Incidence and predictors of abnormal fasting plasma glucose among the university hospital employees in Thailand

diabetes research and clinical practice 79 (2008) 343–349

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Incidence and predictors of abnormal fasting plasma glucose among the university hospital employees in Thailand Wiroj Jiamjarasrangsi a,*, Vitool Lohsoonthorn a, Somrat Lertmaharit a, Somkiat Sangwatanaroj b a b

Department of Preventive and Social Medicine, Faculty of Medicine, Chulalongkorn University, Pathumwan, Bangkok 10330, Thailand Department of Internal Medicine, Faculty of Medicine, Chulalongkorn University, Pathumwan, Bangkok 10330, Thailand

article info

abstract

Article history:

The purposes of this study were to determine the incidence rates and predictors of type 2

Received 4 July 2007

diabetes and impaired fasting plasma glucose (IFG) among the employees of a university

Accepted 12 September 2007

hospital in Bangkok, Thailand. Totally 2370 and 1619 workers without diabetes and IFG at

Published on line 22 October 2007

baseline, respectively, who were +35 years old were followed up during 2001–2005. Type 2 diabetes incidence rates (95% CI) were 13.6 (8.4–22.3) and 6.4 (4.5–9.1) per 1000 PYs, respec-

Keywords:

tively, for men and women, while those of the IFG were 37.8 (26.3–54.4) and 23.6 (19.3–29.0)

Type 2 diabetes

per 1000 PYs, respectively, for both genders. Baseline FBS predicted future IFG risk even at

Impaired fasting glucose

the levels as low as 63–70 mg/dl. The OR (95% CI) of IFG for those with baseline FPG of 63–70,

Incidence

71–80, and >80 mg/dl—compared to those with baseline FPG 62 mg/dl—were 2.51 (1.12–

Risk factors

5.64), 5.39 (2.51–11.56), and 8.30 (3.67–18.75), respectively. Future diabetes risk was observed only in those with baseline FPG of 96 mg/dl or higher, with the OR (95% CI) of 6.0 (2.29–15.75). In conclusion, baseline FPG even at the level as low as 63–70 mg/dl predicts future IFG risk among a hospital employee group in Thailand, while increased diabetes risk was found only in those at the FBS level of 96 mg/dl. # 2007 Elsevier Ireland Ltd. All rights reserved.

1.

Introduction

Changes in human environment, behaviors, and way-of-life during the last 50 years have resulted in the worldwide epidemic of type 2 diabetes including Thailand [1,2]. The number of people with type 2 diabetes is estimated to increase rapidly within the next 25 years. Adult populations are particularly affected. It was estimated that the number of people with diabetes in adults aged 20 years and over, in Thailand will increase from 1,017,000 in 2000 to 1,923,000 in 2025 [2].

Up until now, limited data existed about the incidence of type 2 diabetes and other abnormal plasma glucose specifically for Thai population. Only one recent study reported the incidence rates of type 2 diabetes among professional workers in Bangkok [3], however, few predicting variables were included in the analysis. The purposes of this study were to determine the incidence rates of abnormal plasma glucose (namely type 2 diabetes and impaired fasting plasma glucose or IFG) among the employees of a university hospital in Bangkok, Thailand. We also aimed at examining the prospective associations between conventional cardiovascular

* Corresponding author. Tel.: +66 2 2564000x3700; fax: +66 2 2564292. E-mail address: [email protected] (W. Jiamjarasrangsi). 0168-8227/$ – see front matter # 2007 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.diabres.2007.09.008

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diabetes research and clinical practice 79 (2008) 343–349

risk factors and biochemical parameters and future type 2 diabetes and IFG risks.

2.

Material and methods

2.1.

Study population

The university hospital contained 1200 beds and employed totally 5000 workers in 2001. As the annual fasting plasma glucose was offered only for workers who were 35 years of age or older, the target population for this study were those who were +35 years old who had participated in the annual physical checkup at least once during years 2001–2004.

