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Article

Association of Serum 25-Hydroxyvitamin D and Vitamin D Intake with the Prevalence of Metabolic Syndrome in Korean Adults: 2013–2014 Korea National Health and Nutrition Examination Survey

by
Su-In Yoon
1,2,
Jae-Yeon Min
1,
Sun Yung Ly
1,
SuJin Song
3 and
Jin Ah Cho
1,*
1
Department of Food and Nutrition, Chungnam National University, Daejeon 34134, Republic of Korea
2
Research Center for Microbiome-Brain Disorders, Chungnam University, Daejeon 34134, Republic of Korea
3
Department of Food and Nutrition, Hannam University, Daejeon 34054, Republic of Korea
*
Author to whom correspondence should be addressed.
Appl. Sci. 2023, 13(6), 3748; https://0-doi-org.brum.beds.ac.uk/10.3390/app13063748
Submission received: 20 February 2023 / Revised: 13 March 2023 / Accepted: 14 March 2023 / Published: 15 March 2023
(This article belongs to the Special Issue Functional Food and Chronic Disease II)
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Abstract

:
Vitamin D deficiency is prevalent in Korea and an insufficient vitamin D status increases the risk of various chronic diseases including metabolic syndrome (MetS). We examined the relationship between serum 25-hydroxyvitamin D (25(OH)D) levels, dietary vitamin D intake, and MetS. The 2013–2014 Korea National Health and Nutrition Examination Survey’s (KNHANES) included participants (n = 4.541; 1145 men; 1368 women) who were aged ≥19. In men, higher serum 25(OH)D levels were correlated with significantly increased protein intake (p = 0.032) and saturated fatty acid intake (p = 0.006), but significantly decreased fat intake (p = 0.027), monounsaturated fatty acid intake (p = 0.005), and polyunsaturated fatty acid intake (p = 0.003), and significantly decreased serum triglycerides levels (p = 0.002), whereas women had no association with any dietary intake or biochemical markers. Furthermore, our study found a significant negative correlation between abdominal obesity (OR, 0.970; CI, 0.946, 0.994) and hypertriglyceridemia (OR, 0.974; CI, 0.950, 0.998) and serum 25(OH)D levels in men, as well as a significant decrease in hypertriglyceridemia (OR, 0.980; CI, 0.961, 0.999) with vitamin D intake. However, women had a significantly negative correlation between serum LDL cholesterol (β, −1.751; p = 0.018) and vitamin D intake. By increasing the vitamin D intake and serum 25(OH)D levels, Korean adults could reduce their risk of MetS-related factors.

1. Introduction

Metabolic syndrome (MetS), also referred to as Syndrome X in 1988 [1], is a group of conditions characterized by abdominal obesity, high blood pressure, hypertriglyceridemia, high fasting blood glucose, and low high-density lipoprotein (HDL) cholesterol levels [2]. It is associated with a higher risk of cardiovascular disease and type 2 diabetes [3,4,5]. According to a national study in Korea, 31.3% of adults (over the age of 19) have MetS, and this estimate is projected to increase as the Korean population ages [6]. MetS prevention is one of essential public health objectives for reducing the future social and economic burden of diabetes and cardiovascular disease.
Vitamin D is a fat-soluble vitamin that is well known for being essential for the preservation of bone mass and calcium homeostasis with its active form, calcitriol (1.25 (OH)2 D). However, new attention is being paid to vitamin D action, as it is known that the vitamin D receptor (VDR) and 1α-hydroxylase needed to convert vitamin D into an active form are expressed in various tissues such as the kidney, pancreas, prostate, immune system, and epithelia, and synthesize calcitriol locally [7]. Recent researchers have revealed that vitamin D has additional functions, such as reducing the insulin resistance in diabetes, regulating lipolysis, and preventing the development of obesity and other diseases, such as allergies, cancers, and autoimmune diseases [8,9,10,11,12,13,14,15,16,17,18,19]. Consequently, vitamin D insufficiency is thought to cause insulin resistance, which can be inferred to be associated with MetS. A few studies reported an inverse connection between serum vitamin D and the likelihood of developing MetS [20,21,22,23,24,25], while others did not [14,26,27,28].
The majority of vitamin D is obtained by the skin in reaction to ultraviolet B from the sun, or by consuming a few vitamin D-rich foods such as mushrooms, eggs, fish and shellfish, and milk and dairy products. The use of vitamin D supplements is another growing source of vitamin D. However, modern society’s decreased outdoor activity time and overuse of sunscreen significantly reduce UVB exposure. As a result, increasing vitamin D intake through food and supplements is critical for maintaining optimal serum vitamin D concentrations.
Vitamin D, which is synthesized in the skin or ingested, is converted into 25-hydroxyvitamin D (25(OH)D) in the liver, which is the predominant form with a long half-life. Thus, serum 25(OH)D concentration is currently the most accurate reflection of the vitamin D status [29]. Vitamin D insufficiency is defined by the American Medical Association and the Institute of Medicine (IOM) as a serum 25(OH)D level of less than 20.0 ng/mL, based on the inference for bone health [30]. Using the IOM’s level (<20 ng/mL), current estimates show that 39% of healthy adults in the United States are not vitamin D sufficient [31]. In South Korea, the prevalence of vitamin D deficiency was 51.8% among males and 68.2% among females in the overall population in 2008, but it increased to 75.2% and 82.5%, respectively, in 2014 [32]. The actual cause is unknown, although it is assumed that inadequate vitamin D intake was not compensated for by deteriorating environmental factors such as increased pollution and urban life, a lack of vitamin D-fortified foods, and a lack of dietary supplements.
In the Korean Dietary Reference Intakes (KDRIs), an adequate intake (AI) for vitamin D was established as the reference value. The AI in the 2010 KDRIs was 5 μg/d for people younger than 50 years old and 10 μg/d for adults older than 50 years old [33]. Following 2015, the AI for vitamin D was raised to 10 μg/d and 15 μg/d for people aged 12–64 years and adults over 65 years old [34,35]. Vitamin D was absent in the food composition tables used for the Korea National Health and Nutrition Examination Survey (KNHANES); hence, vitamin D intakes among Koreans could not be well measured. In 2015, Yoo et al. created a vitamin D database (DB) containing 1555 food items and analyzed vitamin D intakes using the 2009 KNHANES IV-3 [36]. The average daily vitamin D intakes from food and beverages for men and women aged ≥20 years old were 4.00 ± 0.17 μg/day and 2.64 ± 0.10 μg/day, respectively. The percentages of men and women who did not receive enough vitamin D were 83.0% and 89.4%, respectively. The vitamin D consumption of Koreans is clearly inadequate. A vitamin D DB covering 4444 dietary products was recently updated by the same group [37]. In this study, this updated vitamin D DB was used in our study’s analysis of the 2013–2014 KNHANES to examine the relationship between the serum 25(OH)D level, vitamin D intake, and MetS among Korean adults.

2. Materials and Methods

2.1. Study Population and Design

The Korea Centers for Disease Control and Prevention (KCDC) of the Ministry of Health and Welfare administers a continuous annual surveillance system known as the KNHANES. The current cross-sectional study is based on the data collected from the 2013 and 2014 KNHANES (VI-1 and VI-2). Based on a stratified, multistage probability sampling approach, the target population for this survey consists of non-institutionalized Koreans, and it contains nationally representative samples aged 1 year or older. The KNHNAES includes health interviews, physical examinations, and nutrition surveys [38].
Of the 15,568 participants who participated in the 2013–2014 KNHANES, 12,089 participants (5214 men; 6875 women) aged 19 years and older were included. The participants who had missing data in the dietary intake survey (n = 1326); improbable energy intakes (<500 or ≥5000 kcal per day, n = 169) [39,40]; vitamin D intake >100 µg/day (upper limit (n = 9)); MetS-related diseases, such as hypertension, dyslipidemia, diabetes mellitus (n = 2043); missing data regarding occupation, education, drinking, smoking and physical status, season of blood draw (n = 1896), blood pressure, anthropometric and biochemical examination (n = 799), dietary supplements (n = 62), and serum 25(OH)D concertation (n = 3506) were excluded (Figure 1). Finally, 2513 participants (1145 men and 1368 women) were selected for this study. The KCDC’s institutional review board (IRB) approved this survey (IRB approval number in 2013 and 2014: 2013-07CON-03-4C and 2013-12EXP-03-5C).

