Effects Of Age Structure Research Articles

Cross-National Trends in Adolescents Psychological and Somatic Complaints Before and After the Onset of COVID-19 Pandemic

PurposeBuilding on research suggesting that the COVID-19 pandemic may have led to an exacerbation of deteriorating trends in mental health among adolescents, this paper examined trends in adolescents' psychological and somatic complaints across 35 countries from 2010 to 2022, and tested trends in sociodemographic inequalities in these outcomes between 2018 and 2022. MethodsUsing data from 792,606 adolescents from 35 countries (51% girls; mean age = 13.5; standard deviation 1.6) across four Health Behaviour in School-aged Children surveys (2010, 2014, 2018, 2022), hierarchical multilevel models estimated cross-national trends in adolescent psychological and somatic complaints. We tested whether observed values in 2022 were in line with predicted values based on 2010–2018 linear trends. Finally, moderation effects of age, family affluence, and family structures on the outcomes were tested (2018–2022). ResultsBoth girls and boys showed substantially higher levels of psychological complaints in 2022 compared with the predicted values. For somatic complaints, higher levels than predicted in 2022 were observed only in girls. Moderation analyses revealed an increase from 2018 to 2022 in age gaps and a narrowing in the socioeconomic gap for both outcomes. Also, there was a widening gap between adolescents living with 2 parents and those living in a single parent household in 2022 compared to 2018. DiscussionCross-national increases in adolescent psychological and somatic complaints were higher than expected in 2022, based on previous trends. Magnitudes of change varied across different sociodemographics groups, with implications for pre-existing mental health inequalities.

Decomposition of official population projections in Brazil

Brazil’s population has continually changed over time. However, the effects of each demographic component on official population projections are still unclear. In this research, we replicate the Population Projections Revision 2018 of the Brazilian Institute of Geography and Statistics using a projection matrix model and the cohort-component method by sex, age and geographic regions. Thereafter, we established four alternative scenarios to decompose the official benchmark scenario into four demographic effects (fertility, age structure, mortality, and migration) and one residual effect. The results reveal that fertility and age structure effects have been the main drivers of the population dynamics between 2010 and 2060. On the one hand, the negative effect of fertility below replacement level has been mostly offset by the still positive effect of the age structure, even across regions in the country. On the other hand, age structure effect has been decreasing over time. By 2048, the effects of age structure, mortality and migration will no longer counterbalance fertility effects, resulting in a population decline.

The Effect of Age Structure and Two Delays on the Predator-prey Model with Prey Fear Cost and Variable Predator Search Speed

The Effect of Age Structure and Two Delays on the Predator-prey Model with Prey Fear Cost and Variable Predator Search Speed

Profitability in Public Housing Companies: A Longitudinal and Regional Analysis Using Swedish Panel Data

Public Housing Companies (PHCs) play an important role in the Swedish housing market, with approximately 300 companies managing circa 802,000 dwellings. The public housing sector thereby represents almost 20 percent of the total housing stock in Sweden and half of the apartments that are available for rental. The purpose of this paper is to analyze the most important factors behind the profitability in Swedish PHCs between 2010 and 2019. The effects of internal growth, age, and capital structure in the PHCs are analyzed together with the effect of the growth of the local market, as well as local rent levels. Financial information for circa 300 PHCs in Sweden was gathered from annual reports published between 2010 to 2019. The financial information was analyzed using panel data analysis methods with several explanatory variables to explain the financial performance of the PHCs. The results from the analysis indicate a highly significant and positive relationship between the annual change in population, age, and profitability in the PHC. A highly significant and negative relationship was found between the PHC internal growth, capital structure, and profitability. The results showed no significant relationship between changes in income, rent levels, and profitability in Swedish PHC.

The burden of disease and economic growth: The nonlinear effect of population age structure

This study aims to detangle the impact of health on economic growth as empirical evidence shows a mixture of findings. We use data on the Burden of Disease (BoD) from the Institute of Health Metric Evaluation (IHME) to measure health capital and the economic data of 87 countries from 1990 to 2018. Using panel threshold regression, this study shows that the old dependency ratio is a good measure of the threshold variable, which divides the country groups into four. The BoD, whether it comes from communicable diseases (CD), non-communicable diseases (NCD), or injuries, has a negative impact on economic growth. However, the negative relation is somewhat diminished as the population gets older, demonstrating that the BoD's impact on economic growth is less pronounced for the older population than the younger population.

