Starosno-polna struktura stanovništva u Republici Severnoj Makedoniji početkom 21. veka

The territorial and gender differences of the transformational process in the age structure of the Ukrainian population during the 20-years’ period are analyzed in the article. The key factors and tendencies in age structure in various regions are determined. The comparative analysis of its changes among urban and country-side population is performed. The general tendency characterizing the age structure of the urban and country-side population of Ukraine is pointed out – that is the decrease in the share of the younger than active work force, and the increase in the share of the senior citizens. In the present-day structure of the urban population every fourth citizen represents the 60+ age group. The differences in the degree and intensity of aging of the rural and urban population are shown. The index of aging among urban population is much higher and makes 175,6% against 146,9% on the rural territory. The intensification of the process of demographic aging by gender is proven. In 2021, in the total number of population of Ukraine the share of men in the 60+ age group was 36,1%, while the share of women of the same age group was 63,9%. In the years 2001- 2021, the share of women at post-workable age grew to 29,5% of the total number of female population, and that of men grew to 19,3% of the total number of male population. The growth in the share of women and men at post-workable age in the urban area and its decline in the rural area are indicated. Interregional differences in the transformational process in the age structure of the Ukrainian population are defined. The smallest share of the citizens in post-workable age is observed in Volyn, Rivne, and Transcarpathean regions. The biggest share of the citizens in post-workable age is observed in Luhansk, Donetsk, Chernihiv, Sumy, Cherkasy, Zaporizhzhia, Kirovohrad, and Poltava regions. The chare of the workable age citizens is growing in 22 administrative units of Ukraine. The consequences of the transformation in the age structure of population are evaluated. The hypothesis has been proven that the age structure changes are correlated with the share of women at reproductive age, and demographic load. The decrease in the share of workable population was caused by the decrease in the share of women at reproductive age from 48,4% to 43,4%. In the years 2000 – 2021 the demographic load on the workable population grew mainly due to the older age group population (in 2021 the demographic load difference between children and the retired was 148 people). The demographic load on the workable population is 7,8% higher in the rural area than in the urban. The attention is drawn to the necessity of taking into consideration territorial peculiarities in the process of transformation in the population age structure when substantiating national programs and measures of active demographic policy. The regions of Ukraine characterized by low economic development are facing the biggest hardships in the adaptation process towards the changes of population age structure. Key words: transformation in the age structure of population, urban and rural population, demographic aging, demographic load.

The population (human resources) is the bearer of economic and social development. The demographic development is shaped by natural (birth and death) and by migration components (immigration/emigration); when is presented by changes in the number and structures of the population, it can be stimulating, slowing down or can be a limitation for economic, social and spatial development. Demographic changes in Serbia in the first decade of the 21st century are a continuation of the negative tendencies which began in the last decade of the 20th century, substantially fuelled initiated by political and socioeconomic processes. In the last decade, the changes were more intensive and demographic development was marked by extremely depopulation, weakening of demographic potential and aging population. This has resulted in an increase disparity in the territorial distribution of the population (drastically discharge of rural and undeveloped areas). The aim of this research is to analyze the demographic changes in Serbia in the last intercensal period, spatial distribution and age structure of the population as a factor of development / constraints of balanced development.

Who gains from the demographic dividend? Forecasting income by age

Age structure is one of the most important demographic characteristics of the population, which is multicausally related to almost all population processes. On one hand, age structure is the complex result of processes such as fertility, mortality, immigration and emigration. At the same time, it substantially affects a number of socio-demographic phenomena such as marriage, divorce, migration, potential labour resources etc. Certain relationships between the age structure and other population characteristics, such as ethnic, educational, sex, economic or religious structure can also be observed. The demographic behaviour of the European population in the second half of the 20th and the beginning of the 21st century is characterised by significant changes. They are reflected in a number of population processes and indicies, which are typically interconnected and interrelated. These changes have been most strikingly manifested in a drop of fertility rates, changes in family behaviour, and shifts in the age structure of the population. The main aim of this paper is to analyse the time-space development of the age structure of the European population. The period of investigation is 1950-2010 which is extended by a projected development until 2060. Changes in age structure are analysed through several indicators such as coefficients of inflow, outflow and exchange, as well as with indices of economic and social support. Authors make also efforts to provide a complex assessment on population ageing. Using the method of standardised variable, 11 indicators of age structures for 39 European countries are used in the synthesis. In view of the londer time span, several types of age structures are pointed out in Europe.

