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Diabetes and impaired glucose tolerance in a rural area in Pakistan and associated risk factors
Diabetes & Metabolic Syndrome: Clinical Research & Reviews (2008) 2, 125—130
http://diabetesindia.com/
ORIGINAL PAPER
Diabetes and impaired glucose tolerance in a rural area in Pakistan and associated risk factors Naeem Zahid *, Bjørgulf Claussen, Akhtar Hussain Department of General Practice and Community Medicine, University of Oslo, Norway KEYWORDS Pakistan; Rural; Diabetes
Summary Aims: To determine the prevalence of diabetes and IFG and associated risk factors in a rural area of Pakistan. Methods: Two thousand one hundred and nineteen rural individuals aged 20 years and above were included in the study. Fasting plasma glucose (FPG), oral glucose tolerance test (OGTT), height, weight, waist, hips, body fat percentage (BF%), lipid profile and blood pressure were recorded. Results: The prevalence of diabetes in men was 3.7% (95% CI: 2.3—5.1), in women 6.9% (95% CI: 5.5—8.3) and in total 5.8% (95% CI: 4.8—6.8). The prevalence of IFG in men, women and for the total was 4.7% (95% CI: 3.1—6.3), 5.8% (95% CI: 4.5—7.1) and 5.4% (95% CI: 4.4—6.4). Age, gender, waist/hip ratio, BF% and hypertension were significant risk factors for diabetes after controlling for potential confounding factors. Conclusions: A relatively high prevalence of type 2 diabetes and impaired fasting plasma glucose was observed in the rural population of Pakistan. WHR was independently associated with the occurrence of diabetes. # 2008 Diabetes India. Published by Elsevier Ltd. All rights reserved.
Introduction South Asian immigrants in Europe have particularly high prevalence of type 2 diabetes mellitus (T2DM). Prevalence for South Asian immigrants in Oslo (predominantly from Pakistan) aged 30—59 is 27.5% among women and 14.3% among men, compared to 2.9% in Western women and 5.9% in Western men [1]. Similar high diabetes prevalence was also noted amongst Pakistanis in the UK [2]. * Corresponding author at: Department of General Practice and Community Medicine, University of Oslo, Post Box 1130 Blindern, N-0318 Oslo, Norway. E-mail address: [email protected] (N. Zahid).
A relatively small number of studies have been conducted in Pakistan to estimate the occurrence of diabetes [3,4]. The prevalence of diabetes in these studies [3,4] has been high, but considerably lower than from the above-mentioned studies from the west [1,2]. However, due to diverged investigation and selection procedures in the above-mentioned studies [1,3,4], it is difficult to make a valid comparison in order to estimate the increased risk of diabetes among the Pakistani immigrants in Europe. It has been suggested that changes in food habits and adoption of a sedentary lifestyle in a genetically susceptible population may have contributed to the increased preponderance of diabetes in migrant populations [2].
1871-4021/$ — see front matter # 2008 Diabetes India. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.dsx.2008.02.007
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Therefore, we conducted a relatively large population based study in rural areas of Pakistan to determine the prevalence and associated risk factors for diabetes prior to changes that occur due to migration. Since the majority of Pakistanis in Norway originate from rural Kharian, an area in the district of Gujrat, we set out perform the study in this area.
blood glucose with a HEMOCUE machine and to draw venous blood samples. The first author, leading the fieldwork, did blood pressure, medical consultation and the final registration. The first author was present at the field at all times. The work performed by the fieldworkers was assessed continuously.
Measurements
Methods Study area The study was conducted during the months of March to July 2006 in the areas of Kharian; which is situated in the northern part of the province Punjab, approximately 150 km from the capital Islamabad. The area had about 250 villages. Five villages where the rural life style had been abandoned due to major migration to Europe and the USA were excluded from the study with a view to secure lifestyle related to the rural population in Pakistan.
Sample size We estimated the sample size by the following formula: n¼
Z2 Q p
: d2 Where Z was 1.96, p was prevalence, Q is 1 p, and d was the upper limit of the 95% CI minus the prevalence. The prevalence was set to 5.4% [3]. D was set to 1%. This gives an n of 1963.
Study population Villages were continuously added into the survey until our goal of 2000 subjects was met; in total 44 villages were surveyed. Large villages were divided into sectors and surveyed separately. Camps were set in a total of 57 times in these 44 villages. For each session, 20 randomly selected households were invited to participate. Participants were given information about the purpose of the survey; they were informed that they could withdraw from the survey at any point. Since many were illiterate, information was given orally to the participants to avoid selection bias, and oral consent was received prior to the enrolment into the study.
Fieldworkers Fieldworkers were recruited from the community and trained for one week. They were trained to measure height, weight, waist, hip, body fat percentage (BF%),
For measuring body weight a digital weight machine was used, using a foot-to-foot bio-impedance method it also showed body fat percentage (BF%). The weight machine was placed on a flat surface. The subjects were wearing light clothes but not shoes. Weight was taken to the nearest kg; percentages were noted to the nearest whole number. High BF% was defined as >25% for men and >35% for women. Height was measured without shoes; the subjects standing upright against a wall with the heels, buttocks, shoulders and the back of the head touching a wall onto which a measuring tape was attached. BMI was calculated by dividing the weight in kilograms on the square of the height in meters. Underweight was defined as BMI <18.5 kg/m2; normal weight 18.5—24.9 kg/m2, overweight was defined as BMI between 25 and 29.9 kg/m2, obesity was defined as a BMI 30 kg/m2 [5]. Waist and hip circumference was measured using a non-elastic tape measure. Waist girth was measured midway between the lower border of the ribs and the iliac crest. Hip circumference was measured at the greatest protrusion of the buttocks. The measurements were taken to the nearest centimeter. Waist/hip ratio was calculated by dividing the hip circumference on the waist circumference. High waist/hip ratio (WHR) was defined as >0.88 for men and >0.81 for women [6]. Blood pressure was measured using a standard sphygmomanometer. The blood pressure was measured while the subjects were sitting, the cuff was attached to the upper arm; the bell of the stethoscope was placed over the brachial artery. If the first systolic measurement was above 135, two additional measurements were taken, and the mean was noted. The pressure was recorded to the nearest 10 mmHg. High blood pressure was defined as systolic pressure 140 mmHg, diastolic pressure 90 mmHg or both.