2.2.

Survey procedure

Personal demographic data (such as gender, date of birth, educational level) was obtained from the computerized database of the hospital. Additional information about individual’s personal and family history of disease, cigarette smoking, and alcoholic consumption was obtained by a questionnaire survey, which was conducted once in 2003. Annual health examinations were conducted during 2001– 2005. Totally 494 (17.4%), 1307 (46.0%), 371 (13.1%), 459 (16.1%), and 159 (5.6%) were first examined consecutively during this period. After an overnight fast, the participants underwent the anthropometric measurements and blood samples. Weight, height, and blood pressure (in the sitting position) were measured by staff nurses. Fasting plasma glucose, serum total cholesterol, triglycerides, uric acid, blood urea nitrogen (BUN), creatinine, alanine aminotransferase (ALT), aspartate aminotransferase (AST), and alkaline phosphatase (ALK) were measured in a standardized manner at the biomedical laboratory of the hospital. Similar procedures were utilized in the follow-up examinations.

2.3.

Follow-up

In the study of type 2 diabetes incidence rate, participants without type 2 diabetes at baseline were followed up until having the disease or until the last available annual examination result for those who did not develop the disease during the follow-up period (2002–2005). In the determination of IFG incidence rate, only participants without type 2 diabetes or IFG at baseline were included. They were then followed until having IFG or until the last available examination year for those who have not developed IFG. Participants who had only one annual examination result were excluded from the analysis.

2.4.

Definitions

Diagnosis of diabetes was defined according to the American Diabetic Association (ADA) criteria, i.e. when FPG level was 126 mg/dl (7.0 mmol/l) or having history of diabetes diagnosed by physician. For impaired fasting glucose (IFG) or prediabetes was defined as those with FPG levels 100 mg/dl (5.6 mmol/l) but <126 mg/dl (7.0 mmol/l) [4]. Body mass index (BMI) was calculated as (weight in kg)/ (height in meters)2. Physical status of individual was classified

basing on the BMI as: underweight for BMI < 18.5 kg/m2; normal for BMI 18.5–22.9 kg/m2; overweight for BMI 23.0– 24.9 kg/m2; obesity I for BMI 25.0–29.9 kg/m2; obesity II for BMI 30.0 kg/m2 [5]. Blood pressure was classified as normal (systolic blood pressure or SBP < 120 mmHg and diastolic blood pressure or DBP < 80 mmHg), prehypertension (SBP = 120–139 or DBP = 80– 89 mmHg), stage 1 hypertension (SBP = 140–159 or DBP = 90– 99 mmHg), or stage 2 hypertension (SBP  160 or DBP  100 mmHg) according to the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC-7) [6]. Total serum cholesterol level was categorized into desirable (<200 mg/dl), borderline high (200–239 mg/dl), or high (240 mg/dl); and triglyceride was categorized into normal (<150 mg/dl), borderline (150–199 mg/dl), high (200–499 mg/ dl), and very high (500 mg/dl) according to the Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (ATP III) [7]. Serum uric acid, BUN, creatinine, AST, ALT, and ALK were classified into quartile. Furthermore, FBS, BMI, systolic and diastolic blood pressure, and serum lipid levels were also classified into quartile (in addition to their traditional classifications described above) to assure comparable numbers of participants in each group and facilitate detailed examination about their associations with abnormal plasma glucose levels.

2.5.

