Assessment of Factors Associated with Life Expectancy Gap Based on the Preston Curve: A Cross-Sectional Study

Background: Some countries experience lower or higher life expectancy than what is predicted based on their income. This study examines why life expectancy deviation is experienced with the aim of exploring which factors and conditions contribute to better health outcome (life expectancy) at low cos...

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Main Authors: Fatemeh Yari, Lotfali Agheli, Hossein Sadeghi, Sajjad Faraji Dizaji
Format: Article
Language:English
Published: Shahid Sadoughi University of Medical Sciences 2023-11-01
Series:Journal of Community Health Research
Subjects:
Online Access:http://jhr.ssu.ac.ir/article-1-971-en.pdf
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author Fatemeh Yari
Lotfali Agheli
Hossein Sadeghi
Sajjad Faraji Dizaji
author_facet Fatemeh Yari
Lotfali Agheli
Hossein Sadeghi
Sajjad Faraji Dizaji
author_sort Fatemeh Yari
collection DOAJ
description Background: Some countries experience lower or higher life expectancy than what is predicted based on their income. This study examines why life expectancy deviation is experienced with the aim of exploring which factors and conditions contribute to better health outcome (life expectancy) at low cost. Methods: In this study at the first stage, the well-known Preston curve is reproduced and updated using the cross-sectional data of variables of life expectancy at birth (years) and per capita gross domestic product (GDP) by purchasing power parity (PPP) of 182 countries around the World in 2018 based on the latest available data. After estimating the deviation of each countries life expectancy from the curve, the characteristics of countries with more than four years of positive (group 1) and negative (group 2) gaps from the curve were compared by applying the mean comparison test of two independent groups (t-test). Results: The identified drivers of gains or losses in longevity relative to income included using at least basic sanitation (P = 0.012) and drinking water services (P = 0.045), Universal Health Coverage (UHC) (P = 0.012), access to electricity (P = 0.004), CO2 emissions (P = 0.037), inequality in income (P = 0.003), health expenditure per capita (P = 0.000), non-communicable (P = 0.000) and communicable diseases and maternal, prenatal, and nutrition conditions (P = 0.000), literacy rate (P = 0.057), and road injuries (P = 0.001). Conclusion: Better health outcome in countries and regions with relatively low income or few resources can be achieved that would be critical for global improvement in population health. However, it needs to take effective measures and is of great importance for policy-making.
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spelling doaj.art-2d553765a3ba4834bca2da2b9f0e3b282024-04-23T06:00:56ZengShahid Sadoughi University of Medical SciencesJournal of Community Health Research2322-56882345-26092023-11-01122217227Assessment of Factors Associated with Life Expectancy Gap Based on the Preston Curve: A Cross-Sectional StudyFatemeh Yari0Lotfali Agheli1Hossein Sadeghi2Sajjad Faraji Dizaji3 Department of Economic Development and Planning, Faculty of Management and Economics, Tarbiat Modares Univrersity, Tehran, Iran Economic Research Institute, Tarbiat Modares Univrersity, Tehran, Iran Department of Economic Development and Planning, Faculty of Management and Economics, Tarbiat Modares Univrersity, Tehran, Iran Department of Economic Development and Planning, Faculty of Management and Economics, Tarbiat Modares Univrersity, Tehran, Iran Background: Some countries experience lower or higher life expectancy than what is predicted based on their income. This study examines why life expectancy deviation is experienced with the aim of exploring which factors and conditions contribute to better health outcome (life expectancy) at low cost. Methods: In this study at the first stage, the well-known Preston curve is reproduced and updated using the cross-sectional data of variables of life expectancy at birth (years) and per capita gross domestic product (GDP) by purchasing power parity (PPP) of 182 countries around the World in 2018 based on the latest available data. After estimating the deviation of each countries life expectancy from the curve, the characteristics of countries with more than four years of positive (group 1) and negative (group 2) gaps from the curve were compared by applying the mean comparison test of two independent groups (t-test). Results: The identified drivers of gains or losses in longevity relative to income included using at least basic sanitation (P = 0.012) and drinking water services (P = 0.045), Universal Health Coverage (UHC) (P = 0.012), access to electricity (P = 0.004), CO2 emissions (P = 0.037), inequality in income (P = 0.003), health expenditure per capita (P = 0.000), non-communicable (P = 0.000) and communicable diseases and maternal, prenatal, and nutrition conditions (P = 0.000), literacy rate (P = 0.057), and road injuries (P = 0.001). Conclusion: Better health outcome in countries and regions with relatively low income or few resources can be achieved that would be critical for global improvement in population health. However, it needs to take effective measures and is of great importance for policy-making.http://jhr.ssu.ac.ir/article-1-971-en.pdflife expectancyincomepopulation health
spellingShingle Fatemeh Yari
Lotfali Agheli
Hossein Sadeghi
Sajjad Faraji Dizaji
Assessment of Factors Associated with Life Expectancy Gap Based on the Preston Curve: A Cross-Sectional Study
Journal of Community Health Research
life expectancy
income
population health
title Assessment of Factors Associated with Life Expectancy Gap Based on the Preston Curve: A Cross-Sectional Study
title_full Assessment of Factors Associated with Life Expectancy Gap Based on the Preston Curve: A Cross-Sectional Study
title_fullStr Assessment of Factors Associated with Life Expectancy Gap Based on the Preston Curve: A Cross-Sectional Study
title_full_unstemmed Assessment of Factors Associated with Life Expectancy Gap Based on the Preston Curve: A Cross-Sectional Study
title_short Assessment of Factors Associated with Life Expectancy Gap Based on the Preston Curve: A Cross-Sectional Study
title_sort assessment of factors associated with life expectancy gap based on the preston curve a cross sectional study
topic life expectancy
income
population health
url http://jhr.ssu.ac.ir/article-1-971-en.pdf
work_keys_str_mv AT fatemehyari assessmentoffactorsassociatedwithlifeexpectancygapbasedontheprestoncurveacrosssectionalstudy
AT lotfaliagheli assessmentoffactorsassociatedwithlifeexpectancygapbasedontheprestoncurveacrosssectionalstudy
AT hosseinsadeghi assessmentoffactorsassociatedwithlifeexpectancygapbasedontheprestoncurveacrosssectionalstudy
AT sajjadfarajidizaji assessmentoffactorsassociatedwithlifeexpectancygapbasedontheprestoncurveacrosssectionalstudy