GENDER AND NONCOMMUNICABLE DISEASES IN KYRGYZSTAN

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GENDER AND NONCOMMUNICABLE

DISEASES IN KYRGYZSTAN

Analysis of STEPS data

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GENDER AND NONCOMMUNICABLE

DISEASES IN KYRGYZSTAN

Analysis of STEPS data

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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 KYRGYZSTAN

WHO/EURO:2020-1668-41419-56461

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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 19 DIFFERENCES IN MEN AND WOMEN NOT MEASURED FOR RISK FACTORS 20

LIFESTYLE ADVICE GIVEN BY A HEALTH-CARE PROFESSIONAL 23

CONCLUSIONS 25

REFERENCES 29

ANNEX 1. SUPPLEMENTARY TABLES 31

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 Ainura Akmatova, Head of Department, Public Health Office, Ministry of Health of Kyrgyzstan. 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.

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v

This country profile for Kyrgyzstan 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 the WHO Regional Office for Europe’s gender and noncommunicable diseases (NCDs) initiative to improve the response to NCDs in the Region through a gender approach. It is the first gender analysis of NCD risk-factor data for adults in Kyrgyzstan 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 Kyrgyzstan.

• 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 significantly 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.

• Prevalence for men and women varies by risk factor and socioeconomic variable, with the variance being different for women and men. A high education level for men and women is not associated with lower prevalence of behavioural risk factors. Higher prevalence of biological risk factors is observed for medium- and low-education women, but this is not the case for men. Prevalence of behavioural risk factors tends to be higher among high- income men; for biological risk factors, prevalence varies for men and women by risk factor.

Differences by ethnicity are more prominent for men for behavioural risk factors and for women for biological risk factors.

EXECUTIVE SUMMARY

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women have been given lifestyle advice by a health-care professional on most behavioural risk factors.

• More men and women in rural areas have not been measured for risk factors. Though more urban women have been measured than urban and rural men, the percentage of rural women not measured is not significantly different from percentages of men in rural and urban areas not measured. Women and (especially) men in the low education level are being measured for risk factors less than those in the high education level. Both men and women in the low income level have higher percentages of not having been measured for risk factors. The difference between low- and high-income groups overall is greater for women than men. Men and women of Kyrgyz and Uzbek ethnicity are more likely not to be measured for risk factors.

• Improving access to services for women and men may therefore require that additional attention is paid to the following groups: men and (especially) women in rural areas, women in the low education level and men in the low and medium education levels, low-income men and (especially) women, and men and women of Kyrgyz and Uzbek ethnicity.

• 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.

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INTRODUCTION

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The WHO Regional Office for Europe launched a gender and noncommunicable diseases (NCDs) initiative in 2019 to improve the response to NCDs in the WHO European 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 WHO European 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 on data gathered through the WHO STEPwise Approach to Surveillance (STEPS) NCD risk-factor survey.

This country profile for Kyrgyzstan presents an analysis of sex-disaggregated data linked with other variables, such as geographic location, education, income and ethnicity, 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

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GENDER AND NONCOMMUNICABLE DISEASES IN KYRGYZSTAN

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The analysis follows the key elements on gender and NCDs 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.

The survey in Kyrgyzstan was carried out from October 2013 to December 2013. A cluster sample design was used to produce nationally representative data for the age range of 24–64 years. The overall response rate was 100%, with 2623 adults participating in the survey. The data were weighted for complex survey design, non-response rate and population distribution by age and sex.

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 health services access.

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).

INTRODUCTION

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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 they are the greatest burden of disease in Kyrgyzstan. NCDs are estimated to account for 83% of all deaths in Kyrgyzstan (9), with cardiovascular diseases accounting for approximately 53% of all deaths in the country.

Though improvements have been made, further action is needed to address the expected increase in the overall burden of NCDs (10). As of 2013, it was estimated that 23% of the adult population had raised blood pressure, 26% smoked tobacco, 13% were physically inactive, 15% were obese, 9% had diabetes and 6%

used alcohol harmfully (9).

Kyrgyzstan has made specialized care and treatment for cardiovascular diseases a priority in recent years in an effort to address this disease burden (10). The prevalence of risk factors that account for NCDs nevertheless are different between and among men and women, and important differences exist 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

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DIFFERENCES IN BEHAVIOURAL

AND BIOLOGICAL RISK FACTORS

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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, and, for biological risk factors, 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 the prevalence among men is significantly higher than for women in nearly all the behavioural risk factors (current tobacco use, alcohol and diet), the same trend is not found for the biological risk factors.