Blood samples Ten ml blood was drawn from a venous puncture into plastic tubes; the blood was transported to a local hospital within 2 h of collection. Before transportation, the blood was stored in refrigerators. The laboratory ran daily controls and calibrations. They also had monthly inter-laboratory controls.
Diabetes and impaired glucose tolerance in Pakistan and associated risk factors
Fasting plasma glucose estimation
127
For the fasting plasma glucose (FPG) blood was collected in tubes with anticoagulant and a glycolysis inhibitor. In the event that we were unable to get blood or the patient refused to give a venous sample (n = 78). We collected a drop of blood from the tip of a finger that was analyzed by a HEMOCUE glucose analyzer, which converted the results to a plasma-equivalent glucose concentration.
according to WHOs diagnostic criteria 1999 [7]; subjects with FPG between 6.1 and 6.9 mmol/L ware classified as having IFG, subjects with FPG 7.0 mmol/L were classified as having diabetes. Subjects with OGGT values between 7.9 and 11.0 mmol/L were classified as having IGT; those who had values above 11.1 mmol/L were classified as having diabetes. Those who met these criteria received thorough information and referred to a clinic for follow-up.
Oral glucose tolerance test
Statistics
For the oral glucose tolerance test (OGTT), the subjects were given a drink containing 75 g of glucose dissolved in 3 dl water. Blood glucose values, which were converted to plasma values were measured after 2 h using a HEMOCUE glucose analyzer. All subjects were invited to take part in this test. OGTT was performed on 1694 subjects as the others refused to wait for 2 h.
Statistical analyses were done using SPSS 12.0.1. Odd ratios were given with 95% confidential interval. Student’s t-test was performed for continuous variables. Logistic regressions were used to control for potential confounding factors. For the estimation of odds ratios, we used five models. In the fist model all the OR were crude while in the following three models the OR was adjusted for potential influencing factors. Statistical significance was set at p < 0.05. All the tests presented were two tailed.
Lipid profile Total cholesterol (TotChol), HDL, LDL and triglycerides (TG) were measured. For these analyses blood was collected in plain tubes. LDL was computed by Friedwhals formula. TotChol/HDL >5 was defined as high. TG was defined as high if >1.7 mmol/L [7].
Diabetes, IFG and IGT Diabetes, impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) were defined
Results The mean age of the participants was 44.2 years, 45.5 years for men and 44.0 years for women (Table 1). Significant difference by gender was observed for height, weight, diastolic blood pressure, fasting plasma glucose, oral glucose tolerance test, LDL, Triglycerides, waist, hip and BF%. The women had significantly higher BMI and BF% than
Table 1 Description of the study population with n, means and one standard deviation of the mean Male Age in years Height in cm * Weight in kg * BMI in kg/m2 * Systolic pressure in mmHg Diastolic pressure in mmHg * FPG in mmol/L * OGTT in mmol/L * Total Cholesterol LDL in mmol/L * HDL in mmol/L Triglycerides * TotChol/HDL Waist in cm * Hip in cm * Waist/hip ratio * BF% * *
Female
n
Mean
n
Mean
740 715 713 713 678 678 710 581 691 687 690 691 689 708 708 708 683
45.4 18.4 170.6 7.5 64.0 13.4 22.0 4.3 124.1 17.5 78.5 11.1 5.0 1.5 6.7 3.2 4.4 0.9 2.8 0.6 1.0 0.4 1.4 0.6 4.6 1.9 83.7 12.8 92.2 10.1 0.91 0.08 27.0 10.1
1367 1327 1326 1323 1260 1260 1307 1113 1248 1234 1246 1248 1245 1277 1278 1277 1282
44.0 15.6 156.4 6.1 61.3 14.8 25.1 5.6 125.5 17.8 80.4 10.4 5.2 2.0 7.4 3.7 4.7 1.1 2.9 0.7 1.0 0.4 1.5 0.7 4.6 0.7 88.2 13.5 103.2 13.5 0.85 0.07 40.3 8.8
p < 0.005 for the difference between the genders.
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Table 2 Prevalence of diabetes and IFG per 100 in different age groups with 95% confidential intervals in brackets Gender
Age group
n
Cases of diabetes
Prev per 100
Male
20—40 41—60 61—99 Total/adjusted
311 223 175 709
2 16 8 26
0.6 7.2 4.6 3.7
(0.3—1.6) (3.7—10.6) (1.4—7.7) (2.3—5.1)/3.3
10 14 9 33
3.2 6.3 5.1 4.7
(1.2—5.2) (3.0—9.5) (1.8—8.5) (3.1—6.2)
Female
20—40 41—60 61—99 Total/adjusted
619 460 223 1302
14 50 27 91
2.3 (1.1—3.5) 10.9 (8.0—13.8) 12.1 (7.7—16.5) 7.0 (5.6—8.4)/6.8
22 35 18 75
3.6 7.6 8.1 5.8
(2.1—5.0) (5.1—10.1) (4.4—11.7) (4.5—7.1)
Total
20—40 41—60 61—99 Total
930 683 398 2011
16 66 35 117
32 49 27 108
3.4 7.2 6.8 5.4
(2.2—4.6) (5.2—9.2) (4.3—9.3) (4.4—6.4)
1.7 9.7 8.8 5.8
Cases of IFG
(0.9—2.6) (7.4—11.9) (6.0—11.6) (4.8—6.9)
Prev per 100
Age adjusted prevalence behind slashes.
