DIABETICMedicine DOI: 10.1111/dme.12386
Research: Epidemiology Cardiovascular disease risk factors in the South Asian population living in Kuwait: a cross-sectional study N. Elkum, M. Al-Arouj, M. Sharifi, K. Behbehani and A. Bennakhi Dasman Diabetes Institute, Kuwait City, Kuwait Accepted 22 October 2013
Abstract High rates of diabetes and cardiovascular disease have been reported in South Asian immigrants in many countries. However, the prevalence and characteristics of cardiovascular disease risk factors among a South Asian population living in Kuwait have not yet been investigated. This study was therefore designed to estimate the prevalence of cardiovascular disease risk factors and determine whether they are independently associated with diabetes in such a population.
Background
Methods A population-based cross-sectional study was conducted on 1094 South Asians (781 men and 313 women), mainly Indian and Pakistani (≥ 18 years of age), of whom 75.1% were Indians. Interviews were carried out, during which socio-demographic and anthropometric data were collected, followed by a physical examination and collection of fasting blood samples for laboratory investigations. Diabetes was defined by fasting plasma glucose ≥ 7 mmol/l, or being on treatment, and/or self-reported previously diagnosed Type 2 diabetes.
The prevalence of diabetes was 21.1%, with 3.4% of that percentage of people being newly diagnosed. Using BMI measurements, 24.0% of those who participated in the study were obese and 46.1% were overweight. Dyslipidaemia was found in 77.6% and hypertension in 44.8%. Advancing age (≥ 40 years), male gender, high LDL, high total cholesterol, hypertension and positive family history of diabetes were significantly associated with increased risk of diabetes.
Results
Our study shows that the prevalence of cardiovascular disease risk factors in South Asian expatriates in Kuwait exceeds prevalence rates reported in their homeland and other countries. This may suggest the added stress of environmental factors on the development of cardiovascular disease risk factors in such populations. Specialized prevention programmes targeting such high-risk ethnic populations are paramount and need to be implemented.
Conclusion
Diabet. Med. 31, 531–539 (2014)
Introduction The State of Kuwait is a small, oil-producing country of 17 820 km2, which has experienced rapid economic growth and socio-demographic and epidemiological transitions over the past six decades. This economic boom attracted many expatriates to come for work in Kuwait. According to the 2011 consensus, expatriates form 67% (2 514 107) of the population of Kuwait, with an average population growth rate of 6.7% annually. The vast majority of the expatriates come from South Asian countries, mainly from India and Pakistan, and constitute 44% (1 106 207) of the total expatriate population.
Correspondence to: Naser Elkum. E-mail: [email protected]
ª 2013 The Authors. Diabetic Medicine ª 2013 Diabetes UK
The International Diabetes Federation (IDF) Atlas ranked Kuwait as having the sixth-highest prevalence of Type 2 diabetes mellitus worldwide, with a prevalence of 23.9% (http://www.idf.org/diabetes-atlas-2012-update-out-now) [1]. Health services in Kuwait are provided free of charge for nationals and for a minimal fee of one Kuwaiti dinar ($US3.5) for expatriates to cover the cost of diagnosis, laboratory investigations and medications. Providing health care for this population presents a huge financial burden and challenge for the health authorities of the country. The prevalence of Type 2 diabetes and related cardiovascular disease risk factors varies among different ethnicities [2,3]. Amongst all the ethnic groups, South Asian immigrants in North America and Europe have an increased prevalence of Type 2 diabetes mellitus and cardiovascular disease risk factors [4,5]. Moreover, the prevalence of Type 2 diabetes
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Cardiovascular risk factors among South Asian emigrants in Kuwait N. Elkum et al.
What’s new?
Enrolment and interview procedures
• This study investigated, for the first time, the prevalence of cardiovascular disease risk factors and identified independent factors associated with Type 2 diabetes in a South Asian population residing in Kuwait.
All those willing to participate were invited to come to the study site at Dasman Diabetes Institute after a minimum of a 10-h overnight fast. Interviewers explained the study once more to those who had agreed to take part and obtained their signed consent; blood samples were then collected and interviews were conducted after serving a light breakfast. Each person was interviewed privately by interviewers speaking their language. The study was approved by the Scientific Advisory Council and Ethical Review Committee at Dasman Diabetes Institute. Informed written consent was obtained from those who had agreed to participate before their enrolment in the study.
• This study shows a high prevalence of diabetes and cardiovascular disease risk factors among South Asians, with rates that even exceed those reported in similar populations in Europe, North America, and in their homeland. and cardiovascular disease risk factors in expatriates living in these countries exceeded the prevalence in their homelands [6,7]. The most important risk factors associated with cardiovascular disease are Type 2 diabetes mellitus, hypercholesterolaemia, hypertension, obesity, smoking and sedentary lifestyle [8]. To date, prevalence and characteristics of a wide range of cardiovascular disease risk factors in the South Asian population in Kuwait and other Gulf countries has not been investigated. The main objectives of this study were therefore to estimate, for the first time, the prevalence of cardiovascular disease risk factors and to identify independent factors associated with Type 2 diabetes in a South Asian population residing in Kuwait.
Subjects and methods A cross-sectional population-based survey was conducted with a random representative sample of adults (≥ 18 years) of multi-ethnic origin across the six governorates (strata) of the State of Kuwait. A simple random sample was selected from each stratum with proportional allocation. For each stratum, a population frame included expatriates of both genders. A stratified random sampling technique was used for the selection of people from the computerized register of the Public Authority of Civil Information. The total study sample comprised 4077 non-Kuwaiti men and women, randomly selected across the six strata; out of the total study population invited for participation, 3460 (40.2% women) agreed to participate in the study. This article presents the data of 1094 people from India and Pakistan. This survey was carried out between June 2011 and August 2012. The study team consisted of trained supervisors, nurses, callers, interviewers and phlebotomists. Recruitment was through a telephone call in which details of the study were explained and, if the response was positive, appointments for a study visit were booked. Face-to-face interviews were then carried out by multilingual staff. Meticulous care was taken to protect the privacy and confidentiality of those who took part in the survey.
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Anthropometric and physical measurements
Physical and anthropometric measurements included, body weight, height, waist circumference and blood pressure. Blood pressure was measured using an Omron HEM-907XL digital sphygmomanometer (Omron Healthcare, Inc., Vernon Hills, IL, USA). An average of three blood pressure readings, with 5- to 10-min rest between each, was noted. Height and weight were measured, with subjects wearing light indoor clothing and with bare feet, using calibrated portable electronic weighing scales and portable inflexible bars to measure height. Waist circumference was measured using a constant tension tape at the end of a normal expiration, with arms relaxed at the sides, at the highest point of the iliac crest at the mid-axillary line. BMI was calculated using the standard formula of body weight in kilograms divided by height in metres squared.
Laboratory measurements
Blood samples were obtained after an overnight fast of at least 10 h and were analysed for fasting glucose, HbA1c, insulin levels and lipid profiles that included triglycerides, total cholesterol, LDL and HDL. Glucose and lipid profiles were measured on the Siemens Dimension RXL chemistry analyser (Diamond Diagnostics, Holliston, MA, USA). HbA1c was determined using the Variant device (Bio-Rad Laboratories, Hercules, CA, USA). All laboratory tests were performed by certified technicians at the clinical laboratories of the Dasman Diabetes Institute, using the Ministry of Health approved methods and quality standards.
