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Association between serum zinc level and body composition: The Korean National Health and Nutrition Examination Survey
Nutrition 32 (2016) 332–337
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Applied nutritional investigation
Association between serum zinc level and body composition: The Korean National Health and Nutrition Examination Survey Ha-Na Kim M.D., M.Sc. a, Sang-Wook Song M.D., Ph.D. a, Whan-Seok Choi M.D., Ph.D. b, * a b
Department of Family Medicine, College of Medicine, St. Vincent’s Hospital, The Catholic University of Korea, Seoul, Republic of Korea Department of Family Medicine, College of Medicine, Seoul St. Mary’s Hospital, The Catholic University of Korea, Seoul, Republic of Korea
a r t i c l e i n f o
a b s t r a c t
Article history: Received 3 June 2015 Accepted 14 September 2015
Objective: The aim of this study was to examine the association between serum zinc levels and several body composition factors in Korean adults. Methods: We used data from the Korean National Health and Nutrition Examination Survey, a cross-sectional survey of Korean civilians. Data from 1896 adults were analyzed. Results: Serum zinc levels in men with elevated waist circumference were higher than in those with normal waist circumference (152.1 3.7 mg/dL versus 137.8 2.2 mg/dL; P < 0.001) and serum zinc levels increased with increasing tertiles of total body fat percentage (134.2 2.8 mg/dL, 142 2.9 mg/dL, and 148 2.7 mg/dL; P ¼ 0.001). Among men with a normal waist circumference, serum zinc levels of those with the highest total body fat percentage were higher than in those with the lowest or medium total body fat percentage values (145.4 mg/dL versus 135.2 mg/dL; P ¼ 0.029). In contrast, in men with an elevated waist circumference, no difference in serum zinc levels according to total body fat percentage was detected. There was no relationship between serum zinc levels and body composition factors in women. Conclusions: Body zinc status might be associated with the quantity and distribution of body fat in Korean men. Additional sex-specific studies are needed to determine whether the relationship of body zinc status with abdominal obesity and total body fat affects metabolic disorders and cardiovascular diseases. Ó 2016 Elsevier Inc. All rights reserved.
Keywords: Zinc Body composition Body fat percentage Waist circumference Lean body mass
Introduction Body composition is important not only for physiological functioning but also in relation to metabolic disorders, cardiovascular disease (CVD), and mortality. Obesity, which is the excess accumulation of body fat, is an important public health problem because it is associated with an increased risk for type 2 diabetes mellitus, dyslipidemia, hypertension, and CVD, and its prevalence is increasing worldwide [1]. Furthermore, abdominal obesity, presenting as an increase in visceral adiposity, plays a vital role in the development of insulin resistance and the H-NK and W-SC conceived the study. H-NK, S-WS, and W-SC analyzed and interpreted the data. H-NK and W-SC wrote the manuscript. S-WS supervised the writing of the paper and provided critical revisions. All authors read and approved the final manuscript. The authors have no conflicts of interest to report. * Corresponding author: Tel.: þ82 31 249 8230; fax: þ82 31 248 7404. E-mail address: [email protected] (W.-S. Choi). http://dx.doi.org/10.1016/j.nut.2015.09.006 0899-9007/Ó 2016 Elsevier Inc. All rights reserved.
associated metabolic abnormalities [2]. In contrast, a reduction in muscle mass, known as sarcopenia, is associated with physical and functional impairment [3] and negative metabolic outcomes [4]; therefore, sarcopenia is a major global health issue. Zinc is the second most abundant trace element in the body and plays catalytic, structural, and regulatory roles in various cellular processes as an essential micronutrient. Additionally, zinc not only plays critical roles in cellular proliferation and differentiation [5], it also has an insulinomimetic effect on energy metabolism [6,7]. The association between zinc status and body composition such as body weight, body fat percentage, and lean body mass has been assessed in experimental studies. One study reported that zinc supplementation increased the body fat percentage in both genetic and diet-induced obese mice [8], and another showed that Znt7-deficient mice, which show dysfunctional incorporation of zinc in the Golgi apparatus, were lean due to a significant reduction in body fat composition [9]. In another study, maternal zinc
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restriction in rats increased body fat percentage and decreased lean and fat-free mass (FFM) in offspring [10]. In several studies conducted in children or adolescents, body zinc status was found to affect body composition. Zinc supplementation in Peruvian children with mild to moderate growth stunting induced an increase in the FFM [11], whereas in a study of children ages <2 y, zinc supplementation increased height but had no effect on weight gain [12]. Recent meta-analyses revealed that zinc supplementation increased linear growth and weight gain in children [13,14]. However, studies assessing the association between zinc status and body composition in adult populations are rare, and the results remain controversial [15,16]. Additionally, few studies have assessed the association between zinc status and body composition in a Korean population [17]. Therefore, using data from the Korean National Health and Nutrition Examination Survey (KNHANES), we evaluated whether serum zinc levels are associated with body composition in Korean adults. Methods Study population The present study used data collected from the KNHANES V-1, which was conducted between January and December 2010 [18]. We originally examined the data from 1988 adults, assessing serum zinc levels. Participants with missing information or data for major variables (n ¼ 81), decreased kidney function (estimated glomerular filtration rate [eGFR] <30 mL/min/1.73 m2; n ¼ 2), or who were pregnant (n ¼ 9) were excluded. Therefore, the present study population consisted of 1896 participants. This study was approved by the Institutional Review Board of the Catholic University of Korea (IRB approval no: VC14 EIME0157). Measurements of body composition factors After an overnight fast, specially trained examiners measured participants’ height, weight, and waist circumference (WC). WC was measured using a measuring tape in the horizontal plane around the umbilical region after exhaling. Abdominal obesity was defined as WC 90 cm (85 cm for women) [19]. Body mass index (BMI) was calculated as each participant’s weight (kg) divided by height squared (m2) and was