Comparison of pregnancy and neonatal outcomes in a retrospective full pregnancy history survey versus population-based prospective records: a validation study in rural Sarlahi District, Nepal.

INTRODUCTION: Countries without complete civil registration and vital statistics systems rely on retrospective full pregnancy history surveys (FPH) to estimate incidence of pregnancy and mortality outcomes, including stillbirth and neonatal death. Yet surveys are subject to biases that impact demographic estimates, and few studies have quantified these effects. We compare data from an FPH vs. prospective records from a population-based cohort to estimate validity for maternal recall of live births, stillbirths, and neonatal deaths in a rural population in Sarlahi District, Nepal. METHODS: We used prospective data, collected through frequent visits of women from early pregnancy through the neonatal period, from a population-based randomized trial spanning 2010-2017. We randomly selected 76 trial participants from three pregnancy outcome groups: live birth (n = 26), stillbirth (n = 25), or neonatal death (n = 25). Data collectors administered the Nepal 2016 Demographic and Health Surveys (DHS)-VII pregnancy history survey between October 22, 2021, and November 18, 2021. We compared total pregnancy outcomes and numbers of pregnancy and neonatal outcomes between the two data sources. We matched pregnancy outcomes dates in the two sources within ± 30 days and calculated measures of validity for adverse outcomes. RESULTS: Among 76 participants, we recorded 122 pregnancy outcomes in the prospective data and 104 outcomes in the FPH within ± 30 days of each woman's total observation period in the trial. Among 226 outcomes, we observed 65 live births that survived to 28 days, 25 stillbirths, and 32 live births followed by neonatal death in the prospective data and participants reported 63 live births that survived to 28 days, 15 stillbirths, and 26 live births followed by neonatal death in the pregnancy history survey. Sixty-two FPH outcomes were matched by date within ± 30 days to an outcome in prospective data. Stillbirth, neonatal death, higher parity, and delivery at a health facility were associated with likelihood of a non-matched pregnancy outcome. CONCLUSIONS: Stillbirth and neonatal deaths were underestimated overall by the FPH, potentially underestimating the burden of mortality in this population. There is a need to develop tools to reduce or adjust for biases and errors in retrospective surveys to improve reporting of pregnancy and mortality outcomes.

Return Migration Selection and Its Impact on the Migrant Mortality Advantage: New Evidence Using French Pension Data.

The migrant mortality advantage (MMA) has been observed in many immigrant-receiving countries, but its underlying factors remain poorly understood. This article examines the role of return migration selection effects in explaining the MMA among males aged 65+ using a rich, unique dataset from France. This dataset contains information on native-born and foreign-born pensioners who are tracked worldwide until they die, providing a rare opportunity to assess return migration selection effects and their impact on the MMA. Results provide evidence of substantial and systematic negative return migration selection among foreign-born males in France. Old-age returns, in particular, appear particularly affected by such selection; however, they are not frequent enough to explain the MMA at ages 65+. By contrast, returns at younger ages are much more frequent, and the MMA at ages 65+ essentially disappears once these earlier returns are considered. This study extends the literature on negative selection at return and its impact on the MMA by providing evidence that such negative selection may operate not only at older ages but throughout the life course, with impacts on the MMA that are larger than previously suggested.

Quality of vital event data for infant mortality estimation in prospective, population-based studies: an analysis of secondary data from Asia, Africa, and Latin America.

INTRODUCTION: Infant and neonatal mortality estimates are typically derived from retrospective birth histories collected through surveys in countries with unreliable civil registration and vital statistics systems. Yet such data are subject to biases, including under-reporting of deaths and age misreporting, which impact mortality estimates. Prospective population-based cohort studies are an underutilized data source for mortality estimation that may offer strengths that avoid biases. METHODS: We conducted a secondary analysis of data from the Child Health Epidemiology Reference Group, including 11 population-based pregnancy or birth cohort studies, to evaluate the appropriateness of vital event data for mortality estimation. Analyses were descriptive, summarizing study designs, populations, protocols, and internal checks to assess their impact on data quality. We calculated infant and neonatal morality rates and compared patterns with Demographic and Health Survey (DHS) data. RESULTS: Studies yielded 71,760 pregnant women and 85,095 live births. Specific field protocols, especially pregnancy enrollment, limited exclusion criteria, and frequent follow-up visits after delivery, led to higher birth outcome ascertainment and fewer missing deaths. Most studies had low follow-up loss in pregnancy and the first month with little evidence of date heaping. Among studies in Asia and Latin America, neonatal mortality rates (NMR) were similar to DHS, while several studies in Sub-Saharan Africa had lower NMRs than DHS. Infant mortality varied by study and region between sources. CONCLUSIONS: Prospective, population-based cohort studies following rigorous protocols can yield high-quality vital event data to improve characterization of detailed mortality patterns of infants in low- and middle-income countries, especially in the early neonatal period where mortality risk is highest and changes rapidly.

