GENDER AND NONCOMMUNICABLE
DISEASES IN ARMENIA
Analysis of STEPS data
GENDER AND NONCOMMUNICABLE
DISEASES IN ARMENIA
Analysis of STEPS data
need to be unpacked through sociodemographic characteristics, because men and women are not homogenous groups. The report also recognizes gaps in evidence and calls for further analysis of the impact of gender-based inequalities.
KEYWORDS
NONCOMMUNICABLE DISEASES GENDER
SOCIOECONOMIC FACTORS RISK FACTORS
HEALTHY DIET ALCOHOL TOBACCO USE OBESITY
BLOOD PRESSURE ARMENIA
WHO/EURO:2020-1665-41416-56458
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iii
ACKNOWLEDGMENTS iv
EXECUTIVE SUMMARY v
INTRODUCTION 1 NCDS CONSTITUTE THE MAIN BURDEN OF DISEASE FOR BOTH WOMEN AND MEN,
BUT THERE ARE IMPORTANT DIFFERENCES 4
DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS 5
SIGNIFICANT DIFFERENCES BETWEEN MEN AND WOMEN 6
PREVALENCE OF THREE OR MORE RISK FACTORS 7
MORTALITY RATES AMONG MEN AND WOMEN 8
DIFFERENCES IN SPECIFIC RISK FACTORS AMONG MEN AND WOMEN BETWEEN AGE GROUPS 9 DIFFERENCES IN THE WAY MEN AND WOMEN ACCESS SERVICES 15 DIFFERENCES IN MEN AND WOMEN NOT MEASURED FOR RISK FACTORS 16 LIFESTYLE ADVICE GIVEN BY A HEALTH-CARE PROFESSIONAL 18 CONCLUSIONS 21 REFERENCES 25 ANNEX 1. SUPPLEMENTARY TABLES 29
CONTENTS
between the Gender and Human Rights programme and the WHO European Office for the Prevention and Control of Noncommunicable Diseases to accelerate progress towards reducing the burden of noncommunicable diseases using a gender approach.
The editors of the series and of this report are Isabel Yordi Aguirre and Ivo Rakovac from the WHO Regional Office for Europe. They conceptualized the series’ publications, defined content, provided overall input, and reviewed and amended the content of the report to ensure alignment with overall WHO policy and guidance documents. The authors of the report are Brett J. Craig, WHO Regional Office for Europe, and Diana Andreasyan, Deputy Director of the National Institute of Health, Ministry of Health of Armenia. Overall support and leadership for this initiative was provided by João Breda, Head of the WHO European Office for Prevention and Control of Noncommunicable Diseases, Nino Berdzuli, Director of the Division of Country Health Programmes, and Natasha Azzopardi- Muscat, Director of the Division of Country Health Policies and Systems, WHO Regional Office for Europe.
Input was provided by: Rosemary Morgan, Johns Hopkins Bloomberg School of Public Health, United States of America; and Åsa Nihlén, Jill Farrington, Juan Tello and Enrique Loyola, WHO Regional Office for Europe.
The work to create the country profile was made possible by the generous support of the governments of the Russian Federation and Germany.
v
EXECUTIVE SUMMARY
This country profile for Armenia presents an analysis of sex-disaggregated data linked with other variables, such as education and income, gathered through the WHO STEPwise (STEPS) survey as part of WHO Regional Office for Europe’s gender and noncommunicable diseases (NCDs) initiative to improve the response to NCDs in the WHO European Region through a gender approach. It is the first gender analysis of NCD risk factor data for adults in Armenia and makes an important contribution to, and serves as an evidence base for, international commitments on NCDs in accelerating action towards reducing the NCD burden and ensuring universal health coverage. It also contributes to raising awareness and building capacity among country-based researchers and policy-makers on the rationale for applying a gender analysis to health data.
A gender analysis of STEPS NCD risk-factor survey data describes how risk factors for chronic diseases differ between and among men and women by exploring and tracking the direction and magnitude of trends in risk factors and accessing services. It enables better planning and/or evaluation of gender-responsive health promotion or preventive campaigns and gender-responsive interventions.
The analysis in this country profile examined differences in risk factors and accessing services between men and women overall by age group, education and income level. Important differences hide even in sex-disaggregated data that need to be unpacked by including sociodemographic characteristics, because men and women are not homogenous groups.
Globally, more than 100 countries have collected data through the STEPS surveys, but this is the first time a more in-depth analysis from a gender perspective has been conducted. The following findings of the gender analysis therefore can be used to address specific needs and policy opportunities for Armenia.
• Significantly higher percentages of men than women in most age groups engage in the behavioural risk factors for NCDs (like tobacco-smoking, alcohol consumption, insufficient levels of physical activity, insufficient intake of fruit and vegetables, adding salt to the diet and frequent consumption of processed foods), and higher percentages of women than men in the older age groups are found with most of the biological risk factors (overweight and obesity, and raised blood pressure, glucose and cholesterol).
• Over the life-course, prevalence of biological risk factors is higher among women than men in the older age groups but is lower among women than men in the younger age groups.
• Associations between behavioural risk factors and education levels vary for both men and women. Differences in biological risk factors show significantly higher prevalence among medium-education men and medium- and low-education women. Observed variation by income is smaller than by education.
