scholarly journals Intraday Variation Mapping of Population Age Structure via Urban-Functional-Region-Based Scaling

2021 ◽  
Vol 13 (4) ◽  
pp. 805
Author(s):  
Yuncong Zhao ◽  
Yuan Zhang ◽  
Hongyan Wang ◽  
Xin Du ◽  
Qiangzi Li ◽  
...  
Keyword(s):  
Age Structure ◽  
Population Distribution ◽  
Population Variation ◽  
Accuracy Evaluation ◽  
Mobility Patterns ◽  
Functional Region ◽  
Population Age Structure ◽  
Ring Road ◽  
Optimal Subset ◽  
Time Period

The spatial distribution of the population is uneven for various reasons, such as urban-rural differences and geographical conditions differences. As the basic element of the natural structure of the population, the age structure composition of populations also varies considerably across the world. Obtaining accurate and spatiotemporal population age structure maps is crucial for calculating population size at risk, analyzing populations mobility patterns, or calculating health and development indicators. During the past decades, many population maps in the form of administrative units and grids have been produced. However, these population maps are limited by the lack of information on the change of population distribution within a day and the age structure of the population. Urban functional regions (UFRs) are closely related to population mobility patterns, which can provide information about population variation intraday. Focusing on the area within the Beijing Fifth Ring Road, the political and economic center of Beijing, we showed how to use the temporal scaling factors obtained by analyzing the population survey sampling data and population dasymetric maps in different categories of UFRs to realize the intraday variation mapping of elderly individuals and children. The population dasymetric maps were generated on the basis of covariates related to population. In this article, 50 covariates were calculated from remote sensing data and geospatial data. However, not all covariates are associate with population distribution. In order to improve the accuracy of dasymetric maps and reduce the cost of mapping, it is necessary to select the optimal subset for the dasymetric model of elderly and children. The random forest recursive feature elimination (RF-RFE) algorithm was introduced to obtain the optimal subset of different age groups of people and generate the population dasymetric model in this article, as well as to screen out the optimal subset with 38 covariates and 26 covariates for the dasymetric models of the elderly and children, respectively. An accurate UFR identification method combining point of interest (POI) data and OpenStreetMap (OSM) road network data is also introduced in this article. The overall accuracy of the identification results of UFRs was 70.97%, which is quite accurate. The intraday variation maps of population age structure on weekdays and weekends were made within the Beijing Fifth Ring Road. Accuracy evaluation based on sampling data found that the overall accuracy was relatively high—R2 for each time period was higher than 0.5 and root mean square error (RMSE) was less than 0.05. On weekdays in particular, R2 for each time period was higher than 0.61 and RMSE was less than 0.02.

Panel data comparative analysis on the influence of population age structure on the size of government expenditure in Africa and Asia

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chukwuebuka Bernard Azolibe
Keyword(s):  
Cross Sections ◽  
Age Structure ◽  
Government Expenditure ◽  
Empirical Literature ◽  
Size Of Government ◽  
Population Age Structure ◽  
Content Type ◽  
Time Period ◽  
The World ◽  
Age Structures

PurposeAfrica and Asia are the two most populous continents in the world and are projected to increase further in the near future and this puts the governments under great stress in terms of increased public expenditure and dealing with a low revenue generation. Thus, the purpose of this study is to assess the influence of population age structure on the size of government expenditure in Africa and Asia covering the period 1990–2018.Design/methodology/approachThe study employed panel fully modified ordinary least squares (FMOLS) estimation in estimating the relevant relationship between the variables in the model.FindingsThe key findings revealed that the major population age structures that influence the size of government expenditure in Africa are population aged 0–14 years and population aged 15–64 years, while that of Asia are population aged 15–64 years and population aged 65 years and above. The findings provided strong support for the Population Reference Bureau report (2019) that countries in Africa are home to some of the world's youngest population, that is, those aged 15 years or below, while Asia is home to some of the world's oldest population, that is, those aged 65 years and above.Research limitations/implicationsWhile generalized method of moments (GMM) estimation is beneficial in the presence of endogeneity, it is only designed for situations with a small time period (T) and a large number of cross sections (N). Hence, the estimation technique was limited only to FMOLS as the number of the cross sections or countries which is ten for Africa and ten for Asia is lower than the time period which is 29 years (1990–2018).Originality/valueEmpirical literature investigating the influence of population age structure on the size of government expenditure has focussed mainly on one aspect of the population age structure and government expenditure, which is the influence of ageing population on government expenditure on health. Hence, this study focussed on assessing the influence of population age structure on the size of government expenditure. The study is unique as it compared the two most populous continents in the world, which are Africa and Asia to determine which of the population age structures have the most significant influence on the size of government expenditure.

scholarly journals Modeling Population Spatial-Temporal Distribution Using Taxis Origin and Destination Data

2021 ◽  
Vol 13 (7) ◽  
pp. 3727
Author(s):  
Fatema Rahimi ◽  
Abolghasem Sadeghi-Niaraki ◽  
Mostafa Ghodousi ◽  
Soo-Mi Choi
Keyword(s):  
Regression Analysis ◽  
Mean Squared Error ◽  
Population Distribution ◽  
Temporal Distribution ◽  
Coefficient Of Determination ◽  
Temporal Modeling ◽  
Location Data ◽  
Time Period ◽  
Proposed Model