Statistical analysis

The diabetes and IFG incidence rates among those without the conditions at baseline, as well as their corresponding 95% confidence intervals (CIs), were calculated assuming the Poisson distribution of the disease occurrence [8]. Due to unequal follow-up period for each individual, the diabetes or IFG incidence rates (IRs) were calculated as number of new diabetes or IFG cases divided by person–years (PYs) of followup and reported as rate per 1000 PYs. Person–time for each individual was calculated as the period of time between the first survey year until the year of first diabetes or IFG diagnosis or until the last survey year for those without diabetes or IFG diagnosis. In the comparison among the normal, IFG, and type 2 diabetes groups, means (standard deviation, S.D.) or medians (interquartile ranges) were calculated for continuous variables with normal or skewed distributions, respectively, while proportions (S.D.) were calculated for categorical variables. Skew data was log transformed and Anova was then used to assess the significant difference among groups. Test for trend among these FPG groups was also conducted by using Kruskal–Wallis test [9]. Separated multivariable logistic regression models were used to assess the associations between abnormal fasting plasma glucose status (normal versus IFG or type 2 diabetes; dependent variables) and anthropometric measures, physiological and biochemical parameters (independent variables). Backward selection procedures were used in the statistical modeling. Variables with p-value <0.2 were eligible for addition into the modeling procedures, and p-value of <0.05 was the cutoff for the statistically significant level [10]. Adjusted odds ratios (95% CI) were presented for the final models.

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diabetes research and clinical practice 79 (2008) 343–349

3.

Results

3.2.

3.1.

Subject characteristics

Sixteen men and 32 women developed type 2 diabetes, while 29 men and 93 women developed IFG during the follow-up periods. The overall IFG and type 2 diabetes incidence rate for men was approximately 1.6 and 2.1 times higher than those for women [the IFG incidence rates (95% CIs) were 37.8 (26.3–54.4) and 23.6 (19.3–29.0) per 1000 PYs, respectively, for men and women; type 2 diabetes incidence rates (95% CIs) were 13.6 (8.4–22.3) and 6.4 (4.5–9.1) per 1000 PYs, respectively, for both genders] (Table 1). In women, increasing IFG incidence rates according to age was demonstrated in the 35–59 age range, while that pattern for type 2 diabetes incidence rates was demonstrated at 40–64 years age range. Among men, such pattern was shown only for type 2 diabetes in the 35–59 age range.

Of all 3243 workers who were 35–60 years old and eligible for the annual fasting glucose examination during 2001–2005, 2097 workers (64.7%) participated in both health examination and baseline questionnaire survey, while 693 workers (21.4%) participated only in the baseline health examination. These two worker groups (2790 persons) were included in this analysis and amount to 86.0% of the target population. Detailed analysis showed that while the non-participants contained higher proportion of male workers (29.0% versus 19.7%) with higher educational level (53.1% versus 50.5% for those with +13 years of education), they were quite similar to the participants according to age and work duration. The mean age (S.D.) was 42.7 (7.6) years old and the average working duration (S.D.) was 18.1 (7.7) years. Of all 2790 workers included in the study, 344 (12.3%) and 105 (3.8%) workers had IFG and type 2 diabetes, respectively, at baseline. Of 2685 workers without type 2 diabetes at baseline, 2370 workers (88.3%) participated +2 annual examination years and were followed up for the determination of type 2 diabetes incidence rate. The remaining 315 non-participants were slightly younger and had lower baseline FBS level than the participants (mean ages were 42.0 and 44.2 years, with p < 0.05; mean baseline FBS levels were 86.3 and 89.8 mg/dl, with p < 0.05, respectively, for non-participant and participant groups). However, their baseline BMI levels were comparable (means baseline BMI were 23.6 and 23.7, with p > 0.05, respectively, for non-participant and participant groups). Of 2341 workers without IFG or type 2 diabetes at baseline, 1619 workers (69.1%) participated +2 annual examination years and were followed up for the determination of IFG incidence rate. Overall, the 722 non-participants were slightly younger than the participant (mean ages at baseline were 42.1 and 44.0 years, respectively, for both groups, with p < 0.05). However, their baseline BMI (23.5 and 23.4 for non-participants and participants, with p > 0.05) and FBS (86.0 and 87.6 mg/dl for nonparticipants and participants, with p < 0.05) were comparable. The proportions of gender and those with family history of diabetes were comparable between all participant and nonparticipant groups. The median (range) of follow-up time was 3 (1–4) years.

3.3.

