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Using census data to measure maternal mortality: A review of recent experience.

ABSTRACT: BACKGROUND:The Sustainable Development Goals adopted by the United Nations General Assembly in 2015 (United Nations 2015) set national targets for reducing maternal mortality, putting pressure on governments of countries lacking comprehensive statistical systems to find other ways to measure it. One approach tested since the 1990s has been to collect necessary data through national population censuses. OBJECTIVE:This paper reviews maternal mortality data from the 2010 round of censuses for several countries to determine whether the census is useful for monitoring maternal mortality. METHODS:Data on births, deaths, and pregnancy-related deaths from two censuses for 10 countries was evaluated using standard methods; adjustments were applied to the reported numbers if so indicated. RESULTS:In general, the censuses underreported births moderately and underreported deaths by larger amounts; except in one case, proportions of pregnancy-related deaths appeared plausible. Adjusted estimates of the pregnancy-related mortality ratio (PRMR) were generally higher than estimates from Demographic and Health Survey sibling data or estimates of maternal mortality developed by cross-national studies. CONCLUSIONS:Analysis of recent data confirms results of earlier assessments: Census data provides imperfect but still valuable information on maternal mortality. Data requires careful assessment and often adjustment, resulting in estimates with large uncertainty. CONTRIBUTION:This paper provides additional evidence as to whether maternal mortality can usefully be measured by population censuses in countries lacking civil registration data.

SUBMITTER: Hill K

PROVIDER: S-EPMC6903798 | biostudies-literature | 2018 Jul-Dec

REPOSITORIES: biostudies-literature

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Using census data to measure maternal mortality: A review of recent experience.

Hill Kenneth K Johnson Peter P Singh Kavita K Amuzu-Pharin Anthony A Kharki Yagya Y

Demographic research 20180701

<h4>Background</h4>The Sustainable Development Goals adopted by the United Nations General Assembly in 2015 (United Nations 2015) set national targets for reducing maternal mortality, putting pressure on governments of countries lacking comprehensive statistical systems to find other ways to measure it. One approach tested since the 1990s has been to collect necessary data through national population censuses.<h4>Objective</h4>This paper reviews maternal mortality data from the 2010 round of cen ...[more]

PMID: 31824231

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Project description:BackgroundFor countries to contribute to Sustainable Development Goal 3.1 of reducing the global maternal mortality ratio (MMR) to less than 70 per 100,000 live births by 2030, identifying the drivers of maternal mortality is critically important. The ability of countries to identify the key drivers is however hampered by the lack of data sources with sufficient observations of maternal death to allow a rigorous analysis of its determinants. This paper overcomes this problem by utilising census data. In the context of Indonesia, we merge individual-level data on pregnancy-related deaths and households' socio-economic status from the 2010 Indonesian population census with detailed data on the availability and quality of local health services from the Village Census. We use these data to test the hypothesis that health service access and quality are important determinants of maternal death and explain the differences between high maternal mortality and low maternal mortality provinces.MethodsThe 2010 Indonesian Population Census identifies 8075 pregnancy-related deaths and 5,866,791 live births. Multilevel logistic regression is used to analyse the impacts of demographic characteristics and the existence of, distance to and quality of health services on the likelihood of maternal death. Decomposition analysis quantifies the extent to which the difference in maternal mortality ratios between high and low performing provinces can be explained by demographic and health service characteristics.FindingsHealth service access and characteristics account for 23% (CI: 17.2% to 28.5%) of the difference in maternal mortality ratios between high and low-performing provinces. The most important contributors are the number of doctors working at the community health centre (8.6%), the number of doctors in the village (6.9%) and distance to the nearest hospital (5.9%). Distance to health clinics and the number of midwives at community health centres and village health posts are not significant contributors, nor is socio-economic status. If the same level of access to doctors and hospitals in lower maternal mortality Java-Bali was provided to the higher maternal mortality Outer Islands of Indonesia, our model predicts 44 deaths would be averted per 100,000 pregnancies.ConclusionIndonesia has employed a strategy over the past several decades of increasing the supply of midwives as a way of decreasing maternal mortality. While there is evidence of reductions in maternal mortality continuing to accrue from the provision of midwife services at village health posts, our findings suggest that further reductions in maternal mortality in Indonesia may require a change of focus to increasing the supply of doctors and access to hospitals. If data on maternal death is collected in a subsequent census, future research using two waves of census data would prove a useful validation of the results found here. Similar research using census data from other countries is also likely to be fruitful.

