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  1. Mustafa N, Kamarudin NA, Ismail AA, Khir AS, Ismail IS, Musa KI, et al.
    Diabetes Care, 2011 Jun;34(6):1362-4.
    PMID: 21498788 DOI: 10.2337/dc11-0005
    OBJECTIVE:
    To determine the prevalence of prediabetes and diabetes among rural and urban Malaysians.
    RESEARCH DESIGN AND METHODS:
    This cross-sectional survey was conducted among 3,879 Malaysian adults (1,335 men and 2,544 women). All subjects underwent the 75-g oral glucose tolerance test (OGTT).
    RESULTS:
    The overall prevalence of prediabetes was 22.1% (30.2% in men and 69.8% in women). Isolated impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) were found in 3.4 and 16.1% of the study population, respectively, whereas 2.6% of the subjects had both IFG and IGT. Based on an OGTT, the prevalence of newly diagnosed type 2 diabetes was 12.6% (31.0% in men and 69.0% in women). The prediabetic subjects also had an increased prevalence of cardiovascular disease risk factors.
    CONCLUSIONS:
    The large proportion of undiagnosed cases of prediabetes and diabetes reflects the lack of public awareness of the disease.
  2. Dagenais GR, Gerstein HC, Zhang X, McQueen M, Lear S, Lopez-Jaramillo P, et al.
    Diabetes Care, 2016 05;39(5):780-7.
    PMID: 26965719 DOI: 10.2337/dc15-2338
    OBJECTIVE: The goal of this study was to assess whether diabetes prevalence varies by countries at different economic levels and whether this can be explained by known risk factors.

    RESEARCH DESIGN AND METHODS: The prevalence of diabetes, defined as self-reported or fasting glycemia ≥7 mmol/L, was documented in 119,666 adults from three high-income (HIC), seven upper-middle-income (UMIC), four lower-middle-income (LMIC), and four low-income (LIC) countries. Relationships between diabetes and its risk factors within these country groupings were assessed using multivariable analyses.

    RESULTS: Age- and sex-adjusted diabetes prevalences were highest in the poorer countries and lowest in the wealthiest countries (LIC 12.3%, UMIC 11.1%, LMIC 8.7%, and HIC 6.6%; P < 0.0001). In the overall population, diabetes risk was higher with a 5-year increase in age (odds ratio 1.29 [95% CI 1.28-1.31]), male sex (1.19 [1.13-1.25]), urban residency (1.24 [1.11-1.38]), low versus high education level (1.10 [1.02-1.19]), low versus high physical activity (1.28 [1.20-1.38]), family history of diabetes (3.15 [3.00-3.31]), higher waist-to-hip ratio (highest vs. lowest quartile; 3.63 [3.33-3.96]), and BMI (≥35 vs. <25 kg/m(2); 2.76 [2.52-3.03]). The relationship between diabetes prevalence and both BMI and family history of diabetes differed in higher- versus lower-income country groups (P for interaction < 0.0001). After adjustment for all risk factors and ethnicity, diabetes prevalences continued to show a gradient (LIC 14.0%, LMIC 10.1%, UMIC 10.9%, and HIC 5.6%).

    CONCLUSIONS: Conventional risk factors do not fully account for the higher prevalence of diabetes in LIC countries. These findings suggest that other factors are responsible for the higher prevalence of diabetes in LIC countries.

  3. Tan CE, Emmanuel SC, Tan BY, Jacob E
    Diabetes Care, 1999 Feb;22(2):241-7.
    PMID: 10333940 DOI: 10.2337/diacare.22.2.241
    OBJECTIVE: The purpose of the 1992 Singapore National Health Survey was to determine the current distribution of major noncommunicable diseases and their risk factors, including the prevalence of diabetes and dyslipidemia, in Singapore.

    RESEARCH DESIGN AND METHODS: A combination of disproportionate stratified sampling and systematic sampling were used to select the sample for the survey. The final number of respondents was 3,568, giving a response rate of 72.6%. All subjects fasted for 10 h and were given a 75-g glucose load, except those known to have diabetes. Blood was taken before and 2 h after the glucose load. Diagnosis of diabetes was based on 2-h glucose alone.