Incidence of abnormal plasma glucose

Cardiovascular risk profile

Comparison of baseline clinical and metabolic parameters across the FPG statuses at the end of the follow-up period showed significant trend of increase (from the normal FPG group, the incidence IFG group, the incidence diabetes group, to the prevalence diabetes group) for age, BMI, systolic and diastolic blood pressures, FPG level, serum triglyceride level, serum ALT and AST, and the AST to ALT ratio in men and women (Tables 2 and 3). However, significant increase trend across groups for serum cholesterol, uric acid, and the ALP were shown only in women. These parameters for the normal FPG group were significantly lower than those for the other groups, particularly in women. No obvious trend was found among these groups for the prevalence of cigarette smoking, alcohol drinking, family history of diabetes, and those with less than or equal to 6 years of education.

3.4.

Predictors of abnormal FPG

Univariable analyses showed that the gender, age at the start of the follow-up, baseline systolic and diastolic blood pressure, baseline levels of age, BMI, FPG, serum triglyceride, BUN, uric acid, AST, ALT, and AST to ALT ratio were significantly associated with both IFG and type 2 diabetes risks, while baseline levels of serum cholesterol and creatinine were also significantly associated with IFG risk. However, multivariable analyses showed that only baseline diastolic blood pressure,

Table 1 – Incidence rates (per 1000 person–years) of abnormal plasma glucose according to age and gender Age-group (year)

Female IFG #c/#PYs

Male Diabetes

IR (95% CI)

30–34 35–39 40–44 45–49 50–54 55–59 60–64

1/69 12/884 25/1203 17/756 23/635 14/338 1/51

14.5 13.6 20.8 22.5 36.2 41.4 19.6

(2.0–102.9) (7.7–23.9) (14.0–30.8) (14.0–36.2) (24.1–54.5) (24.5–69.9) (2.8–139.2)

Total

93/3936

23.6 (19.3–29.0)

#c/#PYs 0/72 6/1116 5/1427 5/932 7/860 7/510 2/72 32/4989

IR (95% CI) 0.0 5.4 3.5 5.4 8.1 13.7 27.8

(2.4–12.0) (1.5–8.4) (2.2–12.9) (3.9–17.1) (6.5–28.8) (7.0–111.1)

6.4 (4.5–9.1)

IFG #c/#PYs 0/2 8/182 8/224 4/157 3/102 3/85 3/15 29/767

Diabetes

IR (95% CI) 0 44.0 35.7 25.5 29.4 35.3 200.0

(22.0–87.9) (17.9–71.4) (9.6–67.9) (9.5–91.2) (11.4–109.4) (64.5–620.1)

37.8 (26.3–54.4)

#c/#PYs

IR (95% CI)

0/3 2/286 3/324 2/235 5/174 4/126 0/26

0.0 7.0 9.3 8.5 28.7 31.7 0.0

16/1174

13.6 (8.4–22.3)

(1.8–28.0) (3.0–28.7) (2.1–34.0) (12.0–69.0) (11.9–84.6)

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diabetes research and clinical practice 79 (2008) 343–349

Table 2 – Baseline clinical and metabolic parameters according to plasma glucose levels (men) Characteristics Mean  S.D. Age (year)a BMI (kg/m2) SBP (mmHg) DBP (mmHg) FBS Cholesterol Triglyceridea BUN Cr Uric acid ASTa ALTa AST to ALT ratioa ALPa %  S.D. Smoking Alcohol drinking Family history of DM Education 6 years

Normal FPG group (n = 400)

Incidence IFG group (n = 47)

Incidence DM group (n = 16)

Prevalence DM group (N = 36)

43  11 24.1  0.2 127.0  0.9 76.7  0.6 91.8  0.5 216.7  2.0 121.5  96 13.5  0.2 0.96  0.01 6.3  0.1 24  10 26  20 0.9  0.5 68  22

43  10 24.5  0.6 132.7  2.7 80.9  1.8 101.7  1.4b 220.4  4.8 140  118b 13.9  0.5 0.94  0.02 6.4  0.2 27  15b 39  46b 0.8  0.4 74  31