• A significantly higher percentage of men have not been measured for biological risk factors, while a higher percentage of women have been given lifestyle advice by a health-care professional on most behavioural risk factors. There is a need to further identify gender- specific norms and barriers to access and exposure to risk.
those with high education levels, and education levels vary more for men than women. Men and women at low-income level are being measured less for risk factors than those at high-income level, and low-income women are being measured at virtually the same rate as high-income men.
• Improving access to services for women and men may therefore require that additional attention is paid to the following groups: men in the younger age groups; men with low education levels;
women with low and medium education levels; and men and (especially) women with low income levels.
• Studies that specifically examine gender and social norms and gender inequality in these contexts can be used to complement this analysis by identifying driving and constraining factors for men and women in exposure to risk and access to services.
In addressing the areas identified in this report, cost-effective interventions like best-buy and other interventions recommended by WHO should be prioritized and tailored to the country-specific context to ensure uptake and efficiency. This would greatly contribute to the achievement of universal health coverage and the health-related Sustainable Development Goals.
INTRODUCTION
The WHO Regional Office for Europe launched a gender and noncommunicable diseases (NCDs) initiative in 2019 to improve the response to NCDs in the Region through a gender approach. Gender and rights-based approaches are imperative to accelerate transformative and sustainable progress towards achievement of the United Nations Sustainable Development Goals (SDGs). The strategy on women’s health and well-being in the WHO European Region (1) and the strategy on the health and well-being of men in the WHO European Region (2) strengthen the links between SDGs 3 and 5 in the Region while providing a comprehensive working framework for improving health and well-being in Europe through gender- responsive approaches.
Commitments by Member States of the WHO European Region to accelerate actions towards reducing NCDs build on the Action Plan for the Prevention and Control of Noncommunicable Diseases in the WHO European Region 2016–2025 (3) and high-level meetings, in particular Health Systems Respond to NCDs:
Experience in the European Region (Sitges, Spain, 16–18 April 2018) (4) and the WHO European High-level Conference on Noncommunicable Diseases: Time to Deliver – Meeting Noncommunicable Disease Targets to Achieve the Sustainable Development Goals in Europe (Ashgabat, Turkmenistan, 9 April 2019) (5).
To support these commitments with evidence and knowledge exchange, country profiles of Armenia, Belarus, Georgia, Kyrgyzstan, the Republic of Moldova, Turkey, Ukraine and Uzbekistan have been created using a gender analysis of data gathered through the WHO STEPwise approach to Surveillance (STEPS) NCD risk-factor survey.
This country profile for Armenia presents an analysis of sex-disaggregated data linked with other variables, such as education and income, gathered through the STEPS survey. The analysis allows identification of the main gender-based differences and highlights some of the areas that need further gender analysis. Evidence generated within the country profiles in the series is intended to provide an evidence base and rationale for countries to strengthen health-systems and whole-of-government responses to prevent, detect, manage and control NCDs, particularly at primary-care levels, through gender-responsive actions (Fig. 1).
Source: WHO (6).
Gender unequal Perpetuates inequalities
Gender blind Ignores gender norms
Gender sensitive Acknowledges but does not address inequalities
Gender specific Considers women’s and men’s specific needs
Gender transformative Aims at transforming harmful gender norms, roles and relations
GENDER-RESPONSE POLICY
Considers genders, norms, roles and relations
Takes active measures to reduce harmful effects Fig. 1. WHO gender-response assessment scale
3
GENDER AND NONCOMMUNICABLE DISEASES IN ARMENIA INTRODUCTION
The analysis follows the key elements identified by the WHO Regional Office for Europe (7). A gender analysis considers socially constructed norms, roles, behaviours and attributes that a given society considers appropriate for women and men and how this implies differential degrees of power between and among women and men. It recognizes that women and men are not homogenous groups and that their health opportunities and risks vary according to social, economic, environmental and cultural influences throughout their lifetime, while also considering how gender intersects with other factors behind social inequalities, such as age, income, education, ethnicity or place of residence.
The STEPS surveys (8) gather information on NCD risk factors to help plan and evaluate programmes and interventions by collecting standardized, high-quality risk-factor data to enable comparisons while allowing flexibility. The STEPS surveys consist of interviews (STEP 1), physical measurements such as blood pressure, weight and height (STEP 2) and biochemical measurements like blood glucose and cholesterol (STEP 3). An integrated approach is used, allowing an analysis of multiple risk factors simultaneously in a cost-efficient manner. WHO provides countries with a reference methodology for NCD surveillance and technical support for implementation.
A gender analysis of STEPS NCD risk-factor survey data describes how risk factors for chronic diseases differ between and among men and women by exploring and tracking the direction and magnitude of trends in risk factors and how these differ between and among women and men. It enables better planning and/or evaluation of gender-responsive health promotion or preventive campaigns and gender-responsive interventions. At the same time, data reveal important differences between men and women in relation to access to health services.
The survey in Armenia was carried out from September 2016 to December 2016. A cluster sample design was used to produce nationally representative data for the age range 18–69 years. The overall response rate was 42%, with 2349 adults participating in the survey. The data were weighted for complex survey design, non-response rate and population distribution by age and sex.
The analysis examined differences between and among men and women in risk factors and accessing services. In addition to looking at overall differences between men and women in risk factors, the analysis examined differences in groups of behavioural and biological risk factors. Differences among men and among women were then analysed by age group and other sociodemographic variables for both individual risk factors and groups of risk factors. Overall and within-group differences were also analysed by sociodemographic variables for accessing services. Examining sex-disaggregated data not only for overall differences between men and women but also for differences within these groups across the life-course is necessary because men and women are not homogenous groups. There are important differences hiding even in sex-disaggregated data that need to be unpacked by including sociodemographic characteristics.
