scholarly journals Differences in Life Expectancy and Age-Specific Mortality between the Large Cities of Ukraine

2021 ◽  
pp. 3-21
Author(s):  
N. M. LEVCHUK
Keyword(s):  
Life Expectancy ◽  
Urban Areas ◽  
Excess Mortality ◽  
Age Groups ◽  
Urban Life ◽  
Large Cities ◽  
Life Expectancy At Birth ◽  
Urban Settlements ◽  
Dence Interval ◽  
Almost All

The aim of this paper is to identify the age-specifi c characteristics of the mortality in the large cities of Ukraine and their contributions to the changes in life expectancy in these cities. The article presents the results of a comparative analysis of the dynamics of life expectancy from 2002 through 2019 in six cities: Kyiv, Kharkiv, Odesa, Dnipro, and Donetsk. It is shown that most of the large cities have generally experienced higher life expectancy than other urban settlements in Ukraine, but there is a signifi cant variation in the levels and changes in life expectancy across cities. Overall, the study established the vanguard position of Lviv and Kyiv in terms of life expectancy, although these cities, as well as Kharkiv, showed a slower increase in life expectancy in 2002-2019. In contrast, Dnipro and Odesa, as well as Donetsk (up to 2014) having lower life expectancy and wider diff erences by sex demonstrated the pronounced improvement in life expectancy during that period. In recent years, there has been a trend towards narrowing the gap between cities, and this convergence is occurring more rapidly among men than among women. In 2002, the gap between cities with the highest and lowest life expectancy was 5.4 years for males and 2.6 years for females while in 2019 it was reduced to 2 years for men and 1.6 years for women. We made a decomposition of diff erences in life expectancy at birth between the cities in 2002 and 2019 to assess the age-specifi c mortality contributions into disparities between urban areas. The results have revealed that across almost all cities these diff erences are mainly driven by excess mortality in working ages. Also, we found that excess mortality in the middle working ages and under 1 year of age appeared to be the important factors of lower life expectancy in Donetsk compared to Lviv and Kyiv. Odesa and Dnipro are lagging behind by survival rate not only in the older but also in young working age groups, and Kharkiv has slightly higher mortality among older people (in comparison to Lviv and Kyiv). Th e conclusion is made that the main gradient of diff erences in life expectancy between the large cities has been determined mainly by deaths in working ages, i.e. mostly driven by health-related behavior and lifestyle. Nevertheless, a gradual shift in urban life expectancy diff erences is now taking place towards mortality in older age groups, i.e. more determined by the eff ectiveness of treatment of chronic diseases. Th e issue of data quality is also considered. In particular, the confi dence interval of the probability of dying in the fi rst year of life in the six selected cities is estimated to determine the accuracy of these indicators.

scholarly journals Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis

2021 ◽  
pp. jech-2020-215505
Author(s):  
Jose Manuel Aburto ◽  
Ridhi Kashyap ◽  
Jonas Schöley ◽  
Colin Angus ◽  
John Ermisch ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Excess Mortality ◽  
Prediction Interval ◽  
Age Groups ◽  
Population Level ◽  
England And Wales ◽  
Life Expectancy At Birth ◽  
Using Data ◽  
The Impact ◽  
Excess Deaths

BackgroundDeaths directly linked to COVID-19 infection may be misclassified, and the pandemic may have indirectly affected other causes of death. To overcome these measurement challenges, we estimate the impact of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality from week 10 of 2020, when the first COVID-19 death was registered, to week 47 ending 20 November 2020 in England and Wales through an analysis of excess mortality.MethodsWe estimated age and sex-specific excess mortality risk and deaths above a baseline adjusted for seasonality with a systematic comparison of four different models using data from the Office for National Statistics. We additionally provide estimates of life expectancy at birth and lifespan inequality defined as the SD in age at death.ResultsThere have been 57 419 (95% prediction interval: 54 197, 60 752) excess deaths in the first 47 weeks of 2020, 55% of which occurred in men. Excess deaths increased sharply with age and men experienced elevated risks of death in all age groups. Life expectancy at birth dropped 0.9 and 1.2 years for women and men relative to the 2019 levels, respectively. Lifespan inequality also fell over the same period by 5 months for both sexes.ConclusionQuantifying excess deaths and their impact on life expectancy at birth provide a more comprehensive picture of the burden of COVID-19 on mortality. Whether mortality will return to—or even fall below—the baseline level remains to be seen as the pandemic continues to unfold and diverse interventions are put in place.

