International Journal of Public Health ORIGINAL ARTICLE published: 24 August 2022 doi: 10.3389/ijph.2022.1604946 Gender Gap in Unhealthy Life Expectancy: The Role of Education Among Adults Aged 45+ Aïda Solé-Auró 1*, Pilar Zueras 2,3, Elisenda Rentería 2 and Mariona Lozano 2 1 Department of Political and Social Sciences, Pompeu Fabra University, Barcelona, Spain, 2Center for Demographic Studies, Autonomous University of Barcelona, Barcelona, Spain, 3Institute for Social and Economic Research, Colchester, United Kingdom Objectives: This paper examines the gender gap in unhealthy life expectancy across education levels and age in Spain to understand the extent to which the gender paradox exists over education and across ages. Methods: Death registrations and vital status were taken from the Spanish Statistical Office, while the three health measures (chronic conditions, bad-self rated health and cognitive impairment) from the 2019 European Health Interview Survey. We used Sullivan’s method to compute unhealthy life expectancy by education level. We computed the gender and the education ratios of the proportion of unhealthy life years in each health measure by education and age. Results: At almost all ages and all education levels, women significantly lived longer but in poorer health than men. Marked gender differences are seen across most age-groups, particularly among the low educated. We detected greater health inequalities by education level for women (confirming the gender paradox) and a health gradient due to aging and across the health measures charting the disablement process. Edited by: Matthias Richter, Conclusion: The new education distribution might improve the unhealthy life expectancy Martin Luther University of Halle- and might reduce the gender gap in the number of years spent in poor health. Wittenberg, Germany Reviewed by: Keywords: population health, gender paradox, disablement process, education gradient, Spain Eduardo Oliveira, State Secretary of Health of Minas Gerais (SES), Brazil INTRODUCTION *Correspondence: Aïda Solé-Auró Women’s life expectancy is higher than men’s at all ages in all countries of the world. Yet, while it is aida.sole@upf.edu universally observed that male mortality exceeds that of females, studies examining gender differentials in morbidity generally find that women are in poorer health [1]; however, the Received: 24 March 2022 morbidity difference is less apparent when studying gender inequalities in unhealthy life Accepted: 28 July 2022 expectancy (UHLE) and the gender paradox (women living longer but unhealthier) might not Published: 24 August 2022 be universal. Three general groups can be used to clarify the sex differences explanations in (un) Citation: healthy expectancies: biological factors, lifestyle behaviors and social profiles. For instance, variations Solé-Auró A, Zueras P, Rentería E and in the gender health gap exist by age, time, country context [2, 3], and when using different health Lozano M (2022) Gender Gap in Unhealthy Life Expectancy: The Role of indicators [4]. Differences are also observed by education levels. In fact, education might contribute Education Among Adults Aged 45+. to the reduction of the gender paradox by acting in the less favored groups [5]. Overall, women Int J Public Health 67:1604946. present worse health conditions than men [6] as well as more intensive health care utilization [7]. doi: 10.3389/ijph.2022.1604946 Potential gender health differences in the use of different types of health measures (self-reported or Int J Public Health | Owned by SSPH+ | Published by Frontiers 1 August 2022 | Volume 67 | Article 1604946 Solé-Auró et al. Gender Gap in UHLE diagnosed) should be considered. Researchers have debated on National Registry of deaths by sex, age group, and level of whether gender differences in reporting general health status and educational attainment. We chose to use the 2019 figures health conditions can bias non-objective health indicators and because it is the year previous to the COVID-19 pandemic increase gender health differentials, although the general [19]. Second, the 2019 Spanish population by ten-year age conclusion is that they are unlikely to be the main explanation [4]. groups and gender was obtained from the INE records for This work examines gender differences in UHLE based on 45 to 85+ year-olds. We have not used five-year age groups as diagnosed and self-reported health indicators by education level they do not guarantee a sufficient sample size by gender and in Spain. Disparities in health measures by sex and education over education level. Finally, we calculated the prevalence of each