classified as underweight, normal weight, overweight, or obese according to BMIs of <18.5 kg/m2, 18.5 to 22.9 kg/ m2, 23 to 24.9 kg/m2 and 25 kg/m2, respectively [20]. Body composition factors, including body lean and fat mass were measured using a whole-body dual-energy x-ray absorptiometry scanner (DXA; QDR 4500 A, Hologic, Inc., Waltham, MA, USA). Participants wore a lightweight gown without metal objects during the measurements. Skeletal muscle mass index (SMI) was calculated using the equation: (SMI [%] ¼ total skeletal muscle mass [kg]/body weight [kg] 100) [3]. Total body fat percentage (TBF) was calculated by the equation: (TBF [%] ¼ total fat mass [kg]/body weight [kg] 100). SMI and TBF were categorized into tertiles, with tertile 1, representing the lowest values, tertile 2, the medium values, and tertile 3, the highest values. Laboratory measurements Blood samples were collected from the antecubital vein of each participant after 12 h of fasting, processed, refrigerated immediately, and transported in cold storage to the Central Testing Institute in Seoul, Korea. All blood samples were analyzed within 24 h after arrival at the testing facility. To measure serum zinc concentrations, trace element tubes were used, and levels were determined by inductively coupled plasma mass spectrometry (ICP-MS; ELAN DRC II, PerkinElmer, Waltham, MA, USA). Serum samples were diluted with 2% nitric acid, and zinc concentrations were determined from the linear relationship (r ¼ 0.999) between the concentrations of a standard solution (1000 mg/mL; CLZN2-2 Y, SPEX CertiPrep, Metuchen, NJ, USA) and the absorbance. The accuracy of the analytical methods was assessed using standard reference materials (ClinChek Serum Controls, lyophilised for trace elements, RECIPE, Munich, Germany). The standard deviation index was 0.50, and the inter- and intra-assay coefficients of variation were 2% and 4%, respectively [21]. Serum zinc levels were categorized into tertiles: tertile 1 represented the lowest zinc levels, tertile 2 medium levels, and tertile 3 highest levels. The eGFR was estimated using the re-expressed “Modification of Diet in Renal Disease” study equation with calibrated serum creatinine values and the formula was: 175 (serum creatinine concentration)1.154 (age)0.203 for men, and the value was multiplied by a factor of 0.742 for women [22].
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Other variables Self-reported information regarding age, sex, smoking, alcohol consumption, and the amount of physical activity were obtained. Cigarette smoking was divided into three categories based on current use estimates: nonsmoker, exsmoker, and current smoker. Alcohol consumption was classified into three categories: abstinence (no alcoholic drinks consumed within the previous year), moderate drinking (<14 standard drinks consumed for men or <7 for women per week), and heavy drinking (>14 standard drinks consumed for men or >7 standard drinks for women per week). Physical activity was assessed as the amount and intensity of physical activity per week, and classified as low, moderate, or high. Low physical activity was defined as 150 min of moderate intensity or 75 min of vigorous intensity exercise per week [23]. Dietary intake was assessed using single 24-h recall and was estimated from the food composition tables of the Rural Development Administration in combination with the nutrient database of the Korea Health and Industry of Development Institute [24,25]. The nutrition survey was conducted at participants’ homes by trained dietitians, and additional tools such as food models, two-dimensional food volumes, and containers were used to help participants recall their nutrient intake. The estimated daily energy and fat intake data of the participants were used in this study. Statistical analysis We used the SAS PROC SURVEY module considering strata, clusters, and weights to analyze the data using a complex sampling design [26]. All analyses were performed using the sample weights from KNHANES. The characteristics of the study population were analyzed using analysis of variance for continuous variables and c2 tests for dichotomous variables. The data are expressed as means standard error or as percentages. The proportions of participants in zinc level tertile 3 according to body composition factors were analyzed using c2 tests. The differences in the mean zinc levels according to body composition factors were evaluated using analysis of covariance(ANCOVA). Model 1 was adjusted for age, and model 2 was adjusted for age, smoking, alcohol consumption, physical activity, body weight, total fat and energy intake per day, and eGFR levels as covariates. The associations between serum zinc levels and body composition factors were subjected to a multiple regression analysis. The differences in the mean serum zinc levels according to TBF tertiles and abdominal obesity were analyzed using (ANCOVA) after adjusting for the aforementioned covariates. All statistical analyses were performed using SAS software (ver. 9.2; SAS Institute, Cary, NC, USA). P < 0.05 was considered statistically significant.
Results The present study was conducted using the data from 1896 participants (937 men and 959 women). Table 1 shows the characteristics of the study participants according to serum zinc level tertiles. In men, significant differences in age (45.2, 44.3, and 41.3 y; P ¼ 0.010) and TBF (22.2%, 23.9%, and 23.4%; P ¼ 0.009) were observed according to the tertiles of serum zinc, whereas no differences were seen in women. The proportions of participants with zinc levels in tertile 3 according to body composition factors are shown in Figures 1 and 2. This proportion was lower in men with abdominal obesity than in those without abdominal obesity (27.4% versus 36.1%; P ¼ 0.046; Fig. 1B), and the proportion of men with zinc levels in tertile 3 increased, as the SMI tertiles increased (28.5%, 33.4%, and 39.2%; Ptrend ¼ 0.035; Fig. 1C). The proportion of participants with zinc levels in tertile 3 decreased as the TBF tertiles increased in both men (43.2%, 34%, and 23.4%; Ptrend < 0.001; Fig. 1D) and women (43.6%, 32.5%, and 30.6%; Ptrend ¼ 0.031; Fig. 2D). The mean serum zinc levels according to body composition factors are shown in Table 2. After adjusting for age, smoking, alcohol consumption, physical activity, body weight, total fat and energy intake per day, and eGFR levels, serum zinc levels in men with abdominal obesity were higher than in those without abdominal obesity (152.1 3.7 mg/dL versus 137.8 2.2 mg/dL; P < 0.001). Additionally, serum zinc levels increased as TBF tertiles increased (134.2 2.8 mg/dL, 142 2.9 mg/dL, and 148 2.7 mg/dL; P ¼ 0.001). However, in women, serum zinc levels did not differ according to body composition factors.