Background:In Latin America, climate change, urbanization, and an aging population are intensifying health risks from extreme temperatures. To accurately assess future temperature-related mortality impacts, evidence that integrates key demographic factors—such as the dynamics of population age composition, mortality rates, and population size—is essential.Methods:We projected the impact of nonoptimal temperatures on all-age and age-specific mortality during 2045–2054 for 326 cities in Latin America. Our analysis combined city-level daily mortality counts, gridded temperature data, downscaled and bias-corrected temperature simulations, and demographic data. We projected temperature-mortality impacts under two climate change scenarios while also considering changing population size, age structure, and age-specific mortality rates.Findings:By 2045–2054, the percentage of heat-attributable deaths under the most extreme temperature scenario will more than double from 0.87 % (95 % CI 0.77, 0.96) to 2.06 % (95% CI 1.80, 2.33), but cold-related mortality will decrease. Population growth and aging will exacerbate heat-related risks and offset reductions in cold-related deaths. For example, changes in population age structure will drive an increase in the heat-related mortality rate of 176% from baseline for a moderate temperature scenario.Interpretation:Beyond temperature changes, demographic shifts—particularly population growth and aging—will significantly amplify mid-century temperature impacts on mortality, underscoring the need for targeted climate adaptation and public health strategies.

Variation in age and size of mature nine-spined sticklebacks (Pungitius pungitius) within and among 16 Fennoscandian populations were assessed using skeletochronology. The average age of individuals in a given population varied from 1.7 to 4.7 years. Fish from pond populations were on average older than those from lake and marine populations, and females tended to be older than males. Reproduction in marine and lake populations commenced typically at an age of two years, whereas that in ponds at an age of three years. The maximum life span of the fish varied from 3 to 7 years. Mean body size within and among populations increased with increasing age, but the habitat and population differences in body size persisted even after accounting for variation in population age (and sex) structure. Hence, the population differences in mean body size are not explainable by age differences alone. As such, much of the pronounced intraspecific variation in population age structure can be attributed to delayed maturation and extended longevity of the pond fish. The results are contrasted and discussed in the context of similar data from the three-spined stickleback (Gasterosteus aculeatus) occupying the same geographic area.

The study presents a comprehensive analysis of the issue of population ageing in the countries of the Visegrad Group (V4). Unprecedented changes in the populations’ age structure are examined and described within the broader context of social, economic and demographic developments in Europe. By comparing the demographic behaviour in the examined countries, the study provides new and relevant findings about inherent differences between the individual countries as well as within individual regions (NUTS 2).A comprehensive approach to study of the issue was maintained through the use of a broad range of methods. The temporal analysis was conducted by means of rosset’s classification and the Ossan triangle. The time period for examining the demographic changes was from 1960 to 2012. The Ossan triangle and cartographic analysis facilitate the comparison of age structure at the regional level. The study identifies the degree of population ageing, the key factors at work, and the internal structure of the phenomenon within the studied areas. Right from the onset of population ageing in the Czech Republic and Hungary, these countries have been converging to levels typical for Western European counterparts. A delayed onset of population ageing has been typical for the more conservative countries of Slovakia and Poland. Over the years in this study, several factors have affected population ageing – from economic and social developments to the emergence of new ideological currents as well as the absence of population policies. However, the internal structure of ageing within the examined countries has not been homogeneous. In North Western Czech Republic, Northern Hungary, the Northern Great Plain of Hungary, and Central and Eastern Slovakia, a relatively early timing of fertility is considered as standard due to the different ethnic, religious or educational characteristics of the population as well as weaker economies in these regions. On the other hand, Western Slovakia, Prague, South Eastern Central Hungary and Central Transdanubia have become centers of the newer ideological currents. Eastern Slovakia, Northern Hungary, the Northern Great Plain and the eastern part of Poland, with underdeveloped infrastructure and capital, have quickly become an ageing eastern periphery of the European Union.