The country profiles in this series are the first steps in mainstreaming gender, which is explained and further elaborated in the WHO manual Gender mainstreaming for health managers: a practical approach (6) (Fig. 2).
NCDs constitute the main burden of disease for both women and men, but there are important differences
NCDs are the leading cause of death, disease and disability in the WHO European Region, and represent the greatest burden of disease in Armenia. NCDs are estimated to account for 93% of all deaths in Armenia (9), with deaths from the most prevalent NCDs (circulatory system diseases, malignant neoplasms, diabetes mellitus and chronic obstructive lung diseases) making up 80%. Circulatory system diseases alone account for nearly 55% of all deaths in the country (10). Diabetes mellitus is one of the top five causes of years lived with disability (11). In 2016, it was estimated that 38% of the adult population had raised blood pressure, 28% smoked tobacco, 21% were physically inactive, 20% were obese, 11% had raised blood glucose and 6% used alcohol harmfully (9).
The Ministry of Health has taken steps to reduce the burden of NCDs through the launch of a screening programme in 2015 for hypertension, diabetes and cervical cancer. Preventive health examinations at least once a year are recommended by the ministry for Armenian citizens (12), but the prevalence of risk factors that account for NCDs are different between and among men and women, and there are important differences in the ways men and women access health services.
Source: WHO (6).
ACCOUNTABILITY
Sexdisaggregated data + Gender
analysis + Gender-responsive action
ST EP S
Fig. 2. Gender mainstreaming steps
GENDER AND NONCOMMUNICABLE DISEASES IN ARMENIA
DIFFERENCES IN BEHAVIOURAL
AND BIOLOGICAL RISK FACTORS
For behavioural risk factors, the STEPS data focus specifically on tobacco use, harmful alcohol consumption, unhealthy diet (low fruit and vegetable consumption, diet high in salt and/or processed foods) and insufficient physical activity. For biological risk factors, they look at overweight/obesity, raised blood pressure, raised blood glucose and raised cholesterol. Highlighting where the highest differences exist will help to uncover where inequitable gender norms, roles, behaviours and attributes are likely to have the greatest effect on risk factors.
Significant differences between men and women
The prevalence of these risk factors for men and women was examined and tested for significant differences (Fig. 3 and Annex 1, Table A1.1).
While prevalence among men is significantly higher than for women in most of the behavioural risk factors, the same trend is not found for the biological risk factors. Prevalence is significantly higher for women in obesity, and there is no significant difference between men and women in overweight, raised blood pressure, raised blood glucose and raised cholesterol. The prevalence of raised blood pressure without medication is the only biological risk factor for which men are significantly higher than women.
BMI: body mass index. * Statistically significant difference.
0 10 20 30 40 50 60 70 80 90
Current tobacco use*
Alcohol*
Alcohol (heavy episodic)*
Unhealthy diet ( < 5 fruit/veg per day) Unhealthy diet (add salt)*
Unhealthy diet (processed food) Insufficient physical activity
Overweight (BMI ≥ 25) Behavioural risk factors
Biological risk factors
Obesity (BMI ≥ 30)*
Raised blood pressure (or on medication) Raised blood pressure NOT on medication Raised blood glucose (or on medication) Raised cholesterol (or on medication)
Men Women
Fig. 3. Prevalence of risk factors across countries with differences between men and women (%)
GENDER AND NONCOMMUNICABLE DISEASES IN ARMENIA
7 DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS
Prevalence of three or more risk factors
Differences between men and women in the prevalence of NCD risk factors are also found in those more at risk due to the prevalence of multiple risk factors. In accordance with the STEPS methodology, selected risk factors were used to examine the prevalence of three or more risk factors in the population. These combined risk factors are:
• current daily smokers;
• fewer than five servings of fruit and vegetables per day;
• insufficient physical activity (< 150 minutes of moderate-intensity activity per week, or equivalent);
• overweight (body mass index (BMI) ≥ 25 kg/m2); and
• raised blood pressure (BP) (systolic BP ≥ 140 and/or diastolic BP ≥ 90 mmHg or currently on medication).
Overall, a significantly higher percentage of men (43.2%) have three or more risk factors compared to women (28.4%). A lower percentage of men (4.7%) than women (9.2%) do not have any risk factors.
In addition to overall differences between men and women in multiple risk factors, prevalence through the life-course is different for men and women. As expected, the percentage of men and women with three or more risk factors is higher in older than in younger age groups. Through the age groups from 18–29 to 45–59, the percentages of both men and women with three or more risk factors rises significantly with each successive group; with the 60–69 age group, however, a significantly higher percentage of women have three or more risk factors than in the 45–59 age group, whereas for men there is no significant difference.
The percentage of men with three or more risk factors starts higher in the younger age groups, but the percentage increase among age groups for women becomes more dramatic in the middle age groups.
This causes the difference to lessen until the oldest age group, where there is no significant difference.
While the percentage of men doubles from the 18–29 age group to the 60–69, from 26.6% to 55.7%, the percentage of women with three or more risk factors is more than 13 times greater between comparable age groups, from 5.0% to 66.3% (Fig. 4 and Annex 1, Table A1.2).
