



































Prevalence of Risk Factors for Non-Communicable Diseases in Adult Population of Urban Areas in Kabul City, Afghanistan


 

 

New articles in this journal are licensed under a Creative Commons Attribution 3.0 United States License. 

 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 

 

 

 

 

 

 

 
 

 

 

 

Prevalence of Risk Factors for 

Non-Communicable Diseases in 

the Adult Population of Urban 

Areas in Kabul City, Afghanistan 
 

 

Khwaja Mir Islam Saeed 

 
Afghanistan National Public Health 
Institute, Ministry of Public Health, 
Kabul, Afghanistan 

 

 

 

Vol. 2, No. 2 (2013)   |   ISSN 2166-7403 (online)    

DOI 10.5195/cajgh.2013.69   |   http://cajgh.pitt.edu 



 

 

SAEED 

 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

  

 

Abstract 

Background: Non-Communicable diseases (NCDs) are a major global problem. This study aims to estimate the prevalence of 

common risk factors for NCDs among the adult population in urban areas of Kabul city, Afghanistan. 

Methods and Materials: This study was conducted from December 2011 through March 2012 and involved a survey of 1169 

respondents, aged 40 years and above. Multistage cluster sampling was used for participant selection, followed by random 

sampling of the participants. The World Health Organization STEPwise approachfor Surveillance (STEPS) was modified and 

used for this study.  

Results: The overall prevalence of smoking was 5.1% (14.7% men versus 0.3% women) and using mouth snuff was 24.4% in 

men and 1.3% in women. The prevalence of obesity and hypertension were 19.1% and 45.2 % in men and 37.3% and 46.5% in 

women. Prevalence of diabetes was 16.1% in men and 12% in women. The overall prevalence of obesity, hypertension and 

diabetes mellitus was 31.2%, 46% and 13.3%, respectively. On average, subjects consumed 3.37 servings of fruit and 2.96 

servings of leafy vegetables per week. Mean walking and sitting hours per week (as proxies for physical activity) were 19.4 and 

20.5, respectively. A multivariate model demonstrated that age was a significant risk factor for obesity (OR=1.86), diabetes 

(OR=2/09) and hypertension (OR=4.1). Obesity was significantly associated with sex (OR=1.65).  

Conclusion: These results highlight the need for interventions to reduce and prevent risk factors of non-communicable diseases 

in urban areas of Kabul City, Afghanistan. 

Keywords: non-communicable diseases, risk factors, hypertension, obesity, WHO STEPS 

 

Prevalence of Risk Factors for Non-

Communicable Diseases in Adult 

Population of Urban Areas in Kabul 

City, Afghanistan  

Khwaja Mir Islam Saeed 

 
Afghanistan National Public Health Institute, 
Ministry of Public Health, Kabul, Afghanistan 

Research 

Non-communicable diseases (NCDs) consist of 

a vast group of non-infectious medical conditions; 

however emphasis has been on cardiovascular disease, 

cancer, diabetes, and chronic respiratory diseases. 

Despite being included in the recent, global 

development agenda,
1
 the World Health Assembly also 

endorsed an important, new health goal to reduce 

avoidable mortality from NCDs 25% by 2025.
2
 In 1990, 

there were 26.6 million deaths worldwide from NCDs, 

which increased to 34.5 million in 2010.
3
 Furthermore, 

in 2008 approximately 63% (36 million) of all deaths 

were due to NCDs.
4
 Likewise, the total number of 

disability-adjusted life-years (DALYs) increased from 

43% in 1990 to 54% in 2010 worldwide.
5 

The global 

economic burden of NCDs is large, estimated at US 

$6.3 trillion in 2010, anticipated to rise to $13 trillion by 

2030.
6
 

Due to rapid demographic and epidemiologic 

transitions, South Asian life expectancy is increasing 

and fertility rate is reducing, which has led to an 

increased health burden of NCDs.
7 

The leading risk 

factors for the development of non-communicable 

disease are high blood pressure, high cholesterol, 

inadequate intake of fruit and vegetables, overweight or 

obesity, physical inactivity, and tobacco use.
8 

It has 



 

 

CENTRAL ASIAN JOURNAL OF GLOBAL HEALTH 

 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program, and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

  

 

been indicated that the prevalence of smoking varies in 

South Asian countries from 16-32%, alcohol 

consumption (3-41%), eating less than five servings of 

fruits and vegetables (81-99%), physical inactivity (4-

24%), overweight and obesity (9-44%), elevated blood 

pressure (8-42%), elevated fasting blood sugar (4-9%), 

and elevated blood cholesterol (13-54%).
9
 In a recent 

Indian study, it was shown that those living in urban 

areas were at higher risk for developing NCDs as 

compared to their rural counterparts.
10

 

Hypertension affects nearly one billion people 

worldwide and it is expected to increase to 1.5 billion 

by the year 2025.
11 

The global prevalence of 

hypertension is estimated to be 30% among adults, with 

variations existing between economically developed and 

developing countries.
12 

In the Eastern Mediterranean 

Region (EMR), the prevalence of hypertension is 

approximately 29%, affecting approximately 125 

million individuals.
13 

In Iran, the estimated prevalence 

of hypertension in those aged 30–55 and more than 55 

years was approximately 23% and 50%, respectively.
14 

In a Pakistani study, the overall prevalence of 

hypertension was 26%, with changes in sex as well as 

age.
15 

Global diabetes prevalence was 2.8% in 2000 and 

is projected to grow to 4.4% by 2030.
16

 Developing 

countries are increasingly vulnerable to obesity and 

diseases associated with excess adipose tissue.
17,18

 In 

another Pakistani study, the prevalence of diabetes was 

12.1% in males and 9.8% in females,
19

 while the 

national prevalence of diabetes in Iran in 2005 was 

7.7% with 8.3% of females and 7.1% of males 

affected.
20

 

Complete information of the morbidity and 

mortality associated with NCDs is not fully available in 

Afghanistan due to low attention and years of conflict.  

However, the Afghanistan Mortality Survey (AMS) in 

2010 revealed that 33.3% of all deaths are attributed to 

NCDs compared to 42.6% due to communicable, 

maternal, perinatal, and nutritional conditions. 

Cardiovascular diseases, malignant neoplasms, diabetes, 

respiratory diseases, and digestive diseases are the 

leading causes of deaths due to NCDs.
21 

Based on a 

World Health Organization (WHO) estimate, in 2000 

there were 468,000 people with diabetes in Afghanistan. 

