#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories


Background:
Child mortality estimates from complete birth histories from Demographic and Health Surveys (DHS) surveys and similar surveys are a chief source of data used to track Millennium Development Goal 4, which aims for a reduction of under-five mortality by two-thirds between 1990 and 2015. Based on the expected sample sizes when the DHS program commenced, the estimates are usually based on 5-y time periods. Recent surveys have had larger sample sizes than early surveys, and here we aimed to explore the benefits of using shorter time periods than 5 y for estimation. We also explore the benefit of changing the estimation procedure from being based on years before the survey, i.e., measured with reference to the date of the interview for each woman, to being based on calendar years.

Methods and Findings:
Jackknife variance estimation was used to calculate standard errors for 207 DHS surveys in order to explore to what extent the large samples in recent surveys can be used to produce estimates based on 1-, 2-, 3-, 4-, and 5-y periods. We also recalculated the estimates for the surveys into calendar-year-based estimates. We demonstrate that estimation for 1-y periods is indeed possible for many recent surveys.

Conclusions:
The reduction in bias achieved using 1-y periods and calendar-year-based estimation is worthwhile in some cases. In particular, it allows tracking of the effects of particular events such as droughts, epidemics, or conflict on child mortality in a way not possible with previous estimation procedures. Recommendations to use estimation for short time periods when possible and to use calendar-year-based estimation were adopted in the United Nations 2011 estimates of child mortality.


Vyšlo v časopise: Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories. PLoS Med 9(8): e32767. doi:10.1371/journal.pmed.1001289
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pmed.1001289

Souhrn

Background:
Child mortality estimates from complete birth histories from Demographic and Health Surveys (DHS) surveys and similar surveys are a chief source of data used to track Millennium Development Goal 4, which aims for a reduction of under-five mortality by two-thirds between 1990 and 2015. Based on the expected sample sizes when the DHS program commenced, the estimates are usually based on 5-y time periods. Recent surveys have had larger sample sizes than early surveys, and here we aimed to explore the benefits of using shorter time periods than 5 y for estimation. We also explore the benefit of changing the estimation procedure from being based on years before the survey, i.e., measured with reference to the date of the interview for each woman, to being based on calendar years.

Methods and Findings:
Jackknife variance estimation was used to calculate standard errors for 207 DHS surveys in order to explore to what extent the large samples in recent surveys can be used to produce estimates based on 1-, 2-, 3-, 4-, and 5-y periods. We also recalculated the estimates for the surveys into calendar-year-based estimates. We demonstrate that estimation for 1-y periods is indeed possible for many recent surveys.

Conclusions:
The reduction in bias achieved using 1-y periods and calendar-year-based estimation is worthwhile in some cases. In particular, it allows tracking of the effects of particular events such as droughts, epidemics, or conflict on child mortality in a way not possible with previous estimation procedures. Recommendations to use estimation for short time periods when possible and to use calendar-year-based estimation were adopted in the United Nations 2011 estimates of child mortality.


Zdroje

1. Measure DHS (1996) Sampling manual, DHS-III basic documentation No 6. Calverton: Macro International.

2. HillK, YouD, InoueM, OestergaardMZ (2012) Child Mortality Estimation: Accelerated progress in reducing global child mortality, 1990–2010. PLoS Med 9: e1001303 doi:10.1371/journal.pmed.1001303.

3. United Nations (1993) Sampling errors in household surveys. New York: United Nations Department for Economic and Social Information and Policy Analyses.

4. Ward D (2007) Data and metadata reporting and presentation handbook: Paris: Organisation for Economic Co-operation and Development.

5. Särndal C-E, Swensson B, Wretman J (1992) Model assisted survey sampling. New York: Springer-Verlag. 694 p.

6. Morrison DE, Henkel RE (1970) The significance test controversy: a reader. Piscataway (New Jersey): Aldine Transaction.

7. Kish L (2003) Methods for design effects. In: Kalton G, Heeringa S, editors. Leslie Kish: selected papers. Hoboken: Wiley. pp. 155–178.

8. Hansen MH, Hurwitz WN, Madow WG (1953) Sample survey methods and theory. New York: Wiley.

9. Eurostat (2008) Survey sampling reference guidelines. Luxembourg: Office for Official Publications of the European Communities.

10. ShannonCE (1949) Communication in the presence of noise. Proc Inst Radio Eng 37: 10–21.

11. GuptaKL (1971) Aggregation bias in linear economic models. Int Econ Rev 12: 293–305.

12. AnandS, BärnighausenT (2004) Human resources and health outcomes: cross-country econometric study. Lancet 364: 1603–1609.

13. HojmanDE (1996) Economic and other determinants of infant and child mortality in small developing countries: the case of Central America and the Caribbean. Appl Econ 28: 281–290.

14. Gates SH, Hegre H, Nygård HM, Strand H (2010) Consequences of civil conflict. Washington (District of Columbia): World Bank

15. Carlton-FordS, HamillA, HoustonP (2000) War and children's mortality. Childhood 7: 401–419.

16. Wolter KM (1985) Introduction to variance estimation. New York: Springer-Verlag.

17. Rutstein SO, Rojas G (2006) Guide to DHS statistics. Calverton: Demographic and Health Surveys, ORC Macro.

18. Westat (2002) WesVar 4.2 user's guide. Rockville: Westat.

19. Research Triangle Institute (2001) SUDAAN user's manual, release 8.0. Research Triangle Park (North Carolina): Research Triangle Institute.

20. RajaratnamJK, MarcusJR, FlaxmanAD, WangH, Levin-RectorA, et al. (2010) Neonatal, postneonatal, childhood, and under-5 mortality for 187 countries, 1970–2010: a systematic analysis of progress towards Millennium Development Goal 4. Lancet 375: 1988–2008.

21. United Nations Children's Fund (2011) Levels & trends in child mortality: report 2011. Estimates developed by the UN Inter-agency Group for Child Morality Estimation. New York: United Nations Children's Fund.

Štítky
Interné lekárstvo

Článok vyšiel v časopise

PLOS Medicine


2012 Číslo 8
Najčítanejšie tento týždeň
Najčítanejšie v tomto čísle
Kurzy

Zvýšte si kvalifikáciu online z pohodlia domova

Aktuální možnosti diagnostiky a léčby litiáz
nový kurz
Autori: MUDr. Tomáš Ürge, PhD.

Všetky kurzy
Prihlásenie
Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.

Prihlásenie

Nemáte účet?  Registrujte sa

#ADS_BOTTOM_SCRIPTS#