2.2. Anthropometric and Biochemical Measurement

Anthropometric data (height, weight, waist circumference, and body mass index), blood pressure data (systolic and diastolic), and biochemical test data (fasting blood glucose, triglycerides, total cholesterol, convertible high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol (direct test), and 25(OH)D) were obtained from the data included in KNHANES. These data were collected following an 8 h or longer fast. The 25(OH)D concentration was measured by radioimmunoassay (RIA) using the 25-Hydroxyvitamin D 125I RIA Kit (DiaSorin Inc., Stillwater, MN, USA) and a gamma-counter (1470 WIZARD, Perkin Elmer, Turku, Finland). The serum 25(OH)D concentration was categorized into 3 levels (<10 ng/mL, 10 to <20 ng/mL, and ≥20 ng/mL) [30].

2.3. Dietary Assessment with Vitamin D DB

In KNHANES, an experienced dietitian interviewed participants of the study and recorded what they consumed for the previous 24 h. A total of 4444 vitamin D DB have been developed by modifying and augmenting the previously established vitamin D DB (1588 foods) [36] and described in detail in a recent publication [37]. The daily intake of energy and nutrients, including vitamin D, was computed from data obtained from a single 24-h dietary recall of each participant with a modified vitamin D DB. In this investigation, the vitamin D supplementation of the participants was not addressed due to the absence of a database detailing the amounts of vitamin D supplements.

2.4. Criteria for MetS

MetS was diagnosed using the National Cholesterol Education Program Adult Treatment Panel (NCEP-ATP) III criteria [41], and the Korean Society for the Research of Obesity’s abdominal obesity criterion. The presence of at least 3 of the following was required for diagnosis: (1) abdominal obesity (waist circumference of more than 90 cm for men and 85 cm for women); (2) increased blood pressure (systolic blood pressure greater than 130 mmHg or diastolic blood pressure greater than 85 mmHg); (3) high blood glucose (fasting blood glucose concentration greater than 100 mg/dL); (4) high triglyceride (TG) level (greater than 150 mg/dL); (5) low HDL cholesterol level (below 40 mg/dL for men and below 50 mg/dL for women).

2.5. Statistical Analysis

IBM SPSS version 26.0 was used for all statistical analyses (SPSS, Chicago, IL, USA). According to the KCDC’s statistical guidance, the integrated weight, correlation weight, colony (psu), and stratified variable (kstrata) were used to analyze the complex sample design. Our participants were divided into 25(OH)D levels of deficient (<10), insufficient (10 to <20), and sufficient (≥20 ng/mL) according to the IOM guidelines. To demonstrate the general characteristics of the participants, the frequency (weighted percentage) and mean ± standard error were presented according to the predefined 25(OH)D categories. In complex samples analysis, differences in the distribution of categorical variables and the means of continuous variables were analyzed using the chi-square test or general linear model (GLM). The means and standard errors were calculated for anthropometric measurements, biochemical tests, and nutrient intakes. The p for trend was evaluated with a complex samples general linear model (CSGLM) with the median 25(OH)D to exposure category as a continuous variable.
The composite sample design multiple logistic regression was performed to calculate the adjusted odds ratio (OR) and 95% confidence intervals (CI) to examine the relationship between MetS and serum 25(OH)D concentration or vitamin D intake. Covariates were also chosen after reviewing previous studies which examined the associations of vitamin D intake or serum 25(OH)D with metabolic diseases. All statistical models were adjusted accordingly for sex (only for the total participants), age (continuous), education (elementary school, middle school, high school, or college or more), occupation (office worker, physical work, or inoccupation), region (midland or southland), smoking (not at all, occasionally smoke, or smoke), alcohol drinking (not at all, less than once a month, 2~4 times a month, 2~3 times a week, or 4 or more times a week), physical activity (not at all, 1~2 times a week, 3~4 times a week, or 5 or more times a week), season of blood draw (spring (March–May), summer (June–August), fall (September–November), and winter (December–February)), BMI (continuous), dietary supplement use (yes or no), dietary fiber intake (continuous), saturated fatty acid (SFA) intake (continuous), polyunsaturated fatty acid (PUFA) intake (continuous), and total energy intake (continuous) except for their own analysis. The significance level in all statistical analyses was p < 0.05.

3. Results

3.1. General Characteristics of the Participants by Category of Serum 25(OH)D Concentration

As shown in Figure 2, the median serum level of all participants was 15.4 ng/mL. Men and women had median serum 25(OH)D levels of 16.4 ng/mL and 14.7 ng/mL, respectively, indicating that the overall serum 25(OH)D level was deficient (below 20 ng/mL) and the range of serum level was relatively broad.
The proportion of participants with vitamin D deficiency (<10 ng/mL) and insufficiency (10 to <20 ng/mL) were 13.4% and 61.9%, respectively. The general features of the participants are listed in Table 1 according to categories of their serum 25(OH)D levels. In total, 46.1% of the participants with serum 25(OH)D levels below 10 ng/mL were male, whereas 53.9% were female. Furthermore, 55.8% of men and 44.2% of women had 25(OH)D concentrations of 10 to <20 ng/mL, and 64.8% of men and 35.2% of women had 25(OH)D concentrations greater than 20 ng/mL, indicating that women have significantly lower serum vitamin D levels than men. Higher 25(OH)D levels are associated with an older mean of age in both men and women.
Regarding the educational level, the majority of participants were high school and college graduates; however, their serum levels were relatively lower than those of elementary and middle school graduates. As expected, physical workers had significantly higher serum concentrations than office workers and the unemployed. The residential areas had a significant impact on the serum 25(OH)D concentration, with residents of the southern areas having higher levels than those of the northern areas. These phenomena were more obvious in men. Current smoking, season variation, and physical activity had no effect on the 25(OH)D concentration in the serum. However, the serum 25(OH)D concentrations differed significantly depending on the current alcohol consumption. The level of serum 25(OH)D was significantly and favorably elevated by dietary supplements, especially in women. Dietary supplement use was, therefore, included as a covariate in the statistical models, as it is known that individuals’ supplement use is associated with their diet, lifestyle, and health condition [42].

3.2. Daily Nutrient Intake by the Serum 25(OH)D Concentration

The daily nutrient intake is listed in Table 2 according to the serum 25(OH)D concentration range. The purpose of this study was to investigate the association between vitamin D status and MetS. Thus, the basic adjustment (age, education level, occupation, residential area, smoking, alcohol consumption, physical activity, dietary supplement, and season of blood draw) as well as the intake of energy, dietary fiber, SFA, PUFA, and body mass index (BMI) were additionally adjusted as these variables may influence metabolic profiles such as blood pressure.
Individuals with a blood 25(OH)D concentration of more than 20 ng/mL ingested the most protein and SFA daily. Lower serum 25(OH)D levels (<10 ng/mL) were related with higher daily consumptions of fat, MUFA, and PUFA. The serum 25(OH)D levels were strongly correlated with protein (p = 0.019), fat (p = 0.037), SFA (p = 0.008), MUFA (p = 0.010), and PUFA (p = 0.003) consumption. Similar trends were observed in men. The serum 25(OH)D level was significantly correlated with protein (p = 0.032), fat (p = 0.027), SFA (p = 0.006), MUFA (p = 0.005), and PUFA (p = 0.003) intake. Protein and SFA correlated positively with the serum 25(OH)D level, whereas fat, MUFA, and PUFA correlated negatively with the serum 25(OH)D level. However, in women, there was no connection between the nutrient intake and the serum 25(OH)D levels. Only the cholesterol consumption was slightly higher in those with higher serum 25(OH)D concentrations (p = 0.05).
Note that there was no correlation between the dietary vitamin D intake and the serum 25(OH)D categories. Likewise, there was no significant difference in the consumption of vitamin D-rich food groups of the participants contributing to vitamin D intake by the serum 25(OH)D level and gender (Supplement Table S1).

3.3. Relationship between the Serum 25(OH)D Level and MetS

The participants’ anthropometric and biochemical characteristics were listed in Table 3 in accordance with their serum 25(OH)D levels. Those with higher serum 25(OH)D concentrations (≥20 ng/mL) had significantly lower blood TG (p = 0.008). In addition, men demonstrated a dose-dependent reduction in blood TG alongside 25(OH)D level (p = 0.002), suggesting that an adequate serum 25(OH)D level (≥20 ng/mL) may reduce blood TG levels. There was no association between the serum 25(OH)D concentrations and any anthropometric or biochemical measurements in women.
The connection between the individuals’ serum 25(OH)D and each component of MetS was analyzed using complex sample logistic regression (Table 4). As the serum 25(OH)D concentration of all individuals increases, abdominal obesity and hypertriglyceridemia decrease significantly. A higher serum concentration of 25(OH)D was linked with lower abdominal obesity and a significant decrease in hypertriglyceridemia in men, which is consistent with Table 3’s findings regarding lower blood TG levels in higher serum 25(OH)D levels. In women, however, no association existed between serum 25(OH)D levels and any factor of MetS.

