|Year : 2020 | Volume
| Issue : 1 | Page : 25-31
Prevalence and risk factors for impaired glucose regulation among first-degree relatives of patients with type 2 diabetes mellitus in Maiduguri, Northeastern Nigeria
Haliru Ibrahim1, Fabian H Puepet2, Salisu B Muazu3, Bilkisu M Mubi4, Ibrahim D Gezawa5, Shettima K Mustapha4, Bukar Bakki4, Abdullahi M Talle4, Godspower C Michael6, Ibrahim Aliyu6
1 Department of Medicine, University of Maiduguri Teaching Hospital, Maiduguri, Nigeria; Department of Medicine, Federal Medical Centre, Birnin Kudu, Jigawa, Nigeria
2 Department of Medicine, Jos University Teaching Hospital, Jos, Nigeria
3 Department of Medicine, Ahmadu Bello University Teaching Hospital, Zaria, Nigeria
4 Department of Medicine, University of Maiduguri Teaching Hospital, Maiduguri, Nigeria
5 Department of Medicine, University of Maiduguri Teaching Hospital, Maiduguri, Nigeria; Department of Medicine, Family Medicine, and Paediatrics, Aminu Kano Teaching Hospital, Kano, Nigeria
6 Department of Medicine, Family Medicine, and Paediatrics, Aminu Kano Teaching Hospital, Kano, Nigeria
|Date of Submission||20-Jan-2019|
|Date of Decision||04-Jun-2019|
|Date of Acceptance||25-Jun-2019|
|Date of Web Publication||18-Dec-2019|
Dr. Salisu B Muazu
Department of Medicine, Ahmadu Bello University Teaching hospital, Zaria.
Source of Support: None, Conflict of Interest: None
Background/Purpose: Owing to genetic predilection of type 2 diabetes mellitus (T2DM), the risk of developing impaired glucose metabolism is thought to be higher in first-degree relatives (FDRs) of those with T2DM. The aim of this study was to estimate the prevalence of impaired glucose tolerance (IGT) and impaired fasting glycemia (IFG) and its associated risk factors in FDRs of patients with T2DM. Materials and Methods: This is a cross-sectional descriptive study of 320 cases (FDRs of T2DM outpatients) aged ≥25 years (145 males and 175 females) and 160 controls (76 males, 84 females) who were age and sex matched. All subjects underwent anthropometric, physical activity, and laboratory assessments after an overnight fast. Oral glucose tolerance test with 75g anhydrous glucose was administered. Fasting plasma glucose of 6.1–6.9 mmol/L and 2-h post-fasting glucose value of 7.8–11.0 mmol/L were used to define IFG and IGT, respectively. Statistical analysis was carried out using the Statistical Package for the Social Sciences software, version 20 (SPSS, Chicago, Illinois), and P value of <0.05 was considered significant. Results: The mean (standard deviation) age of the cases and controls was 38.4 (12.3) and 38.9 (10.3) years, respectively, P = 0.66. The prevalence rates of both IGT and IFG in cases and controls were (28.1% vs. 18.1%, P = 0.019 and 10.3% vs. 5.6%, P = 0.0001). The prevalence of IGT and IFG was found to be higher among females, P < 0.05. Multivariate analysis revealed abnormal waist circumference, being FDR, and elevated systolic blood pressure as risk factors for both the IGT and IFG, P < 0.05. Conclusion: FDRs of patients with T2DM are at higher risk of IGT or IFG. The risk increases with the development of obesity and elevated blood pressure in them.