This number is expected to rise to 1,403,000 by 2030, 

representing nearly a threefold increase.
22,23 

Smoking 

prevalence among men 15 years and older in Kabul city 

was reported as 35%,
24

 compounded by the fact that 

Kabul ranked as one of the dirtiest cities in the world in 

terms of ambient air quality, potentially increasing the 

burden of respiratory diseases and different types of 

cancer among humans.
25

 

The STEPwise approach to Surveillance 

(STEPS) developed by WHO has been used by different 

countries in order to identify and monitor the prevalence 

of NCD risk factors.
26

 In the EMR, more than half of 

member states (56%) have already conducted and 

established surveillance systems for NCDs using 

STEPS.
27

 Unfortunately, there is no experience of 

surveillance of NCDs in Afghanistan. This study aims 

to describe the prevalence and risk factors for NCDs 

among adults aged 40 years and older in Kabul City, 

Afghanistan using standardized survey methodology, 

STEPS,
28

 and to provide information for public health 

actions.  

 

Methods and Materials 

Setting 

This cross-sectional study was conducted 

among residents 40 years old and above in Kabul city, 

the capital of Afghanistan. The city has approximately 

534,900 households and 3,289,000 inhabitants, with a 

slightly higher male population (51.8%).
29

 

Administratively, Kabul city is divided into 22 districts, 

in 16 of which people reside. Districts are further 

divided into clusters or neighborhoods (Gozar). 

Initially, we officially requested that the Kabul 

municipality provide us the list of all neighborhoods, 

local representative leaders, and its estimated 



 

 

SAEED 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program, and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

 

 

populations; we were able to obtain information on 13 

districts.  

 

Sample size 

The statistical software program Epi Info was 

used to calculate the sample size for this study. By 

taking into account a precision level of 5%, confidence 

interval of 95%, and proportion of risk factors in 

research studies such as diabetes, blood pressure, 

physical activity, dietary behavior, obesity, age, level of 

education, and smoking status in diseased and non-

diseased people in similar settings, the number of 

subjects in this study was raised to 600 individuals. To 

balance considerations of cost, resources, and time 

without compromising the representativeness of the 

sample, a three-phase cluster sampling technique was 

planned. Lastly, after taking into account the design 

effect (DE=2) of cluster sampling, the final sample size 

reached (2 x 600) = 1,200, which was reasonable for 

achieving study objectives within limited resources and 

funding support. 

 

Participants 

Eligible subjects were selected by multistage 

sampling; in the first stage, a sample of neighborhoods 

was selected randomly from each district. In the second 

stage in each neighborhood a main masjid was selected 

as a hallmark and heads of households around the 

masjid were asked to approach the team settled there. In 

the third stage, one adult person was selected from each 

household randomly and interviewed after consent was 

taken. Of our target 1,200 individuals, 1,193 records 

were available for entry. Seven were lost during 

fieldwork or transportation. Ten subjects were excluded 

due to being less than 40 years old, and 14 others were 

excluded due to unavailability of data for either height 

or weight for calculation of BMI. Therefore, 1,169 

individuals were included in analysis. The study was 

approved by the Institutional Review Board (IRB) of the 

Ministry of Public Health, Afghanistan.  

 

Data Collection and Measurement 

Data collection was carried out from December 

2011 to March 2012. Data collected by questionnaire 

consisted of demographic characteristics, socio-

economic factors, and behavioral risk factors such as 

smoking, fruit and vegetable consumption, and physical 

activity. The questionnaire was modified with expanded 

and optional questions to suit local needs. Extended 

questions were in the STEPS instrument modified by 

adding locally relevant responses. Optional questions 

were added to the instrument because they were deemed 

locally important; for example, snuff use was included 

due to its high prevalence in the area. The questionnaire 

was translated into the Dari language and tested prior to 

actual data collection. Physical measurements included 

weight in bare feet with usual clothing, height in bare 

feet without headwear, waist circumference at the 

narrowest point between the lower costal border and the 

iliac crest measured using a constant tension tape, and 

blood pressure at the midpoint of the arm after 

participants had rested for at least five minutes. Two 

blood pressure readings were obtained for all 

participants. A third reading was taken if there was a 

difference of more than 20 mmHg for systolic blood 

pressure or 10 mmHg for diastolic blood pressure 

between the first two readings. The mean of all 

measures was used and recorded. Biochemical measures 

included random and blood glucose measured in 

capillary blood using a glucometer. Data collection staff 

consisted of paramedical doctors and experienced 

surveyors. They underwent intensive training and 

supervision provided by the Afghan National Public 

Health Institute. A pilot study including 20 participants 

from MoPH staff was conducted, which helped us to 

reword some questions and estimate the timing of the 

interview. Blood pressure instruments were tested 

against each other and showed no differences in 



 

 

CENTRAL ASIAN JOURNAL OF GLOBAL HEALTH 

 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program, and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

  

 

measurement. Questionnaires were administered by 

face-to-face interviews. 

 

Definitions of risk factors 

Overweight was defined as BMI 25-29.9 

kg/m
2
, and obesity as BMI ≥30 kg/m

2
.
30

 Waist-

circumference ≥94 cm in men and ≥80 cm in women 

was taken as the cutoff point to define central obesity.
31

 

Consumption of fruits and vegetables were measured as 

the frequency of servings per week as raw leafy 

vegetables and one medium-sized and seasonal piece of 

fruit. Physical activity was defined as walking, sport, or 

strong physical activity in minutes per day, hours per 

day, and/or per week. Hypertension was diagnosed if 

systolic blood pressure was ≥140 mm of Hg and/or 

diastolic pressure ≥90 mm of Hg, or diagnosed cases 

taking antihypertensive drugs.
32

 Pre-hypertension is 

defined as 120-139 mm Hg systolic blood pressure 

and/or 80-89 mm Hg diastolic pressure.
33

 Individuals 

with a random blood sugar of ≥ 200mg/dL were later 

confirmed by fasting blood sugar (FBS). 
34,35

 An FBS of 

≥ 126mg/dL were considered diabetic.
35

 

 

Statistical Software 

Responses in the questionnaire were coded and 

entered into Epi Info software version 3.5.1.
36

 Statistical 

analyses were performed using SPSS software version 

20.
37

 

 

Results 

Descriptive analysis 

The mean age of study subjects was 49.5 ± 

10.2 years, while according to recent survey in 2010 

women and men are now living past age 60 years.  