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Table 1 Characteristics of study participants according to serum zinc level tertile Men
N Zinc (mg/dL) Age (y) Current smoking (%) Heavy drinking (%) Physical activity (low, %) Energy intake (kcal/d) Fat intake (%) eGFR (mL$min$1.73 m2) Body composition factors Weight (kg) Height (cm) BMI (kg/m2) Waist circumference (cm) SMI (%) TBF (%)
P value
T1*
T2*
T3*
312 112.2 1 45.2 ± 1.2y 42.6 11.5 71.4 2463.1 82.9 18.7 96.6 1.4
313 139.2 0.5 44.3 ± 1.2 46.4 9.7 71 2579.7 85.1 18.1 95.6 1.1
312 173.6 1.8 41.3 ± 0.8 42.4 8.5 68.5 2451.1 66.5 19.9 95.7 0.9
70 0.6 170.7 0.4 24 0.2 83.2 0.6 32.2 22.2
71 0.8 170.6 0.5 24.3 0.2 84.7 0.7 31.6 23.9
70.3 0.8 171.5 0.5 23.9 0.2 83.8 0.6 32 23.4
Women
P value
T1*
T2*
T3*
– – 0.010 0.689 0.586 0.778 0.419 0.107 0.790
319 102.7 0.9 46.8 1.3 4.5 6.7 80.5 1708.4 43.9 17.1 100.9 1.5
320 129 0.5 46.3 1.1 3.8 6.8 81 1743 49.6 17.8 99.4 1.4
320 160.8 1.8 44.6 1.3 6 5.3 78.2 1732.7 49.6 17.5 99.2 1.5
– – 0.480 0.622 0.815 0.803 0.859 0.748 0.678
0.631 0.306 0.249 0.214 0.116 0.009
58.3 0.7 157.7 0.5 23.5 0.4 77.9 0.8 25 33.5
58.6 0.6 157.5 0.4 23.7 0.2 79.2 0.6 24.7 34.7
57 0.7 156.9 0.5 23.2 0.3 76.9 0.7 25 34.6
0.216 0.504 0.401 0.067 0.547 0.120
BMI, body mass index; eGFR, estimated glomerular filtration rate; SMI, skeletal muscle mass index; TBF, total body fat percentage Values are expressed as means standard error or percentages * Tertile (T) 1, the lowest zinc levels; T2, medium zinc levels; and T3, the highest zinc levels. y Results in bold indicate statistical significance at the 0.05 level.
In men, serum zinc levels were positively associated with TBF (b ¼ 0.485; P ¼ 0.010) and, after adjusting for age (model 1), serum zinc levels were positively associated with WC (b ¼ 0.262; P ¼ 0.033) and TBF (b ¼ 0.538; P ¼ 0.004). The positive association between serum zinc levels, WC, and TBF remained significant (b ¼ 1.074; P < 0.001 and b ¼ 0.831; P < 0.001, respectively) after adjusting for age, smoking, alcohol consumption, physical activity, body weight, total fat and energy intake per day, and eGFR levels (model 2; Table 3). Serum zinc levels according to TBF tertiles and abdominal obesity after adjusting for the aforementioned covariates are shown in Figure 3. In men without abdominal obesity, the serum zinc levels of those with TBF tertile 3 were higher than in those with TBF tertile 1 or 2 (145.4 mg/dL versus 135.2 mg/dL; P ¼ 0.029; Fig. 3A). However, in men with abdominal obesity, zinc levels were similar among participants with TBF tertile 1, 2, or 3 (Fig. 3A). There were no differences in women’s serum zinc levels according to TBF tertiles or abdominal obesity (Fig. 3B).
Discussion In the present study, the proportion of men with the highest zinc levels (tertile 3) without abdominal obesity was higher than that of men with abdominal obesity, and the proportion of men with the highest zinc levels decreased as TBF increased (Fig. 1B, 1D). However, associations between abdominal obesity, TBF, and serum zinc levels were altered after adjusting for age and other covariates, such as alcohol consumption [27], smoking [28], physical activity [29], body weight, energy and fat intake per day, and eGFR levels [30], which could affect body zinc status. Therefore, the presence of abdominal obesity and increased body fat were associated positively with serum zinc levels in men (Tables 2 and 3). Inconsistent with this result, a cross-sectional study found that an elevated BMI was associated with low plasma zinc levels [15], and another study reported negative associations of plasma zinc levels with TBF and WC [16]. However, the results from that study were adjusted using only age as
Fig. 1. Percentage of men in the highest zinc level tertile (T3) according to body composition factors. (A) Obesity was defined as a body mass index 25.0 kg/m2. (B) Abdominal obesity was defined as a waist circumference 90 cm. C and D were categorized into tertile 1 (T1) representing the lowest values, T2 the medium values, and T3 the highest values. P values were analyzed using c2 tests. *P < 0.05, yPtrend < 0.05. SMI, skeletal muscle mass index; TBF, total body fat percentage.
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Fig. 2. Percentage of women in the highest zinc level tertile (T3) according to body composition factors. (A) Obesity was defined as a body mass index ‡25.0 kg/m2. (B) Abdominal obesity was defined as a waist circumference 85 cm. C and D were categorized into tertile 1 (T1) representing the lowest values, T2 the medium values, and T3 the highest values. P values were analyzed using c2 tests. *P < 0.05, yPtrend < 0.05. SMI, skeletal muscle mass index; TBF, total body fat percentage.