men ( p < 0.005). More than a quarter, 25.5% of the subjects in the study were overweight. BF% was high in 66.7%. High WHR was recorded in 71.4%: 62.3% in males and 76.4%. High BF% and WHR were significantly more prevalent amongst women compared to men. A high proportion of the subjects, 34.1% had hypertension. In men, hypertension was found in 30.5%, while in women hypertension was found in 36.0%. Diastolic, unlike systolic, pressure was significantly higher amongst women. Fasting plasma glucose was recorded in 2011 subjects (Table 2). The prevalence of diabetes was found to be 5.8% (95% CI: 4.8—6.8) in this population. Females had significantly higher prevalence of diabetes; it was almost twice as high as the prevalence amongst men. The prevalence increased with increasing age for both sexes. The results do not change substantially after adjusting for WHO age standardization rates [8]. The adjusted prevalence was 3.3% for men and 6.4% for women. The overall prevalence of IFG was 5.4% (95% CI: 4.4—6.4). Women had a higher prevalence of IFG but the difference was insignificant. The prevalence of IFG increased with age for both sexes. The increasing prevalence of IFG and diabetes with age was steeper for women compared to men. The OGTT criterion for diabetes was met by 7.6% (95% CI: 6.2—8.8). IGT was diagnosed in 17.2% (95% CI: 15.4—19.0). The prevalence for men was 15.1% (95% CI: 12.2—18.1) and 18.2% (95% CI: 16.0—20.5) for women. There was a good agreement between the diagnosis of diabetes between OGTT and FPG, the agreement between IFG and IGT on the other hand was poor (Table 3). Female gender, age, blood pressure, and WHR remained as independent risk factors for the prevalent cases of diabetes by the FPG criteria after adding all measures of obesity into the regressions (Table 4). Of the measures of obesity having a BMI
above 30, a high WHR ratio and high BF% were significant risk factors diabetes by the OGTT criteria (Table 5).
Discussions Our data suggest a relatively high prevalence of diabetes, IFG and IGT in the rural population. The prevalence of both diabetes and IFG was lower compared to a prevalence study in an urban area of Pakistan were it was found to be 16.2% [9]. Our results are more in line with the National Health Survey of Pakistan [3] and the Pakistan National Diabetes Survey from Baluchistan [10], where the prevalence was 6.5%. Other studies from this region, for example rural areas in India have shown similarly low prevalence of diabetes [11], and data from rural Bangladesh showed an even lower prevalence, 2.3% [12]. It has been shown that rural populations in South Asia have lower rates of diabetes compared to their urban counterparts [12]. The other explanation for the observed difference in prevalence rate is that the study subjects in the previous surveys were older. The inclusion criteria for many of the studies were 25 years and Table 3 Agreement between fasting plasma glucose and oral glucose tolerance test OGTT 7.8
7.9—11.1
FPG 6.0 6.1—7.0 7.0
1198 40 10
243 26 13
32 15 79
1473 81 102
Total
1248
282
126
1656
Kappa 0.327.
11.1
Total
Diabetes and impaired glucose tolerance in Pakistan and associated risk factors
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Table 4 Odds ratios with 95% CI for risk factors for diabetes following the FPG criteria
Female gender Age >40 High blood pressure High TotChol/HDL High TG Underweight Overweight Obese High BF% High WHR
Model 1 a
Model 2 b n = 1757
Model 3 c n = 1701
Model 4 d n = 1720
Model 5 e n = 1654
2.0 5.9 2.5 1.2 2.3 0.3 1.3 1.7 4.2 4.0
2.0 5.1 1.7 1.1 1.7 0.4 0.8 1.3
1.9 4.5 1.7 1.1 1.7
1.8 5.1 1.8 1.1 1.7
1.8 4.3 1.6 1.2 1.5 0.5 0.7 1.1 1.5 3.2
(1.2—3.1) (3.6—10.4) (1.6—3.7) (0.8—1.9) (1.5—3.3) (0.1—0.7) (0.8—2.0) (1.0—2.8) (2.2—8.0) (2.1—7.3)
(1.2—3.3) (2.9—9.2) (1.1—2.6) (0.7—1.7) (1.1—2.5) (0.2—1.1) (0.5—1.4) (0.7—2.2)
(1.2—3.2) (2.5—8.2) (1.1—2.6) (0.7—1.7) (1.1—2.5)
(1.1—1.3) (2.8—9.3) (1.2—2.7) (0.7—1.7) (1.1—2.7)
1.9 (1.0—3.7) * 3.2 (1.4—7.1)
(1.1—3.1) (2.3—8.0) (1.0—2.5) (0.7—2.1) (0.9—2.6) (0.2—1.6) (0.4—1.3) (0.6—2.0) (0.7—3.0) (1.3—7.5)
High blood pressure: 140/90, high TotChol/HDL: >5, high TG: >1.7, underweight: BMI < 18.4, overweight: BMI 25—30, obese: BMI 30, high BF%: >35 for women and >25 for men, high WHR: >0.88 for men and >0.81 for women. a Crude OR, the risk factors are not adjusted for each other. b The risk factors are adjusted for gender, age, blood pressure, TotChol/HDL, TG and BMI. c As Model 2 but BMI is replaced with BF%. d As Model 2 but BMI is replaced with WHR. e Adjusted for all variables. * p = 0.043.