66.5% were female due to low availability of males 

during daytime at home. The majority of participants 

(58%) were less than 50 years of age. Illiteracy, being 

79.4%, was the main concern in women. Fifty-two 

percent of the participants had a monthly income of less 

than 200 USD. Nearly 5% of participants reported being 

current smokers, and 9% reported using mouth snuff.  

Reflecting cultural practice, the prevalence of cigarette 

smoking and mouth snuff used were much higher in 

men than in women. Selected socio-economic and 

demographic characteristics of the participants are 

shown in Table 1.  

 

Table 1. Frequency distribution of the background 

characteristics of study participants (N=1,169). 

 

Two-thirds of families reported using solid 

ghee for cooking in the kitchen. Fifty percent of 

participants ate red meat 1-2 times per week while 90% 

consumed rice 1-2 times per week. Consuming leafy 

vegetables and fresh fruits with lunch or dinner was less 

common due to economic problems; close to 60% 

consumed three servings or less with or after meals. 

Table 2 presents data on behavioral risk factors for 

males and females. The adult population, particularly 

women, in Kabul city performed little physical activity. 

Approximately 15% of respondents reported 10-30 

minutes of different kinds of physical activity daily 

while the rest reported being sedentary. Walking as a 

proxy for physical activity was a better habit among 

citizens. One hour of daily walking for various purposes 

was quite common (31%) among respondents. 

Table 2. Frequency distribution of the Behavior factors 

evaluated (n=1,169). 

 

Overall, 69.3% of study participants were 

either overweight or obese (38.1% overweight and 

31.2% obese). Being overweight and obese was slightly 

more prevalent in women as compared to men. 

Furthermore, 57.8% were centrally obese using waist 

circumference. The average BMI was 27.85 ± 5.17 



 

 

SAEED 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program, and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

 

 

kg/m
2 

and ranged from 15.2 to 62.2 kg/m
2
.  33%, 

48.5%, and 18.5% were hypertensive, pre-hypertensive 

and normotensive, respectively. Table 3 shows the 

prevalence of pathophysiological risk factors. 

 

Table 3. Frequency distribution of pathophysiological 

risk factors for NCDs of study participants (N=1,169). 

 

The prevalence of diabetes mellitus was 13.3% 

and was more common in women (59.5%) as compared 

to men (40.4%). Some study subjects had only one risk 

factor while the others had two or more, which were 

categorized as risk factors groups. For instance, having 

risk factors of diabetes mellitus, blood pressure, and 

obesity at the same time were categorized as triple risk 

factor group. Having double risk factors of diabetes and 

obesity was 5.2%, diabetes and hypertension was 7.8%, 

and hypertension and obesity was 18.3%. Trip risk 

factors were present in 3.6% of the participants. The 

greater the number of risk factors, the higher the 

probability of NCDs among the adult population. 

 

Statistical analysis 

Multivariate logistic regression was performed 

for common risk factors versus pathophysiological risk 

factors such as diabetes mellitus, hypertension and 

obesity in order to find independent associations,as 

reflected in Table 4. Age was a significant risk factor 

for all three conditions with an Adjusted Odds Ratio 

(AOR) and Confidence Interval (CI) of (AOR=1.86, 

95% [1.29, 2.66]), (AOR=2.09, 95% CI [1.32, 3.31],  

(AOR=4.1, 95% CI [2.97, 5.65]), respectively for 

obesity, diabetes and hypertension. There were no 

significant associations between sex and diabetes 

mellitus and hypertension. However, obesity was 

significantly associated with sex, with females more 

likely to be obese as compared to males (OR=1.65, 95% 

CI [1.08, 2.52]). Illiterate participants were less likely to 

be diabetic (OR=0.55, 95% CI [0.34, 0.88]) as 

compared to literate participants. 

 

Table 4. Multivariate analysis risk factors associated 

with obesity, hypertension, and diabetes mellitus. 

 

There were significant associations between 

diabetes and obesity (OR=1.66, 95% CI [1.04, 2.65]) as 

well as obesity and hypertension (OR=2.08, 95% CI 

[1.49, 2.90]). Central obesity was significantly 

associated with hypertension (OR=1.72, 95%CI [1.25, 

2.36]). Proxies for physical activities were daily 

walking, mode of transportation for getting to the 

workplace, and sitting time at work or living place. 

Walking in ‘hours per week’ was significantly 

associated with obesity, and proxies were associated 

with hypertension and diabetes mellitus. Diet was 

categorized by using reported habits of eating red meat 

or chicken, type of kitchen fat, rice, and fruits and 

vegetables by weekly or monthly frequencies. 

Consuming chicken as lunch or dinner was associated 

with obesity and hypertension while eating red meat as 

a meal was significantly associated with diabetes 

mellitus. Cooking meals with liquid ghee was a 

protective factor for diabetes (OR=0.35, 95% CI [0.22, 

0.54]), although we did not find any association of 

cooking fat with obesity and hypertension. Consuming 

rice as a meal is considered a luxury in the country. 

Frequently eating rice as a meal was significantly 

associated with diabetes (OR=2.3, 95% CI [1.48, 3.58]) 

and hypertension (OR=1.43, 95% CI [1.06, 1.93]). We 

found a significant association between frequency of 

consuming fruits and hypertension (OR=1.43, 95% CI 

[1.03, 1.96]) but no association between fruits and 

vegetables with obesity and diabetes mellitus. 

 

 

 



 

 

CENTRAL ASIAN JOURNAL OF GLOBAL HEALTH 

 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program, and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

  

 

Discussion 

Maternal health, malnutrition, vaccine 

preventable diseases, and communicable diseases are 

the main concerns in Afghanistan on which the 

government and its partners are focusing over the last 

decade. However, epidemiological studies focusing on 

risk factors for NCDs are of great importance to fill the 

gap of information and knowledge existing in the 

country. Our study presented the NCD risk factor 

burden using WHO-STEPS tool estimated prevalence of 

diabetes, smoking, snuff use (smokeless tobacco), 

obesity, blood pressure, and physical inactivity among 

the urban population of Kabul city. It could be used as a 

baseline for newly established NCD department at 

MoPH to develop policies and strategies and plan of 

actions against them.  

