The results indicate that in the random effects model of the ratio value, the standardized regression coefficients are very close to 0 for the majority of the influencing factors that are significant. This indicates that the changing trends of ratio over time are generally not significant for most of the countries/regions. Consequently, this paper only presents and discusses the results of the analysis based on the difference value.
Sample description
Differences in life expectancy and health-adjusted life expectancy across 204 countries/regions
The characteristics of the 204 countries/regions in terms of the difference between life expectancy at birth and health-adjusted life expectancy at birth from 1990 to 2019 are outlined below (see Table 2). First, for males, the average difference between these measures is 7.97 years. No country has a difference of less than 5 years, while 199 countries have a difference between 5 and 10 years, and 5 countries have a difference of more than 10 years. Second, for females, the average difference is 10.42 years. In this case, no country has a difference of less than 5 years, while 94 countries have a difference between 5 and 10 years, and 110 countries have a difference of more than 10 years. These results show that the difference between life expectancy at birth and health-adjusted life expectancy at birth is greater for females than for males. This suggests that the duration of unhealthy years throughout the lifespan is longer for females in comparison to males.
The characteristics of the 204 countries/regions in terms of the difference between the average remaining life expectancy at age 65 and the average remaining health-adjusted life expectancy at age 65 from 1990 to 2019 are outlined below (see Table 2). First, for males, the average difference between the two is 3.53 years. Specifically, 52 countries have a difference of less than 3 years, 150 countries have a difference between 3 and 5 years, and 2 countries have a difference of more than 5 years. Second, for females, the average difference is 4.39 years. Here, 4 countries have a difference of less than 3 years, 153 countries have a difference between 3 and 5 years, and 47 countries have a difference of more than 5 years. These findings indicate that the difference between the average remaining life expectancy at age 65 and the average remaining healthy-adjusted life expectancy at age 65 is greater for females than for males. This again suggests that females experience a longer period of unhealthy years in old age compared to their male counterparts.
Table 2
The overview of difference value between life expectancy and health-adjusted life expectancy for 204 countries/regions from 1990 to 2019
| LE at birth - HALE at birth | Classification | Number of countries | RLE at 65 - RHALE at 65 | Classification | Number of countries |
Male | Mean = 7.97 SD = 5.19 | 0–5 years | 0 | Mean = 3.53 SD = 1.24 | 0–3 years | 52 |
5–10 years | 199 | 3–5 years | 150 |
Over 10 years | 5 | Over 5 years | 2 |
Female | Mean = 10.42 SD = 5.68 | 0–5 years | 0 | Mean = 4.39 SD = 1.51 | 0–3 years | 4 |
5–10 years | 94 | 3–5 years | 153 |
Over 10 years | 110 | Over 5 years | 47 |
Note: LE: life expectancy; HALE:Health-adjusted life expectancy; RLE:Average remaining life expectancy; RHALE: remaining health-adjusted life expectancy; SD: Standard deviation |
Risk factor profiles for 204 countries/regions
Following the analysis of the difference between life expectancy and health-adjusted life expectancy for the 204 countries/regions, this section shifts its focus to delineating the trends in the difference between the two metrics. The objective is to provide an overall view of how life expectancy and health-adjusted life expectancy have evolved over time among different countries. To this end, all 204 countries/regions are categorized into three groups: optimized countries, low deterioration countries, and high deterioration countries.
Table 3 presents the results of the interaction analysis between the three types of countries and risk factors for males. There are two main findings. First, in terms of the trend in the difference between life expectancy and health-adjusted life expectancy at birth, there are 8 countries in the first category, 98 countries in the second category, and 98 countries in the third category. This indicates that, over the entire lifespan, only 8 countries experienced a reduction in the duration of unhealthy years from 1990 to 2019. There are significant disparities between the three categories of countries on four risk factors: "unsafe water," "other environmental risks," "high LDL cholesterol," and "high body-mass index." Second, in terms of the trend in the difference between average remaining life expectancy and average remaining health-adjusted life expectancy at age 65, 18 countries are in the first category, 98 countries are in the second category, and 88 countries are in the third category. This indicates that for the elderly, the time spent being unhealthy decreased in only 18 countries from 1990 to 2019. There are significant differences between the three categories of countries on five risk factors: "unsafe water," "air pollution," "other environmental risks," "high fasting blood glucose," and "high LDL cholesterol".