scholarly journals The decomposition of life expectancy for age and cause of death in Tuscany, Italy

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
N Nante ◽  
L Kundisova ◽  
F Gori ◽  
A Martini ◽  
F Battisti ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Causes Of Death ◽  
National Level ◽  
Age Groups ◽  
Resistant Bacteria ◽  
Mortality Data ◽  
Life Expectancy At Birth ◽  
Icd 10 ◽  
Reduction Of Mortality ◽  
The Impact

Abstract Introduction Changing of life expectancy at birth (LE) over time reflects variations of mortality rates of a certain population. Italy is amongst the countries with the highest LE, Tuscany ranks fifth at the national level. The aim of the present work was to evaluate the impact of various causes of death in different age groups on the change in LE in the Tuscany region (Italy) during period 1987-2015. Material and methods Mortality data relative to residents that died during the period between 1987/1989 and 2013/2015 were provided by the Tuscan Regional Mortality Registry. The causes of death taken into consideration were cardiovascular (CVS), respiratory (RESP) and infective (INF) diseases and cancer (TUM). The decomposition of LE gain was realized with software Epidat, using the Pollard’s method. Results The overall LE gain during the period between two three-years periods was 6.7 years for males, with a major gain between 65-89, and 4.5 years for females, mainly improved between 75-89, <1 year for both sexes. The major gain (2.6 years) was attributable to the reduction of mortality for CVS, followed by TUM (1.76 in males and 0.83 in females) and RESP (0.4 in males; 0.1 in females). The major loss of years of LE was attributable to INF (-0.15 in females; -0.07 in males) and lung cancer in females (-0.13), for which the opposite result was observed for males (gain of 0.62 years of LE). Conclusions During the study period (1987-2015) the gain in LE was major for males. To the reduction of mortality for CVS have contributed to the tempestuous treatment of acute CVS events and secondary CVS prevention. For TUM the result is attributable to the adherence of population to oncologic screening programmes. The excess of mortality for INF that lead to the loss of LE can be attributed to the passage from ICD-9 to ICD-10 in 2003 (higher sensibility of ICD-10) and to the diffusion of multi-drug resistant bacteria, which lead to elevated mortality in these years. Key messages The gain in LE during the period the 1987-2015 was higher in males. The major contribution to gain in LE was due to a reduction of mortality for CVS diseases.

scholarly journals Beyond standardized mortality ratios; some uses of smoothed age-specific mortality rates on small areas studies

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Jordi Perez-Panades ◽  
Paloma Botella-Rocamora ◽  
Miguel Angel Martinez-Beneito
Keyword(s):  
Life Expectancy ◽  
Age Groups ◽  
Dependence Structure ◽  
Risk Indicator ◽  
Small Areas ◽  
Life Expectancy At Birth ◽  
First Case ◽  
Wide Range ◽  
Standardized Mortality Ratios

Abstract Background Most epidemiological risk indicators strongly depend on the age composition of populations, which makes the direct comparison of raw (unstandardized) indicators misleading because of the different age structures of the spatial units of study. Age-standardized rates (ASR) are a common solution for overcoming this confusing effect. The main drawback of ASRs is that they depend on age-specific rates which, when working with small areas, are often based on very few, or no, observed cases for most age groups. A similar effect occurs with life expectancy at birth and many more epidemiological indicators, which makes standardized mortality ratios (SMR) the omnipresent risk indicator for small areas epidemiologic studies. Methods To deal with this issue, a multivariate smoothing model, the M-model, is proposed in order to fit the age-specific probabilities of death (PoDs) for each spatial unit, which assumes dependence between closer age groups and spatial units. This age–space dependence structure enables information to be transferred between neighboring consecutive age groups and neighboring areas, at the same time, providing more reliable age-specific PoDs estimates. Results Three case studies are presented to illustrate the wide range of applications that smoothed age specific PoDs have in practice . The first case study shows the application of the model to a geographical study of lung cancer mortality in women. This study illustrates the convenience of considering age–space interactions in geographical studies and to explore the different spatial risk patterns shown by the different age groups. Second, the model is also applied to the study of ischaemic heart disease mortality in women in two cities at the census tract level. Smoothed age-standardized rates are derived and compared for the census tracts of both cities, illustrating some advantages of this mortality indicator over traditional SMRs. In the latest case study, the model is applied to estimate smoothed life expectancy (LE), which is the most widely used synthetic indicator for characterizing overall mortality differences when (not so small) spatial units are considered. Conclusion Our age–space model is an appropriate and flexible proposal that provides more reliable estimates of the probabilities of death, which allow the calculation of enhanced epidemiological indicators (smoothed ASR, smoothed LE), thus providing alternatives to traditional SMR-based studies of small areas.

