Sage Journals: Discover world-class research

Abstract

OBJECTIVES:

Prior research has focused on the relationship between weight change and incidence of metabolic syndrome. Change in body mass index (BMI), components of metabolic syndrome and metabolic syndrome status were investigated over 1 year of follow-up.

Methods:

Subjects with metabolic syndrome from a community health screening project were recruited. Logistic regression was used to analyse the disappearance or remission of metabolic syndrome during 1 year according to changes in BMI, waist circumference, triglycerides, blood pressure, high-density lipoprotein-cholesterol (HDL-C) and fasting plasma glucose (FPG).

Results:

The study included 490 subjects with metabolic syndrome. After 1 year, metabolic syndrome had disappeared in 30.0% (147/490) of subjects. Decreased triglycerides, blood pressure and HDL-C were significantly associated with the 1-year disappearance of metabolic syndrome, whereas BMI, waist circumference and FPG levels were not.

Conclusions:

Short-term weight reduction has no impact on the status of metabolic syndrome. The disappearance of metabolic syndrome was common during a 1-year follow-up. This finding might impact on the treatment and management of people with metabolic syndrome.

Keywords

Metabolic syndrome Body mass index Remission

Introduction

In 1993, Reaven proposed the term “Syndrome X” to describe insulin resistance syndrome, which is now known as metabolic syndrome.¹ Metabolic syndrome was found to increase the risk of cardiovascular disease, type 2 diabetes mellitus and all-cause mortality.^2,3 Most research on the risk factors associated with metabolic syndrome has involved cross-sectional surveys.⁴ Some research has reported on the incidence of metabolic syndrome in Asia;^{5 – 7} however, there have been no reports on the disappearance of metabolic syndrome without intervention in Asian people. Some studies have investigated weight change and the incidence of metabolic syndrome,⁵ but there has been little focus on the relationship between five components of metabolic syndrome (namely, fasting plasma glucose [FPG], waist circumference, blood pressure, triglyceride levels, high-density lipoprotein-cholesterol [HDL-C] levels), body mass index (BMI) and the incidence of metabolic syndrome. The present study investigated whether short-term fluctuations in any of these components were associated with the disappearance of metabolic syndrome without intervention.

Subjects and methods

Study Population

This retrospective study analysed data from the Li-Shin Outreach Neighbourhood Screening (LIONS) programme, the design of which has been described previously.⁸ The LIONS programme recruited citizens of Pingzhen City, Taiwan, who were aged > 30 years. Residents went through multiple health screening, undertaken by an outreach community service, once a year from 2002 onwards. During the study period (2002 – 2008), data on disease and health status were collected annually for each consecutively enrolled subject. Target diseases of the screening programme included three chronic conditions (hyperlipidaemia, hypertension and diabetes mellitus) and five cancers (liver, breast, oral, cervical and colon cancer).

The project was conducted at the Taiwan Landseed Hospital, Pingzhen City, Taiwan. Eligible subjects had to have 2 years of consecutive data between 2002 and 2008, and metabolic syndrome, according to the diagnostic criteria described below, in their first year in the study. Subjects who were pregnant, lost to follow-up during the second year and those with missing data on any of the risk factors associated with metabolic syndrome (including sex, age, height, weight, smoking status, alcohol consumption, betel nut consumption, waist circumference, systolic or diastolic blood pressure [SBP/DBP], triglycerides, HDL-C, FPG) and receiving medication to treat hypertension, diabetes and hyperlipidaemia were excluded from the study.

The study protocol was approved by the Institutional Review Board of the Taiwan Landseed Hospital (IRB-10-07). Written informed consent was obtained from all participants.

Diagnosis of Metabolic Syndrome

Metabolic syndrome was defined according to Taiwan Department of Health criteria, using the modified American Heart Association/National Cholesterol Education Program Adult Treatment Panel III (AHA/NECP ATP III) definition based on Asian waist circumference.^9,10 Metabolic syndrome was diagnosed in patients who met three or more of the following criteria: 1, central obesity (waist circumference ≥ 90 cm for men and ≥ 80 cm for women); 2, elevated triglycerides (≥ 150 mg/dl); 3, decreased HDL-C (< 40 mg/dl for men and < 50 mg/dl for women); 4, elevated blood pressure (SBP ≥ 130 mmHg or DBP ≥ 85 mmHg) or normal blood pressure controlled with anti -hypertensive therapy; 5, elevated FPG (FPG ≥ 100 mg/dl) or normal FPG controlled with diabetes medication.

