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MDG 5 indicators: Concepts and Methodologies

MDG 5 indicators: Concepts and Methodologies. Lale Say MD, MSc and Doris Chou, MD Department of Reproductive Health and Research World Health Organization . MDG 5: improve maternal health. Target 5.A: Reduce by three quarters, between 1990 and 2015, the maternal mortality ratio

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MDG 5 indicators: Concepts and Methodologies

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  1. MDG 5 indicators: Concepts and Methodologies Lale Say MD, MSc and Doris Chou, MD Department of Reproductive Health and Research World Health Organization 08_XXX_MM1

  2. MDG 5: improve maternal health • Target 5.A: Reduce by three quarters, between 1990 and 2015, the maternal mortality ratio • 5.1 Maternal mortality ratio • 5.2 Proportion of births attended by skilled health personnel • Target 5.B: Achieve, by 2015, universal access to reproductive health • 5.3 Contraceptive prevalence rate • 5.4 Adolescent birth rate • 5.5 Antenatal care coverage • at least one visit and at least four visits • 5.6 Unmet need for family planning 08_XXX_MM2

  3. Target 5.A: Reduce by three quarters, between 1990 and 2015, the maternal mortality ratio 5.1 Maternal mortality ratio 08_XXX_MM3

  4. Background • Updates every 5 year since 1990 by WHO, UNICEF, UNFPA – The World Bank joined in 2005 updates • 2008 update – An academic team at University of Berkeley developed/applied in collaboration with MMEIG 08_XXX_MM4

  5. Trends in Maternal Mortality: 1990 to 2008 • Reviewed by the technical advisory group with experts from academic institutions: Berkeley, Harvard, Hopkins, Texas, Aberdeen, Umea, Statistics Norway – in current update • Countries consulted for comments on methodology and additional input 08_XXX_MM5

  6. General framework of the maternal mortality estimates 1990-2008 • Levels and trends of maternal mortality between 1990 and 2008 for 172 countries • Hierarchical/multilevel linear regression model • The input data is the PMDF (proportion maternal among all female deaths 15-49) adjusted for completeness and definition • Covariates: the log(GDP), log(GFR) and SAB • The final output takes into account the maternal mortality related with the HIV/AIDS 08_XXX_MM6

  7. Definition used • => Maternal death: “the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and the site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management but not from accidental or incidental causes.” ICD-10, WHO,1994 • Pregnancy-related death: “the death of a woman while pregnant or within 42 days of termination of pregnancy” 08_XXX_MM7

  8. Estimated measures • Maternal Mortality Ratio (MMR): Ratio of maternal deaths in a period to live births (proxy for risky events) in the same period (x 100,000). • Number of maternal deaths • PMDF: Proportion of maternal among female deaths 15-49 • Lifetime risk of a maternal death: An estimate of the likelihood that a woman who survives to age 15 will die of maternal causes • proportion of women reaching reproductive age who would die of maternal causes, taking into account competing causes 08_XXX_MM8

  9. Input data to the model: PMDF • PMDF is considered less subject to under-reporting than MMR (maternal and non-maternal deaths likely to be under-reported to similar degree) • Maternal deaths as defined by ICD is difficult to capture – usually all deaths in pregnancy measured • Efforts have been made to adjust for: • under reporting • definition • For the model the HIV/AIDS component was taken out from the PMDF; the HIV/AIDS component is added back after the model fitting 08_XXX_MM9

  10. Input database • Database of 172 countries, from 1985 onwards • Nationally representative data => focusing on sources where PMDF is possible to compute 08_XXX_MM10

  11. Sources of Data • Civil registration systems with cause of death assigned by attending physician (generally not complete in developing world) • Sample vital registration systems • Reproductive Age Mortality Surveys (RAMOS): not very common • Household surveys with sibling histories • Population censuses with questions on household deaths • Hospital- or facility-based studies • Other 08_XXX_MM11

  12. Civil Registration Data • WHO estimates that 72 (out of 193) member states have complete recording of deaths • But not all have adequate cause of death data • Even in countries with complete VR, classification of deaths as maternal is problematic • Recent increase in MMR (47% 2002 to 2004) in US due to change of death certificate • Issues: • 14 studies (confidential enquiry, record linkage) of countries with complete registration a median underestimation of 0.5) (true maternal deaths were incorrectly recorded as non-maternal) 08_XXX_MM12

  13. Sample Vital Registration Systems • Special procedures in random sample of areas (4,000+ in India, 160 in China) • Continuous monitoring of vital events plus 6-monthly household survey (India) • Cause of death identified by verbal autopsy (VA) (India) or case records plus VA (China) • Issues: • Requires considerable administrative sophistication • Cannot be implemented rapidly • Needs periodic evaluation 08_XXX_MM13

  14. RAMOS Studies • Starting point is complete listing of deaths of women of reproductive age • Best starting point is close to complete VR • Key feature is triangulation among data sources (eg church records, burial grounds) to identify missed deaths • May be done for a sample (but has to be large) • Each death is investigated in detail to determine whether or not it was maternal • Hospital, health facility records • Household interviews • Issues: • Results may be no better than the frame of deaths • MMR also needs number of births 08_XXX_MM14