Impact of the COVID-19 crisis on the mortality profiles of the foreign-born in France during the first pandemic wave.

BACKGROUND: Immigrants in Western countries have been particularly affected by the COVID-19 crisis. OBJECTIVE: We analysed excess mortality rates among the foreign-born population and changes in their distinctive mortality profiles ("migrant mortality advantage") during the first pandemic wave in France. DATA AND METHODS: Deaths from all causes in metropolitan France from March 18 to May 19, 2020 were used, with information on sex, age, region of residence and country of birth. Similar data from 2016 through 2019 were used for comparisons. RESULTS: During the pre-pandemic period (2016-2019), immigrant populations (except those from Central and Eastern Europe) had lower standardized mortality rates than the native-born population, with a particularly large advantage for immigrants from sub-Saharan Africa. In the regions most affected by COVID-19 (Grand-Est and Île-de-France), the differences in excess mortality by country of birth were large, especially in the working-age groups (40-69 years), with rates 8 to 9 times higher for immigrants from sub-Saharan Africa, and about 3 to 4 times higher for immigrants from North Africa, from the Americas and from Asia and Oceania relative to the native-born population. The relative overall mortality risk for men born in sub-Saharan Africa compared to native-born men, which was 0.8 before the pandemic, shifted to 1.8 during the first wave (0.9 to 1.5 for women). It also shifted from 0.8 to 1.1 for men from North Africa (0.9 to 1.1 for women), 0.7 to 1.0 for men from the Americas (0.9 to 1.3 for women), and 0.7 to 1.2 for men from Asia and Oceania (0.9 to 1.3 for women). CONCLUSION: Our findings shed light on the disproportionate impact of the first wave of the pandemic on the mortality of populations born outside Europe, with a specific burden of excess mortality within the working-age range, and a complete reversal of their mortality advantage.

Divergent age patterns of under-5 mortality in south Asia and sub-Saharan Africa: a modelling study.

BACKGROUND: Understanding the age pattern of under-5 mortality is essential for identifying the most vulnerable ages and underlying causes of death, and for assessing why the decline in child mortality is slower in some countries and subnational areas than others. The aim of this study is to detect age patterns of under-5 mortality that are specific to low-income and middle-income countries (LMICs). METHODS: In this modelling study, we used data from 277 Demographic and Health Surveys (DHSs), 58 Health and Demographic Surveillance Systems (HDSSs), two cohort studies, and two sample-registration systems. From these sources, we collected child date of birth and date of death (or age at death) from LMICs between 1966 and 2020. We computed 22 deaths rates from each survey with the following age breakdowns: 0, 7, 14, 21, and 28 days; 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 18, and 21 months; and 2, 3, 4, and 5 years. We assessed how probabilities of dying estimated for the 22 age groups deviated from predictions generated by a vital registration model that reflects the historical mortality of 25 high-income countries. FINDINGS: We calculated mortality rates of 81 LMICs between 1966 and 2020. In contrast with the other regions of the world, we found that under-5 mortality in south Asia and sub-Saharan Africa was characterised by increased mortality at both ends of the age range (ie, younger than 28 days and older than 6 months) at a given level of mortality. Observed mortality in these regions was up to 2 times higher than predicted by the vital registration model for the younger-than-28 days age bracket, and up to 10 times higher than predicted for the older-than-6 months age bracket. This age pattern of under-5 mortality is significant in 17 countries in south Asia and sub-Saharan Africa. Excess mortality in children older than 6 months without excess mortality in children younger than 28 days was found in 38 countries. In south Asia, results were consistent across data sources. In sub-Saharan Africa, excess mortality in children younger than 28 days was found mostly in DHSs; the majority of HDSSs did not show this excess mortality. We have attributed this difference in data sources mainly to omissions of early deaths in HDSSs. INTERPRETATION: In countries with age patterns of under-5 mortality that diverge from predictions, evidence-based public health interventions should focus on the causes of excess of mortality; notably, the effect of fetal growth restriction and infectious diseases. The age pattern of under-5 mortality will be instrumental in assessing progress towards the decline of under-5 mortality and the Sustainable Development Goals. FUNDING: Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health.