of the life course confirm the relevance of this approach. our three health indicators by ten-year age groups using We consider education as a social determinant of health. In microdata from the 2019 European Health Interview Survey in general, those with higher levels of education present longer life Spain (EHIS), a cross-sectional survey representative of the non- expectancies, lower mortality rates, and lower burdens of disease institutionalized population. [8–10]. Therefore, higher-educated people are more likely to have better access to the knowledge of healthy lifestyles (i.e. higher Variables quality food) and, at the same time, education reflects the capacity We used three health status indicators to compute gender to have access to better health care. It is well documented that differences in UHLE based on the EHIS questionnaire. The European women have experienced a large expansion of their importance of studying these indicators is key for educational attainment during the second half of the 20th understanding the appearance and the duration in life of century. However, this achievement does not seem to be different health measures while aging. First, we used self- reflected in a reduction of gender health inequalities, perceived health over the previous 12 months, the original suggesting that the relationship between education and health question being: “How is your health in general? Is it very differs by gender. For instance, absolute health inequalities by good, good, regular, bad or very bad?“. We grouped these five education level are more evident among women [11]. In addition, responses into two categories: good (very good and good) (coded women with low education levels are the ones in the poorest as 0) and poor health (regular, bad, and very bad) (coded as 1). health [10], and Spain is no exception [12–15]. Second, we analyzed the presence or absence of chronic Socioeconomic differences in mortality levels in Europe have conditions and risk factors. In line with Zueras and Renteria’s historically been lowest in Spain [16, 17], yet they are among the [20] study of trends in healthy life expectancy in Spain, we used highest when considering morbidity measures [13, 17, 18]. an indicator that includes the following conditions: cancer, Specifically, Solé-Auró et al. [14] observed that in 2012 older stroke, myocardial infarction, heart disease, hypertension, Spanish adults presented a marked education gradient in healthy diabetes and high cholesterol, chronic low back and neck pain, life expectancies. This gradient was larger for women in terms of asthma and chronic obstructive pulmonary disease. We the expected number of years living in poor health, despite their considered individuals as presenting the health condition advantage in terms of life expectancy for all levels of education. when they answered affirmatively to all three questions: “Have Similarly, Blanes and Trias-Llimós [15] found a greater you ever suffered from ‘this specific health condition?”, “Have disadvantage of healthy life expectancy for women at age you had it in the last 12 months?” and “Has a doctor told you that 30 in 2019. you have it?”. Our last health measure concerns cognitive Overall, our study aims to examine in depth female-male impairment for which respondents were asked “Do you have differences in UHLE by education status in Spain for middle-aged difficulties remembering or concentrating?”. We dichotomized and older people. Interestingly, we used three health indicators the four possible answers into two categories: cognitively that allow us to provide a more complete view of the appearance impaired (coded as 1) for those declaring themselves as having of several health outcomes while aging. This is of considerable “some difficulty,” “a lot of difficulty” or “cannot do at all” and not relevance to the aging process and ties in closely with the study cognitively impaired (coded as 0) for those reporting no reported here as we also seek to highlight the need for a full difficulties. understanding of health deterioration over the life-course by Here, education serves as our indicator of socioeconomic measures that generally follow on consecutively over the status on the grounds that, first, it is more likely to remain process. Thus, we studied the variation of the gender gap in constant during an adult lifespan and is easily measured for all health expectancy using three health measures and two levels of individuals, even the economically inactive; second, it has been education in an effort to identify the main inequalities in the age- relatively well reported in questionnaires and survey data; and, range