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Estimation of pregnancy-related mortality from deaths reported by households

Description of method

If questions are asked in a census or large household survey about deaths in the household in a reference period, and further questions are asked about the timing relative to pregnancy of deaths of women of childbearing age, it is possible to derive estimates of pregnancy-related mortality. If additional information on cause of death is available, for instance from a verbal autopsy enquiry, it is possible to estimate maternal mortality, but this is quite unusual and will not be covered explicitly here.

The use of census or large survey data on recent household deaths to estimate overall adult mortality, and the evaluation of such data, are described elsewhere. Any error in reporting on deaths is likely to have a proportionately similar effect on estimates of pregnancy-related mortality, so evaluation of data quality, and adjustment if needed, are essential parts of the analysis.

Data requirements and assumptions

Tabulations of data required

• Number of women, by five-year age group from household questionnaire.
• Number of household deaths in the previous 12 months (or similar period) by age and sex.
• For deaths of women of reproductive age (usually 15 to 49), whether the death occurred during pregnancy, delivery or 42 days/2 months post-partum.
• Age-specific fertility rates and General Fertility Rate for the time period.

If sample or design weights have been provided with the data, they must be applied in the appropriate manner in producing input tables.

Important assumptions

• That any effect of household dissolution arising from death of a member is trivial.
• (If adjustment of deaths or births is to be made), that errors in reporting deaths and births are proportional by age.
• That any omission of deaths does not vary with whether or not the deaths are pregnancy-related.
• That reporting of deaths as pregnancy-related is approximately accurate.

Preparatory work and preliminary investigations

Data quality assessment for household deaths and for recent age-specific fertility rates are described elsewhere. The only data quality assessments specific to the estimation of Pregnancy-Related Mortality are of the information on the proportion of deaths of women of reproductive age that are pregnancy-related, PPRD, and the proportions of pregnancy-related deaths that occur during pregnancy, during delivery and in the 42 days (or two months) post-partum.

Potential for data quality assessment for issues other than recording of overall numbers of births and deaths is limited to a plausibility check for reporting of deaths as pregnancy-related. The age pattern of the proportion of deaths that are pregnancy-related should resemble the age distribution of age-specific fertility.

Caveats and warnings

It is widely believed that questions on household deaths and on births in the year before a census or survey often under-report true numbers of events. Careful evaluation of coverage of both types of event is essential. In the unlikely event that under-reporting of both types of event is approximately equal, the pregnancy-related mortality ratio will not be seriously biased, although the pregnancy-related mortality rate will still be biased. However, if data evaluation indicates omission of deaths and births, the data will need to be corrected before a final estimate of pregnancy-related mortality is arrived at.

Application of method

The method is applied in the following stages:

Step 1: Extract tabulations of the data

Instructions as to how to extract the data are outside the scope of this manual. It is usually a simple matter to produce cross-tabulations of the number of women by age group, and the number of deaths of women by age group and timing of death relative to pregnancy (during pregnancy, during delivery, or during the 42 days/2 months post-partum). Where appropriate, the tabulations should be weighted to compensate for under-enumeration (following a post-enumeration survey) and whether the data being analysed are a micro-sample or not. In addition, estimates of age-specific fertility are required. The process of estimating fertility is described elsewhere.

We define the following terms:

$\text{\hspace{0.17em}}{}_{5}D{}_{x}\text{\hspace{0.17em}}$

- the reported number of female household members dying between ages x and x+5

$\text{\hspace{0.17em}}{}_{5}PR{D}_{x}\text{\hspace{0.17em}}$

- the number of pregnancy-related deaths of female household members between ages x and x+5

${\text{\hspace{0.17em}}}_{5}{f}_{x}^{}\text{\hspace{0.17em}}$

- age-specific fertility rates of women aged between x and x+5

${\text{\hspace{0.17em}}}_{5}{N}_{x}^{f}\text{\hspace{0.17em}}$

- the population of women aged between x and x+5 as enumerated in the census or large survey

Tabulations of all four of the above variables are required.

