Low-mortality Countries Research Articles

A 30-nation investigation of lay heritability beliefs.

Lay beliefs about human trait heritability are consequential for cooperation and social cohesion, yet there has been no global characterisation of these beliefs. Participants from 30 countries (N = 6128) reported heritability beliefs for intelligence, personality, body weight and criminality, and transnational factors that could influence these beliefs were explored using public nation-level data. Globally, mean lay beliefs differ from published heritability (h2) estimated by twin studies, with a worldwide majority overestimating the heritability of personality and intelligence, and underestimating body weight and criminality. Criminality was seen as substantially less attributable to genes than other traits. People from countries with high infant mortality tended to ascribe greater heritability for most traits, relative to people from low infant mortality countries. This study provides the first systematic foray into worldwide lay heritability beliefs. Future research must incorporate diverse global perspectives to further contextualise and extend upon these findings.

Cause-of-Death Determinants of Lifespan Inequality

We propose a novel decomposition approach that breaks down the levels and trends of lifespan inequality as the sum of cause-of-death contributions. The suggested method shows whether the levels and changes in lifespan inequality are attributable to the levels and changes in (1) the extent of inequality in the cause-specific age-at-death distribution (the “Inequality” component), (2) the total share of deaths attributable to each cause (the “Proportion” component), or (3) the cause-specific mean age at death (the “Mean” component). This so-called Inequality–Proportion–Mean (or IPM) method is applied to 10 low-mortality countries in Europe. Our findings suggest that the most prevalent causes of death (in our setting, “circulatory system” and “neoplasms”) do not necessarily contribute the most to overall levels of lifespan inequality. In fact, “perinatal and congenital” causes are the strongest drivers of lifespan inequality declines. The contribution of the IPM components to changes in lifespan inequality varies considerably across causes, genders, and countries. Among the three components, the Mean one explains the least lifespan inequality dynamics, suggesting that shifts in cause-specific mean ages at death alone contributed little to changes in lifespan inequality.

Ageing and diversity: Inequalities in longevity and health in low-mortality countries

Ageing and diversity: Inequalities in longevity and health in low-mortality countries

On the measurement of cause of death inequality.

Attempts at assessing heterogeneity in countries' mortality profiles often rely on measures of cause of death (CoD) diversity. Unfortunately, such indicators fail to take into consideration the degree of (dis)similarity among pairs of causes (e.g. 'transport injuries' and 'unintentional injuries' are implicitly assumed to be as dissimilar as 'transport injuries' and 'Alzheimer's disease')－an unrealistic and unduly restrictive assumption. We extend diversity indicators proposing a broader class of heterogeneity measures that are sensitive to the similarity between the causes of death one works with. The so-called 'CoD inequality' measures are defined as the average expected 'dissimilarity between any two causes of death'. A strength of the approach is that such measures are decomposable, so that users can assess the contribution of each cause to overall CoD heterogeneity levels-a useful property for the evaluation of public health policies. We have applied the method to 15 low-mortality countries between 1990 and 2019, using data from the Global Burden of Disease project. CoD inequality and CoD diversity generally increase over time across countries and sex, but with some exceptions. In several cases (notably, Finland), both indicators run in opposite directions. CoD inequality and diversity indicators capture complementary information about the heterogeneity of mortality profiles, so they should be analysed alongside other population health metrics, such as life expectancy and lifespan inequality.

Age and cause-of-death contributions to educational inequalities in life expectancy and lifespan variation in a low-mortality country: A cross-sectional study of 1.67 million deaths in Spain (2016–19)

