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.

Over the last few decades, countries in the South have been undergoing rapid urbanization, as if to make up for lost time. Sub-Saharan Africa is characterized by a very low urbanization rate compared to0 the rest of the world. Although the African continent reached its urban transition in 2015, Niger remains by far the least urbanized country, with a rate of 17%. The city of Niamey is the main urban center, with an estimated population of 1,449,801 hbts in 2023, spread over an area of around 33,100 ha. The aim of this study is to analyze the spatial expansion of the city of Niamey from 1984 to 2023. The main data used in this study are raster images from the United States Geological Survey (USGS), vector data from Open Sources Map (OSM) and GoogleEarth, secondary data from the National Institute of Statistics (INS) and field observation. This study enabled us to conclude that between 1984 and 2023, the city of Niamey underwent very strong spatial expansion. The city grew from 4,690 ha to 33,100 ha, i.e. 28,410 ha absorbed in 39 years, with exceptional growth between 2014 and 2023, when the urban area doubled. Its population has risen from 397,437 at the time of the 1988 general population and housing census to an estimated 1,449,801 in 2023 (INS), an increase of 1,052,364 in 35 years. Between these two dates, population density fell from 87.7 to 43.8 inhabitants/km², i.e. half that of 1984. This spatial expansion has resulted in unprecedented peri-urbanization.

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.

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.

Introduction: Citizen insecurity is a complex, multidimensional and multi-causal social problem, defined as the spaces where people feel insecure mainly due to organized crime in all nations that suffer from it. Objective: To analyzes the sociodemographic factors associated with public insecurity in a Peruvian population. Methodology: The research employed a non-experimental, quantitative design with a descriptive and cross-sectional approach. A total of 11,116, citizens participated, ranging from 18 to 85 years old (young adults, adults, and the elderly), of both sexes, and with any occupation, education level, and marital status. The study employed purposive non-probability sampling to select the participants. Results: More than 50% of the population feels unsafe, in public and private spaces. All analyzed sociodemographic variables (p < 0.05), showing distinctions in the perception of citizen insecurity based on age, gender, marital status, occupation, area of residence, and education level. It was determined that young, single students, who had not experienced a criminal event and reside in urban areas, regardless of gender, perceive a greater sense of insecurity. Contribution: The study is relevant due to the generality of the results in a significant sample, demonstrating that the study contributes to understanding how various elements of the socioeconomic and demographic context can influence the way in which individuals perceive insecurity in their communities, likewise, the perception of citizen insecurity directly affects the general well-being and quality of life of residents, influencing their behaviors and attitudes towards coexistence and public policies; which will help implement more effective actions in the sector to reduce crime rates.