Prevalence is significantly higher for women in overweight, obesity and raised cholesterol, and there is no significant difference between men and women in raised blood pressure and raised blood glucose.

BMI: body mass index. * Statistically significant difference. Source: National Centre of Cardiology and Internal Medicine, Kyrgyz State Medical Institute of Retraining and Professional Development, Ministry of Health, unpublished data, 2013.

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)*

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)*

Behavioural risk factors

Biological risk factors

Men Women

Fig. 3. Prevalence of risk factors across countries with differences between men and women (%)

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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 (39.5%) have three or more risk factors compared to women (30.3%). There is no significant difference between the percentages of men (5.2%) and women (6.5%) who 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. Significantly higher percentages of both men and women in each age group have three or more risk factors than the preceding age group through ages 45–54, with prevalence for men in these age groups significantly higher than for women.

While the percentage of men starts higher in the younger age groups, the increase in percentage is more drastic, causing the difference in percentage between men and women to lessen with each ascending age group. While the percentage of men more than doubles from the 24–34 age group to the 55–64 group, from 23.0% to 54.7%, the percentage of women with three or more risk factors is more than four times greater between comparable age groups, from 12.5% to 53.6% (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 (11): further analysis therefore is warranted to examine differences in these risk factors between men and women as well as among men and women.

DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS

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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 the older age groups (Fig. 5 and Annex 1, Table A1.3) (12).

0 10 20 30 40 50 60 70 80

25–34 35–44 45–54 55–64

Men Women

Fig. 4. Prevalence with three or more risk factors by age group (%)

0 10 20 30 40 50 60 70 80

25–34 35–44 45–54 55–64

Men Women

Fig. 5. Total mortality per 1000

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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 further reveals the importance of a 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).

For men, prevalence is highest with most risk factors in the 45–54 age group, but this is not the case for women.

The story for biological risk factors and age is quite different. The percentages of men and women with biological risk factors are higher with each advancing age group (Fig. 7 and Annex 1, Table A1.5). More important is that the prevalence of some biological risk factors for men starts higher in the youngest age group, but for women is higher across biological risk factors in the 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 both men and women increases with each age group, for women the increase from the youngest age group of 25–34 (42.7%) to the next age group of 35–44 (65.9%) is nearly as much as the increase for men from the youngest age group of 25–34 (35.2%) to the oldest of 55–64 (66.0%). Prevalence of raised blood pressure for 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 25–34 35–44 45–54 55–64

Fig. 6. Prevalence of behavioural risk factors by age group (%)

More men than women engage in behavioural risk factors across the life-course DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS

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starts lower in the youngest age group (18.4%) than is the case for men (26.1%) but ends higher in the oldest age group (75.4%) than for men (71.9%).

Differences between men and women are apparent across the life-course, but disaggregating data reveals additional differences among men and among women. Disaggregation by age group shows specific groups of men and women who are more at risk and differences by sex. Other social and demographic categorizations, such as geographic location, education level, income and ethnicity, further help identify differences between men and women and differences within these groups.

GEOGRAPHIC LOCATION – URBAN AND RURAL

The geographic location of the population can be used to further examine the differences in risk factors not only between, but also among, men and women. Data on geographic location were collected in the STEPS survey and have been categorized into urban and rural for the purposes of analysis. While some differences between men and women in urban and rural areas are observed, these differences are not consistent across the risk factors (Fig. 8 and Annex 1, Table A1.6). For example, a significant difference in prevalence of tobacco use is found by geographic location for women (1.5% rural, 4.7% urban) but not for men (45.6% rural, 53.8% urban). A significant difference is found with alcohol consumption for men (39.4% in rural, 56.3% in urban) and women (15.3% rural, 21.9% urban), but with heavy episodic drinking, the significant difference is only with men (17.5% rural, 34.3% urban). The prevalence of adding salt is significantly higher for both men and women in rural areas (23.6% men, 18.3% women) than in urban (13.2% men, 11.1% women).