    RESULTS: The age-standardized prevalence of diabetes in Singapore residents aged 18-69 years was 8.4%, with more than half (58.5%) previously undiagnosed. Prevalence of diabetes was high across all three ethnic groups. The prevalence of impaired glucose tolerance was 16.1%, that of hypertension was 6.5%, and 19.0% were regular smokers. The total cholesterol (mean +/- SD) of nondiabetic Singaporeans was 5.18 +/- 1.02 mmol/l; 47.9% had cholesterol > 5.2 mmol/l, while 15.4% had levels > 6.3 mmol/l. Mean LDL cholesterol was 3.31 +/- 0.89 mmol/l; HDL cholesterol was 1.30 +/- 0.32 mmol/l, and triglyceride was 1.23 +/- 0.82 mmol/l.

    CONCLUSIONS: Prevalence of diabetes was high across all three ethnic groups. Ethnic differences in prevalence of diabetes, insulin resistance, central obesity, hypertension, smoking, and lipid profile could explain the differential coronary heart disease rates in the three major ethnic groups in Singapore.
  4. van Eekelen A, Stokvis-Brantsma H, Frölich M, Smelt AH, Stokvis H
    Diabetes Care, 2000 Sep;23(9):1435-6.
    PMID: 10977050
  5. Islam N, Kazmi F, Chusney GD, Mattock MB, Zaini A, Pickup JC
    Diabetes Care, 1998 Mar;21(3):385-8.
    PMID: 9540020
    OBJECTIVE: To investigate whether microalbuminuria is associated with markers of the acute-phase response in NIDDM and whether there are ethnic differences in this association among the three main racial groups in Malaysia.

    RESEARCH DESIGN AND METHODS: NIDDM patients of Chinese, Indian, and Malay origin attending a diabetic clinic in Kuala Lumpur, Malaysia, were matched for age, sex, diabetes duration, and glycemic control (n = 34 in each group). Urinary albumin-to-creatinine ratio was measured in an early morning urine sample. Biochemical measurements included markers of the acute-phase response: serum sialic acid, triglyceride, and (lowered) HDL cholesterol.

    RESULTS: The frequency of microalbuminuria did not differ among the Chinese, Indian, and Malay patients (44, 41, and 47%, respectively). In Chinese patients, those with microalbuminuria had evidence of an augmented acute-phase response, with higher serum sialic acid and triglyceride and lower HDL cholesterol levels; and urinary albumin-to-creatinine ratio was correlated with serum sialic acid and triglyceride. The acute-phase response markers were not different in Indians, with microalbuminuria being high in even the normoalbuminuric Indians; only the mean arterial blood pressure was correlated with urinary albumin-to-creatinine ratio in the Indians. Malay NIDDM subjects had an association of microalbuminuria with acute-phase markers, but this was weaker than in the Chinese subjects.

    CONCLUSIONS: Microalbuminuria is associated with an acute-phase response in Chinese NIDDM patients in Malaysia, as previously found in Caucasian NIDDM subjects. Elevated urinary albumin excretion has different correlates in other racial groups, such as those originating from the Indian subcontinent. The acute-phase response may have an etiological role in microalbuminuria.

  6. Ali O, Tan TT, Sakinah O, Khalid BA, Wu LL, Ng ML
    Diabetes Care, 1993 Jan;16(1):68-75.
    PMID: 8422835 DOI: 10.2337/diacare.16.1.68
    OBJECTIVE: To determine the prevalence of diabetes mellitus and IGT in different ethnic groups living in the same physical environment and to find their relationship to nutritional status and dietary intake.

    RESEARCH DESIGN AND METHODS: The study was conducted among Malays and Orang Asli in six rural and urban locations in Malaysia. OGTTs were performed on 706 adult subjects > or = 18 yr of age. WHO criteria were used for diagnosing diabetes mellitus and IGT.

    RESULTS: The overall prevalence of diabetes mellitus and IGT among Orang Asli was 0.3 and 4.4% compared with 4.7 and 11.3%, respectively, among Malays. This increased prevalence of glucose intolerance among Malays was associated with higher levels of social development. Among rural Malays, the crude prevalence of diabetes in a traditional village was 2.8% and in the land scheme was 6.7%, whereas urban Malays had a prevalence of 8.2%. In contrast, the prevalence of IGT (10.5-14.8%) was higher among rural Malays, compared with 9.6% among urban Malays. Ethnic group, > or = 40 yr of age, an income > M$250, fewer daily activity, and obesity were associated with a higher prevalence of diabetes.

