Abstract
Background The data from the WHO showed that life expectancy and health-adjusted life expectancy at global level both increased from 2000 to 2019, while they did not increase at the same rate. Therefore, our study aims to explore the relationship and changing trends between life expectancy and health-adjusted life expectancy, and further comprehensively analyze the factors influencing the difference between the two. Methods This paper uses data from the Global Burden of Disease (GBD) database in life expectancy and health-adjusted life expectancy across 204 countries and regions from 1990 to 2019. It analyses the trends of the relationship between life expectancy and health-adjusted life expectancy at birth and at 65 and over across 204 countries and regions from 1990 to 2019 and classfies all the coutries into three typies: optimized countries, low deterioration countries and high deterioration countries. Then this paper uses the random effects model to analyze the factors that influence the three types of countries and regions in terms of environmental/occupational risk, behavioral risk, and metabolic risk. Results First, for males, for indicator of age at birth, 8 optimized countries were with "drug use" having the greatest impact, 98 low deterioration countries were with "low physical activity" being the most significant; 98 high deterioration countries were with "childhood sexual abuse and bullying" being the most significant; for indicator of age at 65 and over, 18 optimized countries were with "low physical activity" having the greatest impact, 98 low deterioration countries were with "drug use" being the most significant; 88 high deterioration countries were with "occupational risk" being the most significant. Second, for females, for indicator of age at birth, 6 optimized countries were with "drug use" having the greatest impact, 107 low deterioration countries were with "child and maternal malnutrition" being the most significant; 91 high deterioration countries were with "drug use" being the most significant; for indicator of age at 65 and over, 14 optimized countries were with "occupational risks" having the greatest impact, 109 low deterioration countries were with "occupational risk" being the most significant; 81 high deterioration countries were with "drug use" being the most significant. Conclusions Based on the results, it suggested that the policy need to focus on the facts of drug use, occupational risk and low physical activity to narrow the gap between life expectancy and health life expectancy.