Definitions used
The current recommendations and updated guidelines for the definition, diagnosis and classification of Type 2 diabetes, published by the International Diabetes Federation, have been used. Diabetes was defined by fasting plasma glucose ≥ 7 mmol/l, being under treatment, or self-reported previously diagnosed Type 2 diabetes [9]. Impaired fasting
ª 2013 The Authors. Diabetic Medicine ª 2013 Diabetes UK
Research article
glucose was defined by fasting blood glucose values ≥ 5.6 and < 7 mmol/l. Hypertension was defined as blood pressure ≥ 140/90 mmHg, being under treatment, or a self-report of previously diagnosed hypertension [10]. High LDL cholesterol was defined as > 4.1 mmol/l, hypertriglyceridaemia as ≥ 1.7 mmol/l and low HDL cholesterol as < 1.03 mmol/l in men and < 1.29 mmol/l in women [11]. High total cholesterol was defined as > 5.2 mmol/l. Obesity was assessed by using BMI standard criteria: BMI between 18.5 and 24.9 kg/ m2 was considered normal, 25–29.9 kg/m2 overweight and ≥ 30 kg/m2 obese. According to the International Diabetes Federation, abdominal obesity was defined as waist circumference ≥ 90 cm in men and ≥ 80 cm in women [12]. Subjects were asked about different types of physical activity in a typical week, with the level of physical activity rated as ‘sedentary’, ‘moderate’ or ‘vigorous’. Moderate physical activity was deemed to be if subjects engaged in physical efforts that cause light sweating or a slight increase in breathing or heart rate, examples of which included brisk walking, painting houses, gardening and climbing stairs. A harder physical effort that causes heavy sweating or a greater increase in breathing or heart rate was considered vigorous. Examples of this would be carrying a heavy load, construction, digging, running and strenuous sports. Subjects were considered to have a sedentary lifestyle if they did not engage in physical activity or exercise other than regular household work most days. People reporting no vigorous or moderate activity per week were considered physically inactive.
Statistical analysis
Those participating in the study were classified, based on fasting blood glucose levels, into those without Type 2 diabetes, those with impaired fasting glucose and those with Type 2 diabetes. Demographic characteristics are presented against health status using means standard deviation, or as numbers and percentages, as appropriate. Differences between groups of continuous independent variables were analysed using the Student t-test. Differences in the prevalence of individual conditions were compared using the v2-test. Logistic regression analysis was performed to estimate odds ratios and to examine the predictive effect of each factor on risk for Type 2 diabetes. Research Electronic Data Capture was used for data collections and data management. All statistical assessments were two-sided and considered to be significant when the P-value was < 0.05. Data analysis was carried out using SAS version 9.2 (SAS Institute, Cary, NC, USA).
Results Population characteristics
Of the 1355 South Asians who were approached, 1094 (Indians and Pakistanis) were screened; 19% refused to
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participate. Indians comprised 75.1% (822) of the group and Pakistanis 24.9% (272). The majority were men 781 (71.3%). The mean age of the survey population was 42.8 10.1 years, whereas the mean age of those who took part was 42.6 9.6 years (42.7 9.7 years for men and 42.3 9.5 years for women). The socio-demographics of the group studied are shown in Table 1. Compared with Pakistanis, Indians attained a better level of education (P = 0.0002) and were more active (P = 0.0003). The subjects from Pakistan had greater mean BMI (29.3 vs. 26.9 kg/m2; P < 0.0001), waist circumference (98.3 vs. 92.2 cm; P < 0.0001) and a higher mean level of triglycerides (1.86 vs. 1.55 mmol/l; P = 0.0031). Prevalence of cardiovascular disease risk factors
The mean BMI was 27.5 4.7 kg/m2. Twenty-four per cent of the group were obese and 46.1% were overweight. Using the International Diabetes Federation Asian criteria for waist circumference, the results showed that 73.3% had abdominal obesity. Obesity (BMI ≥ 30 kg/m2) was more prominent in Pakistanis (36.4 vs. 19.9%; P < 0.0001). There was a high frequency of hypertension (44.8%), increased total cholesterol (55.7%), low HDL (43.3%), high LDL (23.4%) and high triglycerides (18.9%). A high prevalence of family history of Type 2 diabetes (54.1%) was also observed. Twenty-eight per cent were smokers. Women had significantly higher mean levels of total cholesterol and BMI, while men had higher mean levels of systolic/diastolic blood pressure, fasting blood glucose and triglycerides. There was an increase in the prevalence of general and central obesity, hypertension, Type 2 diabetes, hypercholesterolaemia and high LDL with increasing age (Table 2). In addition, the highest rates of cardiovascular disease risk factors were observed among those with abdominal obesity compared with those who had normal waist circumference (results not reported).
Prevalence of impaired fasting glucose and Type 2 diabetes
The median fasting blood glucose level was 5.2 mmol/l. Impaired fasting glucose was present in 16.6% of the people and was more common in men than women (18.4% vs. 12.1%). Type 2 diabetes was identified in 231 people (21.1%). The prevalence of newly diagnosed Type 2 diabetes was 3.4%, whereas 17.7% of those who participated were known to have diabetes. Of the total known to have diabetes, 89.2% were on medication. The prevalence of Type 2 diabetes increased with age: in those aged 20–29 years, the prevalence was 7.5%, at age 40–59 years 28.9% and in those ≥ 60 years the prevalence was 44.2% (P < 0.0001). The prevalence of Type 2 diabetes was higher in men compared with women (24.2% vs. 13.4%; P < 0.0001). The prevalence of Type 2 diabetes increased significantly with increasing BMI: 16.8% for those of normal weight,
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Table 1 Clinical and socio-demographic characteristics of a South Asian population
Characteristics Age, years Gender Men Women BMI (kg/m2) Waist circumference (cm) Family history of diabetes Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Fasting blood glucose* (mmol/l) HbA1c, IFCC (mmol/mol) DCCT, % Total cholesterol (mmol/l) Triglyceride (mmol/l) HDL cholesterol (mmol/l) LDL cholesterol (mmol/l) Physical activity† Inactive (%) Education, % Illiterate—no schooling 1–12 years > 12 years Smoking‡,% Smoker Non-smoker Income§, % ≤ Kuwaiti dinar 500 > Kuwaiti dinar 500
All (n = 1094) mean SD 42.6 9.6
Indians (n = 822) mean sd 42.6 9.8
782 (71.3) 315 (28.7) 27.5 4.7 93.7 10.7 555 (54.1) 133.6 18.9 82.7 24.1 5.3 2.0
72.14 27.86 26.9 92.2 54.9 133.6 82.4 5.2
45 6.2 1.4 5.2 1.1 1.63 1.2 1.1 0.27 3.5 2.3
Pakistanis (n = 272) mean SD
P-values
42.6 8.9 69.12 30.88 29.3 98.3 51.4 133.5 83.8 5.3
4.3 9.7 18.8 12.0 1.98
44 6.18 1.4 5.2 1.06 1.55 0.97 1.08 0.27 3.55 2.57
46 6.35 5.18 1.86 1.03 3.35
663 (60.6)
57.5
69.9
8 (0.73) 491 (44.8) 598 (54.5)
0.36 41.97 57.66
1.84 52.94 45.22
303 (28.1) 777 (71.9)
27.8 72.2
28.7 71.3
556 (61.1) 355 (38.9)
60.43 39.57
63.08 36.92
5.3 12.2 19.3 43.7 2.09
0.9268 0.3389 < 0.0001 < 0.0001 0.3377 < 0.9841 0.6055 0.3064 0.0838
1.4 1.0 1.56 0.27 0.84
0.6691 0.0031 0.0047 0.0598 0.0003 0.0002
0.7764
0.4866
Data are means SD unless noted otherwise (*medians SD). A person was considered to be inactive if they did not engage in sufficient physical activity or exercise other than regular household work on most days. † A person was considered to be a smoker if they were currently smoking or were an ex-smoker, and a non-smoker if they had never smoked. § A person’s average monthly household income for the last 12 months (1 Kuwaiti dinar = $US3.5). DCCT, Diabetes Control and Complications Trial; IFCC, International Federation of Clinical Chemistry and Laboratory Medicine. †
Table 2 Prevalence of various cardiovascular risk factors in different age groups Age groups, years Risk factors BMI, kg/m2 Normal (18.5–24.9) Overweight (25–29.9) Obese (≥ 30) Central obesity* Hypertension† Diabetes‡ Hypercholesterolaemia (> 5.2 mmol/l) Hypertriglyceridaemia (≥ 1.7 mmol/l) Low HDL < 1.03 mmol/l in men < 1.29 mmol/l in women High LDL (> 4.1 mmol/l)