    CONCLUSIONS: Diabetes mellitus and IGT, which were more common among Malays than Orang Asli, were associated with more affluent life-styles and modernization.
  7. Aminian A, Vidal J, Salminen P, Still CD, Nor Hanipah Z, Sharma G, et al.
    Diabetes Care, 2020 03;43(3):534-540.
    PMID: 31974105 DOI: 10.2337/dc19-1057
    OBJECTIVE: To characterize the status of cardiometabolic risk factors after late relapse of type 2 diabetes mellitus (T2DM) and to identify factors predicting relapse after initial diabetes remission following bariatric surgery to construct prediction models for clinical practice.

    RESEARCH DESIGN AND METHODS: Outcomes of 736 patients with T2DM who underwent Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG) at an academic center (2004-2012) and had ≥5 years' glycemic follow-up were assessed. Of 736 patients, 425 (58%) experienced diabetes remission (HbA1c <6.5% [48 mmol/mol] with patients off medications) in the 1st year after surgery. These 425 patients were followed for a median of 8 years (range 5-14) to characterize late relapse of diabetes.

    RESULTS: In 136 (32%) patients who experienced late relapse, a statistically significant improvement in glycemic control, number of diabetes medications including insulin use, blood pressure, and lipid profile was still observed at long-term. Independent baseline predictors of late relapse were preoperative number of diabetes medications, duration of T2DM before surgery, and SG versus RYGB. Furthermore, patients who relapsed lost less weight during the 1st year after surgery and regained more weight afterward. Prediction models were constructed and externally validated.

    CONCLUSIONS: While late relapse of T2DM is a real phenomenon (one-third of our cohort), it should not be considered a failure, as the trajectory of the disease and its related cardiometabolic risk factors is changed favorably after bariatric surgery. Earlier surgical intervention, RYGB (compared with SG) and more weight loss (less late weight regain) are associated with less diabetes relapse in the long-term.

  8. Chan JCN, Lim LL, Luk AOY, Ozaki R, Kong APS, Ma RCW, et al.
    Diabetes Care, 2019 11;42(11):2022-2031.
    PMID: 31530658 DOI: 10.2337/dci19-0003
    In 1995, the Hong Kong Diabetes Register (HKDR) was established by a doctor-nurse team at a university-affiliated, publicly funded, hospital-based diabetes center using a structured protocol for gathering data to stratify risk, triage care, empower patients, and individualize treatment. This research-driven quality improvement program has motivated the introduction of a territory-wide diabetes risk assessment and management program provided by 18 hospital-based diabetes centers since 2000. By linking the data-rich HKDR to the territory-wide electronic medical record, risk equations were developed and validated to predict clinical outcomes. In 2007, the HKDR protocol was digitalized to establish the web-based Joint Asia Diabetes Evaluation (JADE) Program complete with risk levels and algorithms for issuance of personalized reports to reduce clinical inertia and empower self-management. Through this technologically assisted, integrated diabetes care program, we have generated big data to track secular trends, identify unmet needs, and verify interventions in a naturalistic environment. In 2009, the JADE Program was adapted to form the Risk Assessment and Management Program for Diabetes Mellitus (RAMP-DM) in the publicly funded primary care clinics, which reduced all major events by 30-60% in patients without complications. Meanwhile, a JADE-assisted assessment and empowerment program provided by a university-affiliated, self-funded, nurse-coordinated diabetes center, aimed at complementing medical care in the community, also reduced all major events by 30-50% in patients with different risk levels. By combining universal health coverage, public-private partnerships, and data-driven integrated care, the Hong Kong experience provides a possible solution than can be adapted elsewhere to make quality diabetes care accessible, affordable, and sustainable.
  9. Lim LL, Lau ESH, Kong APS, Davies MJ, Levitt NS, Eliasson B, et al.
    Diabetes Care, 2018 06;41(6):1312-1320.
    PMID: 29784698 DOI: 10.2337/dc17-2010
    OBJECTIVE: The implementation of the Chronic Care Model (CCM) improves health care quality. We examined the sustained effectiveness of multicomponent integrated care in type 2 diabetes.

    RESEARCH DESIGN AND METHODS: We searched PubMed and Ovid MEDLINE (January 2000-August 2016) and identified randomized controlled trials comprising two or more quality improvement strategies from two or more domains (health system, health care providers, or patients) lasting ≥12 months with one or more clinical outcomes. Two reviewers extracted data and appraised the reporting quality.