These combined risk factors, however, do not include all risk factors, such as alcohol consumption or raised cholesterol. Additionally, risk factors have different impacts on NCD morbidity and mortality. For example, the risk associated with smoking is higher at individual level than the risk associated with eating fewer than five servings of fruit and vegetables (13): further analysis therefore is warranted to examine differences in these risk factors between men and women as well as among men and women.
Mortality rates among men and women
Though difficult to calculate, there is probably an influence of mortality rates on prevalence of risk factors in the population when examining differences between men and women through the life-course. The mortality rate for men is significantly higher than for women and increases in older age groups (Fig. 5 and Annex 1, Table A1.3) (14).
0 10 20 30 40 50 60 70 80
18–29 30–44 45–59 60–69
Men Women
Fig. 4. Prevalence with three or more risk factors by age group (%)
0 10 20 30 40 50 60 70 80
20–29 30–44 45–59 60–69
Men Women
Fig. 5. Total mortality per 1000
9
GENDER AND NONCOMMUNICABLE DISEASES IN ARMENIA DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS
The higher mortality rates for men may account for some of the lessening of the gap observed between men and women with three or more risk factors in the older age groups.
Differences in specific risk factors among men and women between age groups
Not only do men and women experience multiple risk factors differently through the life-course, but their experience with individual risk factors is also different. Examining the differences between men and women in more detail and by age group regarding risk factors reveals further the importance of gender analysis. The difference between age groups for either sex in each behavioural risk factor shows how many more men than women engage in nearly all risk factors across age groups (Fig. 6 and Annex 1, Table A1.4).
Where prevalence among men in, for example, alcohol consumption may increase with each ascending age group, prevalence in women is higher in the youngest age group and then decreases. Prevalence for each risk factor also varies between age groups and by sex; for example, differences between age groups for adding salt to the diet may be more pronounced among women, with the differences being less for men.
The story for biological risk factors and age is quite different. The percentages of men and women with biological risk factors is significantly higher with each advancing age group (Fig. 7 and Annex 1, Table A1.5). More important is that prevalence for men starts higher in the youngest age group but for women is higher for every biological risk factor in older age groups.
These data show that prevalence of biological risk factors for women increases with older age groups more dramatically than with men. This applies not only to the population with multiple risk factors, but also to each individual risk factor. For example, though the prevalence of overweight for women is significantly
0 10 20 30 40 50 60 70 80 90 100
Current tobacco use
Alcohol
Alcohol (heavy episodic) Unhealthy diet ( < 5 fruit/veg per day) Unhealthy diet (add salt) Unhealthy diet (processed food) Insufficient physical activity
Men Women 18–29 30–44 45–59 60–69
Fig. 6. Prevalence of behavioural risk factors by age group (%)
More men than women engage in behavioural risk factors across the life-course
higher than for men overall, prevalence for men in the 18–29 age group is significantly higher (30.7%) than for women (19.0%). In the 60–69 age group, however, prevalence is significantly higher for women (84.8%) than for men (60.2%). With obesity, prevalence for women is not signfiicantly different between men and women in the 18–29 age group (3.8% men, 5.1% women), but is more than double for women (52.7%) than it is for men (20.7%) in the 60–69 age group. This same trend is visible with raised blood pressure, raised blood glucose and raised cholesterol.
While differences between men and women are apparent across the life-course, disaggregating data reveals additional differences among men and among women. Disaggregation by age group reveals specific groups of men and women who are more at risk and differences by sex. Other demographic categorizations, such as education and income levels, further help identify differences between men and women and differences within these groups.
EDUCATION LEVELS
The education level of the population can be used to examine further the differences in risk factors not only between men and women, but also within the groups of men and women. Armenia has extremely high literacy rates (99.8% for men, 99.7% for women) and high enrolment in primary (90.9% for boys, 90.6% for girls) and secondary education (87.5% for males, 88.1% for females). A significant difference is visible only at tertiary level (47.1% for males, 67.7% for females) (15).
Data on education level, determined by the highest level of education completed, were collected in the STEPS survey using country-specific categories. The categories have been matched to the levels of the International Standard Classification of Education (ISCED) (16) then condensed to reflect the three levels of low, medium and high (Table 1 and 2).
Overweight (BMI ≥ 25)
Obesity (BMI ≥ 30)
Raised blood pressure (or on medication) Raised blood pressure NOT on medication Raised blood glucose (or on medication)
Raised cholesterol (or on medication)
0 10 20 30 40 50 60 70 80 90 100
Men Women 18–29 30–44 45–59 60–69
Fig. 7. Prevalence of biological risk factors by age group (%)
Prevalence of women with biological risk factors starts lower than men but ends higher
GENDER AND NONCOMMUNICABLE DISEASES IN ARMENIA
11
The prevelence of behavioural risk factors for men and women varies by education level, depending on the risk factor and whether it is men or women in that level (Fig. 8 and Annex 1, Table A1.6). For example, alcohol consumption in the medium education level for men (54.9%) is significantly higher than both the high (43.5%) and low levels of education (43.5%), while for women, the highest prevalence with alcohol consumption is found at medium (23.9%) and high (25.9%) levels of education, with low education being the lowest (17.2%). Differences between men and women and between education levels vary by risk factor, demonstrating that both men and women in the high education level do not necessarily engage less in behavioural risk factors than those at other education levels.