3.4. Relationship between the Dietary Vitamin D Intake and MetS

To examine the relationship between vitamin D intake and MetS, this study examined the correlation between anthropometric and biochemical factors and vitamin D intake calculated using a new established vitamin D DB. In all participants, as shown in Table 5, there found a negative connection between serum LDL cholesterol and vitamin D intake. This phenomenon was observed in women not in men. However, a significant positive correlation existed between weight and waist circumference and vitamin D intake in men. Significance of waist circumference was conserved even after BMI adjustment.
The relationship between vitamin D intake and MetS was then analyzed using composite sample logistic regression, as detailed in Table 6. There were no significant risk factors of MetS associated with a vitamin D intake among all participants. As expected from Table 5, a higher vitamin D intake was related with greater abdominal obesity and increased TG in men. In women, there was no relation between vitamin D intake and any MetS-related factor.

4. Discussion

Since local quantities of calcitriol are necessary for distinct tissue responses, they are dependent on the availability of 25(OH)D in the serum; consequently, the local calcitriol level should typically be higher than the serum level. Local calcitriol binds to the VDR in the cell nucleus. It is generally established that β cells in the pancreatic, musculoskeletal, and adipose tissues express VDR. Hence, the inability of β cells to convert pro-insulin into insulin can lead to vitamin D insufficiency and type 2 diabetes.
One pathophysiological mechanism between obesity and vitamin D deficiency could be vitamin D sequestration and volumetric dilution. Fat-soluble vitamin D is sequestered in adipose tissues and influences a greater volumetric dilution, resulting in decreasing serum vitamin D levels especially in obese individuals. However, other possible rationales also shown in our study may be poor eating habits and differences in gene expression, such as vitamin D metabolizing enzymes, which might follow gender differences. In addition, it is thought to be mediated by adiposity that vitamin D might release from the adipocyte during a reduction in the fat tissue, eventually resulting in a reduction in MetS.
One might think that increasing the vitamin D level would improve or prevent MetS. If serum vitamin D level rise and vitamin D functions properly at the cellular level, vitamin D-controlled transcript regulation such as cell differentiation, cell proliferation, and immunity may be enhanced. It includes the enhancement of the β cell function followed by the efficient regulation of insulin and other MetS-related metabolisms. Although our study design cannot identify the sequential relationship between MetS and vitamin D levels, several previous studies and our study have confirmed the inverse association between the serum 25(OH)D and MetS including obesity, insulin resistance, and blood pressure [19,43,44,45,46,47].
A recent study demonstrated an unfavorable association between serum 25(OH)D and fat intake in people with metabolic genetic risk [48]. Obesity caused by a high-fat diet has been reported to modify vitamin D-related enzymes in previous studies [49,50], which are potential mechanisms underlying the associations between MetS such as obesity and vitamin D status. However, our analysis showed that men with sufficient serum 25(OH)D levels (≥20 ng/mL) had significantly higher protein intake, SFA intake, and lower fat, MUFA, and PUFA intake. In addition, there were no relationships between daily nutrients intake and serum 25(OH)D levels in women.
Therefore, in order to examine the more direct relationship between vitamin D level (either serum level or dietary intake) and MetS, we controlled for some factors related to metabolic profiles such as BMI, total energy intake, dietary fiber intake, SFA intake, and PUFA intake, in addition to the usual factors such as sex, age, education, occupation, living area, smoking, alcohol drinking, physical activity, dietary supplement, and the season of blood draw in this study. The odds ratio for MetS components to the serum 25(OH)D concentration revealed that serum 25(OH)D was negatively correlated with abdominal obesity and increased TG in men, implying that vitamin D has a beneficial impact on lowering serum TG, abdominal obesity, and hypertriglyceridemia in Korean adults, particularly Korean men.
There are continuous reports of vitamin D and other associations with cholesterol and TG, both of which are diagnostic indicators of dyslipidemia [51,52,53,54]. A novel finding in our study is a negative link between the dietary vitamin D intake and serum LDL cholesterol levels only in Korean women, although they did not show a significant association of serum 25(OH)D concentration with MetS or its components and a weak but positive relationship between vitamin D intake and serum 25(OH)D.
Similar to our study, the Qatar women’s study and other studies found an inverse relationship between the MetS prevalence and serum 25(OH)D level, but no relationship between the serum 25(OH)D level and other Mets components, such as waist circumference, blood pressure, HbA1c, blood glucose, HDL cholesterol, and serum TG [55]. A study reported that dietary vitamin D intake and serum 25(OH)D levels were found to be inversely and significantly related to visceral adipose tissue, as well as the total adipose tissue and BMI. Therefore, our data support the current findings that increased dietary vitamin D intake and serum 25(OH)D levels in women may be beneficial for cardiovascular diseases.
The US Endocrine Society defines vitamin D deficiency as circulating 25(OH)D levels less than 20 ng/mL, and it recommends a target 25(OH)D concentration of 30 ng/mL to ensure vitamin D pleiotropic effects [7,56]. According to this definition, only 3.9% of the participants in this study were vitamin D sufficient. As a result, the majority of Korean adults have inadequate serum 25(OH)D levels. Between 2008 and 2014, the serum 25(OH)D levels decreased and vitamin D deficiency increased significantly in both males and females, according to the KNHANES [32,36,38]. However, the vitamin D intake was not adequately increased [36,37]. A variety of measures, including vitamin D consumption education and the development of vitamin D-fortified foods, must be implemented in Korea to improve the vitamin D nutritional status. A continuous follow-up study is being conducted to determine the effect of vitamin D intake and the resulting benefit on serum vitamin D levels and related health factors such as MetS.
The 2013−2014 KNHANES has a large sample size, but as a cross-sectional study, it cannot reveal the precise causal relationship between vitamin D status (intake and serum level) and MetS components. The absence of supplement vitamin D intake data is a weakness of both this study and the KNHANES for vitamin D research, as many adults currently take vitamin D supplements for bone health. In addition, a one-day, 24-h recall method could not calculate the average daily intake of the participants. Although the season for drawing blood is evenly distributed, repeated measurements of 25(OH)D for individuals may provide a more accurate picture of the long-term exposure. Furthermore, no research has been conducted on the effect of exposure time on the serum 25(OH)D concentration.
Interestingly, vitamin D intake did not differ according to the serum 25(OH)D categories, suggesting that vitamin D intake does not precisely reflect the serum 25(OH)D levels, at least in the present study. Despite the fact that there is a discrepancy between serum 25(OH)D and dietary vitamin D intake in terms of serum biomarkers and statistical analysis of MetS, this study is worthwhile to investigate the assessment of dietary vitamin D intake for health caution or a healthier lifestyle. Finally, this study used a newly supplemented and established vitamin D content DB with 2013−2014 KNHANES data to identify factors related to the serum 25(OH)D level, vitamin D intake, and MetS. These findings demonstrated that maintaining a healthy serum 25(OH)D level can improve MetS, particularly abdominal obesity, TG levels in men, and LDL cholesterol levels in women.

Supplementary Materials

The following supporting information can be downloaded at: https://0-www-mdpi-com.brum.beds.ac.uk/article/10.3390/app13063748/s1, Table S1: Contribution of vitamin D-rich food groups towards the daily mean intake of vitamin D by categories of the serum 25(OH)D concentration.

Author Contributions

Conceptualization, J.A.C., S.Y.L. and S.S.; methodology, S.-I.Y., S.S. and J.-Y.M.; software, S.-I.Y., S.Y.L., S.S. and J.-Y.M.; validation, J.A.C., S.-I.Y. and J.-Y.M.; formal analysis, S.-I.Y. and J.-Y.M.; investigation, J.A.C. and S.-I.Y.; resources, J.A.C.; data curation, S.-I.Y. and J.M; writing—original draft preparation, S.-I.Y. and J.A.C.; writing—review and editing, J.A.C. and S.-I.Y.; visualization, S.-I.Y. and J.-Y.M.; supervision, J.A.C.; project administration, J.-Y.M.; funding acquisition, J.A.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2022R1A2C1091570 and NRF-2020R1A5A8017671) and Chungnam National University Research grant.

Institutional Review Board Statement

Ethical review and approval were waived for this study, due to the collection, analysis, and publication of the retrospectively obtained and anonymized data for a non-interventional study.

Informed Consent Statement

Patient consent was waived due to the collection, analysis, and publication of the retrospectively obtained and anonymized data for a non-interventional study.

Data Availability Statement

None of the data were deposited in an official repository. The data that support the study findings are available from authors upon request.