Subjects were categorized as ‘yes', ‘quit', or ‘no' according to smoking status, betel nut and alcohol consumption.

One-Year Analysis of Metabolic Syndrome

The five components of metabolic syndrome and BMI were analysed during a 1-year period by comparing data taken over 2 years; each component of metabolic syndrome and BMI was measured once in year 1 and once in year 2 for each patient. The disappearance of metabolic syndrome was defined as absence of three or more of the five components described above. The differences between the values of the first and second year in each of the five components and BMI were calculated: difference in component value (except HDL-C) = first-year minus second-year value; difference in HDL-C value = second-year minus first-year value. Data were divided into quartiles based on a nearly equal number of subjects, and the quartile containing patients with no/little difference was set as the reference group for comparison of each component of metabolic syndrome and BMI.

Statistical Analyses

All analyses were performed using SPSS^® software, version 14.0 (SPSS Inc., Chicago, IL, USA). Study variables were analysed using the appropriate statistical methods, including Student's t-test and the χ²-test. Logistic regression modelling was used to analyse the relationship between the change in each component of metabolic syndrome and BMI, in subjects considered to be in remission or with disappearance of metabolic syndrome after 1 year. For each demographic and clinical characteristic, crude odds ratios and adjusted odds ratios according to two models were calculated: model 1, lipid-lowering medication use as neither criterion for triglycerides nor for HDL-C; model 2, lipid-lowering medication use as positive criterion for both triglycerides and for HDL-C. A P-value ≤ 0.05 was considered to be statistically significant.

Results

A total of 490 subjects (males n = 251; females n = 239) with metabolic syndrome, with a mean ± SD age of 58 ± 12 years, was included in the study. The rate of disappearance of metabolic syndrome at 1 year was 30% (147/490). Comparison of clinical characteristics of subjects with metabolic syndrome in year 1, and with and without metabolic syndrome after 1 year of follow-up, are shown in Table 1.

Table 1:

Comparison of characteristics among 490 subjects who had metabolic syndrome in the first year of a screening study, stratified by cases with and without metabolic syndrome after 1 year of follow-up

Variable	Metabolic syndrome status after 1 year of follow-up		Statistical significance
Variable	No n = 147	Yes n = 343	Statistical significance
Sex			NS
Male	77 (52.4)	174 (50.7)
Female	70 (47.6)	169 (49.3)
Age, years	56.58 ± 13.32	60.09 ± 12.66	P < 0.05
< 40	19 (12.9)	19 (5.5)	P < 0.05
40 – 49	27 (18.4)	62 (18.1)
50 – 59	44 (29.9)	89 (25.9)
60 – 69	29 (19.7)	81 (23.6)
≥ 70	28 (19.0)	92 (26.8)
BMI, kg/m²	26.45 ± 3.13	27.49 ± 3.31	P < 0.001
< 24	28 (19.0)	43 (12.5)	P < 0.05
24 – 26.9	63 (42.9)	112 (32.7)
≥ 27	56 (38.1)	188 (54.8)
Weight, kg	67.19 ± 11.76	69.81 ± 10.9	P < 0.05
Waist Circumference, cm^a	88.56 ± 9.26	91.90 ± 8.73	P < 0.001
HDL-C, mg/dl^a	52.18 ± 13.29	49.58 ± 13.63	NS
Triglycerides, mg/dl	186.29 ± 95.03	228.17 ± 259.35	P < 0.05
Systolic blood pressure, mmHg	137.02 ± 18.64	141.06 ± 19.18	P < 0.05
Diastolic blood pressure, mmHg	81.40 ± 12.28	83.62 ± 13.11	NS
Fasting plasma glucose, mg/dl	99.89 ± 24.28	115.76 ± 49.49	P < 0.001
Lifestyle
Smoking			NS
No	105 (71.4)	256 (74.6)
Quit	12 (8.2)	27 (7.9)
Yes	30 (20.4)	60 (17.5)
Alcohol			NS
No	109 (74.1)	275 (80.2)
Quit	7 (4.8)	12 (3.5)
Yes	31 (21.1)	56 (16.3)
Betel nut use			NS
No	134 (91.2)	313 (91.3)
Quit	7 (4.8)	17 (5.0)
Yes	6 (4.1)	13 (3.8)
Medication use			NS
Hypertension
No	140 (95.2)	275 (80.2)	P < 0.001
Yes	7 (4.8)	68 (19.8)
Diabetes
No	125 (85.0)	181 (52.8)	P < 0.001
Yes	22 (15.0)	162 (47.2)
Hyperlipidaemia			NS
No	146 (99.3)	331 (96.5)
Yes	1 (0.7)	12 (3.5)

Data presented as n (%) subjects or mean ± SD.