Urban Sociology

Urban Studies ◽  
2020 ◽  
Author(s):  
Daniel J. Monti
Keyword(s):  
Urban Planning ◽  
Urban Areas ◽  
Urban Sociology ◽  
Far East ◽  
Urban Life ◽  
Sociological Inquiry ◽  
Urban Settlements ◽  
The Rich ◽  
Urban Places ◽  
The Way

Urban sociology is among the earliest and richest areas of sociological inquiry. It touches on topics and problems related to the way urban areas develop and the way people live in urban areas. While most of the attention of urban sociologists has been on more contemporary urban settings in Western societies, they’ve shown increasing interest in urban development and urban life in so-called developing countries and the Far East, especially India and China. By nature an interdisciplinary pursuit, five major academic fields contribute to urban sociology: anthropology, economics, history, political science, and social psychology. Specialists in these respective disciplines read and cite each other’s work and borrow from each other’s theoretical insights. One major profession, urban planning, is affiliated with urban sociology. It, too, has its own entry in Oxford Bibliographies in Geography “Urban Planning and Geography”. Another broad field that draws on all the same intellectual sources is urban studies. It was added to the curricula of US colleges and universities in the late 1960s in response to the turmoil that was occurring in many urban areas at that time. Given all the rich disciplinary sources that feed into urban sociology, this area of inquiry probably can be best understood by the themes that allow researchers to connect the disparate kinds of studies they do. The several sections into which this essay is divided have works that reflect one or more of the following four themes: (1) Urban sociologists focus on either the physical development of urban places (i.e., urbanization) or the way of life or culture practiced there (i.e., urbanism). (2) The work of urban sociologists asks how urban places are built and laid out. It also asks how urban settlements might be rebuilt or developed so they better serve or complement the way people live there. (3) Some urban sociologists look at smaller groups or venues such as neighborhoods (i.e., “micro” studies). Others look at much larger geographic areas and whole communities (i.e., “macro” studies). (4) Persons who do this kind of work tend to be either optimistic about the prospects for urban places and people or, more frequently, pessimistic about how well they will fare.

Socioeconomic factors affecting the longevity of the Japanese population: a study for 1980 and 1985

1992 ◽  
Vol 24 (4) ◽  
pp. 497-504 ◽  
Author(s):  
Eiichi Uchida ◽  
Shunichi Araki ◽  
Katsuyuki Murata
Keyword(s):  
Life Expectancy ◽  
Socioeconomic Factors ◽  
Low Income ◽  
Japanese Population ◽  
Age Groups ◽  
High Income ◽  
Factors Affecting ◽  
Life Expectancy At Birth ◽  
Males And Females

SummaryThe effects of urbanisation, low income and rejuvenation of the population on life expectancy at birth and at 20, 40 and 65 years of age for males and females in Japan were examined twice, in 1980 and 1985. For males, urbanisation was the major factor determining life expectancy at birth and at age 20 years, and low income was the key determinant of decreased life expectancy except at 65 years of age. For females high income was the factor significantly decreasing life expectancy at 65 years of age in 1980, and rejuvenation of the population inversely influenced life expectancy except at birth in 1985. Life expectancy for all age groups in 1985 was significantly longer than in 1980 for both males and females.

scholarly journals Impact of the COVID-19 pandemic on life expectancy in Madrid (Spain)

