On average across the 21 OECD countries with available data, at age 30, people with tertiary attainment can expect to live around 5 years longer than those with below upper secondary attainment (54 years versus 49 years).
The association between education and life expectancy at age 30 is larger for men than for women: the average gap in life expectancy by level of education is 6 years for men, compared to 3 years for women.
Adults with tertiary attainment not only expect to live longer, they also report being in better health than adults with below upper secondary attainment. Across all OECD countries with available data, the higher the educational attainment, the higher the percentage of adults reporting being in good or very good health.
Adults with below upper secondary attainment have higher obesity prevalence than those with a tertiary attainment. On average across the 26 OECD countries with available data, the incidence of obesity is particularly high among 25‑64 year‑olds with below upper secondary attainment (25%) and relatively low among those with tertiary attainment (14%).
Education at a Glance 2021
Indicator A6. How are social outcomes related to education?
Highlights
Figure A6.1. Difference in life expectancy at age 30 between those with tertiary attainment and those with below upper secondary attainment, by gender (2017)
Eurostat’s annual data collection on demographic statistics or national surveys
1. Year of reference differs from 2017. Refer to the source table for more details.
2. National data sources.
Countries are ranked in descending order of the difference in life expectancy among total (men and women) at age 30 for those with tertiary attainment and those with below upper secondary attainment.
Source: OECD (2021), Table A6.1. See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3_ChapterA.pdf).
Context
Health is an important policy area in OECD countries, also in light of the rapid increases in life expectancy over the last decades and in the context of the current COVID-19 pandemic.
Moreover, there is a growing interest in looking beyond the traditional outcomes of education – such as income, employment and GDP – towards non-economic aspects of well-being and societal progress – such as health, civic engagement, political interests, crime and happiness (OECD, 2010[1]).
Given this policy climate, policy makers, researchers and practitioners interested in education are starting to consider what role education can play in fostering well-being and reducing health inequalities.A large number of empirical studies indicate that education is strongly linked to health and to determinants of health such as healthy behaviours, risky contexts and preventive service use (Feinstein et al., 2006[2]; Cutler and Lleras-Muney, 2006[3]).
Education at a Glance 2021 looks at the association between educational attainment and healthy behaviours as possible mediating factors in the relationship between educational attainment, obesity, life expectancy or subjective well-being. The analyses presented in the following sections are based on the results of simple bivariate correlations. However, it is important to keep in mind that education does not act on health in isolation from other factors. In fact, many confounding factors influence both education and behaviours, on the one hand, and health outcomes, on the other (Brunello et al., 2011[4]). In addition, the association between education and health is not unidirectional. Poor health may not only result from lower educational attainment, but it can also hinder access to higher levels of education (OECD, 2019[5]). On this, Box A6.1 presents some empirical results on the role of neurodevelopmental conditions as barriers to post-secondary education in Canada, Israel and the United States.
Other findings
The difference in the percentage of adults with tertary attainment reporting being in good or very good health versus those with below upper secondary attainment is larger for women than for men in all countries with available data. On average across OECD countries participating in the EU-SILC, the gap in self‑reported health (i.e. being in good or very good health) between 25-64 year-olds with tertiary attainment and those with below upper secondary attainment is 31 percentage points for women, compared to 24 percentage points for men.
The difference in the prevalence of obesity among adults by educational attainment is slightly greater among women than among men. On average across OECD countries with available data, the education gradient is 13 percentage points for women, compared to 8 percentage points for men.
Individuals with below upper secondary attainment report consuming less fruits and vegetables than those with higher levels of education. On average across the 32 OECD countries with available data, the share of 25-64 year-olds consuming at least five portions of fruits and vegetables per day ranges from 12% among those with below upper secondary attainment to 19% among those with tertiary attainment.
Individuals with below upper secondary education report doing less non-work related physical activity than those with higher levels of education. On average across the 30 OECD countries with available data, the share of 25‑64 year-olds doing at least 180 minutes of non-work related physical activity per week goes from 40% among those with below upper secondary education to 56% among those with tertiary education (i.e. an average gradient of 16 percentage points).
