Epidemiologic Features of Metabolic Syndrome in a General Mongolian Population

Abstract

Background:

Although cardiovascular health is a crucial problem for Mongolian people, little information about metabolic syndrome, which is well known to be associated with the development of cardiovascular disease, is available in Mongolia. The aim of this study was to observe the epidemiological features of metabolic syndrome in a general Mongolian population.

Methods:

This cross-sectional study was performed in 1911 general Mongolian subjects (717 men, 1194 women), who were ≥40 years old and free of ischemic heart disease, by using a dataset from a nationwide population-based cohort study in Mongolia. The prevalence of metabolic syndrome, as defined by International Diabetes Federation criteria, was determined. Alcohol consumption, smoking habits, and physical activity were evaluated. Education, marital status, income, and occupation were also examined as factors of socioeconomic status (SES). Their association with metabolic syndrome was determined by logistic regression models.

Results:

The prevalence of metabolic syndrome was significantly higher in women (n=488, 40.6%) than in men (n=138, 19.4%). The prevalence of metabolic syndrome was high, especially in the Khangai region, in women. Moderate-to-high alcohol consumption was a significantly positively associated factor of metabolic syndrome in men [odds ratio (OR)=2.01; 95% confidence interval (CI) 1.15–3.51; adjusted odds ratio (AOR)=2.41; 95% CI 1.31–4.44] and widowed status was a significantly positively associated factor of metabolic syndrome in women (OR=1.61, 95% CI 1.18–2.18; AOR=1.49, 95% CI 1.07–2.08).

Conclusions:

Metabolic syndrome was prevalent in women compared with men among Mongolian adults. Preventive strategies aimed at men with a higher alcohol consumption and women with widowed status may help reduce metabolic syndrome, thereby improving cardiovascular health conditions in Mongolia.

Introduction

Cardiovascular disease (CVD) is the leading cause of death worldwide.¹ Twice as many deaths due to CVD now occur in developing countries compared with developed countries.² In Mongolia, CVD is also a major health problem, ranking fourth in terms of main causes of morbidity and first in mortality in 2009.^3,4 Public health strategies for the prevention of CVD are, therefore, necessary in Mongolia.

Metabolic syndrome is characterized by clustering risk factors for CVD, such as obesity, dyslipidemia, high blood pressure, and high blood glucose,^5

–10 thereby leading to increased morbidity and mortality of CVD.^1
–3,11 Even though the features of metabolic syndrome can differ between sexes,¹² the prevalence of metabolic syndrome is closely correlated with the epidemic of obesity, a preventative pathology, in both sexes.¹ Thus, metabolic syndrome is thought to be an important target for the primary prevention of CVD.

However, little information about metabolic syndrome is available in Mongolia. To our best knowledge, while prior studies have reported that metabolic syndrome was more prevalent in Mongolian people than in Japanese people,^13,14 these studies were of a relatively small population (about 200–300 patients), were conducted in the capital city only, and did not observe the risk factors for metabolic syndrome. Large-scale and nationwide studies, including the consideration of risk factors, would be necessary to observe the epidemiological features of metabolic syndrome in Mongolia.

Currently, the National Cholesterol Education Program (NCEP) and the International Diabetes Federation (IDF) criteria are primarily used to define metabolic syndrome.^8,11 The IDF criteria were developed in part to allow the comparison of metabolic syndrome features among worldwide ethnic populations in light of ethnicity-specific waist circumferences (WC) as a marker of central obesity.^6

–10 Previous studies of metabolic syndrome in Mongolia used the NCEP criteria,^13,14 so the prevalence of metabolic syndrome in Mongolia based on the IDF criteria is currently unknown.

In terms of the risk factors of metabolic syndrome, developed countries can show more impacts of socioeconomic status (SES) on health conditions, and furthermore, places of residence, education, and income are proposed as new risk factors for metabolic syndrome.^11,15,16 These factors may be crucial in the study of metabolic syndrome and correlated risks,¹⁷ but the association between these factors, including SES, and metabolic syndrome remains to be examined in Mongolia. The purpose of the present study was to observe the epidemiologic features of metabolic syndrome (with the IDF criteria) in a general Mongolian population, by using a dataset from a nationwide large-scale population-based cohort study in Mongolia.

