scholarly journals Some population mortality indicators of the large region of Volga federal district

2021 ◽  
Vol 21 (1) ◽  
pp. 44-48
Author(s):  
Svetlana V. Ustavshchikova ◽  
Keyword(s):  
Total Population ◽  
Alcohol Exposure ◽  
Federal District ◽  
Mortality Rates ◽  
Physical And Mental Health ◽  
Working Age ◽  
External Causes ◽  
Population Mortality ◽  
Regional Authorities ◽  
Drug And Alcohol

Reducing the mortality rate of the population: general, in childhood and people of working age is a priority goal of the federal and regional authorities. However, an increase in the proportion of the population in older ages in the total population, and an increase in life expectancy leads to an aging of the population as a whole, and, consequently, to an increase (all other things being equal) of the relative mortality rates of the entire population. The potential for mortality reduction is a reduction in mortality due to external causes: from accidents, poisoning, injuries, drug and alcohol exposure. Strengthening the physical and mental health of the population will also contribute to this component decrease.

scholarly journals The age vector of risk factors for mortality of young Muscovites

2021 ◽  
Vol 2 (2) ◽  
pp. 15-25
Author(s):  
Victoria G. Semyonova ◽  
Alla E. Ivanova ◽  
Tamara P. Sabgayda ◽  
Galina N. Evdokushkina
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Mental Disorders ◽  
Age Groups ◽  
Mortality Rates ◽  
Health Priorities ◽  
Working Age ◽  
External Causes ◽  
Population Mortality ◽  
High Level

European-like life expectancy levels in Moscow are attributable to the prevalence of older population and the manifold increase in the working-age population mortality, especially among young people. The goal of the study is to identify the age-specific risk factors for Moscow youth mortality. This analysis is based on the official Russian Statistics Service’ data on mortality in the age groups of 15–24 and 25–34 years between 2000 and 2019. As demonstrated, during the study period, the Moscow youth mortality rates decreased twofold between both age groups. Starting from 2017, the mortality rate of Moscow youth began to increase, mainly among the 15–24-year-olds. The age vector of the youth mortality structure indicates a change in risk factors associated with age: while adolescents die from external causes, i.e. specific risks directly leading to death, later on youth mortality is more often associated with long-term behavioral factors indirectly resulting in death (such as sexual conduct as a risk factor for HIV/AIDS mortality, alcohol as the main cause for deaths from digestive system diseases and mental disorders, drugs as a risk factor for deaths from cardiovascular diseases and mental disorders). It is important to take note of the wide age range of the population classified as «young»: while it might be justified in legal and social context, in the demographic context it blurs the differences in mortality among people of different ages. Moreover, the abnormally high level and contribution of mortality from inaccurately described conditions, which the Moscow youth suffered from in the 2000s, calls into question the official rates of mortality due to underlying causes, primarily injuries, poisonings, and circulatory diseases. At the same time, given the increase in the young people’s overall mortality in the recent years, the extremely high mortality rates from inaccurately described conditions make it difficult to identify health priorities for the Moscow youth and, therefore, do not allow determining the reserves for their effective decline.

scholarly journals MEDICAL AND STATISTICAL INDICATORS OF MORTALITY IN EMPLOYEES OF RUSSIAN STATE FIRE SERVICE (1996–2015)

2019 ◽  
pp. 5-26 ◽  
Author(s):  
S. S. Aleksanin ◽  
E. V. Bobrinev ◽  
V. I. Evdokimov ◽  
A. A. Kondashov ◽  
N. A. Mukhina ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Causes Of Death ◽  
Mortality Rates ◽  
Fire Service ◽  
The State ◽  
Russian State ◽  
Working Age ◽  
Icd 10 ◽  
External Causes ◽  
Statistical Indicators

