Armando H. Seuc
UNICEF
Statistics Norway
WHO
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BACKGROUND
MDG 5: Improve Maternal Health
Target 5.A: Reduce by three quarters, between
1990 and 2015, the maternal mortality ratio
– 5.1 Maternal mortality ratio (MMR)
– 5.2 Proportion of births attended by skilled health
personnel (SAB)
Target 5.B: Achieve, by 2015, universal access
to reproductive health
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– 5.3 Contraceptive prevalence rate
– 5.4 Adolescent birth rate
– 5.5 Antenatal care coverage
at least one visit and at least four visits
– 5.6 Unmet need for family planning
Maternal Mortality
Target 5.A: Reduce by three quarters, between
1990 and 2015, the maternal mortality ratio
– 5.1 Maternal mortality ratio
– 5.2 Proportion of births attended by skilled health
personnel
Initially updates every 5 year since 1990 by WHO,
UNICEF, UNFPA – The World Bank joined in 2005
–
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–
2008 update – An academic team at University of Berkeley in
collaboration with MMEIG
2010 update – idem
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MEASURING MATERNAL
MORTALITY
Trends in Maternal Mortality:
1990 to 2008
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Reviewed by the technical
advisory group (TAG) with
experts from academic
institutions: Berkeley,
Harvard, Hopkins, Texas,
Aberdeen, Umea, Statistics
Norway
Countries consulted for
comments on methodology
and additional input
Trends in Maternal Mortality:
1990 to 2010
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Reviewed by the technical
advisory group (TAG) with
experts from academic
institutions: Berkeley,
Harvard, Hopkins, Texas,
Aberdeen, Umea, Statistics
Norway
Countries consulted for
comments on methodology
and additional input
General framework of the maternal mortality
estimates 1990-2008 and 1990-2010
Levels and trends of maternal mortality between 1990
and 2008 for 172 countries (1990-2010 for 181
countries)
Hierarchical/multilevel linear regression model
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The model input data is the PMDF (proportion
maternal among all female deaths 15-49) adjusted for
completeness and definition
Covariates: the log(GDP), log(GFR) and SAB
The final output takes into account the maternal
mortality related with the HIV/AIDS
Definitions used
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Maternal death: “the death of a woman while
pregnant or within 42 days of termination of
pregnancy, irrespective of the duration and the
site of the pregnancy, from any cause related to
or aggravated by the pregnancy or its
management but not from accidental or
incidental causes.” ICD-10, WHO,1994
Pregnancy-related death: “the death of a woman
while pregnant or within 42 days of termination
of pregnancy”
Estimated measures
Maternal Mortality Ratio (MMR): Ratio of maternal
deaths in a period to live births (proxy for risky
events) in the same period (x 100,000).
Number of maternal deaths
PMDF: Proportion of maternal among female
deaths 15-49
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Lifetime risk of a maternal death: An estimate of
the likelihood that a woman who survives to age
15 will die of maternal causes
–
proportion of women reaching reproductive age who
would die of maternal causes, taking into account
competing causes
Input data to the model: PMDF
–
PMDF is considered less subject to under-reporting
than MMR (maternal and non-maternal deaths likely
to be under-reported to similar degree)
–
Maternal deaths as defined by ICD is difficult to
capture – usually all deaths in pregnancy measured
Efforts have been made to adjust for:
under reporting
–
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–
definition
For the model the HIV/AIDS component was taken
out from the PMDF; the HIV/AIDS component is
then added back after the model fitting
Input database
1990-2008: Database of 172 countries territories, from 1985 onwards
1990-2010: Database of 181 countries territories, from 1985 onwards
Nationally representative data
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=> focusing on sources where PMDF is
possible to compute
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METHODS OF DATA
COLLECTION, ESTIMATION
Sources of Data
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Civil registration systems with cause of death
assigned by attending physician
Household surveys with sibling histories
Sample vital registration systems
Reproductive Age Mortality Surveys (RAMOS): not
very common
Population censuses with questions on household
deaths
Hospital- or facility-based studies
Other
Data on maternal mortality:
availability
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Sources
Number Number of
of surveys country-years
Civil Registration
1891
1891 (2125*)
Surveys with Sibling
Histories
Population Censuses
105
819 (895*)
18
19 (19*)
Other (eg special surveys,
verbal autopsies,
surveillance)
Total
80
113 (161*)
2094
2842 (3200*)
*: 1990-2010 estimations
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Data available in the Region:
Afghanistan
Bangladesh
Bhutan
Cambodia
China
Indonesia
Iran
Lao
Mongolia
Myanmar
Nepal
Pakistan
Philippines
Thailand
Papua New Guinea
Group
B
B
B
B
B
B
B
B
C
B
B
B
B
B
C
A. Civil registration
characterized as
complete, with good
attribution of cause
of death
B. Countries lacking
good complete
registration data but