49.5  11 27.0  1.0b 139.9  5.4b 85.5  3.0b 102.3  4.7b 216.6  7.4 199.5  179.5 15.1  1.4 0.96  0.04 6.5  0.3 26.5  7 32  27 0.8  0.4 74.5  22

48  9.5b,c 26.9  0.6b,c 138.9  2.9b 81.7  1.7 149.1  5.7b,c,d 221.2  6.4 175  134 12.7  0.5 0.93  0.03 5.8  0.2 26  16 37.5  35.5b 0.7  0.3b 78  25

5.8  1.2 42.0  2.5 18.0  1.9 13.2  1.7

2.1  2.1 31.9  6.8 21.3  6.0 14.3  5.4

12.5  8.3 37.5  12.1 6.3  6.1 28.6  12.1

5.6  3.8 33.3  7.9 22.2  6.9 23.5  7.3

Test for trend <0.05 <0.05 <0.05 <0.05 <0.05 ns <0.05 ns ns ns <0.05 <0.05 <0.05 ns

ns ns ns ns

ns = Not statistically significant. Median  interquartile range was shown instead of mean  standard deviation. b Significantly different from the normal FPG group. c Significantly different from the incidence IFG group. d Significantly different from the incidence DM group. a

Table 3 – Baseline clinical and metabolic parameters according to plasma glucose levels (women) Characteristics Mean  S.D. Age (year)a BMI (kg/m2) SBP (mmHg) DBP (mmHg) FBS Cholesterol Triglyceridea BUN Cr Uric acid ASTa ALTa AST to ALT ratioa ALPa %  S.D. Smoking Alcohol drinking Family history of DM Education 6 years

Normal FPG group (n = 1759)

Incidence IFG group (n = 116)

Incidence DM group (n = 32)

Prevalence DM group (N = 69)

43  11 23.3  0.1 119.4  0.4 69.8  0.3 88.0  0.2 211.9  0.9 81.5  54 11.8  0.1 0.73  0.00 4.4  0.0 19  6 15  9 1.2  0.5 62  24

48.5  10b 26.6  0.4b 131.4  1.8b 75.6  1.2b 100.7  0.9b 224.3  3.7b 106  79b 11.9  0.3 0.72  0.01 5.0  0.1b 20  8b 18  12b 1.1  0.4b 68  26b

48.5  14 26.9  0.8b 131.2  3.3b 76.0  2.3b 104.3  2.7b 220.0  6.9b 120  91b 12.5  0.6 0.74  0.02 5.0  0.2b 21  13b 26  21.5b,c 0.8  0.4b 75.5  25b,c

50  11b 27.6  0.6b 134.6  2.5b 78.3  1.4b 163.6  6.8b,c,d 229.6  5.6b 143  75b,c 12.4  0.4 0.72  0.02 5.1  0.2b 21  9b 25  15b 0.9  0.3b 72  35b,c

2.6  0.4 36.5  1.1 15.9  0.9 24.4  1.0

0.9  0.9 33.6  4.4 20.7  3.8 21.1  3.8

ns = Not statistically significant. Median  interquartile range was shown instead of mean  standard deviation. b Significantly different from the normal FPG group. c Significantly different from the incidence IFG group. d Significantly different from the incidence DM group. a

0.0  0.0 28.1  7.9 18.8  6.9 24.1  7.9

7.2  3.1c 50.7  6.0 20.3  4.8 30.3  5.7

Test for trend <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 ns ns <0.05 <0.05 <0.05 <0.05 <0.05

ns ns ns ns

diabetes research and clinical practice 79 (2008) 343–349

Table 4 – Multiple logistic regression analysis results for the IFG and type 2 diabetes risk Baseline characteristics

OR (95% CI)

p-Value

IFG vs. normal Diastolic blood pressure (DBP) Quartile I (63 mmHg) Quartile II (64–70 mmHg) Quartile III (71–80 mmHg) Quartile IV (>80 mmHg