Keywords: First-degree relatives, impaired fasting glucose, impaired glucose tolerance, risk factors, Nigeria
|How to cite this article:|
Ibrahim H, Puepet FH, Muazu SB, Mubi BM, Gezawa ID, Mustapha SK, Bakki B, Talle AM, Michael GC, Aliyu I. Prevalence and risk factors for impaired glucose regulation among first-degree relatives of patients with type 2 diabetes mellitus in Maiduguri, Northeastern Nigeria. J Diabetol 2020;11:25-31
|How to cite this URL:|
Ibrahim H, Puepet FH, Muazu SB, Mubi BM, Gezawa ID, Mustapha SK, Bakki B, Talle AM, Michael GC, Aliyu I. Prevalence and risk factors for impaired glucose regulation among first-degree relatives of patients with type 2 diabetes mellitus in Maiduguri, Northeastern Nigeria. J Diabetol [serial online] 2020 [cited 2020 Apr 9];11:25-31. Available from: http://www.journalofdiabetology.org/text.asp?2020/11/1/25/273086
| Introduction|| |
Type 2 diabetes mellitus (T2DM) results from a defect in insulin secretion and impairment of insulin action in hepatic and peripheral tissues, especially muscle tissue and adipocytes. A post-receptor defect is also present, causing resistance to the stimulatory effect of insulin on glucose use. It is an important public health problem worldwide, and its prevalence is increasing in both developed and developing nations. Family members of patients with diabetes are at higher risk of developing diabetes, although genetic factors play a key role in the development of T2DM, in the majority of patients, diabetes is brought about by a combination of genetic and environmental factors.,,, With the increasing prevalence of diabetes mellitus worldwide, the number of first-degree relative (FDR) of patients with T2DM and thus an increased risk of developing diabetes will also increase, which means that identifying risk factors associated with susceptibility to diabetes becomes increasingly important.
Although much is known about the impact of impaired glucose regulation on FDR in developed nations, few studies have been undertaken in developing nations including Nigeria. Studies regarding the prevalence of impaired glucose tolerance (IGT), impaired fasting glycemia (IFG), and its associated risk factors in FDR of patients with diabetes are important to gain a better understanding of the disease and if possible, to prevent or delay its progression and complications in developing countries.
The objective of this study was to estimate the prevalence of IGT, IFG, and its associated risk factors in FDR of people with type 2 diabetes and compare with controls of the same sex and age.
| Materials and Methods|| |
A total of 320 (145 males and 175 females) relatives of 160 patients with type 2 diabetes were recruited (two relatives per one type 2 diabetes proband) as cases from a consecutive sample of patients with T2DM attending outpatient clinics at the University of Maiduguri Teaching Hospital, Maiduguri, Borno State, Nigeria. A total of 160 persons (76 males and 84 females) were recruited as controls from a group of apparently healthy volunteers (not known to be hypertensive or diabetic and with no family history of diabetes). Other exclusion criteria include the following:
- – Patients previously diagnosed with diabetes
- – Patients on antidiabetic treatment
- – Patients on drugs such as beta-adrenergic receptor agonist, diuretics, lipid-lowering medications, and systemic steroids or other agents known to affect glucose tolerance
- – Acute or chronic illness from history and physical examination
- – Pregnancy, subjects who were >4 weeks amenorrheic from last menstrual period
The sample was recruited between March 2009 and March 2010. Review and authorization of all aspects of the study were carried out by the ethics committee of the institution. Approval was obtained from the committee before commencement of the study, and a declaration of informed consent was signed by each participant.