20–39 (n = 438)
40–59 (n = 604)
≥ 60 (n = 52)
163 185 90 274 135 33 192 69
154 290 160 484 312 175 372 136
10 29 13 44 43 23 45 2
P-value for trend 0.0004
(37.2) (42.2) (20.6) (62.6) (30.8) (7.5) (43.8) (15.8)
(25.5) (48.0) (26.5) (80.1) (51.7) (28.9) (61.6) (22.5)
(19.2) (55.8) (25.0) (84.6) (82.7) (44.2) (86.5) (3.9)
198 (45.2)
270 (44.7)
6 (11.5)
91 (20.8)
147 (24.3)
18 (34.6)
< < <
5.2 mmol/l) Hypertriglyceridaemia (≥ 1.7 mmol/l) High LDL (> 4.1 mmol/l) Low HDL (< 1.03 mmol/l) Women General obesity, ≥ 30 kg/m2 Central obesity, waist circumference ≥ 80 cm Hypertension† Hypercholesterolaemia (> 5.2 mmol/l) Hypertriglyceridaemia (≥ 1.7 mmol/l) High LDL (> 4.1 mmol/l) Low HDL (< 1.29 mmol/l) All General obesity Central obesity Hypertension† Hypercholesterolaemia Hypertriglyceridaemia High LDL Low HDL
Without diabetes, % n = 682
Impaired fasting glucose, % n = 181
Diabetes* n = 231
P-value
12.1
29.2
29.6
< 0.0001
58.3
76.4
76.2
< 0.0001
39.3 51.6
63.2 62.5
64.0 70.9
< 0.0001 < 0.0001
17.6
34.0
28.0
< 0.0001
25.2
27.1
20.6
0.3372
48.4
55.6
50.3
0.3314
34.8 88.8
44.7 100.0
30.9 100.0
0.0070 0.0077
22.8 44.6
57.9 57.9
64.3 66.7
< 0.0001 0.0164
5.6
10.5
21.4
0.0025
20.6
23.7
19.1
0.8711
25.3
34.2
23.8
0.4775
19.8 68.7 33.6 49.2 13.5 23.6 40.5
32.4 81.3 62.1 61.5 29.1 26.4 51.1
29.9 80.5 64.1 70.1 26.8 20.4 45.5
< < < <
12 years 1–12 years Illiterate—no schooling Smoking Non-smoker Smoker Income, Kuwaiti dinar ≤ 500 > 500 Physical activity Active Inactive Hypercholesterolaemia No Yes (> 5.2 mmol/l) High LDL† No Yes (> 4.1 mmol/l) Low HDL No Yes (< 1.29 mmol/l) Hypertriglyceridaemia No Yes (≥ 1.7 mmol/l)
Multivariate‡
Prevalence,%
Odds ratio (95% CI)
7.5 28.9 44.2
1 5.0 (3.37–7.44) 9.7 (5.07–18.7)
1 3.7 (2.3–5.8) 6.5 (2.8–15.3)
21.2 21.0
1 1.0 (0.72–1.42)
1 0.9 (0.58–1.41)
13.4 24.2
1 2.1 (1.43–2.96)
1 2.5 (1.5–4.2)
15.9 26.9
1 1.9 (1.43–2.65)
1 2.5 (1.7–3.7)
13.7 30.2
1 2.7 (2.01–3.67)
1 1.6 (1.1–2.4)
16.8 21.2 26.2
1 1.3 (0.93–1.91) 1.8 (1.18–2.62)
1 1.1 (0.7–1.7) 1.6 (1.0–2.7)
17.4 25.6 25.0
0.63 (0.13–3.18) 1.03 (0.21–5.17) 1
1 1.6 (1.1–2.5) 0.83 (0.1–10.9)
23.8 20.2
1 1.2 (0.89–1.69)
1 1.3 (0.8–1.9)
19.3 24.0
1 1.3 (0.96–1.83)
1 0.9 (0.6–1.4)
20.7 21.4
1 1.1 (0.78–1.41)
1 1.3 (0.9–1.9)
14.2 26.6
1 2.2 (1.60–2.98)
1 1.9 (1.3–2.9)
21.9 18.4
1 0.79 (0.56–1.14)
1 2.2 (1.4–3.5)
20.3 22.2
1 1.1 (0.833–1.49)
1 0.9 (0.7–1.5)
19.1 29.9
1 1.8 (1.29–2.56)
1 1.0 (0.6–1.6)
P-value < 0.0001
0.6582
0.0009
< 0.0001
0.0121
0.1277
0.0558
0.2455
0.5950
0.2022
0.0032
0.0012
0.9587
0.9979
*Hypertension was defined as blood pressure ≥ 140/90 mmHg, being under treatment or self-report of previously diagnosed hypertension. LDL was defined as < 1.03 mmol/l in men and < 1.29 mmol/l in women. ‡ For multivariate analyses, values were adjusted for age, gender, BMI, nationality, family history of diabetes, blood pressure, total cholesterol, LDL, HDL, triglycerides, smoking, education and physical activity. †
Type 2 diabetes; individuals with hypertension were 60% more likely to be at risk of Type 2 diabetes. Likewise, individuals with high total cholesterol level or with a high level of LDL were twice as likely to be at risk of Type 2 diabetes.
Discussion This study reports for the first time a high prevalence of Type 2 diabetes and cardiovascular disease risk factors among South Asians living in Kuwait. Our data show that
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the rates exceed those reported in similar populations in Europe, North America and their homeland. Moreover, people from Pakistan appear to have a higher prevalence of such risk factors compared with those from India. These data add further evidence to the role of environmental factors in exacerbating Type 2 diabetes and cardiovascular disease. The reported rates of impaired fasting glucose and Type 2 diabetes mellitus in South Asian expatriates in Kuwait exceeded the prevalence in their homeland [13–16], whereas the prevalence of Type 2 diabetes among South Asians living in the UK, the USA and Canada has been found to be as high
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Research article
as 12–15% [17–19], which is less than the prevalence reported in our study. Older age, being male, having a positive family history of Type 2 diabetes, having hypertension, high total cholesterol and high LDL significantly contributed to increased Type 2 diabetes risk among South Asians in Kuwait. The higher prevalence of cardiovascular risk factors in younger age in the studied population is of particular concern. Our results showed that the prevalence of various cardiovascular risk factors increased more rapidly in the 20- to 39-year age group than at age 60 years (Table 2). We also found that the prevalence of Type 2 diabetes increases with age and the highest proportion of diabetes cases (44.2%) was detected in the ≥ 60-year age group. Similar trends were reported by other studies for South Asians populations [3,14,18,20]. Compared with the < 40-year-old age group, Type 2 diabetes was almost seven times more common among those above 60 years of age. Therefore, the focus of prevention should be at people younger than 20–39 years of age. Our data illustrate that family history of diabetes is an independent predictor of Type 2 diabetes; this observation is in agreement with the findings in another study of a South Asian population [21]. Participants with a family history of diabetes were 2.5 times more likely to develop Type 2 diabetes (odds ratio 2.4, P < 0.0001); this may suggest potential genetic and environmental influences that predispose South Asians to Type 2 diabetes. In the USA, China and Kuwait, family history of diabetes was shown to be significantly associated with the risk of Type 2 diabetes, thus highlighting the importance of gene–environment interaction to the onset of this disease. Our findings are consistent with the findings reported from other populations [22–24]. Dyslipidaemia was common among those who took part in the study, with total dyslipaemia reaching 77.1%. Similar findings were reported from other studies across South Asia [3,15]. This study shows that high total blood cholesterol level and high LDL are the main phenotypic features of dyslipidaemia in Type 2 diabetes and were significant risk factors for developing diabetes mellitus in South Asians populations. This is in agreement with findings from other South Asian studies in India and Pakistan [14,25] and abroad [26], as well as in other Asian populations [27]. A high prevalence of dyslipidaemia justifies the importance of an early screening of lipid disorders in migrant/expatriate South Asians at the primary healthcare level. Using BMI, 70.1% were either overweight or obese. However, BMI has been shown to underestimate adiposity in South Asians, whereas waist circumference may give a more reliable estimate [28]. Using waist circumference as a measure, central obesity was present in 73.3% of those in the study. This high prevalence of central obesity could indicate a predisposition for the South Asian population to deposit abdominal fat. The prevalence of various risk factors increases with central obesity. Obesity is significantly associated with Type 2 diabetes in univariate analysis, but failed