considered. third, the likelihood of reverse causation between education and health at older ages is lower than that between income/occupation and health [21]. We classified our respondents into two groups in METHODS line with the International Standard Classification of Education: First, “Low Education,” corresponding to those with compulsory Study Population education or lower, which includes the first stage of secondary We drew on three data sources provided by the Spanish Statistical education, primary credentials, as well as illiterate individuals Office (Instituto Nacional de Estadística, INE) for individuals (codes 1 to 4 in the original data source); and, second, “High aged 45+. First, mortality data come from the 2019 Spanish Education,” corresponding to those with upper secondary, higher Int J Public Health | Owned by SSPH+ | Published by Frontiers 2 August 2022 | Volume 67 | Article 1604946 Solé-Auró et al. Gender Gap in UHLE TABLE 1 | Sample Characteristics: Sample size, mean age and standard deviation relative measure) in each state of each health measure and for the (sd), and weighted percentage of the education and health variables for Spain two education levels described to examine the magnitude of the for men and women, Age 45+ (Source: European Health Interview Survey (EHIS), Spanish Statistical Office (INE), Spain, 2019). significant differences observed in UHLE estimates. We also examined the education ratios (high/low) of the proportion of Men Women UHLE for men and women. Ratios above one indicate that men Sample Size (N) 6,899 8,111 (or the highly educated) spend a larger proportion of their Mean Age 61.6 63.2 remaining life in a certain health state, whereas ratios below SD Age 11.89 12.84 one indicate that women (or the poorly educated) spend a larger Low Education (in %) 31 37 proportion in that health state. High Education (in %) 69 63 Health variables (in %) Chronic conditions 57 61 Bad Self-rated health 30 39 RESULTS Cognitive Impairment 12 18 Source: European Health Interview Survey (EHIS), Spanish Statistical Office (INE), 2019. Descriptive findings are reported in Table 1 and Figure 1. Table 1 presents the sample characteristics for the entire Spanish population aged 45+ by gender. The sample includes more secondary credentials, vocational training, and university degrees women than men. The overall mean age is around 61.6 for at all levels, BA graduates, masters’ and PhDs (codes 5–9) (INE). men and 63.2 for women. Education levels differ slightly To compute the life tables, we used data from EHIS to calculate between genders. In general, men present higher levels of high the weighted proportion of the presence of the three morbidity education than women (69% vs. 63%, respectively). The health measures considered, within the two education levels and prevalence of being in bad health for each health indicator is ten-year age groups, and for men and women separately. also higher for women compared to men. The statistical hypothesis test confirm that these gender differences are Statistical Analyses significant. First, we estimated life expectancy by each level of education and Figure 1 shows the prevalence of poor health among those gender for the year 2019. As our abridged life table terminates in a aged 45 to 85+, for low and high education levels. Among those large group at ages 85+, we calculated life expectancy at age 45 by with low education, women report poorer health than men on all computing the average number of years lived over this age. We three-health indicators and across all ages. Gender differences in chose 45 as it is safe to assume that for the majority of the prevalence rates are less evident among those with high levels of population their education level will not change and, moreover, education. the question concerning cognitive impairment was only put to Table 2 depicts life and UHLE for men and women by level of individuals of this age and above. Death registries presented education and age groups. Not only in all education groups but missing data on the level of education in 2% of the cases that also at all ages, women can expect to live longer than men. Not were distributed proportionally by the education levels in each surprisingly, there is a gradient in all health measures with aging, age group. When comparing our estimated life expectancy by but we also detect a gradient across the health measures used. level of education with the ones published by INE [19] we found a Thus, individuals spend more years with chronic conditions small difference, that we attribute to different methods of followed by years lived with bad self-perceived