This chapter first presents gender-disaggregated data relating to health from birth and infancy to old age and death, including life expectancy, self-perceived health, physical activity and causes of death. Alongside these key statistics, the chapter explores drivers of observed gender gaps. The chapter then proceeds to lay out policy options to improve gender equality in physical and mental health and reduce gender gaps in physical activity.
Gender Equality in a Changing World
Taking Stock and Moving Forward
Abstract
Gender inequalities in health are complex. Women tend to live longer than men, though many of their additional years of life are spent in poorer health. Over the life course, there are also gendered risks and areas of concern. Women and girls face higher rates of poor self-reported physical and mental health, specific gendered risks related to pregnancy and childbirth, lower rates of participation in physical activity and sport and poorer experiences of healthcare (e.g. unmet healthcare needs, mis- or under-diagnosis). By contrast, men are more likely to engage in more risky behaviours (e.g. smoking, drinking heavily, drug abuse), have higher rates of death by suicide, are more likely to be overweight or obese and exhibit a greater reluctance to use preventive medicine and seek care.
Gender norms and stereotypes around access to and use of healthcare, as well as healthy and health-reducing behaviours among both patients and providers likely contribute to much of the observed narrative. Societal expectations of stoicism, for example, may be deterring men from preventive care, while caregiving duties and limited inclusion in healthcare decision-making and research may be restricting women’s access to care and deepening gaps in understanding women’s specific health needs.
Overcoming gender gaps in physical and mental health requires a comprehensive life course approach, including efforts to combat gender bias in healthcare institutions that limit women’s and men’s access to healthcare and the quality of services they receive. This can be achieved, in part, by mainstreaming gender considerations into all healthcare settings – emergency, long-term treatment and preventive – and by continuing to invest in gender-disaggregated health data and research to support evidence‑based changes in policies and practices among governments and healthcare providers. Combatting gender stereotypes and norms through adequate health education for girls and boys and awareness raising and training among care providers regarding gender sensitivity and unconscious biases can also help ensure girls and boys and women and men can seek and receive adequate care when they need it.
Reducing and eliminating gender gaps in physical activity also requires a range of interventions across various domains and ministries, such as early involvement of girls in physical activity and sports through school curricula and extracurricular activities; investments in safe and inclusive sports complexes, fitness facilities, recreational centres and active transportation methods; and equal and predictable media coverage of women’s sports to provide girls with role models and encourage girls to see themselves as athletes.
Having good health is key to a fulfilling life, giving people the ability to take part in the activities that they most need, value and appreciate (OECD, 2020[1]). “Health” encompasses many aspects including perceptions of health and indications of ill-health, with many metrics used to assess health status, outcomes, behaviours and experiences.
Life expectancy is one of the most commonly used indicators of population health, and gender gaps in life expectancy at birth tend to favour women. In 2021, average life expectancy across OECD countries was 82 years for women and 77 for men (Figure 7.1). But data on life expectancy do not account for the quality of life, including in later years. When looking at healthy life years – a measure of life expectancy adjusted to reflect the number of years a person is expected to be in good and functional health – gender gaps narrow. In fact, adjusting for healthy life years reduces the gender gap from five to two years.
Life expectancy and healthy life years at birth, number of years, 2021
Note: EU‑27 and OECD‑38 averages are unweighted. Healthy life years is the average number of years that a person can expect to live in “full health” by taking into account years lived in less than full health due to disease and/or injury. See WHO “Healthy life expectancy (HALE) at birth (years)” for more details. Data for this figure can be downloaded via Annex 7.A.
Source: WHO “Life expectancy and Healthy life expectancy,” (www.who.int/data/gho/data/themes/topics/indicator-groups/indicator-group-details/GHO/life-expectancy-and-healthy-life-expectancy).
Another commonly used measure of population health is self-perceived health (Cullati et al., 2020[2]). This indicator shows that women consistently report poorer health than men, with 66% of women in OECD‑37 countries reporting good or very good self-perceived health, on average, compared to 71% of men (Figure 7.2). Recent evidence from the OECD’s Patient-Reported Indicator Surveys (PaRIS) confirms the gender health paradox: women live longer than men but consistently report poorer physical and mental health. In addition, women tend to report lower levels of well-being (OECD, 2025[3]). These gender gaps are persistent and remain even after controlling for socio‑economic factors, age and multi-morbidity (OECD, 2025[3]).
Share (%) of women and men (15+) with very good or good self-perceived health, 2023 or latest
Note: EU‑25 and OECD‑37 averages are unweighted. ↗ indicates that the data is sorted according to this series in ascending order. Data from Costa Rica are from 2018. Data from Colombia, Iceland and the United Kingdom are from 2019. Data from Chile are from 2021. Data from Australia, Canada, Israel, Japan, Korea, Switzerland, Türkiye and the United States are from 2022. Perceived health refers to people’s overall self-reported health status. Data are based on general household surveys or on more detailed health interviews. The indicator is based on questions such as: “How is your health, in general?” with answers usually classified as “Very good,” “Good,” “Fair,” “Not very good,” and “Poor,” although in some non-European countries, such as Australia, Canada, Chile, Israel, New Zealand and the United States, different response scales are used, which may lead to an upward bias in the estimates. In the OECD Health Status Database, the response categories from different surveys are rescored to fit into three broad categories of “Good/Very good” (all positive response categories), “Fair” (neither good nor bad), “Bad/Very bad” (all negative response categories). Respondents are generally 16 years or over, though the specific age range varies across countries. See OECD (2023[4]). Data for this figure can be downloaded via Annex 7.A.
Source: OECD Data Explorer “Perceived health status” (http://data-explorer.oecd.org/s/16t).
For both women and men, income is positively associated with self-perceived health. This relationship may reflect that higher incomes facilitate greater access to and use of preventive healthcare and screening, support healthier lifestyle choices (e.g. more frequent health-enhancing behaviours, increased ability to afford healthier foods) and improve living conditions (e.g. improved housing conditions, less exposure to pollutants) (OECD, 2019[5]). At the same time, lower health can limit labour force participation, reduce productivity at work, and lower earnings (Stephens (Jr.) and Toohey, 2018[6]). Among EU‑27 countries, this association is slightly stronger for women than for men, with the share of women perceiving themselves to be in good health rising from 52% to 79% (or 27 percentage points) between the lowest and the highest income quartiles (Online Annex Figure 7‑A1) (Eurostat, 2025[7]). This compares to a rise from 58% to 81% for men (or 22 percentage points).
Recent evidence from the OECD’s Patient-Reported Indicator Surveys (PaRIS) furthers these findings, noting that not only do people with lower education and income fall ill earlier, but once sick, they also experience worse outcomes compared to their higher earning or higher educated counterparts, putting them at a double disadvantage (OECD, 2025[3]).
The complex story presented by these three measures of health – life expectancy at birth, healthy life years and self-perceived health – reflects gender norms and stereotypes around health-related outcomes and behaviours, differences in experiences with and access to healthcare systems, as well as differences in socio‑economic status.
This chapter proceeds as follows. Section 7.1 presents an overview of key gender gaps in health outcomes, behaviours, and experiences using a life course perspective and offers some key causes contributing to gender inequality. Section 7.2 explores policy options and policy combinations to improve gender equality in physical and mental health and reduce gender gaps in physical activity and at all levels of sport.
Starting with childhood, this section examines gender gaps in health outcomes, behaviours and perceptions across the life course, such as life expectancy, self-perceived health, physical activity, mental health and access to and use of healthcare and preventive medicine, among others. Potential explanatory factors are put forth.
