Measuring Under-Five Mortality: Validation of New Low-Cost Methods

English version České info

Background:
There has been increasing interest in measuring under-five mortality as a health indicator and as a critical measure of human development. In countries with complete vital registration systems that capture all births and deaths, under-five mortality can be directly calculated. In the absence of a complete vital registration system, however, child mortality must be estimated using surveys that ask women to report the births and deaths of their children. Two survey methods exist for capturing this information: summary birth histories and complete birth histories. A summary birth history requires a minimum of only two questions: how many live births has each mother had and how many of them have survived. Indirect methods are then applied using the information from these two questions and the age of the mother to estimate under-five mortality going back in time prior to the survey. Estimates generated from complete birth histories are viewed as the most accurate when surveys are required to estimate under-five mortality, especially for the most recent time periods. However, it is much more costly and labor intensive to collect these detailed data, especially for the purpose of generating small area estimates. As a result, there is a demand for improvement of the methods employing summary birth history data to produce more accurate as well as subnational estimates of child mortality.

Methods and Findings:
We used data from 166 Demographic and Health Surveys (DHS) to develop new empirically based methods of estimating under-five mortality using children ever born and children dead data. We then validated them using both in- and out-of-sample analyses. We developed a range of methods on the basis of three dimensions of the problem: (1) approximating the average length of exposure to mortality from a mother's set of children using either maternal age or time since first birth; (2) using cohort and period measures of the fraction of children ever born that are dead; and (3) capturing country and regional variation in the age pattern of fertility and mortality. We focused on improving estimates in the most recent time periods prior to a survey where the traditional indirect methods fail. In addition, all of our methods incorporated uncertainty. Validated against under-five estimates generated from complete birth histories, our methods outperformed the standard indirect method by an average of 43.7% (95% confidence interval [CI] 41.2–45.2). In the 5 y prior to the survey, the new methods resulted in a 53.3% (95% CI 51.3–55.2) improvement. To illustrate the value of this method for local area estimation, we applied our new methods to an analysis of summary birth histories in the 1990, 2000, and 2005 Mexican censuses, generating subnational estimates of under-five mortality for each of 233 jurisdictions.

Conclusions:
The new methods significantly improve the estimation of under-five mortality using summary birth history data. In areas without vital registration data, summary birth histories can provide accurate estimates of child mortality. Because only two questions are required of a female respondent to generate these data, they can easily be included in existing survey programs as well as routine censuses of the population. With the wider application of these methods to census data, countries now have the means to generate estimates for subnational areas and population subgroups, important for measuring and addressing health inequalities and developing local policy to improve child survival.

: Please see later in the article for the Editors' Summary

Vyšlo v časopise: Measuring Under-Five Mortality: Validation of New Low-Cost Methods. PLoS Med 7(4): e32767. doi:10.1371/journal.pmed.1000253
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pmed.1000253

Souhrn

Zdroje

1. United Nations 1990 World declaration on the survival, protection and development of children and plan of action for implementing the world declaration on the survival, protection and development of children in the 1990s: World summit for children. New York: UN Publications. Available: http://www.unicef.org/wsc/plan.htm. Accessed 27 August 2009

2. MurrayCJ

LaaksoT

ShibuyaK

HillK

LopezAD

2007 Can we achieve Millennium Development Goal 4? New analysis of country trends and forecasts of under-5 mortality to 2015. Lancet 370 1040 1054

3. BlackRE

MorrisSS

BryceJ

2003 Where and why are 10 million children dying every year? Lancet 361 2226 2234

4. BryceJ

elAS

PariyoG

LanataC

GwatkinD

2003 Reducing child mortality: can public health deliver? Lancet 362 159 164

5. ClaesonM

GillespieD

MshindaH

TroedssonH

VictoraCG

2003 Knowledge into action for child survival. Lancet 362 323 327

6. JonesG

SteketeeRW

BlackRE

BhuttaZA

MorrisSS

2003 How many child deaths can we prevent this year? Lancet 362 65 71

7. VictoraCG

WagstaffA

SchellenbergJA

GwatkinD

ClaesonM

2003 Applying an equity lens to child health and mortality: more of the same is not enough. Lancet 362 233 241

8. BryceJ

DaelmansB

DwivediA

FauveauV

LawnJE

2008 Countdown to 2015 for maternal, newborn, and child survival: the 2008 report on tracking coverage of interventions. Lancet 371 1247 1258

9. MasanjaH

deSD

SmithsonP

SchellenbergJ

JohnT

2008 Child survival gains in Tanzania: analysis of data from demographic and health surveys. Lancet 371 1276 1283

10. GakidouE

HoganM

LopezAD

2004 Adult mortality: time for a reappraisal. Int J Epidemiol 33 710 717

11. Canadian International Development Agency 2009 The Catalytic Initiative to Save a Million Lives. Available: http://www.acdi-cida.gc.ca/CIDAWEB/acdicida.nsf/En/NAD-1249841-JLG. Accessed 27 February 2009