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to reach statistical significance in multivariate analysis; a similar observation was reported in other Asian Indians [20]. Studies showed that South Asian immigrants exhibit greater central adiposity than Caucasian Europeans [29]. Ethnic-specific BMI and waist circumference cut-off points should be used for risk stratification. The prevalence of hypertension was 44.3%, of which 30.2% was people with Type 2 diabetes. People in the study with hypertension showed a 62% increased risk of developing Type 2 diabetes compared with those without hypertension (odds ratio 1.62). A similar association was reported by other studies from homeland countries and abroad [19,30]. The significant link between hypertension and Type 2 diabetes suggests the need for a common reliable strategy to manage these conditions. It is striking to show that rates of cardiovascular disease risk factors in South Asian expatriates in Kuwait exceeded the prevalence rates reported in their homeland, Europe and the USA. Even although a clear explanation is lacking, it can be postulated that a myriad of factors might be involved. Possible factors that pertain to Kuwait, such as hot weather and epigenetic factors, may play a role. Lifestyle features may be an important determinant in the increased risk of Type 2 diabetes amongst South Asians. Although this supposes to be working population, the rate of physical inactivity was 60.6%. This may reflect the lifestyle in Kuwait where the very hot weather limited the chance of physical activity, and private transportation is widely affordable. However, we did not find an independent relationship between diabetes and physical inactivity. The link between physical activity and the prevalence of diabetes could be confounded by other risk factors, such as abdominal obesity. Promoting lifestyle modification could be important in reducing the impact of these modifiable risk factors. The Indian Diabetes Prevention Program (IDPP-1) demonstrated a relative risk reduction of 28.5% with lifestyle intervention in Asian Indians with impaired glucose tolerance [6]. Smoking is a well-established cause of cancer, lung disease, coronary heart disease and stroke. However, our study did not demonstrate an independent relationship between diabetes and smoking. Finally, it is very well documented that this interaction between the environment and the genetic make-up of the human body—termed epigenetic—is complicated and not very well understood. Epigenetics can influence human genes as a result of environmental interaction by adding chemical marks to genes or proteins that persist over generations [31]. This phenomenon means that the environment can imprint its signature on the human body and transfer this knowledge to the next generation. Keeping this in mind, it is possible to postulate that there might be other factors playing on the epigenetics of this group, leading to increasing their risk of cardiovascular disease and Type 2 diabetes. It will be of great scientific value to understand these factors in the future and potentially find methods that can reverse the risk.
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As with any other population study, our survey also had limitations with regard to study design. The cross-sectional design used in this study makes it impossible to determine any temporal relationship between prevalence of diabetes and possible aetiological factors associated with diabetes. A further study is currently underway to prospectively follow up this cohort to determine causality and directional effect of the causes. Further, the diagnosis of diabetes was not confirmed by a 2-h postprandial blood glucose measurement, meaning that prevalence of Type 2 diabetes may have been underestimated.
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5
6
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Conclusion Our reported rates of cardiovascular disease risk factors in South Asian expatriates in Kuwait exceeded the prevalence rates reported in their homeland, Europe and the USA. This might suggest the role of environmental factors on the development of cardiovascular disease risk factors in such a population. Specialized prevention programmes targeting such high-risk ethnic populations are paramount and need to be implemented.
Funding sources
8
9 10
11
This study was supported by the Kuwait Foundation for the Advancement of Sciences (KFAS). 12
Competing interests
13
None declared.
Acknowledgments
14
We would like to thank our study team for their efforts and excellent work. We are grateful to the Clinical Laboratory and the Tissue Bank Core Facility at the Dasman Diabetes Institute for their contribution in performing the biochemical profile analysis and handling samples, respectively. We would also thank Dr Jawad Al-Lawati from the Oman Ministry of Health for his critical review of the manuscript and helpful comments. We are also indebted to the Kuwait Foundation for the Advancement of Sciences (KFAS) for financial support of this research project (RA-2010-004).
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References 1 International Diabetes Federation. IDF Diabetes Atlas, 5th ed. Brussels: IDF, 2012. 2 Ajjan R, Carter AM, Somani R, Kain K, Grant PJ. Ethnic differences in cardiovascular risk factors in healthy Caucasian and South Asian individuals with the metabolic syndrome. J Thromb Haemost 2007; 5: 754–760. 3 Misra R, Patel T, Kotha P, Raji A, Ganda O, Banerji M et al. Prevalence of diabetes, metabolic syndrome, and cardiovascular
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risk factors in US Asian Indians: results from a national study. J Diabetes Complications 2010; 24: 145–153. Mohanty SA, Woolhandler S, Himmelstein DU, Bor DH. Diabetes and cardiovascular disease among Asian Indians in the United States. J Gen Intern Med 2005; 20: 474–478. Ye J, Rust G, Baltrus P, Daniels E. Cardiovascular risk factors among Asian Americans: results from a National Health Survey. Ann Epidemiol 2009; 19: 718–723. Ramachandran A, Snehalatha C, Mary S, Mukesh B, Bhaskar AD, Vijay V. The Indian Diabetes Prevention Programme shows that lifestyle modification and metformin prevent type 2 diabetes in Asian Indian subjects with impaired glucose tolerance (IDPP-1). Diabetologia 2006; 49: 289–297. Mohan V, Mathur P, Deepa R, Deepa M, Shukla DK, Menon GR et al. Urban rural differences in prevalence of self-reported diabetes in India—the WHO-ICMR Indian NCD risk factor surveillance. Diabetes Res Clin Pract 2008; 80: 159–168. Smith SC Jr, Jackson R, Pearson TA, Fuster V, Yusuf S, Faergeman O et al. Principles for national and regional guidelines on cardiovascular disease prevention: a scientific statement from the World Heart and Stroke Forum. Circulation 2004; 109: 3112–3121. American Diabetes Assocation. Diagnosis and classification of diabetes mellitus. Diabetes Care 2008; 31: S55–60. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr et al. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. J Am Med Assoc 2003; 289: 2560–2572. Program National Cholesterol Education. Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III). J Am Med Assoc 2001; 285: 2486–2497. International Diabetes Federation. The IDF Consensus Worldwide Definition of the Metabolic Syndrome. Brussels: IDF, 2006. Sadikot SM, Nigam A, Das S, Bajaj S, Zargar AH, Prasannakumar KM et al. The burden of diabetes and impaired glucose tolerance in India using the WHO 1999 criteria: Prevalence of Diabetes in India Study (PODIS). Diabetes Res Clin Pract 2004; 66: 301–307. Shera AS, Jawad F, Maqsood A. Prevalence of diabetes in Pakistan. Diabetes Res Clin Pract 2007; 76: 219–222. Basit A, Shera AS. Prevalence of metabolic syndrome in Pakistan. Metab Syndr Relat Disord 2008; 6: 171–175. Whiting DR, Guariguata L, Weil C, Shaw J. IDF diabetes atlas: global estimates of the prevalence of diabetes for 2011 and 2030. Diabetes Res Clin Pract 2011; 94: 311–321. Anand SS, Yusuf S, Vuksan V, Devanesen S, Teo KK, Montague PA et al. Differences in risk factors, atherosclerosis, and cardiovascular disease between ethnic groups in Canada: the Study of Health Assessment and Risk in Ethnic groups (SHARE). Lancet 2000; 356: 279–284. Venkataraman R, Nanda NC, Baweja G, Parikh N, Bhatia V. Prevalence of diabetes mellitus and related conditions in Asian Indians living in the United States. Am J Cardiol 2004; 94: 977– 980. Kanaya AM, Wassel CL, Mathur D, Stewart A, Herrington D, Budoff MJ et al. Prevalence and correlates of diabetes in South Asian Indians in the United States: findings from the metabolic syndrome and atherosclerosis in South asians living in america study and the multi-ethnic study of atherosclerosis. Metab Syndr Relat Disord 2010; 8: 157–164. Prasad DS, Kabir Z, Dash AK, Das BC. Prevalence and risk factors for diabetes and impaired glucose tolerance in Asian Indians: a community survey from urban Eastern India. Diabetes Metab Syndr 2012; 6: 96–101.
