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Global Maternal Mortality Estimates and Trends, 1990-2008

Global Maternal Mortality Estimates and Trends, 1990-2008. John R. Wilmoth, University of California at Berkeley Technical Advisory Group on Maternal Mortality Estimation Geneva, Switzerland, 26 January 2011. Overview of main results. Maternal mortality ratio, 2008.

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Global Maternal Mortality Estimates and Trends, 1990-2008

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  1. Global Maternal Mortality Estimates and Trends, 1990-2008 John R. Wilmoth, University of California at Berkeley Technical Advisory Group on Maternal Mortality Estimation Geneva, Switzerland, 26 January 2011

  2. Overview of main results

  3. Maternal mortality ratio, 2008 Maternal mortality ratio shown here is expressed per 100,000 live births From: WHO et al., 2010, p. 27

  4. Maternal mortality ratio, 1990-2008 From: Wilmoth et al., in preparation

  5. Rate of decline – various estimates • For the world as a whole, the new United Nations estimates suggest that the MMR declined from 1990 to 2008 at an average annual rate of 2.3% (2.1, 2.4) • Prior UN estimates (for 2005) suggested a rate of decline of only 0.4% per year since 1990, but 2.5% when limited to countries with multiple data points • Estimates by Hogan et al. (2010) suggested an annual rate of decline for 1990-2008 of 1.3% (1.0, 1.5), but 2.4% in their “no-HIV” scenario

  6. Data and Methods for Estimating Maternal Mortality

  7. Coverage of estimates • 172 countries or territories: Estimates were derived for all countries with populations of at least 250,000 persons in 2005 • 1990-2008: Estimates refer to 5-year intervals centered on 1990, 1995, 2000, 2005, and 2008

  8. Key points about data and model • Data are sparse: on average, there are only 2.8 observations per country (from late 1980s until 2008)

  9. Country groupings by available data From: WHO et al., 2010, p. 10

  10. Observations by data type: World overview From: Wilmoth et al., in preparation

  11. Observations by data type: Sub-Saharan Africa From: Wilmoth et al., in preparation

  12. Key points about data and model • Data are sparse • Definitions are inconsistent (maternal, pregnancy-related)

  13. Maternal death: Definition • “The death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management but not from accidental or incidental causes.” (WHO, ICD-10) • Two types of maternal deaths: • Direct maternal deaths are due to obstetric complications of pregnancy (including delivery and postpartum) • Indirect maternal deaths are due to other causes but are also aggravated by the physiological effects of pregnancy

  14. Pregnancy-related vs. maternal • Pregnancy-related deaths • Includes all deaths among women aged 15-49 if they occur during pregnancy or within 42 days postpartum • Includes more than just maternal deaths • Maternal deaths • A subset of pregnancy-related deaths • Excludes accidental and incidental deaths • Pregnancy-related deaths, without accidents • Excludes deaths due to accidents only, includes all other pregnancy-related deaths • In practice, treated as equivalent to “maternal” definition, except for AIDS-related maternal deaths

  15. Key points about data and model • Data are sparse • Definitions are inconsistent • Maternal deaths are underreported (and underestimated) • In part because all-cause mortality is underestimated in some data sources • In part because maternal deaths are underrepresented as a proportion of all reported female deaths for ages 15-49, presumably in all data sources

  16. Proportion of maternal deaths • For all data sources, maternal mortality was measured by noting the proportion of female deaths at ages 15-49 that were categorized as “maternal” • The proportion maternal among deaths to females aged 15-49 (PMDF) is defined as follows: PMDF = • For observations deriving from data on “pregnancy-related” deaths, the information was adjusted in order to remove accidental and incidental deaths (approximately) before computing the PMDF Number of maternal deaths All deaths among women aged 15-49

  17. Mortality from all causes • For all countries, estimates of female mortality for all causes combined were obtained from the World Health Organization • All-cause death rates equal the number of female deaths at ages 15-49 (D) divided by the number of women living at these same ages (W): Adult female death rate = D/W