An analysis of biological risk factors by geographic location further shows that urban and rural areas are not associated with risk factors the same for men and women (Fig. 9 and Annex 1, Table A1.7). For women, however, there are significant differences by geographic location in raised blood pressure and raised

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 25–34 35–44 45–54 55–64

Fig. 7. Prevalence of biological risk factors by age group (%)

Prevalence of women with biological risk factors starts lower than men but ends higher

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cholesterol: while higher prevalence of raised blood pressure is found among rural women (46.5%) than urban (37.1%), higher prevalence of raised cholesterol is found among urban women (34.8%) rather than rural (27.0%).

No overall significant difference in raised blood pressure between men and women is seen, but there is a significant difference between women in urban and rural areas. As with disaggregation by age group and geographic location, important differences between men and women are hiding in the aggregated percentages of risk factors for men and women.

Current tobacco use

Alcohol

0 10 20 30 40 50 60 70 80 90 100

Men Women Rural Urban

Fig. 8. Prevalence of behavioural risk factors by geographic location (%)

The association of geographic location and behavioural risk factors is different for men and women

0 10 20 30 40 50 60 70 80 90 100

Fig. 9. Prevalence of biological risk factors by geographic location (%)

The highest percentages of biological risk factors are in the medium level of education for men, and the medium and low levels for women

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EDUCATION LEVEL

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. Kyrgyzstan has extremely high literacy rates (99.7% for men, 99.5% for women) and high enrolment in primary (90.4% for boys, 88.8% for girls) and secondary education (84.6% for males, 84.1% for females). A significant difference is visible only at tertiary level (36.0% for males, 46.7% for females) (13).

Data on education level, determined by the highest level of education completed, were collected in the STEPS survey using country-specific categories. These categories have been matched to the levels of the International Standard Classification of Education (ISCED) (14) then condensed to reflect the three levels of low, medium and high (Table 1 and 2).

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. 10 and Annex 1, Table A1.8). For example, current tobacco use in the low education level for men is lower than other levels, but alcohol consumption

STEPS survey categories ISCED levels

1 = no formal schooling ISCED 0 = early childhood education 2 = primary school completed ISCED 1 = primary education 3 = secondary school not fully

completed ISCED 2 = lower-secondary education

4 = secondary school completed ISCED 3 = upper-secondary education

5 = secondary technical 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 = candidate of medical sciences 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

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in the medium and low levels is lower than in the high level. Prevalence of eating fewer than five servings of fruit or vegetables per day among high-education women is the only level significantly lower than any level for men.

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 (Fig. 11 and Annex 1, Table A1.9).

Current tobacco use

Alcohol

0 10 20 30 40 50 60 70 80 90 100

Men Women Low Medium High

Fig. 10. 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

0 10 20 30 40 50 60 70 80 90 100

Fig. 11. Prevalence of biological risk factors by education level (%)

A high education level is linked with lower biological risk factors for women, but not always for men

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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 in these same risk factors follows a different pattern, with prevalence varying by education level across risk factors.

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, the prevalence of overweight and obesity for high-education women is lower and is comparable with prevalence among men, while low- and medium-education women are significantly higher. With raised blood pressure and raised blood glucose, prevalence is significantly lower among high-education women than the other levels. Though it varies, low-education men tend to be lower than other levels.

INCOME LEVEL

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 (monthly income greater than 6100 Kyrgyzstan som (KGS)) and low income (less than 6100 KGS) were created for this analysis.

The estimated average annual earned income per capita for women in Kyrgyzstan is approximately 47%

of what it is for men (the equivalent of Int$ 2200 for women and Int$ 4700 for men) (13). While 79.3% of men participate in the labour force, only 51.7% of women do. The percentages of men and women who are not currently employed but are seeking employment are not significantly different (6.55% for women, 5.71% for men), though a higher percentage of women (30.4%) than men (19.8%) are part-time workers, and women engage in unpaid work nearly five times as much as men (13).

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. 12 and Annex 1, Table A1.10).

Current tobacco use

Alcohol

0 10 20 30 40 50 60 70 80 90 100

Men Women Low High

Fig. 12. Prevalence of behavioural risk factors by income level (%)

Prevalence tends to be higher in the high- income groups across risk factors for men, with less pronounced differences for women

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While many differences in behavioural risk factors by income level are not significant, the overall trend for men is that prevalence in behaviours such as tobacco and alcohol use, eating processed foods and taking part in insufficient physical activity is higher among high-income groups. The differences for women are 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 the high-income level, with some exceptions (Fig. 13 and Annex 1, Table A1.11).

