Population Division Research Articles

Demographic Factors as Predictors of Revolutionary Situations: Experience in Quantitative Analysis

Although there are plenty of quantitative cross-national analyses on the influence of population age structure on revolutionary risks, there are currently not enough studies that examine its impact on the risks of armed and unarmed revolutions taken separately. Assuming that the dependence of potential political destabilization on the median age will differ for armed and unarmed revolutions, we propose the following hypothesis. High median age and the level of a country’s economic development will negatively correlate with armed revolutions. A moderately young median age will have positive influence on the risks of non-violent rebellions, while the overall dependence of unarmed revolutions on median age will be slightly positive and curvilinear. Relying on materials from NAVCO 1.3 and the UN Population Division databases and by means of utilizing cross-tabulations, correlations and logistic regression, we analyze about 250 revolutionary episodes between 1950 and 2019. All of our hypotheses turn out to be supported. The higher the median age of the population — the less likely the occurrence will be of armed revolutionary instability. On the other hand, as the population ages, the risks of unarmed revolutionary actions first grow, but then decline.

Kenya’s ageing population: Current and future prospects

Introduction: By 2050, 1 in 6 people in the world will be aged over 65 while in 2019 seventeen countries globally reported that a fifth of their populations was geriatric. It is estimated that by 2030, Europe will be home to 24 percent of the world’s ageing population. Meantime, Japan has continued to take lead with the highest proportion of elderly persons. However, by 2050, Korea will surpass Japan. Geriatric population in developing countries is on a trajectory outpacing the developed countries. To confirm this trajectory, sub Saharan Africa is home to the youngest populations where Niger - with a median age of only 15.4 – leads among 17 countries globally. Study Objectives: This study aims to analyse Kenya’s population ageing with a view to presenting its growth since 1999 and projecting its future up to 2050. Study Data and Methods: The study uses data from the Kenya Population and Housing Censuses of 1999, 2009 and 2019. Multiple demographic analyses softwares are used, namely: US Census Bureau’s Population Analysis System (PAS); United Nations Population Division’s Software Package for Mortality Measurement (Mortpak) and Spectrum. Findings: Kenya’s population has grown by almost 20 million in the past two decades from 28.7 million in 1999 to 47.6 million in 2019. During the same period, the elderly population has grown from 3.3 percent to 3.94 percent. After stagnating between 1998 and 2008-09, Kenya’s fertility dropped rapidly from 4.6 births per woman in 2008-09 to 3.4 births per woman a decade later. The transition from youthful to aging population and therefore a shift in the population structure is expected as median age rises from 20 years in 2020 to 28 years by 2050 while total dependency ratio will drop from 75 percent to 48 percent during the same period. Rapid growth is projected in the aging population which is set to more than double from 1.87 million in 2019 to 4.77 million by 2050. Life expectancy will be higher among female geriatric population. By 2050, Kenya’s ageing population (60 and over) will be higher than that of children under five – 9.77 percent compared to 8.44 percent, respectively. Conclusion: Due to population momentum, Kenya’s population is set to grow by almost one million people annually between 2019 and 2050 while the elderly population is set to more than double during the same period. It is critical that considerations are made on expanding retirement age bands to allow the geriatric population to remain labour productive and contribute positively to economic growth. Meantime, the elderly population is important for enhancing social skills and cultural knowledge transfers at community level.

Equilibrium optimizer with divided population based on distance and its application in feature selection problems

Effective machine learning relies on feature selection (FS) to preprocess the data to search for the best feature subset among all feature combinations, which is a global optimization problem (GOPs). The equilibrium optimizer (EO) is a physical-based meta-heuristic that is promising in solving global optimization problems but still exhibits unbalanced exploration and exploitation; low convergence accuracy; and can easily fall into local optima. This paper proposes an equilibrium optimizer with divided population based on distance (DEO) to improve EO’s global optimization abilities and to use it to solve FS problems. First, we propose an adaptive population division strategy with beta distribution, which makes DEO divide populations by particles’ distance weights and dynamic adjustment of the number of particles in the population, facilitating the algorithm to achieve a balance between exploration and exploitation. Second, we add distance factor to the exploitation population update to control the step size, increasing convergence accuracy. Third, the exponential term in the EO algorithm is introduced into the exploration population update as a disturbance factor to enhance the ability to jump out of a local optimum. Finally, twenty benchmark functions are used to verify the effectiveness of the improved strategy. Numerical experiments based on CEC’17 and FS experiments based on 14 UCI datasets are conducted to validate DEO’s global optimization and feature selection capabilities, respectively. Experimental results demonstrate that the proposed DEO significantly outperforms seven state-of-the-art algorithms and five other modified algorithms in terms of the optimization-seeking accuracy and convergence speed. Additionally, DEO also obtains overall better fitness as well as shorter running time than the other seven algorithms in FS problems.