health, and imputing missing data. finally, people spend less years with cognitive impairments at We used Sullivan’s method to estimate Spanish UHLE [22, younger ages, as these only become substantially prevalent at 23]. This is a prevalence-based method for dividing life-table older ages. For example, a man with low education level aged years lived in an age interval into healthy and unhealthy years, 45 years old is expected to live 35.2 years, and from those, 21 years based on the prevalence of each health measure in each age will be lived with a chronic disease, 13.2 years with bad self- group. In this way, health expectancies are similar in their reported health, and 5.2 years with cognitive impairments. This interpretation to total life expectancy, as they indicate the health gradient pattern is consistent across age, education groups expected years lived in a state of good or bad health. The and genders. 2019 prevalence of the three health measures (EHIS) by Regarding gender gaps, women spend more years in bad education level and ten-year age groups are, therefore, health (UHLE) than men for all measures and educational extrapolated to the Spanish population data in the life table to levels through all age groups, and these differences are estimate the expected life years spent in good or bad health. We significant when comparing 95% confidence intervals (years in estimated the unhealthy expectancies by 10-year age groups good health results are available upon request). Regarding (45–54, 55 to 64, 65 to 74, 75 to 84, and 85+) and their educational differences, those with low levels of education live corresponding 95% confidence interval [24], given the more years in poor health. Both of these patterns apply at all ages importance of accounting for uncertainty when reporting and with few exceptions at advanced ages 85+. On one hand, gender interpreting healthy life expectancy estimates [25]. First, we differences in UHLE at the oldest age group with higher presented the descriptive statistics of our health measures by education are not significantly different for all the health level of education of men and women. Then we computed the measures considered. On the other hand, UHLE differences gender ratios (male/female) of the proportion of UHLE (as a between primary and secondary education are not significant Int J Public Health | Owned by SSPH+ | Published by Frontiers 3 August 2022 | Volume 67 | Article 1604946 Solé-Auró et al. Gender Gap in UHLE FIGURE 1 | Descriptive Statistics: Prevalence of poor health condition for men and women by education level for ten-year age groups. Individuals aged 45+ (Source: European Health Interview Survey (EHIS), Spanish Statistical Office (INE), Spain, 2019). at ages 85+ for chronic diseases among men and women, and for The smallest education gap is observed for life spent with chronic men with bad self-reported health. disease. Differences are similar for the other two measures and across age groups, with a reduction at ages 85+. For men, we see a similar pattern than for women, although women show larger Gender and Educational Gaps in Unhealthy education rations than men, except for the years spent in Life Expectancy for Each Health Measure cognitive impairments. Therefore, while individuals with high Over the Lifespan education at age 45 spend 6% (men) and 10% (women) less years Figure 2 (top panel) shows gender ratios (male/female) of the with chronic diseases, the difference is greater than 30% for the expected years living in poor health for each health measure and rest of the measures analyzed. In particular, 45 years-old men level of education within 5 age groups (45–85+). In general, with high levels of education are expected to live 42% less years women in both educational groups spend a higher proportion of with cognitive impairments than 45 years-old men with low their lives in worse health than men through all ages. The only education levels (the corresponding value for women is a exception is life expectancy with bad self-reported health at ages difference of 36%). 