  18. Maternal mortality rate and maternal deaths • The estimated maternal mortality rate equals the PMDF multiplied by the female all-cause death rate for ages 15-49 Maternal mortality rate = PMDF * (D/W) • The estimated number of maternal deaths equals the PMDF multiplied by the total number of female deaths among reproductive-age women Maternal deaths = PMDF * D

  19. Maternal mortality ratio • For all countries, estimates of the number of live births were obtained from the United Nations Population Division • The estimated maternal mortality ratio (MMR) equals the number of maternal deaths divided by the number of live births (B): MMR = Maternal deaths / Live births = PMDF * D / B

  20. Envelope adjustment • The all-cause mortality level is often referred to as the “envelope”, and the practice of multiplying a PMDF times the mortality envelope is known as an “envelope adjustment” • This adjustment offers several advantages: • Avoids problems due to poor estimation of all-cause female mortality in some data sources (e.g., DHS sisterhood) • Assures consistency with an existing estimate of all-cause female mortality • Improves comparability of maternal mortality estimates based on different data sources

  21. Data adjustments • For some data sources, the definition used for the cause-of-death category includes more than just “maternal” deaths properly defined • In addition, for a given definition, the number of deaths may be underreported in practice • PMDF data were adjusted in both regards before computing the various measures of maternal mortality

  22. Adjustment for data based on pregnancy-related definition • For data including all pregnancy-related deaths, the observed value was adjusted by removing a fraction, π, of those deaths, to account for mortality from accidental or incidental causes • Assumed values for π were derived from: • Some surveys where data were collected according to both “maternal” and “pregnancy-related” definitions • WHO data on injuries and accidents • This adjustment was applied after excluding deaths due to AIDS, which were treated separately (as explained later)

  23. Ratio of maternal to pregnancy-related deaths

  24. Assumed values for π • Assumed values for π were as follows: π = 0.10 for countries in Sub-Saharan Africa π = 0.15 for all other low- and middle-income countries • The different value for countries of Sub-Saharan Africa was justified primarily by the WHO injury data, which indicate that accidents in that region comprise a smaller fraction of all pregnancy-related deaths (even after excluding deaths due to AIDS)

  25. Pregnancy-related deaths due to injuries and accidents* * After excluding deaths due to AIDS

  26. Underreporting of maternal or pregnancy-related deaths • Several countries have conducted studies to ascertain the level of under-reporting of maternal deaths in vital registration data, yielding a median adjustment factor of 1.5 • Thus, PMDF estimates from vital registration systems were adjusted by a factor of 1.5, unless a country-specific study indicated a different value (minimum = 1.0, maximum = 2.9) • PMDF estimates from sources other than vital registration were adjusted by a factor of 1.1 to take account of the likely under-identification of maternal deaths due to unreported abortion-related deaths or other causes

  27. Key points about data and model • Data are sparse • Definitions are inconsistent • Maternal deaths are underreported • Model is complex • Separate treatment of AIDS deaths • Multilevel model for non-AIDS component: • Dependent variable / offset term • 3 covariates, each with important effects • Random effects for regions and countries • Throughout: many unknown parameters, with some values chosen based on rather weak empirical evidence

  28. Multilevel* regression model • Choice of dependent variable • Use of offset terms • Choice of covariates • Random effects for countries and regions A “multilevel” regression model includes random elements at various levels; in this case, there are three levels: observations, countries, and regions *

  29. Model specification • In its final form, the regression model is as follows: log(PMDF i ) = β0 + β1 log(GDPi) + β2 log(GFRi) + β3SABi + αj[i] + αk[i] + log(1-ai) + εi • The various elements of this model are described in the next few slides na C R

  30. Dependent variable • The dependent variable of the regression model is the non-AIDS PMDF: PMDF = • Thus, the numerator includes all maternal deaths except for AIDS deaths that were aggravated by the effects of pregnancy (i.e., indirect maternal deaths due to AIDS) • The denominator, on the other hand, includes all deaths among women aged 15-49, including those due to AIDS Number of non-AIDS-related maternal deaths na All deaths among women aged 15-49

