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We examine the factors affecting the life expectancy in countries from the WHO through basic data analysis techniques. We do this by using machine learning algorithms and data visualization tools in R-programming.

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Ishuardev/Life-Expectancy-WHO-Analysis

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LIFE-EXPECTANCY-WHO-Analysis

Life expectancy refers to the number of years a person can expect to live. It is formally defined as an estimate of the average age that a member of a particular population will be when they die. Life expectancy has seen great and rapid changes in comparison to the early 1900s. The global average life expectancy has more than doubled and in 2019 is above 70 years (Roser, 2013). There has been great research on factors affecting the life expectancy of different countries in the world. Some might even argue that the advancement in the healthcare sector plays an important role in determining how long one can live.

This report will cover the data descriptions and analysis using R language. For each of our research objectives, we performed statistical analysis and drew conclusions in the most appropriate approach, together with explanations and elaborations.

Infomration on the data collected, the descriptions and metrics used is added to the file in this repository. The dataset used will also be uploaded as well

References:

Alemu, A. M. (2017, May 29). To what extent does access to improved sanitation explain the observed differences in infant mortality in Africa? African journal of primary health care & family medicine. Retrieved April 17, 2023, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5458576/

Grauer, J., Löwen, H. & Liebchen, B. (2020) - “ Strategic spatiotemporal vaccine distribution increases the survival rate in an infectious disease like Covid-19”. Retrieved from : Sci Rep 10, 21594 . https://doi.org/10.1038/s41598-020-78447-3

Max Roser, Esteban Ortiz-Ospina and Hannah Ritchie (2013) - "Life Expectancy". Published online at OurWorldInData.org. Retrieved from: 'https://ourworldindata.org/life-expectancy' [Online Resource]

Rahman, M. M., Khanam, R., & Rahman, M. (2018, November 22). Health Care Expenditure and Health Outcome Nexus: New evidence from the SAARC-asean region. Globalization and health. Retrieved April 17, 2023, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6249744/

Rice, D., & Galbraith, M. (2008, November 16). Predictions of World Population Life Expectancy Using Cyclical Order Weight / Bias. The International Conference on Computer Science and Applied Mathematic. Retrieved April 17, 2023, from https://iopscience.iop.org/article/10.1088/1742-6596/1255/1/012017/pdf

Roffia, Bucciol, A., & Hashlamoun, S. (2022, ). Determinants of life expectancy at birth: a longitudinal study on OECD countries. International Journal of Health Economics and Management, 1–24. World Health Organization. (n.d.). Sanitation. World Health Organization. Retrieved April 17, 2023, from https://www.who.int/news-room/fact-sheets/detail/sanitation

Worthing, B. (2020, January 23). Extreme Obesity Shaves Years Off Life Expectancy. NIH Intramural Research Program. Retrieved April 16, 2023, from https://irp.nih.gov/blog/post/2020/01/extreme-obesity-shaves-years-off-life-expectancy

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We examine the factors affecting the life expectancy in countries from the WHO through basic data analysis techniques. We do this by using machine learning algorithms and data visualization tools in R-programming.

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