Additional differences in education levels are observed between and among men and women in relation to biological risk factors. Overall, the prevalence of biological factors for women tends to be lower in the high-education group, which is not necessarily the case for men with high-level education. Higher percentages tend to be found at the medium education level for men and medium and low levels for women (Fig. 9 and Annex 1, Table A1.7).
DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS
STEPS survey categories ISCED levels
1 = no formal schooling ISCED 0 = early childhood education 2 = less than primary school
3 = primary school completed ISCED 1 = primary education 4 = secondary school completed ISCED 2 = lower-secondary education 5 = high school completed ISCED 3 = upper-secondary education
ISCED 4 = post-secondary non-tertiary education ISCED 5 = short-cycle tertiary education
6 = college/university completed ISCED 6 = bachelor’s degree or equivalent tertiary education 7 = postgraduate degree ISCED 7 = master’s degree or equivalent tertiary education
ISCED 8 = doctoral degree or equivalent tertiary education Table 1. STEPS survey categories and ISCED levels
Education level for analysis STEPS survey categories ISCED levels Low level of education 1 = no formal schooling
2 = less than primary school 3 = primary school completed 4 = secondary school completed
ISCED 0–2
Medium level of education 5 = high school completed ISCED 3–5
High level of education 6 = college/university completed
7 = postgraduate degree ISCED 6–8
Table 2. Education level for analysis
With overweight, obesity and raised blood pressure, prevalence is lowest among the high education level for women and tends to be similar in the low and medium education levels. Prevalence among men for these risk factors follows a different pattern, with prevalence being lowest among those with low education and highest at the medium education level, with the high education level being somewhat in between.
Additional differences that are not apparent in the overall differences in biological risk factors are observed when comparing education levels between men and women. For example, while the overall prevalence of
Current tobacco use
Alcohol
Alcohol (heavy episodic) Unhealthy diet ( < 5 fruit/veg per day) Unhealthy diet (add salt) Unhealthy diet (processed food) Insufficient physical activity
0 10 20 30 40 50 60 70 80 90 100
Men Women Low Medium High
Fig. 8. Prevalence of behavioural risk factors by education level (%)
Behavioural risk factors for both men and women are not necessarily lower in the higher education groups
Overweight (BMI ≥ 25)
Obesity (BMI ≥ 30)
Raised blood pressure (or on medication) Raised blood pressure NOT on medication Raised blood glucose (or on medication)
Raised cholesterol (or on medication)
0 10 20 30 40 50 60 70 80 90 100
Men Women Low Medium High
Fig. 9. Prevalence of biological risk factors by education level (%)
Highest percentages in medium level of education for men, medium and low levels for women in biological risk factors
13
GENDER AND NONCOMMUNICABLE DISEASES IN ARMENIA DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS
obesity is significantly higher among women (25.0%) than men (14.0%), it is the prevalence among medium (29.6%) and low education level women (28.2%) that drives the difference. Prevalence of obesity among high-education women (13.6%) is not only significantly lower than the other levels for women, but is also not significantly higher than for any of the levels for men (11.0% low, 19.5% medium and 15.6% high).
There is no significant difference between men and women overall for raised blood pressure, but prevalence among medium education level men (55.7%) is significantly higher than for any education level for women (38.8% low, 40.1% medium and 27.0% high). Differences in prevalence of risk factors between men and women are often dependent on prevalence in groups among men and among women.
INCOME LEVELS
An analysis by income level can also be used to examine differences among men and women due to differences in lifestyle and access to resources. Five household income quintiles were used in the STEPS survey; based on average income levels and adjusting for household size, categories of high income (annual income greater than 721 000 Armenian drams (AMD)) and low income (less than 720 000 AMD) were created for this analysis.
The estimated average annual earned income per capita for women in Armenia is approximately 52% of what it is for men (the equivalent of Int$ 6100 for women and Int$ 11 700 for men) (15). While 75.2% of men participate in the labour force, only 55.8% of women do so. The percentages of men and women who are not currently employed but are seeking employment are not significantly different (18.2% for women, 18.3% for men), though a higher percentage of women (42.9%) than men (23.9%) are part-time workers, and woman engage in unpaid work nearly five times as much as men (15).
Disaggregating the STEPS survey data by income levels and sex reveals how the prevalence of behavioural risk factors varies in some groups and not in others (Fig. 10 and Annex 1, Table A1.8).
While many differences in behavioural risk factors by income level are not significant, the overall trend for men is that prevalence of behaviours such as tobacco and alcohol use is higher among low-income groups, whereas eating processed foods and having insufficient physical activity are higher among high-income groups. The differences by income level for women are even less pronounced.
The prevalence of biological risk factors by income level and sex also shows limited variance, with no significant differences between men and women beyond what was already known from the more aggregated comparison. Again, the trend of higher prevalence is at low-income level, with some exceptions (Fig. 11 and Annex 1, Table A1.9).
While prevalence of overweight by income level is higher overall among women (50.1%) than men (45.4%), certain groups are observed to be driving this difference. Prevalence of overweight among high-income men (48.0%) and women (48.3%) is not significantly different, but prevalence among low-income women (51.5%) is significantly higher than in low-income men (42.5%). The association between low income and overweight is different for men and women.
