Longitudinal analysis of the determinants of life expectancy and healthy life expectancy: A causal approach

Understanding the determinants of health is essential for designing effective strategies to advance economic growth, reduce disease and disability, and enhance quality of life. We undertake a comprehensive outlook on public health by incorporating three metrics — life expectancy (LE), healthy life e...

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Main Authors: Rohan Aanegola, Shinpei Nakamura Sakai, Navin Kumar
Format: Article
Language:English
Published: Elsevier 2022-11-01
Series:Healthcare Analytics
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2772442522000077
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author Rohan Aanegola
Shinpei Nakamura Sakai
Navin Kumar
author_facet Rohan Aanegola
Shinpei Nakamura Sakai
Navin Kumar
author_sort Rohan Aanegola
collection DOAJ
description Understanding the determinants of health is essential for designing effective strategies to advance economic growth, reduce disease and disability, and enhance quality of life. We undertake a comprehensive outlook on public health by incorporating three metrics — life expectancy (LE), healthy life expectancy (HLE), and the discrepancy between the two. We investigate the effects of various health and socio-economic factors on these metrics and employ causal machine learning and statistical methods such as propensity score matching, X-learners, and causal forests to calculate treatment effects. An increase in basic water services and public health expenditure significantly increased average LE whereas high human immunodeficiency virus (HIV) prevalence rates and poverty rates reduced average LE. High gross national income (GNI) per capita and moderate body mass index (BMI) increased HLE whilst high HIV prevalence rates decreased HLE. High public health expenditure and high GNI per capita expand the gap between HLE and LE whereas high HIV prevalence rates and moderate BMI diminish this gap. Results suggest that policymakers should utilize governmental resources to improve public health infrastructure rather than provide fiscal incentives to encourage private healthcare infrastructure. Additionally, more emphasis should be placed on increasing educational levels of the general public by increasing educational expenditure and making educational institutions, public and private, more accountable.
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spelling doaj.art-778a413df3bd4ebfa5d930a6e880827e2022-12-22T03:00:52ZengElsevierHealthcare Analytics2772-44252022-11-012100028Longitudinal analysis of the determinants of life expectancy and healthy life expectancy: A causal approachRohan Aanegola0Shinpei Nakamura Sakai1Navin Kumar2Yale School of Medicine, United States of America; Corresponding author.Department of Statistics and Data Science, Yale University, United States of AmericaYale School of Medicine, United States of AmericaUnderstanding the determinants of health is essential for designing effective strategies to advance economic growth, reduce disease and disability, and enhance quality of life. We undertake a comprehensive outlook on public health by incorporating three metrics — life expectancy (LE), healthy life expectancy (HLE), and the discrepancy between the two. We investigate the effects of various health and socio-economic factors on these metrics and employ causal machine learning and statistical methods such as propensity score matching, X-learners, and causal forests to calculate treatment effects. An increase in basic water services and public health expenditure significantly increased average LE whereas high human immunodeficiency virus (HIV) prevalence rates and poverty rates reduced average LE. High gross national income (GNI) per capita and moderate body mass index (BMI) increased HLE whilst high HIV prevalence rates decreased HLE. High public health expenditure and high GNI per capita expand the gap between HLE and LE whereas high HIV prevalence rates and moderate BMI diminish this gap. Results suggest that policymakers should utilize governmental resources to improve public health infrastructure rather than provide fiscal incentives to encourage private healthcare infrastructure. Additionally, more emphasis should be placed on increasing educational levels of the general public by increasing educational expenditure and making educational institutions, public and private, more accountable.http://www.sciencedirect.com/science/article/pii/S2772442522000077Healthy life expectancySocio-economic indicatorsPublic healthTreatment effectsCausal machine learning
spellingShingle Rohan Aanegola
Shinpei Nakamura Sakai
Navin Kumar
Longitudinal analysis of the determinants of life expectancy and healthy life expectancy: A causal approach
Healthcare Analytics
Healthy life expectancy
Socio-economic indicators
Public health
Treatment effects
Causal machine learning
title Longitudinal analysis of the determinants of life expectancy and healthy life expectancy: A causal approach
title_full Longitudinal analysis of the determinants of life expectancy and healthy life expectancy: A causal approach
title_fullStr Longitudinal analysis of the determinants of life expectancy and healthy life expectancy: A causal approach
title_full_unstemmed Longitudinal analysis of the determinants of life expectancy and healthy life expectancy: A causal approach
title_short Longitudinal analysis of the determinants of life expectancy and healthy life expectancy: A causal approach
title_sort longitudinal analysis of the determinants of life expectancy and healthy life expectancy a causal approach
topic Healthy life expectancy
Socio-economic indicators
Public health
Treatment effects
Causal machine learning
url http://www.sciencedirect.com/science/article/pii/S2772442522000077
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AT shinpeinakamurasakai longitudinalanalysisofthedeterminantsoflifeexpectancyandhealthylifeexpectancyacausalapproach
AT navinkumar longitudinalanalysisofthedeterminantsoflifeexpectancyandhealthylifeexpectancyacausalapproach