Aim – The main aim of the study is to determine the dynamics of the ageing process of the Polish population and to present a forecast of population ageing based on comprehensive analysis of the age structure of this population. The separated components of this structure are biological age groups: 0–14, 15–64, 65 years and more. The time period of the research comprises the years 1950–2016, while the population forecast by age is presented for 2020 and 2050. The elaboration includes data from GUS. Research methodology – In assessing the level of the ageing of Polish society there were used, among others, the old age index, old age coefficient, a measure of the similarity of structures, a measure of the structural change intensity, and the median age. Score – In the years 1950–2016 in Poland there were observed changes in the age structure of the population in age groups: 0–14 years old, 15–64 years old, 65 years old and more, including a steady trend in the percentage of people in the age group 0–14 years old and a steady upward trend in the percentage of people aged 65 and over, a strong upward trend in the old age index, and a strong tendency of increase in the post-working age dependency ratio. The Central Statistical Office’s (GUS) forecasts indicate that the population ageing measured by changes in the age structure of the population and the shifting of the median age which are taking place in Poland in a dynamic manner, will continue with increased intensity over the next decades. Originality/value – The added value of the work is the use of the similarity of structures and the intensity of structure changes, which together with an approach based on classical indicators allowed for a comprehensive analysis of the age structure of the Polish population in dynamic terms, determining the quantitative nature of changes in the age structure over time, the direction of these changes and their intensity. It was also pointed out that in light of the ongoing demographic transformations, the concept of silver economy understood as an economic system aimed at using the potential of the elderly and taking into account their needs is becoming a priority.

Estimation of ambient PM2.5-related mortality burden in China by 2030 under climate and population change scenarios: A modeling study.

Background: Rhodiola quadrifida (Pall.) Fisch. & C.A. Mey. (Crassulaceae) is a rare medicinal species in the Kazakh Altai, yet information on its population structure and genetic diversity remains limited. This study presents findings from an investigation of natural R. quadrifida populations. Methods: The morphometric characteristics, population age structure, and genetic diversity of the plants were analysed using PCR-based genome profiling. Genetic diversity within R. quadrifida populations was assessed using PCR primers for binding sites complementary to a specific region at the 3′ terminus of a particular tRNA. Results: The populations exhibited variations in morphological traits, age structures, and reproductive strategies. The IVA-1, IVA-2 and KOK populations represent the most mature stages, characterized by a dominance of vegetative reproduction and a disturbed age structure, with a predominance of senile and virgin individuals. In contrast, the LIN-1 and LIN-2 population is characterized by a balanced age structure, encompassing all ontogenetic groups, and a mixed reproductive system that includes both sexual and vegetative propagation. Genetic diversity, as measured by Shannon’s information index, ranged from 0.194 to 0.247, indicating low genetic diversity in R. quadrifida. Analysis of molecular variance (AMOVA) revealed significantly greater variation within populations (62%) than among populations (38%). Genetic diversity was higher in the LIN-1 and LIN-2 populations, which employs a mixed reproductive system (clonal and seeds), than in populations dominated by vegetative reproduction. Both LIN populations, characterized by a mixed reproductive system, exhibited higher genetic diversity than the KOK, IVA-1 and IVA-2 populations, where vegetative reproduction predominated. Conclusions: These results underscore the necessity for priority conservation measures, including monitoring population size and age structure in populations with low levels of seed reproduction and disturbed age structure. Additional measures include supporting in situ and ex situ conservation, such as clonal collection, seed banks, and tissue cultures, as well as restricting the harvesting of medicinal raw materials.

