The impact of violence on Venezuelan life expectancy and lifespan inequality

International audienceBackground: Venezuela is one of the most violent countries in the world. According to the United Nations, homicide rates in the country increased from 32.9 to 61.9 per 100 000 people between 2000 and 2014. This upsurge coincided with a slowdown in life expectancy improvements. We estimate mortality trends and quantify the impact of violence-related deaths and other causes of death on life expectancy and lifespan inequality in Venezuela.Methods: Life tables were computed with corrected age-specific mortality rates from 1996 to 2013. From these, changes in life expectancy and lifespan inequality were decomposed by age and cause of death using a continuous-change model. Lifespan inequality, or variation in age at death, is measured by the standard deviation of the age-at-death distribution.Results: From 1996 to 2013 in Venezuela, female life expectancy rose 3.57 [95% confidence interval (CI): 3.08–4.09] years [from 75.79 (75.98–76.10) to 79.36 (78.97–79.68)], and lifespan inequality fell 1.03 (–2.96 to 1.26) years [from 18.44 (18.01–19.00) to 17.41 (17.30–18.27)]. Male life expectancy increased 1.64 (1.09–2.25) years [from 69.36 (68.89–59.70) to 71.00 (70.53–71.39)], but lifespan inequality increased 0.95 (–0.80 to 2.89) years [from 20.70 (20.24–21.08) to 21.65 (21.34–22.12)]. If violence-related death rates had not risen over this period, male life expectancy would have increased an additional 1.55 years, and lifespan inequality would have declined slightly (–0.31 years).Conclusions: As increases in violence-related deaths among young men (ages 15–39) have slowed gains in male life expectancy and increased lifespan inequality, Venezuelan males face more uncertainty about their age at death. There is an urgent need for more accurate mortality estimates in Venezuela

Marketing de servicios: Atención al cliente

La atención del cliente es una de las principales característica que una empresa de servicio o consumo, debe tomar como primordial dentro de sus funciones. Mantener un cliente es de gran importancia y es un poco complicado, El triunfo de una Empresa depende fundamentalmente de la demanda de sus clientes. Ellos son los protagonistas principales y el factor más importante que interviene en el juego de los negocios. En este trabajo se presenta una caracterización general para brindar un servicio de atención al cliente de calidad, una herramienta para analizar el mejoramiento del valor de los productos y servicios, además de una profunda reflexión sobre la conveniencia de aprovechar los conocimientos y utilizarlos en problemas de la empresa de tal forma que permita conformar una idea más clara de la importancia y necesidad de contar con un diseño del servicio de atención al cliente. El trabajo que presentamos contiene tres capitulo cada uno con temas muy importantes en donde realizamos una explicación clara y concreta de cada uno de ellos. En la actualidad las empresas dan más interés en la administración de cómo debemos dirigir, administrar los recursos económicos, humanos y materiales; dejando inadvertido el servicio de atención al cliente y que cada día nos preocupamos en crecer pero no tomamos importancia de cómo nuestra competencia está creciendo y que está incrementando sus carteras de clientes; debido al buen servicio y la atención que se brinda. Es por tanto que las empresas pequeñas y grandes deben prestar un servicio de Calidad, para lograr posicionarse en el mercado y marcar la diferencia

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

Unequal impact of the COVID-19 pandemic in 2020 on life expectancy across urban areas in Chile: a cross-sectional demographic study.

OBJECTIVES: To quantify the impact of the COVID-19 pandemic on life expectancy in Chile categorised by rural and urban areas, and to correlate life expectancy changes with socioeconomic factors at the municipal level. DESIGN: Retrospective cross-sectional demographic analysis using aggregated national all-cause death data stratified by year, sex and municipality during the period 2010-2020. SETTING AND POPULATION: Chilean population by age, sex and municipality from 2002 to 2020. MAIN OUTCOME MEASURES: Stratified mortality rates using a Bayesian methodology. These were based on vital and demographic statistics from the national institute of statistics and department of vital statistics of ministry of health. With this, we assessed the unequal impact of the pandemic in 2020 on life expectancy across Chilean municipalities for males and females and analysed previous mortality trends since 2010. RESULTS: Life expectancy declined for both males and females in 2020 compared with 2019. Urban areas were the most affected, with males losing 1.89 years and females 1.33 years. The strength of the decline in life expectancy correlated positively with indicators of social deprivation and poverty. Also, inequality in life expectancy between municipalities increased, largely due to excess mortality among the working-age population in socially disadvantaged municipalities. CONCLUSIONS: Not only do people in poorer areas live shorter lives, they also have been substantially more affected by the COVID-19 pandemic, leading to increased population health inequalities. Quantifying the impact of the COVID-19 pandemic on life expectancy provides a more comprehensive picture of the toll

Drewnowski's index to measure lifespan variation: Revisiting the Gini coefficient of the life table.

The Gini coefficient of the life table is a concentration index that provides information on lifespan variation. Originally proposed by economists to measure income and wealth inequalities, it has been widely used in population studies to investigate variation in ages at death. We focus on the complement of the Gini coefficient, Drewnowski's index, which is a measure of equality. We study its mathematical properties and analyze how changes over time relate to changes in life expectancy. Further, we identify the threshold age below which mortality improvements are translated into decreasing lifespan variation and above which these improvements translate into increasing lifespan inequality. We illustrate our theoretical findings simulating scenarios of mortality improvement in the Gompertz model, and showing an example of application to Swedish life table data. Our experiments demonstrate how Drewnowski's index can serve as an indicator of the shape of mortality patterns. These properties, along with our analytical findings, support studying lifespan variation alongside life expectancy trends in multiple species

The impact of COVID-19 on life expectancy across socioeconomic groups in Denmark

Background: Denmark was one of the few countries that experienced an increase in life expectancy in 2020, and one of the few to see a decrease in 2021. Because COVID-19 mortality is associated with socioeconomic status (SES), we hypothesize that certain subgroups of the Danish population experienced changes in life expectancy in 2020 and 2021 that differed from the country overall. We aim to quantify life expectancy in Denmark in 2020 and 2021 by SES and compare this to recent trends in life expectancy (2014–2019). Methods: We used Danish registry data from 2014 to 2021 for all individuals aged 30+. We classified the study population into SES groups using income quartiles and calculated life expectancy at age 30 by year, sex, and SES, and the differences in life expectancy from 2019 to 2020 and 2020 to 2021. We compared these changes to the average 1-year changes from 2014 to 2019 with 95% confidence intervals. Lastly, we decomposed these changes by age and cause of death distinguishing seven causes, including COVID-19, and a residual category. Results: We observed a mortality gradient in life expectancy changes across SES groups in both pandemic years. Among women, those of higher SES experienced a larger increase in life expectancy in 2020 and a smaller decrease in 2021 compared to those of lower SES. Among men, those of higher SES experienced an increase in life expectancy in both 2020 and 2021, while those of lower SES experienced a decrease in 2021. The impact of COVID-19 mortality on changes in life expectancy in 2020 was counterbalanced by improvements in non-COVID-19 mortality, especially driven by cancer and cardiovascular mortality. However, in 2021, non-COVID-19 mortality contributed negatively even for causes as cardiovascular mortality that has generally a positive impact on life expectancy changes, resulting in declines for most SES groups. Conclusions: COVID-19 mortality disproportionally affected those of lower SES and exacerbated existing social inequalities in Denmark. We conclude that in health emergencies, particular attention should be paid to those who are least socially advantaged to avoid widening the already existing mortality gap with those of higher SES. This research contributes to the discussion on social inequalities in mortality in high-income countries