Relevance. Russia has high mortality rates in general and among the working-age population, with dominating effects of external causes.Intention– To study rates and structures of the medical-statistical indicators of mortality due to diseases and the effects of external causes in the employees of the State Fire Service of the EMERCOM of Russia over 20 years from 1996 to 2015.Methods.Annual population under study averaged (108.8 ± 6.2) thousand people, or about 80% of all the employees of the State Fire Service of Russia who had special military ranks. Operating staff comprised 53.4%, other employees – 46.6%. Mortality rates were calculated per 100 thousand employees of the State Fire Service of Russia. Data on the mortality of working-age men in Russia was obtained on the website of the Federal Statistics Service of Russia (Rosstat) [http://www.gks.ru/]. The unification of accounting and analysis of indicators was achieved using the International Statistical Classification of Diseases and Related Health Problems, the 10th revision (ICD-10). Results and Discussion. Mortality rate among employees of the State Fire Service of the EMERCOM of Russia in 1996–2015 was (116.9 ± 5.7) deaths per 100 thousand employees per year vs 11 times higher mortality rate among the working-age male population of Russia: (1063.9 ± 33.7) deaths per 100 thousand men (p < 0.001). The mean age of the deceased employees of the State Fire Service of Russia was (44.5 ± 0.3) years, with overall mean age (36.9 ± 1.6) years (p < 0.001). The leading causes of death among employees of the State Fire Service of Russia (from more to less significant) were injuries and other effects of external causes (ICD-10 chapter XIX), diseases of the circulatory system (chapter IX) and neoplasms (II), diseases of the digestive system (XI) and diseases of the respiratory system (X). Mortality rates from these causes per 100 thousand employees per year amounted to (63.3 ± 33.7), (32.6 ± 2.7), (7.1 ± 0.6), (5.3 ± 1.0) and (5.0 ± 0.9) deaths; in cause-of-death structure – 54.2, 27.9, 6.0, 4.5 and 4.3%, respectively. The mortality rate from suicide among working-age Russian men was 6.4 times higher than that of firefighters – (66.0 ± 4.1) and (10.3 ± 1.1) deaths per 100 thousand men, respectively. However, in the overall cause-of-death structure, this cause accounted for a larger share in employ ees of the Russian State Fire Service (6.2 vs 8.8%). Statistically significant difference (p < 0.05) was found when comparing occupational fatalities among the operating personnel of the State Fire Service of Russia and working population in Russia: (14.9 ±1.4) deaths per 100 thousand employees per year vs (11.6 ± 0.7) deaths per 100 thousand workers per year. Mortality rates of firefighters were calculated in the Federal districts and regions of Russia. For a number of causes of death in firefighters, there is a significant contribution of occupational factors, which require further research.Conclusion.There is a low alertness for identifying neoplasms and crisis conditions in firefighters. Focusing on the leading diseases, behavioral disorders, prevention of injuries, poisoning and other effects of external causes will improve health and reduce mortality of employees of the State Fire Service of Russia.Authors declare the absence of existing and potential conflicts of interest concerning the article publication. 

ACTORS IN THE FORMATION OF HUMAN CAPITAL IN THE FAR EAST REGIONS

2020 ◽  
pp. 5-17
Author(s):  
Artem S. Lukyanets ◽  
◽  
Roman V. Manshin ◽  
Keyword(s):  
Human Capital ◽  
Far East ◽  
Development Program ◽  
Federal District ◽  
United Nations Development Program ◽  
The Far East ◽  
Working Age ◽  
External Causes ◽  
The Cost ◽  
Far Eastern

The article examines the main factors in the formation of human capital in the regions of the Far Eastern Federal District. The article discusses in detail the main indicators that form the integral human development index, developed by the specialists of the United Nations Development Program. The key characteristics of socio-economic processes were identified, an analysis of the most important economic indicators of the studied subjects of the Russian Federation was given. It was found that one of the most important components of human capital is the social and economic stability of society. In the regions of the Far East, on the whole, an unfavorable socio-economic situation has developed, which directly affects human capital. It was found that, despite the higher level of income compared to the average for Russia, the real incomes of residents, adjusted for the cost of living in the considered regions, turned out to be lower than in Russia. An important factor in the development of human capital is the life expectancy of the population, which in the regions of the Far East is below the national average and does not reach the planned targets set by the Concept of the Demographic Policy of the Far East for the period up to 2025. It has been established that the main contribution is made by external causes of death in the male working-age population in the most sparsely populated regions, characterized by a low level of development of medical infrastructure and its availability. Another factor in the development of human capital is the level of education of the population. The development of this factor in the Far East repeats the all-Russian trajectory, maintaining the tendency to reduce the number of educational institutions at all levels, an increase in the number of students in programs of primary secondary and complete education is recorded. The persistence of such trends, together with changes in the age structure of the population, can negatively affect the development of human capital in the regions of the Far East.