a covariate, and the findings from the cross-sectional study were not adjusted for age or other factors that could affect body zinc status. Additionally, zinc is highly concentrated in animal food sources such as the flesh and organs of mammals, fowl, crustaceans and fish, and a high intake of protein- and fat-rich foods could contribute to the elevation of serum zinc levels [31]. Therefore, we performed this analysis after adjusting for energy and fat intake per day. The mechanism underlying the positive association of serum zinc levels with TBF and abdominal obesity in Korean men is unclear, but it could be explained by certain factors. First, zinc has a stimulatory effect on lipogenesis, similar to the effects of insulin on lipid metabolism, which stimulates fatty acid and triacylglycerol synthesis in adipocytes and increases triglyceride uptake into fat tissues, suggesting that the insulinomimetic effects of zinc on adipose tissue might affect body fat accumulation [6,7,32]. Second, body zinc status is related to appetite [33,34]. It
has been reported that low zinc intake in zinc-deficient rats resulted in reduced carbohydrate consumption and decreased body fat [35]. One study with rats showed that oral zinc intake stimulated food intake through orexigenic peptides coupled to the afferent vagal nerve [36]. The mechanism by which zinc status affects appetite is unclear because the neurobiological regulation of appetite is complex. In an animal study, the release of neuropeptide Y (NPY) from terminals in the paraventricular nucleus of the hypothalamus of zinc-deficient animals was impaired significantly; thus, zinc deficiency might cause anorexia by inhibiting the release of NPY [37]. Third, zinc is an essential cofactor for antioxidant enzymes, such as glutathione peroxidase and superoxide dismutase, decreases the generation of reactive oxygen species, and activates metallothionein, which decreases the hydroxyl radical burden [38]. Visceral adiposity and TBF are related to chronic inflammation [39] and oxidative stress [40]. Therefore, as visceral adiposity and TBF increase, it is
Table 2 Mean serum zinc levels according to body composition factors Men
Women
Unadjusted BMI Underweight Normal weight Overweight Obese P value Waist circumference Abdominal obesity, no Abdominal obesity, yes P value SMIz Tertile 1 Tertile 2 Tertile 3 P value TBFz Tertile 1 Tertile 2 Tertile 3 P value
140.3 140.2 148.2 143 0.381
2.1 3 5.1 2.5
Model 1* 147 139.9 140 142.8 0.452
5.3 2.1 3 2.5
Model 2* 143.5 137.4 140.1 146.1 0.187
6.7 2.7 3.1 3.3
Unadjusted 131.4 129.1 129.8 126.8 0.425
2.3 3 3.5 2.6
Model 1* 127.5 131 129.8 128 0.669
3.6 2.3 3 2.7
Model 2* 129.7 129.5 129.9 127.5 0.933
4.9 2.3 3.2 3
139.8 ± 1.8y 146.5 ± 2.8 0.009
139.2 ± 1.8 146.9 ± 2.8 0.002
137.8 ± 2.2 152.1 ± 3.7 <0.001
130.2 2.1 128.7 2.2 0.536
129.5 2.1 130.1 2.3 0.791
127.4 2.1 132 2.6 0.151
142.9 2.4 141.6 2.7 140 2.4 0.6231
143.2 2.4 141.7 2.7 138.5 2.4 0.249
143 2.6 143.6 3.2 137.8 2.5 0.137
129.1 2.7 129.8 2.1 129.6 2.7 0.977
130.2 2.7 129.8 2.1 128.9 2.7 0.927
129.5 2.5 129.7 2.1 127.9 2.8 0.843
136.6 ± 2.2 142.4 ± 2.6 145.9 ± 2.2 <0.001
135.7 ± 2.2 142.5 ± 2.7 145.7 ± 2.3 <0.001
134.2 ± 2.8 142.0 ± 2.9 148 ± 2.7 0.001
128.4 2.7 129.3 2.3 130.8 2.7 0.751
127.5 2.7 129.8 2.3 131.8 2.6 0.467
127.8 3.1 128.1 2.1 131.3 2.5 0.453
BMI, body mass index; eGFR, estimated glomerular filtration rate; SMI, skeletal muscle mass index; TBF, total body fat percentage Values are expressed as means standard error * Model 1, adjusted for age; model 2, adjusted for age, alcohol consumption, smoking, physical activity, body weight, energy and fat intake per day, and eGFR levels. y Results in bold indicate statistical significance at the 0.05 level. z Tertile 1 represents the lowest values, tertile 2 medium values, and tertile 3 highest values.
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Table 3 Associations between serum zinc levels and body composition factors Men
Unadjusted BMI (kg/m2) WC (cm) SMI (%) TBF (%) Model 1y BMI (kg/m2) WC (cm) SMI (%) TBF (%) Model 2y BMI (kg/m2) WC (cm) SMI (%) TBF (%)
Women
b
SE
b
SE
P value
0.187 0.185 0.076 0.485*
0.337 0.121 0.418 0.188
0.578 0.128 0.854 0.010
0.529 0.178 0.417 0.294
0.333 0.134 0.582 0.261
0.114 0.185 0.470 0.262
0.184 0.262 0.368 0.538
0.331 0.122 0.426 0.184
0.579 0.033 0.388 0.004
0.288 0.061 0.075 0.458
0.331 0.150 0.631 0.272
0.385 0.683 0.905 0.094
1.003 1.074 0.419 0.831
0.963 0.293 0.547 0.296
0.299 <0.001 0.443 <0.001
0.581 0.241 0.190 0.527
0.809 0.305 0.653 0.308
0.473 0.431 0.770 0.089
P value
BMI, body mass index; eGFR, estimated glomerular filtration rate; SE, standard error; SMI, skeletal muscle mass index; TBF, total body fat percentage; WC, waist circumference * Results in bold indicate statistical significance at the 0.05 level. y Model 1, adjusted for age; model 2, adjusted for age, alcohol consumption, smoking, physical activity, body weight, energy and fat intake per day, and eGFR levels.