The cases (FDR of patients with T2DM) included siblings, children, or parents, probands were the persons with T2DM whose FDR is studied. All the subjects reported to the clinic in the morning after an overnight fast (8–12h), they were asked to abstain from vigorous exercise and smokers were encouraged to abstain from smoking in the evening and morning before examination. The questionnaire to obtain personal demographic information was administered to those who cannot read or write, whereas the literate among them were able to do that by themselves. Information concerning physical activities, both in active and leisure states, of the study population was sought and scored on the pro forma for the purpose of grouping them into the following different classes of activities as defined:
Work-related physical activity was separated into three grades according to occupation as defined by the National Noncommunicable Disease Survey:
- Not active (sedentary) (e.g., office work and unemployment)
- Moderately active (e.g., housework, trade work, and nursing)
- Very active (e.g., laboring)
Leisure time physical activity was graded as follows:
- Not active (e.g., housebound)
- Moderately active (e.g., gardening, walking, and sports 1–2 days/week)
- Very active (e.g., sports 3 days/week)
On arrival at the clinic, the information on family history in the questionnaire completed by the subjects was verified. Height was measured to the nearest 0.1cm using standard graduated height scale with subjects in the erect position and without footwear or headwear., Body weight in kilograms (kg) was measured to the nearest 0.1kg with subjects wearing light clothing and without shoes, using a standard hospital weighing scale positioned on a flat horizontal surface. Body mass index (BMI) (kg/m2) was calculated as weight (in kg) divided by the square of the height (in m2). Subjects with BMI < 18.5kg/m2 were classified as underweight and those with BMI between 18.5 and 24.9kg/m2 were classified as having normal weight. Those with BMI of 25.0–29.9 and ≥30.0kg/m2 were classified as overweight and obese, respectively.,
Waist circumference (WC) was measured to the nearest 0.1cm with tape measure placed midway between the lower rib margin and the iliac crest with the patient breathing normally. WC of ≥102cm in males and ≥88cm in females was considered abnormal. Hip circumference (HC) (in cm) was measured to the nearest 0.1cm as the horizontal level of maximum circumference around the buttocks (posteriorly) and the pubic symphysis (anteriorly). Waist-to-hip ratio (WHR) was calculated as the ratio of the WC (in cm) divided by the HC (in cm). WHR of ≥ 0.90 in males and ≥0.85 in females was considered abnormal. Resting blood pressure (BP) was measured after subjects had been seated for 10min by using a mercury sphygmomanometer and appropriately sized cuffs, using a standard technique.
Fasting venous blood samples were collected from an antecubital vein of each study and control subjects using aseptic technique, and emptied into fluoride and plain bottles for glucose and serum lipids, respectively. The samples were transferred to the laboratory immediately, promptly centrifuged, and analyzed on the same day for the estimation of fasting glucose and lipid profiles (total cholesterol, low-density lipoprotein [LDL] cholesterol, high-density lipoprotein [HDL] cholesterol, and triglyceride) using glucose oxidase and enzymatic methods. Study and control subjects were then given 75g of anhydrous glucose dissolved in 300mL of bottled water to drink within 5min. Blood samples were obtained 2h after the ingestion of oral glucose for post-glucose load plasma glucose estimation. Those with fasting plasma glucose concentration between 6.1 and 6.9 mmol/L after 8–12h fast were considered to have IFG. Plasma glucose concentration of 7.8–11.0 mmol/L after standard oral glucose load was considered IGT. Blood glucose concentration of <7.8 mmol/L 2h after 75g oral glucose and/or fasting plasma glucose ≤ 6.0 mmol/L was considered normal glucose tolerance. All the blood sampling processes were performed in the central laboratory of the University of Maiduguri Teaching Hospital using an enzyme-linked method.
All data collected were analyzed using the Statistical Package for the Social Sciences statistical program, version 20 (SPSS, Chicago, Illinois). Mean ± standard deviation (SD) values were used to describe continuous variables and proportions for categorical data. Statistical method used included Student’s t-test, chi-squared test, and multiple logistic regressions.
Two-tailed Student’s t-test was used for comparison of mean values and chi-squared (χ2) test for proportions. Fisher’s exact test was used where cells contained values less than five. Comparison of proportion in ordered categories was made using the chi-squared test for linear trend.
Multivariate analysis using multiple logistic regressions was used to determine the independent risk factors for IGT and IFG. The following covariates were considered in the multivariate adjusted analyses: age, gender, being FDR, BMI, WC, HC, and systolic blood pressure (SBP) and diastolic blood pressure (DBP).