7.1.1. Childhood and youth: Gender gaps in health outcomes start early
From the earliest years, there are gender gaps in health outcomes. Some of these gaps favour boys, and some of these gaps favour girls pointing to the complex interaction of gender norms and stereotypes around health and healthcare, as well as gender differences in risk factors and health-inducing behaviour.
Boys have higher mortality rates, but girls are less likely to feel very healthy
Although mortality rates are low for both genders between birth and the age of 14 years, boys have higher mortality rates than girls (Figure 7.3, Panel A). Mortality rates increase and gender gaps grow larger around the beginning of adulthood (i.e. age 15 years), with mortality rates for boys and young men more than double that of girls and young women.
Despite a lower likelihood of mortality, girls are less likely than boys to feel very healthy. In OECD‑28 countries, for example, only 26% of girls aged 11, 13 and 15 years rate their health as “excellent,” compared to 38% of boys of the same age (Figure 7.3, Panel B). In most countries, including those who rate their health as “good” alongside those who rate their health as “excellent” increases shares of positive self-perceived health for both girls and boys, with slightly larger increases for girls. For the OECD‑28 countries, an average of 87% of boys and 78% of girls perceive their health as “good” or “excellent.”
Mortality rates by age group and gender, deaths per 100 000 population, population aged 0‑24 years, OECD‑38 countries, 2021 (Panel A) and share (%) of 11‑, 13‑, and 15‑year‑old children who rate their own health as “excellent,” 2021‑22 (Panel B)
Note: For Panel A, OECD‑38 average is unweighted. For more details on underlying input sources and metadata, see IHME (2021[8]). For more details on methodology, see the Lancet Global Burden of Disease (GBD) Resource Centre (www.thelancet.com/gbd). For Panel B, OECD‑27 and EU‑25 averages are unweighted. Data for the United Kingdom refer to the unweighted average of England, Scotland and Wales. Data for Belgium refer to the unweighted average of the Flemish- and French-speaking regions. Data refer to the percent of children who, when asked “Would you say your health is …?” and presented with the response options “Excellent,” “Good,” “Fair” or “Poor,” respond with “Excellent.” “11‑, 13‑ and 15‑year‑old school children” refers to children aged 11, 13 and 15 attending mainstream schools. Estimates are based on the Health Behaviour in School-aged Children (HBSC) World Health Organization Collaborative Cross-National Survey. The combined series of “good” and “excellent” is available in the Online Annex. Data for this figure can be downloaded via Annex 7.A.
Source: Institute for Health Metrics and Evaluation (IHME) Global Burden of Disease (GBD) Results Tool (https://vizhub.healthdata.org/gbd-results/) (Panel A) and OECD Child-Well Being Data Portal on Child Well-Being Outcomes (www.oecd.org/en/data/datasets/child-well-being-outcomes0.html) (Panel B).
Boys are more likely to exercise, but girls are less likely to be overweight or obese
Many sources, across countries and over time, show that boys are more likely to engage in physical activity than girls (OECD/European Commission, 2024[9]; Graf and Cecchini, 2019[10]; OECD/European Union, 2016[11]; OECD/WHO, 2023[12]; International Children’s Accelerometry Database (ICAD) Collaborators, 2023[13]; Women in Sport, 2017[14]; Telford et al., 2016[15]). Indeed, in a 2021‑22 survey of health behaviours among school-aged children across OECD countries, an average of 24% of boys aged 11, 13 and 15 years reported engaging in at least 60 minutes of physical activity daily, compared to only 14% of girls (Figure 7.4, Panel A).
In this same survey, girls were less likely than boys to be classified as overweight or obese based on their body mass index (BMI) (17% versus 27%) (Figure 7.4, Panel B). Physical activity is only one factor that contributes to children being or becoming overweight or obese. Other factors include socio‑economic factors (e.g. income), personal characteristics (e.g. lifestyle preferences, diet) and family history (e.g. genetic makeup) (OECD/European Union, 2020[16]; OECD, 2021[17]; OECD/European Commission, 2024[9]; OECD/European Commission, 2024[9]). All of these factors likely interact with gender.
Share (%) of children aged 11‑, 13‑, and 15‑years-old being physically active for a total of at least 60 minutes every day for the last 7 days (Panel A) and who are classified as overweight or obese (Panel B), by gender, 2021‑22
Note: EU and OECD averages are unweighted. For Panel A, data for the United Kingdom refer to the unweighted average of England, Scotland and Wales. Data for Belgium refer to the unweighted average of the Flemish- and French-speaking regions. Children were told “Physical activity is any activity that increases your heart rate and makes you get out of breath some of the time. Physical activity can be done in sports, school activities, playing with friends, or walking to school. Some examples of physical activity are running, brisk walking, rollerblading, biking, dancing, skateboarding, swimming, soccer, basketball, football, and surfing [additional country-specific examples could be given].” Children were then asked “Over the past 7 days, on how many days were you physically active for a total of at least 60 minutes per day? Please add up all the time you spent in physical activity each day.” Data refer to the share of children who respond with “7 days”. The WHO guideline for physical activity is at least an average of 60 minutes per day of moderate to vigorous-intensity, mostly aerobic, physical activity across the week (WHO, 2020[18]). For Panel B, data for Belgium refer to the unweighted average of the Flemish- and French-speaking regions. Data refer to the percent with a Body Mass Index (BMI) that would be classified as “overweight” or “obese” according to the WHO’s age‑ and sex-specific child growth curve (www.who.int/growthref/en/). BMI data were calculated based on self-reported height and weight. See Figure 7.3 for additional notes. Data for this figure can be downloaded via Annex 7.A.
Source: OECD Child-Well Being Data Portal on Child Well-Being Drivers (www.oecd.org/en/data/datasets/child-well-being-drivers.html) (Panel A) and OECD Child-Well Being Data Portal on Child Well-Being Outcomes (www.oecd.org/en/data/datasets/child-well-being-outcomes0.html) (Panel B).
On average, across 22 EU and OECD countries,1 less than percentage of girls aged 15 years state that they expect to be athletes and sports players (ISCO‑08 code 3 421) by age 30 years (OECD, 2024[19]), compared to almost 4% of boys. Several explanations contribute to this gender gap, including:
Gender norms: Sports are traditionally associated with “masculine” traits – such as strength, resilience, speed and competitiveness – and women and girls who engage in sports are often perceived as more masculine (EIGE, 2017[20]; Midgley et al., 2021[21]). As a result, it is not surprising that boys aged 8‑18 years are four times more likely to participate in organised youth sport than girls (Emmonds et al., 2021[22]), and lower sports participation among girls and women also naturally translates into lower career expectations in sport.
Poorer media coverage: Sportswomen receive less media coverage than sportsmen, and when they do, it is often about their appearance as opposed to their performance (Fink, 2015[23]; EIGE, 2017[20]; Midgley et al., 2021[21]). Since career expectations are influenced by media (Chambers et al., 2018[24]), lower visibility of women athletes translates into fewer girls seeing themselves as sportswomen.
Lack of women role models, coaches and officials: Sports, including coaching and officiating, are dominated by men (EIGE, 2017[20]). A lack of women coaches and role models may affect girls’ interest in sports and the development of girls as athletes, especially at crucial stages such as puberty. Indeed, evidence shows that women are more motivated by “same‑gender and sport-matched” role models (Midgley et al., 2021[21]).
