Measuring differential maternal mortality using census data Tiziana Leone LSE Health

Outline  Definitions  Background  Objectives and rationale  Lesotho, Nicaragua and Zimbabwe  Mortality/fertility adjustments  Differential analysis  Discussion

Definition A maternal death is 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 causes. A pregnancy related death the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the cause of death.

Measures of Maternal Mortality

Background  Pressure to get the indicators right to measure progress of MDG 5  Vital registration coverage not sufficient to record maternal deaths  Maternal mortality ‘rare’ event: sample surveys need big sample in order to collect enough information  Differential analysis even more challenging  Census has been recommended in countries that lack complete vital registration  The data are unused

Objectives  Apply methodology to three different settings : Nicaragua, Lesotho and Zimbabwe  Apply smoothing functions to differential mortality

Few numbers PopulationTFRMMRGNI per capita Net migration HIV Lesotho1.8m3.1 (4.2) 960 (530) $1, ‰ (-1) 40 (57) 23% (~9%) Nicaragua5.7m $ ‰710.2% Zimbabwe11m3.9880$340-22‰4415.6% Data refer to latest available year. Number in brackets for Lesotho refer to 1995

Data  Nicaragua census  Lesotho census  Zimbabwe census

Methods for the PRMR Series of evaluations methods based on demographic ‘indirect techniques’ with adjustments when needed. Hill et al Check degree of death coverage in the population General Growth Balance Synthetic extinct generation Check quality of fertility data P/F Ratio Check quality of information on pregnancy related deaths No formal methods.

Mortality Adjustment Regression line fitted for (5+)-(65+)

Adjustment factors LesothoNicaraguaZimbabwe GGB coverage %130%75% SEG coverage %135%79% Intercept of fitted line Coverage of census 1 to census P/F ratio

Plausibility checks

MMR CensusCensus unadjusted UNICEF/ WHO* estimate Reported ( ) Lesotho568 (1996) (1995) 760 Nicaragua133 (2005) (2005) 87 Zimbabwe771 (2002) (2005) 560 *

Age specific PRMR

Limitations PRMR Combines limitation of two adjustment measures Balance between migration and HIV issues (5-65+ vs ) Adjustment is intercensal while PRD refer to year before the census –Same for fertility In a period of rapid fertility decline and increasing mortality (e.g. Lesotho and Zimbabwe) it might not be wise to use intercensal estimates. All causes of MM included –Only approximation of real MM

Differential analysis (Lesotho, Nicaragua) Residence Education level –Head of Household Wealth calculated using asset index Filmer and Pritchett Assumed adjustment factors constant

Differential PMMR ResidenceEducation level Head of Household Wealth UrbanRuralNo ed1-3 years 4-7 years 8+PoorMiddleRich Lesotho Nicaragua

Smoothing modelling LOESS function in R (Cleveland and Devlin, 1988) logit (m a )=s(a) + e a Where m=PRMR a=age e=random error term By differentials (e.g.: education, wealth, residence) Scatterplot smoothing algorithm that behaves like a generalised linear model but without having to specify the form of independence

Some work and some don’t…

Discussion on differential analysis Differential analysis can spot differential inconsistencies Oversensitive on the tales due to low numbers –Loess curve a feasible option Best function to adapt data –Loess curves perform better than splines and polynomials as based on local estimation hence less influences by values at the extremes Interpretation should focus on trend rather than single points Need for sensitivity analysis

Discussion on MM in census data Census data give reasonable estimates Although it’s only pregnancy related Quick fix not feasible with high levels of migration- e.g. Zimbabwe Constant adjustment by age might not work for maternal mortality Need to cross-validate with DSS data. More synergies needed between adult mortality and MM Need for more advocacy and training