  31. Offset terms • Alternative choices of the dependent variable were explored and implemented using offset terms • As a first alternative, the PMDF was adjusted further for the effects of the HIV epidemic by removing AIDS deaths from the denominator as well as the numerator: AMDF = • A second alternative was a non-AIDS MMR, with only non-AIDS-related maternal deaths in the numerator and all live births in the denominator na Number of non-AIDS-related maternal deaths na All non-AIDS deaths among women aged 15-49

  32. Offset terms (cont.) • These alternative dependent variables are related to the non-AIDS PMDF as follows: AMDF = PMDF / (1-a) MMR = PMDF * D / B where a is the proportion of AIDS deaths in women aged 15-49 • In logarithms, these relationships are as follows: log(AMDF ) = log(PMDF ) – log(1-a) log(MMR ) = log(PMDF ) + log(D) – log(B) The logarithmic equations are used to determine the proper form for the offset term of the regression equation na na na na na na na na

  33. Two equivalent models • With the offset term: log(PMDF i ) = β0 + β1 log(GDPi) + β2 log(GFRi) + β3SABi + αj[i] + αk[i] + log(1-ai) + εi • Without the offset term: log(AMDF i ) = β0 + β1 log(GDPi) + β2 log(GFRi) + β3SABi + αj[i] + αk[i] + εi na C R na C R

  34. Three model variants • Three variants of the model were explored, using PMDF , AMDF , and MMR as the dependent variable • To make these models comparable, each one is written with log(PMDF ) on the left-hand side of the equation, with an appropriate offset term on the right-hand side • Thus, for the simple model with only the 3 covariates, the three variants are as follows: log(PMDFi ) = β0 + β1 log(GDPi) + β2 log(GFRi) + β3SABi + εi log(PMDFi ) = β0 + β1 log(GDPi) + β2 log(GFRi) + β3SABi + log(1-ai) + εi log(PMDFi ) = β0 + β1 log(GDPi) + β2 log(GFRi) + β3SABi + log(Bi) - log(Di) + εi na na na na na (PMDF) (AMDF) na (MMR) na

  35. Three model variants (cont.) • The three model variants (PMDF, AMDF, and MMR) were estimated using the same data set, and the three sets of results were compared in order to determine which variant provides the best fit to the data • In general, the AMDF variant was found to provide the closest fit to the observed data, followed by the MMR and then the PMDF variants; for this reason, an offset term of log(1-ai) was included in the final model • Model coefficients (β1,β2, and β3) should be interpreted in terms of associated changes in AMDF na

  36. Model covariates The regression model includes three covariates: • Gross domestic product (GDP) • National income per capita • Expressed in constant 2005 international dollars, i.e., inflation-adjusted “purchasing power parity” (PPP) • General fertility rate (GFR) • Number of live births per woman aged 15-49 • Skilled attendant at birth (SAB) • Proportion of live births where a trained health worker was present at time of delivery

  37. Model covariates (cont.) • These three covariates were selected to represent causal dimensions thought to be the primary determinants of the level of maternal mortality (options considered are listed in parentheses): • Development (GDP, female life expectancy, HDI, child mortality) • Exposure (GFR, total fertility rate) • Process (SAB, antenatal care, institutional deliveries) • In all three groups, the selected covariate is arguably the single best representation of the given dimension; in some cases (in particular for the SAB) it was also the most widely available

  38. Estimated model coefficients* * Table shows estimated coefficients for the final model, which also includes random effects for countries and regions (not shown here)

  39. Annual data series • For each covariate or offset variable, complete annual data series were either obtained or created • Data on population size, fertility, and all-cause mortality were already available as annual data series • In most other cases, simple interpolation was used to fill in missing information between the available values • For SAB, annual values were derived from a logit regression model with time as the sole covariate; this model was fitted separately to the data for each country