Acknowledgments

The authors would like to thank the Ministry of Health and Welfare, as well as the Centers for Disease Control and Prevention, for allowing their survey data to be analyzed for the purpose of this study.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Reaven, G.M. Role of insulin resistance in human disease (syndrome X): An expanded definition. Annu. Rev. Med. 1993, 44, 121–131. [Google Scholar] [CrossRef] [PubMed]
  2. Grundy, S.M.; Cleeman, J.I.; Daniels, S.R.; Donato, K.A.; Eckel, R.H.; Franklin, B.A.; Gordon, D.J.; Krauss, R.M.; Savage, P.J.; Smith, S.C., Jr.; et al. Diagnosis and management of the metabolic syndrome: An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 2005, 112, 2735–2752. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Kendall, D.M.; Harmel, A.P. The metabolic syndrome, type 2 diabetes, and cardiovascular disease: Understanding the role of insulin resistance. Am. J. Manag. Care 2002, 8, S635–S653, quiz S654–637. [Google Scholar] [PubMed]
  4. McNeill, A.M.; Rosamond, W.D.; Girman, C.J.; Golden, S.H.; Schmidt, M.I.; East, H.E.; Ballantyne, C.M.; Heiss, G. The metabolic syndrome and 11-year risk of incident cardiovascular disease in the atherosclerosis risk in communities study. Diabetes Care 2005, 28, 385–390. [Google Scholar] [CrossRef] [Green Version]
  5. Cornier, M.A.; Dabelea, D.; Hernandez, T.L.; Lindstrom, R.C.; Steig, A.J.; Stob, N.R.; Van Pelt, R.E.; Wang, H.; Eckel, R.H. The metabolic syndrome. Endocr. Rev. 2008, 29, 777–822. [Google Scholar] [CrossRef]
  6. Ranasinghe, P.; Mathangasinghe, Y.; Jayawardena, R.; Hills, A.P.; Misra, A. Prevalence and trends of metabolic syndrome among adults in the asia-pacific region: A systematic review. BMC Public Health 2017, 17, 101. [Google Scholar] [CrossRef] [Green Version]
  7. Holick, M.F. Vitamin D deficiency. N. Engl. J. Med. 2007, 357, 266–281. [Google Scholar] [CrossRef]
  8. Bener, A.; Al-Hamaq, A.; Öztürk, M.; Tewfik, I. Vitamin D and Elevated Serum Uric Acid as Novel Predictors and Prognostic Markers for Type 2 Diabetes Mellitus. J. Pharm. Bioallied Sci. 2019, 11, 127–132. [Google Scholar] [CrossRef]
  9. Bener, A.; Al-Hamaq, A.O.; Kurtulus, E.M.; Abdullatef, W.K.; Zirie, M. The role of vitamin D, obesity and physical exercise in regulation of glycemia in Type 2 Diabetes Mellitus patients. Diabetes Metab. Syndr. 2016, 10, 198–204. [Google Scholar] [CrossRef]
  10. Gagnon, C.; Lu, Z.X.; Magliano, D.J.; Dunstan, D.W.; Shaw, J.E.; Zimmet, P.Z.; Sikaris, K.; Grantham, N.; Ebeling, P.R.; Daly, R.M. Serum 25-hydroxyvitamin D, calcium intake, and risk of type 2 diabetes after 5 years: Results from a national, population-based prospective study (the Australian Diabetes, Obesity and Lifestyle study). Diabetes Care 2011, 34, 1133–1138. [Google Scholar] [CrossRef] [Green Version]
  11. Gröber, U.; Holick, M.F. Diabetes Prevention: Vitamin D Supplementation May Not Provide Any Protection If There Is No Evidence of Deficiency! Nutrients 2019, 11, 2651. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Kuroda, M.; Sakaue, H. Role of vitamin D and calcium in obesity and type 2 diabetes. Clin. Calcium 2016, 26, 349–354. [Google Scholar]
  13. Mathieu, S.V.; Fischer, K.; Dawson-Hughes, B.; Freystaetter, G.; Beuschlein, F.; Schietzel, S.; Egli, A.; Bischoff-Ferrari, H.A. Association between 25-Hydroxyvitamin D Status and Components of Body Composition and Glucose Metabolism in Older Men and Women. Nutrients 2018, 10, 1826. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Nur-Eke, R.; Özen, M.; Çekin, A.H. Pre-Diabetics with Hypovitaminosis D Have Higher Risk for Insulin Resistance. Clin. Lab. 2019, 65, 5. [Google Scholar] [CrossRef] [PubMed]
  15. Sacerdote, A.; Dave, P.; Lokshin, V.; Bahtiyar, G. Type 2 Diabetes Mellitus, Insulin Resistance, and Vitamin D. Curr. Diab. Rep. 2019, 19, 101. [Google Scholar] [CrossRef]
  16. De Pergola, G.; Martino, T.; Zupo, R.; Caccavo, D.; Pecorella, C.; Paradiso, S.; Silvestris, F.; Triggiani, V. 25 Hydroxyvitamin D Levels are Negatively and Independently Associated with Fat Mass in a Cohort of Healthy Overweight and Obese Subjects. Endocr. Metab. Immune Disord. Drug Targets 2019, 19, 838–844. [Google Scholar] [CrossRef]
  17. Leu, M.; Giovannucci, E. Vitamin D: Epidemiology of cardiovascular risks and events. Best Pract. Res. Clin. Endocrinol. Metab. 2011, 25, 633–646. [Google Scholar] [CrossRef]
  18. Lystsova, N.L.; Petelina, T.I.; Gapon, L.I.; Avdeeva, K.S.; Bucova, S.G.; Suplotov, S.N. The role of vitamin D in the pathogenesis of arterial hypertension. Klin. Lab. Diagn. 2020, 65, 5–10. [Google Scholar] [CrossRef]
  19. Mousa, A.; Naderpoor, N.; de Courten, M.P.J.; Scragg, R.; de Courten, B. 25-hydroxyvitamin D is associated with adiposity and cardiometabolic risk factors in a predominantly vitamin D-deficient and overweight/obese but otherwise healthy cohort. J. Steroid Biochem. Mol. Biol. 2017, 173, 258–264. [Google Scholar] [CrossRef]
  20. Lee, K.; Kim, J. Serum vitamin D status and metabolic syndrome: A systematic review and dose-response meta-analysis. Nutr. Res. Pract. 2021, 15, 329–345. [Google Scholar] [CrossRef]
  21. Ju, S.Y.; Jeong, H.S.; Kim, D.H. Blood vitamin D status and metabolic syndrome in the general adult population: A dose-response meta-analysis. J. Clin. Endocrinol. Metab. 2014, 99, 1053–1063. [Google Scholar] [CrossRef] [PubMed]
  22. Parker, J.; Hashmi, O.; Dutton, D.; Mavrodaris, A.; Stranges, S.; Kandala, N.B.; Clarke, A.; Franco, O.H. Levels of vitamin D and cardiometabolic disorders: Systematic review and meta-analysis. Maturitas 2010, 65, 225–236. [Google Scholar] [CrossRef]
  23. Lu, Y.; Liu, M.; Pei, Y.; Li, J.; Tian, H.; Cheng, X.; Fang, F.; Sun, B.; Xiao, H.; Li, N.; et al. Low levels of serum 25-hydroxyvitamin D and risk of metabolic syndrome in China. Int. J. Clin. Exp. Med. 2015, 8, 13790–13796. [Google Scholar] [PubMed]
  24. Pannu, P.K.; Zhao, Y.; Soares, M.J.; Piers, L.S.; Ansari, Z. The associations of vitamin D status and dietary calcium with the metabolic syndrome: An analysis of the Victorian Health Monitor survey. Public Health Nutr. 2017, 20, 1785–1796. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Pham, T.M.; Ekwaru, J.P.; Setayeshgar, S.; Veugelers, P.J. The Effect of Changing Serum 25-Hydroxyvitamin D Concentrations on Metabolic Syndrome: A Longitudinal Analysis of Participants of a Preventive Health Program. Nutrients 2015, 7, 7271–7284. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Obispo Entrenas, A.; Legupin Tubio, D.; Lucena Navarro, F.; Martin Carvajal, F.; Gandara Adan, N.; Redondo Bautista, M.; Abiles Osinaga, J. Relationship Between Vitamin D Deficiency and the Components of Metabolic Syndrome in Patients with Morbid Obesity, Before and 1 Year After Laparoscopic Roux-en-Y Gastric Bypass or Sleeve Gastrectomy. Obes. Surg. 2017, 27, 1222–1228. [Google Scholar] [CrossRef] [PubMed]