1.00 0.99 (0.53–1.87) 1.87 (1.04–3.36) 2.46 (1.28–4.74)

ns <0.05 <0.01

Triglyceride (TG) Normal (<150 mg/dl) Borderline (150–199 mg/dl) High (200–499 mg/dl) Very high (500 mg/dl)

1.00 1.92 (1.11–3.34) 1.93 (1.07–3.48) 4.22 (0.36–49.49)

<0.05 <0.05 ns

Fasting blood sugar (FBS) Quartile I (62 mg/dl) Quartile II (63–70 mg/dl) Quartile III (71–80 mg/dl) Quartile IV (>80 mg/dl)

1.00 2.51 (1.12–5.64) 5.39 (2.51–11.56) 8.30 (3.67–18.75)

<0.05 <0.001 <0.001

DM vs. normal Body mass index (BMI) Underweight/Normal (22.9 kg/m2) Overweight (23.0–24.9 kg/m2) Obesity I (25.0–29.9 kg/m2) Obesity II (30.0 kg/m2)

1.00 2.21 (0.86–5.68) 2.45 (1.01–5.90) 4.16 (1.55–11.16)

ns <0.05 <0.01

Fasting blood sugar (FBS) Quartile I (83 mg/dl) Quartile II (84–89 mg/dl) Quartile III (90–95 mg/dl) Quartile IV (96 mg/dl)

1.00 0.62 (0.17–2.34) 0.64 (0.17–2.43) 6.00 (2.29–15.75)

ns ns <0.001

Alanine aminotransferase (ALT) Quartile I (13 mg/dl) Quartile II (14–17 mg/dl) Quartile III (18–25 mg/dl) Quartile IV (26 mg/dl)

1.00 3.02 (0.58–15.81) 6.09 (1.35–27.45) 9.48 (2.17–41.40)

ns <0.05 <0.01

ns = Not statistically significant.

serum triglyceride, and FBS levels were independently and significantly associated with increased IFG risk, while baseline BMI, highest quartile of FBS, ALT levels were independently associated with increased diabetes risk (Table 4). Dose– response patterns were also demonstrated for all of these associations. Including interaction terms among these parameters did not improve the prediction efficiency of the final models (result not shown).

4.

Discussion

In this study, we reported the incidence rates of abnormal fasting plasma glucose among predominantly female employees in a university hospital in Bangkok, Thailand. The overall incidence rates of type 2 diabetes were 6.4 and 13.6 per 1000 PYs, respectively, for female and male employees, while those incidence rates of IFG were 23.6 and 37.8 per 1000 PYs, respectively, for both genders. Individual who would develop IFG or type 2 diabetes had already shown certain abnormal test results at baseline survey. However, only higher BMI, elevated FBS and ALA levels were independent predictors of type 2

