What does your neighbourhood say about you? : a study of life expectancy in 1.3 million Swiss neighbourhoods

BACKGROUND: Switzerland had the highest life expectancy at 82.8 years among the Organisation for Economic Co-operation and Development (OECD) countries in 2011. Geographical variation of life expectancy and its relation to the socioeconomic position of neighbourhoods are, however, not well understood. METHODS: We analysed the Swiss National Cohort, which linked the 2000 census with mortality records 2000-2008 to estimate life expectancy across neighbourhoods. A neighbourhood index of socioeconomic position (SEP) based on the median rent, education and occupation of household heads and crowding was calculated for 1.3 million overlapping neighbourhoods of 50 households. We used skew-normal regression models, including the index and additionally marital status, education, nationality, religion and occupation to calculate crude and adjusted estimates of life expectancy at age 30 years. RESULTS: Based on over 4.5 million individuals and over 400,000 deaths, estimates of life expectancy at age 30 in neighbourhoods ranged from 46.9 to 54.2 years in men and from 53.5 to 57.2 years in women. The correlation between life expectancy and neighbourhood SEP was strong (r=0.95 in men and r=0.94 women, both p values <0.0001). In a comparison of the lowest with the highest percentile of neighbourhood SEP, the crude difference in life expectancy from skew-normal regression was 4.5 years in men and 2.5 years in women. The corresponding adjusted differences were 2.8 and 1.9 years, respectively (all p values <0.0001). CONCLUSIONS: Although life expectancy is high in Switzerland, there is substantial geographical variation and life expectancy is strongly associated with the social standing of neighbourhoods.

Life expectancy, educational attainment, and fertility choice

This paper explores the role of mortality as a determinant of educational attainment and fertility, both during the demographic transition and after its completion. Two main points distinguish our analysis from the previous ones. Together with the investments of parents in the human capital of children, traditional in the fertility literature, we introduce investments of adult individuals (parents) in their own education, which ultimately determines productivity in both the goods and household sectors. Second, we let adult longevity affect the way parents value each individual child. Increases in adult longevity or reductions in child mortality eventually raise the investments in adult education. Together with the higher utility derived from each child, this tilts the quality-quantity trade off towards less and better educated children, and increases the growth rate of the economy. This setup can explain both the demographic transition and the recent behavior of fertility in “post-transition” countries. Evidence from historical experiences of demographic transition, and from the recent behavior of fertility, education, and growth generally supports the predictions of the model.

Life expectancy and human capital investment: the arrival of AIDS treatment in Brazil

This paper provides microevidence on the relationship between life expectancy and educational investment decisions. Human capital theory predicts an increase in life expectancy should lead to an augmenting in schooling investment. This paper uses an unique data set on AIDS patients among Brazilian inhabitants in an attempt to estimate the impact of the arrival of Antiretroviral therapy (ART) on educational outcomes. The availability of ART offsets the negative relationship between vertical HIV-transmission and schooling, around 68% and 57% for elementary and high school completion, respectively. Robustness tests indicate the results are not driven by convergence effects.

Life Expectancy and Entropy Values for Workers of Pachycondyla striata (Hymenoptera: Formicidae: Ponerinae)

We investigated the life expectancy and entropy value for workers of the ant Pachycondyla striata. Seven nests were excavated and these colonies were raised in laboratory conditions. The workers have a mean life-span of 74.48 days, these have a high mortality rate in the period of 1 to 85 days with a high entropy value of H = 0.611, confirming the number of deaths in the initial period.

Temporal polyethism and life expectancy of workers in the eusocial wasp polistes canadensis canadensis Linnaeus (Hymenoptera: Vespidae)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Individual and spousal education, mortality and life expectancy in Switzerland: a national cohort study.