85+ for women with high education (although the gender gap was not significant). Thus, the gender paradox is confirmed for the two levels of education studied here. The most striking result is DISCUSSION that cognitive impairment among individuals with high education shows the largest gender differences. At age 45 men Our findings show the persistence of marked gender differences spend 15% and 11% less years with chronic diseases than women in health across most ages 45+ and among those with low with lower education and higher education, respectively. The educational attainment. In particular, we found (1) longer life corresponding ratio for years spent with cognitive impairment for women at all ages and at all levels of education, but with longer increases to 34% and 40% for men compared to women with periods subject to health problems compared to men; (2) greater lower and higher education, respectively. Overall, the gender gaps health inequalities by education level for women (except for the are similar for each health measure across age groups in both years lived with cognitive impairment); and (3) a health gradient education levels. The observed reduction of the gender gap of associated with aging as well as across the health measures. Thus, UHLE at age 85+ with chronic disease and life with cognitive we can confirm the gender paradox for all health measures, both impairment draw on non-significant gender differences educational levels, and across all ages. Regardless of age, and for (Table 2). both levels of education, women spend a higher proportion of Figure 2 (bottom panel) shows the education ratios (high/low) their lives with chronic morbidity, worse self-rated health and of the proportion of total life expectancy spent with health cognitive impairment. Our results are consistent with previous problems for men and women aged 45 to 85+. Among evidence from a comparative study including more than a dozen women, those with low levels of education spend a higher countries from Europe, Asia and America that confirmed that at proportion of their lives in worse health than those with high present women live longer than men and have more disabling levels of education for all three health measures and at all ages. chronic conditions while men have more lethal conditions [26]. Int J Public Health | Owned by SSPH+ | Published by Frontiers 4 August 2022 | Volume 67 | Article 1604946 Solé-Auró et al. Gender Gap in UHLE However, this gender gap is greater among those with primary (7.8–8.1) (6.9–7.1) (5.6–5.9) (0.6–0.6) (4.3–4.5) (3.6–3.8) (2.5–2.7) (0.4–0.5) (4–4.3) (5–5.2) TABLE 2 | Life expectancy and unhealthy life expectancy (in years) for both men and women and for low and high levels of education by ten-year age groups, Source: European Health Interview Survey (EHIS), Spanish education with the exception of cognitive impairment. Those greater gender differences might reflect the lower employment rate and higher precariousness among Spanish women [27] 7.9 7.0 5.7 4.1 0.6 5.1 4.4 3.7 2.6 0.4 CI Women among those with lower education, reflected in their greater involvement in care work across their life-course [28]. (5.1–5.3) (4.4–4.6) (2.7–2.8) (0.4–0.5) (2.6–2.6) (2.1–2.2) (1.4–1.5) (0.4–0.4) The socioeconomic differences observed here go in the (3.8–4) (3–3.1) Years Cognitive impairment expected direction. Those with low education levels spend more years in worse health than those with high education, a finding that holds across all ages. When comparing each 3.03 2.60 2.19 1.46 0.40 5.2 4.5 3.9 2.8 0.5 CI health measure, the education ratios are lower when measuring the presence of chronic diseases. This might be attributable to Men the lower frequency of use of medical/health services by (17.4–18.1) (14.7–15.2) (10.9–11.3) (11.7–12.1) (9.6–10.1) (6.5–6.9) (0.7–0.7) (7.1–7.5) (4.1–4.4) (0.5–0.6) Years individuals with low education levels [29, 30], making them less likely to receive a diagnosis. Previous research has shown that women experience greater socioeconomic inequalities in morbidity measures [18], but gender inequalities across the 17.8 15.0 11.1 11.9 6.7 0.7 9.9 7.3 4.3 0.5 CI social gradient are not often the focus of analysis. Our findings indicate that educational attainment is more beneficial for Women Years with health problems(UHLE) women than it is for men in terms of the proportion of life (12.9–13.5) (10.7–11.2) Bad self-reported health (7.8–8.2) (0.6–0.6) (7.3–7.6) (5.3–5.6) (3.2–3.5) (0.5–0.6) (5–5.4) (8.7–9) Years spent in good health, as the gains of increasing education are greater, with the exception of cognitive impairment. Our results suggest that both gender and education gaps in cognitive impairment reflect the better situation of high 13.2 11.0 8.0 5.2 0.6 8.8 7.4 5.4 3.4 0.6 CI educated men compared to any other education and gender group, consistent with the lower prevalence observed, whether Men (24.3–25.2) (20.6–21.3) (14.9–15.4) (21.9–22.6) (13.2–13.9) it responds to their better cognitive status or their better self- (18.2–19) (8.2–8.5) (0.9–0.9) (7.2–7.8) (0.8–0.9) Years reported performance. Both morbidity and mortality patterns by gender and education might explain the observed relative advantage of high-educated men. These finding merits further research. 