possible that serum zinc levels increase to cope with chronic inflammation and oxidative stress caused by elevated body fat. Although total body fat plays an important role in the development of metabolic abnormalities [41], it has been reported that abdominal obesity presenting as increased visceral adiposity is another major contributor to metabolic risk and CVD [42]. In the present study, subgroup analysis according to abdominal obesity revealed that men without abdominal adiposity but with high body fat had higher serum zinc levels than those with low to moderate body fat. However, in men with abdominal obesity, the serum zinc level in those with high body fat was similar to those who have low to moderate body fat. Thus, the positive relationship between TBF and serum zinc levels seen in men overall might be attenuated in men with abdominal obesity, suggesting that the men with high body fat and abdominal obesity may be relatively zinc deficient. Indeed, zinc supplementation prevents additional redox stress-associated damage and enhances cardiac function [43] and, hence, could have favorable effects in obesity, diabetes, and CVD. However, in a meta-analysis of 20 randomized controlled trials, zinc had a divergent effect on cholesterol metabolism related to insulin resistance, which is closely associated with abdominal obesity; in
healthy individuals, zinc supplementation was associated with a decrease in plasma high-density lipoprotein cholesterol (HDL-C) levels, but in those with type 2 diabetes mellitus, zinc supplementation showed an increased HDL-C, which contributed to a reduction in CVD risk [44]. Further studies are needed to determine whether additional dietary or supplemental zinc intake should be recommended in men with abdominal obesity and high body fat, and whether high zinc levels in men without abdominal obesity but with high body fat affect the risk for CVD. There were no significant associations in women between serum zinc levels and body composition factors. Consistent with these results, a cross-sectional study involving 580 Mexican women identified no associations between plasma zinc levels and TBF, BMI, and abdominal obesity after adjusting for age, crowding, and years of mother’s education [45]. However, in a study conducted without adjustment for covariates in 105 women, plasma zinc levels decreased as BMI increased [46]. There are several factors that could affect body composition in women in particular such as pregnancy, use of oral contraceptives, or altered sex hormone levels. Although we excluded pregnant women (n ¼ 9) from the analysis, we did not adjust for other covariates that might affect body composition in women because they were not measured or surveyed in the KNHANES. Therefore, additional studies are needed to clarify the association between body zinc status and body composition in women. A strength of this study was that the data were collected through a representative nationwide survey of the South Korean population. Additionally, this is the first study with Korean adults to investigate the associations between serum zinc levels and various body composition parameters. However, this study also had certain limitations. First, it was conducted using a crosssectional design. Second, the dietary patterns and the types of food as sources of zinc intake were not included as covariates because dietary zinc intake was not estimated in the KNHANES. The bioavailability of zinc is determined mostly by the amount of zinc as well as by phytate in the diet, which is a major inhibitor of zinc absorption. Therefore, not only total zinc intake but also the types of foods or dietary patterns should be considered when assessing dietary zinc intake [47], and further studies are warranted to clarify the associations between dietary zinc intake, serum zinc levels, and body composition factors. Third, other confounding conditionsdsuch as acute stress, infection, altered steroid hormone levels, weight loss, or muscle catabolism during illnessesdcan affect serum zinc levels but are not associated with the actual status of body zinc. However, these factors were not considered in this study. Finally, we did not consider other
Fig. 3. Serum zinc levels according to TBF tertiles and the presence of abdominal obesity. TBF was categorized into tertile 1 (T1) representing the lowest values, T2 the medium values, and T3 the highest values. Data are expressed as means standard error, and analyzed using analysis of covariance. (A and B) Abdominal obesity was defined as a waist circumference 90 cm (85 cm for women). *P < 0.05, yPtrend < 0.05. TBF, total body fat percentage.
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trace elements, such as copper, that could affect body zinc status, because the elemental minerals were not measured in the KNHANES. Conclusion Serum zinc concentrations were positively associated with both abdominal obesity and total body fat in men overall. In men without abdominal obesity, serum zinc levels of those with the highest total body fat were higher than in those with low to medium values of total body fat; however, there was no positive relationship between serum zinc levels and total body fat in men with abdominal obesity. The findings suggest that serum zinc concentrations might be associated with the quantity and distribution of body fat in Korean men. Further sex-specific studies are needed to determine whether the associations between serum zinc concentrations and body fat status affect the development or prevention of CVD. References [1] Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2014;384:766–81. [2] Neeland IJ, Ayers CR, Rohatgi AK, Turer AT, Berry JD, Das SR, et al. Associations of visceral and abdominal subcutaneous adipose tissue with markers of cardiac and metabolic risk in obese adults. Obesity 2013;21:E439–47. [3] Janssen I, Heymsfield SB, Ross R. Low relative skeletal muscle mass in older persons is associated with functional impairment and physical disability. J Am Geriatr Soc 2002;50:889–96. [4] Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: report of the European Working Group on Sarcopenia in Older People. Age Ageing 2010;39:412–23. [5] MacDonald RS. The role of zinc in growth and cell proliferation. J Nutr 2000;130:1500s–8s. [6] Yoshikawa Y, Ueda E, Kojima Y, Sakurai H. The action mechanism of zinc complexes with insulinomimetic activity in rat adipocytes. Life Sci 2004;75:741–51. [7] Ilouz R, Kaidanovich O, Gurwitz D, Eldar-Finkelman H. Inhibition of glycogen synthase kinase-3 beta by bivalent zinc ions: insight into the insulin-mimetic action of zinc. Biochem Biophys Res Commun 2002;295:102–6. [8] Chen MD, Lin PY, Cheng V, Lin WH. Zinc supplementation aggravates body fat accumulation in genetically obese mice and dietary-obese mice. Biol Trace Elem Res 1996;52:125–32. [9] Huang L, Yu YY, Kirschke CP, Gertz ER, Lloyd KK. Znt7 -deficient mice display reduced body zinc status and body fat accumulation. J Biol Chem 2007;282:37053–63. [10] Padmavathi IJ, Kishore YD, Venu L, Ganeshan M, Harishankar N, Giridharan NV, et al. Prenatal and perinatal zinc restriction: effects on body composition, glucose tolerance and insulin response in rat offspring. Exp Physiol 2009;94:761–9. [11] Arsenault JE, Lopez de Romana D, Penny ME, Van Loan MD, Brown KH. Additional zinc delivered in a liquid supplement, but not in a fortified porridge, increased fat-free mass accrual among young Peruvian children with mild-to-moderate stunting. J Nutr 2008;138:108–14. [12] Abdollahi M, Abdollahi Z, Fozouni F, Bondarianzadeh D. Oral zinc supplementation positively affects linear growth, but not weight, in children 6-24 months of age. Int J Prev Med 2014;5:280–6. [13] Imdad A, Bhutta ZA. Effect of preventive zinc supplementation on linear growth in children under 5 years of age in developing countries: a metaanalysis of studies for input to the lives saved tool. BMC Public Health 2011;11:S22. [14] Brown KH, Peerson JM, Baker SK, Hess SY. Preventive zinc supplementation among infants, preschoolers, and older prepubertal children. Food Nutr Bull 2009;30:S12–40. [15] Ozata M, Mergen M, Oktenli C, Aydin A, Sanisoglu SY, Bolu E, et al. Increased oxidative stress and hypozincemia in male obesity. Clin Biochem 2002;35:627–31. [16] Singh RB, Beegom R, Rastogi SS, Gaoli Z, Shoumin Z. Association of low plasma concentrations of antioxidant vitamins, magnesium and zinc with high body fat per cent measured by bioelectrical impedance analysis in Indian men. Magnes Res 1998;11:3–10.