Understanding the influence of individual attributes on demographic processes is a key objective of wildlife population studies. Capture-recapture and age data are commonly collected to investigate hypotheses about survival, reproduction, and viability. We present a novel age-structured Jolly-Seber model that incorporates age and capture-recapture data to provide comprehensive information on population dynamics, including abundance, age-dependent survival, recruitment, age structure, and population growth rates. We applied our model to a multi-year capture-recapture study of polar bears (Ursus maritimus) in western Hudson Bay, Canada (2012–2018), where management and conservation require a detailed understanding of how polar bears respond to climate change and other factors. In simulation studies, the age-structured Jolly-Seber model improved precision of survival, recruitment, and annual abundance estimates relative to standard Jolly-Seber models that omit age information. Furthermore, incorporating age information improved precision of population growth rates, increased power to detect trends in abundance, and allowed direct estimation of age-dependent survival and changes in annual age structure. Our case study provided detailed evidence for senescence in polar bear survival. Median survival estimates were lower (<0.95) for individuals aged <5 years, remained high (>0.95) for individuals aged 7–22 years, and subsequently declined to near zero for individuals >30 years. We also detected cascading effects of large recruitment classes on population age structure, which created major shifts in age structure when these classes entered the population and then again when they reached prime breeding ages (10–15 years old). Overall, age-structured Jolly-Seber models provide a flexible means to investigate ecological and evolutionary processes that shape populations (e.g., via senescence, life expectancy, and lifetime reproductive success) while improving our ability to investigate population dynamics and forecast population changes from capture-recapture data.

Patterns of infection and prevalence result from complex interactions between hosts and parasites, the effects of which are likely to vary by species. We investigated the effects of age, sex and season on the likelihood of individual infection, and the effects of host population size, sex ratio and age structure on parasite prevalence. We capitalized on data from a long‐term study of yellow‐bellied marmots Marmota flaviventris potentially infected with fecal–orally transmitted intestinal parasites (Ascaris sp., Eimeria spp. and Entamoeba sp.), ectoparasitic fleas Thrassis stanfordi, and a flea‐ and louse‐transmitted blood parasite Trypanosoma lewisi. Patterns of individual‐ and group‐level infection varied widely by parasite. Yearlings were more likely to be infected with Tr. lewisi and Ascaris. Yearlings were also slightly more likely than adults to have Eimeria, but female yearlings had higher infection levels than female adults, while male yearlings had lower infection levels than male adults. Entamoeba infection decreased as the season progressed. Adults and males were more likely to be infected with Th. stanfordi. Ascaris prevalence increased with colony size. There were no significant relationships between colony size and prevalence of Entamoeba, Tr. lewisi, Eimeria or Thrassis. There was a small, but significant positive correlation between male‐biased sex ratio and prevalence of fleas. The host population's age structure affected the prevalence of infection of Ascaris and Eimeria. Overall intestinal parasite diversity increased with colony size. Taken together, our results show a great deal of variation in the likelihood of individual infection and patterns of parasite prevalence in marmots.

In the context of todays ageing population, this paper uses the connectedness network model proposed by Diebold and Yilmaz in 2014 to analyse the directionality and degree of interaction between the population ageing index, life expectancy, per capita gross domestic product, and per capita health expenditure from a systematic perspective for China; then, these results from China are compared with the United States. A number of new findings can be identified, as follows: (1) for China and the United States, economic growth may promote the growth of health expenditure and increased life expectancy may cause an increase in the ageing population; (2) China's population age structure has already led to some constraints on economic growth, whereas the United StatesUS's population age structure has had a weak impact on its economic growth; and (3) the ageing population structure for China has a net impact on per capita health expenditure, whereas no such net directional impact was found in the United States. These findings support the idea that policy synergies should be strengthened in the economic, social, and health fields in order to promote both the quality of life of the ageing population and the sustainable development of the economy.