Does higher early neonatal mortality in boys reverse over the neonatal period? A pooled analysis from three trials of Nepal.

OBJECTIVES: Neonatal mortality is generally 20% higher in boys than girls due to biological phenomena. Only a few studies have examined more finely categorised age patterns of neonatal mortality by sex, especially in the first few days of life. The objective of this study is to examine sex differentials in neonatal mortality by detailed ages in a low-income setting. DESIGN: This is a secondary observational analysis of data. SETTING: Rural Sarlahi district, Nepal. PARTICIPANTS: Neonates born between 1999 and 2017 in three randomised controlled trials. OUTCOME MEASURES: We calculated study-specific and pooled mortality rates for boys and girls by ages (0-1, 1-3, 3-7, 7-14, 14-21 and 21-28 days) and estimated HR using Cox proportional hazards models for male versus female mortality for treatment and control groups together (n=59 729). RESULTS: Neonatal mortality was higher in boys than girls in individual studies: 44.2 vs 39.7 in boys and girls in 1999-2000; 30.0 vs 29.6 in 2002-2006; 33.4 vs 29.4 in 2010-2017; and 33.0 vs 30.2 in the pooled data analysis. Pooled data found that early neonatal mortality (HR=1.17; 95% CI: 1.06 to 1.30) was significantly higher in boys than girls. All individual datasets showed a reversal in mortality by sex after the third week of life. In the fourth week, a reversal was observed, with mortality in girls 2.43 times higher than boys (HR=0.41; 95% CI: 0.31 to 0.79). CONCLUSIONS: Boys had higher mortality in the first week followed by no sex difference in weeks 2 and 3 and a reversal in risk in week 4, with girls dying at more than twice the rate of boys. This may be a result of gender discrimination and social norms in this setting. Interventions to reduce gender discrimination at the household level may reduce female neonatal mortality. TRIAL REGISTRATION NUMBER: NCT00115271, NCT00109616, NCT01177111.

Growing up and moving out: Migration and the demographic transition in low- and middle-income nations.

International migration has increased since 1990, with increasing numbers of migrants originating from low- and middle-income countries (LMICs). Efforts to explain this compositional shift have focused on wage gaps and other push and pull factors but have not adequately considered the role of demographic factors. In many LMICs, child mortality has fallen without commensurate economic growth and amid high fertility. This combination increases young adult populations and is associated with greater outmigration: in the poorest countries, we estimate that a one-percentage-point increase in the five-year lagged growth rate of the population of 15-24-year-olds was associated with a 15 per cent increase in all-age outmigrants, controlling for other factors. Increases in growth of young adult populations led to 20.4 million additional outmigrants across 80 countries between 1990 and 2015. Understanding the determinants of these migration shifts should help policymakers in origin and destination countries to maximize their potential positive effects.

Global, regional, and national trends in under-5 mortality between 1990 and 2019 with scenario-based projections until 2030: a systematic analysis by the UN Inter-agency Group for Child Mortality Estimation.

