Dataset Information

Why Does Child Mortality Decrease With Age? Modeling the Age-Associated Decrease in Mortality Rate Using WHO Metadata From 14 European Countries.

ABSTRACT: Background: Mortality rate rapidly decreases with age after birth, and, simultaneously, the spectrum of death causes show remarkable changes with age. This study analyzed age-associated decreases in mortality rate from diseases of all main chapters of the 10th revision of the International Classification of Diseases. Methods: The number of deaths was extracted from the mortality database of the World Health Organization. As zero cases could be ascertained for a specific age category, the Halley method was used to calculate the mortality rates in all possible calendar years and in all countries combined. Results: All causes mortality from the 1st day of life to the age of 10 years can be represented by an inverse proportion model with a single parameter. High coefficients of determination were observed for total mortality in all populations (arithmetic mean = 0.9942 and standard deviation = 0.0039). Slower or no mortality decrease with age was detected in the 1st year of life, while the inverse proportion method was valid for the age range [1, 10) years in most of all main chapters with three exceptions. The decrease was faster for the chapter "Certain conditions originating in the perinatal period" (XVI).The inverse proportion was valid already from the 1st day for the chapter "Congenital malformations, deformations and chromosomal abnormalities" (XVII).The shape of the mortality decrease was very different for the chapter "Neoplasms" (II) and the rates of mortality from neoplasms were age-independent in the age range [1, 10) years in all populations. Conclusion: The theory of congenital individual risks of death is presented and can explain the results. If it is valid, latent congenital impairments may be present among all cases of death that are not related to congenital impairments. All results are based on published data, and the data are presented as a supplement.

SUBMITTER: Dolejs J

PROVIDER: S-EPMC7653179 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Why Does Child Mortality Decrease With Age? Modeling the Age-Associated Decrease in Mortality Rate Using WHO Metadata From 14 European Countries.

Dolejs Josef J Homolková Helena H

Frontiers in pediatrics 20201027

<b>Background:</b> Mortality rate rapidly decreases with age after birth, and, simultaneously, the spectrum of death causes show remarkable changes with age. This study analyzed age-associated decreases in mortality rate from diseases of all main chapters of the 10th revision of the International Classification of Diseases. <b>Methods:</b> The number of deaths was extracted from the mortality database of the World Health Organization. As zero cases could be ascertained for a specific age categor ...[more]

PMID: 33194882

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Project description:Background: In humans, the mortality rate dramatically decreases with age after birth, and the causes of death change significantly during childhood. In the present study, we attempted to explain age-associated decreases in mortality for congenital anomalies of the central nervous system (CACNS), as well as decreases in total mortality with age. We further investigated the age trajectory of mortality in the biologically related category "diseases of the nervous system" (DNS). Methods: The numbers of deaths were extracted from the mortality database of the World Health Organization (WHO) for the following nine countries: Denmark, Finland, Norway, Sweden, Austria, the Czech Republic, Hungary, Poland, and Slovakia. Because zero cases could be ascertained over the age of 30 years in a specific age category, the Halley method was used to calculate the mortality rates in all possible calendar years and in all countries combined. Results: Total mortality from the first day of life up to the age of 10 years and mortality due to CACNS within the age interval of [0, 90) years can be represented by an inverse proportion with a single parameter. High coefficients of determination were observed for both total mortality (R2 = 0.996) and CACNS mortality (R2 = 0.990). Our findings indicated that mortality rates for DNS slowly decrease with age during the first 2 years of life, following which they decrease in accordance with an inverse proportion up to the age of 10 years. The theory of congenital individual risk (TCIR) may explain these observations based on the extinction of individuals with more severe impairments, as well as the bent curve of DNS, which exhibited an adjusted coefficient of determination of R¯2 = 0.966. Conclusion: The coincidence between the age trajectories of all-cause and CACNS-related mortality may indicate that the overall decrease in mortality after birth is due to the extinction of individuals with more severe impairments. More deaths unrelated to congenital anomalies may be caused by the manifestation of latent congenital impairments during childhood.

Project description:ImportanceCauses of death in children with birth defects are poorly understood.ObjectiveTo determine mortality rates by cause of death in children with and without birth defects.Design, setting, and participantsThis longitudinal cohort study included a population-based sample of 1 037 688 children and was conducted in all hospitals in Quebec, Canada, with 7 700 596 person-years of follow-up between birth and age 14 years (April 1, 2006, to March 31, 2020).ExposuresPresence or absence of a birth defect.Main outcomes and measuresOutcomes were all-cause and cause-specific mortality. Hazard ratios (HRs) and 95% CIs were computed for the association between birth defects and mortality with Cox proportional hazards models adjusted for patient characteristics.ResultsAmong the 1 037 688 children in the cohort, 95 566 had birth defects (56.5% boys). There were 532 542 boys in the cohort (51.3%), and mean (SD) age at the end of follow-up was 7.42 (3.72) years. There were 918 deaths among children with defects, and the mean (SD) age was 0.93 (2.07) years at death; there were 1082 deaths among the 942 122 children without defects, and the mean (SD) age at death was 0.50 (1.51) years. Mortality rates were higher for children with birth defects compared with no defect (1.3 vs 0.2 deaths per 1000 person-years, respectively). Girls (HR, 5.66; 95% CI, 4.96-6.47) and boys (HR, 4.69; 95% CI, 4.15-5.29) with birth defects had an elevated risk of death before 14 years compared with unaffected children. Birth defects were associated with mortality from circulatory (HR, 26.59; 95% CI, 17.73-39.87), respiratory (HR, 23.03; 95% CI, 15.09-35.14), and digestive causes (HR, 31.77; 95% CI, 11.87-85.04), but anomalies were rarely listed as the cause of death. Compared with children with no defect, those with birth defects were at greatest risk of death between 28 and 364 days of life.Conclusions and relevanceThis cohort study of 1 037 688 children suggests that birth defects were strongly associated with mortality owing to circulatory, respiratory, and digestive causes. This finding suggests that the contribution of birth defects may be underestimated in mortality statistics.