In all statistical comparisons, probability (P) value of <0.05 was considered significant.
| Results|| |
This was a hospital-based cross-sectional study to estimate the prevalence of IGT and IFG and its associated risk factors in FDRs of people with T2DM (cases) attending the diabetes clinic of University of Maiduguri Teaching Hospital Maiduguri, Borno State, Nigeria, compared with that of the controls from among a group of apparently healthy volunteers with no family history of diabetes or hypertension.
Of the 320 cases (145 males [45.3%] and 175 females [54.7%]), 173 had normal oral glucose tolerance test (101 males [58.4%] and 72 females [41.6%]), 24 (7.5%) had diabetes (6 males and 18 females), 90 (28.1%) had IGT (29 males and 61 females), and 33 (10.3%) had IFG (9 males and 24 females).
The prevalence of IGT increased with age in both study (χ2 for trend = 70.13, P = 0.0001) and control (χ2 for trend = 18.1, P = 0.0013 [Fisher’s exact result]) subjects, with peak in the age group of 35–44 years in cases, whereas in controls, it peaked in the age group of 45–54 years. A decline in the prevalence of IGT was noted in the age group of 65–74 and 55–64 years in cases and controls, respectively.
The prevalence of IGT and IFG in cases and controls was 28.1% versus 10.3% and 18.1% versus 5.6%, respectively. The prevalence of IGT in cases was statistically higher than in controls (P = 0.019); similarly, the prevalence of IFG was statistically higher among cases than that in controls (0.0001).
The prevalence of IGT was found to be higher among females than that in males in both cases (34.9% vs. 20%, P = 0.004) and control (21.4% vs. 14.5%, P = 0.44) subjects.
To determine the influence of potential factors on IGT and IFG, multivariate analysis was used to determine the independent risk factors in the study population.
Age, WC, WHR, FDR, DBP, and SBP were identified independent risk factors for IGT. However, WC, WHR, and being FDR were stronger independent predictors for IGT while being FDR, SBP, and WC were the identified risk factors for IFG as shown in [Table 1].
|Table 1: Odds ratio estimates for impaired glucose tolerance/impaired fasting glycemia from multiple logistic regression|
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Exercise and prevalence of impaired glucose tolerance in cases and control subjects
The prevalence of IGT increased with decreasing level of physical activity in both cases (χ2 for trend = 4.17, P = 0.041) and control (χ2 for trend = 9.8, P = 0.002 [Fisher’s exact result]) subjects.
The observed prevalence of IGT was found to be significantly higher among the inactive (18.1%) than that in the very active (0.6%) study subjects, as shown in [Table 2]. The difference was statistically significant (P = 0.005). Similarly, the prevalence of IGT was 15.6% in the inactive versus 0% in the very active controls (P = 0.0001), as shown in [Table 2].
|Table 2: Level of physical activity and prevalence of impaired glucose tolerance/impaired fasting glycemia in the case/control populations|
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Similarly, the prevalence of IFG as shown in [Table 2], was higher in case subjects who engaged in sedentary lifestyle (6.3%) compared with those who were very active (0.3%), P < 0.05. Impaired fasting glucose was also found to be significantly higher among the inactive control subjects (4.4%) compared with the very active group (P < 0.05) as in [Table 2].
No significant difference was observed in the mean values of total cholesterol, HDL cholesterol, LDL cholesterol, and triglycerides in case and control subjects (P > 0.05) as shown in [Table 3].
|Table 3: Distribution of serum lipids in case and control subjects by gender|
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|Table 4: Comparison of the clinical and metabolic characteristics of the case and control populations|
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However, the distribution of serum lipids in cases and controls according to the presence of IGT showed the mean (SD) of total cholesterol (4.9 [0.88]) and LDL cholesterol (2.9 [0.82]) to be significantly higher among case subjects with IGT compared to those without IGT (P = 0.0001 and 0.002, respectively) as shown in [Table 3]. The mean (SD) triglyceride was also found to be higher in case subjects with IGT (1.3 [0.52]) than in those without IGT (1.2 [0.54]) though the difference was not statistically significant (P = 0.13). In case subjects with IGT, the mean (SD) HDL cholesterol was found to be lower (1.4 [0.42]) than in those without (1.5 [0.45]) IGT, the difference was, however, not significant (P = 0.070) as shown in [Table 3].