Modeling the Health and Economic Burden of Chronic Obstructive Pulmonary Disease in China From 2020 to 2039: A Simulation Study

ObjectivesDespite a growing prevalence of respiratory diseases in recent decades in China, limited evidence is available on the health and economic burden of chronic obstructive pulmonary disease (COPD). We estimated the 20-year health and economic burden of COPD in China from 2020 to 2039. MethodsWe created a probabilistic dynamic open-cohort Markov model of COPD for the Chinese population aged ≥40 years. Projections of population growth and urbanization rates were obtained from the United Nations Population Division. Other parameter inputs including smoking prevalence, COPD prevalence and severity distributions, disease-related costs, and utility weights were obtained from the most recent published literature. We modeled number of COPD patients, excess mortality due to COPD, exacerbations, COPD-attributable losses of quality-adjusted life-years, and direct and indirect COPD costs over the 20 years. ResultsThe number of COPD patients was projected to increase from 88.3 million in 2020 to 103.3 million in 2039. The projected total losses of quality-adjusted life-years and the excess mortality due to COPD were, respectively, estimated to be 253.6 million and 3.9 million over the 20 years. The projected 20-year total discounted direct and indirect costs of COPD were, respectively, $3.1 trillion and $360.5 billion. The projected health and economic burden was higher in males and urban areas. ConclusionsCOPD is projected to inflict a substantial burden to the society and the health care system in China. Effective strategies for prevention and early management of COPD are needed to mitigate the forthcoming disease burden.

Optimization of Load Sharing in Compressor Station Based on Improved Salp Swarm Algorithm

In long-distance gas transmission pipelines, there are many booster compressor stations consisting of parallel compressors that provide pressure for the delivery of natural gas. So, it is economically important to optimize the operation of the booster compressor station. The booster compressor station optimization problem is a typical mixed integer nonlinear programming (MINLP) problem, and solving it accurately and stably is a challenge. In this paper, we propose an improved salp swarm algorithm based on good point set, adaptive population division and adaptive inertia weight (GASSA) to solve this problem. In GASSA, three improvement strategies are utilized to enhance the global search capability of the algorithm and help the algorithm jump out of the local optimum. We also propose a constraint handling approach. By using semi-continuous variables, we directly describe the on or off state of the compressor instead of using auxiliary binary variables to reduce the number of variables and the difficulty of solving. The effectiveness of GASSA is firstly verified using eight standard benchmark functions, and the results show that GASSA has better performance than other selected algorithms. Then, GASSA is applied to optimize the booster compressor station load distribution model and compared with some well-known meta-heuristic algorithms. The results show that GASSA outperforms other algorithms in terms of accuracy and reliability.

A Q-Learning-Based Artificial Bee Colony Algorithm for Distributed Three-Stage Assembly Scheduling with Factory Eligibility and Setup Times

The assembly scheduling problem (ASP) and distributed assembly scheduling problem (DASP) have attracted much attention in recent years; however, the transportation stage is often neglected in previous works. Factory eligibility means that some products cannot be manufactured in all factories. Although it extensively exists in many real-life manufacturing processes, it is hardly considered. In this study, a distributed three-stage ASP with a DPm→1 layout, factory eligibility and setup times is studied, and a Q-learning-based artificial bee colony algorithm (QABC) is proposed to minimize total tardiness. To obtain high quality solutions, a Q-learning algorithm is implemented by using eight states based on population quality evaluation, eight actions defined by global search and neighborhood search, a new reward and an adaptive ε−greedy selection and applied to dynamically select the search operator; two employed bee swarms are obtained by population division, and an employed bee phase with an adaptive migration between them is added; a new scout phase based on a modified restart strategy is also presented. Extensive experiments are conducted. The computational results demonstrate that the new strategies of QABC are effective, and QABC is a competitive algorithm for the considered problem.