BACKGROUND: The Sustainable Development Goals (SDGs), set in 2015 by the UN General Assembly, call for all countries to reach an under-5 mortality rate (U5MR) of at least as low as 25 deaths per 1000 livebirths and a neonatal mortality rate (NMR) of at least as low as 12 deaths per 1000 livebirths by 2030. We estimated levels and trends in under-5 mortality for 195 countries from 1990 to 2019, and conducted scenario-based projections of the U5MR and NMR from 2020 to 2030 to assess country progress in, and potential for, reaching SDG targets on child survival and the potential under-5 and neonatal deaths over the next decade. METHODS: Levels and trends in under-5 mortality are based on the UN Inter-agency Group for Child Mortality Estimation (UN IGME) database on under-5 mortality, which contains around 18 000 country-year datapoints for 195 countries-nearly 10 000 of those datapoints since 1990. The database includes nationally representative mortality data from vital registration systems, sample registration systems, population censuses, and household surveys. As with previous sets of national UN IGME estimates, a Bayesian B-spline bias-reduction model (B3) that considers the systematic biases associated with the different data source types was fitted to these data to generate estimates of under-5 (age 0-4 years) mortality with uncertainty intervals for 1990-2019 for all countries. Levels and trends in the neonatal mortality rate (0-27 days) are modelled separately as the log ratio of the neonatal mortality rate to the under-5 mortality rate using a Bayesian model. Estimated mortality rates are combined with livebirths data to calculate the number of under-5 and neonatal deaths. To assess the regional and global burden of under-5 deaths in the present decade and progress towards SDG targets, we constructed several scenario-based projections of under-5 mortality from 2020 to 2030 and estimated national, regional, and global under-5 mortality trends up to 2030 for each scenario. FINDINGS: The global U5MR decreased by 59% (90% uncertainty interval [UI] 56-61) from 93·0 (91·7-94·5) deaths per 1000 livebirths in 1990 to 37·7 (36·1-40·8) in 2019, while the annual number of global under-5 deaths declined from 12·5 (12·3-12·7) million in 1990 to 5·2 (5·0-5·6) million in 2019-a 58% (55-60) reduction. The global NMR decreased by 52% (90% UI 48-55) from 36·6 (35·6-37·8) deaths per 1000 livebirths in 1990, to 17·5 (16·6-19·0) in 2019, and the annual number of global neonatal deaths declined from 5·0 (4·9-5·2) million in 1990, to 2·4 (2·3-2·7) million in 2019, a 51% (47-54) reduction. As of 2019, 122 of 195 countries have achieved the SDG U5MR target, and 20 countries are on track to achieve the target by 2030, while 53 will need to accelerate progress to meet the target by 2030. 116 countries have reached the SDG NMR target with 16 on track, leaving 63 at risk of missing the target. If current trends continue, 48·1 million under-5 deaths are projected to occur between 2020 and 2030, almost half of them projected to occur during the neonatal period. If all countries met the SDG target on under-5 mortality, 11 million under-5 deaths could be averted between 2020 and 2030. INTERPRETATION: As a result of effective global health initiatives, millions of child deaths have been prevented since 1990. However, the task of ending all preventable child deaths is not done and millions more deaths could be averted by meeting international targets. Geographical and economic variation demonstrate the possibility of even lower mortality rates for children under age 5 years and point to the regions and countries with highest mortality rates and in greatest need of resources and action. FUNDING: Bill & Melinda Gates Foundation, US Agency for International Development.

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.

Adapting and validating the log quadratic model to derive under-five age- and cause-specific mortality (U5ACSM): a preliminary analysis.

BACKGROUND: The mortality pattern from birth to age five is known to vary by underlying cause of mortality, which has been documented in multiple instances. Many countries without high functioning vital registration systems could benefit from estimates of age- and cause-specific mortality to inform health programming, however, to date the causes of under-five death have only been described for broad age categories such as for neonates (0-27 days), infants (0-11 months), and children age 12-59 months. METHODS: We adapt the log quadratic model to mortality patterns for children under five to all-cause child mortality and then to age- and cause-specific mortality (U5ACSM). We apply these methods to empirical sample registration system mortality data in China from 1996 to 2015. Based on these empirical data, we simulate probabilities of mortality in the case when the true relationships between age and mortality by cause are known. RESULTS: We estimate U5ACSM within 0.1-0.7 deaths per 1000 livebirths in hold out strata for life tables constructed from the China sample registration system, representing considerable improvement compared to an error of 1.2 per 1000 livebirths using a standard approach. This improved prediction error for U5ACSM is consistently demonstrated for all-cause as well as pneumonia- and injury-specific mortality. We also consistently identified cause-specific mortality patterns in simulated mortality scenarios. CONCLUSION: The log quadratic model is a significant improvement over the standard approach for deriving U5ACSM based on both simulation and empirical results.

