Estimating 1a0 and 4a1 in a Life Table: A Model Approach Based on Newly Collected Data.

The average age of infant deaths, a10, and the average number of years lived-in the age interval-by those dying between ages 1 and 5, a41, are important quantities allowing the construction of any life table including these ages. In many applications, the direct calculation of these parameters is not possible, so they are estimated using the infant mortality rate-or the death rate from 0 to 1-as a predictor. Existing methods are general approximations that do not consider the full variability in the age patterns of mortality below the age of 5. However, at the same level of mortality, under-five deaths can be more or less concentrated during the first weeks and months of life, thus resulting in very different values of a10 and a41. This article proposes an indirect estimation of these parameters by using a recently developed model of under-five mortality and taking advantage of a new, comprehensive database by detailed age-which is used for validation. The model adapts to a variety of inputs (e.g., rates, probabilities, or the proportion of deaths by sex or for both sexes combined), providing more flexibility for the users and increasing the precision of the estimates. This fresh perspective consolidates a new method that outperforms all previous approaches.

Pregnancy-related mortality up to 1 year postpartum in sub-Saharan Africa: an analysis of verbal autopsy data from six countries.

OBJECTIVE: To compare the causes of death for women who died during pregnancy and within the first 42 days postpartum with those of women who died between >42 days and within 1 year postpartum. DESIGN: Open population cohort (Health and Demographic Surveillance Systems). SETTING: Ten Health and Demographic Surveillance Systems (HDSS) in The Gambia, Kenya, Malawi, Tanzania, Ethiopia and South Africa. POPULATION: 2114 deaths which occurred within 1 year of the end of pregnancy where a verbal autopsy interview was conducted from 2000 to 2019. METHODS: InterVA5 and InSilicoVA verbal autopsy algorithms were used to attribute the most likely underlying cause of death, which were grouped according to adapted International Classification of Diseases-Maternal Mortality categories. Multinomial regression was used to compare differences in causes of deaths within 42 days versus 43-365 days postpartum adjusting for HDSS and time period (2000-2009 and 2010-2019). MAIN OUTCOME MEASURES: Cause of death and the verbal autopsy Circumstances of Mortality Categories (COMCATs). RESULTS: Of 2114 deaths, 1212 deaths occurred within 42 days postpartum and 902 between 43 and 365 days postpartum. Compared with deaths within 42 days, deaths from HIV and TB, other infectious diseases, and non-communicable diseases constituted a significantly larger proportion of late pregnancy-related deaths beyond 42 days postpartum, and health system failures were important in the circumstances of those deaths. The contribution of HIV and TB to deaths beyond 42 days postpartum was greatest in Southern Africa. The causes of pregnancy-related mortality within and beyond 42 days postpartum did not change significantly between 2000-2009 and 2010-2019. CONCLUSIONS: Cause of death data from the extended postpartum period are critical to inform prevention. The dominance of HIV and TB, other infectious and non-communicable diseases to (late) pregnancy-related mortality highlights the need for better integration of non-obstetric care with ante-, intra- and postpartum care in high-burden settings.

Lifetime risk of maternal near miss morbidity: a novel indicator of maternal health.

BACKGROUND: The lifetime risk of maternal death quantifies the probability that a 15-year-old girl will die of a maternal cause in her reproductive lifetime. Its intuitive appeal means it is a widely used summary measure for advocacy and international comparisons of maternal health. However, relative to mortality, women are at an even higher risk of experiencing life-threatening maternal morbidity called 'maternal near miss' (MNM) events-complications so severe that women almost die. As maternal mortality continues to decline, health indicators that include information on both fatal and non-fatal maternal outcomes are required. METHODS: We propose a novel measure-the lifetime risk of MNM-to estimate the cumulative risk that a 15-year-old girl will experience a MNM in her reproductive lifetime, accounting for mortality between the ages 15 and 49 years. We apply the method to the case of Namibia (2019) using estimates of fertility and survival from the United Nations World Population Prospects along with nationally representative data on the MNM ratio. RESULTS: We estimate a lifetime risk of MNM in Namibia in 2019 of between 1 in 40 and 1 in 35 when age-disaggregated MNM data are used, and 1 in 38 when a summary estimate for ages 15-49 years is used. This compares to a lifetime risk of maternal death of 1 in 142 and yields a lifetime risk of severe maternal outcome (MNM or death) of 1 in 30. CONCLUSIONS: The lifetime risk of MNM is an urgently needed indicator of maternal morbidity because existing measures (the MNM ratio or rate) do not capture the cumulative risk over the reproductive life course, accounting for fertility and mortality levels.

Comparison of programmatic data from antenatal clinics with population-based HIV prevalence estimates in the era of universal test and treat in western Kenya.