Note
The differences by educational attainment and by gender displayed in this indicator do not account for socio-economic status or other moderating or mediating factors. The educational attainment gradient should therefore be interpreted with caution.
Analysis
Evidence on the relationship between education and life expectancy
Life expectancy reflects a long trajectory of individuals’ socio-economic circumstances that affect their health conditions and other mortality risks. In OECD countries, life expectancy at birth, on average, reached almost 81 years in 2018 and is about 5 years higher for women than for men (83 years for women, compared to 78 years for men) (OECD, Health Statistics database).
Life expectancy in OECD countries varies by socio-economic status as measured, for instance, by education level. A higher level of education not only provides the means to improve the socio-economic conditions in which people live and work, but may also promote the adoption of healthier lifestyles and facilitate access to appropriate health care (OECD, 2019[6]). On average across the 21 OECD countries with available data, at age 30, people with tertiary attainment can expect to live around 5 years longer than those with below upper secondary attainment (54 years versus 49 years) (Figure A6.1).
Data show that the association between education and life expectancy at age 30 is larger for men than for women. The average gap in life expectancy by level of education is six years for men, compared to three years for women. Differences are particularly wide in Hungary, Poland and the Slovak Republic, where a 30-year-old tertiary-graduated man can expect to live at least 11 years longer than a 30-year-old man who has not completed upper secondary education (Figure A6.1).
Evidence on the relationship between education and subjective well-being
Adults with higher levels of education not only expect to live longer, but also report being in better health than adults with lower levels of education. Across OECD countries with available data, the higher the educational attainment, the higher the percentage of adults reporting being in good or very good health. In 2019, the share of those reporting being in good or very good health ranged from 37% (Lithuania) to 80% (Greece) among 25-64 year-old adults with below upper secondary attainment, from 45% (Lithuania) to 90% (Greece) among those with upper secondary or post-secondary non-tertiary education, and from 68% (Latvia) to 94% (Greece) among those with tertiary attainment (Table A6.2).
Figure A6.2. Difference in self-perceived health between those with tertiary attainment and those with below upper secondary attainment, by gender (2019)
Based on the percentage of 25-64 year-olds reporting being in good or very good health
1. Year of reference differs from 2019. Refer to the source table for more details.
2. Population of reference differs from 25-64 year-olds.
3. Data for Mexico are from the OECD Survey of Adult Skills (PIAAC); data for all other non-European OECD countries are from national surveys.
Countries are ranked in descending order of the difference in self-perceived health among men with tertiary attainment and those with below upper secondary attainment.
Source: OECD (2021), Table A6.2. See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3_ChapterA.pdf).
The difference in the percentage of adults with tertiary attainment reporting being in good or very good health versus those with below upper secondary attainment is larger for women than for men in all countries with available data. On average across the OECD countries participating in the EU-SILC, the gap in self‑reported health (i.e. being in good or very good health) between 25-64 year-olds with tertiary attainment and those with below upper secondary attainment is 31 percentage points for women, compared to 24 percentage points for men. The gap in self-reported health ranges from 15 to 44 percentage points for women (Italy and the Czech Republic, respectively) and from 10 to 37 percentage points for men (Sweden and Poland, respectively). Overall, with the exception of Australia, this pattern is confirmed also across OECD countries with available data from national data sources or from the Survey of Adult Skills (PIAAC) (Figure A6.2).
Evidence on the relationship between education and obesity
An epidemic of obesity has been developing in virtually all OECD countries over the last 30 years. In 2015, nearly one in five adults (19.5%) were obese across the OECD (OECD, 2017[7]). Being overweight, including pre-obesity and obesity, is a major risk factor for chronic diseases such as diabetes, cardiovascular diseases and certain cancers (OECD, 2019[6]). The World Health Organization estimates that obesity causes at least 2.8 million deaths worldwide each year (WHO, 2021[8]). And there is some evidence that obesity increases the risk of becoming severely ill from COVID-19. For example, a study conducted in France concludes that the odds of developing a severe case of COVID-19 are seven times higher in patients with obesity (Simonnet et al., 2020[9]).