where other types of
data are available
C. No national data on
maternal mortality
General Problems with
Maternal Mortality Measurement
Rare events
–
–
National trends unstable
For household surveys requires very large samples
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Certain types of maternal deaths hard to identify
(especially abortion-related)
Non-VR methods tend to measure pregnancyrelated mortality PRMR
Civil Registration Data
WHO estimates that approx. 72 (out of 193)
member states have complete recording of
deaths
–
But not all have adequate cause of death data
Even in countries with complete VR,
classification of deaths as maternal is
problematic
–
Recent increase in MMR (47% 2002 to 2004) in US
due to change of death certificate
Issues:
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–
14 studies (confidential enquiries, record linkages) of
countries with complete registration: a median
underestimation of 0.5 true maternal deaths were
incorrectly recorded as non-maternal
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Household Surveys
With Sibling Histories
Key questions for sibling history:
– Each sibling listed individually
– Record sex
– Record age in completed years for surviving sibs
– Record year of death, age at death for dead sibs
– For deaths of women of reproductive age, 3 questions
about timing of death relative to pregnancy
Widely used by DHS program (41countries,65 surveys)
Issues:
– Measures pregnancy-related mortality
– Estimates are usually made for 7 years before survey
– May under-estimate overall mortality
Sample Vital Registration Systems
Special procedures in random sample of areas
(4,000+ in India, 160 in China)
Continuous monitoring of vital events plus 6monthly household survey (India)
Cause of death identified by verbal autopsy (VA)
(India) or case records plus VA (China)
Issues:
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–
Requires considerable administrative sophistication
– Cannot be implemented rapidly
– Needs periodic evaluation
RAMOS Studies
Starting point is complete listing of deaths of women
of reproductive age
–
–
–
Best starting point is close to complete VR
Key feature is triangulation among data sources (eg
church records, burial grounds) to identify missed deaths
May be done for a sample (but has to be large)
Each death is investigated in detail to determine
whether or not it was maternal
–
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Hospital, health facility records
– Household interviews
Issues:
–
–
Results may be no better than the frame of deaths
MMR also needs number of births
Censuses with Questions on Deaths
Population censuses can include questions on
deaths in households in defined recent reference
period
Reported deaths of reproductive aged women
trigger questions about the timing of death relative
to pregnancy
Issues:
–
–
–
–
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–
–
Pregnancy-related mortality
Census misses deaths in single-person households
Death of head of household may result in household breakup
Experience suggests there is almost always some underreporting
Need to evaluate carefully
No consensus as to the quality of the data obtained
Facility-Based Studies
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Useful for identifying areas for improved care
(confidential enquiries)
Potential for gold standard case identification
(case notes)
Facility deaths (and births) are selected on
characteristics that may not be known
Not readily generalizable to a national MMR
estimate
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ESTIMATION (MODELLING)
Modelling
Countries in Group A
– No modelling was
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used
– Essentially data from
CR were adjusted by a
1.5 factor
Countries in Groups B
and C
– Multilevel model was
used to predict PMDF
with GDP, GFR and
SAB as predictors
– Group C countries
«borrowed» from other
countries in the region
– PMDF was converted
into MMR
Input data to the model:
Adjustment by type of source
Adjustment for completeness of reporting
specified in relation to the type of data
–
CR system: Review of recent literature on
underestimation of maternal deaths in CR systems
adjustment by a factor of 1.5
–
Sibling histories: age-standardization,
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1.1 adjustment (underestimation of early pregnancy
deaths)
0.9, 0.85 adjustment (remove accidental deaths)
–
Other special studies (e.g., RAMOS):
1.1 adjustment
Covariates
GDP: gross domestic product PPP per capita, in
constant 2005 international dollar; the World
Bank series, complemented by other sources
GFR: general fertility rate, the number of births
in a population divided by the number of women
at reproductive ages; UNPD World Population
Prospects
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SAB: the proportion of deliveries with a skilled
attendant at birth from UNICEF database
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Covariates and the model
A time series of these three covariates were
constructed for the 1985-2008 (1985-2010) period
Time-matched average values of the covariates for
time intervals corresponding to the period of each
observation of the dependent variable PMDF were
computed
A hierarchical/multilevel model with three main
covariates, plus random effects for countries and
regions and an offset which will adjust the
denominator of PMDF for AIDS.