Difference between groups analysed using Student's t-test and χ²-test.

Asian version of waist circumference as a positive criteria: male > 90 cm, female > 80 cm.

Asian version of HDL-cholesterol as a positive criteria: male < 40 mg/dl, female < 50 mg/dl.

NS, not statistically significant (P > 0.05); HDL-C, high-density lipoprotein-cholesterol.

The differences between the value of the first year and the second year of the five components and BMI were divided into quartiles (Table 2) After adjusting for sex, age and baseline BMI in logistic regression model 1, a decrease in SBP of ≥ 14 mmHg, an increase in HDL-C of ≥ 5 mg/dl, a reduction in triglycerides of ≥ 67 mg/dl and a reduction in DBP of 3 – 9 mmHg significantly increased the likelihood of metabolic syndrome disappearing in 1 year. Waist circumference, FPG levels and BMI were not associated with the disappearance of metabolic syndrome.

Table 2:

Logistic regression analysis of the relationship between changes in five components and body mass index (BMI) and the disappearance of metabolic syndrome, divided by quartiles, in 490 subjects with metabolic syndrome in the first year of study

Variable	Crude OR 95% CI	Model 1^a Adjusted OR 95% CI	Model 2^a Adjusted OR 95% CI
Sex^c
Male	1.00	1.00	1.00
Female	0.94 (0.64 – 1.38)	0.92 (0.56 – 1.50)	0.87 (0.53 – 1.42)
Age in first study year, years^d
≤ 39	1.00	1.00	1.00
40 – 49	0.44 (0.20 – 0.95)	0.23 (0.09 – 0.59)	0.23 (0.09 – 0.60)
50 – 59	0.49 (0.24 – 1.03)	0.26 (0.10 – 0.66)	0.27 (0.11 – 0.68)
60 – 69	0.36 (0.17 – 0.77)	0.18 (0.07 – 0.47)	0.16 (0.06 – 0.42)
≥ 70	0.30 (0.14 – 0.65)	0.17 (0.07 – 0.45)	0.17 (0.07 – 0.45)
BMI in first study year, kg/m²
≤ 23.9	1.00	1.00	1.00
24 – 26.9	0.86 (0.49 – 1.52)	0.80 (0.38 – 1.67)	0.73 (0.35 – 1.50)
≥ 27	0.46 (0.26 – 0.80)	0.32 (0.15 – 0.67)	0.30 (0.15 – 0.62)
Component change, first year to second year^e
Systolic blood pressure, mmHg
≤ −7	0.77 (0.42 – 1.41)	0.78 (0.38 – 1.59)	0.81 (0.40 – 1.66)
–6 – 2	1.00	1.00	1.00
3 – 13	2.05 (1.17 –3.61)	1.68 (0.86 – 3.29)	1.79 (0.92 – 3.49)
≥ 14	2.47 (1.41 – 4.31)	2.99 (1.50 – 5.97)	3.10 (1.55 – 6.19)
Diastolic blood pressure, mmHg
≤ −4	0.63 (0.35 – 1.13)	0.69 (0.34 – 1.39)	0.75 (0.37 – 1.51)
–3 – 2	1.00	1.00	1.00
3 – 9	1.74 (1.01 – 3.01)	2.10 (1.07 – 4.11)	2.36 (1.21 – 4.60)
≥ 10	1.27 (0.72 – 2.22)	0.53 (0.26 – 1.10)	0.58 (0.28 – 1.20)
Fasting plasma glucose, mg/dl
≤ –6	0.33 (0.18 – 0.61)	0.27 (0.13 – 0.56)	0.28 (0.14 – 0.58)
–5 – 1	1.00	1.00	1.00
2 – 11	1.30 (0.77 – 2.19)	1.79 (0.94 – 3.42)	1.82 (0.95 – 3.47)
≥ 12	0.86 (0.50 – 1.48)	1.02 (0.54 – 1.94)	1.04 (0.55 – 1.96)
Triglycerides, mg/dl
≤ −27	0.46 (0.24 – 0.88)	0.45 (0.21 – 0.94)	0.45 (0.21 – 0.94)
–26 – 14	1.00	1.00	1.00
15 – 66	1.58 (0.92 – 2.72)	1.47 (0.77 – 2.80)	1.50 (0.79 – 2.86)
≥ 67	2.53 (1.47 – 4.36)	2.04 (1.03 – 4.03)	2.02 (1.02 – 3.99)
HDL-C, mg/dl, second year to first year^f
≤ −5	0.65 (0.37 – 1.16)	0.78 (0.40 – 1.52)	0.73 (0.37 – 1.44)
–4 – 1	1.00	1.00	1.00
2 – 4	1.71 (0.98 – 2.97)	1.65 (0.85 – 3.20)	1.67 (0.86 – 3.25)
≥ 5	2.49 (1.49 – 4.18)	2.74 (1.46 – 5.12)	2.70 (1.45 – 5.01)
Waist circumference, cm
≤-2	0.93 (0.54-1.60)	1.24(0.64-2.42)	1.38(0.72-2.67)
-1-2	1.00	1.00	1.00
3-5	1.62 (0.95-2.75)	1.72(0.89-3.30)	1.78(0.92-3.41)
≥6	1.61 (0.93-2.79)	1.63 (0.82-3.24)	1.60(0.80-3.18)
BMI, kg/m²
≤-0.4	0.50 (0.28-0.89)	0.37(0.18-0.76)	0.38(0.19-0.78)
-0.3 - 0.1 kg/m²	1.00	1.00	1.00
0.2 - 0.8 kg/m²	0.80 (0.46-1.37)	0.54(0.28-1.04)	0.54(0.28-1.04)
≥ 0.9 kg/m²	0.96 (0.56-1.63)	0.64 (0.33-1.25)	0.63 (0.32-1.22)
Lifestyle, first year
Smoking		-	-
No	1.00
Quit	1.08 (0.53-2.22)
Yes	1.22 (0.74-2.00)
Alcohol use		-	-
No	1.00
Quit	1.47(0.56-3.84)
Yes	1.40 (0.85-2.28)
Betel nut use		-	-
No	1.00
Quit	0.96 (0.39-2.37)
Yes	1.08 (0.40-2.90)