Many OECD countries are concerned not only about the pace of the increase in obesity, but also about inequalities in its distribution across social groups, particularly by level of education, socio-economic status and ethnic background (Devaux et al., 2011[10]).
Figure A6.3. Proportion of adults with obesity, by educational attainment (2017)
European Union Survey on Income and Living Conditions (EU-SILC) ad hoc module "Health and children’s health" or national surveys, 25-64 year-olds
1. Year of reference differs from 2017. Refer to the source table for more details.
2. European Health Interview Survey 2019 (EHIS).
3. National data sources.
Countries are ranked in ascending order of the percentage of tertiary-educated 25-64 year-olds having a Body Mass Index above 30 kg/m2.
Source: OECD (2021), Table A6.3. See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3_ChapterA.pdf).
Data confirm that adults with below upper secondary attainment have higher obesity prevalence than those with tertiary attainment. On average across the 26 OECD countries with available data, the incidence of obesity is particularly high among 25-64 year-olds with below upper secondary attainment (25%) and relatively low among those with tertiary attainment (14%) (Table A6.3).
The incremental difference in health outcomes associated with more education is commonly called the education gradient. The steeper the gradient, the stronger the association between educational attainment and health outcome. The gradient is greater than 10 percentage points in the majority of OECD countries with available data and is at least 14 percentage points in the Czech Republic and Slovenia and about 19 percentage points in Australia. In Latvia and the United States, 25-64 year-old the prevalence of obesity among adults with upper secondary or post-secondary non-tertiary attainment is higher than among those adults with below upper secondary or with tertiary attainment. In addition, these two countries are characterised by a relatively small (less than 5 percentage points) gradient (Figure A6.3).
The difference in the proportion of adults with obesity by educational attainment is slightly higher among women than among men. On average across OECD countries with available data, the education gradient is 13 percentage points for women, compared to 8 percentage points for men. This gradient is 15 percentage points or higher in 10 of the 26 OECD countries with available data for women, while for men this is true only in the case of Australia (Table A6.3).
Evidence on the relationship between education and health behaviours
While multiple factors contribute to weight gain, including genetic predisposition and environmental influences, overweight primarily occurs due to the imbalance between energy intake from diet and energy output through physical activity. Individuals living in OECD countries have increasingly unhealthy lifestyles, including a poor diet and an insufficient consumption of fruits and vegetables, a greater consumption of which has been associated with a reduced risk of obesity and other chronic diseases. In addition, people have self-reported insufficient levels of physical activity and spend a significant part of their time in sedentary behaviour involving very low energy expenditure (OECD, 2019[5]).
Figure A6.4. Proportion of adults consuming at least five portions of fruits and vegetables per day, by educational attainment (2014)
European Health Interview Survey (EHIS) or national surveys, 25-64 year-olds
1. Year of reference differs from 2014. Refer to the source table for more details.
2. National data sources.
3. European Health Interview Survey 2019 (EHIS).
Countries are ranked in descending order of the percentage of tertiary-educated 25-64 year-olds who report consuming at least five portions of fruits and vegetables per day.
Source: OECD (2021), Table A6.4. See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3_ChapterA.pdf).
Eating fruits and vegetables
Individuals with a lower level of education or a lower socio-economic status are more likely to consume an unhealthy diet. On this, the WHO suggests consuming more than 400 greams of fruits and vegetables per day (i.e. five portions) to improve overall health and reduce the risck of becoming oveweight/obese or developing cardiovascular deseases, diabetes, cacers and respiratory deseases, among the others (WHO, 2020[11]).
On average across the 32 OECD countries with available data, the share of 25-64 year-olds consuming at least five portions of fruits and vegetables per day spans from 12% among those with below upper secondary attainment to 19% among those with tertiary attainment (i.e. an average gradient of 7 percentage points). This education gradient is 15 percentage points or higher in Denmark, Ireland and the United Kingdom; it is 5 percentage points or less in about half of the OECD countries with available data (Figure A6.4).
Men in general report consuming less fruits and vegetables than women do. In the large majority of OECD countries with available data, the share of men reporting eating at least five portions of fruits and vegetables per day is consistently lower than the share of women, regardless of level of education. In addition, the difference in the proportion of adults eating at least five portions of fruits and vegetables per day by educational attainment is relatively larger among women than among men. On average across OECD countries, this education gradient is 9 percentage points for women, compared to 4 percentage points for men (Table A6.4).