Methods

Study population

We conducted a nationwide cross-sectional study among the general population in Mongolia. Considering the significance of metabolic syndrome for the primary prevention of CVD, this study excluded patients with ischemic heart disease (IHD) (369 patients). A total of 1911 Mongolian adults, aged 40 years or above, were randomly selected from four Mongolian provinces in addition to the capital city of Ulaanbaatar.

Questionnaire

A standard questionnaire of the World Health Organization (WHO) STEPS Surveillance Manual was used.¹⁸ The questionnaire consisted of eight chapters with a total of 80 closed-ended and open-ended questions. This questionnaire included the individual's SES, alcohol consumption, tobacco use, nutrition, physical activity, and health status. Subjects' answers to the questionnaires were confirmed by interviews. Physical examinations were conducted following an overnight fast.

Physical and biochemical examinations

Height was measured in centimeters (without shoes), and weight in kilograms (with heavy clothing removed). The body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. We measured the WC on standing subjects with a soft tape midway between the lowest rib and iliac crest. Hip circumference was measured over the widest part of the gluteus region, and the waist-to-hip ratio was calculated as one of the measures for central obesity. The blood pressure recordings were obtained from the right arm of participants in a sitting position after 10 min of rest, and the mean values of two recordings were calculated. Overnight fasting blood samples were obtained for measurement of serum lipids and glucose. Concentrations of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (TGs), and fasting blood glucose were assessed enzymatically.

SES variables

Education variables were collected at study entry, including years of education as categorized in the Mongolian education system. The variables were divided into the five categories of elementary (<7 years), noncomplete secondary (7–9 years), complete secondary (10–12 years), vocational (13–14 years), and university graduates (>14 years).

Monthly income was categorized into three types—lower, middle, and upper types—according to average salary per month.⁴ Socioeconomic position was measured and defined as social classes on the basis of the longest held occupation recorded at study entry (meaning the current occupation as of the time of the study) and using a Registrar General's Classification.¹⁹ Class I corresponded to the upper/wealthy social class. Participants were placed into six groups: Social class I (professional, e.g., physicians, engineers); social class II (managerial, e.g., teachers, sales managers); social class III (semiskilled nonmanual, e.g., bricklayers etc.); social class IV (partly skilled, e.g., postmen); social class V (unskilled, e.g., porters, laborers); and nonemployed VI (retired, unemployed, housewives). Individuals classified as housewives, students, those who were registered with no information on last occupation, and individuals whose stated occupation could not be classified were placed in social class VI (the nonemployed group).

Definition of the metabolic syndrome

The IDF criteria for metabolic syndrome⁶ were as follows. WC ≥90 cm for men and ≥80 cm for women is classified as central obesity, plus any two of the following criteria: Elevated TGs of ≥1.7 mmol/L, reduced HDL-C <1.03 mmol/L in men and <1.29 mmol/L in women, elevated blood pressure [systolic blood pressure (SBP) ≥130 or diastolic (DBP) ≥85 mmHg] and/or treatment of previously diagnosed hypertension, and elevated plasma fasting glucose ≥5.6 mmol/L and/or previously diagnosed diabetes. This is different from the NCEP criteria in terms of central obesity criteria (WC ≥102 cm in men and greater ≥88 cm in women) and elevated fasting plasma glucose (≥6.1 mmol/L).^13,14

Statistical analyses

The association between the factors and the prevalence of metabolic syndrome was analyzed by the chi-squared test or t-test. Logistic regression analyses were used to calculate the odds ratios for evaluating the association between independent variables and metabolic syndrome. Adjustments were carried out for the independent variables that were significantly associated with metabolic syndrome by the chi-squared test. These variables were age, education, smoking habits, alcohol consumption habits, and physical activity. The trend in odds was evaluated by using the likelihood ratio test. All probabilities were judged in a two-tailed way, and all confidence intervals were estimated at the 95% level. The Statistical Package for the Social Sciences (SPSS Version 18.0) was used for the analyses. The criterion for statistical significance was set at p<0.05.