    RESULTS: In a meta-analysis of 181 trials (N = 135,112), random-effects modeling revealed pooled mean differences in HbA1c of -0.28% (95% CI -0.35 to -0.21) (-3.1 mmol/mol [-3.9 to -2.3]), in systolic blood pressure (SBP) of -2.3 mmHg (-3.1 to -1.4), in diastolic blood pressure (DBP) of -1.1 mmHg (-1.5 to -0.6), and in LDL cholesterol (LDL-C) of -0.14 mmol/L (-0.21 to -0.07), with greater effects in patients with LDL-C ≥3.4 mmol/L (-0.31 vs. -0.10 mmol/L for <3.4 mmol/L; Pdifference = 0.013), studies from Asia (HbA1c -0.51% vs. -0.23% for North America [-5.5 vs. -2.5 mmol/mol]; Pdifference = 0.046), and studies lasting >12 months (SBP -3.4 vs. -1.4 mmHg, Pdifference = 0.034; DBP -1.7 vs. -0.7 mmHg, Pdifference = 0.047; LDL-C -0.21 vs. -0.07 mmol/L for 12-month studies, Pdifference = 0.049). Patients with median age <60 years had greater HbA1c reduction (-0.35% vs. -0.18% for ≥60 years [-3.8 vs. -2.0 mmol/mol]; Pdifference = 0.029). Team change, patient education/self-management, and improved patient-provider communication had the largest effect sizes (0.28-0.36% [3.0-3.9 mmol/mol]).

    CONCLUSIONS: Despite the small effect size of multicomponent integrated care (in part attenuated by good background care), team-based care with better information flow may improve patient-provider communication and self-management in patients who are young, with suboptimal control, and in low-resource settings.
  10. Bhavadharini B, Mohan V, Dehghan M, Rangarajan S, Swaminathan S, Rosengren A, et al.
    Diabetes Care, 2020 11;43(11):2643-2650.
    PMID: 32873587 DOI: 10.2337/dc19-2335
    OBJECTIVE: Previous prospective studies on the association of white rice intake with incident diabetes have shown contradictory results but were conducted in single countries and predominantly in Asia. We report on the association of white rice with risk of diabetes in the multinational Prospective Urban Rural Epidemiology (PURE) study.

    RESEARCH DESIGN AND METHODS: Data on 132,373 individuals aged 35-70 years from 21 countries were analyzed. White rice consumption (cooked) was categorized as <150, ≥150 to <300, ≥300 to <450, and ≥450 g/day, based on one cup of cooked rice = 150 g. The primary outcome was incident diabetes. Hazard ratios (HRs) were calculated using a multivariable Cox frailty model.

    RESULTS: During a mean follow-up period of 9.5 years, 6,129 individuals without baseline diabetes developed incident diabetes. In the overall cohort, higher intake of white rice (≥450 g/day compared with <150 g/day) was associated with increased risk of diabetes (HR 1.20; 95% CI 1.02-1.40; P for trend = 0.003). However, the highest risk was seen in South Asia (HR 1.61; 95% CI 1.13-2.30; P for trend = 0.02), followed by other regions of the world (which included South East Asia, Middle East, South America, North America, Europe, and Africa) (HR 1.41; 95% CI 1.08-1.86; P for trend = 0.01), while in China there was no significant association (HR 1.04; 95% CI 0.77-1.40; P for trend = 0.38).

    CONCLUSIONS: Higher consumption of white rice is associated with an increased risk of incident diabetes with the strongest association being observed in South Asia, while in other regions, a modest, nonsignificant association was seen.

  11. Anjana RM, Mohan V, Rangarajan S, Gerstein HC, Venkatesan U, Sheridan P, et al.
    Diabetes Care, 2020 12;43(12):3094-3101.
    PMID: 33060076 DOI: 10.2337/dc20-0886
    OBJECTIVE: We aimed to compare cardiovascular (CV) events, all-cause mortality, and CV mortality rates among adults with and without diabetes in countries with differing levels of income.

    RESEARCH DESIGN AND METHODS: The Prospective Urban Rural Epidemiology (PURE) study enrolled 143,567 adults aged 35-70 years from 4 high-income countries (HIC), 12 middle-income countries (MIC), and 5 low-income countries (LIC). The mean follow-up was 9.0 ± 3.0 years.

    RESULTS: Among those with diabetes, CVD rates (LIC 10.3, MIC 9.2, HIC 8.3 per 1,000 person-years, P < 0.001), all-cause mortality (LIC 13.8, MIC 7.2, HIC 4.2 per 1,000 person-years, P < 0.001), and CV mortality (LIC 5.7, MIC 2.2, HIC 1.0 per 1,000 person-years, P < 0.001) were considerably higher in LIC compared with MIC and HIC. Within LIC, mortality was higher in those in the lowest tertile of wealth index (low 14.7%, middle 10.8%, and high 6.5%). In contrast to HIC and MIC, the increased CV mortality in those with diabetes in LIC remained unchanged even after adjustment for behavioral risk factors and treatments (hazard ratio [95% CI] 1.89 [1.58-2.27] to 1.78 [1.36-2.34]).