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.

Lessons learned and lessons missed: impact of the coronavirus disease 2019 (COVID-19) pandemic on all-cause mortality in 40 industrialised countries and US states prior to mass vaccination.

Background: Industrialised countries had varied responses to the coronavirus disease 2019 (COVID-19) pandemic, and how they adapted to new situations and knowledge since it began. These differences in preparedness and policy may lead to different death tolls from COVID-19 as well as other diseases. Methods: We applied an ensemble of 16 Bayesian probabilistic models to vital statistics data to estimate the impacts of the pandemic on weekly all-cause mortality for 40 industrialised countries from mid-February 2020 through mid-February 2021, before a large segment of the population was vaccinated in these countries. Results: Over the entire year, an estimated 1,410,300 (95% credible interval 1,267,600-1,579,200) more people died in these countries than would have been expected had the pandemic not happened. This is equivalent to 141 (127-158) additional deaths per 100,000 people and a 15% (14-17) increase in deaths in all these countries combined. In Iceland, Australia and New Zealand, mortality was lower than would be expected if the pandemic had not occurred, while South Korea and Norway experienced no detectable change in mortality. In contrast, the USA, Czechia, Slovakia and Poland experienced at least 20% higher mortality. There was substantial heterogeneity across countries in the dynamics of excess mortality. The first wave of the pandemic, from mid-February to the end of May 2020, accounted for over half of excess deaths in Scotland, Spain, England and Wales, Canada, Sweden, Belgium, the Netherlands and Cyprus. At the other extreme, the period between mid-September 2020 and mid-February 2021 accounted for over 90% of excess deaths in Bulgaria, Croatia, Czechia, Hungary, Latvia, Montenegro, Poland, Slovakia and Slovenia. Conclusions: Until the great majority of national and global populations have vaccine-acquired immunity, minimising the death toll of the pandemic from COVID-19 and other diseases will require actions to delay and contain infections and continue routine health care.

Infant mortality among native-born children of immigrants in France, 2008-17: results from a socio-demographic panel survey.

BACKGROUND: Within Europe, France stands out as a major country that lacks recent and reliable evidence on how infant mortality levels vary among the native-born children of immigrants compared with the native-born children of two parents born in France. METHODS: We used a nationally representative socio-demographic panel consisting of 296 400 births and 980 infant deaths for the period 2008-17. Children of immigrants were defined as being born to at least one parent born abroad and their infant mortality was compared with that of children born to two parents born in France. We first calculated infant mortality rates per 1000 live births. Then, using multi-level logit models, we calculated odds ratios of infant mortality in a series of models adjusting progressively for parental origins (M1), core demographic factors (M2), father's socio-professional category (M3) and area-level urbanicity and deprivation score (M4). RESULTS: We documented a substantial amount of excess infant mortality among those children born to at least one parent from Eastern Europe, Northern Africa, Western Africa, Other Sub-Saharan Africa and the Americas, with variation among specific origin countries belonging to these groups. In most of these cases, the excess infant mortality levels persisted after adjusting for all individual-level and area-level factors. CONCLUSIONS: Our findings, which can directly inform national public health policy, reaffirm the persistence of longstanding inequality in infant mortality according to parental origins in France and add to a growing body of evidence documenting excess infant mortality among the children of immigrants in Europe.

Magnitude, demographics and dynamics of the effect of the first wave of the COVID-19 pandemic on all-cause mortality in 21 industrialized countries.

The Coronavirus Disease 2019 (COVID-19) pandemic has changed many social, economic, environmental and healthcare determinants of health. We applied an ensemble of 16 Bayesian models to vital statistics data to estimate the all-cause mortality effect of the pandemic for 21 industrialized countries. From mid-February through May 2020, 206,000 (95% credible interval, 178,100-231,000) more people died in these countries than would have had the pandemic not occurred. The number of excess deaths, excess deaths per 100,000 people and relative increase in deaths were similar between men and women in most countries. England and Wales and Spain experienced the largest effect: ~100 excess deaths per 100,000 people, equivalent to a 37% (30-44%) relative increase in England and Wales and 38% (31-45%) in Spain. Bulgaria, New Zealand, Slovakia, Australia, Czechia, Hungary, Poland, Norway, Denmark and Finland experienced mortality changes that ranged from possible small declines to increases of 5% or less in either sex. The heterogeneous mortality effects of the COVID-19 pandemic reflect differences in how well countries have managed the pandemic and the resilience and preparedness of the health and social care system.