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[35] Rains TM, Shay NF. Zinc status specifically changes preferences for carbohydrate and protein in rats selecting from separate carbohydrate-, protein-, and fat-containing diets. J Nutr 1995;125:2874–9. [36] Ohinata K, Takemoto M, Kawanago M, Fushimi S, Shirakawa H, Goto T, et al. Orally administered zinc increases food intake via vagal stimulation in rats. J Nutr 2009;139:611–6. [37] Huntington CE, Shay NF, Grouzmann E, Arseneau LM, Beverly JL. Zinc status affects neurotransmitter activity in the paraventricular nucleus of rats. J Nutr 2002;132:270–5. [38] Maret W, Krezel A. Cellular zinc and redox buffering capacity of metallothionein/thionein in health and disease. Mol Med 2007;13:371–5. [39] Item F, Konrad D. Visceral fat and metabolic inflammation: the portal theory revisited. Obes Rev 2012;13:S30–9. [40] Fujita K, Nishizawa H, Funahashi T, Shimomura I, Shimabukuro M. Systemic oxidative stress is associated with visceral fat accumulation and the metabolic syndrome. 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Applied nutritional investigation
Association between serum zinc level and body composition: The Korean National Health and Nutrition Examination Survey Ha-Na Kim M.D., M.Sc. a, Sang-Wook Song M.D., Ph.D. a, Whan-Seok Choi M.D., Ph.D. b, * a b
Department of Family Medicine, College of Medicine, St. Vincent’s Hospital, The Catholic University of Korea, Seoul, Republic of Korea Department of Family Medicine, College of Medicine, Seoul St. Mary’s Hospital, The Catholic University of Korea, Seoul, Republic of Korea
a r t i c l e i n f o
a b s t r a c t
Article history: Received 3 June 2015 Accepted 14 September 2015
Objective: The aim of this study was to examine the association between serum zinc levels and several body composition factors in Korean adults. Methods: We used data from the Korean National Health and Nutrition Examination Survey, a cross-sectional survey of Korean civilians. Data from 1896 adults were analyzed. Results: Serum zinc levels in men with elevated waist circumference were higher than in those with normal waist circumference (152.1 3.7 mg/dL versus 137.8 2.2 mg/dL; P < 0.001) and serum zinc levels increased with increasing tertiles of total body fat percentage (134.2 2.8 mg/dL, 142 2.9 mg/dL, and 148 2.7 mg/dL; P ¼ 0.001). Among men with a normal waist circumference, serum zinc levels of those with the highest total body fat percentage were higher than in those with the lowest or medium total body fat percentage values (145.4 mg/dL versus 135.2 mg/dL; P ¼ 0.029). In contrast, in men with an elevated waist circumference, no difference in serum zinc levels according to total body fat percentage was detected. There was no relationship between serum zinc levels and body composition factors in women. Conclusions: Body zinc status might be associated with the quantity and distribution of body fat in Korean men. Additional sex-specific studies are needed to determine whether the relationship of body zinc status with abdominal obesity and total body fat affects metabolic disorders and cardiovascular diseases. Ó 2016 Elsevier Inc. All rights reserved.
Keywords: Zinc Body composition Body fat percentage Waist circumference Lean body mass
Introduction Body composition is important not only for physiological functioning but also in relation to metabolic disorders, cardiovascular disease (CVD), and mortality. Obesity, which is the excess accumulation of body fat, is an important public health problem because it is associated with an increased risk for type 2 diabetes mellitus, dyslipidemia, hypertension, and CVD, and its prevalence is increasing worldwide [1]. Furthermore, abdominal obesity, presenting as an increase in visceral adiposity, plays a vital role in the development of insulin resistance and the H-NK and W-SC conceived the study. H-NK, S-WS, and W-SC analyzed and interpreted the data. H-NK and W-SC wrote the manuscript. S-WS supervised the writing of the paper and provided critical revisions. All authors read and approved the final manuscript. The authors have no conflicts of interest to report. * Corresponding author: Tel.: þ82 31 249 8230; fax: þ82 31 248 7404. E-mail address: [email protected] (W.-S. Choi). http://dx.doi.org/10.1016/j.nut.2015.09.006 0899-9007/Ó 2016 Elsevier Inc. All rights reserved.