Litter decomposition and nutrient release are faster under secondary forests than under Chinese fir plantations with forest development

In terrestrial ecosystems, leaf litter is the main source of nutrients returning to the soil. Understanding how litter decomposition responds to stand age is critical for improving predictions of the effects of forest age structure on nutrient availability and cycling in ecosystems. However, the changes in this critical process with stand age remain poorly understood due to the complexity and diversity of litter decomposition patterns and drivers among different stand ages. In this study, we examined the effects of stand age on litter decomposition with two well-replicated age sequences of naturally occurring secondary forests and Chinese fir (Cunninghamia lanceolata) plantations in southern China. Our results showed that the litter decomposition rates in the secondary forests were significantly higher than those in the Chinese fir plantations of the same age, except for 40-year-old forests. The litter decomposition rate of the Chinese fir initially increased and then decreased with stand age, while that of secondary forests gradually decreased. The results of a structural equation model indicated that stand age, litter quality and microbial community were the primary factors driving nutrient litter loss. Overall, these findings are helpful for understanding the effects of stand age on the litter decomposition process and nutrient cycling in plantation and secondary forest ecosystems.

Factors Affecting Firm Performance: DER as Intervening Variable

This study aims to analyze the effect of tangibility, growth opportunity, firm age and capital structure on firm performance with capital structure as intervening variables in manufacturing companies in the sub-sector of goods and consumption listed on the Indonesia Stock Exchange in 2017-2021. The sampling technique in this study uses the purposive sampling method. The research method used was quantitative research with a sample of 14 Food and Beverage companies listed on the Indonesia Stock Exchange. The analysis used is the path analysis using SPSS version 23. The results showed that growth opportunities and firm age had an effect on company performance. While tangibility and capital structure have no effect on company performance. Capital structure cannot mediate the relationship between tangibility and firm performance. Capital structure cannot mediate the relationship between growth opportunity and firm performance. Capital structure cannot mediate the relationship between Firm Age and Firm Performance.

Growing older and growing apart? Population age structure and trade

PurposeThis paper explores the empirical relationship between population age structure and bilateral trade.Design/methodology/approachThe author includes age structure in both log and Poisson pseudo-maximum likelihood (PPML) formulations of the gravity equation of trade. The author studies relative age effects, using differences in the demographic structure of each country-pair.FindingsThe author finds that a relatively larger share of population in working age increases bilateral exports. This is robust to various estimation models, as well as to changes in the method of specifying the demographic controls. Old-age shares have a negative, but less robustly estimated impact on trade. Estimating instead the balance of trade between trading partners produces similar results, with positive effects of age structure peaking later in working life.Practical implicationsGlobal populations are poised to undergo a massive transition. Trade a crucial way that the demographic deficits of one country may be offset by the dividends of another as comparative advantages shift along with the size and strength of their underlying workforce.Originality/valueThe author’s work is among the first to quantify the effect of relative age structure between two countries and their bilateral trade flows. Focusing on the aggregate flows, relative age shares and PPML estimates of the trade relationship, this paper provides the most comprehensive picture to date on how age structure affects trade.

Investigating the Relationship between Population Structure and Poverty

Introduction: Poverty reduction is one of the important macroeconomic goals of any country, but achieving this important issue requires examining the factors affecting it. Changing the age structure of the population is one of the effective factors in reducing poverty in countries. Therefore, governments can make the most of their population, given the capacity of countries and providing the necessary conditions, and as a result, achieve high growth and development among countries. The purpose of this study is to investigate and analyze the effect of population age structure on poverty in Iran. Method: The method of this research is analytical-descriptive. First, theoretical topics and experimental studies and research data are collected, and the appropriate analysis model is selected. Then, with the Generalized Method of Momen for Iran since 1975 until 2017, the desired research models have been estimated, and finally, using statistical and econometric inferences, the research results have been studied. Findings: In general, according to the results, it can be concluded that the dependent population of the child and years of schooling have a negative and significant relationship with the dependent variable, the elderly dependent population has a negative and significant relationship with the dependent variable and also the percentage of trade in GDP and Physical capital inventories have a negative relationship with the dependent variable. Discussion: In this study, the years of schooling, the percentage of trade in GDP, as well as capital stock are based on a coefficient that agrees with the theory. The positive effect of the elderly population on poverty reduction indicates the existence of high savings in old age. Paying attention to the growth of highly educated employees as well as employing specialized personnel increases the productivity of the labor force and also creates the possibility of creating new production methods that have significant effects on poverty reduction.