Table 3
The overview of risk factor scores for three categories countries/regions for males
Risk Factors | Male |
Level 1 | Level 2 | Age 0 | Age 65+ |
I | II | III | I | II | III |
A.Environmental/occupational risks | A1. Unsafe water | 50.26** | 39.12** | 35.34** | 43.86** | 50.62** | 22.17** |
A2.Air pollution | 32.78 | 32.66 | 31.18 | 38.87** | 44.89** | 26.82** |
A3.Non-optimal temperature | 26.71 | 25.41 | 27.91 | 27.26 | 25.03 | 28.34 |
A4.Other environmental risks | 49.69** | 43.39** | 44.42** | 90.81** | 87.05** | 82.49** |
A5.Occupational risks | 4.21 | 3.76 | 3.97 | 2.70 | 2.71 | 2.56 |
B.Behavioral risks | B1.Child and maternal malnutrition | 1.37 | 1.79 | 1.73 | -- | -- | -- |
B2. Tobacco | 24.97 | 26.99 | 26.83 | 24.04 | 19.58 | 23.32 |
B3. Alcohol use | 12.62 | 10.39 | 10.79 | 8.81 | 7.12 | 10.60 |
B4. Drug use | 0.18 | 0.17 | 0.19 | 0.04 | 0.04 | 0.04 |
B5. Dietary risks | 42.85 | 41.18 | 39.80 | 38.89 | 40.07 | 40.66 |
B6. Intimate partner violence | -- | -- | -- | -- | -- | -- |
B7. Childhood sexual abuse and bullying | 7.56 | 8.01 | 8.40 | 3.69 | 4.43 | 3.48 |
B8. Low physical activity | 2.97 | 3.02 | 4.22 | 5.79 | 6.61 | 7.58 |
C.Metabolic risks | C1.High fasting plasma glucose | 8.95 | 12.05 | 11.66 | 27.29** | 30.12** | 32.55** |
C2. High LDL cholesterol | 28.51** | 31.77** | 34.46** | 38.34** | 38.97** | 47.49** |
C3. High systolic blood pressure | 27.69 | 30.75 | 29.13 | 53.75 | 51.09 | 52.20 |
C4. High body-mass index | 14.67** | 19.01** | 19.20** | 16.04 | 15.11 | 19.47 |
C5. Low bone mineral density | 12.47 | 11.43 | 11.87 | 19.41 | 19.94 | 16.18 |
C6. Kidney dysfunction | 23.27 | 21.60 | 19.77 | 39.93 | 38.12 | 44.30 |
Number of countries | 8 | 98 | 98 | 18 | 98 | 88 |
Note: I. Optimised countries, II. Low deterioration countries, III. High deterioration countries, the same below. **indicates p < 0.05. "--" indicates that the indicator does not apply to this category, the same below. |
Table 4 presents the results of the interaction analysis between the three categories of countries and risk factors for females. There are two main findings. First, in terms of the trend in the difference between life expectancy and health-adjusted life expectancy at birth, 6 countries are in the first category, 107 countries are in the second category, and 91 countries are in the third category. This suggests that, across the entire lifespan, only 6 countries experienced a reduction in unhealthy time from 1990 to 2019. There are significant differences between the three categories of countries on five risk factors: "unsafe water," "air pollution," "other environmental risks," "tobacco," and "high LDL cholesterol." Second, in terms of the trend in the difference between average remaining life expectancy and average remaining health-adjusted life expectancy at age 65, 14 countries are in the first category, 109 countries are in the second category, and 81 countries are in the third category. This indicates that, for the elderly age group, only 14 countries experienced a decrease in unhealthy time from 1990 to 2019. There were significant differences among the three categories of countries on six risk factors: "unsafe water," "air pollution," "other environmental risks," "tobacco," "high LDL cholesterol," and "kidney dysfunction."