In control subjects with IGT, the mean (SD) values of total cholesterol (P = 0.041), LDL cholesterol (P = 0.32), and triglyceride (P = 0.004) were higher than in controls without IGT. The mean (SD) HDL cholesterol, however, was found to be the same in controls with and without IGT (P = 1.000) as shown in [Table 3].
| Discussion|| |
In this cross-sectional study, cases (FDR of T2DM) showed increased prevalence of IGT, IFG, and eventually developing diabetes. In most cases, this is accompanied by unfavorable BMI, WC, lifestyle, BP, and lipid profile. With the increasing prevalence of diabetes mellitus worldwide, the number of FDRs of persons with type 2 diabetes, and thus an increased risk of developing diabetes, will also increase, which means that identifying risk factors associated with susceptibility to diabetes becomes increasingly important.
This study showed a relatively higher prevalence of IGT at 28.1% (34.9% in females and 20% in males, P = 0.004) among the cases compared with controls at 18.1% (21.4% in females and 14.5% in males, P = 0.44). This finding is similar to prevalence of 20% in Western European population of adults (25 years and older). In the US, the prevalence of IGT varies from 15.6% to 20.3%,, which is similar to the findings among controls in this study. The International Diabetes Federation (IDF) reported prevalence of 26% in United Arab Emirates, which is similar to the finding in this study.
The prevalence observed in this study is also similar to what was observed in Dar-es-Salaam, Tanzania (20%). The extrapolated prevalence in Nigeria according to US Census Bureau International data base was 21.3%, which was similar to the prevalence among controls. In Jos, North Central Nigeria, the reported prevalence was 26% among FDRs, which is similar to the findings in this study.
The finding of higher prevalence of IGT among females is similar to the report of IDF expert committee and the observation by Bakari and Onyemelukwe in Northern Nigeria.
The prevalence of IFG in this study was found to be 10.3% and 5.6% among study and control subjects, respectively. This is lower than the reported prevalence of 12.6% and 16.3% from Denmark and France, respectively. In the US, a prevalence of 12.1% was reported, which is higher than what was observed in this study. The subjects in the American study were older than those in the index study (40 vs. 25 years), which may explain the difference. Studies from Asia (India, 11%; China, 12.7%; and Iran 17.3%) also reported higher prevalence rates compared with this study. These studies from Asia were larger multicenter epidemiological studies and these may account for the higher prevalence rates observed.
On the African front, Amoah et al. reported a prevalence of 5.5% in indigenous Ghanaian subjects aged 25–75 years, which is similar to the findings among controls. In Jos, North Central Nigeria, a prevalence of 9.3% was reported among the cases, which is similar to the finding in this study.
This study found a higher prevalence of IGT among the non-active cases compared to the physically active ones (18.1% vs. 10%, P = 0.005). Similarly, among controls, the prevalence of IGT was lower in those that were physically active (2.5%) compared to those that were inactive (15.6%), P = 0.0001. It is, however, interesting that subjects and controls that engaged in exercise had significantly lower prevalence of IGT than those who did not engage in exercise.
The higher risk of IGT, IFG, and eventually diabetes associated with the cases was amplified in the presence of overweight, obesity, and sedentary lifestyle. Obesity was associated with T2DM in the general population as well.