BACKGROUND Household measures of socioeconomic position may better account for the shared nature of material resources, lifestyle, and social position of cohabiting persons, but household measures of education are rarely used. We aimed to evaluate the association of combined educational attainment of married couples on mortality and life expectancy in Switzerland. METHODS The study included 3 496 163 ever-married persons aged ≥30 years. The 2000 census was linked to mortality records through 2008. Mortality by combined educational attainment was assessed by gender-age-specific HRs, with 95% CIs from adjusted models, life expectancy was derived using abridged life tables. RESULTS Having a less educated partner was associated with increased mortality. For example, the HR comparing men aged 50-64 years with tertiary education married to women with tertiary education to men with compulsory education married to women with compulsory education was 2.05 (1.92-2.18). The estimated remaining life expectancy in tertiary educated men aged 30 years married to women with tertiary education was 4.6 years longer than in men with compulsory education married to women with compulsory education. The gradient based on individual education was less steep: the HR comparing men aged 50-64 years with tertiary education with men with compulsory education was 1.74 (1.67-1.81). CONCLUSIONS Using individual educational attainment of married persons is common in epidemiological research, but may underestimate the combined effect of education on mortality and life expectancy. These findings are relevant to epidemiologic studies examining socio-demographic characteristics or aiming to adjust results for these characteristics.

What does your neighbourhood say about you? A study of life expectancy in 1.3 million Swiss neighbourhoods

BACKGROUND Switzerland had the highest life expectancy at 82.8 years among the Organisation for Economic Co-operation and Development (OECD) countries in 2011. Geographical variation of life expectancy and its relation to the socioeconomic position of neighbourhoods are, however, not well understood. METHODS We analysed the Swiss National Cohort, which linked the 2000 census with mortality records 2000-2008 to estimate life expectancy across neighbourhoods. A neighbourhood index of socioeconomic position (SEP) based on the median rent, education and occupation of household heads and crowding was calculated for 1.3 million overlapping neighbourhoods of 50 households. We used skew-normal regression models, including the index and additionally marital status, education, nationality, religion and occupation to calculate crude and adjusted estimates of life expectancy at age 30 years. RESULTS Based on over 4.5 million individuals and over 400 000 deaths, estimates of life expectancy at age 30 in neighbourhoods ranged from 46.9 to 54.2 years in men and from 53.5 to 57.2 years in women. The correlation between life expectancy and neighbourhood SEP was strong (r=0.95 in men and r=0.94 women, both p values <0.0001). In a comparison of the lowest with the highest percentile of neighbourhood SEP, the crude difference in life expectancy from skew-normal regression was 4.5 years in men and 2.5 years in women. The corresponding adjusted differences were 2.8 and 1.9 years, respectively (all p values <0.0001). CONCLUSIONS Although life expectancy is high in Switzerland, there is substantial geographical variation and life expectancy is strongly associated with the social standing of neighbourhoods.

Modeling absolute differences in life expectancy with a censored skew-normal regression approach.

Parameter estimates from commonly used multivariable parametric survival regression models do not directly quantify differences in years of life expectancy. Gaussian linear regression models give results in terms of absolute mean differences, but are not appropriate in modeling life expectancy, because in many situations time to death has a negative skewed distribution. A regression approach using a skew-normal distribution would be an alternative to parametric survival models in the modeling of life expectancy, because parameter estimates can be interpreted in terms of survival time differences while allowing for skewness of the distribution. In this paper we show how to use the skew-normal regression so that censored and left-truncated observations are accounted for. With this we model differences in life expectancy using data from the Swiss National Cohort Study and from official life expectancy estimates and compare the results with those derived from commonly used survival regression models. We conclude that a censored skew-normal survival regression approach for left-truncated observations can be used to model differences in life expectancy across covariates of interest.

Trends in life expectancy of HIV-positive adults on antiretroviral therapy across the globe: comparisons with general population.