Being physically active
Individuals with a lower level of education or a lower socio-economic status are less likely to do sufficient physical activity outside their work. In particular, the WHO recommends that 16-64 year-olds spend between 150 and 300 minutes per week doing aerobic pysical activity (WHO, 2020[12]).
Figure A6.5. Proportion of adults doing at least 180 minutes of physical activity per week, by educational attainment (2017)
European Union Survey on Income and Living Conditions (EU-SILC) ad hoc module "Health and children’s health" or national surveys, 25-64 year-olds
1. Year of reference differs from 2017. Refer to source the table for more details.
2. National data sources.
3. European Health Interview Survey 2019 (EHIS).
Countries are ranked in descending order of the percentage of tertiary-educated 25-64 year-olds who report doing at least 180 minutes of physical activity per week.
Source: OECD (2021), Table A6.5. See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3_ChapterA.pdf).
On average across the 30 OECD countries with available data, the share of 25‑64 year‑olds doing at least 180 minutes of non-work related physical activity per week ranges from 40% among those with below upper secondary attainment to 56% among those with tertiary attainment (i.e. an average gradient of 16 percentage points). This gradient is 30 percentage points or more in the Czech Republic and Lithuania; it is less than 10 percentage points in Estonia, Finland, Italy, the Netherlands, New Zealand and Norway (Figure A6.5).
On average across countries with available data, the difference in the percentage of adults with tertiary attainment reporting performing at least 180 minutes of non-work related physical activity per week versus those with below upper secondary attainment is larger for men than for women. The average gradient is 18 percentage points for men and 14 percentage points for women. It ranges between 8 (New Zealand) and 39 percentage points (the Czech Republic) for men and between 1 (the Netherlands), and 30 percentage points (Canada) for women (Table A6.5).
Box A6.1. Neurodevelopmental conditions as barriers to post-secondary education
Education is associated with positive health outcomes, such as greater life expectancy, lower morbidity, lower obesity and lower prevalence of smoking (OECD, 2013[13]). However, the relationship between education and health is bidirectional, meaning that education is a determinant of health, and good health can also be a determinant of higher educational attainment. Some of the usual predictors for pursuing a post-secondary education are parental education, household income, students’ academic success and gender (Cutler and Lleras-Muney, 2006[3]). There is very little evidence on the role of mental health and neurodevelopmental disorders on post-secondary enrolment internationally. Students that suffer from mental health and neurodevelopmental disorders, such as attention-deficit/hyperactivity disorder (ADHD) and learning disabilities, likely face unique challenges in pursuing post-secondary education (Mezzanotte, 2020[14]). Learning disabilities include various conditions (such as dyslexia or dysgrpahia) that interfere with an individual’s ability to learn. In Canada, Arim and Frenette (2019[15]) provide some evidence which will be summarised here and compared to data from Israel and the United States.
This box addresses this information gap by comparing the post-secondary enrolment rates of students who were diagnosed with a learning disability and/or ADHD in secondary education to students that were not diagnosed with a disability. Longitudinally linked survey and/or administrative data for students, combining secondary education health information with post-secondary enrolment information, is presented for Canada, Israel and the United States. These data can provide insights into whether secondary education students with learning disabilities face barriers to accessing post-secondary education.
Students who had a learning disability in secondary education were significantly less likely to enrol in post-secondary education. In Canada, 77% of students that did not have a disability enrolled in post-secondary education by their early to mid-20s, the percentage was 79% in the United States and 46% in Israel. In contrast, 60% of students from Canada, 49% of students from the United States and 21% of students from Israel who were diagnosed with a learning disability enrolled in post-secondary education over the same period (Figure A6.6).
For students diagnosed with ADHD, only 48% of students from Canada and 57% of students from the United States enrolled in post-secondary education. Students diagnosed with both conditions (learning disability and ADHD) were even less likely to enrol, with only 36% of students from Canada and 49% of students from the United States enrolling in post-secondary education. In Canada, this difference is 41 percentage points less than when compared to students with no disabilities and 30 percentage points less in the United States (Figure A6.6).