This study also found higher serum lipid level in both study and control subjects with IGT, which concurs with previous report.,, This is most likely because IGT and diabetes are associated with a higher prevalence of additional cardiovascular risk factors, which collectively result in a high-risk profile. Indeed, insulin resistance seems to play a major role in dyslipidemia in subjects with both normal and abnormal glucose tolerance, and appears to be the common element accounting for the cluster of atherogenic metabolic abnormalities found in the metabolic syndrome (IGT, hypertension, and dyslipidemia), which confers a high risk for cardiovascular disease.
The strength of this study borders on its design and contents. However, it is limited in its ability to allow definite generalizations to be made, and sequence of risk factor development could not be inferred. The study was designed to assess IGT (and by extension pancreatic beta cell function); insulin sensitivity and secretion are better indicators of pancreatic beta cell function and they can easily be assessed using homeostasis model assessment method, and this requires measurement of plasma insulin. Unfortunately, insulin assay could not be carried out as a part of this study.
Another limitation is that the study and control subjects were informed about the results and those diagnosed with T2DM are being followed up in the diabetes clinic but those with IGT and IFG were only counseled on appropriate lifestyle modifications as the study was not interventional.
| Conclusion|| |
In summary, the prevalence of IGT and IFG was higher in female cases (FDR of persons with T2DM) than that in controls of similar age and sex. Independent risk factors most closely associated with IGT were abnormal WC and WHR, FDR, elevated SBP, and DBP, whereas those closely associated with IFG were abnormal WC, FDR, and elevated SBP. These results emphasize the importance of controlling for all known diabetes risk factors, especially overweight and obesity, in FDR of people with T2DM.
These findings may prove useful in identifying a specific group of population at particular risk of developing metabolic disturbances known to predispose to cardiovascular disease and strongly support the regular screening of FDR of persons with T2DM.
Future studies on this topic may need to involve the assessment of the beta cell function so as to ascertain the level of secretory defect among the affected and perhaps genetic studies to establish the link between the patient and the FDR for better understanding and prospect of intervention.
Informed consent was obtained from all individual participants of this study.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
World Health Organization (WHO). Definition, diagnosis and classification of diabetes mellitus and its complications. Report of a WHO Consultation part 1: Diagnosis and classification of diabetes mellitus. 1999.
Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: Estimate for the year 2000 and projection 2030. Diabetes Care 2004;27:1047-53.
Grill V, Persson G, Carlsson S, Norman A, Alvarsson M, Ostensson CG. Family history of diabetes in middle-aged Swedish men is a gender unrelated factor which associates with insulinopenia in newly diagnosed diabetic’s subjects. Diabetologia 1999;42:15-23.
Park HS, Yim KS, Cho SI. Gender differences in familial aggregation of obesity-related phenotypes and dietary intake patterns in Korean families. Ann Epidemiol 2004;14:486-91.
Li JK, Ng MC, So WY, Chiu CK, Ozaki R, Tong PC et al
. Phenotypic and genetic clustering of diabetes and metabolic syndrome in Chinese families with type 2 diabetes mellitus. Diabetes Metab Res Rev 2006 22:46-52.
Ramachandran A, Snehalatha C, Satyavani K, Sivasankari S, Vijay V. Cosegregation of obesity with familial aggregation of type 2 diabetes mellitus. Diabetes Obes Metab 2000;2:149-54.
Dowse GK, Zimmet P. A model method for diabetes and other non-communicable disease field survey. World Health Stat Q 1992;45:360-73.
World Health Organization Expert Committee. Physical status, the use and interpretation of anthropometry. Report of a WHO Expert Committee. Technical Report Series 854. Geneva, Switzerland: WHO; 1995.
Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults--The Evidence Report. National Institutes of Health. Obes Res 1998Sep;6 Suppl 2:51S-209S. Review. No abstract available. Erratum in:Obes Res 1998Nov;6(6):464.
American Diabetes Association. Report of the expert committee on diagnosis and classification of diabetes mellitus. Diabetes Care 1997;20:1183-97.
National Diabetes Data Group. Classification and diagnosis of diabetes and other categories of glucose intolerance. Diabetes 1979;28:1039-57.