scholarly journals Disaggregating Proportional Multistate Lifetables by Population Heterogeneity to Estimate Intervention Impacts on Inequalities

2021 ◽  
Author(s):  
Patrick Andersen ◽  
Anja Mizdrak ◽  
Nick Wilson ◽  
Anna Davies ◽  
Laxman Bablani ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Total Population ◽  
Case Fatality ◽  
Mortality Rates ◽  
Time Step ◽  
Life Years ◽  
All Cause Mortality ◽  
Population Mortality ◽  
Rate Ratios

Abstract BackgroundSimulation models can be used to quantify the projected health impact of interventions. Quantifying heterogeneity in these impacts, for example by socioeconomic status, is important to understand impacts on health inequalities.We aim to disaggregate one type of Markov macro-simulation model, the proportional multistate lifetable, ensuring that under business-as-usual (BAU) the sum of deaths across disaggregated strata in each time step returns the same as the initial non-disaggregated model. We then demonstrate the application by deprivation quintiles for New Zealand (NZ), for: hypothetical interventions (50% lower all-cause mortality, 50% lower coronary heart disease mortality) and a dietary intervention to substitute 59% of sodium with potassium chloride in the food supply. MethodsWe developed a disaggregation algorithm that iteratively rescales mortality, incidence and case fatality rates by time-step of the model to ensure correct total population counts were retained at each step.To demonstrate the algorithm on deprivation quintiles in NZ, we used the following inputs: overall (non-disaggregated) all-cause mortality & morbidity rates, coronary heart disease incidence & case fatality rates; stroke incidence & case fatality rates. We also obtained rate ratios by deprivation for these same measures. Given all-cause and cause-specific mortality rates by deprivation quintile, we derived values for the incidence, case fatality and mortality rates for each quintile, ensuring rate ratios across quintiles and the total population mortality and morbidity rates were returned when averaged across groups.The three interventions were then run on top of these scaled BAU scenarios. ResultsThe algorithm exactly disaggregated populations by strata in BAU. The intervention scenario life years and health adjusted life years (HALYs) gained differed slightly when summed over the deprivation quintile compared to the aggregated model, due to the stratified model (appropriately) allowing for differential background mortality rates by strata. Modest differences in health gains (health adjusted life years) resulted from rescaling of sub-population mortality and incidence rates to ensure consistency with the aggregate population.ConclusionPolicy makers ideally need to know the effect of population interventions estimated both overall, and by socioeconomic and other strata. We demonstrate a method and provide code to do this routinely within proportional multistate lifetable simulation models and similar Markov models.

scholarly journals Risk of death among people with rare autoimmune diseases compared to the general population in England during the 2020 COVID-19 pandemic

2020 ◽  
Author(s):  
Emily Peach ◽  
Megan Rutter ◽  
Peter Lanyon ◽  
Matthew J Grainge ◽  
Richard Hubbard ◽  
...  
Keyword(s):  
General Population ◽  
Healthcare Services ◽  
Mortality Rates ◽  
Published Data ◽  
List Type ◽  
Risk Of Death ◽  
Increased Risk ◽  
Working Age ◽  
Population Mortality ◽  
The Uk