According to our findings, two thirds of the 

adult (age ≥40) urban citizens of Kabul city, the capital 

of Afghanistan, are overweight or obese with nearly one 

third of them meeting the criteria for obesity. In 

addition, more than half of the adult population has 

central obesity.  Although no information is available to 

assess the trends of obesity, the economic condition of 

urban citizens is getting better. Moreover, culturally 

being overweight and obese is perceived as healthy, and 

people are not interested in losing weight; particularly 

fat women are considered to be beautiful. Increasing age 

has a negative effect on the level of obesity at bivariate 

as well as multivariate levels. Based on recent studies 

the life expectancy is 62 years in the country.
38

 Since 

the study was conducted on upper age groups, it can be 

justified that older ages suffering from chronic diseases, 

which are attributed to low appetite and being on a diet, 

are not gaining weight. Likewise, gender as a non-

modifying factor has a relationship at both level of 

analysis. As females are mostly confined at home as 

housewives and are less likely to be physically 

functional, they are not as obese as compared to males. 

Therefore, health promotion strategies should focus on 

obesity as a problem of productive groups. The 

proportion as well as the effect of age and gender on 

obesity is comparable with other studies.
39-45

 

The independent significant association of 

obesity and blood pressure as well as diabetes depict 

that the factors are related to each other and combined 

intervention concentrating on multiple factors is 

beneficial. With the prevalence of hypertension and 

diabetes found here, we can posit that the country has 

already entered an epidemic of non-communicable 

diseases, which requires strengthening efforts for its 

control and prevention. The health education campaigns 

should be tailored to cover all of them. Walking as a 

proxy for physical activity is a protective factor against 

obesity as well as other NCDs. Community awareness 

and establishment of sport centers and jogging lots, 

which is lacking in urban settings particularly for 

women, should be encouraged and discussed with 

relevant sectors. This statement was proved by this 

study as well as other studies.
19,46,47

 Our study shows the 

higher percentage of blood glucose in people who are 

equal to or more than 40 years of age (13.57%) in Kabul 

city. As there is no data regarding prevalence of 

diabetes in the country, this information can fill the gap 

of information and help the newly established NDC 

department at MoPH to plan and focus on target groups.  

The diabetic control center should be strengthened in 

the country, and they should focus on older productive 

age groups with preventive and modifying interventions 

of life style. Using bivariate analysis, age was a 

significant non-modifiable factor, which influenced the 

prevalence of diabetes by change of 9% from lower to 

higher age groups. High prevalence of diabetes in older 

age groups who also have other aging diseases will put 

them in a vicious circle, which could lead to 

overburdening the health system in the country. 

Working ahead of time for such diseases, not only 

reduces the economic burden on health system but also 

improves the life style of productive groups. Men are at 

more risk than women, which is not a modifying factor 

and could be due to genetic makeup. These findings are 



 

 

SAEED 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program, and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

 

 

consistent with national studies in neighboring countries 

and other nations in the region.
23,48-50

  

Based on our findings, the prevalence of 

smoking and snuffing is much higher in men versus 

women that are probably due to cultural unacceptability 

and less freedom of smoking among women versus 

men. As the baseline for smoking is not available it is 

not supposed to higher. In summary, according to 

multivariate model we are recommending strategic 

actions to be concentrated on older ages, education 

level, cousin marriage to reduce history of diabetes in 

the family, using liquid oil in kitchen, and short daily 

walking. Focusing on these factors certainly will lead to 

reduction of cases in future.  

According to the findings of this study, 

approximately half of the adult population in Kabul city 

has hypertension. Results of an Iranian study support 

these findings, in which the overall prevalence rate of 

hypertension was 27.1% with higher rates in men 

(32.3%) as compared to women (22.5%). It provides a 

baseline, or a trigger point, for policy makers to focus 

upon and take it seriously for future planning and 

potential interventions. In addition, there was a positive 

correlation between the hypertension prevalence and 

age as well as education. The link between education 

and health is now well established, and growth in 

literacy rates, particularly among women, has been 

shown to have a positive impact on health. It seems that 

non-communicable diseases are occurring as a 

combined syndrome in adult population. Convenient 

modes of transportation to the workplace and sedentary 

lifestyle (including decreased physical activity) have a 

negative impact on health and the risk of hypertension. 

The prevalence of diabetes and obesity, either central or 

general, is affecting the level of blood pressure at the 

bivariate level of analysis and needs to be considered as 

comorbidity while managing hypertension. It means that 

some screening program, if established, will prevent the 

development of raised blood pressure. Multivariate 

analysis revealed higher age, education level as 

socioeconomic factors, consuming chicken, rice, fruits 

and walking habits as behavioral factors are 

significantly and independently affecting the level of 

blood pressure, diabetes and obesity among the adult 

population in Kabul city. This small study hypothesize 

that the country is entering in critical situation of NCDs 

while still no attention is given to them. Other research 

conducted in Angola and China found similar findings 

that older age, lower level of education, 

retirement/unemployment and higher body mass index 

were significantly associated with hypertension.
51-55

 It 

seems that the factors are mostly associated with each 

other and/or concurrently present in one individual at 

the same time. The interventions are needed to target a 

group of risk factors rather than just one or two factors. 

This study, despite of having limitations, has 

provided useful baseline information for policy 

development and design of interventions. Inclusion of 

upper age groups has limited the application of findings 

to population. In the present study, two thirds of 

participants were females, which are likely had an 

influence on the results for women because data were 

not weighted for age and sex to national population. The 

under representation of men in this age group was due 

to some being away from home at the time of the 

survey. However, the findings of our study illustrated 

for the first time the prevalence of main NCD risk 

factors in an urban setting of the country. The main 

limitation of the study was financial resources for 

covering cost, which might have affected the result of 

the study by not going door to door and randomly 

interviewing individuals or performing glucose 

tolerance test instead of testing fasting blood sugar. The 

technique used for recruiting the study participants 

could encourage participation of those with chronic 

diseases and leading to possible overestimated 

prevalence of chronic diseases including obesity. Not 

withstanding this study demonstrates the impact of non-

communicable diseases such as diabetes, blood 

pressure, and obesity on a population already 



 

 

CENTRAL ASIAN JOURNAL OF GLOBAL HEALTH 

 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program, and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

  

 

significantly burdened by communicable and 

preventable diseases.  