  40. Time-matched covariates • For the regression model, average values of covariates and offset variables were computed over time intervals matched to each PMDF observation • For example, if the observation interval for PMDFi extends from 1 June 2000 through 31 May 2003, the time-matched value for the GDP covariate was computed as follows: GDPi= (1/3) [(7/12)*GDP2000 + GDP2001 + GDP2002 + (5/12)*GDP2003] • For a PMDF observation interval that lies entirely within a single calendar year, the GDP estimate for that year was taken as the covariate value (the same for GFR and SAB)

  41. Country/region random effects • The final model includes random effects for both countries and regions: αj[i] is the coefficient for country j, where j[i] denotes the country associated with observation i αk[i] is the coefficient for region k, where k[i] denotes the region associated with observation i • The random effect for region k depicts the estimated differential level of maternal mortality for that region compared to an average level across all regions • Similarly, the random effect for country j depicts the estimated differential level for that country compared to an average across countries of its region C R

  42. Variance components • Inclusion of random effects for countries and regions provides a simple means of depicting those components of the variability in PMDF that are not well described by the simple model with three covariates • For a given set of covariate values, PMDF still varies across observations (within countries), across countries (within regions), and across regions • The framework of the multilevel model allows us to assess the uncertainty of predictions (or estimates) while taking into account these three levels of variability; this approach is especially important for countries with no, or very few, empirical observations of maternal mortality levels na na

  43. Variance components (cont.) • The error term, εi , depicts the variability of the dependent variable within countries and is assumed to follow a normal distribution with a mean of zero and a variance of σ2: εi ~ N(0,σ2) • The country/region coefficients are treated as random, not fixed, in the sense that each set of random coefficients (for countries or regions) is assumed to follow a normal distribution with a mean of zero and a variance of σ2or σ2: αj ~ N(0,σ2) and αk ~ N(0,σ2) y y C R C R C R

  44. Estimated variance components Source: Wilmoth et al. (2010), Technical report

  45. Separate treatment of AIDS deaths • A multilevel regression model was used to describe and predict levels of non-AIDS-related maternal mortality • As noted already, some deaths due to AIDS qualify as indirect maternal deaths because of the aggravating effects of the pregnancy on HIV disease • Rather than attempting to create a more complicated regression model capable of accounting for such interactions, AIDS-related maternal deaths were modeled and estimated separately • Thus, the final estimates of maternal mortality include both a non-AIDS and an AIDS-related component

  46. Four categories of pregnancy-related deaths

  47. AIDS-related maternal deaths • Indirect maternal deaths due to HIV/AIDS are depicted by a simple model of the AIDS-related PMDF: PMDF = uva • The three pieces of this model are defined as follows: a denotes the proportion of deaths due to HIV/AIDS among women aged 15-49 (as estimated by UNAIDS) v is the estimated proportion of such deaths that strike pregnant women u is the assumed fraction of AIDS deaths among pregnant women that qualify as indirect maternal deaths a

  48. All-cause maternal mortality • The total PMDF equals the sum of its non-AIDS and AIDS-related components: PMDF = PMDF + PMDF = PMDF + uva • All other indicators of maternal mortality are derived from the estimated PMDF; for example, the MMR is obtained as follows: MMR = PMDF * D / B a na na

  49. Estimating the value of v • The parameter v in the model of the AIDS-related PMDF was computed using the following equation: v = where c equals the average exposure-to-risk (in years) of pregnancy-related mortality per live birth, and k is the relative risk of dying from AIDS for a pregnant versus a non-pregnant woman (see Technical Report) • Values of c=1.0 and k=0.4 were used for this analysis, based on various arguments and evidence (which were fairly solid in the case of c, but rather weak for k) kcGFR 1 + (k – 1)cGFR

  50. Assumed value for u • By definition, the value of u must lie somewhere on the interval between zero and one • Assuming that some but not all AIDS deaths among pregnant women were aggravated by the pregnancy, two values in this range can be dismissed as incorrect: zero and one • Beyond that, there is very little in the way of arguments or evidence to guide a specific choice for the value of u (which could differ over time and across populations) • In the absence of better information, it was assumed that u=0.5 in all situations

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