associated metabolic abnormalities [2]. In contrast, a reduction in muscle mass, known as sarcopenia, is associated with physical and functional impairment [3] and negative metabolic outcomes [4]; therefore, sarcopenia is a major global health issue. Zinc is the second most abundant trace element in the body and plays catalytic, structural, and regulatory roles in various cellular processes as an essential micronutrient. Additionally, zinc not only plays critical roles in cellular proliferation and differentiation [5], it also has an insulinomimetic effect on energy metabolism [6,7]. The association between zinc status and body composition such as body weight, body fat percentage, and lean body mass has been assessed in experimental studies. One study reported that zinc supplementation increased the body fat percentage in both genetic and diet-induced obese mice [8], and another showed that Znt7-deficient mice, which show dysfunctional incorporation of zinc in the Golgi apparatus, were lean due to a significant reduction in body fat composition [9]. In another study, maternal zinc
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restriction in rats increased body fat percentage and decreased lean and fat-free mass (FFM) in offspring [10]. In several studies conducted in children or adolescents, body zinc status was found to affect body composition. Zinc supplementation in Peruvian children with mild to moderate growth stunting induced an increase in the FFM [11], whereas in a study of children ages <2 y, zinc supplementation increased height but had no effect on weight gain [12]. Recent meta-analyses revealed that zinc supplementation increased linear growth and weight gain in children [13,14]. However, studies assessing the association between zinc status and body composition in adult populations are rare, and the results remain controversial [15,16]. Additionally, few studies have assessed the association between zinc status and body composition in a Korean population [17]. Therefore, using data from the Korean National Health and Nutrition Examination Survey (KNHANES), we evaluated whether serum zinc levels are associated with body composition in Korean adults. Methods Study population The present study used data collected from the KNHANES V-1, which was conducted between January and December 2010 [18]. We originally examined the data from 1988 adults, assessing serum zinc levels. Participants with missing information or data for major variables (n ¼ 81), decreased kidney function (estimated glomerular filtration rate [eGFR] <30 mL/min/1.73 m2; n ¼ 2), or who were pregnant (n ¼ 9) were excluded. Therefore, the present study population consisted of 1896 participants. This study was approved by the Institutional Review Board of the Catholic University of Korea (IRB approval no: VC14 EIME0157). Measurements of body composition factors After an overnight fast, specially trained examiners measured participants’ height, weight, and waist circumference (WC). WC was measured using a measuring tape in the horizontal plane around the umbilical region after exhaling. Abdominal obesity was defined as WC 90 cm (85 cm for women) [19]. Body mass index (BMI) was calculated as each participant’s weight (kg) divided by height squared (m2) and was classified as underweight, normal weight, overweight, or obese according to BMIs of <18.5 kg/m2, 18.5 to 22.9 kg/ m2, 23 to 24.9 kg/m2 and 25 kg/m2, respectively [20]. Body composition factors, including body lean and fat mass were measured using a whole-body dual-energy x-ray absorptiometry scanner (DXA; QDR 4500 A, Hologic, Inc., Waltham, MA, USA). Participants wore a lightweight gown without metal objects during the measurements. Skeletal muscle mass index (SMI) was calculated using the equation: (SMI [%] ¼ total skeletal muscle mass [kg]/body weight [kg] 100) [3]. Total body fat percentage (TBF) was calculated by the equation: (TBF [%] ¼ total fat mass [kg]/body weight [kg] 100). SMI and TBF were categorized into tertiles, with tertile 1, representing the lowest values, tertile 2, the medium values, and tertile 3, the highest values. Laboratory measurements Blood samples were collected from the antecubital vein of each participant after 12 h of fasting, processed, refrigerated immediately, and transported in cold storage to the Central Testing Institute in Seoul, Korea. All blood samples were analyzed within 24 h after arrival at the testing facility. To measure serum zinc concentrations, trace element tubes were used, and levels were determined by inductively coupled plasma mass spectrometry (ICP-MS; ELAN DRC II, PerkinElmer, Waltham, MA, USA). Serum samples were diluted with 2% nitric acid, and zinc concentrations were determined from the linear relationship (r ¼ 0.999) between the concentrations of a standard solution (1000 mg/mL; CLZN2-2 Y, SPEX CertiPrep, Metuchen, NJ, USA) and the absorbance. The accuracy of the analytical methods was assessed using standard reference materials (ClinChek Serum Controls, lyophilised for trace elements, RECIPE, Munich, Germany). The standard deviation index was 0.50, and the inter- and intra-assay coefficients of variation were 2% and 4%, respectively [21]. Serum zinc levels were categorized into tertiles: tertile 1 represented the lowest zinc levels, tertile 2 medium levels, and tertile 3 highest levels. The eGFR was estimated using the re-expressed “Modification of Diet in Renal Disease” study equation with calibrated serum creatinine values and the formula was: 175 (serum creatinine concentration)1.154 (age)0.203 for men, and the value was multiplied by a factor of 0.742 for women [22].
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Other variables Self-reported information regarding age, sex, smoking, alcohol consumption, and the amount of physical activity were obtained. Cigarette smoking was divided into three categories based on current use estimates: nonsmoker, exsmoker, and current smoker. Alcohol consumption was classified into three categories: abstinence (no alcoholic drinks consumed within the previous year), moderate drinking (<14 standard drinks consumed for men or <7 for women per week), and heavy drinking (>14 standard drinks consumed for men or >7 standard drinks for women per week). Physical activity was assessed as the amount and intensity of physical activity per week, and classified as low, moderate, or high. Low physical activity was defined as 150 min of moderate intensity or 75 min of vigorous intensity exercise per week [23]. Dietary intake was assessed using single 24-h recall and was estimated from the food composition tables of the Rural Development Administration in combination with the nutrient database of the Korea Health and Industry of Development Institute [24,25]. The nutrition survey was conducted at participants’ homes by trained dietitians, and additional tools such as food models, two-dimensional food volumes, and containers were used to help participants recall their nutrient intake. The estimated daily energy and fat intake data of the participants were used in this study. Statistical analysis We used the SAS PROC SURVEY module considering strata, clusters, and weights to analyze the data using a complex sampling design [26]. All analyses were performed using the sample weights from KNHANES. The characteristics of the study population were analyzed using analysis of variance for continuous variables and c2 tests for dichotomous variables. The data are expressed as means standard error or as percentages. The proportions of participants in zinc level tertile 3 according to body composition factors were analyzed using c2 tests. The differences in the mean zinc levels according to body composition factors were evaluated using analysis of covariance(ANCOVA). Model 1 was adjusted for age, and model 2 was adjusted for age, smoking, alcohol consumption, physical activity, body weight, total fat and energy intake per day, and eGFR levels as covariates. The associations between serum zinc levels and body composition factors were subjected to a multiple regression analysis. The differences in the mean serum zinc levels according to TBF tertiles and abdominal obesity were analyzed using (ANCOVA) after adjusting for the aforementioned covariates. All statistical analyses were performed using SAS software (ver. 9.2; SAS Institute, Cary, NC, USA). P < 0.05 was considered statistically significant.