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Input data to the model:
Definition and HIV/AIDS adjustment
MODELLING OF PMDFna
PMDF=Y=dependent variable;
datapoints collected (n=680)
Cleaning process
Datapoints included (n=484)
unadjusted
PMDF
Cleaning, adjustments,
inter/extra-polations
MMR
Adjustments:
1. For all countries:
- including underreporting / misclassifications
(1.5 for VR; 1.1 for others)
2. For Groups B-C countries:
- excluding AIDS-related
[from numerator (*) and from
denominator (**)], and excluding
non-maternal from numerator
using π=10% or 15% (**)
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Covariates: GDP, GFR, SAB
(*): PMDFadj1=(PMDFadj0 – ũ v a) (1-π)δ
(**): offset term, i.e.
log(PMDFadj1) = b0 + j + k
+ b1 log(GDP) + b2 log(GFR)
+ b3 SAB + log(1‐a) + ε
Adjusted GDP, GFR, SAB
adjusted/observed
PMDFna
Multilevel
modelling
validation
Model fitting
PMDFna
predictions
1
Excluding AIDS-related
deaths from PMDF:
PMDFadj1=(PMDFadj0 – ũ v a) (1-π)δ
o removes from numerator
a = fraction of AIDS deaths among deaths to women aged 15-49
v = proportion of such AIDS deaths that occur during pregnancy (or within 42
days after delivery)
ũ = fraction “actually" counted as maternal
log(PMDFadj1) = b0 + j + k
+ b1 log(GDP) + b2 log(GFR)
+ b3 SAB + log(1‐a) + ε
o removes from denominator
AMDF = AIDS-adjusted (denominator) PMDF = (PMDFadj1)/(1-a)
Final estimates of PMDF:

PMDFa : splitting the UNAIDS estimate of total
AIDS deaths among women aged 15‐49;
PMDFa = u v a
a = fraction of AIDS deaths among deaths to women
aged 15-49
v = proportion of such AIDS deaths that occur during
pregnancy (or within 42 days after delivery)
u = fraction that “should be" counted as maternal

PMDF = PMDFna + PMDFa
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Uncertainty
Components of uncertainty include:
Any remaining bias in adjusted PMDF values
Uncertainty in model parameters (c, k, u, and pi)
Regression prediction uncertainty within the
PMDF model
Possible error in MMR conversion (estimated
births and deaths)
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Alternative models, covariates, etc.
What is new in 2008 and 2010
compared with 2005
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Trend estimates for countries
=> bigger database
Definition issue addressed
Maternal deaths related with HIV/AIDS taken
into account
Statistical model – more detailed
What is new in 2010 compared with 2008
Data availability:
– 3200 country-years of data in 2010 compared
with 2842 in 2008 (13% increase)
– Total female deaths in the reproductive age
were updated backward (routine updating
process by WHO)
Countries included:
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– 181 in 2010 vs. 172 in 2008. The population
cut-off for country inclusion was 100000 in
2010 vs. 250000 in 2008
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COUNTRY CONSULTATION
Country consultation
CL.33.2011 (8 December 2011):
– “Following WHO’s quality standards for data
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publication and prior to the official release of the
above estimates, WHO is consulting with its Member
States to review each individual country estimate in
order to identify and make use of primary data
sources that may not have been previously identified.”
Focal point identification and review. Comments
received during consultation.
Accepted amendments to data input
–
source of reference clearly identified