2020 ◽  
Author(s):  
Sergi Trias-Llimós ◽  
Usama Bilal
Keyword(s):  
Life Expectancy ◽  
Surveillance System ◽  
Excess Mortality ◽  
Daily Mortality ◽  
Life Expectancy At Birth ◽  
The World ◽  
Using Data ◽  
The Impact ◽  
Mortality Surveillance ◽  
Annual Mortality

The COVID-19 pandemic is causing substantial increases in mortality across populations, potentially causing stagnation or decline in life expectancy. We explored this idea by examining the impact of excess mortality linked to the COVID-19 crisis on life expectancy in the region of Madrid (Spain). Using data from the Daily Mortality Surveillance System (MoMo), we calculated excess mortality (death counts) for the weeks 10th to 14th in 2020 using data on expected and observed mortality, assuming no further excess mortality during the rest of the year. The expected annual mortality variation was +6%, +21% and +25% among men aged under 65, between 65 and 74 and over 75, respectively, and +5%, +13%, and 18% for women, respectively. This excess mortality during weeks 10th to 14th resulted in a life expectancy at birth decline of 1.6 years among men and 1.1 years among women. These estimates confirm that Madrid and other severely hit regions in the world may face substantial life expectancy declines.

scholarly journals The Adoption of Smoking and Its Effect on the Mortality Gender Gap in Netherlands: A Historical Perspective

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Fanny Janssen ◽  
Frans van Poppel
Keyword(s):  
Life Expectancy ◽  
Sex Difference ◽  
Gender Gap ◽  
Cancer Mortality ◽  
Historical Perspective ◽  
Excess Mortality ◽  
Attributable Mortality ◽  
Life Expectancy At Birth ◽  
Specific Mortality

We examine in depth the effect of differences in the smoking adoption patterns of men and women on the mortality gender gap in Netherlands, employing a historical perspective. Using an indirect estimation technique based on observed lung cancer mortality from 1931 to 2012, we estimated lifetime smoking prevalence and smoking-attributable mortality. We decomposed the sex difference in life expectancy at birth into smoking-related and nonsmoking-related overall and cause-specific mortality. The smoking epidemic in Netherlands, which started among men born around 1850 and among women from birth cohort 1900 onwards, contributed substantially to the increasing sex difference in life expectancy at birth from 1931 (1.3 years) to 1982 (6.7 years), the subsequent decline to 3.7 years in 2012, and the high excess mortality among Dutch men born between 1895 and 1910. Smoking-related cancer mortality contributed most to the increase in the sex difference, whereas smoking-related cardiovascular disease mortality was mainly responsible for the decline from 1983 onwards. Examining nonsmoking-related (cause-specific) mortality shed new light on the mortality gender gap and revealed the important role of smoking-related cancers, the continuation of excess mortality among women aged 40–50, and a smaller role of biological factors in the sex difference than was previously estimated.

scholarly journals Excess mortality in patients with schizophrenia spectrum disorders in Malaga (Spain): A cohort study

2021 ◽  
Vol 30 ◽  
Author(s):  
Berta Moreno-Küstner ◽  
Jose Guzman-Parra ◽  
Yolanda Pardo ◽  
Yolanda Sanchidrián ◽  
Sebastián Díaz-Ruiz ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Excess Mortality ◽  
Years Of Life Lost ◽  
Schizophrenia Spectrum Disorders ◽  
Case Register ◽  
Factors Associated ◽  
Life Expectancy At Birth ◽  
Schizophrenia Spectrum ◽  
Causes Of Mortality ◽  
Spectrum Disorders

