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DSS and DHS: longitudinal and cross-sectional viewpoints on child and adolescent mortality in Ethiopia.

Byass P, Worku A, Emmelin A, Berhane Y - Popul Health Metr (2007)

Bottom Line: Patterns of mortality over time were broadly comparable using DSS and DHS approaches.Both DSS and DHS approaches to mortality surveillance gave similar overall results, but both showed method-dependent advantages and disadvantages.In many settings, this kind of joint-source data analysis could offer significant added value to results.

View Article: PubMed Central - HTML - PubMed

Affiliation: Umeå International School of Public Health, Umeå University, Umeå, Sweden. peter.byass@epiph.umu.se.

ABSTRACT

Background: In countries where routine vital registration data are scarce, Demographic Surveillance Sites (DSS: locally defined populations under longitudinal surveillance for vital events and other characteristics) and Demographic and Health Surveys (DHS: periodic national cluster samples responding to cross-sectional surveys) have become standard approaches for gathering at least some data. This paper aims to compare DSS and DHS approaches, seeing how they complement each other in the specific instance of child and adolescent mortality in Ethiopia.

Methods: Data from the Butajira DSS 1987-2004 and the Ethiopia DHS rounds for 2000 and 2005 formed the basis of comparative analyses of mortality rates among those aged under 20 years, using Poisson regression models for adjusted rate ratios.

Results: Patterns of mortality over time were broadly comparable using DSS and DHS approaches. DSS data were more susceptible to local epidemic variations, while DHS data tended to smooth out local variation, and be more subject to recall bias.

Conclusion: Both DSS and DHS approaches to mortality surveillance gave similar overall results, but both showed method-dependent advantages and disadvantages. In many settings, this kind of joint-source data analysis could offer significant added value to results.

No MeSH data available.


Related in: MedlinePlus

Cumulative under-5 year child mortality and infant mortality rates from Ethiopian 2000 and 2005 DHS and BRHP DSS data, in 5-year periods from DHS survey rounds. DHS 2000 and 2005 figures are taken from DHS reports [4,5]; DHS adjusted figures from a Poisson regression model of combined 2000 and 2005 DHS data; and BRHP DSS results from the same Poisson regression model, adjusted for age-group, sex and urban-rural residence.
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Figure 2: Cumulative under-5 year child mortality and infant mortality rates from Ethiopian 2000 and 2005 DHS and BRHP DSS data, in 5-year periods from DHS survey rounds. DHS 2000 and 2005 figures are taken from DHS reports [4,5]; DHS adjusted figures from a Poisson regression model of combined 2000 and 2005 DHS data; and BRHP DSS results from the same Poisson regression model, adjusted for age-group, sex and urban-rural residence.

Mentions: Comparisons of the DSS and DHS results for infant and cumulative under-5 year child mortality are shown in Figure 2. DHS figures from the 2000 and 2005 rounds are shown as presented in DHS reports (and thus using standard DHS methods for weighting, etc.) [4-6], compared with adjusted values based on the Poisson regression model described above (combined 2000 and 2005 DHS and the 18-year DSS data). Direct contemporaneous comparisons of DHS mortality shown in Figure 2 between the two survey rounds, with an additional 5 years of recall, suggest that the effects of recall bias may have led to underestimates of infant and under-5 mortality by between 14% and 27% over 5 years.


DSS and DHS: longitudinal and cross-sectional viewpoints on child and adolescent mortality in Ethiopia.

Byass P, Worku A, Emmelin A, Berhane Y - Popul Health Metr (2007)

Cumulative under-5 year child mortality and infant mortality rates from Ethiopian 2000 and 2005 DHS and BRHP DSS data, in 5-year periods from DHS survey rounds. DHS 2000 and 2005 figures are taken from DHS reports [4,5]; DHS adjusted figures from a Poisson regression model of combined 2000 and 2005 DHS data; and BRHP DSS results from the same Poisson regression model, adjusted for age-group, sex and urban-rural residence.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2235826&req=5

Figure 2: Cumulative under-5 year child mortality and infant mortality rates from Ethiopian 2000 and 2005 DHS and BRHP DSS data, in 5-year periods from DHS survey rounds. DHS 2000 and 2005 figures are taken from DHS reports [4,5]; DHS adjusted figures from a Poisson regression model of combined 2000 and 2005 DHS data; and BRHP DSS results from the same Poisson regression model, adjusted for age-group, sex and urban-rural residence.
Mentions: Comparisons of the DSS and DHS results for infant and cumulative under-5 year child mortality are shown in Figure 2. DHS figures from the 2000 and 2005 rounds are shown as presented in DHS reports (and thus using standard DHS methods for weighting, etc.) [4-6], compared with adjusted values based on the Poisson regression model described above (combined 2000 and 2005 DHS and the 18-year DSS data). Direct contemporaneous comparisons of DHS mortality shown in Figure 2 between the two survey rounds, with an additional 5 years of recall, suggest that the effects of recall bias may have led to underestimates of infant and under-5 mortality by between 14% and 27% over 5 years.

Bottom Line: Patterns of mortality over time were broadly comparable using DSS and DHS approaches.Both DSS and DHS approaches to mortality surveillance gave similar overall results, but both showed method-dependent advantages and disadvantages.In many settings, this kind of joint-source data analysis could offer significant added value to results.

View Article: PubMed Central - HTML - PubMed

Affiliation: Umeå International School of Public Health, Umeå University, Umeå, Sweden. peter.byass@epiph.umu.se.

ABSTRACT

Background: In countries where routine vital registration data are scarce, Demographic Surveillance Sites (DSS: locally defined populations under longitudinal surveillance for vital events and other characteristics) and Demographic and Health Surveys (DHS: periodic national cluster samples responding to cross-sectional surveys) have become standard approaches for gathering at least some data. This paper aims to compare DSS and DHS approaches, seeing how they complement each other in the specific instance of child and adolescent mortality in Ethiopia.

Methods: Data from the Butajira DSS 1987-2004 and the Ethiopia DHS rounds for 2000 and 2005 formed the basis of comparative analyses of mortality rates among those aged under 20 years, using Poisson regression models for adjusted rate ratios.

Results: Patterns of mortality over time were broadly comparable using DSS and DHS approaches. DSS data were more susceptible to local epidemic variations, while DHS data tended to smooth out local variation, and be more subject to recall bias.

Conclusion: Both DSS and DHS approaches to mortality surveillance gave similar overall results, but both showed method-dependent advantages and disadvantages. In many settings, this kind of joint-source data analysis could offer significant added value to results.

No MeSH data available.


Related in: MedlinePlus