  27. Pott-Junior, H.; Nascimento, C.M.C.; Costa-Guarisco, L.P.; Gomes, G.A.O.; Gramani-Say, K.; Orlandi, F.S.; Gratão, A.C.M.; Orlandi, A.; Pavarini, S.C.I.; Vasilceac, F.A.; et al. Vitamin D Deficient Older Adults Are More Prone to Have Metabolic Syndrome, but Not to a Greater Number of Metabolic Syndrome Parameters. Nutrients 2020, 12, 748. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Zeng, Y.; Luo, M.; Pan, L.; Chen, Y.; Guo, S.; Luo, D.; Zhu, L.; Liu, Y.; Pan, L.; Xu, S.; et al. Vitamin D signaling maintains intestinal innate immunity and gut microbiota: Potential intervention for metabolic syndrome and NAFLD. Am. J. Physiol. Gastrointest. Liver Physiol. 2020, 318, G542–G553. [Google Scholar] [CrossRef]
  29. Holick, M.F. Vitamin D status: Measurement, interpretation, and clinical application. Ann. Epidemiol. 2009, 19, 73–78. [Google Scholar] [CrossRef] [Green Version]
  30. Ross, A.C. The 2011 report on dietary reference intakes for calcium and vitamin D. Public Health Nutr. 2011, 14, 938–939. [Google Scholar] [CrossRef] [Green Version]
  31. Mitchell, D.M.; Henao, M.P.; Finkelstein, J.S.; Burnett-Bowie, S.A. Prevalence and predictors of vitamin D deficiency in healthy adults. Endocr. Pract. 2012, 18, 914–923. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Park, J.H.; Hong, I.Y.; Chung, J.W.; Choi, H.S. Vitamin D status in South Korean population: Seven-year trend from the KNHANES. Medicine 2018, 97, e11032. [Google Scholar] [CrossRef] [PubMed]
  33. Society, T.K.N. Dietary Reference Intakes for Koreans 2010; The Korean Nutrition Society: Seoul, Republic of Korean, 2010. [Google Scholar]
  34. Ministry of Health and Welfare, T.K.N.S. Dietary Reference Intakes for Koreans 2015; The Korean Nutrition Society: Sejong, Republic of Korean, 2015. [Google Scholar]
  35. Ministry of Health and Welfare, T.K.N.S. Dietary Reference Intakes for Koreans 2020; The Korean Nutrition Society: Sejong, Republic of Korean, 2020. [Google Scholar]
  36. Yoo, K.; Cho, J.; Ly, S. Vitamin D Intake and Serum 25-Hydroxyvitamin D Levels in Korean Adults: Analysis of the 2009 Korea National Health and Nutrition Examination Survey (KNHANES IV-3) Using a Newly Established Vitamin D Database. Nutrients 2016, 8, 610. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Shin, H.R.; Park, H.J.; Song, S.; Ly, S.Y. Dietary vitamin D intake in low ultraviolet irradiation seasons is associated with a better nutritional status of vitamin D in Korean adults according to the 2013-2014 National Health and Nutrition Examination Survey. Nutr. Res. 2022, 105, 53–65. [Google Scholar] [CrossRef]
  38. Kweon, S.; Kim, Y.; Jang, M.J.; Kim, Y.; Kim, K.; Choi, S.; Chun, C.; Khang, Y.H.; Oh, K. Data resource profile: The Korea National Health and Nutrition Examination Survey (KNHANES). Int. J. Epidemiol. 2014, 43, 69–77. [Google Scholar] [CrossRef] [Green Version]
  39. Subar, A.F.; Thompson, F.E.; Kipnis, V.; Midthune, D.; Hurwitz, P.; McNutt, S.; McIntosh, A.; Rosenfeld, S. Comparative validation of the Block, Willett, and National Cancer Institute food frequency questionnaires: The Eating at America’s Table Study. Am. J. Epidemiol. 2001, 154, 1089–1099. [Google Scholar] [CrossRef] [Green Version]
  40. Lee, M.S.; Carcone, A.I.; Ko, L.; Kulik, N.; Ellis, D.A.; Naar, S. Managing Outliers in Adolescent Food Frequency Questionnaire Data. J. Nutr. Educ. Behav. 2021, 53, 28–35. [Google Scholar] [CrossRef]
  41. Executive Summary of The 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). JAMA 2001, 285, 2486–2497. [CrossRef]
  42. Bezerra, F.F.; Normando, P.; Fonseca, A.C.P.; Zembrzuski, V.; Campos-Junior, M.; Cabello-Acero, P.H.; Faerstein, E. Genetic, sociodemographic and lifestyle factors associated with serum 25-hydroxyvitamin D concentrations in Brazilian adults: The Pró-Saúde Study. Cad. Saude Publica 2022, 38, e00287820. [Google Scholar] [CrossRef]
  43. Lagunova, Z.; Porojnicu, A.C.; Lindberg, F.; Hexeberg, S.; Moan, J. The dependency of vitamin D status on body mass index, gender, age and season. Anticancer Res. 2009, 29, 3713–3720. [Google Scholar] [CrossRef]
  44. Lagunova, Z.; Porojnicu, A.C.; Lindberg, F.A.; Aksnes, L.; Moan, J. Vitamin D status in Norwegian children and adolescents with excess body weight. Pediatr. Diabetes 2011, 12, 120–126. [Google Scholar] [CrossRef] [PubMed]
  45. Lagunova, Z.; Porojnicu, A.C.; Vieth, R.; Lindberg, F.A.; Hexeberg, S.; Moan, J. Serum 25-hydroxyvitamin D is a predictor of serum 1,25-dihydroxyvitamin D in overweight and obese patients. J. Nutr. 2011, 141, 112–117. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Akter, S.; Eguchi, M.; Kurotani, K.; Kochi, T.; Kashino, I.; Ito, R.; Kuwahara, K.; Tsuruoka, H.; Kabe, I.; Mizoue, T. Serum 25-hydroxyvitamin D and metabolic syndrome in a Japanese working population: The Furukawa Nutrition and Health Study. Nutrition 2017, 36, 26–32. [Google Scholar] [CrossRef] [PubMed]
  47. Vigna, L.; Cassinelli, L.; Tirelli, A.S.; Felicetta, I.; Napolitano, F.; Tomaino, L.; Mutti, M.; Barberi, C.E.; Riboldi, L. 25(OH)D Levels in Relation to Gender, Overweight, Insulin Resistance, and Inflammation in a Cross-Sectional Cohort of Northern Italian Workers: Evidence in Support of Preventive Health Care Programs. J. Am. Coll. Nutr. 2017, 36, 253–260. [Google Scholar] [CrossRef] [PubMed]
  48. Isgin-Atici, K.; Alathari, B.E.; Turan-Demirci, B.; Sendur, S.N.; Lay, I.; Ellahi, B.; Alikasifoglu, M.; Erbas, T.; Buyuktuncer, Z.; Vimaleswaran, K.S. Interaction between Dietary Fat Intake and Metabolic Genetic Risk Score on 25-Hydroxyvitamin D Concentrations in a Turkish Adult Population. Nutrients 2022, 14, 382. [Google Scholar] [CrossRef] [PubMed]
  49. Park, J.M.; Park, C.Y.; Han, S.N. High fat diet-Induced obesity alters vitamin D metabolizing enzyme expression in mice. Biofactors 2015, 41, 175–182. [Google Scholar] [CrossRef]