AbstractObjectivesTo quantify the risk of death among people with rare autoimmune rheumatic diseases (RAIRD) during the UK 2020 COVID-19 pandemic compared to the general population, and compared to their pre-COVID risk.MethodsWe conducted a cohort study in Hospital Episode Statistics for England 2003 onwards, and linked data from the NHS Personal Demographics Service. We used ONS published data for general population mortality rates.ResultsWe included 168,691 people with a recorded diagnosis of RAIRD alive on 01/03/2020. Their median age was 61.7 (IQR 41.5-75.4) years, and 118,379 (70.2%) were female. Our case ascertainment methods had a positive predictive value of 85%. 1,815 (1.1%) participants died during March and April 2020. The age-standardised mortality rate (ASMR) among people with RAIRD (3669.3, 95% CI 3500.4-3838.1 per 100,000 person-years) was 1.44 (95% CI 1.42-1.45) times higher than the average ASMR during the same months of the previous 5 years, whereas in the general population of England it was 1.38 times higher. Age-specific mortality rates in people with RAIRD compared to the pre-COVID rates were higher from the age of 35 upwards, whereas in the general population the increased risk began from age 55 upwards. Women had a greater increase in mortality rates during COVID-19 compared to men.ConclusionThe risk of all-cause death is more prominently raised during COVID-19 among people with RAIRD than among the general population. We urgently need to quantify how much risk is due to COVID-19 infection and how much is due to disruption to healthcare services.Key messagesPeople with RAIRD had an increased risk of dying during COVID-19 from age 35 years onwards, whereas in the general population it increased from the age of 55 onwards.Women had a greater increase in their risk of death during COVID-19 compared to men.The risk of working age people with RAIRD dying during COVID-19 was similar to that of someone 20 years older in the general population.

scholarly journals Didelis priešlaikinis Lietuvos vyrų mirtingumas. Kaita ir priežastys

2014 ◽  
Vol 8 ◽  
pp. 79-88
Author(s):  
Daumantas Stumbrys
Keyword(s):  
Premature Mortality ◽  
Mortality Rates ◽  
High Rate ◽  
Mortality Pattern ◽  
Human Mortality ◽  
Health Lifestyle ◽  
Social Fund ◽  
Working Age ◽  
External Causes ◽  
G 11

Lietuvos socialinių tyrimų centrasA. Goštauto g. 11, LT-01108 Vilnius, LietuvaTel. (8-5) 275 34 46El. paštas: [email protected]  Posovietinių valstybių gyventojams būdinga mirtingumo pokyčių diferenciacija pagal socialinius demografinius požymius. Straipsnyje, remiantis Wiliamo C. Cockerhamo su sveikata susijusios gyvensenos teorija, nagrinėjama didelio priešlaikinio Lietuvos vyrų mirtingumo problema. Straipsnio tikslas – pristatyti, kaip kito darbingo amžiaus Lietuvos vyrų mirtingumo rodikliai nuo 1959 m. ir kokie buvo tų rodiklių kaitos skirtumai, palyginti su kitomis Europos šalimis. Gyventojų mirtingumo rodiklių statistinė analizė atlikta naudojant Human Mortality Database ir European Mortality Database duomenis. Nustatyta, kad darbingo amžiaus vyrų mirtingumo rodikliai, palyginti su kitomis Vakarų Europos šalimis, Lietuvoje yra ypač dideli. Lietuvos vyrų tikimybė numirti 25–44 metų 2009 m. buvo 2,9 karto didesnė negu Prancūzijos vyrų ir3,4 karto didesnė negu Lietuvos moterų. Vienas iš svarbiausių tokio didelio Lietuvos vyrų mirtingumo veiksnių – ypač didelis mirtingumas dėl išorinių mirties priežasčių. Mokslinis tyrimas finansuojamas Europos socialinio fondo lėšomis pagal visuotinės dotacijos priemonę (sutarties Nr. VP1-3.1-ŠMM-07-K-02-067).Pagrindiniai žodžiai: mirties priežastys, mirtingumo diferenciacija, priešlaikinis vyrų mirtingumasHigh Premature Morality Rates Among Men in Lithuania. Patterns and Causes Daumantas Stumbrys Summary The mortality pattern of the post-soviet population shows a notable life expectancy differentiation by sex, marital status, education, place of residence, and other socio-demographic variables. This publication presents results of a study of mortality patterns among working-age men in Lithuania. The study is based on the Cockerham health lifestyle theory. The main purpose of the study is to evaluate men’s mortality fluctuation since the year 1959. The Lithuanian mortality rates were compared with the mortality rates in other European countries. This study is based on data from the Human Mortality Database and the European Mortality Database. The results of the study confirm that for men the probability to die in the working age in Lithuania is more than twice as high as in France. The Lithuanian working-age men’s population has a very high rate of mortality from external causes and alcohol-related deaths. This research is funded by the European Social Fund under the Global Grant measure (project No. VP1-3.1-ŠMM-07-K-02-067). Key words: causes of death, mortality differentials, men’s premature mortality