above [9] while we have included subjects from the age of 20 years and above. Our data showed considerably lower prevalence of diabetes compared to the prevalence rate of diabetes among people from Pakistan in Norway; but comparison is difficult because in the Norwegian study only people above 30 were enrolled [1]. It is also noteworthy that in the above-mentioned studies [1,3,9,10,13], subjects were labeled as having diabetes if they had positive history or met a cut off value for fasting blood glucose. We have however analyzed our data following only FPG cut offs. Our results showed that there is a higher prevalence of diabetes among females in all most all
categories. This might be explained be the higher prevalence of obesity amongst women. Women had higher OR for diabetes, even when corrected for age, TotChol/HDL ratio, blood pressure, BMI, WHR and BF%. The difference between males and females is in contrast with data from white populations and data from Pakistan [10], where males had a higher prevalence of diabetes; it is on the other hand in accordance with data on Pakistanis in Europe [1] and also data from Bangladesh [12]. Obesity is a well-known risk factor for diabetes [14]. We therefore paid special interest to this topic. Our study showed that overweight and obesity was prevalent in this population, while this
Table 5 Odds ratios with 95% CI for risk factors for diabetes following the OGTT criteria
Female gender Age >40 High blood pressure High TotChol/HDL High TG Underweight Overweight Obese High BF% High WHR
Model 1 a
Model 2 b n = 1626
Model 3 c n = 1575
Model 4 d n = 1591
Model 5 e n = 1533
1.4 7.6 3.0 1.2 2.1 0.4 1.9 2.6 4.8 5.2
1.2 6.5 1.7 1.1 1.6 0.6 1.5 2.2
1.4 5.6 1.9 1.1 1.6
1.1 6.0 1.9 1.1 1.7
1.1 5.6 1.6 1.1 1.7 0.5 1.3 2.2 1.2 2.5
(0.9—2.2) (4.2—12.5) (2.0—4.4) (0.8—1.8) (1.4—3.1) (0.1—0.9) (1.2—3.0) (1.6—4.4) (2.6—8.4) (2.6—10.7)
(0.8—1.9) (3.6—11.8) (1.2—2.6) (0.7—1.7) (1.1—2.4) (0.2—1.4) (0.9—2.3) (1.3—3.8)
(0.9—2.1) (3.1—10.2) (1.3—2.9) (0.7—1.7) (1.1—2.4)
(0.7—1.7) (3.2—11.1) (1.3—2.8) (0.7—1.7) (1.1—2.5)
2.2 (1.2—4.3) 2.5 (1.3—5.0)
(0.7—1.8) (3.0—10.5) (1.0—2.4) * (0.6—1.8) (1.0—2.9) * (0.1 -1.6) (0.8—2.2) (1.2—3.8) (0.6—2.5) (1.2—5.3)
High blood pressure: 140/90, high TotChol/HDL: >5, high TG: >1.7, underweight: BMI < 18.4, overweight: BMI 25—30, obese: BMI 30, high BF%: >35 for women and >25 for men, high WHR: >0.88 for men and >0.81 for women. a Crude OR, the risk factors are not adjusted for each other. b The risk factors are adjusted for gender, age, blood pressure, TotChol/HDL ratio, TG and BMI. c As Model 2 but BMI is replaced with BF%. d As Model 2 but BMI is replaced with WHR. e Adjusted for all variables. * p < 0.05.
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was found to be exceedingly prevalent among the Pakistanis in Norway [15] and in the UK [2]. In our survey, we used three different means for obesity. Being obese in terms of having a BMI above 30 was a significant risk factor for diabetes by the OGTT criteria. Significant association was observed with WHR and diabetes by the OGTT criterion. These findings are in accordance with the data from Bangladesh [16]. Finally, we have also measured BF% using a BIA method. BF% and WHR were significant risk factors for diabetes irrespective of criterions used for classifying diabetes. WHR, unlike BF%, was a significant risk factor even when all the measures of obesity were entered into the regressions. Data has shown that BF% as well as WHR was higher in Indian subjects compared to the Caucasians even when BMI was similar [2]. It is difficult to generalize the results for the whole rural population in Pakistan since the prevalence rate of diabetes appeared to differ amongst 5 ethnic groups that constitute the population in Pakistan [3]. However, our results indicate that diabetes is highly prevalent in this part of rural Pakistan. The results also showed that overweight, obesity and hypertension were largely prevalent, especially among women. As the life expectancy for Pakistanis is also increasing diabetes is and will continue to consume ever larger portion of the health budget and become an even greater challenge for health authorities. As of today, prevention remains the only alternative to this lifelong entrenched disease. Urgent measures are needed to promote lifestyle encouraging a reduction of sedentary lifestyle and weight gain and thereby better glycaemic control. Advanced knowledge on the etiology and will provide clues to prevention and more effective treatment of diabetes, which is urgently needed in societies where the resource for health is scarce.
Acknowledgements We are grateful to all participants, fieldworkers and the co-workers, without whom we could not have accomplished this work. The Norwegian Research Council supported the study financially.