Underinvestment in women’s sports: Long-standing inequities in public and private funding for women’s sports contribute to women’s underrepresentation. Women, for example, find it “difficult to access specialised equipment” and struggle to obtain “optimal times on hockey rinks, basketball courts, or golf courses” (Midgley et al., 2021[21]). In a recent survey in the United Kingdom across 28 different sports, 99 out of 143 elite sportswomen responded that most of the equipment they use is not specifically designed for women (BBC, 2024[25]).
Underrepresentation of women as decision-makers: In 2024 in the EU‑27, in the national sports federations of the top ten most funded Olympic sports, women accounted for only 24% of members (EIGE, 2024[26]). Similarly, at the political level, women account for only 31% of ministers responsible for sports in their portfolios (EIGE, 2024[27]).
Fewer professional opportunities and lower compensation: For much of sports history – and in some cases until quite recently – women were unable to compete in certain sports at certain events. For example, despite competing internationally in ski jumping events since the 1990s, women were excluded from the Olympic sport until 2014 (Encyclopaedia Britannica, 2025[28]). Pole vault was also not on the women’s programme of the Olympics until 2000 (Encyclopaedia Britannica, 2025[29]), despite being a competitive event at the Games since 1896. Some countries also had restrictive rules that severely limited the growth of women’s sports. In England, for example, the Football Association banned women from playing on professional grounds and pitches between 1921 and 1971, relegating women’s clubs to public parks and smaller grounds (The Football Association, n.d.[30]). In addition, in many countries and sports, women’s amateur and professional sports remain underdeveloped (Canadian Women and Sport, 2023[31]). Even when professional opportunities exist, women athletes are often paid less than men (UN Women, 2024[32]).
More information is available from the recording of a 2024 OECD event for International Equal Pay Day, entitled “Closing the Gender Play Gap: Towards Pay Equity in Sports.”
Girls attempt suicide more often than boys, while boys are far more likely to die by suicide
Suicide is a leading cause of death for young people, and boys and young men are far more likely to die by suicide than girls and young women. In OECD countries, for example, an average of about 9 boys and young men aged 15‑19 years will die by suicide for every 100 000 boys and young men of the same age (Figure 7.5). For girls and young women, this figure is 3 per 100 000. Among those aged 20‑24 years, rates rise to 17 per 100 000 for men, compared to 4 per 100 000 for women. Although boys and young men are more likely to die by suicide, girls and young women are found to have a higher risk of suicide attempts (Miranda-Mendizabal et al., 2019[33]; Committee on Adolescence, 2016[34]).
In a systematic review and meta‑analysis of longitudinal studies, risk factors for suicide among boys and young men were “drug abuse, externalising disorders (e.g. conduct disorder, substance abuse disorder, deviant behaviour) and access to means (e.g. firearms, pesticides, toxic gas)” (Miranda-Mendizabal et al., 2019[33]). For girls and young women, risk factors for suicide attempts include eating disorders, post-traumatic stress disorder, bipolar disorder, being a victim of dating violence, depressive symptoms and interpersonal problems (Miranda-Mendizabal et al., 2019[33]).
Gender differences in mortality from suicide attempts may be explained, at least in part, by differences in methods. Boys and young men, for instance, are more likely to use methods that have a higher risk of death, such as weapons and hanging, while girls and young women are more likely to use less lethal means, such as drug poisoning (Miranda-Mendizabal et al., 2019[33]; Beautrais, 2003[35]; Mergl et al., 2015[36]; Rhodes, Lu and Skinner, 2014[37]).
Death rate due to self-harm, population aged 0‑24 years by age group and gender, rate per 100 000 persons, OECD‑38 average, 2021
Note: EU‑27 and OECD‑38 are unweighted averages. IHME GBD provides estimates of the prevalence of a range of mental health conditions and neurological disorders based on a wide variety of data sources and a set of modelling assumptions. Data for this figure can be downloaded via Annex 7.A.
Source: IHME GBD Results Tool (https://vizhub.healthdata.org/gbd-results/).
Girls and boys are diagnosed with different mental health conditions and neurological disorders
The prevalence of mental health conditions and neurological disorders is higher among boys aged 0‑14 years than among similarly aged girls, while it is higher among girls and young women aged 15‑19 and 20‑24 years than among similarly aged boys and young men (see Online Annex Figure 7‑A2). Nonetheless, these aggregates mask considerable variation by type of mental health condition or neurological disorder, with girls and young women facing higher prevalence rates in the case of anxiety, depressive and eating disorders and boys and young men facing higher prevalence rates for autism, attention-deficit hyperactivity disorder (ADHD) and conduct disorders (Figure 7.6).
Prevalence of various mental health conditions and neurological disorders by age group and gender, population aged 0‑24 years, rate per 100 000 population, OECD‑38 averages, 2021
Note: OECD‑38 averages are unweighted. ADHD is short for attention-deficit hyperactivity disorder. IHME GBD provides estimates of the prevalence of a range of mental health conditions and neurological disorders based on a wide variety of data sources and a set of modelling assumptions. IHME GBD defines prevalence as the proportion of people in a population who are a case of a disease, injury or sequela. All results refer to point prevalence. Data for this figure can be downloaded via Annex 7.A.
Source: IHME GBD Results Tool (https://vizhub.healthdata.org/gbd-results/).
Gender gaps in children’s and young people’s mental health and neurological disorders take place against the backdrop of under-developed and variable public support (including in schools) for children with mental health conditions and neurological disorders across EU and OECD countries (Brussino, 2020[38]; OECD, 2019[39]). For example, some countries provide only limited support to children with disability, difficulty and disadvantage at particular stages of learning, and some countries exclude some children with disability, difficulty and disadvantage from mainstream schools (Brussino, 2020[38]).
In face of significant challenges in the integration of children with mental health conditions and neurological disorders, many countries are attempting to develop adequate and inclusive educational, health and social systems for all children, which is foundational for improving outcomes for both girls and boys. Related to this, countries must also ensure that gender norms and stereotypes are not preventing diagnoses of girls and women, thereby limiting their access to these types of (developing) supports (Box 7.3).
Girls and women may be underdiagnosed in many areas of health (see Section 7.1.2), including certain neurological disorders, such as autism and attention deficit hyperactivity disorder (ADHD). These two neurological disorders have long been identified as conditions experienced predominantly or mainly by men and boys (Werling and Geschwind, 2013[40]; Lai, Baron-Cohen and Buxbaum, 2015[41]). Although biology may explain part of this gender gap, other explanatory factors relate to the fact that early research on these issues included mostly or only men, and that gender norms and stereotypes may mediate typical signs and symptoms, both of which could lead to the mis- or underdiagnosis of these conditions in girls and women (Bölte et al., 2023[42]; Christiansen, McCarthy and Seeman, 2022[43]).
Clinicians, for instance, are more likely to recognise restricted interests in stereotypically “male” domains, such as transportation and space, as an indication of autism spectrum disorder, but may overlook restricted interests in stereotypically “female” areas, such as animals, art or literature (Harvard Medical School, 2023[44]). Repetitive patterns of behaviour may also present differently in girls and women compared to men and boys, tending toward behaviours such as perfectionism or disordered eating instead of rocking and hand or finger movements. In addition, girls and women with autism are more likely to be misdiagnosed by clinicians with conditions like anxiety, mood disorders and eating disorders – a phenomenon referred to as “diagnostic overshadowing.” Consider, too, that girls and women with autism tend to have “stronger social imitation skills and the ability to mimic social behaviour” (Harvard Medical School, 2023[44]), often having “one or two close friendships” that help them to “absorb social rules and norms” and to mask or moderate personal challenges with socialising and communicating (Harvard Medical School, 2023[44]). This, however, makes it more challenging to identify autism in girls in “everyday interactions or larger classroom or employment settings” (Harvard Medical School, 2023[44]).