Current tobacco use
Alcohol
Alcohol (heavy episodic) Unhealthy diet ( < 5 fruit/veg per day) Unhealthy diet (add salt) Unhealthy diet (processed food) Insufficient physical activity
0 10 20 30 40 50 60 70 80 90 100
Men Women Low High
Fig. 10. Prevalence of behavioural risk factors by income level (%)
Prevalence tends to be higher in the low-income group across risk factors, more so for men than women
Overweight (BMI ≥ 25)
Obesity (BMI ≥ 30)
Raised blood pressure (or on medication) Raised blood pressure NOT on medication Raised blood glucose (or on medication)
Raised cholesterol (or on medication)
0 10 20 30 40 50 60 70 80 90 100
Men Women Low High
Fig. 11. Prevalence of biological risk factors by income level (%)
Low income level has the opposite effect on prevalence of overweight for women as for men
GENDER AND NONCOMMUNICABLE DISEASES IN ARMENIA
DIFFERENCES IN THE WAY MEN
AND WOMEN ACCESS SERVICES
In addition to the differences observed between and among men and women in NCD risk factors, significant differences are also found between men and women in accessing services for NCDs. A significantly higher percentage of men report never having had their blood pressure, blood glucose and cholesterol levels measured by a health-care professional (Fig. 12 and Annex 1, Table A1.10).
Differences in men and women not measured for risk factors
The groups can be examined further to identify target populations that may be facing barriers to accessing services (Fig. 13 and Annex 1, Table A1.11).
0 20 40 60 80 100
Blood pressure
not measured Blood glucose
not measured Cholesterol
not measured Men Women
Fig. 12. Percentage not measured for risk factors by a health-care professional
Blood pressure not measured
Blood glucose not measured
Cholesterol not measured
0 10 20 30 40 50 60 70 80 90 100
Men Women 18–29 30–44 45–59 60–69
Fig. 13. Percentage not measured for risk factors by age group
17
GENDER AND NONCOMMUNICABLE DISEASES IN ARMENIA DIFFERENCES IN THE WAY MEN AND WOMEN ACCESS SERVICES
It is not surprising that the percentages of men and women who have not been measured for these risk factors decreases with each age group. The benefit the analysis brings, however, is to expose the significant differences between men and women at each age group, and to identify which age groups are significantly different for both men and women. This reveals that trends in accessing services differ between men and women across the life-course.
The lowest prevalence of blood pressure not being measured, for example, is in the 60–69 age group for both men and women. The percentage of men not measured in this age group (27.5%), however, is almost equal to the lowest age groups for women (18–29, 26.1% and 30–44, 26.6%). The percentage of men who have not had their blood glucose and cholesterol levels measured does not decrease between the 18–29 age group (78.1% for glucose and 81.5% for cholesterol) and the 30–44 group (77.6% and 82.4%). More men than women have not been measured in every age group.
EDUCATION LEVEL
Further differences can be seen when those not being measured for risk factors are examined by education level. Overall, both men and women with lower education levels are being measured less than those with high education levels (Fig. 14 and Annex 1, Table A1.12).
Education level has a different effect on men and women and also by the risk factor for which men and women are being measured. For example, while a higher percentage of men report never having had their blood pressure measured, analysis by education level reveals this difference is only significant for men with low (44.2%) and medium (38.5%) levels of education. For women who have never had their blood pressure measured, there is no difference between education levels (23.3% low, 22.9% medium and 23.3% high), while there is more variance for men, and more men with low education levels (44.2%) have not been measured.
Blood pressure not measured
Blood glucose not measured
Cholesterol not measured
0 10 20 30 40 50 60 70 80 90 100
Men Women Low Medium High
Fig. 14. Percentage not measured for risk factors by education level
Men and women in the lower education levels are measured for risk factors less
INCOME LEVEL
Just as education level can present barriers to accessing services for men and women, income level may also compromise access due to its relationship with resources. Overall, higher percentages of men and women with low incomes have not been measured for risk factors (Fig. 15 and Annex 1, Table A1.13).
The difference between low- and high-income groups of men and women who have not had these risk factors assessed is greater for blood glucose and cholesterol measurements than for blood pressure.
Differences in income level for blood glucose and cholesterol reveal that while overall more men than women have not been measured, low-income women (60.6% glucose and 71.5% cholesterol) have not been measured at a similar rate as high-income men (67.3% glucose and 69.8% cholesterol). High-income women and low-income men are driving the difference seen in the aggregate. Efforts to increase access therefore should not focus on men as a homogenous group, as low-income men are being measured less and low-income women are not being measured at a similar rate to high-income men.
Lifestyle advice given by a health-care professional
Men and women access services differently, and the responses they receive when they access services can also differ. The STEPS survey gathered information on whether men and women had been given lifestyle advice when they had visited a health-care professional. The topics under lifestyle advice can be compared with the prevalence of related risk factors (Table 4) to examine more differences between sexes.
Blood pressure not measured
Blood glucose not measured
Cholesterol not measured
0 10 20 30 40 50 60 70 80 90 100
Men Women Low High
Fig. 15. Percentage not measured for risk factors by income level
Low-income men and women are measured less for risk factors
Lifestyle advice topic Related risk factor
Quit using tobacco or don’t start Current tobacco use
Reduce salt in your diet Unhealthy diet (added salt)
Eat at least five servings of fruit and/or vegetables each day Unhealthy diet (< 5 fruit/veg) Start or do more physical activity Insufficient physical activity Maintain a healthy body weight or lose weight Overweight (BMI ≥ 25) Table 4. Lifestyle advice topics and prevalence of related risk factors
GENDER AND NONCOMMUNICABLE DISEASES IN ARMENIA
19
In one lifestyle topic (avoiding tobacco use), a significantly higher percentage of men than women have been given advice, while a significantly higher percentage of women have been given advice on eating more fruit and vegetables.