The incidence and prevalence of motor neurone disease in South Australia

Background Motor neurone disease (MND) is a neurodegenerative disease that leads to significant morbidity and mortality. The Global Burden of Disease (GBD) project estimated the MND all-age global prevalence is 4.5 (95% confidence interval (CI)=4.1–5.0) per 100,000 persons and the all-age incidence of 0.78 (95% CI = 0.71–0.86) per 100,000 person-years. Whether the prevalence and incidence of MND within South Australia using registry data is in keeping with these global estimates has not been studied. Objective To describe the prevalence and annual incidence rates (IRs) of MND in South Australia between 2017 and 2019. Methods A retrospective cohort study calculating the point prevalence of MND on 31 December 2017, 2018 and 2019 utilizing data from the Australasian Motor Neurone Disease Registry (AMNDR). The annual IRs between 2017 and 2019 were calculated using population data reported in the 2016 Australian census and age-standardized rates utilized the world population from the United Nations Population Division’s World Population Prospects. Results A total of 256 MND patients were identified, of whom 114 were alive on 31 December 2019. Based on the 2016 population of 1,676,653 persons, the estimated prevalence was 6.79 per 100,000 persons. The crude IR for the all-age South Australian population was 3.34 per 100,000 person-years (95% CI, 2.85–3.88). The estimated annual IRs based on those ≥20 yo were 4.98 (3.84–6.35), 3.68 (2.71–4.88), and 4.21 (3.17–5.49) per 100,000 person-years for 2017, 2018, and 2019, respectively. Conclusion The crude prevalence and incidence of MND in South Australia were considerably higher than global estimates. This may reflect higher rates of the disease or higher rates of case ascertainment compared to the GBD project.

Measuring potential interest in a postpartum contraceptive vaginal ring among breastfeeding women in India.

Access to safe and effective contraception for postpartum women is an important priority in India, where the unmet need for postpartum contraception is high. In this paper, we estimate the potential market size in India for the progesterone vaginal ring (PVR), a novel user-controlled contraceptive method that offers additional contraceptive choice for lactating women. We integrated results of a one-year phase-3 multicenter clinical trial for the PVR conducted in India with an analysis of the National Family Health Survey (2015-16) and 2019 United Nations Population Division data to generate three estimates of potential market size for the PVR among postpartum breastfeeding women in India. We estimate the potential market size for the PVR ranges from a low estimate of 543,262 women to a high estimate of 1.3 million women, with a separate intermediate estimate of 737,460 women. Our analysis indicates the PVR could play an important role in decreasing unmet need among postpartum women in India, thereby reducing risks to mothers and children associated with short birth intervals, helping to prevent unintended pregnancies, and helping to address access-related issues heightened by the COVID-19 pandemic.

Population Dynamics in Russia in the Context of Global Trends

—The article examines the current demographic trends in Russia as compared to population changes in the world and its major regions based on data from the Russian Federal State Statistics Service (Rosstat), Eurostat, and the UN Population Division. It is shown that in terms of a number of characteristics of population reproduction—low fertility, ageing population structure, natural population decline—Russia is quite similar to the developed countries group. However, Russia is behind many countries in reducing the mortality rate of the middle-aged and older population, especially in men, and, correspondingly, in life expectancy for all age groups, which results in a noticeable increase in natural population decline and in deformation of the sex structure of the population. The specifics of the age structure of the Russian population that have been formed by a number of demographic waves are such that changes in the number of births and in age group sizes come in waves; this trend will continue in the coming decades. The article also analyzes excess mortality in Russia during the COVID-19 pandemic in comparison with similar data for the European Union (EU-27) and compares healthy life expectancy estimates for Russia, the entire world, individual countries, and different groups of countries by income.

Cancer mortality and predictions for 2022 in selected Australasian countries, Russia, and Ukraine with a focus on colorectal cancer.