Table 4
The overview of risk factor scores for three categories of countries/regions for females
Risk Factors | Female |
Level 1 | Level 2 | Age 0 | Age 65+ |
I | II | III | I | II | III |
A.Environmental/occupational risks | A1. Unsafe water | 74.44** | 60.92** | 61.66** | 77.72** | 71.64** | 45.39** |
A2.Air pollution | 40.44** | 27.94** | 35.22** | 46.75** | 42.75** | 23.82** |
A3.Non-optimal temperature | 28.95 | 25.95 | 27.34 | 26.81 | 25.00 | 28.84 |
A4.Other environmental risks | 50.01** | 29.83** | 36.15** | 89.02** | 73.16** | 65.89** |
A5.Occupational risks | 2.46 | 2.35 | 2.41 | 2.00 | 1.66 | 1.51 |
B.Behavioral risks | B1.Child and maternal malnutrition | 18.09 | 16.75 | 17.70 | -- | -- | -- |
B2. Tobacco | 16.81** | 23.37** | 21.69** | 3.17** | 5.07** | 8.27** |
B3. Alcohol use | 1.57 | 4.12 | 3.80 | 2.04 | 2.09 | 4.36 |
B4. Drug use | 0.11 | 0.12 | 0.13 | 0.04 | 0.04 | 0.05 |
B5. Dietary risks | 37.02 | 34.18 | 33.03 | 33.90 | 34.82 | 33.38 |
B6. Intimate partner violence | 19.66 | 22.62 | 24.08 | 21.84 | 23.70 | 16.74 |
B7. Childhood sexual abuse and bullying | 7.23 | 7.73 | 7.10 | 2.26 | 2.69 | 2.22 |
B8. Low physical activity | 1.48 | 4.01 | 4.87 | 4.36 | 6.77 | 8.22 |
C.Metabolic risks | C1.High fasting plasma glucose | 10.58 | 11.09 | 10.29 | 24.72 | 27.93 | 28.43 |
C2. High LDL cholesterol | 29.21** | 35.86** | 34.82** | 38.55** | 43.26** | 52.97** |
C3. High systolic blood pressure | 28.91 | 27.97 | 26.60 | 57.92 | 57.84 | 57.01 |
C4. High body-mass index | 20.36 | 24.46 | 21.92 | 20.25 | 21.64 | 26.72 |
C5. Low bone mineral density | 21.18 | 20.03 | 21.52 | 36.16 | 37.53 | 31.21 |
C6. Kidney dysfunction | 22.27 | 22.76 | 21.32 | 35.82** | 42.55** | 49.12** |
Number of countries | 6 | 107 | 91 | 14 | 109 | 81 |
Note: **indicates p < 0.05. |
Analysis of influencing factors
This study aimed to examine how risk factors influenced the difference between life expectancy and health-adjusted life expectancy among 204 countries/regions from 1990 to 2019. Given that 30-year follow-up data was available for each country, panel models were used for the analysis. Panel models typically consist of three types: mixed effects models, fixed effects models, and random effects models. To determine the most appropriate model for each panel data analysis, we conducted two-by-two comparisons among the three models using F-tests, BP-tests, and Hausman tests. Based on the results of these tests, the random effects model was found to be the most suitable for the panel data in this paper. The results of the data analysis presented in the subsequent sections are all based on this method.
The results of the random effects model of the influence of risk factors on the difference between life expectancy and health-adjusted life expectancy for males at birth for the three categories of countries (see Table 5) showed the following. First, for the optimized countries, the risk factor with the largest effect is "drug use" (with a standardized regression coefficient of 0.855), followed by "child and maternal malnutrition" (0.521), with "low physical activity" (0.334), and "low bone mineral density" (0.303) also having a large effect. Second, for low deterioration countries, the risk factor with the highest impact is "low physical activity" (0.131), followed by "high fasting blood glucose" (0.020), and "high body-mass index" (0.022). Third, for high deterioration countries, the most influential risk factor is "childhood sexual abuse and bullying" (0.147), followed by "high fasting blood glucose" (0.073). These results show that, for the first group of countries, behavioral and metabolic risk factors have a greater impact, for the second group of countries, the impact of metabolic risks is greater, while for the third group of countries, environmental/occupational risks have more influence.