In all three countries, among the students who did not have a disability, women were more likely to attend post-secondary education than men. On the opposite, there was a higher proportion of male students with a learning disability or ADHD who were enrolled in post-secondary education. In Canada, 54% of students that did not have a disability and attended post-secondary education were female. In Israel, this share was 64% and in the United States it was 55%. For men in Canada the share was 46%, Israel 36% and the United States 45%. In contrast, 57% of students in both Canada and the United States that were diagnosed with a learning disability and attended post-secondary education were male. Among students with disability in Israel, women are more likely than men to attend post-secondary education (53% and 47% respectively). Students who had ADHD were 70% male in Canada and 68% in the United States (Figure A6.7). In addition, ADHD in young girls is often overlooked and many females are not diagnosed until they are adults (Mezzanotte, 2020[14]).
Figure A6.6. Percentage of students that enrolled in post-secondary education by age 21-22, by type of disability diagnosis in secondary education
Note: All values are significantly different from no disability diagnosis category at p<0.05 for Canada and the United States. Administrative data were used for Israel, so every difference is significant as well.
Due to the various periods covered, the information on the year of reference of the data presented in this figure was included in Annex 3.
1. Data for Israel refer to students that enrolled in tertiary education by age 24. In Israel, the category of learning disability includes students diagnosed with Learning disability only, Attention-deficit hyperactivity/disorder only and students diagnosed with Attention-deficit hyperactivity/disorder and Learning disability together. The other two categories in the chart are not available due to inability to distinguish between the three categories.
Source: Arim and Frenette (2019) . US Department of Education, National Center for Education Statistics, High School Longitudinal Study of 2009, 2016 follow-up. Israeli Ministry of Education, administrative data files, 1993 cohort, 2018.
Figure A6.7. Gender composition of students that enrolled in post-secondary education by age 21-22, by type of disability diagnosis in secondary education
Note: All values are significantly different from no disability diagnosis category at p<0.05 for Canada and the United States. Administrative data were used for Israel, so every difference is significant as well.
Due to the various periods covered, the information on the year of reference of the data presented in this figure was included in Annex 3.
1. Data for Israel refer to students that enrolled in tertiary education by age 24. In Israel, the category of learning disability includes also students diagnosed with Learning disability and Attention-deficit hyperactivity/disorder together.
Source: Arim and Frenette (2019). US Department of Education, National Center for Education Statistics, High School Longitudinal Study of 2009, 2016 follow-up. Israeli Ministry of Education, administrative data files, 1993 cohort, 2018.
For the three countries analysed in this box, students with a learning disability and/or ADHD were significantly less likely to enrol in post-secondary education compared to students not diagnosed with a disability. In the case of comorbidity (i.e. students diagnosed with both learning disability and ADHD), students were even less likely to enrol in post-secondary education. The vast majority of students with learning disabilities and/or ADHD were male.
Definitions
Age groups: Adults refer to 25-64 year-olds.
Educational attainment refers to the highest level of education successfully completed by an individual.
Education gradient refers to the difference in health outcomes between adults with tertiary attainment and those with a below upper secondary attainment.
Levels of education: See the Reader’s Guide at the beginning of this publication for a presentation of all ISCED 2011 levels.
Life expectancy at birth and at age 30 is the average number of years that a person at that age can expect to live, assuming that age-specific mortality levels remain constant over time.
Pre-obesity is defined as a body mass index from 25 to 29kg/m2, with weight in kilogrammes and height in metres.
Obesity is defined as a body mass index of 30kg/m2 or more, with weight in kilogrammes and height in metres.
Methodology
The analyses presented in this indicator are based on the results of simple bivariate correlations. However, it is important to keep in mind that education does not act on health in isolation from other factors. In fact, there are many confounding factors influencing both education and behaviours, on the one hand, and health outcomes, on the other. In addition, the association between education and health is not unidirectional. Poor health may not only result from lower educational attainment, but it can also hinder access to higher levels of education. As such, the results discussed in this indicator should be interpreted with caution.
