Health expectancy is an essential population health indicator and can be used to monitor changes and/or assess differences in population health. This article provides a brief overview of health expectancy and the issues to be considered in operationalizing and interpreting health expectancy. The article introduces the concept of health expectancy, discusses measures used to compute health expectancy, and methods of calculation. The discussion of measures relates health expectancy to the concept of "health" and clarifies that values of health expectancy depend on how "health" is defined. Software available to compute health expectancy including IMaCh, SPACE and ELECT are also briefly introduced.

The methods and materials of health expectancy

To estimate the age-standardized incidence, prevalence, and mortality rates of autoimmune diseases including rheumatoid arthritis (RA), inflammatory bowel disease (IBD), multiple sclerosis (MS), type 1 diabetes mellitus (T1DM), asthma, and psoriasis in women of childbearing age from 1990 to 2019, and to further analyze their changing trends, at global, regional, and national levels.Women of childbearing age was defined as 15-49 years old. The estimates and 95% uncertainty intervals (UIs) for case number of RA, IBD, MS, T1DM, asthma and psoriasis in seven age groups (15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49 years) were extracted from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Age standardization by direct method was adopted to estimate the age-standardized incidence, prevalence, and mortality rates of these autoimmune diseases in women of childbearing age. Joinpoint regression analysis was utilized to analyze the changing trends of estimated age-standardized incidence, prevalence, and mortality rates from 1990 to 2019 by calculating the average annual percentage change (AAPC) and its 95% confidence intervals (CIs).In 2019, the estimated global age-standardized incidence, prevalence, and mortality rates of RA in women of childbearing age was 17.13 (95% UI: 12.39 to 22.60), 215.86 (95% UI: 179.04 to 259.70), and 0.06 (95% UI: 0.04 to 0.08); of IBD was 5.85 (95% UI: 4.72 to 7.12), 63.54 (95% UI: 53.50 to 74.37), and 0.11 (95% UI: 0.08 to 0.13); of MS was 1.63 (95% UI: 1.05 to 2.28), 28.74 (95% UI: 23.80 to 34.46), and 0.17 (95% UI: 0.14 to 0.27); of T1DM was 6.22 (95% UI: 2.75 to 11.50), 290.51 (95% UI: 221.39 to 370.19), and 0.63 (95% UI: 0.48 to 0.78); of asthma was 291.14 (95% UI: 157.06 to 468.78), 2796.25 (95%UI: 1987.07 to 3842.97), and 1.42 (95% UI: 1.12 to 1.75), respectively. The estimated global age-standardized incidence and prevalence rates of psoriasis in women of childbearing age was 58.68 (95% UI: 51.04 to 66.85) and 477.20 (95% UI: 440.30 to 515.76). Highest disease burden generally exists in Region of the Americas and European Region. From 1990 to 2019, the estimated global age-standardized incidence and prevalence rates of RA (AAPC: 0.18, 95% CI: 0.11 to 0.24; AAPC: 0.24, 95% CI: 0.18 to 0.30) and T1DM (AAPC: 1.47, 95% CI: 1.40 to 1.54; AAPC: 0.83, 95% CI: 0.79 to 0.88) in women of childbearing age showed significantly increasing trends whereas those of IBD (AAPC: -0.76, 95% CI: -0.80 to -0.73; AAPC: -0.65, 95% CI: -0.70 to -0.60), MS (AAPC: -0.20, 95% CI: -0.23 to -0.16; AAPC: -0.25, 95% CI: -0.26 to -0.23), asthma (AAPC: -0.53, 95% CI: -0.60 to -0.47; AAPC: -0.74, 95% CI: -0.81 to -0.68), and psoriasis (AAPC: -0.83, 95% CI: -0.85 to -0.82; AAPC: -0.99, 95% CI: -1.02 to -0.96) showed significantly decreasing trends. Favorably, the estimated global age-standardized mortality rate of RA (AAPC: -1.32, 95% CI: -1.63 to -1.01), IBD (AAPC: -0.95, 95% CI: -1.06 to -0.84), MS (AAPC: -0.96, 95% CI: -1.12 to -0.80), T1DM (AAPC: -1.05, 95% CI: -1.21 to -0.89), and asthma (AAPC: -2.27, 95% CI: -2.34 to -2.19) in women of childbearing age all declined. The changing trends of estimated age-standardized incidence, prevalence, and mortality rates varied significantly across 204 countries and territories.Our study provides an accurate estimation on the age-standardization of disease indicators of autoimmune diseases in women of childbearing age. There are remarkable disparities in the incidence, prevalence, and mortality burden related to autoimmune diseases in women of childbearing age, as well as their changing trends across the world, suggesting that each individual government should establish flexible health policies and make reasonable source allocation to address different needs for autoimmune diseases in this population. 