Features of population mortality from the main causes in 2009–2018 in the Russian federation, the Far East, the Khabarovsk territory

2020 ◽  
pp. 36-41
Keyword(s):  
Russian Federation ◽  
Far East ◽  
Circulatory System ◽  
Federal District ◽  
Malignant Neoplasms ◽  
Causes Of Mortality ◽  
The Russian Federation ◽  
External Causes ◽  
Population Mortality ◽  
Far Eastern

The article is devoted to the analysis of changes in the mortality rate of the population in the Russian Federation, the Far Eastern Federal District and the Khabarovsk Territory in general and due to the main causes of mortality: diseases of the circulatory system, malignant neoplasms and external causes for the period from 2009 to 2018.

scholarly journals Disaggregating proportional multistate lifetables by population heterogeneity to estimate intervention impacts on inequalities

2022 ◽  
Vol 20 (1) ◽  
Author(s):  
Patrick Andersen ◽  
Anja Mizdrak ◽  
Nick Wilson ◽  
Anna Davies ◽  
Laxman Bablani ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Total Population ◽  
Case Fatality ◽  
Simulation Models ◽  
Mortality Rates ◽  
Time Step ◽  
Life Years ◽  
All Cause Mortality ◽  
Population Mortality ◽  
Rate Ratios

Abstract Background Simulation models can be used to quantify the projected health impact of interventions. Quantifying heterogeneity in these impacts, for example by socioeconomic status, is important to understand impacts on health inequalities. We aim to disaggregate one type of Markov macro-simulation model, the proportional multistate lifetable, ensuring that under business-as-usual (BAU) the sum of deaths across disaggregated strata in each time step returns the same as the initial non-disaggregated model. We then demonstrate the application by deprivation quintiles for New Zealand (NZ), for: hypothetical interventions (50% lower all-cause mortality, 50% lower coronary heart disease mortality) and a dietary intervention to substitute 59% of sodium with potassium chloride in the food supply. Methods We developed a disaggregation algorithm that iteratively rescales mortality, incidence and case-fatality rates by time-step of the model to ensure correct total population counts were retained at each step. To demonstrate the algorithm on deprivation quintiles in NZ, we used the following inputs: overall (non-disaggregated) all-cause mortality & morbidity rates, coronary heart disease incidence & case fatality rates; stroke incidence & case fatality rates. We also obtained rate ratios by deprivation for these same measures. Given all-cause and cause-specific mortality rates by deprivation quintile, we derived values for the incidence, case fatality and mortality rates for each quintile, ensuring rate ratios across quintiles and the total population mortality and morbidity rates were returned when averaged across groups. The three interventions were then run on top of these scaled BAU scenarios. Results The algorithm exactly disaggregated populations by strata in BAU. The intervention scenario life years and health adjusted life years (HALYs) gained differed slightly when summed over the deprivation quintile compared to the aggregated model, due to the stratified model (appropriately) allowing for differential background mortality rates by strata. Modest differences in health gains (HALYs) resulted from rescaling of sub-population mortality and incidence rates to ensure consistency with the aggregate population. Conclusion Policy makers ideally need to know the effect of population interventions estimated both overall, and by socioeconomic and other strata. We demonstrate a method and provide code to do this routinely within proportional multistate lifetable simulation models and similar Markov models.

scholarly journals Mortality and Alcohol as Its Cause—Comparative Characteristics of the Two Neighboring Countries: Ukraine and Poland

2021 ◽  
Vol 18 (20) ◽  
pp. 10810
Author(s):  
Oleh Lyubinets ◽  
Marta Kachmarska ◽  
Katarzyna Maria Sygit ◽  
Elżbieta Cipora ◽  
Jaroslaw Grshybowskyj
Keyword(s):  
Alcohol Consumption ◽  
Age Groups ◽  
Mortality Rates ◽  
Male Population ◽  
Classification Of Diseases ◽  
Working Age ◽  
International Statistical Classification ◽  
The Difference ◽  
Population Mortality