We aimed at predicting cancer mortality rates for the current year for the Russian Federation, Ukraine, Israel, Hong Kong SAR, Japan, Korea, and Australia, with a focus on colorectal cancer. We retrieved official death certification and population data from the WHO and the United Nations Population Division databases. We analyzed mortality for all cancers combined and for 10 major cancer sites from 1970 to 2019, or the latest available year. We predicted numbers of deaths and age-standardized mortality rates for 2022 using Poisson joinpoint regression models. We estimated the number of averted deaths over the period 1994-2022 because of the decline in mortality rates. Total cancer mortality declined in all countries and both sexes. Russia had the highest total cancer predicted rates for 2022: 156.4/100 000 (world standard) in men and 81.4 in women; the lowest rates were reported in Israeli men (90.6/100 000) and Korean women (44.5/100 000). Between 1994 and 2022, a total of 1 487 000 deaths were estimated to be avoided in Russia, 502 000 in Ukraine, 58 000 in Israel, 102 000 in Hong Kong SAR, 1 020 000 in Japan, 533 000 in the Republic of Korea, and 263 000 in Australia. Colorectal cancer mortality trends were downward for the last decades with favorable predictions for 2022 in both sexes. In the countries considered, predicted downward trends started later and were less marked than those in the European Union and the USA. Despite overall favorable predictions, colorectal cancer remains one of the major causes of cancer mortality.

International Migration Drivers: Economic, Environmental, Social, and Political Effects

This paper evaluates the recent trends in international migration and different viewpoints (arguments and counterarguments) on global population movement and examines the impacts of the social, economic, ecological, and political determinants of regional and international migration. The paper aims to analyse and compare the causal relationships between international migration, on the one hand, and economic, ecological, and socio-politic dimensions of EU countries’ development, on the other. The authors consider the impact power of the above-mentioned dimensions on the long-term net migration for the potential candidates to access the EU. First, it identifies and justifies the object of research as the EU countries and the potential EU candidates. Second, the article provides a short literature review as the authors highlight that the EU countries had the highest share of all world migrants, according to the report of the U.N. Population Division. Third, it provides the background of materials collection and methods of the study of the analyses of the panel data for 2000–2018 using the FMOLS and DOLS. Fourth, it presents the results of the study having analysed the different concepts and theories, the authors single out the core economic, ecological, and socio-politic determinants of international migration: wages, unemployment rate, income inequality (measured by the Gini coefficient), corruption, and political stability (measured by World Government Indicators), CO2 emissions and material footprint per capita (measured by Sustainable Development Index). The discussion and conclusion section summarizes the findings of the research and evaluates the structural similarities and differences among the EU countries and potential candidates and if these similarities (or differences) cause them to respond similarly to the economic conditions and changes.

The health-adjusted dependency ratio as a new global measure of the burden of ageing: a population-based study

The old-age dependency ratio (OADR), which is the ratio of older people (aged ≥65 years) to working age people (aged 20-64 years), is the most common way to assess and compare the burden of population ageing in different countries. However, the relationship between chronological age and dependency varies widely across countries. We therefore present the health-adjusted dependency ratio (HADR), a new measure of ageing burden based on the ageing-related health of the adult population. In this population-based study we used health data for diseases and injuries for 2017 from the Global Burden of Disease project and population data for 2017 from the UN's Population Division to identify the number of adults (aged >20 years) in each country who have the same or higher ageing-related disease burden as the global average 65-year-old. We then calculated the HADR as the ratio of adults who were less healthy than the average 65-year-old (dependent population) to those in better health (supporting population) and compared the HADR with the OADR for 188 countries. We also used cross-sectional, bivariate regression analysis to investigate whether the HADR is a more powerful predictor of changes in per capita health-care expenditure than the OADR as a measure of predictive validity. Many demographically younger populations have an earlier onset of ageing-related disease, and many demographically older populations have a later onset. For instance, Pakistan has an OADR of 0·09 and an HADR of 0·19, and France has an OADR of 0·35 and an HADR of 0·13. Relative to the OADR, the HADR suggests that Asia, western Europe, and North America have a lower ageing burden, whereas central Asia, southern Asia, and Africa have a greater burden. While Japan and countries in western Europe have the highest OADR, Russia, Papua New Guinea, and countries in southeast Europe have the highest HADR. Relative to the OADR, the HADR suggests that there is much less variation in the burden of ageing across countries than has previously been assumed. HADR was also more closely associated with growth in health spending than the OADR. A 0·1 increase in the HADR was associated with a 2·9 percentage points larger growth rate in per capita spending (p=0·0001), and a 0·1-point increase in the OADR was associated with a 1·8 percentage point larger growth rate. The OADR probably overestimates the burden of population ageing in many demographically older countries and underestimates the ageing burden in many demographically younger countries, which implies that the challenges associated with ageing are more universal than previously thought, and that the world cannot easily be divided in a young and an old groups of nations. None.