References [1] Jenum AK, Holme I, Graff-Iversen S, Birkeland KI. Ethnicity and sex are strong determinants of diabetes in an urban Western society: implications for prevention. Diabetologia 2005;48(3):435—9. [2] Barnett AH, Dixon AN, Bellary S, Hanif MW, O’hare JP, Raymond NT, et al. Type 2 diabetes and cardiovascular risk in the UK south Asian community. Diabetologia 2006;49(10): 2234—46. [3] Jafar TH, Levey AS, White FM, Gul A, Jessani S, Khan AQ, et al. Ethnic differences and determinants of diabetes and central obesity among South Asians of Pakistan. Diabet Med 2004;21(7):716—23. [4] Shera AS, Jawad F, Maqsood A. Prevalence of diabetes in Pakistan. Diabetes Res Clin Pract 2006. [5] WHO. Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. Geneva, WHO; 1995 [Ref Type: Report]. [6] Snehalatha C, Viswanathan V, Ramachandran A. Cutoff values for normal anthropometric variables in Asian Indian adults. Diabetes Care 2003;26(5):1380—4. [7] WHO. Definition, diagnosis and classification of diabetes mellitus and its complications. Geneva, WHO: 1999 [Ref Type: Report]. [8] Ahmad OB, Boschi-Pinto C, Lopez AD, Murray CJL, Lozano R, Inoue M. Age standardization of rates: a new WHO standard. Geneva: WHO; 2000. [9] Shera AS, Rafique G, Khwaja IA, Ara J, Baqai S, King H. Pakistan national diabetes survey: prevalence of glucose intolerance and associated factors in Shikarpur, Sindh Province. Diabet Med 1995;12(12):1116—21. [10] Shera AS, Rafique G, Khawaja IA, Baqai S, King H. Pakistan National Diabetes Survey: prevalence of glucose intolerance and associated factors in Baluchistan province. Diabetes Res Clin Pract 1999;44(1):49—58. [11] Dhadwal D, Ahluwalia SK, Das Gupta DJ, Kaushal SS, Yadav R, Gupa A. Prevalence of NIDDM in the general population (>40 years) in Shimla. Indian J Med Sci 1997;51(12):459—64. [12] Hussain A, Rahim MA, Zad Khan AK, Ali SM, Vaaler S. Type 2 diabetes in rural and urban population: diverse prevalence and associated risk factors in Bangladesh. Diabet Med 2005;22(7):931—6. [13] Shera AS, Rafique G, Khwaja IA, Baqai S, Khan IA, King H. Pakistan National Diabetes Survey prevalence of glucose intolerance and associated factors in North West at Frontier Province (NWFP) of Pakistan. J Pak Med Assoc 1999;49(9):206—11. [14] Hussain A, Claussen B, Ramachandran A, Williams R. Prevention of type 2 diabetes: a review. Diabetes Res Clin Pract 2007;76(3):317—26. [15] Kumar BN, Meyer HE, Wandel M, Dalen I, Holmboe-Ottesen G. Ethnic differences in obesity among immigrants from developing countries, in Oslo, Norway. Int J Obes (Lond) 2006;30(4):684—90. [16] Hussain A, Vaaler S, Sayeed MA, Mahtab H, Ali SM, Khan AK. Type 2 diabetes and impaired fasting blood glucose in rural Bangladesh: a population-based study. Eur J Public Health 2006.
Available online at www.sciencedirect.com
http://diabetesindia.com/
ORIGINAL PAPER
Diabetes and impaired glucose tolerance in a rural area in Pakistan and associated risk factors Naeem Zahid *, Bjørgulf Claussen, Akhtar Hussain Department of General Practice and Community Medicine, University of Oslo, Norway KEYWORDS Pakistan; Rural; Diabetes
Summary Aims: To determine the prevalence of diabetes and IFG and associated risk factors in a rural area of Pakistan. Methods: Two thousand one hundred and nineteen rural individuals aged 20 years and above were included in the study. Fasting plasma glucose (FPG), oral glucose tolerance test (OGTT), height, weight, waist, hips, body fat percentage (BF%), lipid profile and blood pressure were recorded. Results: The prevalence of diabetes in men was 3.7% (95% CI: 2.3—5.1), in women 6.9% (95% CI: 5.5—8.3) and in total 5.8% (95% CI: 4.8—6.8). The prevalence of IFG in men, women and for the total was 4.7% (95% CI: 3.1—6.3), 5.8% (95% CI: 4.5—7.1) and 5.4% (95% CI: 4.4—6.4). Age, gender, waist/hip ratio, BF% and hypertension were significant risk factors for diabetes after controlling for potential confounding factors. Conclusions: A relatively high prevalence of type 2 diabetes and impaired fasting plasma glucose was observed in the rural population of Pakistan. WHR was independently associated with the occurrence of diabetes. # 2008 Diabetes India. Published by Elsevier Ltd. All rights reserved.
Introduction South Asian immigrants in Europe have particularly high prevalence of type 2 diabetes mellitus (T2DM). Prevalence for South Asian immigrants in Oslo (predominantly from Pakistan) aged 30—59 is 27.5% among women and 14.3% among men, compared to 2.9% in Western women and 5.9% in Western men [1]. Similar high diabetes prevalence was also noted amongst Pakistanis in the UK [2]. * Corresponding author at: Department of General Practice and Community Medicine, University of Oslo, Post Box 1130 Blindern, N-0318 Oslo, Norway. E-mail address: [email protected] (N. Zahid).
A relatively small number of studies have been conducted in Pakistan to estimate the occurrence of diabetes [3,4]. The prevalence of diabetes in these studies [3,4] has been high, but considerably lower than from the above-mentioned studies from the west [1,2]. However, due to diverged investigation and selection procedures in the above-mentioned studies [1,3,4], it is difficult to make a valid comparison in order to estimate the increased risk of diabetes among the Pakistani immigrants in Europe. It has been suggested that changes in food habits and adoption of a sedentary lifestyle in a genetically susceptible population may have contributed to the increased preponderance of diabetes in migrant populations [2].
1871-4021/$ — see front matter # 2008 Diabetes India. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.dsx.2008.02.007
126
N. Zahid et al.
Therefore, we conducted a relatively large population based study in rural areas of Pakistan to determine the prevalence and associated risk factors for diabetes prior to changes that occur due to migration. Since the majority of Pakistanis in Norway originate from rural Kharian, an area in the district of Gujrat, we set out perform the study in this area.
blood glucose with a HEMOCUE machine and to draw venous blood samples. The first author, leading the fieldwork, did blood pressure, medical consultation and the final registration. The first author was present at the field at all times. The work performed by the fieldworkers was assessed continuously.
Measurements
Methods Study area The study was conducted during the months of March to July 2006 in the areas of Kharian; which is situated in the northern part of the province Punjab, approximately 150 km from the capital Islamabad. The area had about 250 villages. Five villages where the rural life style had been abandoned due to major migration to Europe and the USA were excluded from the study with a view to secure lifestyle related to the rural population in Pakistan.
Sample size We estimated the sample size by the following formula: n¼
Z2 Q p
: d2 Where Z was 1.96, p was prevalence, Q is 1 p, and d was the upper limit of the 95% CI minus the prevalence. The prevalence was set to 5.4% [3]. D was set to 1%. This gives an n of 1963.