Effects of population age structure on parenteral antimicrobial use estimations

Antimicrobial use (AMU) is conventionally reported as unadjusted defined daily doses (DDDs) or population-adjusted DDDs per 1000 inhabitants per day (DID). DID is frequently used to monitor national AMU trends, this metric does not intrinsically take temporal changes in population age structure into account. We examined the effects of population age structure on DID estimates of parenteral AMU in Japan, and predicted future trends in DDDs based on population projections. Parenteral AMU data from 2013 to 2018 were acquired from a national claims database. We assessed temporal trends in parenteral AMU by age group (children aged < 15 years, working-age persons aged 15–64 years, and older persons aged ≥ 65 years) using both DID and DDDs. In addition, we modeled DDD predictions based on age-specific population projections from 2019 to 2030. DID values for older persons were 8.08–10.15 times and 5.43–5.63 times higher than in children and working-age persons, respectively. DID was stable, but DDDs increased in older persons. The prediction models showed that DDDs will continue to increase until 2030 if DID remains steady or decreases. DID estimates were skewed by the older population. More rigorous antimicrobial stewardship efforts targeting geriatric care are needed to counter the aging-associated increase in AMU.

Population age structure, asset price, and financial stability

AbstractBased on the data collected from 32 countries, the empirical test is conducted by constructing the financial stability index FSCI (Financial Stability Conditions Index). Results found that the changes in population age structure will affect financial stability, but the effects of different age structures are inconsistent, and there is country heterogeneity. The laborers are the main force in financial markets and significantly contribute to financial stability. The elderly population is also conducive to long‐term financial stability due to their low‐risk attitude. Results also confirmed that a change in population age structure affects household asset allocation prices.

Using mechanistic model-based inference to understand and project epidemic dynamics with time-varying contact and vaccination rates

Epidemiological models range in complexity from relatively simple statistical models that make minimal assumptions about the variables driving epidemic dynamics to more mechanistic models that include effects such as vaccine-derived and infection-derived immunity, population structure and heterogeneity. The former are often fitted to data in real-time and used for short-term forecasting, while the latter are more suitable for comparing longer-term scenarios under differing assumptions about control measures or other factors. Here, we present a mechanistic model of intermediate complexity that can be fitted to data in real-time but is also suitable for investigating longer-term dynamics. Our approach provides a bridge between primarily empirical approaches to forecasting and assumption-driven scenario models. The model was developed as a policy advice tool for New Zealand’s 2021 outbreak of the Delta variant of SARS-CoV-2 and includes the effects of age structure, non-pharmaceutical interventions, and the ongoing vaccine rollout occurring during the time period studied. We use an approximate Bayesian computation approach to infer the time-varying transmission coefficient from real-time data on reported cases. We then compare projections of the model with future, out-of-sample data. We find that this approach produces a good fit with in-sample data and reasonable forward projections given the inherent limitations of predicting epidemic dynamics during periods of rapidly changing policy and behaviour. Results from the model helped inform the New Zealand Government’s policy response throughout the outbreak.

Host age structure reshapes parasite symbiosis: collaboration begets pathogens, competition begets virulent mutualists

BackgroundSymbiotic relationships are ubiquitous in the biosphere. Inter-species symbiosis is impacted by intra-specific distinctions, in particular, those defined by the age structure of a population. Older individuals compete with younger individuals for resources despite being less likely to reproduce, diminishing the fitness of the population. Conversely, however, older individuals can support the reproduction of younger individuals, increasing the population fitness. Parasitic relationships are commonly age structured, typically, more adversely affecting older hosts.ResultsWe employ mathematical modeling to explore the differential effects of collaborative or competitive host age structures on host-parasite relationships. A classical epidemiological compartment model is constructed with three disease states: susceptible, infected, and recovered. Each of these three states is partitioned into two compartments representing young, potentially reproductive, and old, post-reproductive, hosts, yielding 6 compartments in total. In order to describe competition and collaboration between old and young compartments, we model the reproductive success to depend on the fraction of young individuals in the population. Collaborative populations with relatively greater numbers of post-reproductive hosts enjoy greater reproductive success whereas in purely competitive populations, increasing the post-reproductive subpopulation reduces reproductive success.ConclusionsWe demonstrate that, in collaborative host populations, pathogens strictly impacting older, post-reproductive individuals can reduce population fitness even more than pathogens that directly impact younger, potentially reproductive individuals. In purely competitive populations, the reverse is observed, and we demonstrate that endemic, virulent pathogens can oxymoronically form a mutualistic relationship with the host, increasing the fitness of the host population. Applications to endangered species conservation and invasive species containment are discussed.