Results

The mean age and standard deviation of the 1911 individuals was 52.9±9.2 years. Table 1 shows the prevalence of metabolic syndrome by the IDF criteria among the study population according to age, sex, geographic variables, SES status, and pernicious habits. The prevalence of metabolic syndrome was 32.8% in the 1911 people in this study. The prevalence of diabetes in total subjects was 5.2% (n=99) (5.9% in men and 4.8% in women), and the prevalence of metabolic syndrome was 31.5% (n=1812) in those without diabetes (17.8% in men and 39.6% in women). As a reference, the prevalence of metabolic syndrome was 26.1% when we used the NCEP criteria. While we previously reported the Mongolian study of patients with IHD,¹⁸ the prevalence of metabolic syndrome was 32.2% in those with IHD (n=369) when we reanalyzed the prevalence on the basis of the previously used dataset (the prevalence of metabolic syndrome was not clearly different from that of that study, and it may partly be due to a selection bias of the use of survivors with IHD in that study).¹⁸

Table 1.

Descriptive Statistics of Study Population

	Entire population, n	Metabolic syndrome, n (%)	P value	Total men, n	Men with metabolic syndrome, n (%)	P value	Total women, n	Women with metabolic syndrome, n (%)	P value
Total	1911	626 (32.8)		717	138 (19.2)		1194	488 (40.9)
Age group			0.086			0.448			0.048
40–44	382	122 (31.9)		128	21 (16.4)		254	101 (39.8)
45–49	438	122 (27.9)		155	25 (16.1)		283	97 (34.3)
50–54	411	138 (33.6)		159	34 (21.4)		252	104 (41.3)
55–59	293	103 (35.2)		110	20 (18.2)		183	83 (45.4)
60+	387	141 (36.4)		165	38 (23.0)		222	103 (46.4)
Residence			0.140			0.565			0.070
Urban	1076	341 (31.7)		413	83 (20.1)		663	258 (38.9)
Rural	835	285 (34.1)		304	55 (18.1)		531	230 (43.3)
Regions			<0.001			0.064			0.001
Ulaanbaatar	1076	341 (31.7)		413	83 (20.1)		663	258 (38.9)
Central	274	87 (31.8)		113	19 (16.8)		161	68 (42.2)
Eastern	110	35 (31.8)		48	9 (18.8)		62	26 (41.9)
Western	185	42 (22.7)		62	5 (8.1)		123	37 (30.1)
Khangai	266	121 (45.5)		81	22 (27.2)		185	99 (53.5)
Monthly income			0.085			0.775			0.162
Lower	737	265 (35.5)		239	48 (20.1)		498	231 (43.8)
Middle	481	150 (31.2)		188	33 (17.6)		293	117 (39.9)
Upper	625	190 (30.4)		252	50 (19.8)		373	140 (37.5)
Education (years)			0.132			0.045			0.434
Elementary	183	72 (39.3)		58	13 (22.4)		125	59 (47.2)
Incomplete secondary	434	129 (29.7)		205	30 (14.6)		229	99 (43.2)
Complete secondary	504	157 (31.2)		182	29 (15.9)		322	128 (39.8)
Vocational	304	108 (35.5)		73	15 (20.5)		231	93 (40.3)
University	486	160 (32.9)		199	51 (25.6)		287	109 (38.0)
Occupation			0.120			0.516			0.401
Social class I	597	191 (32.0)		232	44 (19.0)		365	147 (40.3)
Social class II	431	121 (33.2)		97	22 (22.7)		267	99 (37.1)
Social class III	92	39 (42.4)		25	8 (32.0)		67	31 (46.3)
Social class IV	75	19 (25.3)		60	12 (20.0)		15	7 (46.7)
Social class V	165	45 (27.3)		76	13 (17.1)		89	32 (36.0)
Social class VI	618	211 (34.1)		227	39 (17.2)		391	172 (44.0)
Smoking			<0.001			0.888			0.975
Nonsmoker	1359	498 (36.6)		280	56 (20.0)		1079	442 (41.0)
Current smoker	444	105 (23.6)		347	66 (19.0)		97	39 (40.2)
Ex-smoker	108	23 (21.3)		90	16 (17.8)		18	7 (38.9)
Alcohol consumption			0.015			0.016			0.369
None	757	266 (35.1)		179	28 (15.6)		578	238 (41.2)
Low moderate	380	118 (31.1)		88	10 (11.4)		292	108 (37.0)
High moderate	322	118 (36.6)		129	35 (27.1)		193	83 (43.0)
Heavy	452	124 (27.4)		321	65 (20.2)		131	59 (45.0)
Marital status			<0.001			0.914			<0.001
Married	1463	461 (31.5)		621	119 (19.2)		842	342 (40.6)
Single or divorced	107	25 (23.4)		33	6 (18.2)		74	19 (25.7)
Widowed	238	116 (48.7)		27	6 (22.2)		211	110 (52.1)
Physical activity
Vigorous intensity at work			0.005			0.068			0.465
Yes	269	69 (25.7)		155	24 (15.5)		114	45 (39.5)
No	1093	371 (33.9%)		376	81 (21.5)		717	290 (40.4)
Moderate intensity at work			0.159			0.382			0.206
Yes	686	212 (30.9)		271	51 (18.8)		415	161 (38.8)
No	673	226 (33.6)		257	52 (20.2)		416	174 (41.8)
Vigorous intensity in free time			0.002			0.252			0.082
Yes	346	91 (26.3)		169	29 (17.2)		177	62 (35.0)
No	1552	533 (34.3)		543	108 (19.9)		1009	425 (42.1)
Moderate intensity in free time			0.414			0.475			0.088
Yes	1161	384 (33.1)		367	70 (19.1)		794	314 (39.5)
No	745	242 (32.5)		348	68 (19.5)		397	174 (43.8)
Walking at least 10 min a day			0.419			0.284			0.358
Yes	1627	535 (32.9)		601	113 (18.8)		1026	422 (41.1)
No	284	91 (32.0)		116	25 (21.6)		168	66 (39.3)
Vegetable consumption			0.483			0.205			0.263
Yes	1759	577 (32.8)		659	124 (18.8)		1100	453 (41.2)
No	152	49 (32.2)		58	14 (24.1)		94	35 (37.2)
Fruit consumption			0.214			0.190			0.093
Yes	1358	437 (32.2)		462	84 (18.2)		896	353 (39.4)
No	553	189 (34.2)		255	54 (21.2)		298	135 (45.3)