The results of the random effects model of the influence of risk factors on the difference between life expectancy and health-adjusted life expectancy for females at birth for the three categories of countries (see Table 5) showed the following. First, for the optimized countries, the risk factor with the greatest influence is "drug use" (0.827), followed by "alcohol use" (0.784), "low physical activity" (0.776), and "childhood sexual abuse and bullying" (0.770). Second, for low deterioration countries, the highest impact risk is "child and maternal malnutrition" (0.152), followed by "alcohol use" (0.051). Third, for high deterioration countries, the most influential risk factor is "drug use" (0.695), followed by "childhood sexual abuse and bullying" (0.201). These results show that environmental/occupational and behavioral risks are more influential for the first group of countries, while behavioral risks are more influential for the second group of countries. Behavioral risks are also more influential for the third group of countries.
Table 5
Random effects model of risk factors influencing the difference value between life expectancy and health-adjusted life expectancy at birth
| Male | Female |
| I | II | III | I | II | III |
Intercept | -4.147 | 7.918** | 10.766** | 38.449** | 13.846** | 12.960** |
A1. Unsafe water | 0.021** | -0.005 | 0.022** | 0.094** | -0.015 | -0.018 |
A2.Air pollution | 0.045 | 0.002 | 0.024** | 0.082** | 0.002 | -0.010 |
A3.Non-optimal temperature | 0.035** | -0.001 | 0.029** | 0.032** | -0.003 | -0.024 |
A4.Other environmental risks | -0.010 | 0.016** | 0.026** | 0.130** | 0.016** | -0.008 |
A5.Occupational risks | -0.172 | -0.080 | -0.261 | 0.531** | -0.086 | -0.175 |
B1.Child and maternal malnutrition | 0.521** | -0.080 | -0.083 | 0.557** | 0.152** | 0.101** |
B2. Tobacco | 0.077** | -0.019 | -0.019 | 0.408** | 0.030** | -0.013 |
B3. Alcohol use | 0.086 | 0.016 | 0.031 | 0.784** | 0.051** | 0.023 |
B4. Drug use | 0.855** | -0.543 | -0.267 | 0.827** | -0.583 | 0.695** |
B5. Dietary risks | 0.084 | 0.003 | 0.044** | 0.104** | 0.004 | -0.032 |
B6. Intimate partner violence | -- | -- | -- | 0.188** | 0.006 | -0.014 |
B7. Childhood sexual abuse and bullying | 0.049** | -0.022 | 0.147** | 0.770** | -0.048 | 0.201** |
B8. Low physical activity | 0.334** | 0.131** | -0.011 | 0.776** | -0.010 | 0.050 |
C1.High fasting plasma glucose | 0.083** | 0.020** | 0.073** | -0.014 | 0.005 | 0.063 |
C2. High LDL cholesterol | 0.032 | -0.002 | 0.016** | -0.198 | -0.002 | -0.029 |
C3. High systolic blood pressure | 0.118** | 0.006 | -0.002 | 0.125** | -0.010 | 0.006 |
C4. High body-mass index | 0.105** | 0.022** | 0.020 | 0.111 | 0.025** | 0.033 |
C5. Low bone mineral density | 0.303** | 0.014 | 0.022 | 0.616** | 0.036 | 0.089 |
C6. Kidney dysfunction | 0.233** | -0.008 | 0.048 | 0.004 | -0.003 | 0.021 |
Sample size/number of countries | 240/8 | 2940/98 | 2940/98 | 180/6 | 3210/107 | 2730/91 |
R2 | 0.708 | 0.466 | 0.754 | 0.839 | 0.511 | 0.710 |
Note: **indicates p < 0.05. |
The results of the random effects model of the influence of risk factors on the difference between average remaining life expectancy and average remaining health-adjusted life expectancy for males at age 65 for the three categories of countries (see Table 6) showed the following. First, for the optimized countries, the risk factor with the greatest influence is "low physical activity" (0.105), followed by "non-optimal temperature" (0.071), and "alcohol use" (0.055). Second, for the low deterioration countries, the most influential risk factor is "drug use" (0.802), followed by "occupational risk" (0.228). Third, for the high deterioration countries, the most influential risk factor is "occupational risk" (0.254), followed by "high fasting blood glucose" (0.024), "high body-mass index" (0.023), and "air pollution" (0.022). These results show that environmental/occupational and behavioral risks are more influential for the first group of countries. Metabolic risks are more influential for the second group, and environmental/occupational and metabolic risks are more influential for the third group.
