Abstract:
DHS surveys provide many indicators that are
used for program planning and monitoring.
Some of these are particularly sensitive and
attract attention when the results of a new
survey are released. This methodological
report focuses on six demographic indicators
of widespread interest: the Total Fertility
Rate (TFR), Infant Mortality Rate (IMR),
Under-five Mortality Rate (U5MR), the Adult
Female Mortality Rate (AFMP), the Adult Male
Mortality Probability (AMMP) and the Maternal
Mortality Ratio (MMR). It is not unusual for
the results of a new survey to be questioned
because they differ from another source. The
goal of this report is to provide guidance on
how to determine whether the estimates of
these important indicators are plausible and
consistent with other sources, or not
plausible.
Determining whether a DHS estimate is
consistent with other sources is usually a
matter of degree. Some differences are
expected for a variety of reasons. The report
includes a discussion of potential reasons
for discrepancies. The report then analyzes
51 surveys conducted since 2010. The DHS
estimates are systematically compared with
estimates of the TFR, AFMP, and AMMP from the
UN Population Division, estimates of the IMR
and U5MR from the UN’s Inter Agency Group for
Child Mortality Estimation (IGME), and MMR
estimates from the World Health Organization
(WHO). The structure of the comparisons can
be applied to other sources, although it is
always necessary to account for the potential
kinds of differences discussed earlier. Two
specific surveys provide focus for the
comparisons.
The report also illustrates a strategy for
comparing fertility rates computed from DHS
data with those from other sources. We
compare DHS fertility rate estimates with
those from Performance Monitoring and
Accountability 2020 (PMA2020) surveys,
explore the effect of a slightly different
methodology for computing rates on DHS
estimates, and simulate the effects of a
different sampling strategy and rate
estimation method on fertility rates. Using a
standard methodology, fertility rates
computed from PMA2020 data in five countries
showed a range of 5% to 22% difference in
TFRs and a 4% to 17% difference in adolescent
fertility rates compared to results from DHS
surveys conducted within a three-year
timespan.
To assess the effect of alternate measurement
on fertility rates from the exact same
survey, we used 256 DHS datasets to compare
the results of a 2-year 2-birth adjusted
estimation technique versus a 3-year n-birth
technique with the same data. Our results
show an average of only about one percentage
point difference in total fertility and
adolescent fertility rates from the same data
using the alternate technique. In addition to
measurement differences, it is important to
consider design effects of a different
cluster sample. In Ethiopia, we simulated
subsamples of DHS data with a cluster
distribution similar to a corresponding
PMA2020 survey and recomputed fertility rates
with a 2-year 2-birth adjusted estimation
technique. These combined differences in
sampling and methodology produced an average
of between 3 to 4% difference in rate
estimates but could plausibly produce as much
as a 10% difference in TFR and a 23%
difference in adolescent fertility rates.
Notably, since the PMA2020 cluster sample
sizes are larger than those used by DHS, this
simulation is likely an overestimate of the
effect of sampling differences.
Comparisons of DHS Estimates of Fertility and Mortality with Other Estimates (PDF, 1265K)