Step 2: Derive measures of mortality

The age-specific mortality rate is derived by dividing the reported deaths of women in the household by the number of person years lived by the population in each age group,

$5 M x = 5 D x 5 N x f$
Equation 1

The age-specific pregnancy-related mortality rate in each age group is given by

$5 PRMRat e x = 5 PR D x 5 N x f$
Equation 2

And the age-specific pregnancy-related mortality ratio is

$5 PRM R x =100,000.( 5 PR D x 5 N x f . 5 f x )$
Equation 3

Finally, the proportion of deaths that are pregnancy-related is

$5 PPR D x = 5 PR D x 5 D x f .$
Equation 4

The proportionate distribution of the PRD over ages 15 to 49 is given by

$5 DPR D x = 5 PR D x ∑ x=15,5 45 5 PR D x$
Equation 5

Worked example

We use as an example the data from the 2008 Malawi Census, specifically the data from questions concerning deaths in the 12 months before the survey/census.

Step 1: Extract tabulations of the data

Table 1 is tabulated from individual-level data from a 10 per cent IPUMS sample from the Malawi Census. The table shows the female population of reproductive age by five-year age groups, female deaths reported as occurring in the 12 months before the census, and, for deaths of females aged 15 to 49, whether the death occurred during pregnancy, during delivery, or in the 42 days post-partum.

Table 1 Female population of reproductive age 15-49 and deaths by whether pregnancy-related, Malawi 2008 Census

 Female Deaths Age Group Female Population During Pregnancy During Delivery Post-Partum Total Pregnancy-Related All deaths (i) (ii) (iii) (iv) (v) (vi) 15-19 67,918 43 25 26 94 235 20-24 69,069 68 40 36 144 389 25-29 57,478 84 31 32 147 442 30-34 41,073 92 24 37 153 471 35-39 29,993 56 15 23 94 346 40-44 22,294 42 4 14 60 238 45-49 17,564 38 3 4 45 185 Total 15-49 310,748 423 142 172 737 2,306 Source: Malawi 2008 Census, 10% sample

Step 2: Derive measures of mortality

Application of the method for data available in the form given in Table 1 is shown in Table 2. All cause age-specific mortality is calculated (col. i) by dividing deaths (col. vi of Table 1) by female population (col. i of Table 1) as per Equation 1. Note that strictly speaking the deaths pertain to a population on average half a year earlier than that recorded, but the error involved in ignoring this complication is trivial and will be included in an adjustment if the deaths are corrected using one of the appropriate death distribution methods. Age-specific pregnancy-related mortality rates are then calculated by dividing pregnancy-related deaths (col. v of Table 1) by female population (col. i of Table 1) as in Equation 2. Age-specific pregnancy-related mortality ratios in col. iv of Table 2 are then obtained by dividing the age-specific pregnancy-related mortality rates (col. ii) by age-specific fertility rates (col. iii, obtained from other sources) – as in Equation 3. Age-specific proportions of deaths pregnancy-related are then calculated, dividing pregnancy-related deaths (col. v of Table 1) by all-cause deaths (col. vi of Table 1) (Equation 4). Finally, the proportional contribution of each age group to overall pregnancy-related deaths is calculated by dividing the number of pregnancy-related deaths in each age group by the total number of pregnancy-related deaths (col. v of Table 1) (Equation 5).