BackgroundWe aim to assess the age- and cause-specific contributions to differences in life expectancy and lifespan variation between the high- and low-educated groups in Spain. MethodsWe use sex-, age-, education- and cause-specific mortality and population data for individuals aged 30 and over for 2016-19 in Spain. We estimated life expectancies, and standard deviations of the age-at-death distribution (lifespan variation), and we disentangled the contribution of age-causes of death to educational differences in both indicators. FindingsLife expectancy at age 30 was higher for high-educated groups compared to low-educated groups, 5.5 years for males and 3.0 years for females. Lifespan variation was higher for low-educated groups compared to high-educated groups, 2.9 years for males and 2.2 years for females. The main contributors to the life expectancy gaps in males were lung cancer (0.58 years) and ischaemic heart diseases (0.42 years), and in females were other cardiovascular causes (0.26 years), and ischaemic heart diseases (0.22 years). The main contributors to the lifespan variation gaps were in males lung cancer (−0.25 years) and ischaemic heart diseases (−0.22 years), while in females were other neoplasms and other diseases of the nervous system. InterpretationWhereas behavioural causes are more important in explaining educational inequalities in mortality among men, ageing-related causes of death seem more important among women. Attempts at narrowing socioeconomic gaps in mortality may benefit from applying gender-specific preventive policy measures.

Frailty at death: An examination of multiple causes of death in four low mortality countries in 2017.

The increasing prevalence of frailty in aging populations represents a major social and public health challenge which warrants a better understanding of the contribution of frailty to the morbid process. To examine frailty-related mortality as reported on the death certificate in France, Italy, Spain and the United States in 2017. We identify frailty at death for the population aged 50 years and over in France, Italy, Spain and the United States. We estimate the proportions of deaths by sex, age group and country with specific frailty-related ICD-codes on the death certificate 1) as the underlying cause of death (UC), 2) elsewhere in Part I (sequence of diseases or conditions or events leading directly to death), and 3) anywhere in Part II (conditions that do not belong in Part I but whose presence contributed to death). The age-standardized proportion of deaths with frailty at ages 50 and over is highest in Italy (25.0%), then in France (24.1%) and Spain (17.3%), and lowest in the United States (14.0%). Cross-country differences are smaller when frailty-related codes are either the underlying cause of the death or reported in Part II. Frailty-related mortality increases with age and is higher among females than males. Dementia is the most frequently reported frailty-related code. Notable cross-country differences were found in the prevalence and the type of frailty-related symptoms at death even after adjusting for differential age distributions.

Evaluation of age-specific causes of death in the context of the Italian longevity transition

In many low-mortality countries, life expectancy at birth increased steadily over the last century. In particular, both Italian females and males benefited from faster improvements in mortality compared to other high-income countries, especially from the 1960s, leading to an exceptional increase in life expectancy. However, Italy has not become the leader in longevity. Here, we investigate life expectancy trends in Italy during the period 1960–2015 for both sexes. Additionally, we contribute to the existing literature by complementing life expectancy with an indicator of dispersion in ages at death, also known as lifespan inequality. Lifespan inequality underlies heterogeneity over age in populating health improvements and is a marker of uncertainty in the timing of death. We further quantify the contributions of different age groups and causes of death to recent trends in life expectancy and lifespan inequality. Our findings highlight the contributions of cardiovascular diseases and neoplasms to the recent increase in life expectancy but not necessarily to the decrease in lifespan inequality. Our results also uncover a more recent challenge across Italy: worsening mortality from infectious diseases and mortality at older age.

Predictors of mortality and morbidity in critically ill COVID-19 patients: An experience from a low mortality country.

Background and AimsClinical characteristics and factors associated with mortality in patients admitted to the intensive care unit (ICU) in countries with low case fatality rates (CFR) are unknown. We sought to determine these in a large cohort of critically ill COVID‐19 patients in Qatar and explore the early mortality predictors.MethodsWe retrospectively studied the clinical characteristics and outcomes in patients admitted to the ICU at the national referral hospital for COVID‐19 patients in Qatar. Logistic regression analysis was used to determine factors associated with mortality.ResultsBetween March 7 and July 16, 2020, a total of 1079 patients with COVID‐19 were admitted to the ICU. The median (IQR) age of patients was 50 (41–59) years. Diabetes (47.3%) and hypertension (42.6%) were the most common comorbidities. In‐hospital mortality was 12.6% overall and 25.9% among those requiring mechanical ventilation. Factors independently associated with mortality included older age ([OR]; 2.3 [95% CI; 1.92–2.75] for each 10‐year increase in age, p < 0.001), chronic kidney disease (OR; 1.9 [95% CI; 1.02–3.54], p = 0.04), active malignancy (OR; 6.15 [95% CI; 1.79–21.12], p = 0.004), lower platelet count at ICU admission (OR; 1.41 [95% CI; 1.13–1.75] for each 100 × 103/µl decrease, p = 0.002), higher neutrophil‐to‐lymphocyte ratio at admission (OR; 1.01 [95% CI; 1–1.02] for each 1‐ point increase, p = 0.016), higher serum ferritin level at admission (OR; 1.05 [(95% CI; 1.02–1.08] for each 500 µg/L increase, p = 0.002), and higher serum bilirubin level at admission (OR; 1.19 [95% CI; 1.04–1.36] for each 10 μmol/L increase, p = 0.01).ConclusionsThe mortality rate among critically ill COVID‐19 patients is low in Qatar compared to other countries. Older age, chronic kidney disease, active malignancy, higher neutrophil‐to‐lymphocyte ratios, lower platelet counts, higher serum ferritin levels, and higher serum bilirubin levels are independent predictors of in‐hospital mortality.