ORs based on differences versus variable with little or no change (OR = 1.00); 95% CIs denote statistical significance when ranges do not cross 1.

Model 1: lipid-lowering medication excluded as criterion for triglycerides and high-density lipoprotein cholesterol (HDL-C).

Model 2: lipid-lowering medication included as positive criterion for triglycerides and HDL-C.

Males used as reference group for sex.

Subjects aged ≤ 39 years used as reference group for age.

Components (except HDL-C) and BMI change: first-year minus second-year value.

HDL-C change: second-year minus first-year value.

OR, odds ratio; CI, confidence interval; HDL-C, high-density lipoprotein-cholesterol.

If the use of lipid-lowering medicine was included as a positive criterion for both triglycerides and HDL-C (model 2), the multivariate logistic regression analysis for the 1-year disappearance of metabolic syndrome revealed no obvious difference compared with model 1 (Table 2).

Discussion

The World Health Organization (WHO) first proposed a definition for metabolic syndrome in 1998.¹¹ Since then, several different definitions have been proposed by the NCEP ATP III in 2001,¹² the International Diabetes Foundation in 2005,¹³ and the AHA/National Heart Lung and Blood Institute in 2005.¹⁴ Finally, in 2009, the AHA, the World Heart Federation and the International Atherosclerosis Society proposed a joint definition of metabolic syndrome¹⁵ as including any three of the following five components: elevated waist circumference according to population- and country-specific definitions; elevated triglycerides (drug treatment as an alternate indicator) ≥ 150 mg/dl; reduced HDL-C (drug treatment as an alternate indicator) < 40 mg/dl in males, < 50 mg/dl in females; elevated blood pressure (drug treatment as an alternate indicator) of systolic ≥ 130 and/or diastolic ≥ 85 mmHg; elevated FPG (drug treatment as an alternate indicator) ≥ 100 mg/dl.

In Asia, the prevalence of metabolic syndrome is high, affecting 18% of the population in the Philippines,¹⁶ 25 – 27% in South Korea,¹⁷ 15 – 23% in Singapore,¹⁸ 15 – 27% in China^{19 – 21} and 10 – 27% in Taiwan.^{22 – 24} Few studies have investigated the incidence of the metabolic syndrome in Asia.⁴ Based on the NCEP ATP III definition, the 3-year incidence in Iran⁵ and South Korea⁶ has been assessed; using the Asian criteria for abdominal obesity ATP III, the 10-year incidence⁷ and 4-year incidence in Taiwan²⁵ has been reported. No study, however, has investigated the remission or disappearance of metabolic syndrome without intervention in Asian populations.