Epidemic time series similarity is related to geographic distance and age structure.

ObjectiveMore similar locations may have similar infectious disease dynamics. There is clear overlap in putative causes for epidemic similarity, such as geographic distance, age structure, and population size. We compare the effects of these potential drivers on epidemic similarity compared to a baseline assumption that differences in the basic reproductive number (R0) will translate to differences in epidemic trajectories.MethodsUsing COVID-19 case counts from United States counties, we explore the importance of geographic distance, population size differences, and age structure dissimilarity on resulting epidemic similarity.ResultsWe find clear effects of geographic space, age structure, population size, and R0 on epidemic similarity, but notably the effect of age structure was stronger than the baseline assumption that differences in R0 would be most related to epidemic similarity.ConclusionsTogether, this highlights the role of spatial and demographic processes on SARS-CoV2 epidemics in the United States.

The impact of age structure and vaccine prioritization on COVID-19 in West Africa.

The ongoing COVID-19 pandemic has been a major global health challenge since its emergence in 2019. Contrary to early predictions that sub-Saharan Africa (SSA) would bear a disproportionate share of the burden of COVID-19 due to the region's vulnerability to other infectious diseases, weak healthcare systems, and socioeconomic conditions, the pandemic's effects in SSA have been very mild in comparison to other regions. Interestingly, the number of cases, hospitalizations, and disease-induced deaths in SSA remain low, despite the loose implementation of non-pharmaceutical interventions (NPIs) and the low availability and administration of vaccines. Possible explanations for this low burden include epidemiological disparities, under-reporting (due to limited testing), climatic factors, population structure, and government policy initiatives. In this study, we formulate a model framework consisting of a basic model (in which only susceptible individuals are vaccinated), a vaccine-structured model, and a hybrid vaccine-age-structured model to assess the dynamics of COVID-19 in West Africa (WA). The framework is trained with a portion of the confirmed daily COVID-19 case data for 16 West African countries, validated with the remaining portion of the data, and used to (i) assess the effect of age structure on the incidence of COVID-19 in WA, (ii) evaluate the impact of vaccination and vaccine prioritization based on age brackets on the burden of COVID-19 in the sub-region, and (iii) explore plausible reasons for the low burden of COVID-19 in WA compared to other parts of the world. Calibration of the model parameters and global sensitivity analysis show that asymptomatic youths are the primary drivers of the pandemic in WA. Also, the basic and control reproduction numbers of the hybrid vaccine-age-structured model are smaller than those of the other two models indicating that the disease burden is overestimated in the models which do not account for age-structure. This result is also confirmed through the vaccine-derived herd immunity thresholds. In particular, a comprehensive analysis of the basic (vaccine-structured) model reveals that if 84%(73%) of the West African populace is fully immunized with the vaccines authorized for use in WA, vaccine-derived herd immunity can be achieved. This herd immunity threshold is lower (68%) for the hybrid model. Also, all three thresholds are lower (60% for the basic model, 51% for the vaccine-structured model, and 48% for the hybrid model) if vaccines of higher efficacies (e.g., the Pfizer or Moderna vaccine) are prioritized, and higher if vaccines of lower efficacy are prioritized. Simulations of the models show that controlling the COVID-19 pandemic in WA (by reducing transmission) requires a proactive approach, including prioritizing vaccination of more youths or vaccination of more youths and elderly simultaneously. Moreover, complementing vaccination with a higher level of mask compliance will improve the prospects of containing the pandemic. Additionally, simulations of the model predict another COVID-19 wave (with a smaller peak size compared to the Omicron wave) by mid-July 2022. Furthermore, the emergence of a more transmissible variant or easing the existing measures that are effective in reducing transmission will result in more devastating COVID-19 waves in the future. To conclude, accounting for age-structure is important in understanding why the burden of COVID-19 has been low in WA and sustaining the current vaccination level, complemented with the WHO recommended NPIs is critical in curbing the spread of the disease in WA.