12. GadomskiA

BlackR

MosleyH

1990 Constraints to the potential impact of child survival in developing countries. Health Policy Plan 5 235 245

13. MulhollandK

2005 Commentary: comorbidity as a factor in child health and child survival in developing countries. Int J Epidemiol 34 375 377

14. MathersCD

FatDM

InoueM

RaoC

LopezAD

2005 Counting the dead and what they died from: an assessment of the global status of cause of death data. Bull World Health Organ 83 171 177

15. China State Family Planning Commission 1991 National sample survey of fertility and contraception. Seattle Population Research Center Working Paper No. 3. Seattle (Washington): University of Washington

16. International Institute for Population Sciences 2008 District Level Household and Facility Survey (Reproductive and Child Health Project). Available: http://www.rchiips.org/index.html. Accessed 2 December 2008

17. HuqMN

ClelandJ

1990 Bangladesh fertility survey, 1989 Dhaka, Bangladesh National Institute of Population Research and Training

18. Macro International Inc MEASURE DHS. Demographic and Health Surveys. Calverton (Maryland). Available: http://www.measuredhs.com/. Accessed 28 August 2009

19. ArnoldF

1990 Assessment of the quality of birth history data in the demographic and health surveys. Methodological Reports No. 1: An assessment of DHS-I data quality: 81–111 Columbia (Maryland) Institute for Resource Development, Inc

20. CurtisSL

1995 Assessment of the quality of data used for direct estimation of infant and child mortality in DHS-II surveys. Occasional Papers No. 3 Calverton (Maryland) Macro International Inc

21. HillK

LopezAD

ShibuyaK

JhaP

2007 Interim measures for meeting needs for health sector data: births, deaths, and causes of death. Lancet 370 1726 1735

22. MyburghCA

1956 Estimating the fertility and mortality of African populations from the total number of children ever born and the number of these still living. Popul Stud 10 193 206

23. BrassW

CoaleAJ

1968 Methods of analysis and estimation.

BrassW

CoaleAJ

DemenyP

HeiselDF

LorimerF

The demography of tropical Africa Princeton (New Jersey) Princeton University Press

24. TrussellTJ

1975 A re-estimation of the multiplying factors for the Brass technique for determining childhood survivorship rates. Popul Stud 29 97 107

25. EwbankDC

1982 The sources of error in Brass's method for estimating child survival: the case of Bangladesh. Popul Stud 36 459 474

26. FeeneyG

1980 Estimating infant mortality trends from child survivorship data. Popul Stud 34 109 128

27. KralyEP

NorrisDA

1978 An evaluation of Brass mortality estimates under conditions of declining mortality. Demography 15 549 557

28. SullivanJM

1972 Models for the estimation of the probability of dying between birth and exact ages of early childhood. Popul Stud 26 79 97

29. HillK

FigueroaME

2001 Child mortality estimation by time since first birth.

ZabaB

BlackerJ

Brass tacks London Athlone Press

30. United Nations 1983 Manual X: indirect techniques for demographic estimation. Population studies No. 81 New York United Nations Department of International Economic and Social Affairs

31. CollumbienM

SloggettA

2001 Adjustment methods for bias in the indirect childhood mortality estimates.

ZabaB

BlackerJ

Brass Tacks London Athlone Press

32. National Population Commission 1999 Appendix C. Nigeria Demographic and Health Survey 1999. Calverton (Maryland): National Population Commission and ORC/Macro. Available: http://www.measuredhs.com/pubs/pdf/FR115/17AppendixC.pdf. Accessed 27 February 2009

33. GarenneM

GakusiE

2006 Health transitions in sub-Saharan Africa: overview of mortality trends in children under 5 years old (1950-2000). Bull World Health Organ 84 470 478

34. ClevelandWS

LoaderCL

1996 Smoothing by local regression: principles and methods.

HaerdleW

SchimekMG

Statistical theory and computational aspects of smoothing New York Springer

35. KingG

TomzM

WittenbergJ

2000 Making the most of statistical analyses: improving interpretation and presentation. Am J Polit Sci 341 355

36. United Nations Population Division 1990 QFIVE New York United Nations, Department of International Economic and Social Affairs

37. LouisTA

ShenW

1999 Innovations in Bayes and empirical Bayes methods: estimating parameters, populations and ranks. Stat Med 18 2493 2505

38. RobinsonGK

1991 That BLUP is a good thing: the estimation of random effects. Stat Sci 6 15 32

39. Mexico National Institute of Statistics, Geography, and Informatics via Minnesota Population Center 2008 Integrated public use microdata series - international: version 4.0 Minneapolis University of Minnesota

40. BruchH

HartmanS

Sanchez-CrespoJ

1980 The health and vital statistics systems of Mexico. Vital registration systems in five developing countries Hyattsville (Maryland) National Center for Health Statistics