Measuring Adult Mortality Using Sibling Survival: A New Analytical Method and New Results for 44 Countries, 1974–2006
Background:
For several decades, global public health efforts have focused on the development and application of disease control programs to improve child survival in developing populations. The need to reliably monitor the impact of such intervention programs in countries has led to significant advances in demographic methods and data sources, particularly with large-scale, cross-national survey programs such as the Demographic and Health Surveys (DHS). Although no comparable effort has been undertaken for adult mortality, the availability of large datasets with information on adult survival from censuses and household surveys offers an important opportunity to dramatically improve our knowledge about levels and trends in adult mortality in countries without good vital registration. To date, attempts to measure adult mortality from questions in censuses and surveys have generally led to implausibly low levels of adult mortality owing to biases inherent in survey data such as survival and recall bias. Recent methodological developments and the increasing availability of large surveys with information on sibling survival suggest that it may well be timely to reassess the pessimism that has prevailed around the use of sibling histories to measure adult mortality.
Methods and Findings:
We present the Corrected Sibling Survival (CSS) method, which addresses both the survival and recall biases that have plagued the use of survey data to estimate adult mortality. Using logistic regression, our method directly estimates the probability of dying in a given country, by age, sex, and time period from sibling history data. The logistic regression framework borrows strength across surveys and time periods for the estimation of the age patterns of mortality, and facilitates the implementation of solutions for the underrepresentation of high-mortality families and recall bias. We apply the method to generate estimates of and trends in adult mortality, using the summary measure 45q15—the probability of a 15-y old dying before his or her 60th birthday—for 44 countries with DHS sibling survival data. Our findings suggest that levels of adult mortality prevailing in many developing countries are substantially higher than previously suggested by other analyses of sibling history data. Generally, our estimates show the risk of adult death between ages 15 and 60 y to be about 20%–35% for females and 25%–45% for males in sub-Saharan African populations largely unaffected by HIV. In countries of Southern Africa, where the HIV epidemic has been most pronounced, as many as eight out of ten men alive at age 15 y will be dead by age 60, as will six out of ten women. Adult mortality levels in populations of Asia and Latin America are generally lower than in Africa, particularly for women. The exceptions are Haiti and Cambodia, where mortality risks are comparable to many countries in Africa. In all other countries with data, the probability of dying between ages 15 and 60 y was typically around 10% for women and 20% for men, not much higher than the levels prevailing in several more developed countries.
Conclusions:
Our results represent an expansion of direct knowledge of levels and trends in adult mortality in the developing world. The CSS method provides grounds for renewed optimism in collecting sibling survival data. We suggest that all nationally representative survey programs with adequate sample size ought to implement this critical module for tracking adult mortality in order to more reliably understand the levels and patterns of adult mortality, and how they are changing.
: Please see later in the article for the Editors' Summary
Vyšlo v časopise:
Measuring Adult Mortality Using Sibling Survival: A New Analytical Method and New Results for 44 Countries, 1974–2006. PLoS Med 7(4): e32767. doi:10.1371/journal.pmed.1000260
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pmed.1000260
Souhrn
Background:
For several decades, global public health efforts have focused on the development and application of disease control programs to improve child survival in developing populations. The need to reliably monitor the impact of such intervention programs in countries has led to significant advances in demographic methods and data sources, particularly with large-scale, cross-national survey programs such as the Demographic and Health Surveys (DHS). Although no comparable effort has been undertaken for adult mortality, the availability of large datasets with information on adult survival from censuses and household surveys offers an important opportunity to dramatically improve our knowledge about levels and trends in adult mortality in countries without good vital registration. To date, attempts to measure adult mortality from questions in censuses and surveys have generally led to implausibly low levels of adult mortality owing to biases inherent in survey data such as survival and recall bias. Recent methodological developments and the increasing availability of large surveys with information on sibling survival suggest that it may well be timely to reassess the pessimism that has prevailed around the use of sibling histories to measure adult mortality.