Some studies have investigated the relationship between weight change and incidence of metabolic syndrome,^5,6 but there has been no focus on the relationship between changes in the five components assessed in the present study and the incidence of metabolic syndrome. To our knowledge, this is the first study to explore the association between short-term fluctuations in the five components of metabolic syndrome and the disappearance of metabolic syndrome without intervention.

Metabolic syndrome disappeared after 1 year in approximately one third of subjects in the present study; this disappearance was not related to the treatment of metabolic syndrome in these subjects. As metabolic syndrome was not a target disease for screening in the LIONS programme, no prospective diagnosis of metabolic syndrome was made in the health screening report for any subject. This study analysed the disappearance of metabolic syndrome retrospectively, and was not therefore related to the management of metabolic syndrome. The only treatments administered to study subjects that may have impacted on the metabolic syndrome were given for the management of diabetes, hypertension or hyperlipidaemia (which was defined as a total cholesterol level ≥ 250 mg/dl or a triglyceride level ≥ 500 mg/dl); any medication use for diabetes and hypertension was classified as a positive criterion for elevated FPG and elevated blood pressure, with regard to the definition of the metabolic syndrome. In addition, during the second year, the total number of new cases treated for diabetes, hypertension or hyperlipidaemia was < 4% (data not shown) of the total number of study subjects.

Logistic regression analysis of the five components showed that significant reductions in SBP, HDL-C and triglycerides, and moderate reductions in DBP, significantly increased the likelihood of metabolic syndrome disappearing after 1 year. A reduction in waist circumference or BMI was, however, not associated with the 1-year disappearance of metabolic syndrome, suggesting that short-term weight reduction may do little to change metabolic syndrome status.

In logistic regression modelling, the definition of metabolic syndrome differed according to the use of lipid-lowering medicine as a criterion: model 1 neglected the use of lipid-lowering medicine as a criterion while model 2 included such medicine as a positive criterion for the control of both triglycerides and HDL-C. There was no difference between the two models in terms of the change in metabolic syndrome components and the 1-year disappearance of metabolic syndrome. Nevertheless, only a few subjects used lipid-lowering medicine in this study sample; a larger study is needed to confirm our observation. Other limitations of this study included selection bias, due to the inclusion of subjects being restricted to the community screening project, and the age of this community-based population being different from the general population. Thus, the findings cannot be generalized to the larger population of Taiwan. Additional limitations were the availability of only 2 years of consecutive data, and the fact that measurements of each metabolic syndrome component and BMI were taken only once per year for each subject. Thus, without calculating mean values from data taken over the course of the year it is difficult to make strong conclusions or extrapolate data based on a single annual measurement.

In summary, fluctuations in some of the five components used to define metabolic syndrome were associated with the disappearance of metabolic syndrome after 1 year. Of these components, reduction in BP, HDL-C, and triglycerides but not waist circumference, BMI or FPG, might play an important role in the disappearance of metabolic syndrome. Characteristics of the fluctuations in each component and the subsequent disappearance of metabolic syndrome not only impact the treatment efficacy and outcomes in many studies, they also raise the question of whether metabolic syndrome only temporarily disappears or whether subjects attain remission from metabolic syndrome. Additional evidence-based research is required to explore the long-term disappearance of metabolic syndrome, and questions remain as to how best to define the remission. In addition, further investigations are needed to explore the difference in cardiovascular morbidity and mortality in relation to the disappearance of metabolic syndrome, and a large well-controlled study is needed to determine the role that treatment plays in the disappearance of this syndrome.

Footnotes

Acknowledgements

We acknowledge the Taiwan Landseed Hospital (Grant no: LS-2011-07), and thank Hsin Ju Ho and Hui Fang Chen for their support during this study.

Conflicts of interest: The authors had no conflicts of interest to declare in relation to this article.

References

Reaven

: Role of insulin resistance in human disease (syndrome X): an expanded definition. Annu Rev Med 1993; 44: 121–131.

Sattar

, Gaw

, Scherbakova

: Metabolic syndrome with and without C-reactive protein as a predictor of coronary heart disease and diabetes in the West of Scotland Coronary Prevention Study. Circulation 2003; 108: 414–419.

Lakka

, Laaksonen

, Lakka

: The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men. JAMA 2002; 288: 2709–2716.