  15. Censuses with Questions on Deaths • Population censuses can include questions on deaths in households in defined recent reference period • Reported deaths of reproductive aged women trigger questions about the timing of death relative to pregnancy • Issues: • Pregnancy-related mortality • Census misses deaths in single-person households • Death of head of household may result in household breakup • Experience suggests there is almost always some under-reporting • Need to evaluate carefully • No consensus as to the quality of the data obtained 08_XXX_MM15

  16. Facility-Based Studies • Useful for identifying areas for improved care (confidential enquiries) • Potential for gold standard case identification (case notes) • Facility deaths (and births) are selected on characteristics that may not be known • Not readily generalizable to a national MMR estimate 08_XXX_MM16

  17. Household Surveys With Sibling Histories • Key questions for sibling history: • Each sibling listed individually • Record sex • Record age in completed years for surviving sibs • Record year of death, age at death for dead sibs • For deaths of women of reproductive age, 3 questions about timing of death relative to pregnancy • Widely used by DHS program (41countries,65 surveys) • Issues: • Measures pregnancy-related mortality • Even in surveys of 30,000 households, estimates are made for 7 years before survey • May under-estimate overall mortality 08_XXX_MM17

  18. General Problems with Maternal Mortality Measurement • Rare events (only ~ 5% of child deaths) • National trends unstable • For household surveys requires very large samples • Certain types of maternal death hard to identify (especially abortion-related) • Non-VR methods tend to measure pregnancy-related mortality PRMR 08_XXX_MM18

  19. Input data to the model:Adjustment by type of source • Adjustment for completeness of reporting specified in relation to the type of data • CR system: Review of recent literature on underestimation of maternal deaths in CR systems • – adjustment by a factor of 1.5 • Sibling histories: age-standardization, • 1.1 upward adjustment (underestimation of early pregnancy deaths) • 0.9, 0.85 downward adjustment (remove accidental deaths) • Other special studies (e.g., RAMOS): • 1.1 upward adjustment 08_XXX_MM19

  20. Data on maternal mortality: availability 08_XXX_MM20 24 countries had no nationally representative data that met inclusion criteria

  21. Covariates • GDP: gross domestic product PPP per capita, in constant 2005 international dollar; the World Bank series, complemented by other sources • GFR: general fertility rate, the number of births in a population divided by the number of women at reproductive ages; UNPD World Population Prospects the 2008 revision • SAB: the proportion of deliveries with a skilled attendant at birth from UNICEF database 08_XXX_MM21

  22. Covariates and the model • A time series of these three covariates were constructed for the 1985-2008 period • Time-matched average values of the covariates for time intervals corresponding to the period of each observation of the dependent variable PMDF were computed • A hierarchical/multilevel model with three main covariates, plus random effects for countries and regions and an offset which will adjust the denominator of PMDF for AIDS. 08_XXX_MM22

  23. Input data to the model:Definition and HIV/AIDS adjustment • Observed PMDF were grouped into 3 categories according to the definition • Maternal mortality • Pregnancy-related • Pregnancy-related without accident 08_XXX_MM23

  24. Input data to the model: Addressing HIV/AIDS • The fraction of AIDS deaths among women aged 15-49 that occur during pregnancy (v) : v = c*k*GFR / ( 1 + c*(k‐1)*GFR) • c = average period of exposure-to-risk associated with each live birth • k = relative risk of dying from HIV/AIDS for a pregnant versus non-pregnant woman • ũ = the fraction of AIDS deaths that were presumably included in a PMDF or MMR observation. • = 1 if “pregnancy-related” definition (with or without accidents) • = 0.5 otherwise • PMDF observations adjusted to remove estimated included AIDS deaths before running regression: PMDF – ũ * v * a where a = proportion of AIDS deaths among all deaths in age range 15-49 for women 08_XXX_MM24

  25. Fitting and add back HIV/AIDS • The model fitted to the complete set of observations for 172 countries • Add back a fraction, u, of the total number of AIDS deaths estimated to have occurred during pregnancy • Predicted PMDF converted to MMRs: MMR = PMDF(D/B) • D = N female deaths 15-49 estimated from WHO life tables • B = N live births from UN Population Division estimates 08_XXX_MM25

  26. Country consultation • Focal point identification and review • Comments received during consultation • Accepted amendments to data input • source of reference clearly identified 08_XXX_MM26

  27. Maternal mortality in 2008 and average annual change between 1990 and 2008 08_XXX_MM27 * Numbers are rounded

  28. Maternal mortality ratios 1990-2008 08_XXX_MM28 http://www.who.int/gho/mdg/maternal_health/situation_trends_maternal_mortality/en/index.html