PURPOSE OF REVIEW Improved virological and immunological outcomes and reduced toxicity of antiretroviral combination therapy (ART) raise the hope that life expectancy of HIV-positive persons on ART will approach that of the general population. We systematically review the literature and summarize published estimates of life expectancy of HIV-positive populations on ART. We compare their life expectancy with the life expectancy of the general or, in sub-Saharan Africa, HIV-negative populations, by time period and gender. RECENT FINDINGS Ten relevant studies were published from 2006 to 2015. Three studies were from Canada, two from European countries, three from sub-Saharan Africa and two were multicountry studies. Life expectancy increased over time in all studies and regions. Expressed as the percentage of life expectancy in the HIV-negative or general population, estimated life expectancy at age 20 years in HIV-positive people on ART ranged from 60.3% (95% CI 58.0-62.6%) in Rwanda (2008-2011) to 89.1% (95% CI 84.7-93.6%) in Canada (2008-2012). The percentage of life expectancy in the HIV-negative or general population achieved was higher in HIV-positive women than in HIV-positive men in all countries, except for Canada wherein the opposite was the case. SUMMARY Life expectancy in HIV-positive people on ART has improved worldwide in recent years, but important gaps remain compared with the general and HIV-negative population, and between regions and genders.

Distribution of quality adjusted life expectancy: A systems approach

Statistical methods are developed which assess survival data for two attributes; (1) prolongation of life, (2) quality of life. Health state transition probabilities correspond to prolongation of life and are modeled as a discrete-time semi-Markov process. Imbedded within the sojourn time of a particular health state are the quality of life transitions. They reflect events which differentiate perceptions of pain and suffering over a fixed time period. Quality of life transition probabilities are derived from the assumptions of a simple Markov process. These probabilities depend on the health state currently occupied and the next health state to which a transition is made. Utilizing the two forms of attributes the model has the capability to estimate the distribution of expected quality adjusted life years (in addition to the distribution of expected survival times). The expected quality of life can also be estimated within the health state sojourn time making more flexible the assessment of utility preferences. The methods are demonstrated on a subset of follow-up data from the Beta Blocker Heart Attack Trial (BHAT). This model contains the structure necessary to make inferences when assessing a general survival problem with a two dimensional outcome. ^

Estimates of life expectancy gains from reducing/eliminating major causes of death in the USA: An update analysis for population in 2001--2008

Evaluation of the impact of a disease on life expectancy is an important part of public health. Potential gains in life expectancy (PGLE) that can properly take into account the competing risks are an effective indicator for measuring the impact of the multiple causes of death. This study aimed to measure the PGLEs from reducing/eliminating the major causes of death in the USA from 2001 to 2008. To calculate the PGLEs due to the elimination of specific causes of death, the age-specific mortality rates for heart disease, malignant neoplasms, Alzheimer disease, kidney diseases and HIV/AIDS and life table constructing data were obtained from the National Center for Health Statistics, and the multiple decremental life tables were constructed. The PGLEs by elimination of heart disease, malignant neoplasms or HIV/AIDS continued decreasing from 2001 to 2008, but the PGLE by elimination of Alzheimer's disease or kidney diseases revealed increased trends. The PGLEs (by years) for all race, male, female, white, white male, white female, black, black male and black female at birth by complete elimination of heart disease 2001–2008 were 0.336–0.299, 0.327–0.301, 0.344–0.295, 0.360–0.315, 0.349–0.317, 0.371–0.316,0.278–0.251, 0.272–0.255, and 0.282–0.246 respectively. Similarly, the PGLEs (by years) for all race, male, female, white, white male, white female, black, black male and black female at birth by complete elimination of malignant neoplasms, Alzheimer's disease, kidney disease or HIV/AIDS 2001–2008 were also uncovered, respectively. Most diseases affect specific population, such as, HIV/AIDS tends to have a greater impact on people of working age, heart disease and malignant neoplasms have a greater impact on people over 65 years of age, but Alzheimer's disease and kidney diseases have a greater impact on people over 75 years of age. To measure the impact of these diseases on life expectancy in people of working age, partial multiple decremental life tables were constructed and the PGLEs were computed by partial or complete elimination of various causes of death during the working years. Thus, the results of the study outlined a picture of how each single disease could affect the life expectancy in age-, race-, or sex-specific population in USA. Therefore, the findings would not only assist to evaluate current public health improvements, but also provide useful information for future research and disease control programs.^