Age-standardized incidence, prevalence, and mortality rates of autoimmune diseases in women of childbearing age from 1990 to 2019

To describe the burden and examine transnational inequities in overall cardiovascular disease (CVD) and ten specific CVDs across different levels of societal development.Estimates of disability-adjusted life-years (DALYs) for each disease and their 95% uncertainty intervals (UI) were extracted from the Global Burden of Diseases (GBD). Inequalities in the distribution of CVD burdens were quantified using two standard metrics recommended absolute and relative inequalities by the World Health Organization (WHO), including the Slope Index of Inequality (SII) and the relative concentration Index.Between 1990 and 2019, for overall CVD, the Slope Index of Inequality changed from 3760.40 (95% CI: 3758.26 to 3756.53) in 1990 to 3400.38 (95% CI: 3398.64 to 3402.13) in 2019. For ischemic heart disease, it shifted from 2833.18 (95% CI: 2831.67 to 2834.69) in 1990 to 1560.28 (95% CI: 1559.07 to 1561.48) in 2019. Regarding hypertensive heart disease, the figures changed from-82.07 (95% CI: −82.56 to-81.59) in 1990 to 108.99 (95% CI: 108.57 to 109.40) in 2019. Regarding cardiomyopathy and myocarditis, the data evolved from 273.05 (95% CI: 272.62 to 273.47) in 1990 to 250.76 (95% CI: 250.42 to 251.09) in 2019. Concerning aortic aneurysm, the index transitioned from 104.91 (95% CI: 104.65 to 105.17) in 1990 to 91.14 (95% CI: 90.94 to 91.35) in 2019. Pertaining to endocarditis, the figures shifted from-4.50 (95% CI: −4.64 to-4.36) in 1990 to 16.00 (95% CI: 15.88 to 16.12) in 2019. As for rheumatic heart disease, the data transitioned from-345.95 (95% CI: −346.47 to-345.42) in 1990 to-204.34 (95% CI: −204.67 to-204.01) in 2019. Moreover, the relative concentration Index for overall CVD and each specific type also varied from 1990 to 2019.There’s significant heterogeneity in transnational health inequality for ten specific CVDs. Countries with higher levels of societal development may bear a relatively higher CVD burden except for rheumatic heart disease, with the extent of inequality changing over time.

Transnational inequities in cardiovascular diseases from 1990 to 2019: exploration based on the global burden of disease study 2019

The global all-ages prevalence of epidemiologically-measured 'functional' presbyopia was estimated at 24.9% in 2015, affecting 1.8 billion people. This prevalence was projected to stabilise at 24.1% in 2030 due to increasing myopia, but to affect more people (2.1 billion) due to population dynamics. Factors affecting the prevalence of presbyopia include age, geographic location, urban versus rural location, sex, and, to a lesser extent, socioeconomic status, literacy and education, health literacy and inequality. Risk factors for early onset of presbyopia included environmental factors, nutrition, near demands, refractive error, accommodative dysfunction, medications, certain health conditions and sleep. Presbyopia was found to impact on quality-of-life, in particular quality of vision, labour force participation, work productivity and financial burden, mental health, social wellbeing and physical health. Current understanding makes it clear that presbyopia is a very common age-related condition that has significant impacts on both patient-reported outcome measures and economics. However, there are complexities in defining presbyopia for epidemiological and impact studies. Standardisation of definitions will assist future synthesis, pattern analysis and sense-making between studies. 

BCLA CLEAR Presbyopia: Epidemiology and impact.

Nutritional deficiencies remain serious medical and public health issues worldwide, especially in children. This study aims to analyze cross-country inequality in four common nutritional deficiencies (protein-energy malnutrition, dietary iron deficiency, vitamin A deficiency and iodine deficiency) among children from 1990 to 2019 based on Global Burden of Disease (GBD) 2019 data. Prevalence and disability-adjusted life years (DALYs) data as measures of four nutritional deficiency burdens in people aged 0 to 14 years were extracted from the GBD Results Tool. We analyzed temporal trends in prevalence by calculating the average annual percent change (AAPC) and quantified cross-country inequalities in disease burden using the slope index. Globally, the age-standardized prevalence rates of dietary iron deficiency, vitamin A deficiency and iodine deficiency decreased, with AAPCs of -0.14 (-0.15 to -0.12), -2.77 (-2.96 to -2.58), and -2.17 (-2.3 to -2.03) from 1999 to 2019, respectively. Significant reductions in socio-demographic index (SDI)-related inequality occurred in protein-energy malnutrition and vitamin A deficiency, while the health inequality for dietary iron deficiency and iodine deficiency remained basically unchanged. The age-standardized prevalence and DALY rates of the four nutritional deficiencies decreased as the SDI and healthcare access and quality index increased. The global burden of nutritional deficiency has decreased since 1990, but cross-country health inequalities still exist. More efficient public health measures are needed to reduce disease burdens, particularly in low-SDI countries/territories.