  29. Uncertainty Components of uncertainty include: • Any remaining bias in adjusted PMDF values • Uncertainty in model parameters (c, k, u, and pi) • Regression prediction uncertainty within the PMDF model • Possible error in MMR conversion (estimated births and deaths) • Alternative models, covariates, etc. 08_XXX_MM29

  30. Maternal deaths due to HIV/AIDS • Overall, it was estimated that there were 42 000 deaths due to HIV/AIDS among pregnant women in 2008 • About half of those were assumed to be maternal • The contribution of HIV/AIDS was highest in sub-Saharan Africa where 9% of all maternal deaths were estimated to be due to HIV/AIDS • Globally, 6% of maternal deaths estimated to be due to HIV/AIDS 08_XXX_MM30

  31. Maternal mortality ratios at country level 08_XXX_MM31

  32. CEE/CIS countries 08_XXX_MM32

  33. What is new compared with the 2005 analysis • Trend estimates for countries => bigger database • Definition issue addressed • Maternal deaths related with HIV/AIDS taken into account • Statistical model – more detailed 08_XXX_MM33

  34. Differences with IHME analysis • The data used by IHME and MMEIG are very similar • Global totals for 2008 similar, differences in 1990 estimates and individual countries likely to be due to technical differences in the methods • adjustments made to data from various sources differed, in some cases use of sub-national data • modelling strategies • different covariates used • IHME: TFR, GDP, HIV prevalence, NMR, female education • MMEIG: GDP, GFR, SAB • addressing HIV: IHME used HIV prevalence as a covariate • adult mortality databases 08_XXX_MM34

  35. Next steps • Database and the statistical programme available on web www.who.int/reproductivehealth/publications/monitoring/9789241500265/en/index.html • January: TAG meeting – call for inputs and collaboration • Review feedback and continuous interaction with countries in: • strengthening capacity in using the model • reviewing data quality • updating the database • supporting the use of data for decision making • Regional workshops 08_XXX_MM35

  36. Target 5.A: Reduce by three quarters, between 1990 and 2015, the maternal mortality ratio 5.2 Proportion of births attended by skilled health personnel 08_XXX_MM36

  37. Births attended by Skilled Health Personnel • Health service coverage indicator • Measurement as a percentage • Numerator: # births attended by SBA • Denominator: total # live births in time pd • Skilled birth attendant • an accredited health professional (midwife, nurse, doctor) trained and able to manage uncomplicated pregnancy, childbirth, postnatal period, and able to identify, manage, refer complications of women and newborns • Definition excludes traditional birth attendants (with or without training) 08_XXX_MM37

  38. SBA Data Sources • Household surveys • Respondents asked about each live birth and who helped • Facility based records • Where high proportion of births occur in facilities • Used in Latin America • Data issues • Some survey reports may present a total % of births attended by a type of provider (eg includes community health workers) • Standardization of definition of SBA is difficult because of training differences 08_XXX_MM38

  39. SBA reporting • Data reported annually by UNICEF and WHO • Weighted averages of country data using number live births for reference year in country • No figures are reported if less than 50% live births in region covered • Disaggregation • Location • Education level • Wealth quintile • Health personnel • Place of delivery • Administrative region • Health region 08_XXX_MM39

  40. Target 5.B: Achieve, by 2015, universal access to reproductive health 5.5 Antenatal care coverage at least one visit at least four visits 08_XXX_MM40

  41. Antenatal Coverage • Health service coverage • Measurement as a percentage • Numerator: # women aged 15-49 with live birth in time pd who received ANC (at least once or at least 4 times) during pregnancy • Denominator: total # of women aged 15-49 with live birth in time pd 08_XXX_MM41

  42. ANC Data Sources • Household surveys • Based upon standard questions that ask if, and how many times, and by whom the health of woman was checked in pregnancy • Facility reporting systems • Used where coverage is high • Data issues • Receiving ANC does not guarantee all interventions to improve maternal health • Indicator for at least one visit refers to skilled provider • Indicator for 4 or more visits measures any provider • Standardization of definition of SBA is difficult because of training differences 08_XXX_MM42

  43. Antenatal Care reporting • Data reported annually by UNICEF and WHO • Population weighted averages weighted by total number live births • No figures are reported if less than 50% live births in region covered • Disaggregation • Location • Education level • Wealth quintile • Administrative region • Health region 08_XXX_MM43

  44. Summary • Indicators are markers of health status, service provision, resource availability • Indicators are designed to monitor service performance or programme goals • Indicators have inherent limitations 08_XXX_MM44

  45. Implications • Interpretation of indicators is challenging due to variability • Lack of reliable statistics for measuring progress results in an evolving understanding of the interpretation 08_XXX_MM45

  46. Conclusion • Gradual – but variable decline of maternal mortality, globally off the pace required by the MDG 5 target • Preventable maternal deaths occur every day • Need for real and better numbers: • Maternal deaths must be counted to guide action and monitoring progress • Estimates are imprecise, but important as a means to assess progress and engage countries • Not knowing the exact numbers of women dying should not deflect anyone's attention from stepping up our efforts to reduce maternal mortality 08_XXX_MM46

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