The Cross-sectional Average Inequality in Lifespan (CAL†): A Lifespan Variation Measure That Reflects the Mortality Histories of Cohorts.

Lifespan variation is a key metric of mortality that describes both individual uncertainty about the length of life and heterogeneity in population health. We propose a novel and timely lifespan variation measure, which we call the cross-sectional average inequality in lifespan, or CAL†. This new index provides an alternative perspective on the analysis of lifespan inequality by combining the mortality histories of all cohorts present in a cross-sectional approach. We demonstrate how differences in the CAL† measure can be decomposed between populations by age and cohort to explore the compression or expansion of mortality in a cohort perspective. We apply these new methods using data from 10 low-mortality countries or regions from 1879 to 2013. CAL† reveals greater uncertainty in the timing of death than the period life table-based indices of variation indicate. Also, country rankings of lifespan inequality vary considerably between period and cross-sectional measures. These differences raise intriguing questions as to which temporal dimension is the most relevant to individuals when considering the uncertainty in the timing of death in planning their life courses.

Vaccines for preventing rotavirus diarrhoea: vaccines in use.

Vaccines for preventing rotavirus diarrhoea: vaccines in use.

Rotavirus-Diarrhea

Rotavirus is a double-stranded RNA virus that causes vomiting and diarrhea among children under 5 years. The main cause of mortality from rotavirus gastroenteritis (RVGE) is dehydration if not corrected appropriately with oral rehydration salts (ORS). Though the prevalence of RVGE is similar across countries and socio-economic groups, the higher mortality in Sub-Saharan Africa and South Asia is presumably due to poor awareness and poor health system responsiveness rather than poor hygiene. Enzyme immunoassays are the most commonly used tools for diagnosis of RVGE from stool samples. ORS and zinc remain the mainstay of treatment. Water, sanitation and hygiene measures did not appear to be very effective leaving vaccination among young children as the primary means of prevention. 4 WHO prequalified live attenuated, oral vaccines are available with different efficacy in high- versus low-mortality countries. There is a high degree of protection in countries with low RV mortality, and lower protection in countries with high RV morbidity and more fatalities. Rotavirus vaccines were associated with intussusception, though larger trials failed to establish increased risk in vaccinated groups compared to placebo recipients.

What Can We Learn from the Functional Clustering of Mortality Data? An Application to the Human Mortality Database

This study analyzed whether there are different patterns of mortality decline among low-mortality countries by identifying the role played by all the mortality components. We implemented a cluster analysis using a functional data analysis (FDA) approach, which allowed us to consider age-specific mortality rather than summary measures, as it analyses curves rather than scalar data. Combined with a functional principal component analysis, it can identify what part of the curves is responsible for assigning one country to a specific cluster. FDA clustering was applied to the data from 32 countries in the Human Mortality Database from 1960 to 2018 to provide a comprehensive understanding of their patterns of mortality. The results show that the evolution of developed countries followed the same pattern of stages (with different timings): (1) a reduction of infant mortality, (2) an increase of premature mortality and (3) a shift and compression of deaths. Some countries were following this scheme and recovering the gap with precursors; others did not show signs of recovery. Eastern European countries were still at Stage (2), and it was not clear if and when they will enter Stage 3. All the country differences related to the different timings with which countries underwent the stages, as identified by the clusters.