P value, within respective factors.

The prevalence of metabolic syndrome by the IDF criteria was higher in women (40.9%) than in men (19.2%) (p=0.0001) in this study. The difference was mainly due to the following metabolic syndrome components, which showed a clearly different prevalence—abdominal obesity (75.9% in women and 45.0% in men) and reduced HDL-C (33.6% in women and 18.3% men). The other components showed a similar prevalence—elevated blood pressure (73.0% in women and 64.4% in men), elevated TGs (36.9% in women and 43.5% in men), and elevated plasma glucose (29.6% in women and 31.4% in men). The prevalence of metabolic syndrome was increased significantly with age in women, and was higher in the 60+ age group than in the 40- to 44-year age group (46.4% vs. 39.8%). Metabolic syndrome was also significantly more frequent in women who were widowed than those who never married (52.1% vs. 25.7%, p=0.0001). There were statistically significant differences in the prevalence of metabolic syndrome by region, with metabolic syndrome being higher in the Khangai region for the entire population and especially for women (P<0.01). In the Khangai region, the prevalence of metabolic syndrome was 27.2% in men and 53.5% in women. In contrast, in the western region, the prevalence was 8.1% in men and 30.1% in women.

Table 2 shows the data for subjects with or without metabolic syndrome by sex according to the IDF criteria. There was a significant difference in the clinical characteristics of subjects between the metabolic syndrome group and non–metabolic syndrome group in women. In women, age was higher in the metabolic syndrome group than in the non–metabolic syndrome group, but in men there was no significant difference in age between the two groups. The levels of physical and biochemical characteristics (BMI, blood pressure, WC, TGs, and glucose) were statistically higher in metabolic syndrome group than in the non–metabolic syndrome group in both sexes, whereas in women, significant differences were seen in cholesterol (total, HDL-C, and LDL-C) levels.