In addition, as most of the tables developed for this indicator combine data from different sources, in certain cases, cross‑country comparability could be compromised. Thus, the main focus should be on within-county differences in health outcomes and behaviours across levels of educational attainment, rather than on cross-country comparisons.
For the European sources, the metadata information can be found in the following links: for the demographic statistics: https://ec.europa.eu/eurostat/cache/metadata/en/demo_mor_esms.htm; for the EU Survey on Income and Living Conditions (EU-SILC) and its ad hoc module “Health and Children’s health”: https://ec.europa.eu/eurostat/statistics-explained/index.php?title=EU_statistics_on_income_and_living_conditions_(EU-SILC)_methodology; and for the European Health Interview Survey (EHIS): https://ec.europa.eu/eurostat/web/products-manuals-and-guidelines/-/KS-02-18-240.
For data from the Survey of Adult Skills (PIAAC), the observations based on a numerator with fewer than 5 observations or on a denominator with fewer than 30 observations times the number of categories have been replaced by “c” in the tables.
Data for the Box A6.1 used the following methodology by country:
Canada: The category “learning disability” also includes epilepsy, cerebral palsy, intellectual disability and learning disability. These other disabilities make up 14% of the total of the learning disability category. The comparison group consisted of students that had no long-term diagnosed health condition. Students were between 6 and 15 years of age when their long-term disability was diagnosed. Data are for 21-22 year-olds.
Israel: Learning disability category includes students in grade 11 or 12 that were identified and diagnosed with a learning disability and/or with ADHD. They were enrolled in the following three types of special settings: 1) students receiving inclusion services in regular classes; 2) special classes in regular schools; and 3) special schools (segregation). The comparison group consisted of the rest of the cohort, who have not been identified as special education needs students and were enrolled in a regular setting. Data are for 24 year-olds, to take into account the time required to complete compulsory service.
United States: Disability diagnosis is based on “parent told 9th grader has learning disability”. Comparison group includes students with parents that weren’t told that their 9th grader has a disability. Data are for 21-22 year-olds.
Post-secondary education for Israel refers to enrolment at the tertiary level only and excludes post-secondary non-tertiary, while post-secondary education for Canada and the United States includes all post-secondary enrolments.
Source
For Table A6.1 (Life expectancy at age 30, by educational attainment and gender): Demographic statistics by Eurostat for European OECD member countries, except for Belgium, France, Iceland, the Netherlands and Spain; and national data sources (Belgium: Census 2011 and Population Register 2017; Canada: Canadian Census Health and Environment Cohorts; France: Échantillon démographique permanent; Iceland: Population Statistics; Israel: Israeli Social Survey; the Netherlands: National Health Statistics; and Spain: Indicadores Demográficos Básicos).
For Table A6.2 (Percentage of the population reporting being in good or very good health, by educational attainment and gender): EU Survey on Income and Living Conditions (EU-SILC) for European OECD member countries; the OECD Health Database for Chile, Japan and Korea; the OECD Survey of Adult Skills (PIAAC) for Mexico; and national data sources (Australia: National Health Survey; Canada: Canadian Community Health Survey; Israel: Israeli Social Survey; New Zealand: New Zealand Health Survey; and the United States: National Health Interview Survey).
For Table A6.3 (Proportion of obese adults, by educational attainment and gender): EU-SILC ad hoc module “Health and children’s health” for European OECD member countries except for Italy and Portugal; and national data sources (Australia: National Health Survey; Canada: Canadian Community Health Survey; Israel: Israeli Social Survey; Italy: data submitted to Eurostat [but not published yet] according to the 2019 European Health Interview Survey (EHIS); New Zealand: New Zealand Health Survey; Portugal: National Health Survey [follows the EHIS regulations]; Switzerland: Survey on Income and Living Conditions [SILC]; and the United States: National Health and Nutrition Examination Survey).