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21 Tan JT, Tan LS, Chia KS, Chew SK, Tai ES. A family history of type 2 diabetes is associated with glucose intolerance and obesity-related traits with evidence of excess maternal transmission for obesity-related traits in a South East Asian population. Diabetes Res Clin Pract 2008; 82: 268–275. 22 Valdez R, Yoon PW, Liu T, Khoury MJ. Family history and prevalence of diabetes in the US population: the 6-year results from the National Health and Nutrition Examination Survey (1999– 2004). Diabetes Care 2007; 30: 2517–2522. 23 Xu F, Wang Y, Ware RS, Tse LA, Dunstan DW, Liang Y, et al. Physical activity, family history of diabetes and risk of developing hyperglycaemia and diabetes among adults in Mainland China. Diabet Med 2012; 29: 593–599. 24 Alarouj M, Bennakhi A, Alnesef Y, Sharifi M, Elkum N. Diabetes and associated cardiovascular risk factors in the State of Kuwait: the first national survey. Int J Clin Pract 2013; 67: 89–96. 25 Prasad DS, Kabir Z, Dash AK, Das BC. Prevalence and risk factors for metabolic syndrome in Asian Indians: a community study from urban Eastern India. J Cardiovasc Dis Res 2012; 3: 204–211.
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26 Raji A, Seely EW, Arky RA, Simonson DC. Body fat distribution and insulin resistance in healthy Asian Indians and Caucasians. J Clin Endocrinol Metab 2001; 86: 5366–5371. 27 Tirosh A, Shai I, Bitzur R, Kochba I, Tekes-Manova D, Israeli E et al. Changes in triglyceride levels over time and risk of type 2 diabetes in young men. Diabetes Care 2008; 31: 2032–2037. 28 Misra A, Vikram NK. Insulin resistance syndrome (metabolic syndrome) and obesity in Asian Indians: evidence and implications. Nutrition 2004; 20: 482–491. 29 Misra A, Ganda OP. Migration and its impact on adiposity and type 2 diabetes. Nutrition 2007; 23: 696–708. 30 Anjana RM, Pradeepa R, Deepa M, Datta M, Sudha V, Unnikrishnan R et al. Prevalence of diabetes and prediabetes (impaired fasting glucose and/or impaired glucose tolerance) in urban and rural India: phase I results of the Indian Council of Medical Research-INdia DIABetes (ICMR-INDIAB) study. Diabetologia 2011; 54: 3022–3027. 31 Thayer ZM, Kuzawa CW. Biological memories of past environments: epigenetic pathways to health disparities. Epigenetics 2011; 6: 798–803.
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Research: Epidemiology Cardiovascular disease risk factors in the South Asian population living in Kuwait: a cross-sectional study N. Elkum, M. Al-Arouj, M. Sharifi, K. Behbehani and A. Bennakhi Dasman Diabetes Institute, Kuwait City, Kuwait Accepted 22 October 2013
Abstract High rates of diabetes and cardiovascular disease have been reported in South Asian immigrants in many countries. However, the prevalence and characteristics of cardiovascular disease risk factors among a South Asian population living in Kuwait have not yet been investigated. This study was therefore designed to estimate the prevalence of cardiovascular disease risk factors and determine whether they are independently associated with diabetes in such a population.
Background
Methods A population-based cross-sectional study was conducted on 1094 South Asians (781 men and 313 women), mainly Indian and Pakistani (≥ 18 years of age), of whom 75.1% were Indians. Interviews were carried out, during which socio-demographic and anthropometric data were collected, followed by a physical examination and collection of fasting blood samples for laboratory investigations. Diabetes was defined by fasting plasma glucose ≥ 7 mmol/l, or being on treatment, and/or self-reported previously diagnosed Type 2 diabetes.
The prevalence of diabetes was 21.1%, with 3.4% of that percentage of people being newly diagnosed. Using BMI measurements, 24.0% of those who participated in the study were obese and 46.1% were overweight. Dyslipidaemia was found in 77.6% and hypertension in 44.8%. Advancing age (≥ 40 years), male gender, high LDL, high total cholesterol, hypertension and positive family history of diabetes were significantly associated with increased risk of diabetes.
Results
Our study shows that the prevalence of cardiovascular disease risk factors in South Asian expatriates in Kuwait exceeds prevalence rates reported in their homeland and other countries. This may suggest the added stress of environmental factors on the development of cardiovascular disease risk factors in such populations. Specialized prevention programmes targeting such high-risk ethnic populations are paramount and need to be implemented.
Conclusion
Diabet. Med. 31, 531–539 (2014)
Introduction The State of Kuwait is a small, oil-producing country of 17 820 km2, which has experienced rapid economic growth and socio-demographic and epidemiological transitions over the past six decades. This economic boom attracted many expatriates to come for work in Kuwait. According to the 2011 consensus, expatriates form 67% (2 514 107) of the population of Kuwait, with an average population growth rate of 6.7% annually. The vast majority of the expatriates come from South Asian countries, mainly from India and Pakistan, and constitute 44% (1 106 207) of the total expatriate population.
Correspondence to: Naser Elkum. E-mail: [email protected]
ª 2013 The Authors. Diabetic Medicine ª 2013 Diabetes UK
The International Diabetes Federation (IDF) Atlas ranked Kuwait as having the sixth-highest prevalence of Type 2 diabetes mellitus worldwide, with a prevalence of 23.9% (http://www.idf.org/diabetes-atlas-2012-update-out-now) [1]. Health services in Kuwait are provided free of charge for nationals and for a minimal fee of one Kuwaiti dinar ($US3.5) for expatriates to cover the cost of diagnosis, laboratory investigations and medications. Providing health care for this population presents a huge financial burden and challenge for the health authorities of the country. The prevalence of Type 2 diabetes and related cardiovascular disease risk factors varies among different ethnicities [2,3]. Amongst all the ethnic groups, South Asian immigrants in North America and Europe have an increased prevalence of Type 2 diabetes mellitus and cardiovascular disease risk factors [4,5]. Moreover, the prevalence of Type 2 diabetes
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Cardiovascular risk factors among South Asian emigrants in Kuwait N. Elkum et al.
What’s new?
Enrolment and interview procedures
• This study investigated, for the first time, the prevalence of cardiovascular disease risk factors and identified independent factors associated with Type 2 diabetes in a South Asian population residing in Kuwait.
All those willing to participate were invited to come to the study site at Dasman Diabetes Institute after a minimum of a 10-h overnight fast. Interviewers explained the study once more to those who had agreed to take part and obtained their signed consent; blood samples were then collected and interviews were conducted after serving a light breakfast. Each person was interviewed privately by interviewers speaking their language. The study was approved by the Scientific Advisory Council and Ethical Review Committee at Dasman Diabetes Institute. Informed written consent was obtained from those who had agreed to participate before their enrolment in the study.