Table 2.

Clinical Characteristics of Subjects With and Without Metabolic Syndrome

	Men		Women
	Without metabolic syndrome	With metabolic syndrome	Without metabolic syndrome	With metabolic syndrome
n (%)	579 (80.8)	138 (19.2)	706 (59.1)	488 (40.9)
Age (year)	53.0±9.1	54.4±9.8	51.8±8.7	53.2±9.7^*
Body mass index (kg/m²)	25.9±4.7	30.9±3.9^*	25.9±5.1	29.2±4.4^*
Height (cm)	159.4±8.8	161.6±9.4^*	158.9±8.2	160.0±8.9^*
Weight (kg)	65.9±12.3	80.7±12.5^*	65.9±14.4	74.7±12.7^*
Waist circumference (cm)	95.4±9.2	104.3±8.1^*	95.7±9.8	102.0±8.0^*
Systolic blood pressure (mmHg)	124.9±22.5	136.3±21.9^*	123.7±21.5	136.6±27.3^*
Diastolic blood pressure (mmHg)	81.7±14.4	88.8±14.6^*	80.8±13.2	89.1±16.3^*
Total cholesterol (mmol/L)	179.4±41.2	185.9±44.3	176.4±40.6	181.6±44.8^*
HDL-C (mmol/L)	1.53±0.87	1.51±0.67	1.64±0.58	1.46±0.72^*
LDL-C (mmol/L)	2.43±1.03	2.31±1.11	2.33±0.97	2.46±0.99^*
Triglycerides (mmol/L)	1.59±1.01	2.28±1.44^*	1.39±0.67	1.72±0.70^*
Fasting glucose (mmol/L)	4.99±1.33	5.72±1.72^*	4.74±1.06	5.34±1.49^*
Overweight (BMI ≥25), n (%)	215 (37.1)	54 (39.1)	223 (31.6)	224 (45.9)
Obesity (BMI ≥30), n (%)	100 (17.3)	80 (58.0)^*	143 (20.3)	191 (39.1)^*
High blood pressure (SBP ≥130 or DBP ≥85), n (%)	121 (20.9)	57 (41.3)	132 (18.7)	196 (40.2)
Elevated glucose (fasting glucose ≥6.1 mmol/L), n (%)	42 (7.3)	20 (14.5)	38 (5.4)	58 (11.9)

P value<0.05 (within respective factors).

HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure.

Table 3 shows the odds ratios for metabolic syndrome as the dependent variable and associated factors as independent variables. Specifically for men, alcohol consumption was a significant association with a higher odds ratio [odds ratio (OR)=2.01; 95% confidence interval (CI) 1.15–3.51]. This significance remained after adjustment in multivariate analysis [adjusted odds ratio (AOR)=2.41; 95% CI 1.31–4.44]. The widowed status was significantly associated with metabolic syndrome in women. Inversely, single or divorced women had a lower prevalence of metabolic syndrome (OR=0.46; 95% CI 0.26–0.82; AOR=0.45; 95% CI 0.25–0.80). Additionally, when we compared men with alcohol consumption to those without, the prevalence of obesity (46.7%) and elevated glucose levels (32.3%) were, respectively, higher in those with alcohol consumption than that of obesity (40.2%, p=0.079) and elevated glucose (28.5%, p=0.193) in those without alcohol consumption. When we compared widowed to nonwidowed women, the prevalence of obesity (83.9%) and hypertension (82.5%) was, respectively, higher in widowed women than that of obesity (75.0%, p=0.003) and hypertension (71.2%, p=0.0001) in nonwidowed women.

Table 3.