  50. De Oliveira, L.F.; de Azevedo, L.G.; da Mota Santana, J.; de Sales, L.P.C.; Pereira-Santos, M. Obesity and overweight decreases the effect of vitamin D supplementation in adults: Systematic review and meta-analysis of randomized controlled trials. Rev. Endocr. Metab. Disord. 2020, 21, 67–76. [Google Scholar] [CrossRef]
  51. Surdu, A.M.; Pînzariu, O.; Ciobanu, D.M.; Negru, A.G.; Căinap, S.S.; Lazea, C.; Iacob, D.; Săraci, G.; Tirinescu, D.; Borda, I.M.; et al. Vitamin D and Its Role in the Lipid Metabolism and the Development of Atherosclerosis. Biomedicines 2021, 9, 172. [Google Scholar] [CrossRef]
  52. Weber, K.; Erben, R.G. Differences in triglyceride and cholesterol metabolism and resistance to obesity in male and female vitamin D receptor knockout mice. J. Anim. Physiol. Anim. Nutr. 2013, 97, 675–683. [Google Scholar] [CrossRef]
  53. Imga, N.N.; Karci, A.C.; Oztas, D.; Berker, D.; Guler, S. Effects of vitamin D supplementation on insulin resistance and dyslipidemia in overweight and obese premenopausal women. Arch. Med. Sci. 2019, 15, 598–606. [Google Scholar] [CrossRef]
  54. Fu, J.; Hou, C.; Li, L.; Feng, D.; Li, G.; Li, M.; Li, C.; Gao, S.; Li, M. Vitamin D modifies the associations between circulating betatrophin and cardiometabolic risk factors among youths at risk for metabolic syndrome. Cardiovasc. Diabetol. 2016, 15, 142. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Ganji, V.; Sukik, A.; Alaayesh, H.; Rasoulinejad, H.; Shraim, M. Serum vitamin D concentrations are inversely related to prevalence of metabolic syndrome in Qatari women. Biofactors 2020, 46, 180–186. [Google Scholar] [CrossRef] [PubMed]
  56. Pludowski, P.; Holick, M.F.; Grant, W.B.; Konstantynowicz, J.; Mascarenhas, M.R.; Haq, A.; Povoroznyuk, V.; Balatska, N.; Barbosa, A.P.; Karonova, T.; et al. Vitamin D supplementation guidelines. J. Steroid. Biochem. Mol. Biol. 2018, 175, 125–135. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Applsci 13 03748 g001 550
Figure 1. Flowchart of participant inclusion and exclusion in the Korea National Health and Nutrition Examination Survey 2013–2014 (BMI; body mass index; 25(OH)D, 25-hydroxyvitamin D).
Figure 1. Flowchart of participant inclusion and exclusion in the Korea National Health and Nutrition Examination Survey 2013–2014 (BMI; body mass index; 25(OH)D, 25-hydroxyvitamin D).
Applsci 13 03748 g001
Applsci 13 03748 g002 550
Figure 2. Distribution of serum 25-hydroxyvitamin D (25(OH)D) concentration of participants. Median is represented by the line in the box. The interquartile range box represents the middle 50% of the distance (Q3–Q1) between the first and third quartiles (25th percentile and 75th percentile). The connecting lines of the boxes are the minimum and maximum values.
Figure 2. Distribution of serum 25-hydroxyvitamin D (25(OH)D) concentration of participants. Median is represented by the line in the box. The interquartile range box represents the middle 50% of the distance (Q3–Q1) between the first and third quartiles (25th percentile and 75th percentile). The connecting lines of the boxes are the minimum and maximum values.
Applsci 13 03748 g002
Table
Table 1. General characteristics of the participants by categories of serum 25-hydroxyvitamin D (25(OH)D) concentration and gender.
Table 1. General characteristics of the participants by categories of serum 25-hydroxyvitamin D (25(OH)D) concentration and gender.
VariablesSerum 25(OH)D Concentration (ng/mL)
All (n = 2513)Men (n = 1145)Women (n = 1368)
<10≥10, <20≥20p-Value<10≥10, <20 ≥20p-Value<10≥10, <20≥20p-Value
No. of participants(n = 336)(n = 1556)(n = 621) (n = 119)(n = 688)(n = 338) (n = 217)(n = 868)(n = 283)
Sex <0.001
Men119 (46.1)688 (55.8)338 (64.8)
Women217 (53.9)868 (44.2)283 (35.2)
Age, years40.2 ± 0.943.0 ± 0.746.0 ± 0.7<0.00139.4 ± 1.342.7 ± 0.946.0 ± 0.9<0.00139.6 ± 1.241.0 ± 0.943.6 ± 1.0<0.001
Education <0.001 0.001 <0.001
Elementary31 (5.6)129 (5.8)110 (11.7) 10 (5.1)39 (4.1)49 (9.7) 21 (6.0)90 (7.9)61 (15.4)
Middle school21 (6.0)114 (6.1)79 (11.5) 5 (3.9)54 (6.4)42 (10.6) 16 (7.8)60 (5.7)37 (13.2)
High school153 (49.3)631 (43.5)227 (41.3) 59 (52.3)285 (45.3)126 (42.1) 94 (46.7)346 (41.1)101 (39.9)
College or more131 (39.1)682 (44.7)205 (35.5) 45 (38.7)310 (44.2)121 (37.6) 86 (39.5)372 (45.3)84 (31.6)
Occupation <0.001 <0.001 0.014
Office worker, expert103 (32.4)469 (31.2)138 (25.7) 34 (31.5)231 (33.3)91 (29.7) 69 (33.1)238 (28.7)47 (18.2)
Physical work95 (28.6)567 (37.2)277 (44.0) 39 (30.8)311 (43.5)185 (51.2) 56 (26.7)256 (29.2)92 (30.7)
Inoccupation138 (39.1)520 (31.6)206 (30.3) 46 (37.7)146 (23.2)62 (19.1) 92 (40.3)374 (42.1)144 (51.1)
Region 0.001 0.006 0.010
Midland256 (74.8)1061 (69.2)365 (60.9) 92 (76.1)485 (70.3)198 (62.1) 164 (73.8)576 (67.8)167 (58.5)
Southland80 (25.2)495 (30.8)256 (39.1) 27 (23.9)203 (29.7)140 (37.9) 53 (26.2)292 (32.2)116 (41.5)
Current smoking 0.824 0.150 0.169
Not at all262 (72.6)1192 (70.7)474 (72.9) 63 (51.9)375 (52.6)205 (61.0) 199 (90.4)817 (93.4)269 (94.8)
Occasionally smoke10 (3.7)46 (3.5)13 (2.5) 8 (6.5)28 (4.5)8 (2.7) 2 (1.3)18 (2.3)5 (2.1)
Smoke64 (23.6)318 (25.8)134 (24.6) 48 (41.6)285 (42.9)125 (36.3) 16 (8.2)33 (4.3)9 (3.1)
Current alcohol use <0.001 0.009 0.013
Not at all72 (18.0)316 (16.4)135 (19.5) 17 (11.7)71 (9.8)55 (15.5) 55 (23.4)245 (24.8)80 (27.0)
Less than once per month120 (35.8)495 (32.0)172 (25.4) 30 (27.9)167 (25.8)65 (18.8) 90 (42.6)328 (39.7)107 (37.5)
2~4 times a month89 (29.2)404 (27.8)168 (29.5) 44 (37.9)215 (31.7)98 (30.9) 45 (22.0)189 (22.8)70 (26.7)
2~3 times a week33 (10.4)272 (19.0)98 (17.1) 17 (13.4)174 (24.8)78 (22.8) 16 (7.7)98 (11.8)20 (6.6)
4 or more times a week22 (6.6)69 (4.8)48 (8.5) 11 (9.2)61 (8.0)42 (12.0) 11 (4.3)8 (0.9)6 (2.1)
Physical activity 0.078 0.155 0.617
Not at all252 (71.7)1120 (69.1)416 (62.6) 72 (58.2)429 (61.2)198 (55.7) 180 (83.2)691 (78.9)218 (75.3)
1~2 times a week33 (10.3)191 (13.3)84 (15.3) 15 (13.3)100 (15.3)50 (16.2) 18 (7.7)91 (10.8)34 (13.6)
3~4 times a week29 (9.4)152 (11.4)60 (11.3) 13 (12.1)96 (14.8)43 (13.9) 16 (7.1)56 (7.0)17 (6.4)
5 or more times a week22 (8.6)93 (6.3)61 (10.8) 19 (16.4)63 (8.7)47 (14.2) 3 (2.0)30 (3.3)14 (4.7)
Dietary supplement <0.001 <0.001 <0.001
No222 (68.8)873 (58.7)270 (44.5) 86 (76.4)434 (64.0)173 (50.2) 136 (62.3)439 (52.1)97 (34.0)
Yes114 (31.2)683 (41.3)351 (55.5) 33 (23.6)254 (36.0)165 (49.8) 81 (37.7)429 (47.9)186 (66.0)
Season
Spring74 (20.0)406 (25.5)137 (21.9)0.34224 (18.2)173 (25.1)73 (21.9)0.22650 (21.6)233 (26.0)64 (21.9)0.371