• This study shows a high prevalence of diabetes and cardiovascular disease risk factors among South Asians, with rates that even exceed those reported in similar populations in Europe, North America, and in their homeland. and cardiovascular disease risk factors in expatriates living in these countries exceeded the prevalence in their homelands [6,7]. The most important risk factors associated with cardiovascular disease are Type 2 diabetes mellitus, hypercholesterolaemia, hypertension, obesity, smoking and sedentary lifestyle [8]. To date, prevalence and characteristics of a wide range of cardiovascular disease risk factors in the South Asian population in Kuwait and other Gulf countries has not been investigated. The main objectives of this study were therefore to estimate, for the first time, the prevalence of cardiovascular disease risk factors and to identify independent factors associated with Type 2 diabetes in a South Asian population residing in Kuwait.
Subjects and methods A cross-sectional population-based survey was conducted with a random representative sample of adults (≥ 18 years) of multi-ethnic origin across the six governorates (strata) of the State of Kuwait. A simple random sample was selected from each stratum with proportional allocation. For each stratum, a population frame included expatriates of both genders. A stratified random sampling technique was used for the selection of people from the computerized register of the Public Authority of Civil Information. The total study sample comprised 4077 non-Kuwaiti men and women, randomly selected across the six strata; out of the total study population invited for participation, 3460 (40.2% women) agreed to participate in the study. This article presents the data of 1094 people from India and Pakistan. This survey was carried out between June 2011 and August 2012. The study team consisted of trained supervisors, nurses, callers, interviewers and phlebotomists. Recruitment was through a telephone call in which details of the study were explained and, if the response was positive, appointments for a study visit were booked. Face-to-face interviews were then carried out by multilingual staff. Meticulous care was taken to protect the privacy and confidentiality of those who took part in the survey.
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Anthropometric and physical measurements
Physical and anthropometric measurements included, body weight, height, waist circumference and blood pressure. Blood pressure was measured using an Omron HEM-907XL digital sphygmomanometer (Omron Healthcare, Inc., Vernon Hills, IL, USA). An average of three blood pressure readings, with 5- to 10-min rest between each, was noted. Height and weight were measured, with subjects wearing light indoor clothing and with bare feet, using calibrated portable electronic weighing scales and portable inflexible bars to measure height. Waist circumference was measured using a constant tension tape at the end of a normal expiration, with arms relaxed at the sides, at the highest point of the iliac crest at the mid-axillary line. BMI was calculated using the standard formula of body weight in kilograms divided by height in metres squared.
Laboratory measurements
Blood samples were obtained after an overnight fast of at least 10 h and were analysed for fasting glucose, HbA1c, insulin levels and lipid profiles that included triglycerides, total cholesterol, LDL and HDL. Glucose and lipid profiles were measured on the Siemens Dimension RXL chemistry analyser (Diamond Diagnostics, Holliston, MA, USA). HbA1c was determined using the Variant device (Bio-Rad Laboratories, Hercules, CA, USA). All laboratory tests were performed by certified technicians at the clinical laboratories of the Dasman Diabetes Institute, using the Ministry of Health approved methods and quality standards.
Definitions used
The current recommendations and updated guidelines for the definition, diagnosis and classification of Type 2 diabetes, published by the International Diabetes Federation, have been used. Diabetes was defined by fasting plasma glucose ≥ 7 mmol/l, being under treatment, or self-reported previously diagnosed Type 2 diabetes [9]. Impaired fasting
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glucose was defined by fasting blood glucose values ≥ 5.6 and < 7 mmol/l. Hypertension was defined as blood pressure ≥ 140/90 mmHg, being under treatment, or a self-report of previously diagnosed hypertension [10]. High LDL cholesterol was defined as > 4.1 mmol/l, hypertriglyceridaemia as ≥ 1.7 mmol/l and low HDL cholesterol as < 1.03 mmol/l in men and < 1.29 mmol/l in women [11]. High total cholesterol was defined as > 5.2 mmol/l. Obesity was assessed by using BMI standard criteria: BMI between 18.5 and 24.9 kg/ m2 was considered normal, 25–29.9 kg/m2 overweight and ≥ 30 kg/m2 obese. According to the International Diabetes Federation, abdominal obesity was defined as waist circumference ≥ 90 cm in men and ≥ 80 cm in women [12]. Subjects were asked about different types of physical activity in a typical week, with the level of physical activity rated as ‘sedentary’, ‘moderate’ or ‘vigorous’. Moderate physical activity was deemed to be if subjects engaged in physical efforts that cause light sweating or a slight increase in breathing or heart rate, examples of which included brisk walking, painting houses, gardening and climbing stairs. A harder physical effort that causes heavy sweating or a greater increase in breathing or heart rate was considered vigorous. Examples of this would be carrying a heavy load, construction, digging, running and strenuous sports. Subjects were considered to have a sedentary lifestyle if they did not engage in physical activity or exercise other than regular household work most days. People reporting no vigorous or moderate activity per week were considered physically inactive.
Statistical analysis
Those participating in the study were classified, based on fasting blood glucose levels, into those without Type 2 diabetes, those with impaired fasting glucose and those with Type 2 diabetes. Demographic characteristics are presented against health status using means standard deviation, or as numbers and percentages, as appropriate. Differences between groups of continuous independent variables were analysed using the Student t-test. Differences in the prevalence of individual conditions were compared using the v2-test. Logistic regression analysis was performed to estimate odds ratios and to examine the predictive effect of each factor on risk for Type 2 diabetes. Research Electronic Data Capture was used for data collections and data management. All statistical assessments were two-sided and considered to be significant when the P-value was < 0.05. Data analysis was carried out using SAS version 9.2 (SAS Institute, Cary, NC, USA).
Results Population characteristics
Of the 1355 South Asians who were approached, 1094 (Indians and Pakistanis) were screened; 19% refused to
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participate. Indians comprised 75.1% (822) of the group and Pakistanis 24.9% (272). The majority were men 781 (71.3%). The mean age of the survey population was 42.8 10.1 years, whereas the mean age of those who took part was 42.6 9.6 years (42.7 9.7 years for men and 42.3 9.5 years for women). The socio-demographics of the group studied are shown in Table 1. Compared with Pakistanis, Indians attained a better level of education (P = 0.0002) and were more active (P = 0.0003). The subjects from Pakistan had greater mean BMI (29.3 vs. 26.9 kg/m2; P < 0.0001), waist circumference (98.3 vs. 92.2 cm; P < 0.0001) and a higher mean level of triglycerides (1.86 vs. 1.55 mmol/l; P = 0.0031). Prevalence of cardiovascular disease risk factors
The mean BMI was 27.5 4.7 kg/m2. Twenty-four per cent of the group were obese and 46.1% were overweight. Using the International Diabetes Federation Asian criteria for waist circumference, the results showed that 73.3% had abdominal obesity. Obesity (BMI ≥ 30 kg/m2) was more prominent in Pakistanis (36.4 vs. 19.9%; P < 0.0001). There was a high frequency of hypertension (44.8%), increased total cholesterol (55.7%), low HDL (43.3%), high LDL (23.4%) and high triglycerides (18.9%). A high prevalence of family history of Type 2 diabetes (54.1%) was also observed. Twenty-eight per cent were smokers. Women had significantly higher mean levels of total cholesterol and BMI, while men had higher mean levels of systolic/diastolic blood pressure, fasting blood glucose and triglycerides. There was an increase in the prevalence of general and central obesity, hypertension, Type 2 diabetes, hypercholesterolaemia and high LDL with increasing age (Table 2). In addition, the highest rates of cardiovascular disease risk factors were observed among those with abdominal obesity compared with those who had normal waist circumference (results not reported).