In a similar way, the diagnostic bias in ADHD likely reflects a combination of biologically determined differences in symptom presentation and gender-specific perceptions of ADHD symptoms in girls and boys (Waite, 2010[45]; Martin, 2024[46]).
7.1.2. Adulthood: Women report higher unmet healthcare needs, but men have higher mortality rates
Gender gaps in health outcomes, behaviours and experiences in childhood and youth foreshadow those in adulthood across key indicators, including unmet healthcare needs, mortality, self-perceived health, physical activity, mental health, suicide and more.
Women are more likely to report unmet healthcare needs
Self-reported unmet healthcare needs – an important indication of perceived access to care – are higher among women than among men across all age groups (Figure 7.7, Panel A). In EU‑27 countries, for example, 28% of women report unmet healthcare needs due to financial reasons, distance or transportation, or a waiting list, while only 23% of men report the same.
Share (%) of women and men (15+) reporting unmet healthcare needs, by age group, 2019 (Panel A) and share (%) of women and men who believe that they and their household have or would have access to good quality and affordable healthcare, 2024 (Panel B)
Note: In Panel A, EU‑27 is a weighted average. Estimates refer to the proportion of people in need of healthcare reporting to have experienced delay in getting healthcare in the previous 12 months for reasons of financial barriers, long waiting lists, distance or transportation problems. In Panel B, OECD‑27 is an unweighted average of the 27 OECD countries participating in the OECD RTM Survey. The share refers to the percentage of respondents who agree or strongly agree with the following statement “I think that my household and I have/would have access to good quality and affordable public services in the area of health services, if needed.” Response options were “Strongly disagree,” “Disagree,” “Neither agree nor disagree,” “Agree,” “Strongly agree” and “Can’t choose.” Data for this figure can be downloaded via Annex 7.A.
Source: Eurostat “Self-reported unmet needs for healthcare by sex, age, specific reasons and educational attainment level” (https://doi.org/10.2908/HLTH_EHIS_UN1E) (Panel A) and OECD Secretariat calculations using OECD 2024 Risks that Matter Survey microdata (https://oe.cd/rtm) (Panel B).
These gender gaps likely reflect the combination of several factors, including (but not limited to):
A greater need for care among women than men due to poorer health over the life course (see below).
An elevated risk of mis- and under-diagnosis among women compared to men (see below), which may cause women to regularly return to the doctor to find answers.
A lower ability to afford care due to women’s lower earnings (see Chapter 5).
A greater prevalence of gender-based violence (see Chapter 8) and/or differing or more severe physical and mental health impacts among women compared to men.
Gender-specific health issues relating to pregnancy, childbirth (e.g. postpartum depression), menopause and reproductive health (e.g. endometriosis).
Gender gaps in unmet healthcare needs may also reflect stereotypes and norms around “waiting it out” and being “tough” that are stronger for men than for women (i.e. men may have a higher threshold for seeking treatment than women) (Cleveland Clinic, 2019[47]; Höhn et al., 2020[48]). This aligns with findings that men are less likely to use preventive healthcare and medicine (see below).
These factors are reflected in recent results from the 2024 OECD Risks that Matter (RTM) Survey, which finds that women are 6 percentage points less likely than men to believe that they and their family would have access to affordable and good quality health services, if needed (Figure 7.7, Panel B). In 11 of 27 participating RTM countries, women are statistically significantly less likely to express this belief.
Higher unmet healthcare needs among women may stem from poorer health
In EU and OECD countries, women are less likely to feel healthy than men, with 66% of women reporting good or very good self-perceived health in OECD‑37 countries, compared to 71% of men (Figure 7.2). This gender difference is driven by a complex combination of biological, social, behavioural and socio‑economic factors, including that women and men experience different physical and mental health conditions.
In the flagship 2025 OECD Patient Reported Indicator Surveys (PaRIS), for example, women were more likely to report arthritis and mental health conditions, while men were more likely to report hypertension and cardiovascular and heart conditions (Figure 7.8). This is aligned with other work that finds that women experience a higher burden of morbidity-driven conditions (e.g. low back pain, depressive disorders and headache disorders), while men have a higher burden for mortality-driven conditions (e.g. road injuries, ischemic heart disease). Indeed, the six causes with the highest disease burden disfavouring women were headache disorders, anxiety, depressive disorders, other musculoskeletal disorders, low back pain and dementia (Patwardhan et al., 2024[49]).
Share (%) of women and men by chronic conditions, women and men with one or more chronic conditions, 2024
Note: * indicates that the difference is statistically significant (p<0.05). Conditions are sorted by the relative difference calculated by dividing the prevalence in men by the prevalence in women. Data for this figure can be downloaded via Annex 7.A.
Source: Figure 5.1 from OECD (2025[3]), available at https://stat.link/qnsd52.
Women are more likely to be underdiagnosed than men
Evidence points to the potential for significant gender differences in healthcare diagnosis and treatment within healthcare systems, including that women may be more likely than men to be underdiagnosed or left undiagnosed. In the United Kingdom, for example, women were found to be more likely than men to wait at least 10 months between their first visit to a doctor and their diagnosis for cancer and many women reported “not being taken seriously” (The Brain Tumour Charity, 2016[50]). Other studies find diagnostic delays as well (e.g. Din et al. (2015[51])). Women may also receive different treatments than men. For instance, evidence points to gender differences in the treatment and discharge of patients who suffered a stroke, with women less likely than men to be prescribed statins (Dahl, Hjalmarsson and Andersson, 2020[52]). Women may additionally receive improper diagnoses, with evidence pointing to cases of women with complex trauma being labelled with bipolar disorder, preventing them from receiving proper treatment (Department of Health and Social Care, 2018[53]).
These outcomes may stem, in part, from a lack of health research on women and women’s health issues, which hinders progress in many areas and diseases that disproportionately affect women. For example, women are often underrepresented in clinical trials (Franklin, Bambra and Albani, 2021[54]). Indeed, a study of over 20 000 clinical trials shows gender bias in enrolment, with women’s representation lowest compared to disease burden in oncology, neurology, immunology, and nephrology (Steinberg et al., 2021[55]). This means that medication and treatments may not be as effective for women as for men and may produce different – potentially more harmful – side effects (Franklin, Bambra and Albani, 2021[54]). This may be true even of women-dominated mental health conditions, for which health research often uses primarily men or male animals (Bangasser and Cuarenta, 2021[56]). It also means that doctors may not recognise certain more gendered signs and symptoms. Research is increasingly documenting, for example, that women may experience different heart attack or stroke symptoms like back pain, dizziness, or nausea, while men typically report chest pain and sweating (Department of Cardiovascular Sciences, 2017[57]; Quaye, 2024[58]). In addition to differing signs and symptoms, two common tests used for diagnosing heart attacks – the cardiac troponin test and cardiac catheterisation – are not as effective in women (Quaye, 2024[58]).
Clinical trials also often exclude people with pre‑existing autoimmune diseases (Kehl et al., 2019[59]), many of which are more common in women than men (Kronzer, Bridges and Davis, 2020[60]), as well as pregnant women (Chambers, Polifka and Friedman, 2007[61]; Shields and Lyerly, 2013[62]), significantly limiting the understanding of drug safety and drug interactions, especially during pregnancy and breastfeeding.