Prevalence tends to be higher in the high-income groups for both men and women, but there are some differences. Prevalence of raised blood pressure for low-income women (47.3%) is higher than among high- income women (39.1%), but prevalence for men is higher in the high-income (44.8%) than low-income group (40.7%). While raised blood pressure is higher for women in the low-income group, prevalence of raised cholesterol is higher for the high-income (33.5%) than low-income group (25.2%).

ETHNICITY

An analysis by ethnicity may provide another possible area of difference, as ethnicity can be a social influence on health behaviours and gender roles may vary across ethnic groups. Data on ethnicity were collected in the STEPS survey, and the ethnic groups with sufficiently high numbers of participants (Kyrgyz, Russian and Uzbek) have been used for analysis (Fig. 14 and Annex 1, Table A1.12).

Some significant differences in behavioural risk factors among men and women by ethnicity were observed.

Ethnic Russian men and women tend to have a higher prevalence of risk factors than other ethnicities in Kyrgyzstan, and significant differences between men and women in each ethnic group are also prevalent.

0 10 20 30 40 50 60 70 80 90 100

Men Women Low High

Fig. 13. Prevalence of biological risk factors by income level (%)

Prevalence in the high-income groups tends to be higher for men and women DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS

(24)

Current tobacco use is significantly higher for ethnic Russian men and women than other ethnic groups, and a trend of higher prevalence for the other risk factors is observed.

While prevalence of alcohol consumption overall is significantly different for men and women, by ethnicity, not all men and women are significantly different. Prevalence with ethnic Russian women (30.1%) is as high as it is with ethnic Uzbek men (30.4%). Prevalence of eating fewer than five servings of fruit or vegetables per day for Kyrgyz women (72.7%) is not significantly lower than for ethnic Uzbek men (73.7%), and prevalence of eating processed food is not significantly higher for Kyrgyz men (23.8%) than for Kyrgyz women (22.5%).

Prevalence of biological risk factors varies among ethnic groups; the overall trend is that prevalence is higher for Kyrgyz and ethnic Uzbek men, but prevalence is higher for ethnic Russian women (Fig. 15 and Annex 1, Table A1.13).

While differences between men and women are observed among all three ethnic groups, the differences are more pronounced between ethnic Russian men and women. Most notable are the differences in overweight, obesity, raised blood pressure and raised cholesterol, with prevalence in most risk factors being significantly higher for women than for men and for women in other ethnic groups. Overall, women tend to be higher than men across ethnicities and risk factors.

Current tobacco use

Alcohol

0 10 20 30 40 50 60 70 80 90 100

Men Women Kyrgyz Russian Uzbek

Fig. 14. Prevalence of behavioural risk factors by ethnicity (%)

Behavioural risk factors are more prevalent among ethnic Russian men and women

(25)

17

0 10 20 30 40 50 60 70 80 90 100

Fig. 15. Prevalence of biological risk factors by ethnicity (%)

Prevalence is higher for Kyrgyz and ethnic Uzbek men and for ethnic Russian women DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS

(26)

(27)

DIFFERENCES IN THE WAY MEN

AND WOMEN ACCESS SERVICES

(28)

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 or blood glucose measured by a health- care professional. More men report never having had their cholesterol measured, but the difference is not statistically significant (Fig. 16 and Annex 1, Table A1.14).

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. 17 and Annex 1, Table A1.15).

0 20 40 60 80 100

Blood pressure

not measured Blood glucose

not measured Cholesterol

not measured Men Women

Fig. 16. 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 25–34 35–44 45–54 55–64

Fig. 17. Percentage not measured for risk factors by age group

(29)

21

It is not surprising that the percentages of both men and women who have not been measured for these risk factors decreases with each age group. The benefit of this analysis, 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 the trends in accessing services differ between men and women across the life-course.

For example, the lowest percentages of men and women not measured for raised blood pressure are found in the 55–64 age group, but the percentage of men not measured in this age group is not lower than the highest percentages (age groups 25–34 and 35–44) for women. A significant difference in women not measured for raised blood glucose, however, is only observed in the oldest age group (55–64).

GEOGRAPHIC LOCATION – URBAN AND RURAL

Further differences can be seen when those not being measured for risk factors are examined by geographic location. Higher percentages of both men and women in rural areas than those in urban areas have not been measured for risk factors (Fig. 18 and Annex 1, Table A1.16).

Additionally, the difference between urban and rural areas for men is greater with blood pressure than for women, while for women it is greater with blood glucose than for men. While higher percentages of men than women overall have not been measured for risk factors, by geographic location the percentages of rural women and urban men who have not been measured are not significantly different. For example, the percentage of women in rural areas not measured for blood glucose (74.3%) is not significantly different than it is for men not measured in urban areas (71.5%).

EDUCATION LEVEL

Men and women with different education levels have not been measured for risk factors to the same extent. While both men and women in the low education level have higher percentages of having not been measured than the other levels, the difference is more pronounced for men (Fig. 19 and Annex 1, Table A1.17).

0 10 20 30 40 50 60 70 80 90 100

Fig. 18. Percentage not measured for risk factors by geographic location

Men and women in rural areas are measured less for risk factors than those in urban settings

DIFFERENCES IN THE WAY MEN AND WOMEN ACCESS SERVICES

(30)

The overall trend is that a higher percentage of men and women in the low education level have not been measured for risk factors, and the difference is greater for men. As with geographic location, disaggregation by education level reveals that it is a subgroup, in this case men in the low education level, that is driving the overall difference observed between men and women in accessing services.

INCOME LEVEL

Just as education level can present barriers in accessing services for men and women, income level may also play a role due to its association with accessing resources. Overall, higher percentages of men and women in the low income level have not been measured for risk factors (Fig. 20 and Annex 1, Table A1.18).

An analysis by income level reveals the trend that low-income men and women have a higher percentage of not having been measured for risk factors. The difference between low- and high-income groups overall is greater for women than for men. Men and women are not homogenous groups, and the percentage of low-income women who have not been measured is not significantly lower than the percentage of high- income men who have not been measured.

0 10 20 30 40 50 60 70 80 90 100

Fig. 19. Percentage not measured for risk factors by education level

Men and women in the low education level are measured for risk factors least

0 10 20 30 40 50 60 70 80 90 100

Men Women Low High

Fig. 20. Percentage not measured for risk factors by income level

Fewer low-income men and women are measured for risk factors

(31)

23 GENDER AND NONCOMMUNICABLE DISEASES IN ARMENIA

ETHNICITY

Ethnicity allows for additional examinations of subgroups among men and women accessing services (Fig. 21 and Annex 1, Table A1.19).

While a higher percentage of ethnic Russian men and women are engaging in behavioural risk factors, a higher percentage of them are also being measured for risk factors compared to other ethnic groups.

Significantly higher percentages of Kyrgyz and ethnic Uzbek men and women have not been measured for risk factors.

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 3) to examine more differences between sexes.

Of the five topics in lifestyle advice, two (reduce salt and eat five servings of fruit or vegetables) are reportedly significantly higher for women than men, and one (avoiding tobacco use) is significantly higher

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 3. Lifestyle advice topics and prevalence of related risk factors

0 10 20 30 40 50 60 70 80 90 100

Fig. 21. Percentage not measured for risk factors by ethnicity

Fewer Kyrgyz and ethnic Uzbek men and women are measured for risk factors

DIFFERENCES IN THE WAY MEN AND WOMEN ACCESS SERVICES

(32)

for men than women. On avoiding tobacco use, a significantly higher percentage of men (44.5%) than women (27.2%) report being counselled, but that percentage is similar to prevalence for men of current tobacco use (48.2%); women, however, report being counselled at virtually 10 times the prevalence for women with that risk factor (2.7%) (Fig. 22 and Annex 1, Table A1.20). This may be due to primary health- care protocols addressing women’s health that require the provider to discuss tobacco use, or it may be due to women accessing services more than men. Social stigma surrounding women using tobacco may also have affected responses in the STEPS survey.

The percentages of those receiving lifestyle advice are in some cases much higher than the prevalence of the related risk factor, while in other cases they are much lower. 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. 22. Percentage of lifestyle advice given for related risk factors

A higher percentage of women than men are given lifestyle advice on most risk factors

(33)

CONCLUSIONS

(34)

This country profile presents the first gender analysis of NCD risk-factor data for adults in Kyrgyzstan.

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 Noncommunicable Diseases (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 Kyrgyzstan.

Significantly higher percentages of men than women engage in most of the behavioural risk factors in most age groups, and significantly higher percentages of women than men are found with most of the biological risk factors in the older age groups. 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, higher prevalence in biological risk factors is observed among women in the older age groups than among men, while there is generally lower prevalence in the younger age groups among women than among men.

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 geographic location, education, income and ethnicity further showcases the differences across behavioural and biological risk factors not only between, but also among, men and women.

The association between sociodemographic variables and risk factors is different for men and women.

Prevalence of alcohol consumption is higher for men and women in urban areas, while prevalence of adding salt is higher in rural areas. Prevalence of biological risk factors among men does not vary by geographic location, but prevalence of raised blood pressure for women is higher in rural areas and prevalence of raised cholesterol is higher in urban areas. A high education level for men and women does not equate

(35)

27 CONCLUSIONS

to lower prevalence in behavioural risk factors, as it varies from risk factor to risk factor. Prevalence of biological risk factors is higher among medium- and low-education women, but this is not the case for men. More high-income than low-income men engage in behavioural risk factors. Prevalence of raised blood pressure is higher for low-income women, while prevalence of raised cholesterol is higher for high- income women. Prevalence of behavioural risk factors is higher for ethnic Russian men and women, and more Kyrgyz and ethnic Uzbek men and ethnic Russian women are exposed to biological risk factors.

Important differences are also observed in accessing services. A significantly higher percentage of men are not being measured for biological risk factors. Women have lower behavioural risk factors than men, but higher percentages of women than men are being given lifestyle advice on most behavioural risk factors.

The 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, the higher proportion of women with biological risk factors, especially in the older age groups, and cultural and gender norms.

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, geographic location, education, income and ethnicity.

Though higher percentages of men and women in the older age groups have been measured for biological risk factors, the trends in accessing services over the life-course differ between men and women. The oldest age group and lowest in percentage of blood pressure not measured for men is not lower than the youngest age group and highest percentage not measured for women. The difference in blood glucose not measured only becomes significant in the oldest age group because the percentage of women not measured decreases dramatically.

While fewer men and women in rural areas than in urban have been measured for risk factors, women in rural areas are not being measured at virtually the same rate as men in rural and urban areas. Both men and women in the low education level are being measured for risk factors less than those in the high education level. There is more variance between education levels for men than for women, and men in the low education level are driving the overall higher percentage of not having been measured compared to women. Fewer low-income men and women have been measured for risk factors than those with high incomes, and the difference overall is greater for women than men. The percentages of low-income women not measured are not lower than high-income men. Also, higher percentages of Kyrgyz and ethnic Uzbek men and women have not been measured; more ethnic Russian men and women have been measured, and they also engage in more behavioural risk factors.

Improving access to services for women and men may therefore require that additional attention is paid to the following groups: men (especially in the older groups), rural populations (especially women), women in the low education level and men in the low and medium education levels, low-income men and (especially) women, and Kyrgyz and Uzbek men and women.

(36)

There is a need to identify gender-specific norms and barriers to access to health services and lifestyle change. Barriers are both gender- and disease-specific, with men and women experiencing them differently depending on the risk factor and sociodemographic characteristics (15). 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- and culturally-appropriate responses would then facilitate behavioural change and access to, and use of, services. An analysis of the impact of gender inequalities requires further quantitative and qualitative information that 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 then be addressed through tailored interventions.

Accompanying this country profile is a synthesis report with key findings and commonalities across the initial 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 comprehensive insights. Studies that specifically examine gender and social norms in these contexts can be used to complement these surveys by identifying driving and constraining factors for behaviours 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 (16) 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.

(37)

REFERENCES

¹

1 All weblinks accessed 28 July 2020.

GENDER AND NONCOMMUNICABLE DISEASES IN KYRGYZSTAN

GENDER AND NONCOMMUNICABLE

DISEASES IN KYRGYZSTAN

Analysis of STEPS data

GENDER AND NONCOMMUNICABLE

DISEASES IN KYRGYZSTAN

Analysis of STEPS data

CONTENTS

EXECUTIVE SUMMARY

INTRODUCTION

NCDs constitute the main burden of disease for both women and men, but there are important differences

ST EP S

DIFFERENCES IN BEHAVIOURAL

AND BIOLOGICAL RISK FACTORS

Significant differences between men and women

Prevalence of three or more risk factors

Mortality rates among men and women

Differences in specific risk factors among men and women between age groups

DIFFERENCES IN THE WAY MEN

AND WOMEN ACCESS SERVICES

Differences in men and women not measured for risk factors

Lifestyle advice given by a health-care professional

CONCLUSIONS

REFERENCES