Prevalence of impaired fasting glucose and Type 2 diabetes
The median fasting blood glucose level was 5.2 mmol/l. Impaired fasting glucose was present in 16.6% of the people and was more common in men than women (18.4% vs. 12.1%). Type 2 diabetes was identified in 231 people (21.1%). The prevalence of newly diagnosed Type 2 diabetes was 3.4%, whereas 17.7% of those who participated were known to have diabetes. Of the total known to have diabetes, 89.2% were on medication. The prevalence of Type 2 diabetes increased with age: in those aged 20–29 years, the prevalence was 7.5%, at age 40–59 years 28.9% and in those ≥ 60 years the prevalence was 44.2% (P < 0.0001). The prevalence of Type 2 diabetes was higher in men compared with women (24.2% vs. 13.4%; P < 0.0001). The prevalence of Type 2 diabetes increased significantly with increasing BMI: 16.8% for those of normal weight,
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Table 1 Clinical and socio-demographic characteristics of a South Asian population
Characteristics Age, years Gender Men Women BMI (kg/m2) Waist circumference (cm) Family history of diabetes Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Fasting blood glucose* (mmol/l) HbA1c, IFCC (mmol/mol) DCCT, % Total cholesterol (mmol/l) Triglyceride (mmol/l) HDL cholesterol (mmol/l) LDL cholesterol (mmol/l) Physical activity† Inactive (%) Education, % Illiterate—no schooling 1–12 years > 12 years Smoking‡,% Smoker Non-smoker Income§, % ≤ Kuwaiti dinar 500 > Kuwaiti dinar 500
All (n = 1094) mean SD 42.6 9.6
Indians (n = 822) mean sd 42.6 9.8
782 (71.3) 315 (28.7) 27.5 4.7 93.7 10.7 555 (54.1) 133.6 18.9 82.7 24.1 5.3 2.0
72.14 27.86 26.9 92.2 54.9 133.6 82.4 5.2
45 6.2 1.4 5.2 1.1 1.63 1.2 1.1 0.27 3.5 2.3
Pakistanis (n = 272) mean SD
P-values
42.6 8.9 69.12 30.88 29.3 98.3 51.4 133.5 83.8 5.3
4.3 9.7 18.8 12.0 1.98
44 6.18 1.4 5.2 1.06 1.55 0.97 1.08 0.27 3.55 2.57
46 6.35 5.18 1.86 1.03 3.35
663 (60.6)
57.5
69.9
8 (0.73) 491 (44.8) 598 (54.5)
0.36 41.97 57.66
1.84 52.94 45.22
303 (28.1) 777 (71.9)
27.8 72.2
28.7 71.3
556 (61.1) 355 (38.9)
60.43 39.57
63.08 36.92
5.3 12.2 19.3 43.7 2.09
0.9268 0.3389 < 0.0001 < 0.0001 0.3377 < 0.9841 0.6055 0.3064 0.0838
1.4 1.0 1.56 0.27 0.84
0.6691 0.0031 0.0047 0.0598 0.0003 0.0002
0.7764
0.4866
Data are means SD unless noted otherwise (*medians SD). A person was considered to be inactive if they did not engage in sufficient physical activity or exercise other than regular household work on most days. † A person was considered to be a smoker if they were currently smoking or were an ex-smoker, and a non-smoker if they had never smoked. § A person’s average monthly household income for the last 12 months (1 Kuwaiti dinar = $US3.5). DCCT, Diabetes Control and Complications Trial; IFCC, International Federation of Clinical Chemistry and Laboratory Medicine. †
Table 2 Prevalence of various cardiovascular risk factors in different age groups Age groups, years Risk factors BMI, kg/m2 Normal (18.5–24.9) Overweight (25–29.9) Obese (≥ 30) Central obesity* Hypertension† Diabetes‡ Hypercholesterolaemia (> 5.2 mmol/l) Hypertriglyceridaemia (≥ 1.7 mmol/l) Low HDL < 1.03 mmol/l in men < 1.29 mmol/l in women High LDL (> 4.1 mmol/l)
20–39 (n = 438)
40–59 (n = 604)
≥ 60 (n = 52)
163 185 90 274 135 33 192 69
154 290 160 484 312 175 372 136
10 29 13 44 43 23 45 2
P-value for trend 0.0004
(37.2) (42.2) (20.6) (62.6) (30.8) (7.5) (43.8) (15.8)
(25.5) (48.0) (26.5) (80.1) (51.7) (28.9) (61.6) (22.5)
(19.2) (55.8) (25.0) (84.6) (82.7) (44.2) (86.5) (3.9)
198 (45.2)
270 (44.7)
6 (11.5)
91 (20.8)
147 (24.3)
18 (34.6)
< < <
5.2 mmol/l) Hypertriglyceridaemia (≥ 1.7 mmol/l) High LDL (> 4.1 mmol/l) Low HDL (< 1.03 mmol/l) Women General obesity, ≥ 30 kg/m2 Central obesity, waist circumference ≥ 80 cm Hypertension† Hypercholesterolaemia (> 5.2 mmol/l) Hypertriglyceridaemia (≥ 1.7 mmol/l) High LDL (> 4.1 mmol/l) Low HDL (< 1.29 mmol/l) All General obesity Central obesity Hypertension† Hypercholesterolaemia Hypertriglyceridaemia High LDL Low HDL
Without diabetes, % n = 682
Impaired fasting glucose, % n = 181
Diabetes* n = 231
P-value
12.1
29.2
29.6
< 0.0001
58.3
76.4
76.2
< 0.0001
39.3 51.6
63.2 62.5
64.0 70.9
< 0.0001 < 0.0001
17.6
34.0
28.0
< 0.0001
25.2
27.1
20.6
0.3372
48.4
55.6
50.3
0.3314
34.8 88.8
44.7 100.0
30.9 100.0
0.0070 0.0077
22.8 44.6
57.9 57.9
64.3 66.7
< 0.0001 0.0164
5.6
10.5
21.4
0.0025
20.6
23.7
19.1
0.8711
25.3
34.2
23.8
0.4775
19.8 68.7 33.6 49.2 13.5 23.6 40.5
32.4 81.3 62.1 61.5 29.1 26.4 51.1
29.9 80.5 64.1 70.1 26.8 20.4 45.5
< < < <
12 years 1–12 years Illiterate—no schooling Smoking Non-smoker Smoker Income, Kuwaiti dinar ≤ 500 > 500 Physical activity Active Inactive Hypercholesterolaemia No Yes (> 5.2 mmol/l) High LDL† No Yes (> 4.1 mmol/l) Low HDL No Yes (< 1.29 mmol/l) Hypertriglyceridaemia No Yes (≥ 1.7 mmol/l)
Multivariate‡
Prevalence,%
Odds ratio (95% CI)
7.5 28.9 44.2
1 5.0 (3.37–7.44) 9.7 (5.07–18.7)
1 3.7 (2.3–5.8) 6.5 (2.8–15.3)
21.2 21.0
1 1.0 (0.72–1.42)
1 0.9 (0.58–1.41)
13.4 24.2
1 2.1 (1.43–2.96)
1 2.5 (1.5–4.2)
15.9 26.9
1 1.9 (1.43–2.65)
1 2.5 (1.7–3.7)
13.7 30.2
1 2.7 (2.01–3.67)
1 1.6 (1.1–2.4)
16.8 21.2 26.2
1 1.3 (0.93–1.91) 1.8 (1.18–2.62)
1 1.1 (0.7–1.7) 1.6 (1.0–2.7)
17.4 25.6 25.0
0.63 (0.13–3.18) 1.03 (0.21–5.17) 1
1 1.6 (1.1–2.5) 0.83 (0.1–10.9)
23.8 20.2
1 1.2 (0.89–1.69)
1 1.3 (0.8–1.9)
19.3 24.0
1 1.3 (0.96–1.83)
1 0.9 (0.6–1.4)
20.7 21.4
1 1.1 (0.78–1.41)
1 1.3 (0.9–1.9)
14.2 26.6
1 2.2 (1.60–2.98)
1 1.9 (1.3–2.9)
21.9 18.4
1 0.79 (0.56–1.14)
1 2.2 (1.4–3.5)
20.3 22.2
1 1.1 (0.833–1.49)
1 0.9 (0.7–1.5)
19.1 29.9
1 1.8 (1.29–2.56)
1 1.0 (0.6–1.6)
P-value < 0.0001
0.6582
0.0009
< 0.0001
0.0121
0.1277
0.0558
0.2455
0.5950
0.2022
0.0032
0.0012
0.9587
0.9979
*Hypertension was defined as blood pressure ≥ 140/90 mmHg, being under treatment or self-report of previously diagnosed hypertension. LDL was defined as < 1.03 mmol/l in men and < 1.29 mmol/l in women. ‡ For multivariate analyses, values were adjusted for age, gender, BMI, nationality, family history of diabetes, blood pressure, total cholesterol, LDL, HDL, triglycerides, smoking, education and physical activity. †
Type 2 diabetes; individuals with hypertension were 60% more likely to be at risk of Type 2 diabetes. Likewise, individuals with high total cholesterol level or with a high level of LDL were twice as likely to be at risk of Type 2 diabetes.