Odds Ratio (95% CI) for the Metabolic Syndrome As Dependent Variable and Related Factors As Independent Variables

	Men		Women
	Unadjusted	Multiadjusted	Unadjusted	Multiadjusted
Age group (year)
40–44	1.0	1.0	1.0	1.0
45–49	0.98 (0.52–1.85)	0.98 (0.50–1.90)	0.79 (0.57–1.12)	0.81 (0.56–1.16)
50–54	1.39 (0.76–2.53)	1.29 (0.67–2.47)	1.06 (0.75–1.52)	1.08 (0.75–1.56)
55–59	1.13 (0.58–2.22)	1.20 (0.58–2.48)	1.26 (0.86–1.85)	1.38 (0.93–2.04)
60+	1.53 (0.84–2.76)	1.60 (0.84–3.06)	1.31 (0.91–1.89)	1.32 (0.88–1.97)
Education (years)
Elementary	1.0	1.0	1.0	1.0
Incomplete secondary	0.59 (0.29–1.23)	0.69 (0.34–1.37)	0.85 (0.55–1.32)	1.01 (0.63–1.63)
Complete secondary	0.66 (0.32–1.37)	0.71 (0.34–1.48)	0.74 (0.49–1.12)	0.92 (0.57–1.49)
Vocational	0.89 (0.39–2.07)	1.23 (0.49–3.10)	0.75 (0.49–1.17)	0.85 (0.49–1.47)
University	1.19 (0.59–2.39)	2.43 (0.98–5.99)	0.69 (0.45–1.05)	0.90 (0.51–1.59)
Regions
Ulaanbaatar	1.0	1.0	1.0	1.0
Central	0.80 (0.46–1.39)	0.92 (0.51–1.66)	1.15 (0.81–1.63)	1.06 (0.74–1.52)
Eastern	0.92 (0.43–1.97)	1.24 (0.55–2.79)	1.13 (0.67–1.92)	1.02 (0.60–1.78)
Western	0.35 (0.14–0.90)^*	0.43 (0.16–1.14)	0.68 (0.48–1.02)	0.66 (0.43–1.00)
Khangai	1.48 (0.86–2.56)	1.83 (0.99–3.38)^*	1.81 (1.30–2.51)^*	1.72 (1.21–2.46)^*
Smoking
Non smoker	1.0	1.0	1.0	1.0
Current smoker	0.94 (0.63–1.40)	0.94 (0.63–1.40)	0.97 (0.63–1.48)	0.99 (0.65–1.54)
Ex-smoker	0.87 (0.47–1.60)	1.02 (0.66–1.57)	0.92 (0.35–2.38)	0.78 (0.29–2.09)
Alcohol consumption
None	1.0	1.0	1.0	1.0
Low-to-moderate	0.69 (0.32–1.50)	0.71 (0.31–1.64)	0.84 (0.63–1.12)	0.90 (0.66–1.21)
Moderate-to-high	2.01 (1.15–3.51)^*	2.41 (1.31–4.44)^*	1.08 (0.78–1.50)	1.21 (0.85–1.72)
Heavy	1.37 (0.84–2.23)	1.48 (0.87–2.51)	1.17 (0.80–1.72)	1.28 (0.86–1.90)
Marital status
Widowed	1.33 (0.52–3.41)	1.11 (0.39–3.11)	1.61 (1.18–2.18)^*	1.49 (1.07–2.08)^*
Single or divorced	0.84 (0.32–2.25)	0.95 (0.33–2.72)	0.46 (0.26–0.82)^*	0.45 (0.25–0.80)^*
Married	1	1	1	1

Odds ratio (OR) [95% confidential interval (CI)] adjusted for age, education, region, smoking, alcohol consumption habits and marital status.

P value<0.05.

The Khangai region was a significantly positively associated factor of metabolic syndrome in both sexes (AOR=1.83; 95% CI 0.99–3.38 vs. AOR=1.72; 95% CI 1.21–2.46). We clearly did not find any region-specific factors associated with metabolic syndrome when we observed the association between measured factors and metabolic syndrome by region (data not shown).

Discussion

This study demonstrated that the prevalence of metabolic syndrome, as defined by the IDF criteria, was 32.8% (men 19.4% and women 40.6%) in a general Mongolian population. These data are worth noting, because this is the first finding of metabolic syndrome by the IDF in a nationwide large-scale survey of a general Mongolian adult population.