OBJECTIVE: To compare HIV prevalence estimates from routine programme data in antenatal care (ANC) clinics in western Kenya with HIV prevalence estimates in a general population sample in the era of universal test and treat (UTT). METHODS: The study was conducted in the area covered by the Siaya Health Demographic Surveillance System (Siaya HDSS) in western Kenya and used data from ANC clinics and the general population. ANC data (n = 1,724) were collected in 2018 from 13 clinics located within the HDSS. The general population was a random sample of women of reproductive age (15-49) who reside in the Siaya HDSS and participated in an HIV sero-prevalence survey in 2018 (n = 2,019). Total and age-specific HIV prevalence estimates were produced from both datasets and demographic decomposition methods were used to quantify the contribution of the differences in age distributions and age-specific HIV prevalence to the total HIV prevalence estimates. RESULTS: Total HIV prevalence was 18.0% (95% CI 16.3-19.9%) in the ANC population compared with 18.4% (95% CI 16.8-20.2%) in the general population sample. At most ages, HIV prevalence was higher in the ANC population than in the general population. The age distribution of the ANC population was younger than that of the general population, and because HIV prevalence increases with age, this reduced the total HIV prevalence among ANC attendees relative to prevalence standardised to the general population age distribution. CONCLUSION: In the era of UTT, total HIV prevalence among ANC attendees and the general population were comparable, but age-specific HIV prevalence was higher in the ANC population in most age groups. The expansion of treatment may have led to changes in both the fertility of women living with HIV and their use of ANC services, and our results lend support to the assertion that the relationship between ANC and general population HIV prevalence estimates are highly dynamic.

Modeling Age Patterns of Under-5 Mortality: Results From a Log-Quadratic Model Applied to High-Quality Vital Registration Data.

Information about how the risk of death varies with age within the 0-5 age range represents critical evidence for guiding health policy. This study proposes a new model for summarizing regularities about how under-5 mortality is distributed by detailed age. The model is based on a newly compiled database that contains under-5 mortality information by detailed age in countries with high-quality vital registration systems, covering a wide array of mortality levels and patterns. It uses a log-quadratic approach in predicting a full mortality schedule between ages 0 and 5 on the basis of only one or two parameters. With its larger number of age-groups, the proposed model offers greater flexibility than existing models in terms of both entry parameters and model outcomes. We present applications of this model for evaluating and correcting under-5 mortality information by detailed age in countries with problematic mortality data.

Estimating the infant mortality rate from DHS birth histories in the presence of age heaping.

BACKGROUND: The infant mortality rate (IMR) is a critical indicator of population health, but its measurement is subject to response bias in countries without complete vital registration systems who rely instead on birth histories collected via sample surveys. One of the most salient bias is the fact that child deaths in these birth histories tend to be reported with a large amount of heaping at age 12 months. Because of this issue, analysts and international agencies do not directly use IMR estimates based on surveys such as Demographic and Health Surveys (DHS); they rely instead on mortality models such as model life tables. The use of model life tables in this context, however, is arbitrary, and the extent to which this approach appropriately addresses bias in DHS-based IMR estimates remains unclear. This hinders our ability to monitor IMR levels and trends in low-and middle-income countries. The objective of this study is to evaluate age heaping bias in DHS-based IMR estimates and propose an improved method for adjusting this bias. METHODS AND FINDINGS: Our method relies on a recently-developed log-quadratic model that can predict age-specific mortality by detailed age between 0 and 5. The model's coefficients were derived from a newly constituted database, the Under-5 Mortality Database (U5MD), that represents the mortality experience of countries with high-quality vital registration data. We applied this model to 204 DHS surveys, and compared unadjusted IMR values to IMR values adjusted with the log-quadratic model as well as with the classic model life table approach. Results show that contrary to existing knowledge, age heaping at age 12 months rarely generates a large amount of bias in IMR estimates. In most cases, the unadjusted IMR values were not deviating by more than +/- 5% from the adjusted values. The model life table approach, by contrast, introduced an unwarranted, downward bias in adjusted IMR values. We also found that two regions, Sub-Saharan Africa and South Asia, present age patterns of under-5 mortality that strongly depart from the experience represented in the U5MD. For these countries, neither the existing model life tables nor the log-quadratic model can produce empirically-supported IMR adjustments. CONCLUSIONS: Age heaping at age 12 months produces a smaller amount of bias in DHS-based IMR estimates than previously thought. If a large amount of age heaping is present in a survey, the log-quadratic model allows users to evaluate, and whenever necessary, adjust IMR estimates in a way that is more informed by the local mortality pattern than existing approaches. Future research should be devoted to understanding why Sub-Saharan African and South Asian countries have such distinct age patterns of under-five mortality.