During dangerous circumstances, knowledge about population distribution is essential for urban infrastructure architecture, policy-making, and urban planning with the best Spatial-temporal resolution. The spatial-temporal modeling of the population distribution of the case study was investigated in the present study. In this regard, the number of generated trips and absorbed trips using the taxis pick-up and drop-off location data was calculated first, and the census population was then allocated to each neighborhood. Finally, the Spatial-temporal distribution of the population was calculated using the developed model. In order to evaluate the model, a regression analysis between the census population and the predicted population for the time period between 21:00 to 23:00 was used. Based on the calculation of the number of generated and the absorbed trips, it showed a different spatial distribution for different hours in one day. The spatial pattern of the population distribution during the day was different from the population distribution during the night. The coefficient of determination of the regression analysis for the model (R2) was 0.9998, and the mean squared error was 10.78. The regression analysis showed that the model works well for the nighttime population at the neighborhood level, so the proposed model will be suitable for the day time population.

scholarly journals Polarized nature of the COVID-19 pandemic in Japan: associations with population age structure and behaviours

2021 ◽  
Vol 49 (1) ◽  
Author(s):  
Junko Okumura
Keyword(s):  
Age Structure ◽  
Public Transportation ◽  
Perceived Risk ◽  
Online Survey ◽  
Preventive Measures ◽  
Age Groups ◽  
Cumulative Number ◽  
Population Age Structure ◽  
Major Factors ◽  
Drinking Places

Abstract Background Although the scale of the coronavirus disease (COVID-19) pandemic was relatively small in Japan compared with the rest of the world, the polarisation of areas into high- and low-COVID-19-incidence areas was observed among the 47 prefectures. The aims of this study were not only identifying the factors associated with the polarised COVID-19 pandemic in Japan but also discussing effective preventive measures. Methods This was an ecological study using online survey data which was cross-sectionally conducted by the author. A total of 6000 respondents who resided in 10 low- and 10 high-COVID-19 incidence prefectures, with a wide gap in terms of COVID-19 incidence, in Japan were recruited. Data on COVID-19 cases and geodemographic information were obtained from official government sites. Statistical analyses were conducted to compare variables between the two areas and age groups. Results This study revealed that that age influenced people’s behaviours and perceptions, except one behaviour of ‘wearing facemasks’. The major factors significantly associated with the cumulative number of COVID-19 cases per 100,000 people were ‘commuting by private automobile’ (adjusted odds ratio [AOR], 0.444; 95% confidence interval [CI], 0.394–0.501), ‘commuting by public transportation’ (AOR, 6.813; 95% CI, 5.567–8.336), ‘washing hands’ (AOR, 1.233; 95% CI, 1.005–1.511), ‘opening windows regularly’ (AOR, 1.248; 95% CI, 1.104–1.412), ‘avoiding crowded places (AOR, 0.757; 95% CI, 0.641–0.893), ‘non-scheduled visits to drinking places’ (AOR, 1.212; 95% CI, 1.054–1.392) and ‘perceived risk of contracting COVID-19’ (AOR, 1.380; 95% CI, 1.180–1.612). These factors were strongly associated with age groups. Conclusions Effective preventive measures for COVID-19 transmission can be developed by understanding the characteristics of populated areas, such as public transportation infrastructure and younger people’s movements and behaviours in relation to the population age structure to contain the current epidemic and protect the most vulnerable elderly people.

A Role for the X Chromosome in Sex Differences in Variability in General Intelligence?

2009 ◽  
Vol 4 (6) ◽  
pp. 598-611 ◽  
Author(s):  
Wendy Johnson ◽  
Andrew Carothers ◽  
Ian J. Deary
Keyword(s):  
Sex Differences ◽  
Mental Retardation ◽  
X Chromosome ◽  
Cognitive Abilities ◽  
Population Distribution ◽  
Population Variation ◽  
General Intelligence ◽  
Substantial Evidence ◽  
Normal Distributions ◽  
Intellectual Abilities

There is substantial evidence that males are more variable than females in general intelligence. In recent years, researchers have presented this as a reason that, although there is little, if any, mean sex difference in general intelligence, males tend to be overrepresented at both ends of its overall distribution. Part of the explanation could be the presence of genes on the X chromosome related both to syndromal disorders involving mental retardation and to population variation in general intelligence occurring normally. Genes on the X chromosome appear overrepresented among genes with known involvement in mental retardation, which is consistent with a model we developed of the population distribution of general intelligence as a mixture of two normal distributions. Using this model, we explored the expected ratios of males to females at various points in the distribution and estimated the proportion of variance in general intelligence potentially due to genes on the X chromosome. These estimates provide clues to the extent to which biologically based sex differences could be manifested in the environment as sex differences in displayed intellectual abilities. We discuss these observations in the context of sex differences in specific cognitive abilities and evolutionary theories of sexual selection.

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