Methods and Findings:
We present the Corrected Sibling Survival (CSS) method, which addresses both the survival and recall biases that have plagued the use of survey data to estimate adult mortality. Using logistic regression, our method directly estimates the probability of dying in a given country, by age, sex, and time period from sibling history data. The logistic regression framework borrows strength across surveys and time periods for the estimation of the age patterns of mortality, and facilitates the implementation of solutions for the underrepresentation of high-mortality families and recall bias. We apply the method to generate estimates of and trends in adult mortality, using the summary measure 45q15—the probability of a 15-y old dying before his or her 60th birthday—for 44 countries with DHS sibling survival data. Our findings suggest that levels of adult mortality prevailing in many developing countries are substantially higher than previously suggested by other analyses of sibling history data. Generally, our estimates show the risk of adult death between ages 15 and 60 y to be about 20%–35% for females and 25%–45% for males in sub-Saharan African populations largely unaffected by HIV. In countries of Southern Africa, where the HIV epidemic has been most pronounced, as many as eight out of ten men alive at age 15 y will be dead by age 60, as will six out of ten women. Adult mortality levels in populations of Asia and Latin America are generally lower than in Africa, particularly for women. The exceptions are Haiti and Cambodia, where mortality risks are comparable to many countries in Africa. In all other countries with data, the probability of dying between ages 15 and 60 y was typically around 10% for women and 20% for men, not much higher than the levels prevailing in several more developed countries.
Conclusions:
Our results represent an expansion of direct knowledge of levels and trends in adult mortality in the developing world. The CSS method provides grounds for renewed optimism in collecting sibling survival data. We suggest that all nationally representative survey programs with adequate sample size ought to implement this critical module for tracking adult mortality in order to more reliably understand the levels and patterns of adult mortality, and how they are changing.
: Please see later in the article for the Editors' Summary
Zdroje
1. GakidouE
HoganM
LopezAD
2004 Adult mortality: time for a reappraisal. Int J Epidemiol 33 710 717
2. HillK
LopezAD
ShibuyaK
JhaP
2007 Interim measures for meeting needs for health sector data: births, deaths, and causes of death. Lancet 370 1726 1735
3. MahapatraP
ShibuyaK
LopezAD
CoullareF
NotzonFC
2007 Civil registration systems and vital statistics: successes and missed opportunities. Lancet 370 1653 1663
4. 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
5. The United Nations Children's Fund (UNICEF) 2006 The state of the world's children 2007: women and children - the double dividend of gender equality New York UNICEF
6. United Nations Statistics Division 2007 Demographic yearbook New York United Nations
7. World Health Organization 2008 World Health Statistics 2008 Geneva World Health Organization Available: http://www.who.int/whosis/whostat/2008/en/index.html. Accessed 11 March 2010
8. World Bank HNP Stats database 2010 http://go.worldbank.org/N2N84RDV00. Accessed 11 March 2010
9. HillK
TrussellJ
1977 Further developments in indirect mortality estimation. Population Studies 31 313 334
10. GrahamW
BrassW
SnowRW
1989 Estimating maternal mortality: the sisterhood method. Stud Fam Plann 20 125 135
11. BicegoG
1997 Estimating adult mortality rates in the context of the AIDS epidemic in sub-Saharan Africa: analysis of DHS sibling histories. Health Transit Rev 7 7 22
12. TimaeusIM
JassehM
2004 Adult mortality in sub-Saharan Africa: evidence from Demographic and Health Surveys. Demography 41 757 772
13. MEASURE DHS, ICF Macro 2009 Demographic and Health Surveys: MEASURE DHS: DHS Overview. http://www.measuredhs.com/aboutsurveys/dhs/start.cfm. Accessed 11 March 2010
14. TimaeusIM
1998 Impact of the HIV epidemic on mortality in sub-Saharan Africa: evidence from national surveys and censuses. AIDS 12 S15 S27
15. StantonC
AbderrahimN
HillK
2000 An assessment of DHS maternal mortality indicators. Stud Fam Plann 31 111 123
16. GakidouE
KingG
2006 Death by survey: estimating adult mortality without selection bias from sibling survival data. Demography 43 569 585