Pan

, Yeh

, Weng

: Epidemiology of metabolic syndrome in Asia. Asia Pac J Clin Nutr 2008; 17 (Suppl. 1): 37–42.

Zabetian

, Hadaegh

, Sarbakhsh

: Weight change and incident metabolic syndrome in Iranian men and women; a 3 year follow-up study. BMC Public Health 2009; 9: 138.

Kim

, Kim

, Sung

: Association of smoking status, weight change, and incident metabolic syndrome in men: a 3-year follow-up study. Diabetes Care 2009; 32: 1314–1316.

Sheu

, Chuang

, Lee

: Predictors of incident diabetes metabolic syndrome in middle-aged adults: a 10-year follow-up study from Kinmen, Taiwan. Diabetes Res Clin Pract 2006; 74: 162–168.

Chen

, Chiu

, Luh

: Community-based multiple screening model: design, implementation, and analysis of 42,387 participants. Cancer 2004; 100: 1734–1743.

Heng

, Ma

, Lee

: Modification of the NCEP ATP III definitions of the metabolic syndrome for use in Asians identifies individuals at risk of ischemic heart disease. Atherosclerosis 2006; 186: 367–373.

10.

Bureau of Health Promotion: Criteria of Metabolic Syndrome in Adults in Taiwan. Available at: http://www.bhp.doh.gov.tw/bhpnet/portal/Them.aspx?No=200712250023.

11.

Alberti

, Zimmet

: Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 1998; 15: 539–553.

12.

National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III):

Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report.

Circulation 2002; 106: 3143–3421.

13.

Zimmet

, Magliano

, Matsuzawa

: The metabolic syndrome: a global public health problem and a new definition. J Atheroscler Thromb 2005; 12: 295–300.

14.

Grundy

, Cleeman

, Daniels

: Diagnosis and management of the metabolic syndrome: an American Heart Association/ National Heart, Lung and Blood Institute scientific statement. Circulation 2005; 112: 2735–2752.

15.

Alberti

, Eckel

, Grundy

: Harmonizing the metabolic syndrome a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009; 120: 1640–1645.

16.

Morales

, Punzalan

, Paz-Pacheco

: Metabolic syndrome in the Philippine general population: prevalence and risk for athero -sclerotic cardiovascular disease and diabetes mellitus. Diab Vasc Dis Res 2008; 5: 36–43.

17.

Kim

, Kim

, Jung

: Prevalence of the metabolic syndrome among Korean adults using the new International Diabetes Federation definition and the new abdominal obesity criteria for the Korean people. Diabetes Res Clin Pract 2007; 77: 99–106.

18.

Tan

, Ma

, Wai

: Can we apply the National Cholesterol Education Program Adult Treatment Panel definition of the metabolic syndrome to Asians? Diabetes Care 2004; 27: 1182–1186.

19.

, Yang

, Lv

: Prevalence of the metabolic syndrome in the Yan-an region of northwest China. J Int Med Res 2012; 40: 673–680.

20.

, Wang

, Zhang

: Metabolic syndrome: prevalence and risk factors in southern China. J Int Med Res 2010; 38: 1142–1148.

21.

Wang

, Kong

, Sun

: Epidemiological investigation of metabolic syndrome and analysis of relevant factors in north-eastern China. J Int Med Res 2010; 38: 150–159.

22.

Chuang

, Chen

, Chou

: Prevalence of metabolic syndrome in a large health check-up population in Taiwan. J Chin Med Assoc 2004; 67: 611–620.

23.

Chen

, Pan

: Probable blind spot in the International Diabetes Federation definition of metabolic syndrome. Obesity (Silver Spring) 2007; 15: 1096–1100.

24.

Chen

, Bai

, Yeh

: Influence of metabolic syndrome and general obesity on the risk of ischemic stroke. Stroke 2006; 37: 1060–1064.

25.

Yang

, Wahlqvist

, Lee

: Body mass index (BMI) as a major factor in the incidence of the metabolic syndrome and its constituents in unaffected Taiwanese from 1998 to 2002. Asia Pac J Clin Nutr 2008; 17: 339–351.

Relationship between Changes in Components Associated with Metabolic Syndrome and Disappearance,or Remission,of Metabolic Syndrome during 1 Year

Abstract

OBJECTIVES:

Methods:

Results:

Conclusions:

Keywords

Introduction

Subjects and methods

Study Population

Diagnosis of Metabolic Syndrome

One-Year Analysis of Metabolic Syndrome

Statistical Analyses

Results

Discussion

Footnotes

Acknowledgements

References