Cross-country health inequalities of four common nutritional deficiencies among children, 1990 to 2019: data from the Global Burden of Disease Study 2019

Aims To assess the global burden and economic inequalities in the distribution of blindness and vision loss between 1990 and 2019. Methods A secondary analysis of the Global Burden of Diseases, Injuries and Risk Factors Study (GBD) 2019. Data for disability-adjusted life-years (DALYs) due to blindness and vision loss were extracted from the GBD 2019. Data for gross domestic product per capita were extracted from the World Bank database. Slope index of inequality (SII) and concentration index were computed to assess absolute and relative cross-national health inequality, respectively. Results Countries with high, high-middle, middle, low-middle and low Socio-demographic Index (SDI) had decline of age-standardised DALY rate of 4.3%, 5.2%, 16.0%, 21.4% and 11.30% from 1990 to 2019, respectively. The poorest 50% of world citizens bore 59.0% and 66.2% of the burden of blindness and vision loss in 1990 and 2019, respectively. The absolute cross-national inequality (SII) fell from −303.5 (95% CI −370.8 to −236.2) in 1990 to −256.0 (95% CI −288.1 to −223.8) in 2019. The relative inequality (concentration index) for global blindness and vision loss remained essentially constant between 1991 (−0.197, 95% CI −0.234 to −0.160) and 2019 (−0.193, 95% CI −0.216 to −0.169). Conclusion Though countries with middle and low-middle SDI were the most successful in decreasing burden of blindness and vision loss, a high level of cross-national health inequality persisted over the past three decades. More attention must be paid to the elimination of avoidable blindness and vision loss in low-income and middle-income countries.

Persistence of severe global inequalities in the burden of blindness and vision loss from 1990 to 2019: findings from the Global Burden of Disease Study 2019

Objective To estimate the burden of potential productivity losses due to uncorrected and under-corrected presbyopia in LMICs among the working-age population in both the cross-sectional and longitudinal manner. Methods We extracted data for the prevalence of presbyopia from the Global Burden of Diseases (GBD), Injuries, and Risk Factors Study 2019. Data for the gross domestic product (GDP) per capita were extracted from the World Bank database and Central Intelligence Agency's World Factbook. We introduced life table models to construct age cohorts (in 5-year age groups) of the working-age population (aged from 40 to 64 years old) in LMICs, with simulated follow-up until 65 years old in people with and without uncorrected presbyopia. The differences in productivity-adjusted life years (PALYs) lived and productivity between these two cohorts were calculated. The potential productivity loss was estimated based on GDP per capita. The WHO standard 3% annual discount rate was applied to all years of life and PALYs lived. Results In 2019, there were 238.40 million (95% confidence interval [CI]: 150.92–346.78 million) uncorrected and under-corrected presbyopia cases in LMICs, resulting in 54.13 billion (current US dollars) (95% confidence interval [CI]: 34.34–79.02 billion) potential productivity losses. With simulated follow-up until retirement, those with uncorrected and under-corrected presbyopia were predicted to experience an additional loss of 155 million PALYs (an average loss of 0.7 PALYs per case), which was equivalent to a total loss of US$ 315 billion (an average loss of US$ 1453.72 per person). Conclusions Our findings highlight the considerable productivity losses due to uncorrected and under-corrected presbyopia in LMICs, especially in a longitudinal manner. There is a great need for the development of enabling eye care policies and programs to create access to eye care services, and more healthcare investment in the correction of presbyopia in the working-age population in LMICs. This study could provide evidences for some potential health-related strategies for socio-economic development.

Potential productivity loss from uncorrected and under-corrected presbyopia in low- and middle-income countries: A life table modeling study

Despite its curability by a simple and low-cost surgical procedure, cataract remains the leading cause—accounting for almost one-half—of all blindness in the world. The problem is particularly severe in developing countries, and with the ageing of populations and increasing life expectancy, the burden of cataract disease is expected to increase substantially in the coming years. Using a demographic approach, this study examined the prevalence of cataract and estimated lifetime with and without cataract among older adults in China, a rapidly ageing country with the world’s largest population. Data came from the 2002 Chinese Longitudinal Healthy Longevity Survey and life tables in the same year. Sullivan’s method was used. The results indicated that overall, 5.7% percent of Chinese aged 65 and over reported having cataract that is diagnosed by an ophthalmologist. Cataract increases with age, affects women more than men, and is higher in urban than rural areas. At age 65, men and women can expect on average 0.7 years (4.7%) and 1.2 years (7.3%) of remaining life with cataract, respectively. The corresponding figures for urban and rural older adults are 1.7 (9.8%) and 0.6 (4.1%) years. The prevalence rates and life expectancy with cataract were likely underestimated given the low levels of eye examinations to detect eye diseases among the Chinese, particularly in rural areas. We discussed preventive strategies to minimize the risk and delay the onset of cataract. Policy measures pertaining to availability and accessibility of cataract surgeries are further discussed.

Expected Lifetime with and without Cataract among Older Adults in China

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Persistence of severe global inequalities in the burden of blindness and vision loss from 1990 to 2019: findings from the Global Burden of Disease Study 2019

Potential productivity loss from uncorrected and under-corrected presbyopia in low- and middle-income countries: A life table modeling study

Expected Lifetime with and without Cataract among Older Adults in China