Study population Villages were continuously added into the survey until our goal of 2000 subjects was met; in total 44 villages were surveyed. Large villages were divided into sectors and surveyed separately. Camps were set in a total of 57 times in these 44 villages. For each session, 20 randomly selected households were invited to participate. Participants were given information about the purpose of the survey; they were informed that they could withdraw from the survey at any point. Since many were illiterate, information was given orally to the participants to avoid selection bias, and oral consent was received prior to the enrolment into the study.
Fieldworkers Fieldworkers were recruited from the community and trained for one week. They were trained to measure height, weight, waist, hip, body fat percentage (BF%),
For measuring body weight a digital weight machine was used, using a foot-to-foot bio-impedance method it also showed body fat percentage (BF%). The weight machine was placed on a flat surface. The subjects were wearing light clothes but not shoes. Weight was taken to the nearest kg; percentages were noted to the nearest whole number. High BF% was defined as >25% for men and >35% for women. Height was measured without shoes; the subjects standing upright against a wall with the heels, buttocks, shoulders and the back of the head touching a wall onto which a measuring tape was attached. BMI was calculated by dividing the weight in kilograms on the square of the height in meters. Underweight was defined as BMI <18.5 kg/m2; normal weight 18.5—24.9 kg/m2, overweight was defined as BMI between 25 and 29.9 kg/m2, obesity was defined as a BMI 30 kg/m2 [5]. Waist and hip circumference was measured using a non-elastic tape measure. Waist girth was measured midway between the lower border of the ribs and the iliac crest. Hip circumference was measured at the greatest protrusion of the buttocks. The measurements were taken to the nearest centimeter. Waist/hip ratio was calculated by dividing the hip circumference on the waist circumference. High waist/hip ratio (WHR) was defined as >0.88 for men and >0.81 for women [6]. Blood pressure was measured using a standard sphygmomanometer. The blood pressure was measured while the subjects were sitting, the cuff was attached to the upper arm; the bell of the stethoscope was placed over the brachial artery. If the first systolic measurement was above 135, two additional measurements were taken, and the mean was noted. The pressure was recorded to the nearest 10 mmHg. High blood pressure was defined as systolic pressure 140 mmHg, diastolic pressure 90 mmHg or both.
Blood samples Ten ml blood was drawn from a venous puncture into plastic tubes; the blood was transported to a local hospital within 2 h of collection. Before transportation, the blood was stored in refrigerators. The laboratory ran daily controls and calibrations. They also had monthly inter-laboratory controls.
Diabetes and impaired glucose tolerance in Pakistan and associated risk factors
Fasting plasma glucose estimation
127
For the fasting plasma glucose (FPG) blood was collected in tubes with anticoagulant and a glycolysis inhibitor. In the event that we were unable to get blood or the patient refused to give a venous sample (n = 78). We collected a drop of blood from the tip of a finger that was analyzed by a HEMOCUE glucose analyzer, which converted the results to a plasma-equivalent glucose concentration.
according to WHOs diagnostic criteria 1999 [7]; subjects with FPG between 6.1 and 6.9 mmol/L ware classified as having IFG, subjects with FPG 7.0 mmol/L were classified as having diabetes. Subjects with OGGT values between 7.9 and 11.0 mmol/L were classified as having IGT; those who had values above 11.1 mmol/L were classified as having diabetes. Those who met these criteria received thorough information and referred to a clinic for follow-up.
Oral glucose tolerance test
Statistics
For the oral glucose tolerance test (OGTT), the subjects were given a drink containing 75 g of glucose dissolved in 3 dl water. Blood glucose values, which were converted to plasma values were measured after 2 h using a HEMOCUE glucose analyzer. All subjects were invited to take part in this test. OGTT was performed on 1694 subjects as the others refused to wait for 2 h.
Statistical analyses were done using SPSS 12.0.1. Odd ratios were given with 95% confidential interval. Student’s t-test was performed for continuous variables. Logistic regressions were used to control for potential confounding factors. For the estimation of odds ratios, we used five models. In the fist model all the OR were crude while in the following three models the OR was adjusted for potential influencing factors. Statistical significance was set at p < 0.05. All the tests presented were two tailed.
Lipid profile Total cholesterol (TotChol), HDL, LDL and triglycerides (TG) were measured. For these analyses blood was collected in plain tubes. LDL was computed by Friedwhals formula. TotChol/HDL >5 was defined as high. TG was defined as high if >1.7 mmol/L [7].
Diabetes, IFG and IGT Diabetes, impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) were defined
Results The mean age of the participants was 44.2 years, 45.5 years for men and 44.0 years for women (Table 1). Significant difference by gender was observed for height, weight, diastolic blood pressure, fasting plasma glucose, oral glucose tolerance test, LDL, Triglycerides, waist, hip and BF%. The women had significantly higher BMI and BF% than
Table 1 Description of the study population with n, means and one standard deviation of the mean Male Age in years Height in cm * Weight in kg * BMI in kg/m2 * Systolic pressure in mmHg Diastolic pressure in mmHg * FPG in mmol/L * OGTT in mmol/L * Total Cholesterol LDL in mmol/L * HDL in mmol/L Triglycerides * TotChol/HDL Waist in cm * Hip in cm * Waist/hip ratio * BF% * *
Female
n
Mean
n
Mean
740 715 713 713 678 678 710 581 691 687 690 691 689 708 708 708 683
45.4 18.4 170.6 7.5 64.0 13.4 22.0 4.3 124.1 17.5 78.5 11.1 5.0 1.5 6.7 3.2 4.4 0.9 2.8 0.6 1.0 0.4 1.4 0.6 4.6 1.9 83.7 12.8 92.2 10.1 0.91 0.08 27.0 10.1
1367 1327 1326 1323 1260 1260 1307 1113 1248 1234 1246 1248 1245 1277 1278 1277 1282
44.0 15.6 156.4 6.1 61.3 14.8 25.1 5.6 125.5 17.8 80.4 10.4 5.2 2.0 7.4 3.7 4.7 1.1 2.9 0.7 1.0 0.4 1.5 0.7 4.6 0.7 88.2 13.5 103.2 13.5 0.85 0.07 40.3 8.8
p < 0.005 for the difference between the genders.