1. IntroductionThe population pyramid is one of the most popular visual representations of data in demography. In its standard form it comprises two histograms rolled on their sides and placed back-to-back, with the youngest ages at the bottom of the diagram and the oldest at the top. Generally, the male population is placed on the left and the female population on the right. The populations of each age-sex group are shown either as absolute numbers or as a percentage of the whole population. As an example, Figure 1 presents a population pyramid for Australia at 31 December 2014.A population pyramid can be created in common spreadsheet or statistical software without much difficulty, and is easy to understand. It presents immediately digestible information on the age-sex structure of a population that would be less obvious in tabular form. This distribution is important for understanding the demand for the wide range of goods and services which vary by age and sex, such as baby products, childcare, education, housing for first home buyers, household appliances, recreational activities, aged care, and funeral services (Siegel 2002). Population age structure also affects government spending and taxation receipts (Australian Government 2015). A population pyramid additionally offers clues about a population's fertility history, mortality and migration, position in the demographic transition, and the likely influence of its age-sex structure on future demographic change. The shape of a population pyramid can hint at the economic or demographic role of the population in question, as might be apparent for a university town, a popular seaside retirement region, or an area with a communal establishment like a boarding school or prison. It can also be used to check for potential data problems, such as age heaping. Finally, population pyramids can also be quite entertaining, especially in dynamic form, as presented on some national statistical offices' and researchers' websites. Examples can be found* for Germany,* for Australia, and* for Moldova.Several variations on the standard pyramid have been created. Many involve disaggregating the bars into different categories of population, such as by marital status (e.g., Statistics Canada 2013), household living arrangement (e.g., van Imhoff and Keilman 1991), birthplace (e.g., Statistics Sweden 2009), educational attainment (e.g., Lutz, Cuaresma, and Sanderson 2008), labour force status (Statistics New Zealand 2015), ethnicity (e.g., Coleman 2010), and migrant status (e.g., Price 1998). Some display shadows on the bars of the pyramid where there is an excess number of one sex over another (e.g., Heenan 1965); others show age-sex structure with persons by age in one histogram and age-specific sex ratios in another (Haak 1942). Commonly, two or more population pyramids are overlaid on one another, often to compare age structure over time (e.g., The Economist 2011), to show the outcome of alternative future scenarios (e.g., Statistics Canada 2015), or to display probabilistic prediction intervals (e.g., Keilman, Pham, and Hetland 2002).However, population pyramids are not without their limitations. Because they display only the size of each age-sex group in the population, it is usually not possible to distinguish the relative contributions of different demographic processes to population age structure. For example, if there is an indentation at the young adult ages, is this more the result of a fertility decline two to three decades earlier or recent net out-migration? If age-specific populations at the upper end of the pyramid decline very rapidly with increasing age, is this just the result of mortality, or have past trends in births and migration also contributed?This paper presents a type of population pyramid that illustrates how births, deaths, and net migration have shaped a population's age structure. Termed the components-of-change pyramid, it is described and illustrated in section 2 following this introduction. …

Background: Fine particulate matter (PM2.5) pollution is one of the most critical environmental and public health problems in China, which has caused enormous disease burden, especially long-term PM2.5 exposure. Global climate change is another environmental challenge in the coming decades, which is also an essential factor affecting PM2.5 pollution. Moreover, China is embracing an aging population. However, little evidence exists evaluating the potential impact of climate change and population ageing on long-term PM2.5 exposure-related disease burden. This study aims to quantify the impact of climate and population changes on changes in the disease burden attributed to long-term PM2.5 exposure from 2015 to 2030 in mainland China. Methods: This modeling study investigated long-term PM2.5 exposure-related mortality across China based on PM2.5 projections under Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs) and population scenarios from the Shared Socioeconomic Pathways (SSPs). Three types of population projections in 2030 relative to 2015 were set up as follow: (i) population remained the same from 2015; (ii) the population size changed under SSPs but age structure remained same; (iii) both population size and age structure changed under SSPs. Global Exposure Mortality Model was adopted to estimate PM2.5-related premature deaths. Findings: Ambient PM2.5 concentrations showed a decrease from 2015 to 2030 under two climate and emission scenarios. Estimates of related premature mortality in 2030 declined compared with 2015 due to lower PM2.5 concentrations (RCP4.5: -16.8%; RCP8.5: -16.4%). If the age structure of population remained no change and the population size changed under SSPs, the premature mortality also showed a decrease ranging from -18.6% to -14.9%. When both population size and age structure changed under SSPs, the premature mortality would sharply increase by 35.7%-52.3% (with net increase of 666-977 thousand) in 2030. Interpretations: The PM2.5 pollution in 2030 under both RCP4.5 and RCP8.5 would slightly improve. However, the modest decrease due to air pollution improvement would be offset by population ageing. Funding Statement: None. Declaration of Interests: The authors declare that they have no conflicts of interests.