Evidence further suggests there are large epidemiological and clinical data gaps for conditions predominantly or exclusively affecting women, such as chronic fatigue syndrome, chronic gynaecologic issues (e.g. endometriosis, polycystic ovary syndrome, fibroids), menopause‑related conditions, and certain autoimmune disorders (Temkin et al., 2023[63]). Indeed, stigma around menstrual disorders and female reproductive diseases has led to inadequate treatments and underinvestment in research (As-Sanie et al., 2019[64]). The lack of consistent definitions and measurement scales only contribute to additional biases in diagnosing these conditions. Underdiagnoses and undertreatment may also be an issue for certain men-specific conditions (e.g. male infertility) (Pandruvada et al., 2021[65]) or among men who are experiencing diseases considered to be primarily an issue among women (e.g. osteoporosis) (Rinonapoli et al., 2021[66]).
This lack of research and treatment of gender-specific conditions and gendered differences in the presentation of conditions can feed into and reproduce gender bias, with doctors sometimes attributing the pain and symptoms experienced by women to “emotional rather than physical causes” (Agarwal, 2023[67]; Drossman and Ruddy, 2020[68]; Shahvisi, 2018[69]). As an example, women wait an average of 7‑9 years for a diagnosis of endometriosis, which can impart significant negative impacts physically, psychologically and financially (Frankel, 2022[70]; Ghai et al., 2019[71]). Perceptions that women’s pain is emotionally-driven may also interact with bias against other groups, such as racial and ethnic minorities, compounding the likelihood of misdiagnosis, underdiagnosis and undertreatment (Hoffman et al., 2016[72]; Boakye et al., 2024[73]).
Gender bias in medical education also contributes to gendered outcomes in healthcare settings as curricula and clinical guidelines often overlook gender differences in health conditions, symptoms and treatment responses. These biases in medical education are themselves partly rooted in the above‑noted lack of gender-sensitive research and over-reliance on men in clinical trials.
With mounting evidence that women face disadvantages in medical settings, it is perhaps not surprising that in the EU, 16% of men and 22% of women believe men are treated better by medical staff than women (Eurobarometer, 2024[74]). Women also tend to trust the healthcare system less than men. Recent evidence from the OECD’s Patient-Reported Indicator Surveys (PaRIS), for example, find that in a third of participating countries, the gender gap in trust in the healthcare system is over 10% and in all but two countries it is over 5% (OECD, 2025[3]).
Collectively, these findings suggest that a lack gender mainstreaming into healthcare research may be affecting women’s and men’s experiences and outcomes of care.
Men are more likely to die
Despite men’s better self-perceived health compared to women and women’s greater self-reported unmet healthcare needs compared to men, men are more likely to die than women across all age groups, with gender gaps in mortality increasing with age (Figure 7.9). The top five causes of death in 2022 – cardiovascular disease, cancer, COVID‑19, respiratory disease, and metabolic disorders – accounted for 75% of deaths for both genders.
Gender gap (men minus women) in mortality rates, deaths per 100 000 population, by age group, 2021
Note: OECD‑38 are unweighted averages. IHME GBD provides estimates of the prevalence of a range of mental health conditions and neurological disorders based on a wide variety of data sources and a set of modelling assumptions. Data for this figure can be downloaded via Annex 7.A.
Source: IHME GBD Results Tool (https://vizhub.healthdata.org/gbd-results/).
Higher mortality among men than women across age brackets is driven by numerous causes, including higher levels of assault, intentional self-harm and accidents. Men are considerably more likely to die than women even for those causes of death that rank highly among women, such as malignant neoplasms (cancer) and ischaemic heart diseases (Table 7.1). Indeed, when looking at different causes of death most of them disfavour men. Zeroing in on cancer, for women, breast and lung cancer have the highest mortality rates. For men, it is lung and prostate cancer (Online Annex Figure 7‑A3) (OECD Data Explorer, 2024[75]).
Standardised mortality rates per 100 000 population, women and men, by cause of death, average of 39 EU and OECD countries, 2022 or latest
Note: Gender gap is measured as the rate for men less the rate for women divided by the rate for women. Data are an unweighted average across 39 EU and OECD countries, including all 38 EU countries minus New Zealand and Norway plus Bulgaria, Croatia and Romania. Rates are age‑standardised to remove variations arising from differences in age structures. Data are extracted from the WHO Mortality Database. Data for Australia, Canada, Estonia, Hungary, Iceland, Lithuania, Luxembourg, the Netherlands and Sweden are for 2022. Data for Austria, Bulgaria, Chile, Colombia, Croatia, Czechia, Denmark, Finland, Israel, Japan, Korea, Latvia, Mexico, Poland, the Slovak Republic, Spain, Switzerland and the United States are for 2021. Data for Belgium, Costa Rica, Germany, France, Greece, Ireland, Italy, Slovenia and the United Kingdom are for 2020. Data for Portugal, Romania and Türkiye are from 2019. Data for this figure can be downloaded via Annex 7.A.
Source: OECD Data Explorer “Causes of mortality” (https://data-explorer.oecd.org/s/pv).
Explanations for higher mortality among men
Beyond physiological differences between women and men, there are several reasons why women and men may have different rates of death for these underlying causes.
Lower rates of consultations of medical professionals: Men are less likely to seek and use healthcare. In 2019, in EU‑27 countries, men were less likely to have seen a specialist medical practitioner (13 percentage points), to have seen a general medical practitioner (8 percentage points less likely than women), to have called on a dentist (6 percentage points), to have consulted a physiotherapist (5 percentage points), and to have visited a mental health professional (3 percentage points), in the last 12 months (Online Annex Figure 7‑A4, Panel A) (Eurostat, 2022[76]; 2022[77]).
Lower use of preventive medical services: Self-reported screening for cardiovascular diseases and diabetes is lower among men than among women. In 2019 in EU‑27 countries, men were less likely than women to have undertaken a blood pressure measurement (7 percentage points), a blood sugar measurement (6 percentage points) and a blood cholesterol measurement (5 percentage points) in the past 12 months. By contrast, men were more likely to report having received an influenza vaccination in the past 12 months (3 percentage points). There was little gender difference in reported colonoscopies and colorectal cancer screening (Online Annex Figure 7‑A4, Panel B) (Eurostat, 2022[78]; 2022[79]; 2022[80]; 2022[81]).
Lower prescription medication use: Men are less likely to use prescription medicines than women. In 2019, across EU‑27 countries, 52% of women reported using medicines prescribed by a doctor in the past 2 weeks, compared to 43% of men (Online Annex Figure 7‑A5, Panel A) (Eurostat, 2022[82]). This gender difference may partly reflect women’s use of prescribed contraceptives. However, gender gaps in the use of prescribed medicine exist for all age groups, including among older women, suggesting that contraceptives are not the only explanation. Further to this, the use of non-prescribed medicines shows a similar differential overall and by age group (Online Annex Figure 7‑A5, Panel B) (Eurostat, 2022[83]).