A significantly higher percentage of men (17.4%) than women (1.7%) report having received advice on tobacco use and the prevalence of men who currently use tobacco (51.5%) is three times greater. Women, however, report being given advice at nearly the same percentage as the prevalence of the risk factor of current tobacco use (1.8%). This may be due to primary health-care protocols addressing women’s health that require the provider to discuss tobacco use, or to women accessing services more than men.
Additionally, social stigma surrounding women using tobacco may affect responses to the STEPS survey (Fig. 16 and Annex 1, Table A1.14).
The percentages of those receiving lifestyle advice are in all cases lower than the prevalence of the related risk factors. The difference in lifestyle advice given to men and women, and the corresponding prevalence of the related risk factors, warrants further analysis.
0 20 40 60 80 100
Tobacco Diet
(fruit/veg)
(salt)Diet Physical Body weight
activity
Advice given to men Advice given to men Related risk factor for men Related risk factor for women Advice given to women
Fig. 16. Percentage of lifestyle advice given for related risk factors
DIFFERENCES IN THE WAY MEN AND WOMEN ACCESS SERVICES
CONCLUSIONS
This country profile presents the first gender analysis of NCD risk factor data for adults in Armenia. It makes an important contribution to, and serves as an evidence base for, enabling achievement of the SDGs, women’s and men’s health strategies (1,2), the European action plan for the prevention and control of NCDs (3) and other international commitments on NCDs, and promoting improved use of disaggregated data for better health outcomes, gender equality and human rights. It is also an important tool in accelerating action towards reducing the NCD burden and ensuring universal health coverage by unpacking inequalities by sociodemographic determinants in NCD risk factors and health system response, and contributes to raising awareness and building capacity among country-based researchers and policy-makers on the rationale for applying a gender analysis to health data.
Globally, more than 100 countries have collected data through the STEPS surveys, but this is the first time a more in-depth analysis from a gender perspective has been conducted. The following findings of the gender analysis therefore can be used to address specific needs and policy opportunities for Armenia.
Significantly higher percentages of men than women in most age groups engage in behavioural risk factors, and higher percentages of women than men in the older age groups are found with most of the biological risk factors. Although high prevalence of behavioural and biological risk factors for both men and women is concerning, the greater prevalence for women in the older age groups, despite lower prevalence in behavioural risk factors, demands attention.
Men and women not only engage differently in behavioural risk factors, but also have different risk factor trajectories for both behavioural and biological risk factors over the life-course. Most notably, prevalence of biological risk factors is higher among women than men in the older age groups, but is lower among women than men in the younger age groups. The importance of disaggregation by sex and age becomes apparent when significant differences are found to be hiding in the aggregated percentages of risk factors for men and women. Higher levels of male premature mortality could also contribute to lower prevalence of risk factors among male survivors at older ages, but additional causes of difference in risk factors between men and women should be explored.
The analysis shows that prevalence of both behavioural and biological risk factors can vary in subgroups of men and women, and these subgroups are not equal in their relation to the risk factors. Identifying groups most at risk necessarily requires disaggregation of data and a gender analysis that links sex with age and other relevant sociodemographic variables. The additional analysis by education and income levels further showcases the differences across behavioural and biological risk factors not only between, but also among, men and women. The prevalence of behavioural risk factors for men and women varies by education level and by risk factor. With biological risk factors, differences show significantly higher prevalence among medium- and low-education women. Observed variation by income is smaller than by education. Men in low-income households appear to engage slightly more in behavioural risk factors such as tobacco and alcohol use than men from high-income households, although the differences are not statistically significant. No difference is observed for women.
Important differences are also seen in accessing services. A significantly higher percentage of men are not being measured for biological risk factors, while a higher percentage of women are being given lifestyle
GENDER AND NONCOMMUNICABLE DISEASES IN ARMENIA
23
advice on most behavioural risk factors. Despite accessing services more, the prevalence of biological risk factors as measured during the STEPS survey is still higher for women than men, or is not significantly different. This may in part be due to differences in accessing services among men and women as observed through disaggregation by age, education level and income level.
Higher percentages of men and women in the older age groups have been measured for biological risk factors, but trends in accessing services over the life-course are different for men and women. While the percentage of women measured for risk factors increases with each age group, the percentage of men measured does not increase until the 45–59 group. In some cases, the age group with the highest percentage measured for men (60–69) is only as high as the age group with the lowest percentage for women (18–29).
Both men and women with lower education levels are being measured for risk factors less than those with high education levels, and education levels vary more for men than women. High education level tends to be associated with higher rates of measurement for women, while both medium and high education levels tend to be associated for men. Men and women at low-income level are being measured less for risk factors than the those at high-income level, with the difference more pronounced for blood glucose and cholesterol. Low-income women are being measured at virtually the same rate as high-income men, again demonstrating that efforts to increase access should focus just as much on low-income women as men.
Improving access to services for women and men may therefore require that additional attention is paid to the following groups: men in the younger age groups; men with low education levels; women with low and medium education levels; and men and (especially) women with low income levels.
