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Measuring differential maternal mortality using census data

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.

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Measuring differential maternal mortality using census data

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  1. Measuring differential maternal mortality using census data Tiziana Leone LSE Health

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

  3. 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 deaththe death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the cause of death.

  4. Measures of Maternal Mortality

  5. 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

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

  7. Few numbers Data refer to latest available year. Number in brackets for Lesotho refer to 1995

  8. Data • Nicaragua 1995-2005 census • Lesotho 1986-1996 census • Zimbabwe 1992-2002 census

  9. Methods for the PRMR • Series of evaluations methods based on demographic ‘indirect techniques’ with adjustments when needed. Hill et al 2001. • Check degree of death coverage in the population • General Growth Balance • Synthetic extinct generation • Check quality of fertility data • P/F Ratio 20-24 • Check quality of information on pregnancy related deaths • No formal methods.

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

  11. Adjustment factors

  12. Plausibility checks

  13. MMR *

  14. Age specific PRMR

  15. Limitations PRMR • Combines limitation of two adjustment measures • Balance between migration and HIV issues (5-65+ vs 30-65+) • 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

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

  17. Differential PMMR

  18. Smoothing modelling LOESS function in R (Cleveland and Devlin, 1988) logit (ma)=s(a) + ea • 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

  19. Some work and some don’t…

  20. 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

  21. 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

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