More likely to be overweight and obese: Women are less likely to be overweight or obese than men. In OECD‑32 countries, about 48% of women are overweight or obese using self-reported measures of height and weight to estimate body mass index (BMI) (Online Annex Figure 7‑A6, Panel A) (OECD Data Explorer, 2024[84]). This compares to 61% of men. Such self-reported measures are, however, subject to bias – whether due to misreporting of height or weight (Ng et al., 2011[85]; Merrill and Richardson, 2009[86]). Comparing across data sources for countries where both measured and self-reported data are available, the share of women who are overweight or obese is 8 percentage points higher when using measured data instead of self-reported data, while the share of men who are overweight or obese is 6 percentage points higher (Online Annex Figure 7‑A6, Panel B) (OECD Data Explorer, 2024[84]).
Greater concentration in industries with higher rates of fatality at work: Accidents are a significant cause of death among men and some of these fatal accidents occur at work. In 2022, there were 3.2 fatal accidents per 100 000 employed men, compared to 0.3 per 100 000 employed women (Eurostat, 2024[87]). This gender difference is, in part, driven by occupational and industrial segregation by gender. Construction, transportation and storage, manufacturing and agriculture, forestry and fishing are the industries that contribute the most to fatal accidents at work – all of which are men-dominated (Eurostat, 2024[88]).
Greater risk factors and risky behaviours: Women are less likely than men to engage in health-enhancing behaviours, such as physical activity. In 2019, 29% of women across EU‑27 countries engaged in at least 150 minutes or more of health-enhancing (non-work-related) aerobic physical activity per week – the WHO recommendation (WHO, 2020[18]). This compares to 37% of men (Online Annex Figure 7‑A7) (Eurostat, 2022[89]). By contrast, men are more likely to engage in health-reducing risky behaviours, like smoking and heavy drinking. Men, for example, are 8 percentage points more likely than women to smoke daily, 9 percentage points more likely than women to drink every day and 5 percentage points more likely than women to drink heavily at least once a week (Online Annex Figure 7‑A8) (Eurostat, 2022[90]; 2022[91]; 2022[92]). These risky behaviours are linked to an increased risk of cancer, illness and disease.
Health-reducing behaviours are more common among individuals with low income – and this relationship is much stronger for men than for women. Consider daily smoking: about 18% of women in the lowest income quintile smoke cigarettes daily, while only 13% of women in the highest income quintile do (Online Annex Figure 7‑A9) (Eurostat, 2022[93]). For men, there is an 11 percentage point difference between the top and the bottom, with 28% of men in the first income quintile smoking daily compared to 17% in the fifth income quintile.
Turning to health-enhancing behaviours, only 23% of women in the first income quintile report engaging in at least 150 minutes or more of health-enhancing (non-work-related) aerobic physical activity per week (the WHO recommendation) (WHO, 2020[18]), while 36% of women in the fifth income quintile report doing so (Online Annex Figure 7‑A10) (Eurostat, 2022[94]). The relationship is slightly less strong for men, with 34% of those in the first income quintile and 44% of those in the fifth income quintile meeting or exceeding the WHO recommendation.
Given the higher rate of death for men at work in men-dominated industries, occupational health and safety has long been concerned with improving working conditions in jobs dominated by men. Although it is vitally important to continue to improve occupational health and safety in these jobs, this focus has also left occupational health and safety in traditionally women-dominated fields, such as in cleaning, hairdressing and healthcare, both understudied and underreported. There is, for instance, a general lack of knowledge regarding the health impact of the interaction of the different types of chemical products used in traditionally women-dominated occupations and the health impact of long-term exposure to such products individually or in combination. There may also be important differences in the rates at which women and men uptake and metabolise different dangerous substances even within the same occupation, and exposure to certain dangerous substances can affect women’s fertility and foetal development. In addition, in both men- and women-dominated industries and occupations, personal protection equipment (PPE) (e.g. gloves, boots, masks, helmets, body armour) designed to be gender neutral may be ill-fitting, hamper work and/or create safety and health hazards.
Source: Criado Perez (2019[95]), Canadian Centre for Occupational Health and Safety (2023[96]) and European Agency for Safety and Health at Work (2013[97]).
Self-perceived mental health is lower for women than for men
Women tend to fare worse than men across a range of metrics related to mental health, including self-perceived mental health and common mental health conditions (EIGE, 2021[98]). Data from the EU Statistics on Income and Living Conditions (EU-SILC) Survey, for instance, show that women are more likely to be at risk of experiencing mental distress than men across all age groups (Figure 7.10). Results from OECD’s Patient-Reported Indicator Surveys (PaRIS) confirm these findings, with women more likely to report mental health conditions (e.g. depression, anxiety) and lower levels of mental health (OECD, 2025[3]).
Share (%) of women and men at risk of experiencing mental distress by age group, average of 26 OECD countries, 2018
Note: The MHI‑5 questionnaire consists of five questions, including “Have you been a happy person” (reverse coded), “Have you felt calm and peaceful” (reverse coded), “Have you been a very nervous person,” “Have you felt downhearted and blue,” and “Have you felt so down in the dumps that nothing could cheer you up.” Response options are “All of the time,” “Most of the time,” “A good bit of the time,” “Some of the time,” “A little of the time,” and “None of the time,” with scores ranging from 1 (All of the time) to 6 (None of the time). All items are added together to provide a score ranging from 5‑30, which is then transformed into a variable ranging from 0‑100 using a standard linear transformation. Risk of mental distress is defined as having a score greater than or equal to 52 on a scale from 0 (least distressed) to 100 (most distressed). Data for this figure can be downloaded via Annex 7.A.
Source: Figure 3.4 (https://stat.link/3yntk5) in OECD (2023[99]) based on the 2018 European Union Statistics on Income and Living Conditions (EU-SILC) Survey.
Prevalence rates of common mental health disorders also tend to be higher among women. Across OECD countries, for example, the prevalence of anxiety disorders stands at 7 834 women per 100 000 population, compared to 4 325 men per 100 000 population. For depressive disorders, prevalence rates are, on average, 6 114 per 100 000 population for women versus 3 725 per 100 000 population for men. By contrast, the prevalence rates of ADHD, autism spectrum disorder and conduct disorder are higher among men (Box 7.3). Rates for these conditions and disorders are, nevertheless, considerably lower than reported rates for anxiety and depression.
Prevalence of mental disorders, women and men, rate per 100 000 population, 2021
Note: OECD‑38 are unweighted averages. IHME GBD provides estimates of the prevalence of a range of mental health conditions and neurological disorders based on a wide variety of data sources and a set of modelling assumptions. The IHME defines prevalence as the proportion of people in a population who are a case of a disease, injury or sequela. All results refer to point prevalence. Data for this figure can be downloaded via Annex 7.A.
Source: IHME GBD Results Tool (https://vizhub.healthdata.org/gbd-results/).
While all available data suggests considerable gendered patterns in mental health outcomes (“objective” differences in women’s and men’s experiences of mental health and ill-health), differential rates of reporting are also likely influenced by social and cultural norms. Surveys on attitudes toward mental health and stigma in Sweden, for instance, have found that women are more likely to “report feeling positive attitudes towards those with mental health conditions” than men, which could imply a greater willingness for women to be open about their own mental health (OECD, 2023[99]). Men have also been found to minimise their symptoms more than women, especially when reporting symptoms may result in follow-up treatments and care (OECD, 2023[99]). On top of this, men may struggle with recognising and communicating issues relating to mental ill health to health professionals and with rapport-building (Yousaf, Grunfeld and Hunter, 2013[100]). This suggests that enhancing access to mental health support is only one piece of the puzzle in combatting gender gaps in mental health. Governments should also consider addressing gender norms and stereotypes that discourage men from reporting mental distress and seeking care, and invest in education to help men recognise and communicate about mental ill-health.