This paper presents a comparative assessment of mortality in Poland and Ukraine, including due to alcohol consumption, by sex, place of residence, and age groups. Mortality from alcohol consumption is and remains one of the health problems of the state’s population. The aim of this study was to establish the difference in mortality, including due to alcohol consumption, in the two neighboring countries. The analysis was conducted in 2008 and 2018 according to statistical institutions in Poland and Ukraine. Data from the codes of the International Statistical Classification of Diseases of the 10th edition: F10, G31.2, G62.1, I42.6, K70, K86.0, and X45 were used to calculate mortality due to alcohol consumption. The share of mortality caused by alcohol consumption in Ukraine in 2008 was 3.52%, and 1.83% in 2018. At the same time, in Poland, there is an increase in this cause of death from 1.72% to 2.36%. Mortality caused by alcohol consumption is the main share of mortality in the section “Mental and behavioral disorders” in both Ukraine, at 73–74%, and Poland, at 82–92%. Changes in the mortality rate in the cities and villages of Ukraine and Poland showed different trends: Poland nated, a significant increase in mortality, while in Ukraine it has halved on average. Overall and alcohol mortality rates in both countries were higher among the male population. The analysis of mortality among people of working age showed that the highest proportion of deaths from alcohol consumption in both countries was among people aged 25–44. Despite the geographical proximity, and similarity of natural and climatic characteristics and population, mortality rates in each country reflect the difference in the medical and demographic situation, and the effectiveness of state social approaches to public health.

scholarly journals Disaggregating proportional multistate lifetables by population heterogeneity to estimate intervention impacts on inequalities

2021 ◽  
Author(s):  
Patrick Andersen ◽  
Anja Mizdrak ◽  
Nick Wilson ◽  
Anna Davies ◽  
Laxman Bablani ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Total Population ◽  
Case Fatality ◽  
Simulation Models ◽  
Mortality Rates ◽  
Time Step ◽  
Life Years ◽  
All Cause Mortality ◽  
Population Mortality ◽  
Rate Ratios

AbstractBackgroundSimulation models can be used to quantify the projected health impact of interventions. Quantifying heterogeneity in these impacts, for example by socioeconomic status, is important to understand impacts on health inequalities.We aim to disaggregate one type of Markov macro-simulation model, the proportional multistate lifetable, ensuring that under business-as-usual (BAU) the sum of deaths across disaggregated strata in each time step returns the same as the initial non-disaggregated model. We then demonstrate the application by deprivation quintiles for New Zealand (NZ), for: hypothetical interventions (50% lower all-cause mortality, 50% lower coronary heart disease mortality) and a dietary intervention to substitute 59% of sodium with potassium chloride in the food supply.MethodsWe developed a disaggregation algorithm that iteratively rescales mortality, incidence and case fatality rates by time-step of the model to ensure correct total population counts were retained at each step.To demonstrate the algorithm on deprivation quintiles in NZ, we used the following inputs: overall (non-disaggregated) all-cause mortality &morbidity rates, coronary heart disease incidence &case fatality rates; stroke incidence &case fatality rates. We also obtained rate ratios by deprivation for these same measures. Given all-cause and cause-specific mortality rates by deprivation quintile, we derived values for the incidence, case fatality and mortality rates for each quintile, ensuring rate ratios across quintiles and the total population mortality and morbidity rates were returned when averaged across groups.The three interventions were then run on top of these scaled BAU scenarios.ResultsThe algorithm exactly disaggregated populations by strata in BAU. The intervention scenario life years and health adjusted life years (HALYs) gained differed slightly when summed over the deprivation quintile compared to the aggregated model, due to the stratified model (appropriately) allowing for differential background mortality rates by strata. Modest differences in health gains (health adjusted life years) resulted from rescaling of sub-population mortality and incidence rates to ensure consistency with the aggregate population.ConclusionPolicy makers ideally need to know the effect of population interventions estimated both overall, and by socioeconomic and other strata. We demonstrate a method and provide code to do this routinely within proportional multistate lifetable simulation models and similar Markov models.

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