Spatial Patterns of Population Growth and Demographic Change: A Historical–Geographical Assessment of Countries Worldwide
Abstract
transformation and regional development across the world. This study examined the spatial patterns of population growth and demographic change using a historical–geographical perspective based on a global dataset comprising 234 countries and territories from 1970 to 2022. A quantitative, retrospective research design was employed using publicly available secondary data. Descriptive statistics, continental comparisons, historical trend analysis, and Pearson correlation analysis were performed in Python to evaluate relationships among population size, population density, growth rate, land area, and world population share. The findings revealed a continuous increase in the global population over the study period, accompanied by substantial geographical variation across continents. Asia recorded the largest population and highest average population density, whereas Africa exhibited the highest average demographic growth rate. Correlation analysis indicated a moderate positive relationship between land area and total population, while population growth rate showed only weak associations with geographical variables. These results demonstrate that demographic change is characterized by distinct spatial patterns influenced by multiple regional factors rather than geographical extent alone. The study contributes to historical geography by integrating temporal demographic trends with comparative spatial analysis and provides valuable evidence for population studies, regional planning, and sustainable development. Future research should incorporate socioeconomic, environmental, and migration-related variables to improve understanding of global demographic dynamics.
References
2.Banerjee, S. (2022). World Population Dataset [Data set]. Kaggle. https://www.kaggle.com/datasets/iamsouravbanerjee/world-population-dataset
3.Chen, C., Li, J., & Huang, J. (2022). Spatial–temporal patterns of population aging in rural China. International Journal of Environmental Research and Public Health, 19(23), 15631.
4.Chen, X., Ding, Z., Li, X., Baiyinbaoligao, & Liu, H. (2025). Spatiotemporal Dynamics, Risk Mechanisms, and Adaptive Governance of Flood Disasters in the Mekong River Countries. Sustainability, 17(21), 9664.
5.Dadashpoor, H., & Saeidi Shirvan, S. (2026). Definition and evolution of urban spatial structure. In The encyclopedia of human geography (pp. 261-271). Cham: Springer Nature Switzerland.
6.Fischer, A. M. (2025). A demographic case for a Global South focus in development studies. The European Journal of Development Research, 37(2), 374-390.
7.Grinin, L., & Grinin, A. (2023). Demographic transformations in the historical process in the light of technological development: Theoretical approach. Social Evolution & History, 22(2), 159-202.
8.Hazen, H. D., Alberts, H. C., & Zaniewski, K. J. (2023). Population geography: social justice for a sustainable world. Routledge.
9.Livi-Bacci, M. (2025). A concise history of world population. John Wiley & Sons.
10.Long, H. (2022). Theorizing land use transitions: A human geography perspective. Habitat international, 128, 102669.
11.Ma, M., Zhang, S., Liu, J., Yan, R., Cai, W., Zhou, N., & Yan, J. (2025). Building floorspace and stock measurement: A review of global efforts, knowledge gaps, and research priorities. Nexus, 2(3).
12.MISRA, R., MISHRA, S., & MAURYA, N. K. (2025). DEMOGRAPHY AND POPULATION STUDIES: THEORY, TECHNIQUES AND POLICY. PHI Learning Pvt. Ltd.
13.Newsham, N., & Rowe, F. (2023). Understanding trajectories of population decline across rural and urban Europe: A sequence analysis. Population, Space and Place, 29(3), e2630.
14.Norlund, P., Arsanjani, J. J., & Paasch, J. M. (2026). Spatio-Temporal COVID-19 Modeling: A Global Systematic Review of Data Integration, Equity, and Lessons for Pandemic Preparedness. International Journal of Environmental Research and Public Health, 23(5), 627.
15.Poot, J. (2026). The economics of negative population growth: global to local perspectives. New Zealand Economic Papers, 1-42.
16.Qiu, Y., Cao, G., & Liu, T. (2025). Population Growth and Decline in China: A Geographical Analysis, 1982–2020. Population, Space and Place, 31(2), e70003.
17.Rasoanaivo, Z. R. (2025). Benchmarking WASH Trajectories in Africa: A Comparative Assessment of Six Country Archetypes (2000–2022).
18.Sarkodie, S. A., Owusu, P. A., & Taden, J. (2024). Green growth assessment across 203 economies: Trends and insights. Sustainable Horizons, 10, 100083.
19.Ventsiv, P. (2023). Demographic processes in the context of regional development concepts. Human Geography Journal, 34, 42-48.
20.Wahl, B., Menon, G. I., Nyhan, K., Ren, Y., Coria, A. L., & Mukherjee, B. (2025). Global health data precarity: Safeguarding the Demographic and Health Survey program as a global public good. Scientific Data, 12(1), 1827.
21.Wang, S., Huang, X., Liu, P., Zhang, M., Biljecki, F., Hu, T., ... & Bao, S. (2024). Mapping the landscape and roadmap of geospatial artificial intelligence (GeoAI) in quantitative human geography: An extensive systematic review. International Journal of Applied Earth Observation and Geoinformation, 128(C).
22.Warf, B. (2026). Demographic transition. In The Encyclopedia of Human Geography (pp. 275-281). Cham: Springer Nature Switzerland.
23.Woods, R., & Rees, P. (Eds.). (2023). Population structures and models: Developments in spatial demography. Taylor & Francis.
24.Zhang, H., Dong, G., Li, B., Xie, Z., Miao, C., Yang, F., ... & Li, X. (2024). Developing an annual global Sub-National scale economic data from 1992 to 2021 using nighttime lights and deep learning. International Journal of Applied Earth Observation and Geoinformation, 133, 104086.
25.Zhang, K., Sun, H., & Li, X. (2022). Aging population spatial distribution discrepancy and impacting factor. Sustainability, 14(15), 9528.