Although we cannot exactly predicate the transition of the epidemiological features of metabolic syndrome because there have been no nationwide studies that use the IDF criteria, speculatively, several risk factors contributing to metabolic syndrome have become worse over recent years in Mongolia. A nationwide survey that was held in 2009²⁰ indicated that obesity, blood pressure, and blood glucose levels might increase when compared with an earlier nationwide survey.²¹ Thus, to determine the prevalence of metabolic syndrome by the IDF criteria in the present study would be also useful for observing the epidemiological change of metabolic syndrome in the future.

The prevalence of metabolic syndrome was noted to be significantly higher in women than in men in this study. This trend seems to be consistent with the data observed in recent Chinese,²² Iranian,²³ and Jamaican studies.²⁴ On the other hand, the prevalence of metabolic syndrome was reported to be similar between sexes in Kuwaitis (36.2% vs. 36.1%) and US adults (24.0% vs. 23.4%).²⁵ The prevalence of metabolic syndrome increased from 32.1% in those aged 40–45 years to 36.2% in those over the age of 60. These findings are consistent with what has been described in China, Kuwait, Iran, and Jamaica in separate studies.^22

–25

The present study further revealed that people, especially women, living in the Khangai region of Mongolia had a higher metabolic syndrome status than the populations of other regions. However, we clearly did not find any region-specific factors associated with metabolic syndrome when we observed the association between the measured factors and metabolic syndrome by region. So, although the reasons for the regional difference in the prevalence of metabolic syndrome remain unknown, several between-region factors unmeasured in this study may be associated with the results. For instance, the poverty and unemployment levels are known to be higher in the Khangai region than the other regions.²⁶ Indeed, a low poverty income ratio and unemployment were reported to be associated with metabolic syndrome.^27
–29 Other factors, such as genetic components, may be a candidate for explaining the results. The regional difference in the prevalence of metabolic syndrome and the reasons for these differences should be explored in future work.

Our findings demonstrate that a moderate-to-high level of alcohol consumption is associated with a higher prevalence of metabolic syndrome in men. The relationship between metabolic syndrome and alcohol consumption is complex.^30,31 Although the relationship has not always been supported across studies, some studies indicate that the metabolic syndrome and its components tend to increase with increasing alcohol consumption.^30,32,33 Regarding the reduction of the odds ratio for the association between metabolic syndrome and heavy alcohol consumption may be in part explained by some reverse epidemiology (i.e., diseased individuals can avoid the adverse behaviors, so an inverse correlation between risk factors and outcomes occurs in such situations).³⁰

The present study found that a significant association between marital status and metabolic syndrome was observed in women, but not in men. Although the association of marital status and metabolic syndrome is not fully clear and their association is often complex,³⁴ those in high-quality marriages are suggested to be at lower risk of developing metabolic syndrome.³⁴ Factors such as depression following becoming widowed as well as factors that might define a healthy/high-quality marriage (e.g., nonabusive, lack of infidelity) can be fruitful areas for further research in this area.

While we believe our study to be valid and statistically sound, the study does have some limitations. The study was conducted using a large sample size on a national scale, including both rural and urban areas. This method of cross-sectional data collection might impede the ability to assess the directional nature of the relationship between current SES and metabolic syndrome. Additionally, we could not fully exclude the possibility of information bias, given that this study was partially based on information obtained through a questionnaire.

In conclusion, metabolic syndrome was found to have a higher prevalence in women compared to men in our Mongolian adult study population. Further studies are warranted to better understand regional differences in the development of the metabolic syndrome. Preventive strategies targeted at men with high levels of alcohol consumption and women who are of widowed status may help in the fight against metabolic syndrome, thereby serving to reduce the prevalence of cardiovascular conditions and improve overall health in Mongolia.

Footnotes

Acknowledgments

The authors thank the Department of Public Health, Jichi Medical University, Japan, and the Department of Epidemiology and Biostatistics, School of Public Health, Mongolia for their advice and support; Dr. Eric Swanson, MD, MPH, Brian Allgood Army Community Hospital, for his expertise and advice; and the people who kindly and faithfully participated.

Author Disclosure Statement

No competing financial interests exist.

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