Project description:ObjectiveTo assess whether application of a standard algorithm to hospitalizations in the prenatal and postpartum (42 days) periods increases identification of severe maternal morbidity (SMM) beyond analysis of only the delivery event.MethodsWe performed a retrospective cohort study using data from the PELL (Pregnancy to Early Life Longitudinal) database, a Massachusetts population-based data system that links records from birth certificates to delivery hospital discharge records and nonbirth hospital records for all birthing individuals. We included deliveries from January 1, 2009, to December 31, 2018, distinguishing between International Classification of Diseases Ninth (ICD-9) and Tenth Revision (ICD-10) coding. We applied the modified Centers for Disease Control and Prevention algorithm for SMM used by the Alliance for Innovation on Maternal Health to hospitalizations across the antenatal period through 42 days postpartum. Morbidity was examined both with and without blood transfusion.ResultsOverall, 594,056 deliveries were included in the analysis, and 3,947 deliveries met criteria for SMM at delivery without transfusion and 9,593 with transfusion for aggregate rates of 150.1 (95% CI 146.7-153.5) using ICD-9 codes and 196.6 (95% CI 189.5-203.7) using ICD-10 codes per 10,000 deliveries. Severe maternal morbidity at birth increased steadily across both ICD-9 and ICD-10 from 129.4 in 2009 (95% CI 126.2-132.6) using ICD-9 to 214.3 per 10,000 (95% CI 206.9-221.8) in 2018 using ICD-10. Adding prenatal and postpartum hospitalizations increased cases by 21.9% under both ICD-9 and ICD-10, resulting in a 2018 rate of 258.7 per 10,000 (95% CI 250.5-266.9). The largest increase in detected morbidity in the prenatal or postpartum time period was attributed to sepsis cases.ConclusionInclusion of prenatal and postpartum hospitalizations in the identification of SMM resulted in increased ascertainment of morbid events. These results suggest a need to ensure surveillance of care quality activities beyond the birth event.

Project description:BackgroundSocioeconomic inequalities in mortality are evident in all high-income countries, and ongoing monitoring is recommended using linked census-mortality data. Using such data, we provide the first estimates of education-related inequalities in cause-specific mortality in Australia, suitable for international comparisons.MethodsWe used Australian Census (2016) linked to 13 months of Death Registrations (2016-17). We estimated relative rates (RR) and rate differences (RD, per 100 000 person-years), comparing rates in low (no qualifications) and intermediate (secondary school) with high (tertiary) education for individual causes of death (among those aged 25-84 years) and grouped according to preventability (25-74 years), separately by sex and age group, adjusting for age, using negative binomial regression.ResultsAmong 13.9 M people contributing 14 452 732 person-years, 84 743 deaths occurred. All-cause mortality rates among men and women aged 25-84 years with low education were 2.76 [95% confidence interval (CI): 2.61-2.91] and 2.13 (2.01-2.26) times the rates of those with high education, respectively. We observed inequalities in most causes of death in each age-sex group. Among men aged 25-44 years, relative and absolute inequalities were largest for injuries, e.g. transport accidents [RR = 10.1 (5.4-18.7), RD = 21.2 (14.5-27.9)]). Among those aged 45-64 years, inequalities were greatest for chronic diseases, e.g. lung cancer [men RR = 6.6 (4.9-8.9), RD = 57.7 (49.7-65.8)] and ischaemic heart disease [women RR = 5.8 (3.7-9.1), RD = 20.2 (15.8-24.6)], with similar patterns for people aged 65-84 years. When grouped according to preventability, inequalities were large for causes amenable to behaviour change and medical intervention for all ages and causes amenable to injury prevention among young men.ConclusionsAustralian education-related inequalities in mortality are substantial, generally higher than international estimates, and related to preventability. Findings highlight opportunities to reduce them and the potential to improve the health of the population.