The results of the random effects model of the influence of risk factors on the difference between average remaining life expectancy and average remaining health-adjusted life expectancy for females at age 65 for the three categories of countries (see Table 6) showed the following. First, for the optimized countries, the risk factor with the greatest influence is "occupational risk" (0.624), followed by "childhood sexual abuse and bullying" (0.536). Second, for the low deterioration countries, the most influential risk factor is "occupational risk" (0.251), followed by "tobacco" (0.027). Third, for the high deterioration countries, the most influential risk factor is "drug use" (0.692), followed by "occupational risk" (0.336). These results show that environmental/occupational risks and metabolic risks are more influential for the first group of countries. Metabolic risks are more influential for the second group of countries, and environmental/occupational risks and behavioral risks are more influential for the third group of countries.
Table 6
Random effects model of risk factors influencing the difference value between average remaining lifespan and average healthy remaining lifespan at age 65
| Male | Female |
| I | II | III | I | II | III |
Intercept | 1.008** | 2.553** | 5.387** | 9.186** | 5.207** | 7.559** |
A1. Unsafe water | -0.010 | -0.000 | 0.014** | 0.059 | -0.005 | 0.032** |
A2.Air pollution | 0.034** | -0.002 | 0.022** | 0.019 | 0.009** | -0.011 |
A3.Non-optimal temperature | 0.071** | -0.003 | 0.013** | 0.021** | -0.006 | 0.015** |
A4.Other environmental risks | 0.011 | 0.003 | -0.007 | 0.023** | -0.001 | 0.009** |
A5.Occupational risks | -0.096 | 0.228** | 0.254** | 0.624** | 0.251** | 0.336** |
B1.Child and maternal malnutrition | -- | -- | -- | -- | -- | -- |
B2. Tobacco | 0.002 | -0.006 | 0.019** | -0.078 | 0.027** | 0.033** |
B3. Alcohol use | 0.055** | -0.003 | -0.005 | -0.126 | 0.020 | -0.016 |
B4. Drug use | -0.610 | 0.802** | 0.645 | 0.375 | 0.786 | 0.692** |
B5. Dietary risks | -0.002 | -0.002 | -0.021 | -0.002 | -0.004 | 0.022** |
B6. Intimate partner violence | -- | -- | -- | 0.003 | 0.007** | -0.004 |
B7. Childhood sexual abuse and bullying | 0.027 | 0.058 | 0.055 | 0.536** | 0.018 | -0.138 |
B8. Low physical activity | 0.105** | 0.046 | 0.023 | -0.111 | 0.001 | 0.062** |
C1.High fasting plasma glucose | 0.012 | 0.005 | 0.024** | -0.007 | -0.000 | 0.011 |
C2. High LDL cholesterol | 0.023** | 0.002 | -0.011 | 0.073** | 0.011** | -0.007 |
C3. High systolic blood pressure | 0.003 | 0.001 | -0.004 | 0.024** | 0.004** | 0.008 |
C4. High body-mass index | 0.000 | 0.017** | 0.023** | -0.006 | 0.009** | 0.010 |
C5. Low bone mineral density | 0.009 | 0.006 | 0.012 | 0.028 | 0.001 | -0.002 |
C6. Kidney dysfunction | -0.002 | 0.010** | 0.015** | 0.088** | 0.009** | 0.017** |
Sample size/number of countries | 540/18 | 2940/98 | 2640/88 | 420/14 | 3270/109 | 2430/81 |
R2 | 0.836 | 0.557 | 0.794 | 0.708 | 0.508 | 0.753 |
Note: **indicates p < 0.05. |