Summer80 (21.0)393 (25.3)158 (25.3) 25 (19.3)182 (26.6)87 (24.5) 55 (22.5)211 (23.7)71 (26.9)
Fall82 (26.2)364 (21.9)156 (23.8) 36 (32.1)162 (21.7)80 (22.5) 46 (21.1)202 (22.0)76 (26.1)
Winter100 (32.8)393 (27.3)170 (29.0) 34 (30.4)171 (26.5)98 (31.1) 66 (34.8)222 (28.2)72 (25.1)
All analyses accounted for the national survey’s complex sampling design effect and suitable sampling weights. For qualitative variables, data are presented as the non-weighted number of cases (weighted%) or mean ± standard error for quantitative variable. p-values were taken by complex samples chi-square test or complex samples general linear model.
Table
Table 2. Daily nutrient intake of the participants by categories of serum 25-hydroxyvitamin D (25(OH)D) concentration and gender.
Table 2. Daily nutrient intake of the participants by categories of serum 25-hydroxyvitamin D (25(OH)D) concentration and gender.
VariablesSerum 25(OH)D Concentration (ng/mL)
All (n = 2513)Men (n = 1145)Women (n = 1368)
<10
(n = 336)		≥10, <20
(n = 1556)		≥20
(n = 621)		Trend p<10
(n = 119)		≥10, <20
(n = 688)		≥20
(n = 338)		Trend p<10
(n = 217)		≥10, <20
(n = 868)		≥20
(n = 283)		Trend p
Energy (kcal)2195.9 ± 39.52172.3 ± 34.22234.2 ± 36.40.2042447.31 ± 64.82434.6 ± 51.22511.7 ± 52.10.1641864.6 ± 47.81830.4 ± 44.01861.2 ± 50.50.936
Carbohydrate (g)318.4 ± 5.9312.2 ± 4.7312.6 ± 5.40.348355.7 ± 9.2349.4 ± 6.5351.6 ± 7.10.820276.1 ± 6.0272.8 ± 5.6272.4 ± 6.00.402
Protein (g)71.2 ± 1.873.7 ± 1.576.1 ± 1.90.01979.8 ± 2.884.9 ± 1.987.6 ± 2.60.03257.6 ± 2.457.8 ± 2.259.5 ± 2.40.393
Fat (g)51.7 ± 0.551.1 ± 0.450.5 ± 0.50.03758.1 ± 0.857.3 ± 0.656.4 ± 0.60.02744.1 ± 0.743.7 ± 0.643.7 ± 0.80.543
Dietary fiber (g)23.6 ± 0.822.9 ± 0.623.5 ± 0.80.83125.9 ± 1.125.2 ± 0.825.8 ± 1.10.84920.7 ± 1.120.2 ± 1.021.0 ± 1.20.808
Saturated fatty acid (g)13.6 ± 0.614.9 ± 0.515.3 ± 0.60.00814.1. ± 0.916.0 ± 0.716.9 ± 0.70.00613.2 ± 0.914.0 ± 0.913.8 ± 0.90.265
Monounsaturated fatty acid (g)16.3 ± 0.316.1 ± 0.315.5 ± 0.30.01018.7 ± 0.518.0 ± 0.417.2 ± 0.40.00514.2 ± 0.514.2 ± 0.414.0 ± 0.50.642
Polyunsaturated fatty acid (g)12.7 ± 0.512.8 ± 0.511.2 ± 0.50.00315.5 ± 1.014.7 ± 0.613.0 ± 0.60.0039.0 ± 0.79.9 ± 0.68.7 ± 0.70.561
Omega-3 fatty acid (g)1.8 ± 0.11.8 ± 0.11.8 ± 0.10.6302.0 ± 0.21.9 ± 0.12.0 ± 0.10.6251.6 ± 0.21.6 ± 0.21.6 ± 0.10.624
Omega-6 fatty acid (g)11.2 ± 0.111.2 ± 0.111.2 ± 0.10.97912.5 ± 0.212.6 ± 0.112.5 ± 0.10.9199.3 ± 0.29.2 ± 0.29.3 ± 0.20.899
Cholesterol (mg)255.6 ± 20.5276.1 ± 17.2277.0 ± 17.20.218290.1 ± 31.1316.4 ± 23.8309.1 ± 23.30.657195.0 ± 21.8212.6 ± 20.4228.0 ± 22.30.050
Vitamin D (µg)3.4 ± 0.73.7 ± 0.53.6 ± 0.40.8364.0 ± 1.24.0 ± 0.64.0 ± 0.50.9652.8 ± 1.13.5 ± 1.23.2 ± 1.20.385
Data are expressed as means ± standard errors. p-values were calculated by the complex sampling design using the general linear model procedure. Model was adjusted for sex, age, education, occupation, region, drinking, smoking, physical activity, dietary supplement, season of blood draw, BMI, and intakes of energy, saturated fatty acid, polyunsaturated fatty acid, and dietary fiber, except for itself. Abbreviation: Serum 25(OH)D, Serum 25-hydroxyvitamin D.
Table
Table 3. Anthropometric and biochemical measurements of the participants by categories of serum 25-hydroxyvitamin D (25(OH)D) concentration and gender.
Table 3. Anthropometric and biochemical measurements of the participants by categories of serum 25-hydroxyvitamin D (25(OH)D) concentration and gender.
VariablesSerum 25(OH)D Concentration (ng/mL)
All (n = 2513)Men (n = 1145)Women (n = 1368)
<10
(n = 336)		≥10, <20
(n = 1556)		≥20
(n = 621)		Trend p<10
(n = 119)		≥10, <20
(n = 688)		≥20
(n = 338)		Trend p<10
(n = 217)		≥10, <20
(n = 868)		≥20
(n = 283)		Trend p
Height (cm)164.8 ± 0.5164. 9 ± 0.4166.8 ± 0.40.994170.0 ± 0.8170.4 ± 0.5170.0 ± 0.50.806160.5 ± 0.7160.5 ± 0.6160.7 ± 0.70.741
Weight (kg)64.5 ± 0.964.3 ± 0.764.3 ± 0.80.81868.6 ± 1.369.2 ± 1.069.7 ± 1.00.39560.0 ± 1.360.0 ± 1.259.9 ± 1.40.907
BMI (kg/m2)23.5 ± 0.323.5 ± 0.223.6 ± 0.20.86223.7 ± 0.423.8 ± 0.324.1 ± 0.30.24223.3 ± 0.523.3 ± 0.423.2 ± 0.40.648
Waist circumference (cm)79.3 ± 0.879.4 ± 0.679.0 ± 0.70.58181.4 ± 1.081.7 ± 0.881.5 ± 0.90.98477.9 ± 1.278.0 ± 1.177.7 ± 1.20.761
Systolic blood pressure (mmHg)115.6 ± 1.0115.1 ± 0.8114.1 ± 0.90.122119.9 ± 1.7118.9 ± 1.2117.8 ± 1.20.194109.9 ± 1.2109.7 ± 1.1109.2 ± 1.20.580
Diastolic blood pressure (mmHg)75.5 ± 0.875.0 ± 0.674.6 ± 0.60.30078.4 ± 1.277.5 ± 0.876.8 ± 0.80.19871.9 ± 1.071.5 ± 0.871.6 ± 1.00.841
Fasting blood glucose (mg/dL)94.1 ± 1.094.2 ± 0.893.8 ± 0.90.70096.4 ± 1.594.8 ± 1.294.2 ± 1.30.27291.1 ± 0.992.6 ± 0.892.1 ± 1.10.271
Serum triglycerides (mg/dL)147.3 ± 10.5142.2 ± 8.1128.6 ± 8.80.008174.0 ± 16.2167.3 ± 12.0141.2 ± 12.20.002115.3 ± 8.6108.6 ± 8.6116.0 ± 9.80.936
Serum total-cholesterol (mg/dL)181.6 ± 2.5184.1 ± 2.0183.5 ± 2.10.560180.9 ± 3.6182.6 ± 2.7182.6 ± 2.80.725184.3 ± 3.8187.3 ± 3.3185.9 ± 3.50.617
Serum HDL cholesterol (mg/dL)51.5 ± 0.953.1 ± 0.752.8 ± 0.70.15847.6 ± 0.848.7 ± 0.848.9 ± 0.90.34156.7 ± 1.258.7 ± 1.157.8 ± 1.30.282
Serum LDL cholesterol (mg/dL)111.6 ± 5.8113.5 ± 4.7116.8 ± 6.10.507111.4 ± 7.7106.4 ± 5.4115.8 ± 6.80.52196.1 ± 9.8116.8 ± 6.9101.5 ± 10.60.553
Serum 25(OH)D (ng/mL)9.0 ± 0.215.4 ± 0.225.5 ± 0.3<0.0019.1 ± 0.315.8 ± 0.325.8 ± 0.4<0.0018.4 ± 0.314.6 ± 0.324.8 ± 0.4<0.001
Data are descried as means ± standard errors. p-values were obtained by the complex sampling design using general linear model procedure. Model was adjusted by sex, age, education, occupation, region, drinking, smoking, physical activity, dietary supplement, season of blood draw, BMI, and intakes of energy, saturated fatty acid, polyunsaturated fatty acid, and dietary fiber. BMI was not included as a covariate when compared weight, BMI and waist circumference. Abbreviation: Serum 25(OH)D, Serum 25-hydroxyvitamin D; BMI, body mass index; HDL, high-density lipoprotein; LDL, low-density lipoprotein.
Table
Table 4. Odds ratios for metabolic syndrome and associated factors by serum 25-hydroxyvitamin D (25(OH)D) concentration and gender.
Table 4. Odds ratios for metabolic syndrome and associated factors by serum 25-hydroxyvitamin D (25(OH)D) concentration and gender.
VariablesSerum 25(OH)D per 1 ng/mL Increment, Adjusted
All (n = 2513)Men (n = 1145)Women (n = 1368)
OR(95% CI)p-ValueOR(95% CI)p-ValueOR(95% CI)p-Value
Abdominal obesity0.971(0.951 0.991)0.0050.970(0.946 0.994)0.0170.980(0.949 1.012)0.223