    CONCLUSIONS: CVD rates, all-cause mortality, and CV mortality were markedly higher among those with diabetes in LIC compared with MIC and HIC with mortality risk remaining unchanged even after adjustment for risk factors and treatments. There is an urgent need to improve access to care to those with diabetes in LIC to reduce the excess mortality rates, particularly among those in the poorer strata of society.

  12. Lim TO, Bakri R, Morad Z, Hamid MA
    Diabetes Care, 2002 Dec;25(12):2212-7.
    PMID: 12453963 DOI: 10.2337/diacare.25.12.2212
    OBJECTIVE: Bimodality in blood glucose (BG) distribution has been demonstrated in several populations with a high prevalence of diabetes and obesity. However, other population studies had not found bimodality, thus casting doubt on its universality. We address this question in four ethnic populations-namely Malay, Chinese, Indian, and the indigenous people of Borneo.

    RESEARCH DESIGN AND METHODS: A national health survey was conducted in Malaysia in 1996. A total of 18,397 subjects aged > or =30 years had post-challenge BG measurements taken. To test whether BG was consistent with a bimodal distribution, we fitted unimodal normal and skewed distribution as well a mixture of two normal distributions to the data by age and ethnic groups.

    RESULTS: Age-specific prevalence of diabetes varied from 1.3 to 26.3%. In all ethnic/age groups, the bimodal model fitted the log BG data better (likelihood ratio tests, all P values <0.001).

    CONCLUSIONS: Bimodality in BG distribution is demonstrable even in populations with a very low prevalence of diabetes and obesity. Previous studies that found unimodality had failed to detect the second mode because of inadequate sample size, bias due to treatment of subjects with known diabetes, and inclusion of subjects with type 1 diabetes in the sample. Bimodality implies that diabetes is a distinct entity rather than an arbitrarily defined extreme end of a continuously distributed measurement.
  13. Mathiesen ER, Ali N, Alibegovic AC, Anastasiou E, Cypryk K, de Valk H, et al.
    Diabetes Care, 2021 09;44(9):2069-2077.
    PMID: 34330786 DOI: 10.2337/dc21-0472
    OBJECTIVE: To compare the risk of severe adverse pregnancy complications in women with preexisting diabetes.

    RESEARCH DESIGN AND METHODS: Multinational, prospective cohort study to assess the prevalence of newborns free from major congenital malformations or perinatal or neonatal death (primary end point) following treatment with insulin detemir (detemir) versus other basal insulins.

    RESULTS: Of 1,457 women included, 727 received detemir and 730 received other basal insulins. The prevalence of newborns free from major congenital malformations or perinatal or neonatal death was similar between detemir (97.0%) and other basal insulins (95.5%) (crude risk difference 0.015 [95% CI -0.01, 0.04]; adjusted risk difference -0.003 [95% CI -0.03, 0.03]). The crude prevalence of one or more congenital malformations (major plus minor) was 9.4% vs. 12.6%, with a similar risk difference before (-0.032 [95% CI -0.064, 0.000]) and after (-0.036 [95% CI -0.081, 0.009]) adjustment for confounders. Crude data showed lower maternal HbA1c during the first trimester (6.5% vs. 6.7% [48 vs. 50 mmol/mol]; estimated mean difference -0.181 [95% CI -0.300, -0.062]) and the second trimester (6.1% vs. 6.3% [43 vs. 45 mmol/mol]; -0.139 [95% CI -0.232, -0.046]) and a lower prevalence of major hypoglycemia (6.0% vs. 9.0%; risk difference -0.030 [95% CI -0.058, -0.002]), preeclampsia (6.4% vs. 10.0%; -0.036 [95% CI -0.064, -0.007]), and stillbirth (0.4% vs. 1.8%; -0.013 [95% CI -0.024, -0.002]) with detemir compared with other basal insulins. However, differences were not significant postadjustment.

    CONCLUSIONS: Insulin detemir was associated with a similar risk to other basal insulins of major congenital malformations, perinatal or neonatal death, hypoglycemia, preeclampsia, and stillbirth.

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