For Table A6.4 (Percentage of adults who report consuming at least five portions of fruits and vegetables per day, by educational attainment and gender): EHIS for European OECD member countries, except Portugal; and national data sources (Australia: National Health Survey; Canada: Canadian Community Health Survey; Israel: Israeli Social Survey; New Zealand: New Zealand Health Survey; Portugal: National Health Survey [follows the EHIS regulations]; Switzerland: Swiss Health Survey; and the United States: National Health and Nutrition Examination Survey).
For Table A6.5 (Percentage of adults who report performing at least 180 minutes of physical activity per week, by educational attainment and gender): EU-SILC ad hoc module “Health and children’s health” for European OECD member countries except Portugal; Australia: National Health Survey; Canada: Canadian Community Health Survey; Israel: Israeli Social Survey; New Zealand: New Zealand Health Survey; Portugal: National Health Survey [follows the EHIS regulations]; Switzerland: Survey on Income and Living Conditions [SILC]; and the United States: National Health and Nutrition Examination Survey).
Data for Box A6.1 used national sources (Canada: National Longitudinal Survey of Children and Youth [2000-01 cohort aged 0-11] and T1 Family File [T1FF 2004 to 2015] linked data); Israel: Israel Ministry of Education Administrative Data Files, 1993 birth cohort; and the United States: High School Longitudinal Study of 2009 (HSLS:09) Second Follow-Up (2016)).
References
[15] Arim, R. and M. Frenette (2019), “Are mental health and neurodevelopmental conditions barriers to postsecondary access?”, Analytical Studies Brach Research Paper Series, No. 417, Statistics Canada, https://www150.statcan.gc.ca/n1/pub/11f0019m/11f0019m2019005-eng.htm.
[4] Brunello, G. et al. (2011), “The causal effect of education on health: What is the role of health behaviors?”, IZA Discussion Paper, No. 5944, https://www.iza.org/publications/dp/5944/the-causal-effect-of-education-on-health-what-is-the-role-of-health-behaviors.
[3] Cutler, D. and A. Lleras-Muney (2006), “Education and health: Evaluating theories and evidence”, NBER Working Paper Series, No. 12352, https://www.nber.org/system/files/working_papers/w12352/w12352.pdf.
[10] Devaux, M. et al. (2011), “Exploring the relationship between education and obesity”, OECD Journal: Economic Studies, No. Vol. 2011/1, pp. 140, OECD Publishing, Paris, https://doi.org/10.1787/eco_studies-2011-5kg5825v1k23.
[2] Feinstein, L. et al. (2006), “What are the effects of education on health?”, in Measuring the Effect of Education on Health and Civic Engagement, OECD, Paris, https://www.oecd.org/education/innovation-education/37437718.pdf.
[14] Mezzanotte, C. (2020), “Policy approaches and practices for the inclusion of students with attention-deficit hyperactivity disorder (ADHD)”, OECD Education Working Papers, No. 238, OECD Publishing, Paris, https://dx.doi.org/10.1787/49af95e0-en.
[6] OECD (2019), Health at a Glance 2019: OECD Indicators, OECD Publishing, Paris, https://dx.doi.org/10.1787/4dd50c09-en.
[5] OECD (2019), The Heavy Burden of Obesity: The Economics of Prevention, OECD Health Policy Studies, OECD Publishing, Paris, https://dx.doi.org/10.1787/67450d67-en.
[7] OECD (2017), Obesity Udpate 2017, OECD, Paris, https://www.oecd.org/health/health-systems/Obesity-Update-2017.pdf.
[13] OECD (2013), Education at a Glance 2013: OECD Indicators, OECD Publishing, Paris, https://dx.doi.org/10.1787/eag-2013-en.
[16] OECD (2011), Health at a Glance 2011: OECD Indicators, OECD Publishing, Paris, https://dx.doi.org/10.1787/health_glance-2011-en.
[1] OECD (2010), Improving Health and Social Cohesion through Education, Educational Research and Innovation, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264086319-en.
[9] Simonnet, A. et al. (2020), “High prevalence of obesity in severe acute respiratory syndrome Coronavirus‐2 (SARS‐CoV‐2) requiring invasive mechanical ventilation”, Obesity, Vol. 28/7, pp. 1195-1199, http://dx.doi.org/10.1002/oby.22831.