Research institutions and the MoPH to develop 

more rigorous research and national studies to assess the 

impact of non-communicable diseases in Afghanistan 

may use these findings. Suffering from non-

communicable diseases such as diabetes, high blood 

pressure, and obesity requires concerted interventions 

aimed toward prevention. The findings obtained from 

this study can contribute in formulation of more 

advanced and national studies to have a generalized 

picture of non-communicable diseases and their risk 

factors in the country. It also will assist policy makers to 

develop a strategy for appropriate control and 

prevention of non-communicable diseases in the Afghan 

urban population. 

 

Competing interests 

The author declares that they have no 

competing interests. 

 

Acknowledgement 

I would like to thank the Field Epidemiology 

Training Program (FELTP) Pakistan for contribution in 

concept and design of the study as well as FELTP 

Afghanistan and Ministry of Public Health for financial 

support of data collection. 

 

References 

1. United Nations. Resolution adopted by the General 

Assembly. 66/2: Political declaration of the high-level meeting 

of the general assembly on the prevention and control of non-

communicable diseases. In: United Nations, ed. New York; 

2012. 

2. World Health Organization. Prevention and control of 

non-communicable diseases. In: Organization WH, ed. 65th 

World Health Assembly. Geneva; 2012. 

3. Lozano R, Naghavi M, Foreman K, et al. Global and 

regional mortality from 235 causes of death for 20 age groups 

in 1990 and 2010: A systematic analysis for the Global Burden 

of Disease Study 2010. Lancet. 2012;380(9859):2095-2128. 

4. World Health Organization. The global burden of diseases 

- 2004 update. In: WHO, ed. Geneva; 2008. 

5. Murray CJ, Vos T, Lozano R, et al. Disability-adjusted life 

years (DALYs) for 291 diseases and injuries in 21 regions, 

1990-2010: A systematic analysis for the Global Burden of 

Disease Study 2010. Lancet. 2012;380(9859):2197-2223. 

6. World Health Organization. Global status report on non-

communicable diseases 2010. Geneva: World Health 

Organization;2011. 

7. Engelgau M, El-Saharty S, Kudesia P, Rajan V, 

Rosenhouse S, Okamoto K. Capitalizing on the demographic 

transition: Tackling noncommunicable diseases in South Asia. 

Washington, D.C.: World Bank; 2011. 

8. World Health Organization. The world health report 

2002: Reducing risk promoting healthy life. Geneva: World 

Health Organization;2002. 

9. Salehuddin M, Choudhury KN, Islami N, Zillurahman M, 

Gosh S, Majib M. Burden of non-communicable diseases in 

South Asia. University Heart Journal. 2010. 

10. Bhagyalaxmi A, Atul T, Shikha J. Prevalence of risk 

factors of non-communicable diseases in a district in Gujarat, 

India. J Health Popul Nutr. 2013;31(1):78-85. 

11. Kearney PM, Whelton M, Reynolds K, Muntner P, Whelton 

PK, He J. Global burden of hypertension: Analysis of worldwide 

data. Lancet. 2005;365(9455):217-223. 

12. Medscape Cardiology. Hypertension, but not 

"prehypertension," increases stroke risk: Global prevalence of 

hypertension may be close to 30%. 2004; 

http://www.medscape.com/viewarticle/471536_8  

13. World Health Organization. Non-communicable diseases: 

Hypertension. 2011; 

http://www.emro.who.int/ncd/hypertension.htm. 

14. Haghdoost AK, Behnam Sadeghirad B, 

Rezazadehkermani M. Epidemiology and heterogeneity of 

hypertension in Iran: A systematic review. Arch Iranian Med. 

2008;11(4):444-452. 

15. Safdar S, Omair A, Faisal U, Hasan H. Prevalence of 

hypertension in a low income settlement of Karachi, Pakistan. J 

Pak Med Assoc. 2004;54(10):506-509. 

16. International Diabetes Federation. International Diabetes 

Federation estimation. 2011. 

http://www.medscape.com/viewarticle/471536_8
http://www.emro.who.int/ncd/hypertension.htm


 

 

SAEED 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program, and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

 

 

17. Friedrich MJ. Epidemic of obesity expands its spread to 

developing countries. JAMA. 2002;287:1382-1386. 

18. Reddy KS, Yusuf S. Emerging epidemic of cardiovascular 

disease in developing countries. Circulation. 1998;97:596-601. 

19. Shera AS, Basti A, Fawwad A, et al. Pakistan National 

Diabetes Survey: Prevalence of glucose intolerance and 

associated factors in the Punjab province of Pakistan. Prim Care 

Diabetes. 2010;4(2):79-83. 

20. Esteghamati A, Meysamie A, Khalilzadeh O, et al. Third 

national Surveillance of Risk Factors of Non-Communicable 

Diseases (SuRFNCD-2007) in Iran: Methods and results on 

prevalence of diabetes, hypertension, obesity, central obesity, 

and dyslipidemia. BMC Public Health. 2009;9:167. 

21. Afghan Public Health Institute Ministry of Public Health 

(APHI/MoPH) [Afghanistan], Central Statistics Organization 

(CSO) [Afghanistan], ICF Macro IIoHMRII, [Egypt] 

WHOROftEMWE. Afghanistan Mortality Survey 2010. Maryland, 

USA: Calverton; 2011. 

22. World Health Organization. Prevalence of diabetes in the 

WHO Eastern Mediterranean Region. In: Programme D, ed. 

23. Shaw JE, Sicree RA, Zimmet PZ. Diabetes Atlas: Global 

estimates of the prevalence of diabetes for 2010 and 2030. 

Diabetes Res Clin Pract. 2010;87(1):4-14. 

24. Mohmand KA, Sharifi K, Bahram AA. Smoking prevalence 

survey in Kabul City. 2010 (in press). 

25. Sediqi A. A preliminary assessment of air quality in 

Kabul.  http://www.afghan-

web.com/environment/kabul_air_quality.pdf. 

26. Bonita R, deCourten M, Dwyer T, K. J, Winkelmann R. 

Surveillance of risk factors for non-communicable disease: the 

WHO STEPwise approach. Geneva: World Health 

Organization;2002. 

27. World Health Organization. STEPS country reports. 

28. World Health Organization. The STEPS Manual 2005. 

Geneva2005. 

29. Central Statistics Organization, Islamic Republic of 

Afghanistan , Population Statistics, Population Estimation 2012-

2013  

30. World Health Organization. Obesity: Preventing and 

managing the global epidemic; report of a WHO consultation. 