Abstract Aims There is evidence that patients with schizophrenia spectrum disorders present higher mortality in comparison with the general population. The aim of this study was to analyse the causes of mortality and sociodemographic factors associated with mortality, standardised mortality ratios (SMRs), life expectancy and potential years of life lost (YLL) in patients with schizophrenia spectrum disorders in Spain. Methods The study included a cohort of patients from the Malaga Schizophrenia Case Register (1418 patients; 907 males; average age 42.31 years) who were followed up for a minimum of 10 years (median = 13.43). The factors associated with mortality were analysed with a survival analysis using Cox's proportional hazards regression model. Results The main causes of mortality in the cohort were circulatory disease (21.45%), cancer (17.09%) and suicide (13.09%). The SMR of the cohort was more than threefold that of the population of Malaga (3.19). The life expectancy at birth was 67.11 years old, which is more than 13 years shorter than that of the population of Malaga. The YLL was 20.74. The variables associated with a higher risk of mortality were age [adjusted hazard ratio (AHR) = 1.069, p < 0.001], male gender (AHR = 1.751, p < 0.001) and type of area of residence (p = 0.028; deprived urban zone v. non-deprived urban area, AHR = 1.460, p = 0.028). In addition, receiving welfare benefit status in comparison with employed status (AHR = 1.940, p = 0.008) was associated with increased mortality. Conclusions There is excess mortality in patients with schizophrenia spectrum disorders and also an association with age, gender, socioeconomic inequalities and receiving welfare benefits. Efforts directed towards improved living conditions could have a positive effect on reducing mortality.

Recent mortality in Britain: a review of trends and explanations

2021 ◽  
Author(s):  
Michael Murphy
Keyword(s):  
Life Expectancy ◽  
Excess Mortality ◽  
Seasonal Influenza ◽  
Dominant Role ◽  
Good Health ◽  
Healthy Life ◽  
Life Expectancy At Birth ◽  
Percentage Improvement ◽  
Health And Social Care

Abstract The annual percentage improvement in standardised mortality rates in the period 2011–19 was the lowest for 70 years, whereas the 2001–10 value was the highest since records began in 1841. A similar slowdown occurred from around 2011 in most European Union countries, although this was generally less severe than in Britain. Life expectancy at birth actually fell in USA for three successive years in period 2014–17. The downturn in Britain since 2011 was wide-ranging, affecting young and old, women and men and the more and the less advantaged to a broadly similar extent. Year-to-year variation in mortality increased mainly due to increased volatility in winter excess mortality from 2011, but all seasons showed lower rates of improvement in underlying longer-term trends. Mortality had started to improve at the end of the decade and the 2019 value was the lowest-ever value in Britain. Two main explanations for these trends have been advanced: UK Government post-2008 austerity policies, especially in the health and social care sectors, and the role of seasonal influenza. However, the evidence for a dominant role for either of these is weak. Longer-term overall trends have been determined principally by trends in cardiovascular rather than non-cardiovascular causes of death, although recent changes in discovery and coding of dementias makes it difficult to draw firm conclusions. Healthy life expectancy trends are also affected by changes in data and methods, but the proportion of life spent in good health for both women and men over age 65 has increased slightly since 2010.

scholarly journals Gender gap in life expectancy in India and role of age groups: A comparison between before and after male – female life expectancy at birth crossover

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260657
Author(s):  
Girimallika Borah
Keyword(s):  
Life Expectancy ◽  
Gender Gap ◽  
Age Groups ◽  
Absolute Number ◽  
Reproductive Age ◽  
Sample Survey ◽  
Mortality Data ◽  
Female Life Expectancy ◽  
Life Expectancy At Birth ◽  
Before And After

To assess the gender gap in life expectancy at birth in India and its major states as well as the timing of male-female life expectancy at birth crossover. To analyze the age-specific contributions to the changing gender differences before and after the crossover at the national and sub-national levels. We have used sample-survey-based age-specific mortality data available for the periods 1970–2018 to construct abridged life tables. The contribution of different age groups to the gender gap is estimated by using Arriaga’s method of decomposition. During 1981–85 female life expectancy at birth caught up with male life expectancy at birth for India and by 2005 all major states completed the crossover. The male-female crossover in life expectancy at the national level in the early 80s is remarkable in the face of continued female disadvantage from birth till adolescence, even for some richer states. We provide evidence that gender difference in longevity in favour of females is largely a function of adult age groups and younger age groups contribute negatively to the gender gap in life expectancy at birth in most states. Juxtaposing the results from contribution in an absolute number of years and their relative contribution change before and after the crossover, it is established that although the adult and old age groups contribute the highest in the absolute number of years before and after the crossover, the contribution of the reproductive age groups and childhood years in the recent time is most relevant in relative terms.

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