Gerstein HC, Yusuf S, Holman R, Bosch J, Pogue J; DREAM Trial Investigators. Rational, design and recruitment characteristics of a large, simple international trial of diabetes prevention. The DREAM Trial. Diabetologia 2004;47:1519-27.
Harris MI, Flegal KM, Cowie CC, Eberhardt MS, Goldstein DE, Little RR, et al
. Prevalence of diabetes, impaired fasting glucose and impaired glucose tolerance in US adult. The Third National Health and National Examination Survey (NHNES) 1988–1994. Diabetes Care 1998;21:518-24.
Harris MI, Eastman RC, Flegal KM et al
. Comparison of diabetes diagnostic categories in the US population according to the 1997 American Diabetes Association and 1980-85 WHO diagnostic criteria. Diabetes Care 1997;20:1859-62.
International Diabetes Federation (IDF). Diabetes atlas. BMC Fam Pract 2007;8:60-1.
McCarty DG, Swai AB, Kitange HM, Masuki G, Mtinangi BL, Kilima PM, et al
. Prevalence of diabetes mellitus and impaired glucose tolerance in rural Tanzania. Lancet 1989;1:871-5.
US Census Bureau International Data Base. 2004. Available at: https://www.census.gov/data/developers/data-sets/international-database.htm.
Mijinyawa BB. Prevalence of impaired glucose tolerance among first-degree relatives of persons with type 2 diabetes in Jos. National postgraduate Medical College of Nigeria. Unpublished Dissertation submitted to National Post Graduate Medical College of Nigeria for the award of fellowship in Internal medicine/EDM 2006.
Harris MI. Impaired glucose, prevalence and progression to NIDDM. Int Diabetes Fed Bull 1996;41:12-5.
Bakari AG, Onyemelukwe GC. Glucose intolerance among apparently healthy Hausa-Fulani in Northern Nigeria. Ann Afr Med 2004;3:32-4.
Glummer C, Jorgensen T, Borch-Johnson K. Prevalence of diabetes and impaired glucose regulation in a Danish population. Diabetes Care 2003;26:2335-40.
Balkau B, Eschwege E, Ducimetiere P, Richard JL, Warnet JM. The high risk of death by alcohol related disease in subjects diagnosed as diabetic and impaired glucose tolerance. The Paris prospective study after 15years of follow up. J Clin Epid 1991;44:465-70.
Ramachandran A, Snehalathan C, Kapar A, Vijay V, Mohan V, Das AK, et al
; Diabetes Epidemiology Study Group in India (DESI). High prevalence of diabetes and impaired glucose tolerance in India: National Urban Diabetes Survey. Diabetologia 2001;44:1094-01.
Dong Y, Gao W, Nan H; Quindao Epidemiology Study Group. The prevalence of diabetes and risk factors in Chinese population in Qingdao City. 18th International Diabetes Federation Congress, Paris, France 2003;24-9.
Amini M, Janghorbani M. Diabetes and impaired glucose regulation in first-degree relatives of patients with type 2 diabetes in Isfahan, Iran: Prevalence and risk factors. Rev Diabet Stud 2007;4:169-76.
Amoah AG, Dara PS, Trudy G, Osei K. Insulin resistance, beta-cell function and cardiovascular risk factors on Ghanaian with varying degrees of glucose tolerance. Ethn Dis 2002;12:3-10.
Onyemelukwe GC, Stafford WL. Serum lipids in Nigerians: The effect of diabetes mellitus. Trop Geogr Med 1981;33:323-8.
Folson AR, Szklo M, Stevens J, Liao F, Smith R, Eckfeldt JH. A prospective study of coronary heart disease in relation to fasting insulin, glucose and diabetes. The atherosclerosis risk in communities (ARIC) study. Diabetes Care 1977;20:935-42.
[Table 1], [Table 2], [Table 3], [Table 4]