Geneva: World Health Organization;2000. 

31. International Diabetes Federation. The IDF consensus 

worldwide definitions of the metabolic symdrome. 2006; 

http://www.idf.org/webdata/docs/IDF_Meta_def_final.pdf. 

32. Whitworth JA, World Health Organization, International 

Society of Hypertension Writing Group. 2003 World Health 

Organization (WHO)/International Society of Hypertension 

(ISH) statement on management of hypertension. J Hypertens. 

2003;21(11):1983-1992. 

33. Federal Occupational Health. Hypertension and pre-

hypertension.  

http://www.foh.dhhs.gov/nycu/hypertension.asp. 

34. Rutledge T, Braden AL, Woods G, Herbst KL, Groesz LM, 

Savu M. Five-year changes in psychiatric treatment status and 

weight-related comorbidities following bariatric surgery in a 

veteran population. Obesity surgery. Nov 2012;22(11):1734-

1741. 

35. World Health Organization. Diabetes: Fact sheet #312. 

WHO media center. 2009. 

36. Epi Info [computer program]. Version 3.5.12008. 

37. IBM SPSS Statistics for Windows [computer program]. 

Version 20.0. Armonk, NY: IBM Corporation; 2011. 

38. Sandefur J. Here's the best thing the US has done in 

Afghanistan. The Atlantic. 2013; 

http://www.theatlantic.com/international/archive/2013/10/here

s-the-best-thing-the-us-has-done-in-afghanistan/280484/. 

39. Musaiger AO. Overweight and obesity in eastern 

mediterranean region: Prevalence and possible causes. J Obes. 

2011;2011:1-17. 

40. Yalcin BM, Sahin EM, Yalcin E. Prevalence and 

epidemiological risk factors of obesity in Turkey. MEJFM. 

2004;6(6). 

41. Musaiger AO, Al-Mannai MA. Weight, height, body mass 

index and prevalence of obesity among the adult population in 

Bahrain. Ann Hum Biol. 2001;28(3):346-350. 

42. Al-Nuaim AA, Bamgboye EA, al-Rubeaan KA, al-Mazrou 

Y. Overweight and obesity in Saudi Arabian adult population, 

role of socio-demographic variables. J Community Health. 

1997;22(3):211-223. 

43. Sibai AM, Hwalla N, Adra N, Rahal B. Prevalence of and 

covariates of obesity in Labanon: Finding from the first 

epidemiological study. Obes Res. 2003;11:1353-1361. 

44. Azadbakht L, Mirmiran P, Shiva N, Azizi F. General 

obesity and central adiposity in a representative sample of 

Tehranian adults: Prevalence and determinants. Int J Vitam 

Nutr Res. 2005;75(4):297-304. 

45. Gutiérrez-Fisac JL, Guallar-Castillón P, Díez-Gañán L, 

López García E, Banegas Banegas JR, Rodríguez Artalejo F. 

http://www.afghan-web.com/environment/kabul_air_quality.pdf
http://www.afghan-web.com/environment/kabul_air_quality.pdf
http://www.idf.org/webdata/docs/IDF_Meta_def_final.pdf
http://www.foh.dhhs.gov/nycu/hypertension.asp
http://www.theatlantic.com/international/archive/2013/10/heres-the-best-thing-the-us-has-done-in-afghanistan/280484/
http://www.theatlantic.com/international/archive/2013/10/heres-the-best-thing-the-us-has-done-in-afghanistan/280484/


 

 

CENTRAL ASIAN JOURNAL OF GLOBAL HEALTH 

 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program, and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

  

 

Work-related physical activity is not associated with body mass 

index and obesity. Obes Res. 2002;10(4):270-276. 

46. Lahti-Koski M, Pietinen P, Heliovaara M, Vartiainen E. 

Association of body mass index and obesity with physical 

activity, food choices, alcohol intake and smoking in the 1982-

1997. Am J Clin Nutr. 2002;75:809-817. 

47. Zafar J, Bhatti F, Akhtar N, et al. Prevalence and risk 

factors for diabetes mellitus in a selected urban population of a 

city in Punjab. J Pak Med Assoc. 2011;61(1):40-47. 

48. Ramachandran A. Urban India: A breeding ground for 

Diabetes. Diabetes Voice. 2002;47(1):18-20. 

49. Ning F, Pang ZC, Dong YH, et al. Risk factors associated 

with the dramatic increase in the prevalence of diabetes in the 

adult Chinese population in Qingdao, China. Diabet Med. 

2009;26(9):855-863. 

50. Sahraki MR, Mirshekari H, Sahraki AR, Mohammadi M, 

Sahraki E, Khazaei Feizabad A. Hypertension among 30+ year-

old people in Zahedan (Southeast of Iran). Shiraz E-Medical 

Journal. 2011;12(3). 

51. Khan RJ, Stewart CP, Christian P, et al. A cross-sectional 

study of the prevalence and risk factors for hypertension in 

rural Nepali women. BMC Public Health. 2013. 

52. Pires JE, Sebastião YV, Langa AJ, Nery SV. Hypertension 

in Northern Angola: Prevalence, associated factors, awareness, 

treatment and control. BMC Public Health. 2013;13(1):90. 

53. Sit JW, Sijian L, Wong EM, et al. Prevalence and risk 

factors associated with prehypertension: Identification of foci 

for primary prevention of hypertension. J Cardiovasc Nurs. 

2010;25(6):461-469. 

54. Meshram II, Arlappa N, Balkrishna N, Rao KM, Laxmaiah 

A, Brahmam GN. Prevalence of hypertension, its correlates and 

awareness among adult tribal population of Kerala state, India. 

J Postgrad Med. 2012;58(4):255-261. 

55. Ordinioha B. The prevalence of hypertension and its 

modifiable risk factors among lecturers of a medical school in 

Port Harcourt, south-south Nigeria: Implications for control 

effort. Niger J Clin Pract. 2013;16(1):1-4. 

56. Weiss HA, Quigley MA, Hayes RJ. Male circumcision and 

risk of HIV infection in sub-Saharan Africa: a systematic review 

and meta-analysis. AIDS (London, England). Oct 20 

2000;14(15):2361-2370. 

 

  



 

 

SAEED 

 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

  

 

Table 1: Frequency distribution of the background characteristics of study participants 

(N=1,169). 