Project description:BackgroundIn a given population the age pattern of mortality is an important determinant of total number of deaths, age structure, and through effects on age structure, the number of births and thereby growth. Good mortality models exist for most populations except those experiencing generalized HIV epidemics and some developing country populations. The large number of deaths concentrated at very young and adult ages in HIV-affected populations produce a unique 'humped' age pattern of mortality that is not reproduced by any existing mortality models. Both burden of disease reporting and population projection methods require age-specific mortality rates to estimate numbers of deaths and produce plausible age structures. For countries with generalized HIV epidemics these estimates should take into account the future trajectory of HIV prevalence and its effects on age-specific mortality. In this paper we present a parsimonious model of age-specific mortality for countries with generalized HIV/AIDS epidemics.Methods and findingsThe model represents a vector of age-specific mortality rates as the weighted sum of three independent age-varying components. We derive the age-varying components from a Singular Value Decomposition of the matrix of age-specific mortality rate schedules. The weights are modeled as a function of HIV prevalence and one of three possible sets of inputs: life expectancy at birth, a measure of child mortality, or child mortality with a measure of adult mortality. We calibrate the model with 320 five-year life tables for each sex from the World Population Prospects 2010 revision that come from the 40 countries of the world that have and are experiencing a generalized HIV epidemic. Cross validation shows that the model is able to outperform several existing model life table systems.ConclusionsWe present a flexible, parsimonious model of age-specific mortality for countries with generalized HIV epidemics. Combined with the outputs of existing epidemiological and demographic models, this model makes it possible to project future age-specific mortality profiles and number of deaths for countries with generalized HIV epidemics.

Project description:BACKGROUND:Despite the sharp decline in global under-5 deaths since 1990, uneven progress has been achieved across and within countries. In sub-Saharan Africa (SSA), the Millennium Development Goals (MDGs) for child mortality were met only by a few countries. Valid concerns exist as to whether the region would meet new Sustainable Development Goals (SDGs) for under-5 mortality. We therefore examine further sources of variation by assessing age patterns, trends, and forecasts of mortality rates. METHODS AND FINDINGS:Data came from 106 nationally representative Demographic and Health Surveys (DHSs) with full birth histories from 31 SSA countries from 1990 to 2017 (a total of 524 country-years of data). We assessed the distribution of age at death through the following new demographic analyses. First, we used a direct method and full birth histories to estimate under-5 mortality rates (U5MRs) on a monthly basis. Second, we smoothed raw estimates of death rates by age and time by using a two-dimensional P-Spline approach. Third, a variant of the Lee-Carter (LC) model, designed for populations with limited data, was used to fit and forecast age profiles of mortality. We used mortality estimates from the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) to adjust, validate, and minimize the risk of bias in survival, truncation, and recall in mortality estimation. Our mortality model revealed substantive declines of death rates at every age in most countries but with notable differences in the age patterns over time. U5MRs declined from 3.3% (annual rate of reduction [ARR] 0.1%) in Lesotho to 76.4% (ARR 5.2%) in Malawi, and the pace of decline was faster on average (ARR 3.2%) than that observed for infant (IMRs) (ARR 2.7%) and neonatal (NMRs) (ARR 2.0%) mortality rates. We predict that 5 countries (Kenya, Rwanda, Senegal, Tanzania, and Uganda) are on track to achieve the under-5 sustainable development target by 2030 (25 deaths per 1,000 live births), but only Rwanda and Tanzania would meet both the neonatal (12 deaths per 1,000 live births) and under-5 targets simultaneously. Our predicted NMRs and U5MRs were in line with those estimated by the UN IGME by 2030 and 2050 (they overlapped in 27/31 countries for NMRs and 22 for U5MRs) and by the Institute for Health Metrics and Evaluation (IHME) by 2030 (26/31 and 23/31, respectively). This study has a number of limitations, including poor data quality issues that reflected bias in the report of births and deaths, preventing reliable estimates and predictions from a few countries. CONCLUSIONS:To our knowledge, this study is the first to combine full birth histories and mortality estimates from external reliable sources to model age patterns of under-5 mortality across time in SSA. We demonstrate that countries with a rapid pace of mortality reduction (ARR ? 3.2%) across ages would be more likely to achieve the SDG mortality targets. However, the lower pace of neonatal mortality reduction would prevent most countries from achieving those targets: 2 countries would reach them by 2030, 13 between 2030 and 2050, and 13 after 2050.

Dataset Information

Why Does Child Mortality Decrease With Age? Modeling the Age-Associated Decrease in Mortality Rate Using WHO Metadata From 14 European Countries.

Publications

Why Does Child Mortality Decrease With Age? Modeling the Age-Associated Decrease in Mortality Rate Using WHO Metadata From 14 European Countries.

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