Journal article
Does adjusting for recall in trend analysis affect coverage estimates for maternal and child health indicators? An analysis of DHS and MICS survey data
Background: The Demographic and Health
Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) are the
major data sources in low- and middle-income countries (LMICs) for
evaluating health service coverage. For certain maternal and child
health (MCH) indicators, the two surveys use different recall
periods: 5 years for DHS and 2 years for MICS. Objective: We
explored whether the different recall periods for DHS and MICS
affect coverage trend analyses as well as missing data and coverage
estimates. Designs: We estimated coverage, using proportions with
95% confidence intervals, for four MCH indicators: intermittent
preventive treatment of malaria in pregnancy, tetanus vaccination,
early breastfeeding and postnatal care. Trends in coverage were
compared using data from 1) standard 5-yearDHS and 2-year MICS
recall periods (unmatched) and 2) DHS restricted to 2-year recall
to match the MICS 2-year recall periods (matched). Linear
regression was used to explore the relationship between length of
recall, missing data and coverage estimates. Results: Differences
in coverage trends were observed between matched and unmatched data
in 7 of 18 (39%) comparisons performed. The differences were in the
direction of the trend over time, the slope of the coverage change
or the significance levels. Consistent trends were seen in 11 of
the 18 (61%) comparisons. Proportion of missing data was inversely
associated with coverage estimates in both short (2 years) and
longer (5 years) recall of the DHS (r0.3, p0.02 and r0.4, p0.004,
respectively). The amount of missing information was increased for
longer recall compared with shorter recall for all indicators
(significant odds ratios ranging between 1.44 and 7.43).
Conclusions: In a context where most LMICs are dependent on
population-based household surveys to derive coverage estimates,
users of these types of data need to ensure that variability in
recall periods and the proportion of missing data across data
sources are appropriately accounted for when trend analyses are
conducted
Authors
Languages
- English
Journal
Global Health Action
Volume
2016 Nov 7;9:32408. doi: 10.3402/gha.v9.32408. eCollection 2016.
Type
Journal article
Categories
- Data
Topic references
COV-METH-PUB