Forecasting mortality with international linkages: A global vector-autoregression approach

This paper proposes a Global Vector Autoregression (GVAR) mortality model to simultaneously model and forecast multi-population mortality dynamics. The proposed GVAR model decomposes the global regression model into population-wise local systems. Each local system consists of an intra-population autoregressive component and a small set of global factors, which contain systematic mortality information of all populations. Such a decomposition substantially reduces the extra estimation cost of including new populations compared to unconstrained VAR models, and makes the GVAR model an efficient tool for analyzing the joint mortality dynamics of a large group of populations. Further, under fairly general assumptions, the proposed GVAR model could generate coherent mortality projections between any two ages in any two populations. Using single-age mortality data of 15 low-mortality countries, we find that the global factors have substantial explanatory and forecasting power of mortality changes of individual populations, and the proposed GVAR model could produce satisfying mortality forecasts under various settings.

Future Mortality in Low-Mortality Countries

Future Mortality in Low-Mortality Countries

Real-world effectiveness of rotavirus vaccines, 2006–19: a literature review and meta-analysis

Since licensure in 2006, rotavirus vaccines have been introduced in more than 100 countries. The efficacy of rotavirus vaccines is variable in settings with different child mortality levels. We did an updated review of the published literature to assess the real-world effectiveness of rotavirus vaccines in a range of settings. In this literature review and meta-analysis, we included observational, post-licensure studies of rotavirus vaccines, published from Jan 1, 2006, to Dec 31, 2019, in English, with laboratory-confirmed rotavirus as the endpoint. In addition to product-specific results for Rotarix (GlaxoSmithKline Biologicals, Rixensart, Belgium) or RotaTeq (Merck, West Point, PA, USA), we included Rotarix and RotaTeq mixed series, and non-product-specific vaccine effectiveness estimates from countries where Rotarix and RotaTeq are both available. Studies of other infant rotavirus vaccines were excluded because little or no post-licensure data were available. We fitted random-effects regression models to estimate vaccine effectiveness among children younger than 12 months and aged 12-23 months. On the basis of 2017 UNICEF mortality estimates for children younger than 5 years, countries were stratified as having low (lowest quartile), medium (second quartile), or high mortality (third and fourth quartiles). We identified and screened 1703 articles, of which 60 studies from 32 countries were included. 31 studies were from countries with low child mortality, eight were from medium-mortality countries, and 21 were from high-mortality countries. Rotarix vaccine effectiveness against laboratory-confirmed rotavirus among children younger than 12 months old was 86% (95% CI 81-90) in low-mortality countries, 77% (66-85) in medium-mortality countries, and 63% (54-70) in high-mortality countries. Rotarix vaccine effectiveness among children aged 12-23 months was 86% (81-90) in low-mortality countries, 54% (23-73) in medium-mortality countries, and 58% (38-72) in high-mortality countries. RotaTeq vaccine effectiveness among children younger than 12 months was 86% (76-92) in low-mortality countries and 66% (51-76) in high-mortality countries. RotaTeq vaccine effectiveness among children aged 12-23 months was 84% (79-89) in low-mortality countries. There was no substantial heterogeneity (I2 range: 0-36%). Median vaccine effectiveness in low-mortality countries was similar for Rotarix (83%; IQR 78-91), RotaTeq (85%; 81-92), mixed series (86%; 70-91), and non-product-specific (89%; 75-91) vaccination. Rotavirus vaccines were effective in preventing rotavirus diarrhoea, with higher performance in countries with lower child mortality. None.

Diversification in causes of death in low-mortality countries: emerging patterns and implications

IntroductionAn important role of public health organisations is to monitor indicators of variation, so as to disclose underlying inequality in health improvement. In industrialised societies, more individuals than ever are...

Mortality Forecasting with the Lee-Carter Method: Adjusting for Smoothing and Lifespan Disparity.