17. BicegoG
AhmadOB
1996 Infant and child mortality. DHS Comparative Reports Calverton (Maryland) Macro International, Inc.
18. SchoumakerB
2004 A personal-periodic approach for birth history analysis. Population 59 783 796
19. SchoumakerB
2009 Stalls in fertility transitions in Sub-Saharan Africa: real or spurious? Human fertility in Africa: Trends in the last decade and prospects for change Cape Coast, Ghana International Union for the Scientific Study of Population
20. LopezAD
AhmadOB
GuillotM
2002 World mortality in 2000: life tables for 191 countries Geneva World Health Organization
21. United Nations Population Division 2009 World population prospects: the 2008 revision population database New York United Nations
22. UNAIDS 2008 Report on the global HIV/AIDS epidemic 2008 New York United Nations
23. GleditschNP
WallensteenP
ErikssonM
SollenbergM
StrandH
2002 Armed conflict 1946–2001: a new dataset. J Peace Res 39 615 637
24. National Population Commission 1999 Maternal and child health. Nigeria Demographic and Health Survey 1999 Calverton (Maryland) National Population Commission and ORC/Macro
25. GompertzB
1825 On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies. Philosophical Transactions of the Royal Society of London 115 513 583
26. Human Mortality Database 2009 Human mortality database. Berkeley (California): Max Planck Institute for Demographic Research, University of California, Berkeley. Available: www.mortality.org. Accessed 11 Mar 2010
27. ZabaB
WhitesideA
BoermaJT
2004 Demographic and socioeconomic impact of AIDS: taking stock of the empirical evidence. AIDS 18 Suppl 2 S1 S7
28. TimaeusIM
1991 Measurement of adult mortality in less developed countries: a comparative review. Popul Index 57 552 568
29. AbbottRD
1985 Logistic regression in survival analysis. Am J Epidemiol 121 465 471
30. AdebayoSB
FahrmeirL
2005 Analysing child mortality in Nigeria with geoadditive discrete-time survival models. Stat Med 24 709 728
31. EfronB
1988 Logistic regression, survival analysis, and the Kaplan-Meier curve. J Am Stat Assoc 83 414 425
32. KalbfleischJD
PrenticeRL
1973 Marginal likelihoods based on Cox's regression and life model. Biometrika 60 267 278
33. KingG
TomzM
WittenbergJ
2000 Making the most of statistical analyses: improving interpretation and presentation. Am J Polit Sci 341 355
34. StataCorpLP
2009 Stata/SE 10.1 for Windows.
35. LopezAD
MathersCD
EzzatiM
JamisonDT
MurrayCJ
2006 Global and regional burden of disease and risk factors, 2001: systematic analysis of population health data. Lancet 367 1747 1757
36. 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
37. BanisterJ
HillK
2004 Mortality in China 1964–2000. Popul Stud (Camb) 58 55 75
38. WalgateR
2003 Gates Foundation picks 14 grand challenges for global disease research. Bull World Health Organ 81 915 916
39. LopezAD
AbouZahrC
ShibuyaK
GolloglyL
2007 Keeping count: births, deaths, and causes of death. Lancet 370 1744 1746
40. MurrayCJ
LopezAD
FeehanDM
PeterST
YangG
2007 Validation of the symptom pattern method for analyzing verbal autopsy data. PLoS Med 4 e327 doi:10.1371/journal.pmed.0040327
41. ObermeyerZ
MurrayCJ
GakidouE
2008 Fifty years of violent war deaths from Vietnam to Bosnia: analysis of data from the world health survey programme. BMJ 336 1482 1486
42. LimSS
SteinDB
CharrowA
MurrayCJ
2008 Tracking progress towards universal childhood immunisation and the impact of global initiatives: a systematic analysis of three-dose diphtheria, tetanus, and pertussis immunisation coverage. Lancet 372 2031 2046
Štítky
Interné lekárstvoČlánok vyšiel v časopise
PLOS Medicine
2010 Číslo 4
- Statinová intolerance
- Hydroresponzivní krytí v epitelizační fázi hojení rány
- Parazitičtí červi v terapii Crohnovy choroby a dalších zánětlivých autoimunitních onemocnění
- Metamizol v liečbe pooperačnej bolesti u detí do 6 rokov veku
- Co dělat při intoleranci statinů?
Najčítanejšie v tomto čísle
- Preoperative/Neoadjuvant Therapy in Pancreatic Cancer: A Systematic Review and Meta-analysis of Response and Resection Percentages
- Economic Appraisal of Ontario's Universal Influenza Immunization Program: A Cost-Utility Analysis
- China's Engagement with Global Health Diplomacy: Was SARS a Watershed?
- Laboratory Capacity Building in Asia for Infectious Disease Research: Experiences from the South East Asia Infectious Disease Clinical Research Network (SEAICRN)