VARIABLES CATEGORIES MALE (%) FEMALE (%) TOTAL (%) 

Age in years (missing values =17) 

  40 – 49  152 (22.2) 532 (77.8) 684 (58.5) 

  50 – 59 108 (45.6) 129 (54.4) 237 (20.3) 

  60 – 69 88 (55.7) 70 (44.3) 158 (13.7) 

  70 and over 39 (53.4) 34 (46.6) 73 (6.3) 

Level of education  

  Illiterate 138 (20.6) 531 (79.4) 669 (57.2) 

  Primary/Unofficial Education 59 (50.4) 58 (49.6) 17 (10.0) 

  Secondary School 116 (54.7) 96 (45.3) 212 (18.2) 

  High school and more 79 (46.2) 92 (53.8) 171 (14.6) 

Monthly income (Afghanis) (missing=181) 

  ≤ 10000 187 (36.1) 331 (63.9) 518 (52.4) 

  10000 - 20000 96 (33.0) 195 (67.0) 291 (29.5) 

  20000 – 30000 33 (41.8) 46 (58.2) 79 (8.0) 

  ≥ 30000 53 (53.0) 47 (47.0) 100 (10.1) 

Work Status 

  Government Employee 120 (46.7) 137 (53.3) 257 (22.0) 

  Business 52 (88.1) 7 (11.9) 59 (5.0) 

  Farmer/worker 52 (85.2) 9 (14.8) 61 (5.2) 

  Jobless 63 (13.5) 404 (86.5) 467 (39.9) 

  Unable to work 37 (94.9) 2 (5.1) 39 (3.3) 

  Housewife 68 (23.8) 218 (76.2) 286 (24.5) 

Smoking Status (missing=9) 

  Current Smoker 57 (96.6) 2 (3.4) 059 (05.1) 

  Ever Smoker 85 (89.5) 10 (10.5) 095 (08.2) 

  Never Smoker 246 (24.5) 760 (75.5) 1,006 (86.7) 

Mouth Snuff Use Status (missing =10) 



 

 

CENTRAL ASIAN JOURNAL OF GLOBAL HEALTH 

 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program, and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

  

 

  Current User 95 (90.5) 10 (9.5) 105 (9.0) 

  Ever User 23 (92.0) 2 (8.0) 25 (2.2) 

  Never User 271 (26.3) 758 (73.7) 1,029 (88.8) 

 



 

 

SAEED 

 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

  

 

Table 2: Frequency distribution of the Behavior factors evaluated (n=1,169). 

VARIABLES CATEGORIES MALE (%) FEMALE (%) TOTAL (%) 

Type of kitchen oil  

  Solid Oil 
56

 264 (32.6) 547 (67.4) 811 (69.4) 

  Solid Oil (no) 128 (35.8) 230 (64.2) 358 (30.6) 

  Liquid Oil 
56

 120 (35.8) 215 (64.2) 335 (28.7) 

  Liquid Oil (no) 272 (32.6)  562 (67.4) 834 (71.3) 

Frequency of eating red meat in a month (missing=8) 

  3 times per month 102 (33.7) 201 (66.3) 303 (26.1) 

  3-6 times/month 164 (28.2) 418 (71.8) 582 (50.1) 

  6-9 times/month 61 (38.1) 99 (61.9) 160 (13.8) 

Frequency of eating rice in a month (missing=88) 

  3 times per month 140 (26.3) 392 (73.7) 532 (49.2) 

  3-6 times/month 173 (40.6) 253 (59.4) 426 (39.4) 

  >6 times/month 56 (45.5) 67 (54.5) 123 (11.4) 

Frequency of taking vegetables per week  

  Once of a week 50 (21.2) 186 (78.8) 236 (20.2) 

  Twice a week 81 (28) 208 (72) 289 (24.7) 

  Thrice a week 61 (28) 102 (62.6) 163 (13.9) 

  More than 3 times a week 200 (41.6) 281 (58.4) 481 (41.1) 

Frequency of taking fruits per week  

  Once of a week 59 (33.5) 117 (66.5) 176 (15.1) 

  Twice a week 76 (28.7) 189 (71.3) 265 (22.7) 

  Thrice a week 77 (33.3) 154 (66.7) 231 (19.8) 

  More than 3 times a week 180 (36.2) 317 (63.8) 497 (42.5) 

Frequency of physical activity per day in minutes 



 

 

CENTRAL ASIAN JOURNAL OF GLOBAL HEALTH 

 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program, and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

  

 

  10 minutes per day 319 (31.6) 691 (68.4) 1,010 (86.4) 

  10-30 minutes/day 61 (46.6) 70 (53.4) 131 (11.2) 

  >30 minutes/day 12 (42.9) 16 (57.1) 28 (02.4) 

Frequency of sedentary lifestyle per week in hours 

  10 hours per week 100 (42.6) 135 (57.4) 236 (20.1) 

  10-30 hours/week 220 (27.4) 583 (72.6) 804 (68.7) 

  >30 hours/week 71 (55.0) 58 (45.0) 129 (11.0) 

Frequency of walking per week in hours (missing=7)  

  10 hours per week 133 (35.8) 238 (64.2) 371 (31.9) 

  10-30 hours/week 181 (29.2) 439 (70.8) 620 (53.4) 

  >30 hours/week 74 (43.3) 97 (56.7) 171 (14.7) 

 



 

 

SAEED 

 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

  

 

Table 3: Frequency distribution of pathophysiological risk factors for NCDs of study 

participants (N=1,169).  