The cross-sectional average length of healthy life (HCAL): a measure that summarizes the history of cohort health and mortality.

BACKGROUND: Healthy life years have superseded life expectancy (LE) as the most important indicator for population health. The most common approach to separate the total number of life years into those spent in good and poor health is the Sullivan method which incorporates the health dimension to the classic period life table, thus transforming the LE indicator into the health expectancy (HE) indicator. However, life years derived from a period life table and health prevalence derived from survey data are based on different conceptual frameworks. METHOD: We modify the Sullivan method by combining the health prevalence data with the conceptually better fitting cross-sectional average length of life (CAL). We refer to this alternative HE indicator as the "cross-sectional average length of healthy life" (HCAL). We compare results from this alternative indicator with the conventional Sullivan approach for nine European countries. The analyses are based on EU-SILC data in three empirical applications, including the absolute and relative level of healthy life years, changes between 2008 and 2014, and the extent of the gender gap. RESULTS: HCAL and conventional HE differ in each of these empirical applications. In general, HCAL provides larger gains in healthy life years in recent years, but at the same time greater declines in the proportion of healthy life years. Regarding the gender gap, HCAL provides a more favourable picture for women compared to conventional HE. Nonetheless, the extent of these differences between the indicators is only of minor extent. CONCLUSIONS: Albeit the differences between HE and HCAL are small, we found some empirical examples in which the two indicators led to different conclusions. It is important to note, however, that the measurement of health and the data quality are much more important for the healthy life years indicator than the choice of the variant of the Sullivan method. Nonetheless, we suggest to use HCAL in addition to HE whenever possible because it widens the spectrum of empirical analyses and serves for verification of results based on the highly sensitive HE indicator.

Divergent mortality patterns for second generation men of North-African and South-European origin in France: Role of labour force participation.

INTRODUCTION: In France, second generation men of South-European origin were recently found to experience a mortality advantage, as opposed to second generation men of North-African origin, subjected to a large amount of excess mortality. We analyze the roles of education and labor force participation in the explanation of these contrasting mortality patterns. MATERIALS AND METHODS: Our data consisted of a nationally-representative sample of individuals aged 18-64 years derived from the 1999 census, with mortality follow-up until 2010. RESULTS: The two groups of second generation men, and particularly those of North-African origin, were less educated than the native-origin population, but only the latter was disadvantaged in terms of labor force participation. Relative to the native-origin population, the mortality hazard ratio for second generation men of North-African origin (HR = 1.71 [1.09-2.70]) remained significant after adjusting for level of educational attainment (HR = 1.59 [1.01-2.50]), but not after adjusting for economic activity (HR = 1.20 [0.76-1.89]) or for both variables (1.16 [0.74-1.83]). Conversely, the mortality hazard ratio for second generation men of South-European origin (HR = 0.64 [0.46-0.90]) remained unchanged after adjustment for level of educational attainment and/or economic activity. CONCLUSION: The findings shed light on the salient role of labor market disadvantage in the explanation of the mortality excess of second generation men of North-African origin in France, and on the favorable situation of second-generation men of South-European origin in terms of labour market position and mortality. The theoretical and policy implications of the findings are discussed.

Tracking progress in mean longevity: The Lagged Cohort Life Expectancy (LCLE) approach.

Cohort life expectancy is an important but rarely used indicator of mean longevity. In this paper, we show that there are specific advantages in lagging this indicator in time by its own value, an approach termed Lagged Cohort Life Expectancy (LCLE). We discuss the usefulness of LCLE as an indicator for tracking progress in mean longevity and introduce a new interpretation of LCLE as a reference age separating 'early' deaths from 'late' deaths, or, equivalently, as the age above which individuals in a population can be considered 'above-average' survivors. Using data from 15 countries in the Human Mortality Database, we show that current LCLE can be estimated with a relatively high degree of certainty, at least in these low-mortality populations. Results shed new light on levels and trends in mean longevity in these populations.