The demography of Saudi Arabia has been discussed many times but its conflict with the theories of transition and associated structural changes is unexplained. This research explains the demographic differentials stated as lag - real from theoretical – separately for the native and total population. This research developed demographic indicators revealing trends and patterns by adopting a secondary data analysis method, utilizing the General Authority for Statistics census data and other online data. The demographic transition of Saudi Arabia is in line with the theoretical contentions of pretransition and transition (early, mid, and late) stages but at definite time intervals. The absolute size, percentage change, and annual growth rate are explanatory for natives and are considered separately. Moreover, the structural population changes reveal transition stages from expansive to near expansive and constricting and stabilizing. Furthermore, broad age groups indicate rapid declines in the percentage of children, rapid increases in young adults, slow increases in older adults, and no changes in older persons. Even the sex ratio of natives is at par with other populations in transition (slightly above 100). Thus, it could be concluded that a demographic transition with structural changes as per theories: flawless growth rates with an expanding demographic dividend. At this juncture, the integration of migrants into society by endorsing family life and enabling social and demographic balance appears as imperative to improving the labor sector, productivity, and the image of the country in the international spheres for comparisons and benchmarking.

Recently, there has been a burgeoning fascination with the influence of urban green spaces (UGS) on physical activity (PA) and health. This interest has been accompanied by a mounting body of evidence that establishes a connection between UGS and residents’ PA levels. Numerous studies have been conducted to investigate the significance of UGS and have generally agreed on their connection with health. However, there is still considerable variation in viewpoints regarding the intermediate factors contributing to this association. The primary objective of this study was to investigate the potential correlation between different qualitative factors of UGS and PA. The study involved the collection of data from four parks located in Edinburgh. Four trained observers utilised the Environmental Assessment of Public Recreational Spaces (EARPS Mini) tool to code various environmental characteristics. Additionally, the Method for Observing Physical Activity and Wellbeing (MOHAWk) observation tool was employed to code instances of on-site incivility and the characteristics and behaviours of residents engaging in UGS activities. The results of this study show that the facilities and environment, area and socioeconomic status (SES) of UGS positively affect the type of PA and the level of PA, as well as influence residents’ attentiveness to the environment and their interactions with each other. Demographics such as gender and age group are also significantly related to the level and type of PA. Significant differences in the level and type of PA, and race only differed significantly in the choice of activity type. These results suggest that the quality of the UGS environment affects the level, type, and status of PA among residents and that resident characteristics also have an impact. Future research suggests increasing data collection related to PA frequency and PA duration and considering longitudinal observations over time for refinement.

The study examined the socio-demographic factors affecting access to and utilization of social welfare services in Yenagoa Local Government Area of Bayelsa State, Nigeria. Quantitative and qualitative approaches were adopted to select 570 respondents from the study area. Probability and non-probability sampling techniques were adopted in the selection of communities, and respondents. The quantitative data were analyzed using frequency distribution tables and percentages, while chi-square statistic was used to determine the relationship between socio-demographic variables and access to and utilization of social welfare services. The qualitative data were analyzed in themes as a complement to the quantitative data. This study reveals that although all the respondents reported knowing available social welfare services, 44.3% reported not having access to existing social services due to factors connected to serendipity variables, such as terrain condition, ethnicity and knowing someone in government. Therefore, the study recommends that the government and other stakeholders should push for the massive delivery of much-needed social welfare services to address the issue of welfare service deficit across the nation, irrespective of the ethnic group and whether the community is connected to the government of the day or not, primarily in rural areas.

Based on the population change data of 2005–2009, 2010–2014, 2015–2019 and 2005–2019, the shrinking cities in Northeast China are determined to analyze their spatial distribution pattern. And the influencing factors and effects of shrinking cities in Northeast China are explored by using multiple linear regression method and random forest regression method. The results show that: 1) In space, the shrinking cities in Northeast China are mainly distributed in the “land edge” areas represented by Changbai Mountain, Sanjiang Plain, Xiaoxing’an Mountain and Daxing’an Mountain. In terms of time, the contraction center shows an obvious trend of moving northward, while the opposite expansion center shows a trend of moving southward, and the shrinking cities gather further; 2) in the study of influencing factors, the results of multiple linear regression and random forest regression show that socio-economic factors play a major role in the formation of shrinking cities; 3) the precision of random forest regression is higher than that of multiple linear regression. The results show that per capita GDP has the greatest impact on the contraction intensity, followed by the unemployment rate, science and education expenses and the average wage of on-the-job workers. Among the four influencing factors, only the unemployment rate promotes the contraction, and the other three influencing factors inhibit the formation of shrinking cities to various degrees.

The research aims to explore the degree of acceptance of digital work culture among the youth in the Emirati society within the study sample. Additionally, it aims to reveal the relationship between “gender” and “educational status” as sociodemographic factors among the youth in the study sample and their level of acceptance of digital work culture. Furthermore, the study aims to identify prospective trends in digital work culture among young individuals in Emirati society. Due to the nature of the descriptive research, it employed the “sample social survey” approach. The field study primarily utilized a quantitative tool for data collection, namely the “digital questionnaire.” This questionnaire was administered to a purposefully chosen random sample comprising young individuals actively seeking employment opportunities (unemployed individuals) or those new to the labor market. The participants fell within the age group of 15 to 35 years, totaling 184 individuals. Care was taken to ensure that this sample was representative of all youth categories in Emirati society, considering demographic factors such as gender, place of residence, and educational status. The research findings indicate that an overwhelming majority of young individuals in the study sample (97.8%) have no obstacles to accepting job opportunities that necessitate digital and technological skills. Moreover, the study uncovered a direct and statistically significant relation between “gender” and the “level of acceptance of digital work culture,” favoring females. This implies that females are more inclined to accept digital job opportunities compared to males. Additionally, the results highlighted a positive and statistically significant relation between both “educational status” and the “level of acceptance of digital work culture.” In other words, individuals with higher levels of education demonstrate a greater interest in digital job opportunities. Utilizing Step-wise Regression, the study also made predictions about the spread of “future digital work culture” in the United Arab Emirates based on the variable of “education.”