50 years of spring wild turkey harvest in Indiana, 1970–2019

AbstractFifty years (1970–2019) of spring hunting of eastern wild turkeys (Meleagris gallopavo silvestris) has occurred in Indiana, spanning turkey population restoration in the state. A conservative spring harvest structure of a single bird bag, relatively short seasons with a late April opening date was in place for all spring seasons. Herein, we examined trends in state‐wide harvest parameters over time and modeled annual harvest at the county level to examine drivers of harvest. Statewide, harvests, hunter numbers, success rates, and effort initially increased as restoration progressed, with increases in areas open to hunting and days of hunting opportunity. Spring harvests peaked during 2006–2010 and declined 4.7% during 2015–2019. Hunter success peaked during 1998–2002 at 27 ± 0.7% (mean ± SE), then declined to 21 ± 0.6% during 2015–2019. After 1993, spring trips/hunter began to level off with 5 ± 0.46 trips/hunter during 2015–2019. The subadult portion of harvest grew during 1970–1974, stabilized at 30 ± 2.0% during 1976–95, and then declined to 17 ± 1.4% during 2015–2019. Two‐year old males comprised 49% ± 1.5% of the harvest during 1985–2009, then shifted during 2015–2019 to 41 ± 1.5% 2‐yr‐olds and 42 ± 2.8% males ≥3 yr of age. The conservative spring season structures maintained through the restoration era with restricted county fall seasons (1 bird bag either sex, 12‐day firearm initiated post‐restoration in 2005) likely buffered spring harvests from declining production in recent years. We used a 2‐step approach to model annual harvest at the county level. First, we fit a piecewise temporal model with 2 breakpoints to capture the underlying growth of post‐restoration harvest, and its changing slope over time. Second, we added explanatory covariates to the model to explore potential mechanisms for differences in harvest across space and time. Using a generalized linear mixed model, we included variables related to harvest age structure, landscape composition, and restoration effect. Harvests leveled off over time with the best harvest model showing geometric growth for the first 16 years of harvest, followed with moderate growth for 17–39 years of harvest, before leveling off after 40 years under a conservative season structure. The primary model drivers of annual harvest were the proportion of 2‐yr‐olds in the harvest, followed by the number of years between stocking and harvest and the number of turkeys released on the landscape, landscape edge density, and forest clumpiness. Our model results emphasized the importance of production, supported turkey restoration techniques, and demonstrated the suitability of landscapes with diverse land cover types. Ultimately, the availability of quality brood cover along with climatic shifts toward increased precipitation, will influence production trends critical to sustaining current turkey population levels. These changes will in turn, influence the level of 2‐yr‐old males in subsequent spring harvests, hunter success, and the future of the open‐permit structure, depending on the level of hunter demand.

Age structure affects population productivity in an exploited fish species

Long-term changes in the age and size structure of animal populations are well documented, yet their impacts on population productivity are poorly understood. Fishery exploitation can be a major driver of changes in population age-size structure because fisheries significantly increase mortality and often selectively remove larger and older fish. Climate change is another potential driver of shifts in the demographic structure of fish populations. Northeast Arctic (NEA) cod is the largest population of Atlantic cod (Gadus morhua) and one of the world's most important commercial fish stocks. This population has experienced considerable changes in population age-size structure over the past century, largely in response to fishing. In this study, we investigate whether changes in spawner age structure have affected population productivity in NEA cod, measured as recruits per spawning stock biomass, over the past 75 years. We find evidence that shifts in age structure toward younger spawners negatively affect population productivity, implying higher recruitment success when the spawning stock is composed of older individuals. The positive effect of an older spawning stock is likely linked to maternal effects and higher reproductive output of larger females. Our results indicate a threefold difference in productivity between the youngest and oldest spawning stock that has been observed since the 1950s. Further, our results suggest a positive effect of environmental temperature and a negative effect of intraspecific cannibalism by older juveniles on population productivity, which partly masked the effect of spawner age structure unless accounted for in the model. Collectively, these findings emphasize the importance of population age structure for the productivity of fish populations and suggest that harvest-induced demographic changes can have negative feedbacks for fisheries that lead to a younger spawning stock. Incorporating demographic data into harvest strategies could thus facilitate sustainable fishery management.