Although presented separately, physical health and mental health are intimately related to one another through direct and indirect channels (OECD, 2021[101]; Ohrnberger, Fichera and Sutton, 2017[102]; Canadian Mental Health Association, 2024[103]; Naylor et al., 2016[104]). Chronic stress and anxiety, for instance, have been shown to have negative effects on the cardiovascular, nervous and immune systems. Lower mental health may also affect decision-making processes regarding healthcare, including reduced motivation and use of preventive medicine. From another perspective, living with a chronic condition can have important mental health impacts, especially if the chronic condition limits or interferes with daily living or is subject to bias and discrimination. In addition to influencing one another, many external factors can negatively affect both physical and mental health at the same time, such as poverty, a loss of employment, social isolation, discrimination, trauma, abuse and substance use.
Few OECD countries have publicly available, easily accessible data on race and ethnicity, but race and ethnicity may interact with gender to impact mental health.
In Australia, for example, 42% of First Nations women had a diagnosed mental health condition in 2018‑19, compared to 30% of men – a gap of 12 percentage points (Australian Institute of Health and Welfare, n.d.[105]).
In Canada, 39% of visible minority women and 53% of visible minority men reported excellent or very good mental health in Q2‑Q3 of 2023, for a gender gap of 14 percentage points. This compares to 52% of men and 46% of women who are not a visible minority, a gender gap of 6 percentage points (Statistics Canada, 2024[106]).
7.1.3. Later adulthood: Women live longer than men, but additional years are often in poor health
Upon reaching the age of 60 years, women can continue to expect to live longer than men in all EU and OECD countries. However, as with life expectancies at birth, factoring in healthy life years reduces gender gaps. This suggests that even though men may be dying before women, the extra years gained by women are likely to be lived in poor health (Figure 7.11) (OECD, 2023[107]). It is therefore unsurprising that women represent more than half of all long-term care recipients, both in institutions and in homes (Online Annex Figure 7‑A11) (OECD Data Explorer, 2024[108]).
Life expectancy and healthy life years at age 60 years, number of years, 2021
Note: EU‑27 and OECD‑38 averages are unweighted. The average number of years in full health a person (usually at age 60) can expect to live based on current rates of ill-health and mortality. See WHO “Healthy life expectancy (HALE) at age 60 (years)” for more details. Data for this figure can be downloaded via Annex 7.A.
Source: WHO “Life expectancy and Healthy life expectancy” (www.who.int/data/gho/data/themes/topics/indicator-groups/indicator-group-details/GHO/life-expectancy-and-healthy-life-expectancy).
Beyond the indicators presented in this chapter and in the Online Annex, relevant data sources include:
OECD Health at a Glance: Provides a set of comprehensive indicators on population health and health system performance, including health status, risk factors for health, access to and quality of healthcare, and health system resources.
OECD Dashboard on Gender Gaps: Presents key indicators on gender inequalities in education, employment, governance and private and public leadership, technology and resources and health and well-being.
Institute for Health Metrics (IHME) Global Burden of Disease (GBD): Covers over 400 health outcomes across more than 200 countries and territories to present 600+ billion highly standardised and comprehensive estimates of health outcomes and systems.
World Health Organization (WHO) Health Behaviour in School-Aged Children (HBSC) Study: Presents key indicators into health and well-being and the social determinants of health for young people.
WHO Global Health Observatory: Provides updated data on health and health-related indicators across a range of subjects, including violence, mental health, child mortality, tobacco control, health financing, health taxes and more.
OECD Patient-Reported Indicator Surveys (OECD PaRIS): Presents indicators on self-reported health outcomes and experiences with healthcare among people aged 45 years and older who live with chronic conditions.
OECD Social Institutions and Gender Index (SIGI): Contains data on laws, social norms and practices relating to discrimination in the family, restricted physical integrity, restricted civil liberties and restricted access to productive and financial resources.
Using Table 7.3, this section applies the priority considerations of the conceptual framework included in Chapter 3 to advance gender equality in health by exploring two examples of policy goals (priority consideration 1): improving gender equality in physical and mental health (Outcome A) and reducing gender gaps in physical activity and at all levels of sport (Outcome B). These goals need to be accompanied by a results framework (priority considerations 1 and 4), whose indicators can be drawn from those presented in Section 7.1 and additional sources.
Table 7.3 is designed to assist policy makers in identifying cross-portfolio policy and programme combinations (priority consideration 3) and planning for their evaluation (priority consideration 2). While the list of policy options is extensive, it does not pretend to be exhaustive. At the same time, not all policy options apply in all settings or contexts. Overall, Table 7.3 aims to encourage the consideration of different policy options as part of a cross-sectoral and multi-stakeholder approach that works towards the achievement of gender equality outcomes.
Overcoming gender gaps in physical and mental health, for example, demands a comprehensive approach across the life course. This includes efforts to support a better understanding of gender-specific health conditions and gender differences in signs and symptoms, as well as efforts to address biases in diagnoses and treatments. Governments may need to revisit medical education, curricula and clinical guidelines to ensure that they do not overlook those gender differences, and implement complementary interventions (e.g. awareness raising and training) to address gender biases or underrepresentation in research and clinical trials.
Complementary policies can look at tackling gender stereotypes and norms that may limit the extent to which men seek care, prevent men from recognising and communicating about mental ill-health or distress with medical practitioners, or lead to a belief that women’s pain is a product of emotional rather than physical causes. Tackling gender norms and stereotypes should start early with adequate health education for girls and boys, including a special emphasis on screening, early detection, healthy eating and physical activity.
Approaches to ensure that the specific needs of women and men are better met in healthcare settings encompass ensuring equal representation of women and men as decision-makers on hospital boards and redesigning healthcare services to mainstream gender considerations into both preventive and emergency healthcare (e.g. triage, treatment and discharge). Complementing these interventions with stronger and more inclusive care and social protection systems can contribute to a better work-life balance for both women and men, including access to and use of healthcare services for themselves and their families. Indeed, policies that provide paid parental leave and affordable childcare have been associated with improved physical and mental health outcomes for both parents and children (Van Niel et al., 2020[109]).
Reducing and eliminating gender gaps in physical activity and at all levels of sport also requires a comprehensive approach across various domains and ministries – including education and skills, labour, health, justice and transportation. For instance, supporting the early involvement of girls in physical activity and sports through school curricula and extracurricular activities is crucial for future healthy habits in adulthood. Complementary investments in safe and inclusive sports complexes, fitness facilities, recreational centres and active transportation methods can help to ensure that women feel comfortable and safe engaging in physical activity.
Table 7.3 also highlights the important feedback loops between policy goals. Closing gender gaps in physical activity (Outcome B) will also improve women’s physical health (Outcome A). Preventing and eliminating gender-based violence and supporting victims/survivors (see Chapter 8) can improve physical and mental health for women. Supporting women’s representation in positions of leadership, including in hospitals and sports organisations (see Chapter 6), can help to ensure a greater consideration of those issues facing women and girls. Tackling the (gendered) social determinants of health, including poorer labour market outcomes, lower earnings and a higher risk of old-age poverty for women (see Chapter 5) can further improve women’s health and women’s access to healthcare.
The effectiveness of the policies and programmes outlined in Table 7.3 varies across countries and across time. Continuous monitoring and evaluation that incorporates a gender perspective (priority consideration 5) is essential for governments to understand the gendered effects of policies and programmes (see Chapters 2 and 3); ensure that policies and programmes are achieving their intended outcomes; identify strengths and areas for improvement; improve decision-making, resource allocation and accountability; and inform future strategies (priority consideration 6). While international evidence offers valuable insights on similar interventions, the effectiveness of each policy and programme will depend on their specific design and context – including interactions with other interventions, socio‑economic and cultural factors, available resources, and institutional settings.