Discussion This study reports for the first time a high prevalence of Type 2 diabetes and cardiovascular disease risk factors among South Asians living in Kuwait. Our data show that
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the rates exceed those reported in similar populations in Europe, North America and their homeland. Moreover, people from Pakistan appear to have a higher prevalence of such risk factors compared with those from India. These data add further evidence to the role of environmental factors in exacerbating Type 2 diabetes and cardiovascular disease. The reported rates of impaired fasting glucose and Type 2 diabetes mellitus in South Asian expatriates in Kuwait exceeded the prevalence in their homeland [13–16], whereas the prevalence of Type 2 diabetes among South Asians living in the UK, the USA and Canada has been found to be as high
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as 12–15% [17–19], which is less than the prevalence reported in our study. Older age, being male, having a positive family history of Type 2 diabetes, having hypertension, high total cholesterol and high LDL significantly contributed to increased Type 2 diabetes risk among South Asians in Kuwait. The higher prevalence of cardiovascular risk factors in younger age in the studied population is of particular concern. Our results showed that the prevalence of various cardiovascular risk factors increased more rapidly in the 20- to 39-year age group than at age 60 years (Table 2). We also found that the prevalence of Type 2 diabetes increases with age and the highest proportion of diabetes cases (44.2%) was detected in the ≥ 60-year age group. Similar trends were reported by other studies for South Asians populations [3,14,18,20]. Compared with the < 40-year-old age group, Type 2 diabetes was almost seven times more common among those above 60 years of age. Therefore, the focus of prevention should be at people younger than 20–39 years of age. Our data illustrate that family history of diabetes is an independent predictor of Type 2 diabetes; this observation is in agreement with the findings in another study of a South Asian population [21]. Participants with a family history of diabetes were 2.5 times more likely to develop Type 2 diabetes (odds ratio 2.4, P < 0.0001); this may suggest potential genetic and environmental influences that predispose South Asians to Type 2 diabetes. In the USA, China and Kuwait, family history of diabetes was shown to be significantly associated with the risk of Type 2 diabetes, thus highlighting the importance of gene–environment interaction to the onset of this disease. Our findings are consistent with the findings reported from other populations [22–24]. Dyslipidaemia was common among those who took part in the study, with total dyslipaemia reaching 77.1%. Similar findings were reported from other studies across South Asia [3,15]. This study shows that high total blood cholesterol level and high LDL are the main phenotypic features of dyslipidaemia in Type 2 diabetes and were significant risk factors for developing diabetes mellitus in South Asians populations. This is in agreement with findings from other South Asian studies in India and Pakistan [14,25] and abroad [26], as well as in other Asian populations [27]. A high prevalence of dyslipidaemia justifies the importance of an early screening of lipid disorders in migrant/expatriate South Asians at the primary healthcare level. Using BMI, 70.1% were either overweight or obese. However, BMI has been shown to underestimate adiposity in South Asians, whereas waist circumference may give a more reliable estimate [28]. Using waist circumference as a measure, central obesity was present in 73.3% of those in the study. This high prevalence of central obesity could indicate a predisposition for the South Asian population to deposit abdominal fat. The prevalence of various risk factors increases with central obesity. Obesity is significantly associated with Type 2 diabetes in univariate analysis, but failed
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to reach statistical significance in multivariate analysis; a similar observation was reported in other Asian Indians [20]. Studies showed that South Asian immigrants exhibit greater central adiposity than Caucasian Europeans [29]. Ethnic-specific BMI and waist circumference cut-off points should be used for risk stratification. The prevalence of hypertension was 44.3%, of which 30.2% was people with Type 2 diabetes. People in the study with hypertension showed a 62% increased risk of developing Type 2 diabetes compared with those without hypertension (odds ratio 1.62). A similar association was reported by other studies from homeland countries and abroad [19,30]. The significant link between hypertension and Type 2 diabetes suggests the need for a common reliable strategy to manage these conditions. It is striking to show that rates of cardiovascular disease risk factors in South Asian expatriates in Kuwait exceeded the prevalence rates reported in their homeland, Europe and the USA. Even although a clear explanation is lacking, it can be postulated that a myriad of factors might be involved. Possible factors that pertain to Kuwait, such as hot weather and epigenetic factors, may play a role. Lifestyle features may be an important determinant in the increased risk of Type 2 diabetes amongst South Asians. Although this supposes to be working population, the rate of physical inactivity was 60.6%. This may reflect the lifestyle in Kuwait where the very hot weather limited the chance of physical activity, and private transportation is widely affordable. However, we did not find an independent relationship between diabetes and physical inactivity. The link between physical activity and the prevalence of diabetes could be confounded by other risk factors, such as abdominal obesity. Promoting lifestyle modification could be important in reducing the impact of these modifiable risk factors. The Indian Diabetes Prevention Program (IDPP-1) demonstrated a relative risk reduction of 28.5% with lifestyle intervention in Asian Indians with impaired glucose tolerance [6]. Smoking is a well-established cause of cancer, lung disease, coronary heart disease and stroke. However, our study did not demonstrate an independent relationship between diabetes and smoking. Finally, it is very well documented that this interaction between the environment and the genetic make-up of the human body—termed epigenetic—is complicated and not very well understood. Epigenetics can influence human genes as a result of environmental interaction by adding chemical marks to genes or proteins that persist over generations [31]. This phenomenon means that the environment can imprint its signature on the human body and transfer this knowledge to the next generation. Keeping this in mind, it is possible to postulate that there might be other factors playing on the epigenetics of this group, leading to increasing their risk of cardiovascular disease and Type 2 diabetes. It will be of great scientific value to understand these factors in the future and potentially find methods that can reverse the risk.
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Cardiovascular risk factors among South Asian emigrants in Kuwait N. Elkum et al.
As with any other population study, our survey also had limitations with regard to study design. The cross-sectional design used in this study makes it impossible to determine any temporal relationship between prevalence of diabetes and possible aetiological factors associated with diabetes. A further study is currently underway to prospectively follow up this cohort to determine causality and directional effect of the causes. Further, the diagnosis of diabetes was not confirmed by a 2-h postprandial blood glucose measurement, meaning that prevalence of Type 2 diabetes may have been underestimated.
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Conclusion Our reported rates of cardiovascular disease risk factors in South Asian expatriates in Kuwait exceeded the prevalence rates reported in their homeland, Europe and the USA. This might suggest the role of environmental factors on the development of cardiovascular disease risk factors in such a population. Specialized prevention programmes targeting such high-risk ethnic populations are paramount and need to be implemented.
Funding sources
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This study was supported by the Kuwait Foundation for the Advancement of Sciences (KFAS). 12
Competing interests
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None declared.
Acknowledgments
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We would like to thank our study team for their efforts and excellent work. We are grateful to the Clinical Laboratory and the Tissue Bank Core Facility at the Dasman Diabetes Institute for their contribution in performing the biochemical profile analysis and handling samples, respectively. We would also thank Dr Jawad Al-Lawati from the Oman Ministry of Health for his critical review of the manuscript and helpful comments. We are also indebted to the Kuwait Foundation for the Advancement of Sciences (KFAS) for financial support of this research project (RA-2010-004).
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