Searching for genetic evidence of demographic decline in an arctic seabird: beware of overlapping generations.

Genetic data are useful for detecting sudden population declines in species that are difficult to study in the field. Yet this indirect approach has its own drawbacks, including population structure, mutation patterns, and generation overlap. The ivory gull (Pagophila eburnea), a long-lived Arctic seabird, is currently suffering from rapid alteration of its primary habitat (i.e., sea ice), and dramatic climatic events affecting reproduction and recruitment. However, ivory gulls live in remote areas, and it is difficult to assess the population trend of the species across its distribution. Here we present complementary microsatellite- and SNP-based genetic analyses to test a recent bottleneck genetic signal in ivory gulls over a large portion of their distribution. With attention to the potential effects of population structure, mutation patterns, and sample size, we found no significant signatures of population decline worldwide. At a finer scale, we found a significant bottleneck signal at one location in Canada. These results were compared with predictions from simulations showing how generation time and generation overlap can delay and reduce the bottleneck microsatellite heterozygosity excess signal. The consistency of the results obtained with independent methods strongly indicates that the species shows no genetic evidence of an overall decline in population size. However, drawing conclusions related to the species' population trends will require a better understanding of the effect of age structure in long-lived species. In addition, estimates of the effective global population size of ivory gulls were surprisingly low (~1000 ind.), suggesting that the evolutionary potential of the species is not assured.

COVID-19 in Hong Kong: Policies and community actions mitigate the effects of age structure and population density

Despite the various socio-demographic vulnerabilities of Hong Kong to the COVID-19 pandemic, the city has successfully managed four waves of local outbreaks, as shown by its comparatively low numbers of confirmed cases and deaths. In this paper, we identify and differentiate the unique characteristics of Hong Kong’s COVID-19 outbreaks from those of other territories, and analyse the factors that shaped these characteristics. In particular, we examine four local demographic factors – older age structure, high population density, poor housing conditions and a large migrant population – which, according to current scientific evidence, would likely indicate that the city faces a relatively high risk of the significant spread of COVID-19. We analyse and explain how multiple policies related to border controls, social distancing, testing and tracing, partial lockdowns and housing management, as well as sustained community actions, helped to mitigate the effects of these significant disadvantages.

Accounting for forest management in the estimation of forest carbon balance using the dynamic vegetation model LPJ-GUESS (v4.0, r9710): implementation and evaluation of simulations for Europe

Abstract. Global forests are the main component of the land carbon sink, which acts as a partial buffer to CO2 emissions into the atmosphere. Dynamic vegetation models offer an approach to projecting the development of forest carbon sink capacity in a future climate. Forest management capabilities are important to include in dynamic vegetation models to account for the effects of age and species structure and wood harvest on carbon stocks and carbon storage potential. This article describes the implementation of a forest management module containing even-age and clear-cut and uneven-age and continuous-cover management alternatives in the dynamic vegetation model LPJ-GUESS. Different age and species structure initialisation strategies and harvest alternatives are introduced. The model is applied at stand and European scales. Different management alternatives are applied in simulations of European beech (Fagus sylvaticus) and Norway spruce (Picea abies) even-aged monoculture stands in central Europe and evaluated against above-ground standing stem volume and harvested volume data from long-term experimental plots. At the European scale, an automated thinning and clear-cut strategy is applied. Modelled carbon stocks and fluxes are evaluated against reported data at the continent and country levels. Including wood harvest in regrowth forests increases the simulated total European carbon sink by 32 % in 1991–2015 and improves the fit to the reported European carbon sink, growing stock, and net annual increment (NAI). Growing stock (156 m3 ha−1) and NAI (5.4 m3 ha1 yr1) densities in 2010 are close to reported values, while the carbon sink density in 2000–2007 (0.085 kg C m−2 yr1) equates to 63 % of reported values, most likely reflecting uncertainties in carbon fluxes from soil given the unaccounted for forest land-use history in the simulations. The fit of modelled and reported values for individual European countries varies, but NAI is generally closer to reported values when including wood harvest in simulations.