Project description:BackgroundAdvancements in linking publicly available census records with vital and administrative records have enabled novel investigations in epidemiology and social history. However, in the absence of unique identifiers, the linkage of the records may be uncertain or only be successful for a subset of the census cohort, resulting in missing data. For survival analysis, differential ascertainment of event times can impact inference on risk associations and median survival.MethodsWe modify some existing approaches that are commonly used to handle missing survival times to accommodate this imperfect linkage situation including complete case analysis, censoring, weighting, and several multiple imputation methods. We then conduct simulation studies to compare the performance of the proposed approaches in estimating the associations of a risk factor or exposure in terms of hazard ratio (HR) and median survival times in the presence of missing survival times. The effects of different missing data mechanisms and exposure-survival associations on their performance are also explored. The approaches are applied to a historic cohort of residents in Ambler, PA, established using the 1930 US census, from which only 2,440 out of 4,514 individuals (54%) had death records retrievable from publicly available data sources and death certificates. Using this cohort, we examine the effects of occupational and paraoccupational asbestos exposure on survival and disparities in mortality by race and gender.ResultsWe show that imputation based on conditional survival results in less bias and greater efficiency relative to a complete case analysis when estimating log-hazard ratios and median survival times. When the approaches are applied to the Ambler cohort, we find a significant association between occupational exposure and mortality, particularly among black individuals and males, but not between paraoccupational exposure and mortality.DiscussionThis investigation illustrates the strengths and weaknesses of different imputation methods for missing survival times due to imperfect linkage of the administrative or registry data. The performance of the methods may depend on the missingness process as well as the parameter being estimated and models of interest, and such factors should be considered when choosing the methods to address the missing event times.

Project description:BackgroundIn recent years, births to older mothers and multiparous mothers have increased rapidly with the change of birth policy in China. And mothers of advanced age are more likely to have maternal complications and poor birth outcomes. We aimed to estimate the recent trends and underlying risk factors of maternal mortality.MethodsIn this systematic assessment, we used data from the National Maternal and Child Health Routine Reporting System (2013-2018), Jiangsu Provincial Maternal Mortality Surveillance System (2017-2018), the Integrated National Mortality Surveillance System (2018), City Statistical Yearbooks (2018), City Health Statistical Yearbooks (2018). The factors associated with maternal mortality ratio (MMR) were explored using the stepwise regression analysis and cluster analysis.ResultsThe MMR maintained at low levels between 2013 and 2016 and there was a slight increase in maternal mortality after 2016 in Jiangsu province. With the implementation of the China's universal two child policies, the percentage of multiparous mothers ascended from 34.2% (95% confidence interval (CI) = 34.1-34.3%) in 2013 to 51.4% (95% CI = 51.3-51.6%) in 2018 (beta = 3.88, P < 0.001). Consistently, the percentage of advanced maternal age (≥ 35) increased from 8.4% (95% CI = 8.4-8.5%) in 2013 to 10.4% (95% CI = 10.3-10.4%) in 2018 (beta = 0.50, P = 0.012). And we found that the percentage of multiparous mothers and advanced maternal age among maternal deaths were higher than all pregnant women (P < 0.001). In the stepwise regression analysis, four risk factors were significantly associated with maternal mortality ratio (primary industry of gross domestic product (GDP), rate of delivery in maternal and child health hospital, rate of cesarean section and rate of low birth weight). As the results derived from cluster analysis, the relatively developed regions had lower preventable maternal mortality ratio (43.5% (95% CI = 31.2-56.7%) vs. 62.6% (95% CI = 52.3-72.0%), P = 0.027).ConclusionsSince the universal two child policy has been associated with changes in health related birth characteristics: women giving birth have been more likely to be multiparous, and more likely to be aged 35 and over. This somewhat magnifies the impact of differences in economic development and obstetric services on MMR. The findings based on prefecture level data suggest that interventions must target economic development, the health system and maternal risk factors in synergy. These approaches will be of great benefit to control or diminish environmental factors associated with preventable deaths and will effectively reduce MMR and narrow the gap among the different regions.

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Using census data to measure maternal mortality: A review of recent experience.

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Using census data to measure maternal mortality: A review of recent experience.

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