Reliable mortality forecasts are an essential component of healthcare policies in ageing societies. The Lee-Carter method and its later variants are widely accepted probabilistic approaches to mortality forecasting, due to their simplicity and the straightforward interpretation of the model parameters. This model assumes an invariant age component and linear time component for forecasting. We apply the Lee-Carter method on smoothed mortality rates obtained by LASSO-type regularization and hence adjust the time component with the observed lifespan disparity. Smoothing with LASSO produces less error during the fitting period than do spline-based smoothing techniques. As a more informative indicator of longevity, matching with lifespan disparity makes the time component more reflective of mortality improvements. The forecasts produced by the new method were more accurate during out-of-sample evaluation and provided optimistic forecasts for many low-mortality countries.

Forecasting Mortality with International Linkages: A Global Vector-Autoregression Approach

This paper proposes a multi-population Global Vector Autoregression (GVAR) mortality model, in which the joint mortality dynamics of all populations are formulated in a large vector autoregression model with a set of contemporaneous global mortality factors. By decomposing the large VAR regression into population-wise local mortality systems containing a population-specific autoregressive component and a cross-sectional component of global mortality factors, the proposed GVAR model could substantially reduce the extra estimation cost of including additional populations. Consequentially, the new GVAR model provides an efficient tool to analyze the joint mortality dynamics of a large group of populations, which has been a rather challenging task for existing VAR-type mortality models. Moreover, under fairly general assumptions, the proposed GVAR model could produce coherent projected mortality rates for any two ages and populations. Using single-age mortality data of 15 low-mortality countries as considered in Li and Lee (2005), we find that the global factors have substantial impacts on mortality improvements of individual populations. Furthermore, we show that the proposed GVAR model could produce satisfying mortality forecasts under various settings.

Similarities and Differences Between Sexes and Countries in the Mortality Imprint of the Smoking Epidemic in 34 Low-Mortality Countries, 1950-2014.

IntroductionThe smoking epidemic greatly affected mortality levels and trends, especially among men in low-mortality countries. The objective of this article was to examine similarities and differences between sexes and low-mortality countries in the mortality imprint of the smoking epidemic. This will provide important additions to the smoking epidemic model, but also improve our understanding of the differential impact of the smoking epidemic, and provide insights into its future impact.MethodsUsing lung-cancer mortality data for 30 European and four North American or Australasian countries, smoking-attributable mortality fractions (SAMF) by sex, age (35–99), and year (1950–2014) were indirectly estimated. The timing and level of the peak in SAMF35-99, estimated using weighting and smoothing, were compared.ResultsAmong men in all countries except Bulgaria, a clear wave pattern was observed, with SAMF35-99 peaking, on average, at 33.4% in 1986. Eastern European men experienced the highest (40%) and Swedish men the lowest (16%) peak. Among women, SAMF35-99 peaked, on average, at 18.1% in 2007 in the North American/Australasian countries and five Northwestern European countries, and increased, on average, to 7.5% in 2014 in the remaining countries (4% in Southern and Eastern Europe). The average sex difference in the peak is at least 25.6 years in its timing and at most 22.9 percentage points in its level.ConclusionsAlthough the progression of smoking-attributable mortality in low-mortality countries was similar, there are important unexpected sex and country differences in the maximum mortality impact of the smoking epidemic driven by cross-country differences in economic, political, and emancipatory progress.ImplicationsThe formal, systematic, and comprehensive analysis of similarities and differences between sexes and 34 low-mortality countries in long-term time trends (1950–2014) in smoking-attributable mortality provided important additions to the Global Burden of Disease study and the descriptive smoking epidemic model (Lopez et al.). Despite a general increase followed by a decline, the timing of the maximum mortality impact differs more between sexes than previously anticipated, but less between regions. The maximum mortality impact among men differs considerably between countries. The observed substantial diversity warrants country-specific tobacco control interventions and increased attention to the current or expected higher smoking-attributable mortality shares among women compared to men.

Youth lost to homicides: disparities in survival in Latin America and the Caribbean

IntroductionThe homicide rates among young men in Latin America and the Caribbean (LAC) are the highest in the world. It is not clear how this has impacted the life expectancy...