Youth Cohort Size, Structural Socioeconomic Conditions, and Youth Protest Behavior in Democratic Societies (1995–2014)

Conventional literature associates large youth cohort size (YCS) with increased risk of political violence in countries with such demographic profiles. Key questions which remain unanswered, however, are whether YCS is also associated with young people’s proclivities toward more peaceful forms of protests, and whether structural socioeconomic conditions influence such a relationship? Using multilevel binary logistic regression techniques on pooled individual level data for 51 democratic countries purposively sampled from World Values Survey Waves 3 to 6, and country level data from World Bank, and UN Population Division, I show that YCS demonstrates a positive relationship with young people’s participation in peaceful demonstrations. This relationship is, however, moderated by structural factors such as education and unemployment, which end up reducing young people’s likelihood of participation. I argue that resource limitation, as predicted by the Civic Voluntarism Model, better explains the relationship between YCS and individual youth protest behavior in democratic societies, more than socioeconomic grievance, as suggested by grievance theory. An important implication of this finding is that participation in elite-challenging behaviors such as peaceful protests, can be expected to be more common among young people in affluent democratic societies, than their peers elsewhere in the democratic world.

A Geographical Analysis of Population Distribution in Said Sadiq District

The geographic distribution of population is an important topic in geography and constitutes an important topic in population researches because through it, the facts about the inhabiting of the population and its relations to the location and the environment are shown. For that reason, an attempt is made in this paper to demonstrate the facts of the population distribution onto the location studied in this paper because population distribution is the outcome of the interactions between the population with all the environmental factors that exist in the place where they have dwelt. The divisions can also make some patterns that can be analyzed and explained. In the research, despite using numeric data and information about the population, an attempt is made to use systematic techniques for geo-information and specific statistics relation to the population division to, through the results, show a suitable solution to the (GIS) problems related to the distribution and the imbalance of the distribution of the population. The research includes four main topics (the distribution of the location and the number population, The volume of the population division, The environmental division of the population, and the sorts of the population division) and it is noticed that there is an imbalance in the location, mass, and environmental distribution and the types of the distributions can be a good evidence for such imbalances.

Techno-economic evaluation and parametric study of generating green hydrogen from waste heat recovery of efficient solid oxide fuel cell

According to the United Nations Population Division, the world population is expanding, and this rise has been more pronounced in the last century. As an instance, the population in 2020 is almost two times more than the population in 1970. As a result, the population will have increased by around 4.1 billion people in 50 years (according to Worldometers.info). Energy may be considered to be one of the most fundamental prerequisites for human survival. This research presents a newly projected energy system based on FC and RR-ORC and PEME for green generation on hydrogen and power. The system actually has two power blocks and one hydrogen generation unit. The system has three subsystems that are modeled incomplete form based on the thermodynamic and economic model. The effect of strategic proposal variables are foreseen on the LCOE, overall cost, and exergetic efficiency. Also, the variation of hydrogen production and net power output is predicted. The results show that current density, as well as fuel and air utilization factor, has a crucial effect on the system performance while the parameters of the bottoming cycle as ORC and pinch point variables have little effect on cycle performance; on the other hand, they affect the downstream cycles much, like hydrogen production system. Increasing current density has the highest effect on the system performance by an 8% reduction in exergy efficiency.