Higher percentages of lifestyle advice given to women could be influenced by numerous factors, including higher frequency of interaction of women with health-care services, higher proportion of women with biological risk factors (especially in the older age groups), and cultural and gender norms. There is a need to identify gender-specific norms and barriers to access and exposure to risk. Barriers are both gender- and disease-specific, with men and women experiencing them differently depending on the risk factor and sociodemographic characteristics (17). These barriers can be identified and explored through studies that engage specific sociodemographic groups through quantitative and qualitative approaches.
Such approaches could also explore possible influences, such as the presence of implicit bias in provider counselling, the sex of the health-care professional and social norms regarding social interactions between men and women. Gender-sensitive and culturally appropriate responses would then facilitate behavioural change, access and use of services. An analysis of the impact of gender inequalities requires further quantitative and qualitative information which cannot be retrieved from the STEPS data.
Findings presented in this report highlight the importance of an in-depth gender analysis of existing sex-disaggregated data together with other variables in identifying NCD risk-factor differences not only between men and women, but also among men and among women. The analysis will further reveal specific needs and opportunities in prevention and management of NCDs among different population groups that can be addressed through tailored interventions.
CONCLUSIONS
Accompanying this country profile is a synthesis report with key findings and commonalities across the initial six country profiles. The gender analysis is being extended to other available surveys (including the global adult and youth tobacco surveys, the Health Behaviour in School-aged Children study and the WHO European Childhood Obesity Surveillance Initiative) to obtain more compressive insights. Studies that specifically examine gender and social norms and gender inequality in these contexts can be used to complement these surveys by identifying driving and constraining factors for exposure to risk causing differences between and among men and women. In addressing the areas identified in this report, cost-effective interventions like best-buy and other interventions recommended by WHO (18) should be prioritized and tailored to the country-specific context to ensure uptake and efficiency. This would greatly contribute to the achievement of universal health coverage and the health-related SDGs.
GENDER AND NONCOMMUNICABLE DISEASES IN ARMENIA
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ANNEX 1.
SUPPLEMENTARY TABLES
Current tobacco use 51.5 (47.4–55.6) 1.8 (1.1–2.5)
Alcohol consumption Currently drink 46.1 (40.2–52.0) 21.5 (18.6–24.3)
Heavy episodic drinking 11.1 (8.1–14.0) 0.1 (0.0–0.3)
Unhealthy diet < 5 fruit or vegetables per day 78.4 (74.3–82.4) 73.5 (70.4–76.6) Always or often add salt 40.3 (36.1–44.4) 30.1 (27.1–33.1) Always or often eat processed foods 34.3 (30.0–38.7) 27.8 (24.8–30.7)
Insufficient physical activity 22.0 (18.0–26.1) 20.4 (17.3–23.5)
Biological
Overweight (BMI ≥ 25) 45.4 (40.6–50.2) 50.1 (46.7–53.5)
Obesity (BMI ≥ 30) 14.0 (10.9–17.0) 25.0 (22.4–27.7)
Raised blood pressure (BP) Raised BP (or on medication for raised BP) 39.3 (34.3–44.2) 36.3 (32.9–39.7) Raised BP (NOT on medication) 33.9 (28.8–38.9) 27.2 (24.0–30.4)
Raised blood glucose (or on medication) 6.5 (3.9–9.2) 4.6 (3.4–5.8)
Raised cholesterol (or on medication) 22.6 (17.9–27.3) 24.8 (22.0–27.6)
CI: confidence interval.
Table A1.2. Prevalence of three or more risk factors
Age group Men
% (CI 95%) Women
% (CI 95%)
18–29 26.6 (19.3–34.0) 5.0 (2.1–7.9)
30–44 42.7 (32.9–52.5) 23.6 (18.9–28.4)
45–59 62.1 (53.1–71.1) 46.2 (40.7–51.8)
60–69 55.7 (45.1–66.3) 66.3 (59.4–73.2)
CI: confidence interval.
Table A1.3. Total mortality per 1000
Age group Men Women
18–29 1.95 0.61
30–44 3.72 1.48
45–59 19.73 7.15
60–69 53.51 22.95
Table A1.4. Prevalence of behavioural risk factors by age group
Risk factor Aged 18–29
% (CI 95%) Aged 30–44
% (CI 95%) Aged 45–59
% (CI 95%) Aged 60–69
% (CI 95%) Current
tobacco users Men 45.0 (37.7–52.2) 56.1 (48.2–64.0) 54.8 (47.7–61.8) 50.8 (41.1–60.5) Women 0.5 (0.0–1.2) 1.7 (0.6–2.9) 2.8 (1.4–4.3) 3.5 (0.6–6.4) Alcohol Men 35.3 (26.5–44.0) 48.5 (39.0–57.9) 53.3 (45.3–61.4) 56.5 (46.6–66.4)
Women 25.7 (19.9–31.5) 20.9 (16.8–25.1) 19.5 (15.6–23.5) 13.7 (9.0–18.4) Alcohol
(heavy episodic) Men 7.5 (3.4–11.7) 17.9 (11.4–24.4) 9.1 (5.1–13.0) 7.2 (2.2–12.2) Women 0.1 (0.0–0.4) 0.4 (0.0–0.9) 0.0 (0.0–0.0) 0.0 (0.0–0.0)