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diabetes, whereas elevated DBP, TG, and FBS were significant factors predicting higher risk of incident IFG. Our reported type 2 diabetes incidence rates (6.4 and 13.6 per 1000 PYs, respectively, for female and male employees) were comparable to that reported previously by Aekplakorn et al. among the employees of a state enterprise in Thailand (11.3 per 1000 PYs overall) [11], although they used the 2-h oral glucose tolerance test in the diabetes diagnosis. When comparing to studies among other Asian Pacific populations with comparable age range, our reported diabetes incidence was comparable to those among Taiwanese population (14.4 per 1000 PYs overall) [12] and Japanese population (13.8 per 1000 PYs for men office workers) [13]. Concerning the IFG incidence rate, only one such report existed, which was conducted among older Australians by Cugati et al. [14]. They reported the IFG incidence rates of 14.7 and 17.2 per 1000 PYs, respectively, for women and men age +49 years. Our reported IFG incidence rates (23.6 and 37.8 per 1000 PYs, respectively, for women and men) were approximately twice higher than these reported incidence rates among the Australians. Our observation about the association between baseline BMI, blood pressure, TG, FBS, and ALT levels and future risk of IFG and type 2 diabetes was consistent with previous studies [14–16]. Concerning baseline FBS level, we found that individuals with the level even as low as 63–70 mg/dl had significantly higher IFG risk compared to those with lower baseline FBS level. At higher FBS levels, the IFG risk increases with an obvious step-wise manner. However, increased risk of type 2 diabetes was shown only for those with baseline FBS of 96 mg/dl or higher. Detailed investigation revealed that type 2 diabetes risk was not increase for those with baseline FBS of less than 100 mg/dl, the current cut-off point for IFG (result not shown). The explanation for these findings is not clear, but might be due to a real physiological phenomenon, a random error due to too small sample size, or a biased effect from incomplete follow-up in our study. Recent evidence is accumulating about the association between baseline ALA level and diabetes risk [17–19]. Our study also demonstrated this association, but its details will be presented in a separate report. Although our report revealed the age-related trends for incidence IFG and diabetes, particularly in women, further analysis did not show that age was an independent predictor for these conditions. Its crude associations with future IFG and diabetes risks were largely explained by higher BMI and baseline FBS levels according to age. While most of previous studies reported similar type 2 diabetes risk between women and men [20–23], some studies reported gender discrepancy in the diabetes risk. Haffner et al. conducted study among the Mexican Americans/non-Hispanic whites and reported that type 2 diabetes incidence was 8.13 (95% confidence interval, CI 1.10–59.9) per 1000 PYs in men and 3.62 (95% CI 1.37–9.55) per 1000 PYs in women [24]. Lipscombe and Hux also reported that type 2 diabetes incidence rate among Canadian men was higher than women, particularly among those with +50 years of age [25]. Our result also showed that the risk of type 2 diabetes and IFG risks were approximately twice higher among men than women. However, detailed analyses showed that gender predicted neither

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future IFG nor diabetes risk. The crude association between gender and IFG or type 2 diabetes risks was mainly due to higher baseline BMI and FBS levels among men. Some limitations needed to be mentioned in our study. Approximately 11.7 and 30.9% of eligible subjects lost followup in the diabetes and IFG analyses, respectively. However, detailed investigation showed that participant and nonparticipant groups were quite comparable according to age, baseline BMI and FBS levels, gender composition, and proportion of individuals with family history of diabetes. Anthropometric measures of abdominal obesity such as waist circumference and waist/hip ratio were not measured at baseline examination. We were then unable to investigate the association between central obesity and diabetes incidence. However, data from one study indicated that, although waist circumference and waist/hip ratio were superior to BMI in terms of the diabetes association in men, no differences were found in these three measures in women [26]. More than three-fourths of our study participants were women. Furthermore, a recent meta-analysis suggests that measures of overall obesity (BMI) and measures of central obesity (waist/ hip ratio and waist circumference) performed equally well in predicting type 2 diabetes [27]. We did not use the 2-h oral glucose tolerance test in the diagnosis of diabetes diagnosis. Hence, we might have underestimated the incidence of diabetes [28]. In conclusion, we reported higher IFG and type 2 diabetes risks in men than women among working population in a university hospital in Bangkok, Thailand. Higher BMI, elevated FBS, and ALA levels were independent predictors of type 2 diabetes, whereas elevated DBP, TG, and FBS were significant factors predicting higher risk of incident IFG. Future IFG risk was substantial even for those with baseline FBS level as low as 63–72 mg/dl, while type 2 diabetes risk was not found at the baseline FBS level lower than 100 mg/dl, the lower limit of current diagnostic criteria for abnormal fasting glucose.

[4]

[5]

[6]

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[8] [9] [10]

[11]

[12]

[13]

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[15]

[16]

Acknowledgements This project was supported by Chulalongkorn Memorial Hospital and Chulalongkorn University.

[17]

Conflict of interest The authors state that they have no conflict of interest. [18]

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