[8] WHO (2021), “Obesity”, web page, World Health Organization, Geneva, https://www.who.int/news-room/facts-in-pictures/detail/6-facts-on-obesity#:~:text=Obesity%20has%20reached%20epidemic%20proportions,%2D%20and%20middle%2Dincome%20countries.
[11] WHO (2020), Healthy diet, https://www.who.int/news-room/fact-sheets/detail/healthy-diet (accessed on 22 June 2021).
[12] WHO (2020), Physical activity, https://www.who.int/news-room/fact-sheets/detail/physical-activity (accessed on 22 June 2021).
Indicator A6 tables
Tables Indicator A6. How are social outcomes related to education?
Cut-off date for the data: 17 June 2021. Any updates on data can be found on line at: http://dx.doi.org/10.1787/eag-data-en. More breakdowns can also be found at: http://stats.oecd.org, Education at a Glance Database.
Table A6.1. Life expectancy at age 30, by educational attainment and gender (2017)
Eurostat’s annual data collection on demographic statistics or national surveys
Note: Life expectancy at birth and at age 30 is the average number of years that a person at that age can be expected to live, assuming that age-specific mortality levels remain constant.
1. National data sources.
2. Reference year differs from 2017: 2019 for Iceland; 2018 for Israel; 2016 for Denmark and Estonia; 2011 for Belgium and Canada; 2009-13 for France.
Source: OECD (2021). See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3_ChapterA.pdf).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Table A6.2. Percentage of the population reporting being in good or very good health, by educational attainment and gender (2010, 2015 and 2019)
European Union Survey on Income and Living Conditions (EU-SILC), Survey of Adult Skills (PIAAC) or national surveys, 25‑64 year‑olds
Note: Additional columns showing data by gender are available for consultation on line (see StatLink below).
The average differs from the one published by Eurostat as this is an unweighted average and the country coverage is different.
1. 2010 refers to 2011 for Chile; 2015 refers to 2014 for New Zealand and to 2013 for Japan; 2019 refers to 2018 for Iceland, New Zealand and the United Kingdom, to 2017-18 for Australia, to 2017 for Chile and Mexico, and to 2016 for Japan.
2. Population of reference differs from 25-64 year-olds.
3. Data for Mexico are from the OECD Survey of Adult Skills (PIAAC); data for all other non-European OECD countries are from national surveys.
Source: OECD (2021). See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3_ChapterA.pdf).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Table A6.3. Proportion of obese adults, by educational attainment and gender (2017)
European Union Survey on Income and Living Conditions (EU-SILC) ad hoc module “Health and children’s health” or national surveys, 25-64 year-olds
Note: Obese individuals are defined as those whose body mass index is greater or equal to 30 kg/m2.
1. Year of reference differs from 2017: 2019 for Canada, Italy and Portugal; July 2018 - June 2019 for New Zealand; 2017-18 for Australia.
2. National data sources.
3. European Health Interview Survey 2019 (EHIS).
Source: OECD (2021). See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3_ChapterA.pdf).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Table A6.4. Percentage of adults who report consuming at least five portions of fruits and vegetables per day, by educational attainment and gender (2014)
European Health Interview Survey (EHIS) or national surveys, 25-64 year-olds
1. Reference year differs from 2014: 2019 for Canada, Latvia, Lithuania and Portugal; July 2018 - June 2019 for New Zealand; 2017-18 for Australia and the United States; 2017 for Israel.
2. National data sources.
3. European Health Interview Survey 2019 (EHIS).
Source: OECD (2021). See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3_ChapterA.pdf).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.
Table A6.5. Percentage of adults who report performing at least 180 minutes of physical activity per week, by educational attainment and gender (2017)
European Union Survey on Income and Living Conditions (EU-SILC) ad hoc module “Health and children’s health” or national surveys, 25-64 year-olds
Note: Time spent performing physical activity during work time is excluded.
1. Year of reference differs from 2017: 2019 for Canada and Portugal; July 2018 - June 2019 for New Zealand and 2017-18 for Australia and the United States.
2. National data sources.
3. European Health Interview Survey 2019 (EHIS).
Source: OECD (2021). See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3_ChapterA.pdf).
Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations.