DHS WORKING PAPERS

2005 No. 25

Vinod Mishra

Fred Arnold

Gulnara Semenov

Rathavuth Hong

Altrena Mukuria

Epidemiology of Obesity and Hypertension

in Uzbekistan

August 2005

This document was produced for review by the United States Agency for 

International Development. 

DEMOGRAPHIC

AND

HEALTH

RESEARCH
The DHS Working Papers series is an unreviewed and unedited prepublication series of papers 

reporting on research in progress based on Demographic and Health Surveys (DHS) data. 

Funding for this research was provided by the United States Agency for International 

Development (USAID) through the MEASURE DHS project (# GPO-C-00-03-00002-00). The 

views expressed are those of the authors and do not necessarily reflect the views of the United 

States Agency for International Development, the United States Government, or the organizations 

with which the authors are affiliated. 

MEASURE DHS assists countries worldwide in the collection and use of data 

to monitor and evaluate population, health, and nutrition programs. Additional 

information about the MEASURE DHS project can be obtained by contacting 

ORC Macro, Demographic and Health Research Division, 11785 Beltsville 

Drive, Suite 300, Calverton, MD 20705 (telephone: 301-572-0200; fax: 301-

572-0999; e-mail: reports@orcmacro.com; internet: www.measuredhs.com). 
Epidemiology of Obesity and Hypertension in Uzbekistan 

Vinod Mishra, Fred Arnold, Gulnara Semenov, Rathavuth Hong, Altrena Mukuria 

August 2005 

Corresponding author: Vinod Mishra, Demographic and Health Research Division, ORC Macro, 

11785 Beltsville Drive, Suite 300, Calverton, MD 20705. Phone: (301) 572-0220, Fax: (301) 

572-0999, Email: vinod.mishra@orcmacro.com 

ABSTRACT 

Objective: This study examines the prevalence of obesity and hypertension and associated 

behavioral risk factors in adult men and women in Uzbekistan. The study also estimates the 

effects of overweight and obesity on the risk of hypertension. 

Method: The analysis used data from the 2002 Uzbekistan Health Examination Survey (UHES), 

which included a nationally representative sample of 2,333 men age 15-59 and 5,463 women age 

15-49. The survey included questions on physical activity, dietary habits, tobacco smoking, 

alcohol consumption, and other risk factors, as well as measurements of height, weight, and blood 

pressure for all survey respondents. The analysis was conducted using binary and multinomial 

logistic regression methods, separately for men and women. 

Results: Thirty-one percent of men age 15-59 and 28% of women age 15-49 in Uzbekistan are 

overweight or obese. Overweight men and women were more than twice as likely and obese men 

and women were more than six times as likely to suffer from hypertension as men and women 

with a normal body mass index (BMI). With various risk factors and background factors 

statistically controlled, obese men and women remained about three times as likely to suffer from 

hypertension as men and women with a normal BMI (OR=3.01; 95% CI: 1.67-5.44 for men and 

OR=2.82; 95% CI: 2.05-3.86 for women). The adjusted effects of overweight on hypertension 

were also smaller than the unadjusted effects, but remained positive and significant (OR=1.35 for 

men and OR=1.54 for women). For men, the risk of hypertension was strongly positively 

associated with BMI only at BMI levels above 25, but for women a positive relationship was 

observed at all BMI levels. The study found no significant association between physical activity 

level and the risk of obesity or hypertension. Eating animal source protein and tobacco smoking 

in the past were positively associated with obesity, but there were no consistent associations with 

other dietary indicators or alcohol use. 

Conclusion: The study found a strong positive association between obesity and hypertension in 

adult men and women in Uzbekistan. The shape of the relationship between BMI and 

hypertension is different for women than for men. A lack of association with physical activity 

level and generally weak, inconsistent associations with diet, current smoking, and alcohol use 

may be partly because some men and women may have altered their behavior after becoming 

obese or after being diagnosed with hypertension. Prospective cohort studies are needed to better 

understand the relationships between physical activity, diet, smoking, and risks of obesity and 

hypertension. 

KEY WORDS: overweight, obesity, BMI, nutrition, blood pressure, hypertension, Uzbekistan 

iii
ACKNOWLEDGEMENTS 

The authors thank Shane Khan for research assistance. An earlier version of this paper was 

presented at the 25th IUSSP International Population Conference in Tours, France during July 18-

23, 2005. 

HUMAN SUBJECTS INFORMED CONSENT 

Analysis presented in this paper is based on an analysis of existing survey data with all identifier 

information removed. Informed consent was obtained from all respondents in the survey before 

asking questions and separately before obtaining measurements of height and weight and blood 

pressure. 

iv
INTRODUCTION 

Problems of overweight and obesity are caused by chronic imbalance between energy intake and 

actual energy needs of the body. Declining physical activity and increasing consumption of foods 

rich in saturated fat and sugar are primary reasons for a growing obesity epidemic worldwide 

(WHO 2003). Once considered a problem related to affluence, obesity is now fast growing in 

many developing countries (Monteiro et al. 2004; WHO 2003) and the burden of obesity within 

countries is shifting towards groups with lower socioeconomic status (Monteiro et al. 2004). 

A recent analysis of anthropometric measurements for women age 20-49 in 36 developing 

countries observed that the proportion overweight exceeded the proportion underweight in a 

majority of the countries in both urban and rural areas. In this study, the median ratio of 

overweight to underweight was 5.8 in urban areas and 2.1 in rural areas (Mendez et al. 2005). 

These results are contrary to the general belief that in developing countries overweight is less 

prevalent than underweight and that it is primarily concentrated in urban, higher socioeconomic 

status households. 

A number of factors have been identified as being related to obesity and many of these factors are 

also associated with adverse health outcomes. Consumption of high energy and high fat foods has 

been linked to the risk of obesity (e.g., Hu et al. 2002; Lin et al. 2004). Sedentary behavior (e.g., 

television viewing and use of motorized transportation) and physical inactivity have been 

associated with obesity and markers of cardiovascular disease risk (Jakes et al. 2003; Hu et al. 

2004; Hu et al. 2002; Sobngwi et al. 2002; Gopinath et al. 1994; Lin et al. 2004; Nanchahal et al. 

2005; Vioque et al. 2000; Bell et al. 2002). Tobacco smoking has been positively associated with 

the risk of hypertension (e.g., Niskanen et al. 2004; Okubo et al. 2004), but some studies have 

reported a negative association between smoking and obesity (e.g., Hu et al. 2002). Alcohol 

consumption has been found to be negatively associated with obesity and the risk of metabolic 

disorders (e.g., Djousse et al. 2004). With respect to background characteristics, being married 

has been positively associated with obesity (Jeffery and Rick 2002; Hu et al. 2002) and both 

educational attainment and economic status have been linked with obesity and the risk of 

coronary heart disease (Nanchahal et al. 2005; Monteiro et al. 2001). 

A number of cross-sectional and prospective studies have reported strong associations between 

obesity and risks of hypertension, diabetes, and other cardiovascular diseases (e.g., Kotsis et al. 

2005; Sanchez-Castillo et al. 2005; Liu et al. 2004; Hu et al. 2004; Niskanen et al. 2004; 

Szczygielska et al. 2003; Lee et al. 2004; Venkatramana and Reddy 2002; Misra et al. 2001; 

Gopinath et al. 1994; Nanchahal et al. 2005; Adair 2004; Lerman-Garber et al. 1999). 

There has been limited previous research on the epidemiology and risk factors of obesity and 

associated markers for cardiovascular disease risk in Central Asian countries. From the few 

available studies, it is clear that the problems of obesity are common among adults in these 

countries (Popkin et al. 1997), and a recent study warns of an inevitable epidemic of hypertension 

in Central Asia (Young et al. 2005). An earlier large population-based study in Kazakhstan noted 

a strong association between obesity, hypertension, and coronary heart disease (Kadyrova and 

Salkhanov 1990). Recent studies in Syrdarya Province and the Ferghana Valley in Uzbekistan 

have recorded high prevalence of central obesity and a strong association of obesity with glucose 

intolerance in adults (King et al. 2002; King et al. 1998). 

In summary, the growing obesity pandemic in the developing world is associated with a host of 

other rapidly growing serious health problems, such as hypertension, diabetes, and heart disease. 

In many developing countries, cardiovascular diseases are already a major cause of ill health and 

5
death. In Uzbekistan, for example, cardiovascular diseases account for about two-thirds of all 

deaths (WHO 2005). While the relationships between obesity and hypertension and other 

cardiovascular diseases are well recognized, there is limited understanding of the scope of these 

problems, the relationships among different conditions, and the underlying behavioral risk factors 

in such developing-country settings. This is partly due to a preoccupation with widespread and 

persistent problems of undernutrition. Another limiting factor has been a lack of reliable data on 

the prevalence and distribution of obesity and associated chronic diseases in these populations. 

A recent health examination survey in Uzbekistan measured levels of obesity and hypertension in 

a nationally-representative probability sample of adult men and women. The survey also collected 

information on health risk behaviors, including tobacco smoking, alcohol use, level of physical 

activity, and dietary habits, as well as sociodemographic characteristics. These data provide a 

unique opportunity to study the epidemiology of obesity and hypertension in different population 

groups in Uzbekistan and their associations with selected risk factors. These data also allow a 

close examination of the relationship between body weight and the risk of hypertension. 

6
DATA AND METHODS 

Data 

The analysis is based on the 2002 Uzbekistan Health Examination Survey (UHES). The survey 

collected information from 4,168 sample households in 219 sample enumeration areas (101 in 

urban areas and 118 in rural areas). The sampling design for the survey was developed by the 

State Department of Statistics of the Ministry of Macroeconomics and Statistics. A weighted, 

multistage, cluster sampling design was used. The sample was designed to represent five major 

regions of Uzbekistan—Tashkent City and the Western, Central, East-Central, and Eastern 

Regions (see footnotes to Table 1 for a list of oblasts included in these regions). All women age 

15-49 in the sample households were eligible for interview. All men age 15-59 in the selected 

households in Tashkent City were eligible respondents, but in the remaining four regions men age 

15-59 were eligible to be interviewed in only every third household. Individual questionnaires 

were completed for 98% of eligible women and 95% of eligible men. Overall, interviews were 

completed with 5,463 women age 15-49 and 2,333 men age 15-59. More details on the sample 

design are provided in the main survey report (AIC, Ministry of Health et al. 2004). 

The survey collected information on a wide range of adult health issues, including lifestyle 

factors such as physical activity, diet, smoking, and alcohol use, and other risk factors for 

cardiovascular disease. The survey also collected data on a number of key biomarkers, including 

measurements of height, weight, and blood pressure for all respondents, as well as measurements 

of lipids and diabetes for respondents in Tashkent City. The 2002 UHES provides data on these 

biomarkers and several social and behavioral risk factors representative of the general population, 

as opposed to clinic-based data. 

Measurements of obesity and hypertension 

All survey respondents were weighed using a solar-powered scale with an accuracy of ±100 

grams. Their height was measured using an adjustable wooden measuring board, specifically 

designed to provide accurate measurements (to the nearest 0.1 cm) in a developing-country field 

situation. The weight and height data were used to calculate the body mass index (BMI). 1

 BMI 

was used to define underweight (BMI < 18.5), normal (18.5 ≤ BMI < 25.0), overweight (25.0 ≤

BMI < 30.0), and obese (BMI ≥ 30) adults. 

Blood pressure measurements were taken by female and male interviewers who were nurses and 

doctors. Prior to the survey fieldwork, these interviewers were given refresher training in 

measurement procedures in nonclinical settings. Measurements were made using 

sphygmomanometers (Mercury safe, TRIMLINEm Mercurial Desk Sphygmomanometer) and 

stethoscopes according to the protocols of Westat Inc. (1993). Two measurements of systolic and 

diastolic blood pressure (measured in millimeters of mercury, mmHg) were taken at an interval of 

at least 10 minutes between measurements. Adults were classified as hypertensive if they were 

taking antihypertensive drugs, or if (according to the second blood pressure measurement) their 

systolic blood pressure was ≥ 130 mmHg or their diastolic blood pressure was ≥ 85 mmHg 

(Grundy et al. 2004; IDF 2005). The main survey report used 140 and 90 mmHg cutoffs for 

systolic and diastolic blood pressure to define hypertension (AIC, Ministry of Health et al. 2004). 

 

1

 The body mass index is defined as a woman’s weight in kilograms divided by the square of her height in 

meters (kg/m2

) 

7
Risk factors and confounders 

The risk factors of obesity and hypertension included in the study are: physical activity level 

(expressed as MET-minutes per week, where METs are computed by weighting each type of 

physical activity by its energy requirements; METs are multiples of the resting metabolic rate), 

eight indicators of diet (frequency of eating animal source protein, carbohydrates, fresh fruits and 

vegetables, dried fruits and vegetables, canned or pickled fruits and vegetables, and fried foods, 

and whether salt or fat are added to cooked food), tobacco smoking, and alcohol consumption in 

the last 12 months. The background characteristics of the respondents that are included as 

potential confounders are: age, marital status, education, work status (employment in the last 12 

months and occupation), difficulty in making ends meet (economic status), ethnicity, religion, 

residence, and geographic region. For definitions of these variables, see Table 1. 

Analysis 

Data are analyzed using both descriptive and multivariate logistic regression methods. 

All analysis is done separately for adult men (age 15-9) and women (age 15-49). Women who 

were pregnant at the time of the survey and women who had a live birth or a stillbirth during the 

two months preceding the survey were excluded from the analysis. Results are presented in the 

form of odds ratios (OR) with significance levels and 95% confidence intervals (95% CI). The 

logistic regression models were estimated using the STATA statistical software package (Stata 

Corporation 2003). In the survey, certain states and certain categories of respondents were 

oversampled and nonresponse rates varied from one geographical area to another. In all analysis 

in this study, weights are used to restore the representativeness of the sample (AIC, Ministry of 

Health et al. 2004). 

8
RESULTS 

In Uzbekistan, women (15-49) are much less likely than men (15-59) to be physically active, 

smoke tobacco, or consume alcohol (Table 1). Women consume animal protein, carbohydrates, 

fresh fruits and vegetables, fried foods, and add fat to cooked food more frequently than men. 

Women are slightly less likely to have higher education and considerably less likely to be 

employed than men. About two-thirds of men and women were married at the time of UHES. Six 

percent of women were separated, divorced, or widowed compared with less than 2% of men. 

Sixty percent men and women live in rural areas, more than 85% are Uzbek, and more than 95% 

are Muslim. 

Table 1 Sample distribution (%) of men age 15-59 and women age 15-49 by selected risk factors and background 

characteristics, Uzbekistan 2002 

Characteristic Men Women 

Risk Factors 

Physical activity level1

Low 29.5 44.3 

Medium 33.7 42.3 

High 36.8 13.4 

Diet 

Animal protein2 (days/week) 

<2 31.3 27.3 

2-3 50.4 49.8 

4+ 18.3 22.9 

Carbohydrate3

Not every day 52.1 43.0 

Every day 47.9 57.0 

Fresh fruits and vegetables4

(days/week) 

<3 23.1 21.4 

3-4 40.2 31.8 

5+ 36.7 46.8 

Dried fruits and vegetables5

(days/week) 

<1 27.2 30.1 

1-2 45.5 40.8 

3+ 27.3 29.1 

Canned or pickled fruits and vegetables6

Does not eat 59.8 60.8 

Eats <2 days/week 21.0 18.8 

Eats 2+ days/week 19.2 20.4 

Fried foods7 (days/week) 

<3 36.9 20.3 

3-5 38.6 29.4 

6+ 24.5 50.3 

Adds salt to cooked food 

No 86.6 87.5 

Yes 13.4 12.5 

Adds fat to cooked food 

No 94.1 82.4 

Yes 6.0 17.6 

Tobacco smoking8

Never 59.1 98.6 

Past only 16.9 0.4 

Current 24.1 1.0 

Continued...

9
Table 1—Continued

Characteristic Men Women 

Alcohol consumption in last 12 months9

No 33.6 74.8 

Yes-not a problem drinker 50.6 24.4 

Yes-problem drinker 15.7 0.8 

Background characteristics 

Age 

15-19 16.3 20.8 

20-24 16.6 17.5 

25-29 17.1 14.0 

30-34 12.6 13.7 

35-39 11.0 13.1 

40-44 9.7 12.0 

45-49 8.4 9.0 

50-54 6.0 na 

55-59 2.3 na 

Marital union 

Never married 29.7 27.6 

In union 68.6 66.2 

Separated/divorced/widowed 1.7 6.2 

Education 

Primary/middle 8.0 10.6 

Secondary 56.2 58.0 

Secondary special 20.1 20.7 

Higher 15.6 10.8 

Work status10

Not employed 34.8 54.6 

White collar 32.6 28.5 

Manual/agriculture 32.6 16.9 

Making ends meet11

Great difficulty 26.0 28.4 

Some difficulty 36.2 34.6 

Little or no difficulty 37.8 37.1 

Ethnicity 

Uzbek 86.2 85.2 

Other12 13.8 14.8 

Religion 

Muslim 96.8 95.7 

Other13 3.2 4.3 

Residence 

Rural 60.7 59.6 

Urban 39.3 40.4 

Continued...

10
Table 1—Continued

Characteristic Men Women 

Region14

Tashkent City 8.5 9.5 

Western 13.5 12.7 

Central 21.8 24.2 

East-Central 27.7 25.8 

Eastern 28.5 27.8 

Number of cases15 2,333 5,146 

1

Physical activity level is expressed as MET-minutes per week. METs are multiples of the resting metabolic rate. Using the International 

Physical Activity Questionnaire (IPAQ) guidelines (IPAQ 2004), a physical activity score is calculated for each person based on the 

information on total number of minutes per week spent walking (x3.3 METs), doing moderate physical activity (x4.0 METs), and 

vigorous physical activity (x8.0 METs). Persons with a physical activity score <6000 MET-minutes are defined as having a low level of 

physical activity; 6000-13999 as having a medium level of physical activity; and 14000+ as having a high level of physical activity. 2

Animal protein intake is measured by an average score, which is calculated by adding number of days in the last week eating foods 

from each of the following four categories and dividing by four: 1. cheese, yoghurt, kefir, ice cream, milk, or other milk products; 2. 

eggs; 3. red meats; 4. fish and poultry. 

3

Carbohydrate intake is measured by an average score, which is calculated by adding number of days in the last week eating foods from 

each of the following three categories and dividing by three: 1. roots and tubers such as white potatoes, turnips, radishes, or beet root; 2. 

bread, rice, pasta, cereal, cookies, biscuits or similar products made with wheat or white flour; 3. sugary foods, confectionery, pastry, 

cakes, chocolates, or sweets. 

4

Fresh fruit and vegetable intake is measured by an average score, which is calculated by adding number of days in the last week eating 

foods from each of the following three categories and dividing by three: 1. dark green leafy vegetables or condiments such as parsley, 

dill, spinach, rahon, cilantro, basil, mint, lettuce or cabbage; 2. other fresh vegetables including vegetables in stews, soups, and salads; 3. 

fresh fruits. 

5

Dried fruit and vegetable intake is measured by an average score, which is calculated by adding number of days in the last week eating 

foods from each of the following three categories and dividing by three: 1. beans, peas, or legumes; 2. nuts or seeds; 3. dried fruits. 6

Canned or pickled fruit and vegetable intake is measured by an average score, which is calculated by adding number of days in the last 

week eating foods from each of the following three categories and dividing by three: 1. foods prepared with tomato paste; 2. pickled or 

canned vegetables; 3. canned fruits. 

7

Number of days fried foods eaten in the last week. 

8

Tobacco smoking in past only includes persons who smoked fairly regularly in the past but do not currently smoke. 9

Based on the Rapid Alcohol Problems Screen (RAPS) guidelines (Cherpitel 1997), a person who consumed alcohol in the past 12 

months is defined as a problem drinker or alcohol dependent if he/she answered "yes" to any of the following questions: 1. Do you 

sometimes take a drink in the morning when you first get up? 2. During the past year, has a friend or family member ever told you about 

things you said or did while you were drinking that you could not remember? 3. During the past year, have you failed to do what was 

normally expected of you because of drinking? 4. During the past year, have you lost friends because of your drinking? A fifth screening 

question on feeling of guilt or remorse after drinking was not included due to problems of interpretation in the Uzbekistan context. 10White collar includes professional, technical, managerial, clerical, or sales and services; manual/agriculture includes skilled manual, 

unskilled manual, or agriculture. 

11Making ends meet denotes economic hardship for the household in which the person lives. Little or no difficulty category includes 

households mentioning a little difficulty, fairly easily, easily, or very easily in response to the question on ability to make ends meet. 12Other ethnic groups include Russian, Karakalpak, Tajik, and others. 13Other religions include Christian, no religion, and others. 14Western region includes the Autonomous Republic of Karakalpakstan and Khorezm Oblast; Central region includes Navoi, Bukhara, 

Kashkadarya, and Surkhandarya Oblasts; East-Central region includes Samarkhand, Jizzakh, Syrdarya, and Tashkent Oblasts; Eastern 

region includes Namangan, Ferghana, and Andizhan Oblasts. 15Actual number of cases for individual variables varies slightly depending on the number of missing cases. 

na = Not applicable 

Overall, 26% of men age 15-59 in Uzbekistan are overweight and 5% are obese; only 4% are 

underweight (not shown). Corresponding proportions for women age 15-49 are 21% overweight, 

7% obese, and 6% underweight (Table 2). Notably, women are somewhat less likely to be 

overweight but more likely to be obese than men. A comparison of anthropometric data for 

Uzbekistan from the 1996 Demographic and Health Survey and the 2002 Health Examination 

Survey shows that the proportion overweight or obese among women (15-49) increased from 

11
22% in 1996 to 28% in 2002. Seventeen percent of men age 15-59 and 12% of women age 15-49 

in the 2002 UHES suffered from hypertension. These levels of hypertension are higher from 

those reported in the main survey report (8% for both men and women) due to the differences in 

the definition of hypertension (mentioned earlier). 

Table 2 Prevalence of overweight, obesity, and hypertensiona by selected risk factors and background characteristics, by 

sex, Uzbekistan 2002 

 Men Women 

Characteristic 

Overweight Obese Hypertensive Overweight Obese Hypertensive 

Risk factors 

Physical activity level 

Low 29.1 5.6 16.3 20.3 6.9 12.1 

Medium 27.5 5.1 18.2 21.6 6.8 11.3 

High 23.2 5.2 16.1 18.7 8.2 14.7 

Diet 

Animal protein (days/week) 

<2 24.5 2.5 14.6 20.3 6.5 13.6 

2-3 25.7 5.1 17.3 20.8 6.5 11.3 

4+ 31.6 10.6 19.6 20.9 8.9 12.1 

Carbohydrate 

Not every day 28.9 4.0 15.9 19.7 6.3 13.1 

Every day 23.7 6.7 17.9 21.4 7.6 11.4 

Fresh fruits and vegetables (days/week) 

<3 27.7 3.0 16.5 19.4 5.9 13.9 

3-4 27.4 3.8 15.6 19.9 5.7 11.2 

5+ 24.5 8.4 18.5 21.8 8.5 11.9 

Dried fruits and vegetables (days/week) 

<1 23.7 4.4 19.4 21.2 8.2 11.3 

1-2 26.8 4.7 16.5 21.1 6.4 12.4 

3+ 28.4 7.3 15.0 19.6 6.9 12.6 

Canned or pickled fruits and vegetables 

Does not eat 26.6 5.4 17.6 20.6 7.5 12.4 

Eats <2 days/week 27.4 6.4 16.1 20.2 7.9 11.2 

Eats 2+ days/week 24.1 3.8 15.7 21.2 5.0 12.3 

Fried foods(days/week) 

<3 26.4 5.6 18.4 22.8 7.0 16.0 

3-5 30.9 5.7 15.7 19.7 7.8 13.0 

6+ 19.4 4.2 16.4 20.3 6.6 10.1 

Adds salt to cooked food 

No 25.7 5.3 16.3 20.5 6.4 11.6 

Yes 30.7 5.5 20.7 22.3 11.6 16.2 

Adds fat to cooked food 

No 26.6 5.1 16.7 20.6 6.7 11.6 

Yes 22.8 8.8 19.2 21.2 8.5 14.4 

Tobacco smoking 

Never 24.7 3.0 13.9 u u u 

Past only 29.7 10.2 24.3 u u u 

Current 28.3 7.4 19.0 u u u 

Alcohol consumption in last 12 months 

No 22.6 2.7 12.5 20.5 6.2 11.4 

Yes-not a problem drinker 28.8 6.0 18.3 

Yes-problem drinker 26.6 8.5 21.6 21.3b 9.5b 14.4b

Continued...

12
Table 2—Continued

 Men Women 

Characteristic 

Overweight Obese 

Hypertensive Overweight Obese 

Hypertensive 

Background characteristics 

Age 

15-19 6.3 0.4 4.4 7.5 0.3 3.0 

20-24 16.0 0.7 9.7 13.0 1.7 3.6 

25-29 22.2 2.0 11.0 18.1 3.5 5.8 

30-34 29.8 3.0 13.9 24.2 5.6 8.1 

35-39 36.3 8.1 14.9 29.1 9.4 16.9 

40-44 43.2 9.0 28.3 36.4 17.6 26.7 

45-49 44.6 14.3 37.0 31.2 23.0 39.0 

50-54 34.4 16.9 41.4 na na na 

55-59 50.7 17.5 40.9 na na na 

Marital union 

Never married 10.6 0.3 7.0 8.9 0.9 3.8 

In union 33.3 7.5 20.9 24.5 9.3 14.8 

Separated/divorced/ widowed 24.1 1.7 26.6 31.9 10.6 20.8 

Education 

Primary/middle 17.9 1.8 13.4 15.8 8.5 11.8 

Secondary 24.1 4.3 14.6 20.2 6.1 11.8 

Secondary special 25.3 6.7 18.0 21.7 7.9 11.2 

Higher 40.8 8.8 25.2 26.5 9.3 15.7 

Work status 

Not employed 20.7 1.9 14.7 17.9 5.7 10.5 

White collar 34.7 8.0 19.6 25.5 9.1 13.6 

Manual/agriculture 24.2 6.3 16.5 21.8 8.1 14.8 

Making ends meet 

Great difficulty 23.1 4.7 18.2 20.1 8.0 14.2 

Some difficulty 28.8 4.4 16.1 22.0 6.0 11.1 

Little or no difficulty 26.3 6.5 16.7 20.0 7.3 11.3 

Ethnicity 

Uzbek 26.7 5.5 15.8 21.1 7.2 12.1 

Other 24.2 4.3 23.3 18.5 6.2 12.3 

Religion 

Muslim 26.4 5.4 16.6 20.7 7.0 12.0 

Other 26.8 1.6 23.8 20.2 7.0 13.8 

Residence 

Rural 26.1 4.5 15.3 20.2 6.6 12.7 

Urban 26.8 6.6 19.3 21.4 7.8 11.2 

Region 

Tashkent City 29.5 5.9 26.2 24.7 9.6 6.3 

Western 19.0 7.3 27.3 17.9 9.7 17.0 

Central 29.5 6.1 16.6 20.7 8.1 15.3 

East-Central 31.1 6.6 15.6 21.3 7.9 13.4 

Eastern 22.1 2.3 10.6 20.0 3.3 7.9 

Total 26.4 5.3 16.9 20.7 7.0 12.1 

Number of cases 604 121 393 1,053 359 623 

Note: For variable definitions, see Table 1. 

a

Hypertension is defined as either having systolic blood pressure ≥ 130 mmHg, diastolic blood pressure ≥ 85 mmHg, or taking blood 

pressure medication. 

b

Category includes all alcohol consumers in the last 12 months. 

na = Not applicable 

u = Unknown (Not available because of the small number of female smokers in the sample).

13
Prevalence of overweight, obesity, and hypertension do not vary much by physical activity level, 

except that men with a high level of physical activity are less likely than other men to be 

overweight. Among the diet indicators, frequency of eating animal protein, carbohydrates, fresh 

fruits and vegetables, and adding fat to cooked food are positively associated with obesity in both 

men and women, but frequency of eating dried fruits and vegetables is positively associated with 

obesity only in men and adding salt to cooked food is positively associated with obesity only in 

women. Adding salt to cooked food and adding fat to cooked food are positively associated with 

hypertension in both men and women. The associations of other diet variables with obesity and 

hypertension are generally small and inconsistent. Tobacco smoking (especially in the past) and 

alcohol consumption are associated with higher levels of obesity and hypertension. 

As expected, there is a strong positive association between age and the prevalence of obesity and 

hypertension in both men and women. For both men and women, the proportion overweight or 

obese rises from less than 8% at age 15-19 to more than 50% at age 45-49. The prevalence of 

hypertension similarly rises from less than 5% at age 15-19 to about 40% at age 45-49. Education 

and marital status are also strongly associated with the prevalence of obesity and hypertension, 

but there are no consistent patterns for other background factors. Prevalence levels of obesity and 

hypertension are much lower in the Eastern region than in other regions of Uzbekistan. 

Effects of physical activity, diet, and other factors on risk of overweight and obesity 

Table 3 shows that physical activity level has no significant effect on the risk of being overweight 

or obese in both men and women. This is unexpected and may partly be because some overweight 

adults may increase their level of physical activity in an attempt to lose weight. 

The frequency of eating animal protein is significantly positively associated with the risk of 

obesity in both men and women. Independent of physical activity level and other factors, men 

eating animal protein four or more days per week, on average, are more than four times as likely 

to be obese as those eating animal protein less than two days per week (OR=4.21; 95% CI: 1.97-

8.99), but this effect is much smaller for women (OR=1.73; 95% CI: 1.12-2.68). The results for 

most other diet variables are inconsistent. For example, contrary to expectation, eating fresh fruits 

and vegetables five or more days per week is positively associated with obesity in both men 

(OR=1.76; p=0.166) and women (OR=1.65; p=0.022). Eating dried fruits and vegetables three or 

more days per week is significantly positively associated with obesity in men (OR=2.09; 

p=0.044), but significantly negatively associated with obesity in women (OR=0.65; p=0.035). 

Similarly, adding salt to cooked food is significantly negatively associated with obesity in men 

(OR=0.49; p=0.049), but significantly positively associated with obesity in women (OR=1.67; 

p=0.009). Reasons for these inconsistent findings are not clear. 

In men, tobacco smoking is positively associated with the risk of obesity, but this relationship is 

stronger for past smoking (OR=2.16; p=0.017) than for current smoking (OR=1.43; p=0.258) and 

it is statistically significant only for past smoking. It is possible that some men stopped smoking 

after discovering that they had a smoking-related health problem, say hypertension, which tends 

to be correlated with obesity (as we shall see later). The adjusted effect of alcohol consumption is 

small and not significant for both men and women. 

Among the background factors, age is strongly positively associated with overweight and obesity 

in both men and women, as expected. Men in union are much more likely to be obese than never 

married men (OR=9.28; 95% CI: 3.18-27.14). Women in union are also more likely to be obese 

than never married women (OR=1.54), but this effect is much smaller and not significant 

statistically. Overall, women in union are significantly more likely to be overweight or obese than 

14
never married women (OR=1.37; p=0.062). Interestingly, separated, divorced, or widowed 

women are significantly more likely to be overweight or obese than never married women 

(OR=1.71; p=0.016), but this relationship is not observed for men (OR=0.67; p=0.484). NonUzbek men and women are significantly less likely to be obese than Uzbek men and women 

(OR=0.44 for men and OR=0.50 for women). Urban residence is positively associated with 

obesity in men (OR=1.88; p=0.044), but not in women. By geographic region, men and women 

living in the Eastern region are much less likely to be overweight and obese than those living in 

Tashkent City (OR=0.53 and 0.34 for overweight and obesity in men, and OR=0.71 and 0.35 for 

overweight and obesity in women, respectively). Adjusted effects of education, work status, and 

economic status are generally small and not significant statistically. 

Table 3 Adjusted effects (odds ratios) of selected risk factors on the risk of overweight and obesity, by sex, Uzbekistan 2002

Men Women 

 

Characteristic 

Overweight Obese 

Overweight 

or obese 

Overweight Obese 

Overweight 

or obese 

Risk factors 

Physical activity level 

Low‡ 1.00 1.00 1.00 1.00 1.00 1.00 

Medium 1.03 1.11 1.03 0.97 0.90 0.94 

High 0.82 0.98 0.83 0.84 1.09 0.89 

Diet 

Animal protein (days/week) 

<2‡ 1.00 1.00 1.00 1.00 1.00 1.00 

2-3 1.14 2.30* 1.22 1.14 1.17 1.15 

4+ 1.56† 4.21*** 1.78** 1.20 1.73* 1.30*

Carbohydrate 

Not every day‡ 1.00 1.00 1.00 1.00 1.00 1.00 

Every day 0.75† 0.77 0.76† 1.11 0.93 1.06 

Fresh fruits and vegetables (days/week) 

<3‡ 1.00 1.00 1.00 1.00 1.00 1.00 

3-4 0.83 0.86 0.84 1.01 1.09 1.03 

5+ 0.64* 1.76 0.74 1.05 1.65* 1.16 

Dried fruits and vegetables (days/week) 

<1‡ 1.00 1.00 1.00 1.00 1.00 1.00 

1-2 1.26 1.28 1.28 0.97 0.77 0.93 

3+ 1.63* 2.09* 1.71** 0.85 0.66* 0.81†

Canned or pickled fruits and vegetables 

Does not eat‡ 1.00 1.00 1.00 1.00 1.00 1.00 

Eats <2 days/week 0.94 1.10 0.97 1.03 1.16 1.06 

Eats 2+ days/week 0.82 0.54 0.77 1.06 0.99 1.04 

Fried foods(days/week) 

<3‡ 1.00 1.00 1.00 1.00 1.00 1.00 

3-5 1.42* 0.95 1.34† 0.72* 1.02 0.79*

6+ 0.77 0.54 0.73 0.75* 1.15 0.83 

Adds salt to cooked food 

No‡ 1.00 1.00 1.00 1.00 1.00 1.00 

Yes 0.96 0.49* 0.88 1.22 1.67** 1.33*

Adds fat to cooked food 

No‡ 1.00 1.00 1.00 1.00 1.00 1.00 

Yes 0.67 1.02 0.75 0.96 0.97 0.97 

Tobacco smoking 

Never‡ 1.00 1.00 1.00 u u u 

Past only 0.88 2.16* 1.02 u u u 

Current 0.84 1.43 0.91 u u u 

Continued...

15
Table 3—Continued

Men Women 

Characteristic 

Overweight Obese 

Overweight 

or obese 

Overweight Obese 

Overweight 

or obese 

Alcohol consumption 

in last 12 months 

No‡ 1.00 1.00 1.00 1.00 1.00 1.00 

Yes-not a problem drinker 0.78 1.03 0.79 

Yes-problem drinker 0.70 1.31 0.77 0.93a 1.05a 0.97a

Background factors 

Age 

15-19‡ 1.00 1.00 1.00 1.00 1.00 1.00 

20-24 3.08** 0.35 2.72** 1.42 4.14* 1.55*

25-29 4.45*** 0.60 3.89*** 1.97** 7.98*** 2.24***

30-34 7.61*** 0.71 6.33*** 2.81*** 14.04*** 3.33***

35-39 11.01*** 2.64 10.28*** 3.82*** 27.96*** 4.89***

40-44 15.68*** 3.65 14.89*** 6.62*** 76.40*** 9.57***

45-49 14.80*** 5.29* 15.22*** 5.52*** 94.82*** 9.30***

50-54 10.12*** 7.26* 12.36*** na na na 

55-59 27.20*** 12.95** 29.17*** na na na 

Marital union 

Never married‡ 1.00 1.00 1.00 1.00 1.00 1.00 

In union 1.39 9.28*** 1.50 1.33 1.54 1.37†

Separated/divorced/ widowed 0.73 0.73 0.67 1.77* 1.60 1.71*

Education 

Primary/middle‡ 1.00 1.00 1.00 1.00 1.00 1.00 

Secondary 1.16 2.28 1.23 1.07 0.69 0.95 

Secondary special 1.21 2.66 1.31 1.06 0.72 0.95 

Higher 1.55 2.37 1.57 1.05 0.58† 0.89 

Work status 

Not employed‡ 1.00 1.00 1.00 1.00 1.00 1.00 

White collar 0.95 1.41 0.99 1.14 1.05 1.12 

Manual/agriculture 0.70† 1.64 0.79 0.95 0.85 0.93 

Making ends meet 

Great difficulty‡ 1.00 1.00 1.00 1.00 1.00 1.00 

Some difficulty 1.29 0.89 1.21 1.12 0.75† 1.03 

Little or no difficulty 1.18 1.14 1.16 1.02 0.96 1.00 

Ethnicity 

Uzbek‡ 1.00 1.00 1.00 1.00 1.00 1.00 

Other 0.91 0.44† 0.82 0.71* 0.50** 0.65***

Religion 

Muslim‡ 1.00 1.00 1.00 1.00 1.00 1.00 

Other 1.00 0.35 0.90 0.82 0.87 0.83 

Residence 

Rural‡ 1.00 1.00 1.00 1.00 1.00 1.00 

Urban 1.06 1.88* 1.15 0.88 0.89 0.88 

Region 

Tashkent City‡ 1.00 1.00 1.00 1.00 1.00 1.00 

Western 0.72 1.65 0.83 0.75 1.66† 0.92 

Central 1.16 0.68 1.08 0.75 0.97 0.80 

East-Central 1.04 0.89 1.02 0.82 1.01 0.85 

Eastern 0.53** 0.34* 0.51** 0.71* 0.35*** 0.62**

Number of cases —2,152— 2,152 —4,750— 4,750 

Note: For variable definitions, see Table 1 

‡

Reference category 

†

p<.1, * p<.05, ** p<.01, *** p<.001 a

Category includes all alcohol consumers in the last 12 months 

na = Not applicable 

u = Unknown (Not available because of the small number of female smokers in the sample).

16
Effects of overweight and obesity on the risk of hypertension 

Overall, the risk of hypertension is much greater in men than in women at every level of BMI 

(Figure 1). In men, the risk of hypertension remains relatively low and constant at BMI levels 

below 24 but then it generally increases with BMI. This is consistent with the international cutoff 

of BMI ≥ 25 recommended for defining overweight. However, for women the risk of 

hypertension has a more or less linear positive relationship with the BMI level. Unlike for men, 

there is no clear BMI cutoff point for women beyond which the risk of hypertension accelerates. 

Figure 1. Association between BMI and hypertension, Uzbekistan 2002 

0.0

0.2

0.4

0.6

0.8

10 15 20 25 30 35

BMI (kg/m2

)

Proportion with hypertension

 

0.0

0.1

0.2

0.3

0.4

0.5

10 15 20 25 30 35

BMI (kg/m2

)

Proportion with hypertension

 Men Women 

Table 4 shows the unadjusted and adjusted effects of overweight and obesity on the risk of 

hypertension in alternative models, separately for men and women. Overweight men and women 

are more than twice as likely to suffer from hypertension as those with a normal BMI (OR=2.02; 

95% CI: 1.50-2.72 for men and OR=2.41; 95% CI: 1.90-3.04 for women) (Model 1 for men and 

women). The relationship is much stronger for obesity. Obese men are more than six times 

(OR=6.55; 95% CI: 4.07-10.55) and obese women are more than seven times (OR=7.05; 95% CI: 

5.35-9.28) as likely to suffer from hypertension as men and women with a normal BMI, 

respectively. On the other hand, underweight men and women are significantly less likely to 

suffer from hypertension than those with a normal BMI (OR=0.39 for men and OR=0.56 for 

women). 

Controlling for physical activity level, diet variables, tobacco smoking (only for men), and 

alcohol use in Model 2 makes little difference to the effects of overweight and obesity on the risk 

of hypertension in both men and women. When age and eight other background factors are 

additionally controlled in Model 3, the effects of overweight and obesity are reduced 

considerably, but they remain large and statistically significant. With all the risk factors and 

background factors statistically controlled, obese men and women remain about three times as 

likely to suffer from hypertension as men and women with a normal BMI (OR=3.01; 95% CI: 

1.67-5.44 for men and OR=2.82; 95% CI: 2.05-3.86 for women). The adjusted effects of 

overweight on the risk of hypertension are also smaller than the unadjusted effects, but remain 

positive and statistically significant (OR=1.35 for men and OR=1.54 for women). 

17
Table 4 Unadjusted and adjusted effects (odds ratios) of overweight and obesity and selected risk factors on the risk of 

hypertension, by sex, Uzbekistan 2002 

Men Women 

Characteristic Model 1 Model 2 Model 3 Model 1 Model 2 Model 3 

Risk factors 

BMI (kg/m2) 

<18.5 0.39* 0.41* 0.53 0.56† 0.57† 0.89 

18.5-24.9‡ 1.00 1.00 1.00 1.00 1.00 1.00 

25.0-29.9 2.02*** 2.03*** 1.35† 2.41*** 2.44*** 1.54***

30.0+ 6.55*** 5.77*** 3.01*** 7.05*** 7.18*** 2.82***

Physical activity level 

Low‡ 1.00 1.00 1.00 1.00 

Medium 1.14 1.26 0.88 0.89 

High 0.94 1.06 1.10 1.06 

Diet 

Animal protein (days/week) 

<2‡ 1.00 1.00 1.00 1.00 

2-3 1.23 1.26 0.86 1.01 

4+ 1.30 1.30 0.86 1.09 

Carbohydrate 

Not every day‡ 1.00 1.00 1.00 1.00 

Every day 1.07 0.92 0.85 0.79†

Fresh fruits and vegetables (days/week) 

<3‡ 1.00 1.00 1.00 1.00 

3-4 0.93 0.91 0.79† 0.87 

5+ 1.01 0.98 0.83 0.99 

Dried fruits and vegetables (days/week) 

<1‡ 1.00 1.00 1.00 1.00 

1-2 0.83 0.98 1.29* 1.25 

3+ 0.63 0.85 1.36* 1.22 

Canned or pickled fruits and vegetables 

Does not eat‡ 1.00 1.00 1.00 1.00 

Eats <2 days/week 0.89 0.88 0.85 0.92 

Eats 2+ days/week 0.89 0.82 1.03 1.23 

Fried foods(days/week) 

<3‡ 1.00 1.00 1.00 1.00 

3-5 0.82 0.85 0.81 0.84 

6+ 1.02 1.22 0.64*** 0.81 

Adds salt to cooked food 

No‡ 1.00 1.00 1.00 1.00 

Yes 1.18 0.93 1.10 1.06 

Adds fat to cooked food 

No‡ 1.00 1.00 1.00 1.00 

Yes 1.12 1.05 1.24 1.12 

Tobacco smoking 

Never‡ 1.00 1.00 u u 

Past only 1.51* 1.36 u u 

Current 1.13 1.00 u u 

Alcohol consumption in last 12 months 

No‡ 1.00 1.00 1.00 1.00 

Yes-not a problem drinker 1.30 1.02 

Yes-problem drinker 1.46† 1.11 1.21a 1.04a

Continued...

18
Table 4—Continued

Men Women 

Characteristic Model 1 Model 2 Model 3 Model 1 Model 2 Model 3 

Background characteristics 

Age 

15-19‡ 1.00 1.00 

20-24 2.61** 1.11 

25-29 2.94** 1.95*

30-34 3.37** 2.60**

35-39 3.51** 5.60***

40-44 8.46** 9.21***

45-49 12.46** 17.11***

50-54 13.68*** na 

55-59 12.60*** na 

Marital union 

Never married‡ 1.00 1.00 

In union 1.14 0.96 

Separated/divorced/widowed 1.42 1.37 

Education 

Primary/middle‡ 1.00 1.00 

Secondary 1.05 1.08 

Secondary special 1.13 0.96 

Higher 1.36 1.24 

Work status 

Not employed‡ 1.00 1.00 

White collar 0.59* 0.90 

Manual/agriculture 0.65* 0.92 

Making ends meet 

Great difficulty‡ 1.00 1.00 

Some difficulty 0.92 0.85 

Little or no difficulty 1.02 0.92 

Ethnicity 

Uzbek‡ 1.00 1.00 

Other 1.12 0.86 

Religion 

Muslim‡ 1.00 1.00 

Other 1.01 1.12 

Residence 

Rural‡ 1.00 1.00 

Urban 0.98 0.83 

Region 

Tashkent City‡ 1.00 1.00 

Western 1.09 4.00***

Central 0.47* 2.77***

East-Central 0.44** 2.62***

Eastern 0.30*** 1.39 

Number of cases 2,256 2,250 2,248 5,080 5,069 5,058 

Note: For variable definitions, see Table 1 

‡

Reference category 

†

p<.1, * p<.05, ** p<.01, *** p<.001 a

Category includes all alcohol consumers in the last 12 months 

na = Not applicable 

u = Unknown (Not available because of the small number of female smokers in the sample) 

19
DISCUSSION 

Results confirm strong adverse effects of overweight and obesity on the risk of hypertension in 

adult men and women in Uzbekistan. Overweight men and women are more than twice as likely 

and obese men and women are more than six times as likely to suffer from hypertension as men 

and women with a normal BMI. Even with physical activity level, diet, tobacco smoking, alcohol 

use, and a number of other potentially confounding background factors controlled statistically, 

obese men and women in Uzbekistan are about three times as likely to suffer from hypertension 

as men and women with a normal BMI. The adjusted effects of overweight on hypertension are 

also reduced, but remain positive and statistically significant. This finding of a strong positive 

association between obesity and hypertension is consistent with an earlier study in Central Asia 

(Kadyrova and Salkhanov 1990) and numerous studies from other parts of the world (e.g., Kotsis 

et al. 2005; Sanchez-Castillo et al. 2005; Liu et al. 2004; Niskanen et al. 2004; Lee et al. 2004; Hu 

et al. 2004; Venkatramana and Reddy 2002; Adair 2004; Lerman-Garber et al. 1999). 

Overall, the risk of hypertension is much greater in men than in women at any given level of 

BMI. For men, the risk of hypertension is strongly positively associated with BMI only at BMI 

levels above 25, but for women a positive relationship is observed at all BMI levels. This 

indicates that using a BMI cutoff point of 25 to define overweight is more appropriate for men 

than for women. 

Our analysis of the risk factors of obesity and hypertension produced mixed results. The study 

finds no significant association between physical activity level and the risk of obesity or 

hypertension. Eating animal protein and tobacco smoking in the past are positively associated 

with obesity, but there are no consistent associations with other diet indicators or alcohol use. The 

lack of association of obesity and hypertension with physical activity level and the generally 

weak, inconsistent associations with diet, current smoking, and alcohol use in this study are 

inconsistent with previous research (Jakes et al. 2003; Hu et al. 2004; Hu et al. 2002; Sobngwi et 

al. 2002; Lin et al. 2004; Nanchahal et al. 2005; Vioque et al. 2000; Bell et al. 2002; Niskanen et 

al. 2004; Okubo et al. 2004). 

The study finds that the prevalence of obesity and prevalence of hypertension have strong 

positive associations with age in both men and women, as expected. Urban residence has a strong 

positive association with obesity in men, but not in women. Men in union are considerably more 

likely to be obese than never-married men, independent of other factors. Women in union are also 

more likely to be overweight or obese, but the relationship is much stronger for men. 

A major limitation of our analysis is the cross-sectional nature of the data. In the UHES, the 

prevalence of overweight, obesity, and hypertension, as well as the prevalence of various risk 

factors, were measured at the time of the survey. A lack of association of obesity and 

hypertension with physical activity level and generally weak, inconsistent associations with diet, 

current smoking, and alcohol use may be partly due to the fact that some men and women may 

have altered their physical activity patterns, changed their eating habits, or quit smoking after 

becoming obese or after being diagnosed with hypertension. Prospective cohort studies are 

needed to better understand the relationships between physical activity, diet, smoking, and risks 

of obesity and hypertension. 

Another limitation is that we were not able to consider other measures of obesity, particularly 

abdominal obesity, which may be more relevant for linking obesity with the risk of hypertension. 

In Asian populations, abdominal or central obesity is more common than obesity defined by BMI, 

20
and health risks associated with overweight and obesity occur at lower levels of BMI than in 

North America or Europe (WHO, IASO, IOTF 2000). 

Moreover, our study could not control directly for the extent of use of medical services in 

connection with obesity or hypertension, although the set of control variables used in the study 

includes several measures of socioeconomic status, which are typically correlated with access to 

and use of medical services. 

In conclusion, this study provides important new information on the prevalence of obesity and 

hypertension in different population groups in Uzbekistan. The results show a strong positive 

effect of obesity on the risk of hypertension in both men and women. However, the shape of the 

relationship between BMI and hypertension is different for women than for men. Moreover, 

several other relationships are observed only for men or only for women. 

The findings emphasize the need to strengthen policies and programs to contain the obesity 

epidemic and prevent associated ill health and mortality. Moreover, the notably different findings 

for men and women in some of the analyses suggest that programs related to obesity and 

hypertension need to be gender sensitive. 

21
REFERENCES 

Adair, L.S. 2004. Dramatic rise in overweight and obesity in adult Filipino women and risk of 

hypertension. Obesity Research 12(8):1335-41. 

Analytical and Information Center (AIC), Ministry of Health of the Republic of Uzbekistan 

[Uzbekistan], State Department of Statistics, Ministry of Macroeconomics and Statistics 

[Uzbekistan], and ORC Macro. 2004. Uzbekistan Health Examination Survey 2002. Calverton, 

Maryland, USA: Analytical and Information Center, State Department of Statistics, and ORC 

Macro. 

Bell, A.C., K. Ge, and B.M Popkin. 2002. The road to obesity or the path to prevention: 

motorized transportation and obesity in China. Obesity Research 10(4):277-83. 

Cherpitel, C.J. 1997. Brief screening instruments for alcoholism. Alcohol Health and Research 

World 21(4): 348-51. 

Djousse, L., D.K. Arnett, J.H. Eckfeldt, M.A. Province, M.R. Singer, and R.C. Ellison. 2004. 

Alcohol consumption and metabolic syndrome: does the type of beverage matter? Obesity 

Research 12(9):1375-85. 

Gopinath, N., S.L. Chadha, P. Jain, S. Shekhawat, and R. Tandon. 1994. An epidemiological 

study of obesity in adults in the urban population of Delhi. The Journal of the Association of 

Physicians of India 42(3):212-5. 

Grundy, S.M., H.B. Brewer, J.I. Cleeman, S.C. Smith, and C. Lenfant. 2004. Definition of 

metabolic syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart 

Association Conference on Scientific Issues Related to Definition. Circulation 109:433-8. 

Hu, G., N.C. Barengo, J. Tuomilehto, T.A. Lakka, A. Nissinen, and P. Jousilahti. 2004. 

Relationship of physical activity and body mass index to the risk of hypertension: a prospective 

study in Finland. Hypertension 43(1):25-30. 

Hu, G., H. Pekkarinen, O. Hanninen, H. Tian, and R. Jin. 2002. Comparison of dietary and nondietary risk factors in overweight and normal-weight Chinese adults. British Journal of Nutrition

88(1):91-7. 

International Diabetes Federation (IDF). 2005. The IDF consensus worldwide definition of the 

metabolic syndrome. Brussels, Belgium: International Diabetes Federation. 

IPAQ. 2004. Guidelines for data processing and analysis of the International Physical Activity 

Questionnaire (IPAQ) – Short form, Version 2.0. April 2004. 

http://www.ipaq.ki.se/dloads/Scoring%20short%20April04.pdf (accessed: 5/23/2005). 

Jakes, R.W., N.E. Day, K.T. Khaw, R. Luben, S. Oakes, A. Welch, S. Bingham, and N.J. 

Wareham. 2003. Television viewing and low participation in vigorous recreation are 

independently associated with obesity and markers of cardiovascular disease risk: EPIC-Norfolk 

population-based study. European Journal of Clinical Nutrition 57(9):1089-96. 

Jeffery, R.W., and A.M. Rick. 2002. Cross-sectional and longitudinal associations between body 

mass index and marriage-related factors. Obesity Research 10(8):809-15. 

22
Kadyrova, R.Kh., and B.A. Salkhanov. 1990. The prevalence of obesity among the adult 

population of Kazakhstan. Voprosy Pitaniia Jan-Feb (1):30-3 [Russian]. 

King, H., B. Abdullaev, S. Djumaeva, V. Nikitin, L. Ashworth, and M.G. Dobo. 1998. Glucose 

intolerance and associated factors in the Fergana Valley, Uzbekistan. Diabetic Medicine 

15(12):1052-62. 

King, H., S. Djumaeva, B. Abdullaev, and M.G. Dobo. 2002. Epidemiology of glucose 

intolerance and associated factors in Uzbekistan: a survey in Sirdaria province. Diabetes 

Research and Clinical Practice 55(1):19-27. 

Kotsis, V., S. Stabouli, M. Bouldin, A. Low, S. Toumanidis, and N. Zakopoulos. 2005. Impact of 

obesity on 24-hour ambulatory blood pressure and hypertension. Hypertension 45(4):602-7. 

Lee, J.S., K. Kawakubo, H. Kashihara, and K. Mori. 2004. Effect of long-term body weight 

change on the incidence of hypertension in Japanese men and women. International Journal of 

Obesity and Related Metabolic Disorders 28(3):391-5. 

Lerman-Garber, I., A.R. Villa, C.L. Martinez, L.C. Turrubiatez, C.A. Aguilar Salinas, V. Lucy, 

B. Wong, J.C. Lopez Alvarenga, F. Gomez-Perez, and L.M. Gutierrez-Robledo. 1999. The 

prevalence of obesity and its determinants in urban and rural aging Mexican populations. Obesity 

Research 7(4):402-6. 

Lin, B.H., C.L. Huang, and S.A. French. 2004. Factors associated with women's and children's 

body mass indices by income status. International Journal of Obesity and Related Metabolic 

Disorders 28(4):536-42. 

Liu, L., K. Ikeda, M. Chen, W. Yin, S. Mizushima, T. Miki, Y. Nara, and Y. Yamori. 2004. 

Obesity, emerging risk in China: trend of increasing prevalence of obesity and its association with 

hypertension and hypercholesterolaemia among the Chinese. Clinical and Experimental 

Pharmacology & Physiology 31 Suppl 2:S8-S10. 

Mendez, M.A., C.A. Monteiro, and B.M. Popkin. 2005. Overweight exceeds underweight among 

women in most developing countries. American Journal of Clinical Nutrition 81(3):714-21. 

Misra, A., R.M. Pandey, J.R. Devi, R. Sharma, N.K. Vikram, and N. Khanna. 2001. High 

prevalence of diabetes, obesity and dyslipidaemia in urban slum population in northern India. 

International Journal of Obesity and Related Metabolic Disorders 25(11):1722-29. Erratum in: 

International Journal of Obesity and Related Metabolic Disorders 2002, 26(9):1281. 

Monteiro, C.A., W.L. Conde, and B.M. Popkin. 2001. Independent effects of income and 

education on the risk of obesity in the Brazilian adult population. Journal of Nutrition 

131(3):881S-886S. 

Monteiro, C.A., E.C. Moura, W.L. Conde, and B.M. Popkin. 2004. Socioeconomic status and 

obesity in adult populations of developing countries: a review. Bulletin of the World Health 

Organization 82(12):940-6. 

23
Nanchahal, K., J.N. Morris, L.M. Sullivan, and P.W. Wilson. 2005. Coronary heart disease risk in 

men and the epidemic of overweight and obesity. International Journal of Obesity and Related 

Metabolic Disorders 29(3):317-23. 

Niskanen, L., D.E. Laaksonen, K. Nyyssonen, K. Punnonen, V.P. Valkonen, R. Fuentes, T.P. 

Tuomainen, R. Salonen, and J.T. Salonen. 2004. Inflammation, abdominal obesity, and smoking 

as predictors of hypertension. Hypertension 44(6):859-65. 

Okubo, Y., Y. Suwazono, E. Kobayashi, and K. Nogawa. 2004. An association between smoking 

habits and blood pressure in normotensive Japanese men: a 5-year follow-up study. Drug and 

Alcohol Dependence 73(2):167-74. 

Popkin, B., N. Zohoori, L. Kohlmeier, A. Baturin, A. Martinchik, and A. Deev. 1997. Nutritional 

risk factors in the former Soviet Union. In: Premature death in the New Independent States, ed. 

Jose L. Bobadilla, Christine A. Costello, and Faith Mitchell. Washington, D.C.: National 

Academy Press. 314-34. 

Sanchez-Castillo, C.P., O. Velasquez-Monroy, A. Lara-Esqueda, A. Berber, J. Sepulveda, R. 

Tapia-Conyer, and W.P. James. 2005. Diabetes and hypertension increases in a society with 

abdominal obesity: results of the Mexican National Health Survey 2000. Public Health and 

Nutrition 8(1):53-60. 

Sobngwi, E., J.C. Mbanya, N.C. Unwin, A.P. Kengne, L. Fezeu, E.M. Minkoulou, T.J. Aspray, 

and K.G. Alberti. 2002. Physical activity and its relationship with obesity, hypertension and 

diabetes in urban and rural Cameroon. International Journal of Obesity and Related Metabolic 

Disorders 26(7):1009-16. 

Stata Corporation Inc. 2003. STATA Release 8.1. College Station, Texas, USA: Stata Press. 

Szczygielska, A., S. Widomska, M. Jaraszkiewicz, P. Knera, and K. Muc. 2003. Blood lipids 

profile in obese or overweight patients. Annales Universitatis Mariae Curie-Sklodowska [Med] 

58(2):343-9. 

Venkatramana, P., and P.C. Reddy. 2002. Association of overall and abdominal obesity with 

coronary heart disease risk factors: comparison between urban and rural Indian men. Asia Pacific 

Journal of Clinical Nutrition 11(1):66-71. 

Vioque, J., A. Torres, and J. Quiles. 2000. Time spent watching television, sleep duration and 

obesity in adults living in Valencia, Spain. International Journal of Obesity and Related 

Metabolic Disorders 24(12):1683-88. 

Westat Inc. 1993. Pulse and blood pressure procedures for household interviews. National 

Health and Nutrition Examination Survey III, Cycle 2. Rockville, Maryland, USA: Westat Inc. 

World Health Organization (WHO). 2003. Diet, nutrition, and the prevalence of chronic 

diseases: a report of a Joint WHO/FAO Expert Consultation. Geneva: WHO Technical Report 

Series 916. 

World Health Organization (WHO). 2005. European Health for All Database. 

http://www.euro.who.int/hfadb (accessed: 6/14/2005). 

24
World Health Organization (WHO), International Association for the Study of Obesity (IASO), 

International Obesity Task Force (IOTF). 2000. The Asia-Pacific perspective: redefining obesity 

and its treatment. Geneva: World Health Organization. 

Young, J.H., P. Parler, B. Bristol, and M.J. Klag. 2005. The coming epidemic: hypertension in 

rural Kyrgyzstan, Central Asia. Journal of Human Hypertension 19(2):145-48. 

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