24.7 20.9 15.2 22.3 18.6 13.5 8.4 0.9 7.5 0.8 CI Here, for the first time in Spain, we have estimated life expectancy with cognitive impairment [31], a growing social Women (20.5–21.4) (12.8–13.3) (19.5–20.1) (11.9–12.5) concern given its associations with dementia and increased (17.3–18) (16.3–17) (7.1–7.5) (0.7–0.8) (6.5–7.1) (0.7–.8) Years Chronic Condition dependency among the expanding older population where it represents a major care burden. We found that lower educated Source: European Health Interview Survey (EHIS), Spanish Statistical Office (INE), 2019. men and women live more years with cognitive impairment despite leading shorter lives. These educational differences in 21.0 17.7 13.1 19.8 16.7 12.2 7.3 0.8 6.8 0.8 CI life expectancy with cognitive impairment are consistent with previous research [32]. The marked differences found here, Men (40.8–40.8) (31.6–31.7) (22.9–22.9) (14.5–14.5) (42.7–42.7) (33.2–33.2) (24.1–24.1) (15.5–15.5) particularly among women, reflect the important role of (7.5–7.5) (8.0–8.0) Years education in delaying the onset of, and shortening, cognitive decline [33, 34]. This indicator is expected to improve as better-educated younger cohorts age. Indeed, the greater expansion of education among Spanish female cohorts 40.8 31.6 22.9 14.5 7.46 42.7 33.2 24.1 15.5 8.03 CI may have a marked impact, even if age-specific prevalence is not reduced. Thus, we must be cautious when interpreting any Women (28.2–28.22) (35.2–35.2) (23.5–26.5) (18.7–18.8) (11.9–11.9) (37.3–37.4) (19.9–19.9) (12.6–12.6) improvements in future trends of life expectancy with (6.3–6.3) (6.6–6.6) Statistical Office (INE), Spain, 2019. Years cognitive impairment in Spain as they might reflect a Life Expectancy Note: CI are Confident Intervals. change in the educational composition of the population rather than in adult cognitive ability as they age. Our most relevant contribution is the comparison of gender 37.37 28.21 19.93 12.58 Secondary or more 35.2 26.5 18.8 11.9 6.3 6.6 CI and educational ratios of UHLE for different health measures Primary or less and age groups among adults aged 45-plus. In sensitivity Men analysis, we performed the same analysis for years spent with 45–54 55–59 65–74 75–84 45–54 55–59 65–74 75–84 Years 85+ 85+ activity limitation, measured from the Global Activity Limitation Index (GALI), and results were very similar to Int J Public Health | Owned by SSPH+ | Published by Frontiers 5 August 2022 | Volume 67 | Article 1604946 Solé-Auró et al. Gender Gap in UHLE FIGURE 2 | Ratios of the proportion of unhealthy life expectancy by gender and education. Individuals aged 45+ (Source: European Health Interview Survey (EHIS), Spanish Statistical Office (INE), Spain, 2019). those from the more general measure of self-rated health as they are more likely to suffer the deteriorating sequelae of (results upon request). As we have seen, the selected health these diseases [36]. measures used here present a gradient by age which, despite the Three potential limitations that might affect our results cross-sectional nature of our study, reflects the aging (disabilty) should be mentioned. First, our study employs cross- process [35]—starting with chronic conditions and progressing sectional data and draws on different data sources. The with bad self-reported health, (disability problems, as sensitivity latter leaves our results open to the possible risks analysis revealed) and culminating in cognitive associated with the distribution of deaths by level of impairments–that only becomes substantially prevalent at education, which might be slightly different to the method older ages. Across middle and older ages, gender ratios are used by INE [35], although observed differences were very more strongly negative for women for measures that capture a small (less than 1%). Second, the subjective (self-reported) more acute level of disability. Therefore, morbidity and health measures used might be sensitive to potential bias mortality outcomes suggest that health interventions aimed caused by gender differences in reporting styles [7]. at delaying the onset of disease would benefit men more than Moreover, self-reported measures might be sensitive to the women, while practices that reduce health deterioration level of development (social, economic and cultural). Partly, associated with disease would be more beneficial for women, we have tried to address this potential shortcoming by Int J Public Health | Owned by SSPH+ | Published by Frontiers 6 August 2022 | Volume 67 | Article 1604946 Solé-Auró et al. Gender Gap in UHLE combining self-reported and diagnosed health measures. results. All