For example, a systematic review of the effects of awareness raising and training programmes on gender sensitivity and unconscious biases revealed their positive effects in terms of gender-related knowledge, attitudes and practices among healthcare providers, but highlighted a critical need for more rigorous evaluation of the long-term impact on healthcare providers’ behaviours and practices (Lindsay et al., 2019[110]). Other research has shown that the engagement of men and boys alongside women has proved key in addressing gender inequality and ensuring sexual and reproductive health and rights for all, but a systematic review highlighted that the engagement of men and boys needs to be further strengthened in research and programming (Ruane-McAteer et al., 2019[111]). This is corroborated by studies that indicate that organisations with greater workplace diversity tend to have better patient outcomes (Gomez and Bernet, 2019[112]).
Evidence also suggests that educational initiatives can increase men’s engagement with health services, thereby improving health outcomes (Mahalik, Burns and Syzdek, 2007[113]). This is true also for girls’ physical activity, with a randomised control trial showing that comprehensive school-based interventions increased regular participation in vigorous physical activity among high-school girls (Pate et al., 2005[114]).
7.2.1. Key policy actions across EU and OECD countries
Note: “Env.” stands for Environment and “Agri.” stands for Agriculture.
Source: OECD Secretariat based on desk research and the 2024 OECD Questionnaire on Policy Combinations for Gender Equality, Brussino (2020[38]), Lewis (2023[115]) and Government of Canada (2024[116]).
7.1.1. Country case studies of key policy combinations in EU and OECD countries
According to the OECD Secretariat’s 2024 Questionnaire on Policy Combinations for Gender Equality, many EU and OECD countries have implemented policy combinations to advance gender equality in health. Case studies are provided below.
Improving gender equality in physical and mental health
Health is one of the priorities of Czechia’s Gender Equality Strategy for 2021‑30. The manager and co‑ordinator of the fulfilment of the strategy is the Czech Office of the government, with expected co‑operation and sharing of information between the state administration, local governments, social partners, academic workplaces and non-governmental organisations. The strategy includes several goals, such as reducing gender inequality in access to healthcare, improving the system of assistance for victims of gender-based and domestic violence, increasing the capacity for gender-sensitive health and social services, enhancing the working conditions of healthcare professionals, and raising the satisfaction level of mothers with maternity care. As part of its policy combination, the strategy promotes awareness activities targeted at men, encouraging them to engage more actively in their health. A methodology for risk prevention has also been developed to ensure that the specific needs of women and men are considered. Around motherhood, the strategy prioritises maternal and child health by creating a unified concept of care during pregnancy, childbirth, and the post-partum period. This initiative includes boosting the variability of obstetric services and ensuring these services are reimbursed by public health insurance. The strategy also ensures the regular publication of health statistics disaggregated by gender, supporting the monitoring of health disparities and directing necessary policy adjustments.
In France, support to women’s health is mainly led by the Ministry of Health with support from the Ministries of Solidarity, Education and Equality. The approach targets specific health needs at different life stages. Around childbearing age, for instance, the Ministry of Health focuses on improving access to contraception, particularly for young women in vulnerable circumstances, to empower them to make informed reproductive choices and reduce unplanned pregnancies. This is complemented by improved access to abortion to ensure timely and safe procedures. For women in middle adulthood, the ministry has enhanced comprehensive care and psychological support following miscarriages, recognising their emotional and physical impact. At the same time, the Ministries of Health, Gender, Solidarity and Education have co‑ordinated action to ensure that all women have access to menstrual products, especially those in economic hardship. The Ministry of Health has also prioritised the diagnosis and treatment of endometriosis by increasing awareness and improving care for affected women. Additionally, to improve overall healthcare access, the Ministries of Health and Equality are expanding outreach services to reach women in remote or underserved areas – with 30 mobile health units designed for gynaecological and cardiovascular screening and prevention. Other initiatives have also been put in place in France to improve access to healthcare and reduce health disparities, including “1 000 premiers jours” (1 000 first days), a programme to provide pregnant women and young mothers, particularly those in precarious situations, with enhanced support; the rollout of “Maisons de santé pluridisciplinaires” (multidisciplinary health centres) to provide access to healthcare for isolated populations; and the “Stratégie nationale de santé mentale et de psychiatrie 2018‑23” to focus on prevention and access to appropriate care for vulnerable populations. In addition, specialised units in hospitals to support victims of domestic violence have been introduced. In January 2024, there were 74 dedicated units for women victims of violence attached to hospital structures also known as “women’s health centres.” Additional funding was allocated in 2024 to create new ones, with the aim of covering the entire country.
Latvia has implemented initiatives aimed at addressing gender-specific health needs across different stages of life. These measures, led by the Centre for Disease Prevention and Control under the Ministry of Health, contribute to promoting gender equality in health outcomes. Young adults’ health is supported via awareness raising of Human Papillomavirus (HPV) vaccination for girls and boys, as well as the provision of health guidance and self-examination materials. Latvia also addresses the mental health needs of new parents through information packages of support for postpartum mental health conditions, and specific supports for both mothers and their partners. Additionally, campaigns promote safe practices in beauty care services to address the risks associated with invasive procedures. These efforts are complemented by awareness campaigns for cancer screenings to ensure early detection of gender-specific cancers such as breast, cervical, and prostate cancer. Information materials on sexual and reproductive health for women and men over 50 provide guidance on managing the physiological and emotional changes associated with ageing. Finally, Latvia’s harm reduction programmes, including HIV prevention points and mobile units, provide critical services to high-risk populations.
Australia’s National Women’s Health Strategy 2020‑30 outlines a comprehensive life course approach to improving the health and well-being of women and girls. Key objectives include achieving health equity, enhancing access to health services and supporting preventive health measures. The strategy focuses on empowering women in their healthcare and promoting gender-sensitive practices within the health system.
The Women’s Health Strategy for England, the United Kingdom aims to address health disparities, improve health outcomes and support women’s and girls’ overall well-being through a life course approach. It focuses on prioritising women’s voices, addressing the impact of violence, improving access to health services and tackling specific health issues, such as reproductive health, menopause and mental health. The strategy also emphasises research and data collection to better understand women’s health needs and promote gender-sensitive care within the healthcare system.
Reducing gender gaps in physical activity, including at all levels of sport
The National Programme of Sports 2019‑26, promoted by the Ministry of Tourism and Sports in Croatia, includes gender equality as one of its specific objectives. In addition, the “Action plan for the inclusion of a greater number of women in sports” supports women’s representation in management bodies of sports organisations, as well as in other decision-making positions in sports. At the same time, the “Women in sports” project, implemented in Croatia, promotes campaigns supporting gender equality in sports, including how sport is covered in social networks and the media. It targets specific stakeholders – managers, referees and athletes – as well as the general public. The project has been implemented through co‑ordination between several stakeholders including the Office for Gender Equality of the Government of Croatia, the Ombudsperson for Gender Equality, the Electronic Media Council, and the Croatian Olympic and Paralympic Committees.
Note: Supporting data for all Chapter 7 figures in the main text and the Online Annex are available in the StatLink below.
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← 1. Estimates use a minimum cell size of 10 observations. Only 22 countries met this criterion.