Variables Categories Male (%) Female (%) Total (%) 

Basic Mass index (in kg/m square) 

  Underweight 6 (46.2) 7 (53.8) 13 (1.1) 

  Normal weight  144 (41.6) 202 (58.4) 346 (29.6) 

  Overweight 167 (37.5) 278 (62.5) 445 (38.1) 

  Obese 75 (20.5) 290 (79.5) 365 (31.2) 

Central Obesity (missing=14) 

  Yes 234 (48.9) 245 (51.1) 479 (41.0) 

  No 155 (22.9) 521 (77.1) 676 (57.8) 

Blood Pressure 

  Normotensive 181 (31.9) 386 (68.1) 567 (48.5) 

  Pre-hypertensive 105 (49.1) 109 (50.9) 214 (18.3) 

  Hypertensive 106 (27.3) 282 (72.7) 388 (33.2) 

Diabetes Mellitus 

  No 329 (32.5) 684 (67.5) 1,013 (86.7) 

  Yes 63 (40.4) 93 (59.6) 156 (13.3) 

Diabetes Mellitus and Obesity 

  Both Factors 18 (29.5) 43 (70.5) 61 (5.2) 

  One Factors 102 (25.6) 297 (74.4) 399 (34.1) 

  No Factors 272 (38.4) 437 (61.6) 709 (60.7) 

Diabetes Mellitus and Hypertension 

  Both Factors 36 (39.6) 55 (60.4) 91 (7.8) 

  One Factors 168 (32.8) 344 (67.2) 512 (43.8) 

  No Factors 188 (33.2) 378 (66.8) 566 (48.4) 

Hypertension and Obesity 

  Both Factors 36 (16.8) 178 (83.2) 214 (18.3) 

  One Factors 180 (37.9) 295 (62.1) 475 (40.6) 



 

 

CENTRAL ASIAN JOURNAL OF GLOBAL HEALTH 

 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program, and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

  

 

  No Factors 176 (36.7) 304 (63.3) 480 (41.1) 

Hypertension, Obesity and Diabetes Mellitus 

  All 3 Factors 10 (23.8) 32 (76.2) 42 (3.6) 

  One or 2 Factors 225 (32.5) 468 (67.5) 693 (59.3) 

  No Factors 157 (36.2) 277 (63.8) 434 (37.1) 

 



 

 

SAEED 

 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

  

 

Table 4: Multivariate analysis risk factors associated with obesity, hypertension, and diabetes mellitus.  

    OBESITY DIABETES MELLITUS HYPERTENSION 

Variables  AOR (95% CI) p-value A OR (95% CI) p-value AOR (95% CI) p-value 

Age group  

  <50 years 1 Reference - 1 Reference - 1 Reference - 

  >50 years 1.86 1.29 - 2.66 <0.01 2.09 1.32 - 3.31 <0.01 4.10 2.97 - 5.65 <0.001 

Sex  

  Male 1 Reference - 1 Reference - 1 Reference - 

  Female 1.65 1.08 - 2.52 <0.01 0.88 0.52 - 1.47 >0.05 0.93 0.63 - 1.35 >0.05 

Education Level 

  Literate 1 Reference - 1 Reference - 1 Reference - 

  Illiterate 1.24 0.86 - 1.80 >0.05 0.55 0.34 - 0.88 <0.01 1.35 0.97 - 1.88 >0.05 

Diabetes Mellitus 

  No 1 Reference - - - - 1 Reference - 

  Yes 1.66 1.04 - 2.65 <0.05 - - - 1.19 0.76 - 1.86 >0.05 

Blood Pressure 

  No 1 Reference - 1 Reference - - - - 

  Yes 2.08 1.49 - 2.90 <0.05 0.82 0.52 - 1.28 >0.05 - - - 

Obesity ( BMI>30) 



 

 

CENTRAL ASIAN JOURNAL OF GLOBAL HEALTH 

 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program, and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

  

 

  No - - - 1 Reference - 1 Reference - 

  Yes - - - 1.64 1.02 - 2.63 >0.05 2.16 1.55 - 3.01 <0.001 

Central Obesity  

  No 1 Reference - 1 Reference - 1 Reference - 

  Yes 5.45 3.76 - 7.89 <0.001 1.18 0.73 - 1.88 >0.05 1.72 1.25 - 2.36 <0.001 

Walking habit per week  

  >30 hours 1 Reference - 1 Reference - 1 Reference - 

  <30 hours 0.81 1.10 - 2.99 <0.05 1.37 0.70 - 2.70 >0.05 1.33 0.86 - 2.04 >0.05 

Sitting 10 hours per week  

  <10 hours 1 Reference - 1 Reference - 1 Reference - 

  >10 hours 1.12 0.74 - 1.70 >0.05 3.52 1.78 - 6.96 <0.001 1.13 0.86 - 2.04 >0.05 

Mode of transportation (using car for going to work) 

  No 1 Reference - 1 Reference - 1 Reference - 

  Yes 0.86 0.42 - 1.76 >0.05 2.16 1.04 - 4.48 <0.01 1.17 0.59 - 2.28 >0.05 

Using Chicken as meal  

  <3 times per month 1 Reference - 1 Reference - 1 Reference - 

  >3 times per month 0.62 0.46 - 0.88 <0.01 0.80 0.52 - 1.22 >0.05 1.36 1.01 - 1.83 <0.05 

Using Liquid Ghee in Kitchen 

  No 1 Reference - 1 Reference - 1 Reference - 

  Yes 1.08 0.75 - 1.56 >0.05 0.35 0.22 - 0.54 <0.001 1.04 0.74 - 1.45 >0.05 

Red meat 3 times per month 



 

 

SAEED 

 

This work is licensed under a Creative Commons Attribution 3.0 United States License. 

 

This journal is published by the University Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program, and is cosponsored by the University of Pittsburgh Press. 

 

Central Asian Journal of Global Health 

Volume 2, No. 2 (2013)  |  ISSN 2166-7403 (online)  |  DOI 10.5195/cajgh.2013.69  |  http://cajgh.pitt.edu 

 

 

  <3 times per month 1 Reference - 1 Reference - 1 Reference - 

  >3 times per month 1.04 0.72 - 1.50 >0.05 1.81 1.14 - 2.87 <0.05 1.05 0.75 - 1.45 >0.05 

Rice 3 times per week 

  <3 times per week 1 Reference - 1 Reference - 1 Reference - 

  >3 times per week 0.85 0.65 - 1.19 >0.05 2.30 1.48 - 3.58 <0.001 1.43 1.06 - 1.93 <0.05 

Fruits twice a week 

  <twice a week 1 Reference - 1 Reference - 1 Reference - 

  >twice a week 0.92 0.65 - 1.30 >0.05 0.62 0.38 - 1.02 >0.05 1.43 1.03 - 1.96 <0.05 

Vegetable once a week 

  <once a week 1 Reference - 1 Reference - 1 Reference - 

  >once a week 0.95 0.62 - 1.44 >0.05 0.85 0.45 - 1.56 >0.05 1.28 0.87 - 1.88 >0.05 

Smoking status 

  No 1 Reference - 1 Reference - 1 Reference - 

  Yes 1.66 1.04 - 2.65 <0.05 2.32 0.97 - 5.50 >0.05 1.13 0.55 - 2.33 >0.05 

 