authors provided critical revisions in content, data Finally, the data sources used do not include the analysis and interpretation, and manuscript revision. institutionalized older population and they are not included in our surveys. This might result in the underestimation of the real magnitude of some findings, FUNDING particularly among those aged 85+. Despite these limitations, this study highlights the important The authors acknowledge funding from different sources. AS-A role played by education in subjective well-being and acknowledges funding from the Department of Political and complements previous findings reported for Spain [14]. Social Sciences at Pompeu Fabra University. PZ acknowledges Specifically, it highlights that education has a more powerful funding by the Economic and Social Research Council (ESRC) impact on women’s health, particularly among older cohorts, through the Research Centre on Micro-Social Change (MiSoC) at with a higher proportion of low educated women. This result the University of Essex (ES/S012486/1), and by the Spanish applies to all measures examined here but cognitive impairment Ministry of Science, Innovation and Universities (RTI2018- where men benefit more from high education. Beyond the gender 096730-B-I00). ER acknowledges funding from the Programa gap in life expectancy, education makes a difference in both Estatal de Promoción del Talento y su Empleabilidad, objective and subjective health, which adds a new layer of Subprograma Estatal de Formación y en el Subprograma vulnerability to that already suffered by the most vulnerable Estatal de Incorporación: Ayudas para Contratos Ramón y [37]. This study reaffirms the need to address educational and Cajal 2017 [grant number RYC-2017-22586], and was gender health inequalities in adult age to ensure a better quality of supported by the H2020-ERC-2019-CoG-GA No 864616- life in old age. HEALIN Project and from CERCA Programme Generalitat de To conclude, our results support the argument that the Catalunya. ML acknowledges funding from the Spanish Ministry changing distribution of education should improve the healthy of Science and Innovation, National R&D; I Plan QUALYLIFE life expectancy of the total population and reduce the gender gap (PID2019-111666RJ-I00), GLOBFAM (RTI2018-096730-B-I00) in the number of years spent in poor health. However, while we and COMORHEALTHSES (PID2020-113934RB-I00); and await the arrival of more educated cohorts, reducing poor health support from CERCA Programme Generalitat de Catalunya. for all, but especially women with primary or less education, should be a priority in contributing to active aging and delaying the disablement process. In line with our results, we recommend CONFLICT OF INTEREST addressing age-specific prevalence of diseases by promoting effective health measures with a focus on their impact on the The authors declare that the research was conducted in the genders to enhance independent living for future generations of absence of any commercial or financial relationships that older men and women. could be construed as a potential conflict of interest. AUTHOR CONTRIBUTIONS ACKNOWLEDGMENTS AS-A conceptualized the study and wrote the manuscript. PZ and All authors thank Dr. Amand Blanes for his help with mortality ER performed the analysis. ML designed the visualization of data sources. 6. Oksuzyan A, Brønnum-Hansen H, Jeune B. Gender gap in Health Expectancy. REFERENCES Eur J Ageing (2010) 7(4):213–8. doi:10.1007/s10433-010-0170-4 7. Zacajova A, Huzurbazar S, Todd M. Gender and the Structure of Self-Rated 1. Crimmins EM, Kim JK, Solé-Auró A. 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Jagger C, Cox B, Le Roy, SEHEMU team. Health Expectancy Calculation Copyright © 2022 Solé-Auró, Zueras, Rentería and Lozano. This is an open-access by the Sullivan Method: A Practical Guide. EHEMU Technical Report article distributed under the terms of the Creative Commons Attribution License (CC (2007). BY). The use, distribution or reproduction in other forums is permitted, provided the 25. Villavicencio F, Bergeron-Boucher MP, Vaupel JW. Reply to Permanyer original author(s) and the copyright owner(s) are credited and that the original et al.: The uncertainty surrounding healthy life expectancy indicators. publication in this journal is cited, in accordance with accepted academic practice. Proc Natl Acad Sci U S A (2021) 118(46): e2115544118. doi:10.1073/pnas. No use, distribution or reproduction is permitted which does not comply with these 2115544118 terms. Int J Public Health | Owned by SSPH+ | Published by Frontiers 8 August 2022 | Volume 67 | Article 1604946