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Table 2 Prevalence of diabetes and IFG per 100 in different age groups with 95% confidential intervals in brackets Gender
Age group
n
Cases of diabetes
Prev per 100
Male
20—40 41—60 61—99 Total/adjusted
311 223 175 709
2 16 8 26
0.6 7.2 4.6 3.7
(0.3—1.6) (3.7—10.6) (1.4—7.7) (2.3—5.1)/3.3
10 14 9 33
3.2 6.3 5.1 4.7
(1.2—5.2) (3.0—9.5) (1.8—8.5) (3.1—6.2)
Female
20—40 41—60 61—99 Total/adjusted
619 460 223 1302
14 50 27 91
2.3 (1.1—3.5) 10.9 (8.0—13.8) 12.1 (7.7—16.5) 7.0 (5.6—8.4)/6.8
22 35 18 75
3.6 7.6 8.1 5.8
(2.1—5.0) (5.1—10.1) (4.4—11.7) (4.5—7.1)
Total
20—40 41—60 61—99 Total
930 683 398 2011
16 66 35 117
32 49 27 108
3.4 7.2 6.8 5.4
(2.2—4.6) (5.2—9.2) (4.3—9.3) (4.4—6.4)
1.7 9.7 8.8 5.8
Cases of IFG
(0.9—2.6) (7.4—11.9) (6.0—11.6) (4.8—6.9)
Prev per 100
Age adjusted prevalence behind slashes.
men ( p < 0.005). More than a quarter, 25.5% of the subjects in the study were overweight. BF% was high in 66.7%. High WHR was recorded in 71.4%: 62.3% in males and 76.4%. High BF% and WHR were significantly more prevalent amongst women compared to men. A high proportion of the subjects, 34.1% had hypertension. In men, hypertension was found in 30.5%, while in women hypertension was found in 36.0%. Diastolic, unlike systolic, pressure was significantly higher amongst women. Fasting plasma glucose was recorded in 2011 subjects (Table 2). The prevalence of diabetes was found to be 5.8% (95% CI: 4.8—6.8) in this population. Females had significantly higher prevalence of diabetes; it was almost twice as high as the prevalence amongst men. The prevalence increased with increasing age for both sexes. The results do not change substantially after adjusting for WHO age standardization rates [8]. The adjusted prevalence was 3.3% for men and 6.4% for women. The overall prevalence of IFG was 5.4% (95% CI: 4.4—6.4). Women had a higher prevalence of IFG but the difference was insignificant. The prevalence of IFG increased with age for both sexes. The increasing prevalence of IFG and diabetes with age was steeper for women compared to men. The OGTT criterion for diabetes was met by 7.6% (95% CI: 6.2—8.8). IGT was diagnosed in 17.2% (95% CI: 15.4—19.0). The prevalence for men was 15.1% (95% CI: 12.2—18.1) and 18.2% (95% CI: 16.0—20.5) for women. There was a good agreement between the diagnosis of diabetes between OGTT and FPG, the agreement between IFG and IGT on the other hand was poor (Table 3). Female gender, age, blood pressure, and WHR remained as independent risk factors for the prevalent cases of diabetes by the FPG criteria after adding all measures of obesity into the regressions (Table 4). Of the measures of obesity having a BMI
above 30, a high WHR ratio and high BF% were significant risk factors diabetes by the OGTT criteria (Table 5).
Discussions Our data suggest a relatively high prevalence of diabetes, IFG and IGT in the rural population. The prevalence of both diabetes and IFG was lower compared to a prevalence study in an urban area of Pakistan were it was found to be 16.2% [9]. Our results are more in line with the National Health Survey of Pakistan [3] and the Pakistan National Diabetes Survey from Baluchistan [10], where the prevalence was 6.5%. Other studies from this region, for example rural areas in India have shown similarly low prevalence of diabetes [11], and data from rural Bangladesh showed an even lower prevalence, 2.3% [12]. It has been shown that rural populations in South Asia have lower rates of diabetes compared to their urban counterparts [12]. The other explanation for the observed difference in prevalence rate is that the study subjects in the previous surveys were older. The inclusion criteria for many of the studies were 25 years and Table 3 Agreement between fasting plasma glucose and oral glucose tolerance test OGTT 7.8
7.9—11.1
FPG 6.0 6.1—7.0 7.0
1198 40 10
243 26 13
32 15 79
1473 81 102
Total
1248
282
126
1656
Kappa 0.327.
11.1
Total
Diabetes and impaired glucose tolerance in Pakistan and associated risk factors
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Table 4 Odds ratios with 95% CI for risk factors for diabetes following the FPG criteria
Female gender Age >40 High blood pressure High TotChol/HDL High TG Underweight Overweight Obese High BF% High WHR
Model 1 a
Model 2 b n = 1757
Model 3 c n = 1701
Model 4 d n = 1720
Model 5 e n = 1654
2.0 5.9 2.5 1.2 2.3 0.3 1.3 1.7 4.2 4.0
2.0 5.1 1.7 1.1 1.7 0.4 0.8 1.3
1.9 4.5 1.7 1.1 1.7
1.8 5.1 1.8 1.1 1.7
1.8 4.3 1.6 1.2 1.5 0.5 0.7 1.1 1.5 3.2
(1.2—3.1) (3.6—10.4) (1.6—3.7) (0.8—1.9) (1.5—3.3) (0.1—0.7) (0.8—2.0) (1.0—2.8) (2.2—8.0) (2.1—7.3)
(1.2—3.3) (2.9—9.2) (1.1—2.6) (0.7—1.7) (1.1—2.5) (0.2—1.1) (0.5—1.4) (0.7—2.2)
(1.2—3.2) (2.5—8.2) (1.1—2.6) (0.7—1.7) (1.1—2.5)
(1.1—1.3) (2.8—9.3) (1.2—2.7) (0.7—1.7) (1.1—2.7)
1.9 (1.0—3.7) * 3.2 (1.4—7.1)
(1.1—3.1) (2.3—8.0) (1.0—2.5) (0.7—2.1) (0.9—2.6) (0.2—1.6) (0.4—1.3) (0.6—2.0) (0.7—3.0) (1.3—7.5)
High blood pressure: 140/90, high TotChol/HDL: >5, high TG: >1.7, underweight: BMI < 18.4, overweight: BMI 25—30, obese: BMI 30, high BF%: >35 for women and >25 for men, high WHR: >0.88 for men and >0.81 for women. a Crude OR, the risk factors are not adjusted for each other. b The risk factors are adjusted for gender, age, blood pressure, TotChol/HDL, TG and BMI. c As Model 2 but BMI is replaced with BF%. d As Model 2 but BMI is replaced with WHR. e Adjusted for all variables. * p = 0.043.