Table 2 Adult female mortality rates and pregnancy-related mortality rates: Malawi 2008 Census

 Age Group Age-Specific Proportion of Deaths Pregnancy-Related Proportion of Pregnancy-Related Deaths Proportion of Births in Previous Year Mortality Rate Pregnancy-Related Mortality Rate Fertility Rate Pregnancy-related Mortality Ratio Table 1 (vi)/(i) Table 1 (v)/(i) (ii)/(iii) Table 1 (v)/(vi) Table 1 (v)/Sum(v) 15-19 0.00346 0.00138 0.1108 1249.12 0.40000 0.127544 0.14408 20-24 0.00563 0.00208 0.2464 846.13 0.37018 0.195387 0.32584 25-29 0.00769 0.00256 0.2296 1113.89 0.33258 0.199457 0.25267 30-34 0.01147 0.00373 0.1941 1919.15 0.32484 0.207598 0.15264 35-39 0.01154 0.00313 0.1457 2151.04 0.27168 0.127544 0.08367 40-44 0.01068 0.00269 0.0718 3748.34 0.25210 0.081411 0.03065 45-49 0.01053 0.00256 0.0311 8238.13 0.24324 0.061058 0.01046 Total 15-49 0.00755 0.00241 0.1713 1895.63 0.33804 1 1 Source: Table 1 and Malawi 2008 Census, 10% sample

Diagnostics, analysis and interpretation

Checks and validation

The key checks for this methodology are the assessment of coverage of adult female deaths and of births (see Death Distribution Methods and Assessment of recent fertility data). The only checks specific to this method are of the distribution of pregnancy-related deaths by age and a very weak check, available in many instances, on the distribution of pregnancy-related deaths by whether they occurred during pregnancy, during delivery, or in the 6 weeks/2 months post-partum. For the assessment of the distribution of pregnancy-related deaths by age, the key comparison is with the distribution of births by age. These two distributions are shown in the last two columns of Table 2. The proportions of pregnancy-related deaths through age group 25-29 are lower than the corresponding proportions of births, but above age 30 the reverse is true. This pattern is plausible given accumulating evidence that pregnancy-related mortality risks are broadly similar by age below age 30 but then rise steeply above age 30. It is instructive to compare the patterns with those based on the sibling histories of the 2004 Malawi DHS (described elsewhere). In the sibling history example, the proportions of pregnancy-related deaths contributed by mothers under age 25 were much smaller than the corresponding proportions of births. Here, the proportions are smaller, but not so much smaller as to lead to concerns about data accuracy.

It is noted above that the distribution of pregnancy-related deaths by whether they occurred during pregnancy, during delivery, or in the 6 weeks/2 months post-partum is a weak check. It is weak because there is no strong prior as to what this distribution should look like across different settings, and because in practice the distribution is found to vary wildly by data source.

Interpretation

The importance of evaluating coverage of adult female deaths and births cannot be over-emphasized. Household deaths in some settings seem to be under-reported by as much as 50 per cent, and such an error would translate into a bias in the pregnancy-related mortality ratio of a similar magnitude. Recent births may also be under-reported, an error that may partially compensate for omission of deaths in the PRMR. Death distribution methods suggest that female deaths were under-reported in the 2008 Malawi Census by somewhere between 40 and 50 per cent, whereas application of the relational Gompertz method to the same data indicates births in the year before the census were under-reported by about 18 per cent. The net effect of the two compensating errors would be an under-estimate of the pregnancy-related mortality ratio of about two-fifths.

In interpreting information on pregnancy-related mortality for Malawi, it is also essential to remember that Malawi was affected by a substantial HIV epidemic in the late 1990s and early 2000s. Associated HIV-related mortality will affect the results of death distribution methods, as described elsewhere, so the adjustment factor derived above should be used with caution.

One advantage of census data or large census samples is the lack of sampling uncertainty in the results. Thus whereas it is hazardous to draw conclusions from sibling histories about differentials, similar reservations do not apply to the same extent to estimates derived from census data (though even with a census numbers may be small for sub-groups, introducing stochastic error). Also, given the need to evaluate, and often adjust, data from census questions, any estimates will still be subject to considerable uncertainty.

References

Hill, K, C. Stanton, M. Levin et al. (2011) Measuring Maternal Mortality from a Census: Guidelines for Potential Users. Geneva: World Health Organization.