Does cohort size matter? Assessing the effect of youth cohort size and peer influence on young people’s electoral participation

ABSTRACT Do the relative numbers of young people in the adult population affect their extent of participation in electoral politics? The answer to this question remains elusive in both the theoretical and empirical literature on youth political participation. In this study, we test the hypothesis that young people’s cohort size has a significant effect on their electoral participation. Using individual level data from the World Values Survey and country level data from the United Nations Population Division, we ran a series of multinomial logistic regression analyses with 29 democratic countries. The findings show that youth cohort size exerts a negative effect on young people’s electoral participation. The study finds this effect to be stronger for young people whose main source of information are their peers. The results of this study represent a major step towards improving our understanding of the effect of cohort size on cohort political behaviour; a topic so far neglected within the literature on youth political participation.

Effective Heuristic Techniques for Combined Robust Clustering Problem

Clustering is one of the most important problems in the fields of data mining, machine learning, and biological population division, etc. Moreover, robust variant for [Formula: see text]-means problem, which includes [Formula: see text]-means with penalties and [Formula: see text]-means with outliers, is also an active research branch. Most of these problems are NP-hard even the most classical problem, [Formula: see text]-means problem. For the NP-hard problems, the heuristic algorithm is a powerful method. When the quality of the output can be guaranteed, the algorithm is called an approximation algorithm. In this paper, combining two types of robust settings, we consider [Formula: see text]-means problem with penalties and outliers ([Formula: see text]-MPO). In the [Formula: see text]-MPO, we are given an [Formula: see text]-point set [Formula: see text], a penalty cost [Formula: see text] for each [Formula: see text], an integer [Formula: see text], and an integer [Formula: see text]. The target is to find a center subset [Formula: see text] with [Formula: see text], a penalty subset [Formula: see text] and an outlier subset [Formula: see text] with [Formula: see text], such that the sum of the total costs, including the connection cost and the penalty cost, is minimized. We offer an approximation algorithm using a heuristic local search scheme. Based on a single-swap manipulation, we obtain [Formula: see text]-approximation algorithm.

Brand inequity in access to COVID-19 vaccines

Brand inequity in access to COVID-19 vaccines

The Influx of War Refugees from Ukraine – Recommendations for Poland Based on Turkey’s Experiences

Goal – the presentation of analysis results regarding the numerical comparison of migration crises caused by refugee displacements from Syria and Ukraine and the identification of challenges faced by Poland based on Turkey’s experiences related to the mass influx of refugees. Research methodology – the examination of Poland’s and Turkey’s official state documents, a review of articles and existing studies, the analysis of statistical data on the flows of persons from the following databases: the UNHCR, the UN Population Division, data from the Polish Chancellery of the Prime Minister and the Office for Foreigners. The research methods used also include synthesis and inference. Score/results – although the Syrian and Ukrainian migration crises show various differences, Poland can certainly draw on Turkey’s proven tools and avoid solutions having hindered integration and contributed to the exclusion of Syrian refugees. However, Turkey’s and Poland’s experiences represent evidence for other countries that it is necessary to have a clearly defined migration policy in place. Originality/value – the originality of the article lies in the comparison of the two largest migration crises of recent years and an attempt to identify challenges faced by Poland in connection with the influx of war refugees and possible solutions based on Turkey’s experiences. In addition, the subject has significant research potential due to the imminent economic crisis in Ukraine, which may trigger another wave of migration.

Droop Control Optimization Strategy for Parallel Inverters in a Microgrid Based on an Improved Population Division Fruit Fly Algorithm

When the microgrid topology changes, the traditional droop control strategy affects the dynamic performance and steady-state accuracy of the inverter. To this end, this paper is based on an improved population division fruit fly algorithm. An optimization strategy for grid-connected inverter droop control is proposed in this paper, and then, the PI parameters of microgrid droop control are optimized in real time. This strategy divides the fruit fly population into three zones according to the inverter output and then automatically updates the multistrategy mode according to the difference in fruit fly performance in each zone. Among them, in zone I, a local fine search is conducted to ensure that the population does not degenerate; in zone II, adaptive adjustment is performed, ensuring the diversity and convergence of the algorithm; and in zone III, fruit flies are guided to accelerate convergence. The effectiveness and feasibility of this strategy is verified by this article according to simulation experiments and actual application cases. The results show that the proposed control strategy can make the inverter output follow the changes in the system for adaptive adjustment. The inverter response speed is increased 40-fold, and the steady-state error is reduced by 4.3%.