Increased blood pressure0.991(0.970 1.012)0.4010.991(0.965 1.018)0.5010.997(0.963 1.032)0.865
High blood glucose0.998(0.979 1.017)0.8230.990(0.965 1.016)0.4581.008(0.983 1.034)0.527
Increased blood triglycerides0.976(0.958 0.996)0.0160.974(0.950 0.998)0.0370.985(0.958 1.013)0.289
Decreased HDL cholesterol0.987(0.970 1.004)0.1370.977(0.950 1.006)0.1180.996(0.975 1.017)0.696
Metabolic Syndrome0.984(0.961 1.008)0.1960.981(0.947 1.018)0.3090.992(0.960 1.024)0.610
The information was presented as adjusted odds ratio (OR) and 95% confidence intervals (CIs). Complex sampling design multivariate logistic regression analysis yielded p-values, adjusted for sex, age, education, occupation, region, drinking, smoking, physical activity, dietary supplement, season of blood draw, intakes of saturated fatty acid, polyunsaturated fatty acid, fiber, and energy and BMI (except for analyzing abdominal obesity).Metabolic Syndrome was determined by having three or more risk determinants among those with abdominal obesity (waist circumference greater than 90 cm for men and greater than 85 cm for women), high blood pressure (systolic ≥ 130 mmHg or diastolic ≥ 85 mmHg), high fasting blood glucose of ≥100 mg/dL, high serum triglycerides of ≥150 mg/dL, or low HDL (<40 mg/dL for men and <50 mg/dL for women). Abbreviation: Serum 25(OH)D, Serum 25-hydroxyvitamin D; HDL, high-density lipoprotein.
Table
Table 5. Relationship between anthropometric/biochemical measurements and vitamin D intake of participants.
Table 5. Relationship between anthropometric/biochemical measurements and vitamin D intake of participants.
VariablesVitamin D Intake (µg/day)
All (n = 2513)Men (n = 1145)Women (n = 1368)
β(95% CI)p-Valueβ(95% CI)p-Valueβ(95% CI)p-Value
Height (cm)0.037(−0.010 0.083)0.1260.055(−0.011 0.121)0.1030.032(−0.060 0.067)0.917
Weight (kg)0.084(−0.017 0.174)0.0690.142(0.028 0.257)0.015−0.043(−0.114 0.029)0.242
BMI (kg/m2)0.015(−0.010 0.041)0.2370.029(−0.004 0.063)0.089−0.019(−0.039 0.002)0.078
Waist circumference (cm)0.061(−0.010 0.131)0.0900.107(0.013 0.200)0.026−0.030(−0.094 0.034)0.356
Systolic blood pressure (mmHg)−0.031(−0.115 0.053)0.465−0.024(−0.131 0.082)0.655−0.050(−0.177 0.078)0.443
Diastolic blood pressure (mmHg)−0.033(−0.105 0.040)0.378−0.046(−0.148 0.055)0.371−0.023(−0.100 0.055)0.565
Fasting blood glucose (mg/dL)0.062(−0.027 0.151)0.1700.026(−0.063 0.114)0.5710.127(−0.040 0.294)0.135
HbA1C (%)0.000(−0.003 0.003)0.914−0.001(−0.005 0.002)0.4750.003(−0.003 0.009)0.290
Serum triglycerides (mg/dL)−0.440(−1.071 0.192)0.172−0.873(−1.799 0.052)0.064−0.115(−0.699 0.469)0.699
Serum total cholesterol (mg/dL)−0.171(−0.382 0.041)0.113−0.198(−0.438 0.042)0.106−0.186(−0.553 0.181)0.319
Serum HDL cholesterol (mg/dL)0.000(−0.068 0.068)0.9960.015(−0.077 0.107)0.747−0.031(−0.153 0.091)0.616
Serum LDL cholesterol (mg/dL)−0.684(−1.172 −0.196)0.006−0.397(−0.967 0.172)0.170−1.751(−3.193 −0.309)0.018
Serum 25(OH)D (ng/mL)0.010(−0.039 0.059)0.688−0.009(−0.075 0.057)0.7940.060(0.001 0.119)0.048
p−values were derived from the results of the complex samples general linear model adjusted by sex, age, education, occupation, region, drinking, smoking, physical activity, dietary supplement, BMI, and intakes of energy, saturated fatty acid, polyunsaturated fatty acid, and dietary fiber. For analysis of weight, BMI, and waist circumference, BMI was not included as a covariate. Abbreviation: BMI, body mass index; HbA1C, hemoglobin A1C; HDL, high-density lipoprotein; LDL, low-density lipoprotein; Serum 25(OH)D, Serum 25-hydroxyvitamin D; CI, confidence interval.
Table
Table 6. Odds ratios for metabolic syndrome and its components by vitamin D intake.
Table 6. Odds ratios for metabolic syndrome and its components by vitamin D intake.
VariablesVitamin D Intake per 1 µg/d Increment, Adjusted
All (n = 2513)Men (n = 1145)Women (n = 1368)
OR(95% CI)p-ValueOR(95% CI)p-ValueOR(95% CI)p-Value
Abdominal obesity1.020(0.999 1.043)0.0671.028(1.001 1.051)0.0430.980(0.951 1.010)0.193
Increased BP0.994(0.972 1.015)0.5630.992(0.966 1.019)0.5590.997(0.970 1.025)0.821
High blood glucose1.012(0.995 1.029)0.1761.021(0.996 1.047)0.0990.989(0.964 1.016)0.427
Increased TG0.984(0.968 1.001)0.0720.980(0.961 0.999)0.0410.993(0.967 1.020)0.597
Decreased HDL-C1.004(0.988 1.019)0.6560.997(0.972 1.023)0.8361.010(0.985 1.036)0.435
Metabolic syndrome1.012(0.991 1.033)0.2751.005(0.978 1.033)0.1051.014(0.987 1.041)0.308
The information was presented as odds ratio (OR) and 95% confidence intervals (CIs). Adjusted p-values were derived by a complicated sampling design multivariate logistic regression analysis, adjusted with sex, age, education, occupation, region, drinking, smoking, physical activity, dietary supplement, season of blood draw, intake of saturated fatty acid, polyunsaturated fatty acid, fiber, energy, and BMI (except for analyzing abdominal obesity). Abbreviation: HDL, high-density lipoprotein. Metabolic Syndrome was determined by having 3 or more risk determinants among abdominal obesity (waist circumference greater than 90 cm for men and greater than 85 cm for women), high blood pressure (systolic ≥ 130 mmHg or diastolic ≥ 85 mmHg), high fasting blood glucose of ≥100 mg/dL, high serum triglycerides of ≥150 mg/dL, or low HDL (<40 mg/dL for men and <50 mg/dL for women).
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Yoon, S.-I.; Min, J.-Y.; Ly, S.Y.; Song, S.; Cho, J.A. Association of Serum 25-Hydroxyvitamin D and Vitamin D Intake with the Prevalence of Metabolic Syndrome in Korean Adults: 2013–2014 Korea National Health and Nutrition Examination Survey. Appl. Sci. 2023, 13, 3748. https://0-doi-org.brum.beds.ac.uk/10.3390/app13063748

AMA Style

Yoon S-I, Min J-Y, Ly SY, Song S, Cho JA. Association of Serum 25-Hydroxyvitamin D and Vitamin D Intake with the Prevalence of Metabolic Syndrome in Korean Adults: 2013–2014 Korea National Health and Nutrition Examination Survey. Applied Sciences. 2023; 13(6):3748. https://0-doi-org.brum.beds.ac.uk/10.3390/app13063748

Chicago/Turabian Style

Yoon, Su-In, Jae-Yeon Min, Sun Yung Ly, SuJin Song, and Jin Ah Cho. 2023. "Association of Serum 25-Hydroxyvitamin D and Vitamin D Intake with the Prevalence of Metabolic Syndrome in Korean Adults: 2013–2014 Korea National Health and Nutrition Examination Survey" Applied Sciences 13, no. 6: 3748. https://0-doi-org.brum.beds.ac.uk/10.3390/app13063748

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