above [9] while we have included subjects from the age of 20 years and above. Our data showed considerably lower prevalence of diabetes compared to the prevalence rate of diabetes among people from Pakistan in Norway; but comparison is difficult because in the Norwegian study only people above 30 were enrolled [1]. It is also noteworthy that in the above-mentioned studies [1,3,9,10,13], subjects were labeled as having diabetes if they had positive history or met a cut off value for fasting blood glucose. We have however analyzed our data following only FPG cut offs. Our results showed that there is a higher prevalence of diabetes among females in all most all
categories. This might be explained be the higher prevalence of obesity amongst women. Women had higher OR for diabetes, even when corrected for age, TotChol/HDL ratio, blood pressure, BMI, WHR and BF%. The difference between males and females is in contrast with data from white populations and data from Pakistan [10], where males had a higher prevalence of diabetes; it is on the other hand in accordance with data on Pakistanis in Europe [1] and also data from Bangladesh [12]. Obesity is a well-known risk factor for diabetes [14]. We therefore paid special interest to this topic. Our study showed that overweight and obesity was prevalent in this population, while this
Table 5 Odds ratios with 95% CI for risk factors for diabetes following the OGTT criteria
Female gender Age >40 High blood pressure High TotChol/HDL High TG Underweight Overweight Obese High BF% High WHR
Model 1 a
Model 2 b n = 1626
Model 3 c n = 1575
Model 4 d n = 1591
Model 5 e n = 1533
1.4 7.6 3.0 1.2 2.1 0.4 1.9 2.6 4.8 5.2
1.2 6.5 1.7 1.1 1.6 0.6 1.5 2.2
1.4 5.6 1.9 1.1 1.6
1.1 6.0 1.9 1.1 1.7
1.1 5.6 1.6 1.1 1.7 0.5 1.3 2.2 1.2 2.5
(0.9—2.2) (4.2—12.5) (2.0—4.4) (0.8—1.8) (1.4—3.1) (0.1—0.9) (1.2—3.0) (1.6—4.4) (2.6—8.4) (2.6—10.7)
(0.8—1.9) (3.6—11.8) (1.2—2.6) (0.7—1.7) (1.1—2.4) (0.2—1.4) (0.9—2.3) (1.3—3.8)
(0.9—2.1) (3.1—10.2) (1.3—2.9) (0.7—1.7) (1.1—2.4)
(0.7—1.7) (3.2—11.1) (1.3—2.8) (0.7—1.7) (1.1—2.5)
2.2 (1.2—4.3) 2.5 (1.3—5.0)
(0.7—1.8) (3.0—10.5) (1.0—2.4) * (0.6—1.8) (1.0—2.9) * (0.1 -1.6) (0.8—2.2) (1.2—3.8) (0.6—2.5) (1.2—5.3)
High blood pressure: 140/90, high TotChol/HDL: >5, high TG: >1.7, underweight: BMI < 18.4, overweight: BMI 25—30, obese: BMI 30, high BF%: >35 for women and >25 for men, high WHR: >0.88 for men and >0.81 for women. a Crude OR, the risk factors are not adjusted for each other. b The risk factors are adjusted for gender, age, blood pressure, TotChol/HDL ratio, TG and BMI. c As Model 2 but BMI is replaced with BF%. d As Model 2 but BMI is replaced with WHR. e Adjusted for all variables. * p < 0.05.
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was found to be exceedingly prevalent among the Pakistanis in Norway [15] and in the UK [2]. In our survey, we used three different means for obesity. Being obese in terms of having a BMI above 30 was a significant risk factor for diabetes by the OGTT criteria. Significant association was observed with WHR and diabetes by the OGTT criterion. These findings are in accordance with the data from Bangladesh [16]. Finally, we have also measured BF% using a BIA method. BF% and WHR were significant risk factors for diabetes irrespective of criterions used for classifying diabetes. WHR, unlike BF%, was a significant risk factor even when all the measures of obesity were entered into the regressions. Data has shown that BF% as well as WHR was higher in Indian subjects compared to the Caucasians even when BMI was similar [2]. It is difficult to generalize the results for the whole rural population in Pakistan since the prevalence rate of diabetes appeared to differ amongst 5 ethnic groups that constitute the population in Pakistan [3]. However, our results indicate that diabetes is highly prevalent in this part of rural Pakistan. The results also showed that overweight, obesity and hypertension were largely prevalent, especially among women. As the life expectancy for Pakistanis is also increasing diabetes is and will continue to consume ever larger portion of the health budget and become an even greater challenge for health authorities. As of today, prevention remains the only alternative to this lifelong entrenched disease. Urgent measures are needed to promote lifestyle encouraging a reduction of sedentary lifestyle and weight gain and thereby better glycaemic control. Advanced knowledge on the etiology and will provide clues to prevention and more effective treatment of diabetes, which is urgently needed in societies where the resource for health is scarce.
Acknowledgements We are grateful to all participants, fieldworkers and the co-workers, without whom we could not have accomplished this work. The Norwegian Research Council supported the study financially.
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