Results The present study was conducted using the data from 1896 participants (937 men and 959 women). Table 1 shows the characteristics of the study participants according to serum zinc level tertiles. In men, significant differences in age (45.2, 44.3, and 41.3 y; P ¼ 0.010) and TBF (22.2%, 23.9%, and 23.4%; P ¼ 0.009) were observed according to the tertiles of serum zinc, whereas no differences were seen in women. The proportions of participants with zinc levels in tertile 3 according to body composition factors are shown in Figures 1 and 2. This proportion was lower in men with abdominal obesity than in those without abdominal obesity (27.4% versus 36.1%; P ¼ 0.046; Fig. 1B), and the proportion of men with zinc levels in tertile 3 increased, as the SMI tertiles increased (28.5%, 33.4%, and 39.2%; Ptrend ¼ 0.035; Fig. 1C). The proportion of participants with zinc levels in tertile 3 decreased as the TBF tertiles increased in both men (43.2%, 34%, and 23.4%; Ptrend < 0.001; Fig. 1D) and women (43.6%, 32.5%, and 30.6%; Ptrend ¼ 0.031; Fig. 2D). The mean serum zinc levels according to body composition factors are shown in Table 2. After adjusting for age, smoking, alcohol consumption, physical activity, body weight, total fat and energy intake per day, and eGFR levels, serum zinc levels in men with abdominal obesity were higher than in those without abdominal obesity (152.1 3.7 mg/dL versus 137.8 2.2 mg/dL; P < 0.001). Additionally, serum zinc levels increased as TBF tertiles increased (134.2 2.8 mg/dL, 142 2.9 mg/dL, and 148 2.7 mg/dL; P ¼ 0.001). However, in women, serum zinc levels did not differ according to body composition factors.
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Table 1 Characteristics of study participants according to serum zinc level tertile Men
N Zinc (mg/dL) Age (y) Current smoking (%) Heavy drinking (%) Physical activity (low, %) Energy intake (kcal/d) Fat intake (%) eGFR (mL$min$1.73 m2) Body composition factors Weight (kg) Height (cm) BMI (kg/m2) Waist circumference (cm) SMI (%) TBF (%)
P value
T1*
T2*
T3*
312 112.2 1 45.2 ± 1.2y 42.6 11.5 71.4 2463.1 82.9 18.7 96.6 1.4
313 139.2 0.5 44.3 ± 1.2 46.4 9.7 71 2579.7 85.1 18.1 95.6 1.1
312 173.6 1.8 41.3 ± 0.8 42.4 8.5 68.5 2451.1 66.5 19.9 95.7 0.9
70 0.6 170.7 0.4 24 0.2 83.2 0.6 32.2 22.2
71 0.8 170.6 0.5 24.3 0.2 84.7 0.7 31.6 23.9
70.3 0.8 171.5 0.5 23.9 0.2 83.8 0.6 32 23.4
Women
P value
T1*
T2*
T3*
– – 0.010 0.689 0.586 0.778 0.419 0.107 0.790
319 102.7 0.9 46.8 1.3 4.5 6.7 80.5 1708.4 43.9 17.1 100.9 1.5
320 129 0.5 46.3 1.1 3.8 6.8 81 1743 49.6 17.8 99.4 1.4
320 160.8 1.8 44.6 1.3 6 5.3 78.2 1732.7 49.6 17.5 99.2 1.5
– – 0.480 0.622 0.815 0.803 0.859 0.748 0.678
0.631 0.306 0.249 0.214 0.116 0.009
58.3 0.7 157.7 0.5 23.5 0.4 77.9 0.8 25 33.5
58.6 0.6 157.5 0.4 23.7 0.2 79.2 0.6 24.7 34.7
57 0.7 156.9 0.5 23.2 0.3 76.9 0.7 25 34.6
0.216 0.504 0.401 0.067 0.547 0.120
BMI, body mass index; eGFR, estimated glomerular filtration rate; SMI, skeletal muscle mass index; TBF, total body fat percentage Values are expressed as means standard error or percentages * Tertile (T) 1, the lowest zinc levels; T2, medium zinc levels; and T3, the highest zinc levels. y Results in bold indicate statistical significance at the 0.05 level.
In men, serum zinc levels were positively associated with TBF (b ¼ 0.485; P ¼ 0.010) and, after adjusting for age (model 1), serum zinc levels were positively associated with WC (b ¼ 0.262; P ¼ 0.033) and TBF (b ¼ 0.538; P ¼ 0.004). The positive association between serum zinc levels, WC, and TBF remained significant (b ¼ 1.074; P < 0.001 and b ¼ 0.831; P < 0.001, respectively) after adjusting for age, smoking, alcohol consumption, physical activity, body weight, total fat and energy intake per day, and eGFR levels (model 2; Table 3). Serum zinc levels according to TBF tertiles and abdominal obesity after adjusting for the aforementioned covariates are shown in Figure 3. In men without abdominal obesity, the serum zinc levels of those with TBF tertile 3 were higher than in those with TBF tertile 1 or 2 (145.4 mg/dL versus 135.2 mg/dL; P ¼ 0.029; Fig. 3A). However, in men with abdominal obesity, zinc levels were similar among participants with TBF tertile 1, 2, or 3 (Fig. 3A). There were no differences in women’s serum zinc levels according to TBF tertiles or abdominal obesity (Fig. 3B).
Discussion In the present study, the proportion of men with the highest zinc levels (tertile 3) without abdominal obesity was higher than that of men with abdominal obesity, and the proportion of men with the highest zinc levels decreased as TBF increased (Fig. 1B, 1D). However, associations between abdominal obesity, TBF, and serum zinc levels were altered after adjusting for age and other covariates, such as alcohol consumption [27], smoking [28], physical activity [29], body weight, energy and fat intake per day, and eGFR levels [30], which could affect body zinc status. Therefore, the presence of abdominal obesity and increased body fat were associated positively with serum zinc levels in men (Tables 2 and 3). Inconsistent with this result, a cross-sectional study found that an elevated BMI was associated with low plasma zinc levels [15], and another study reported negative associations of plasma zinc levels with TBF and WC [16]. However, the results from that study were adjusted using only age as
Fig. 1. Percentage of men in the highest zinc level tertile (T3) according to body composition factors. (A) Obesity was defined as a body mass index 25.0 kg/m2. (B) Abdominal obesity was defined as a waist circumference 90 cm. C and D were categorized into tertile 1 (T1) representing the lowest values, T2 the medium values, and T3 the highest values. P values were analyzed using c2 tests. *P < 0.05, yPtrend < 0.05. SMI, skeletal muscle mass index; TBF, total body fat percentage.
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335
Fig. 2. Percentage of women in the highest zinc level tertile (T3) according to body composition factors. (A) Obesity was defined as a body mass index ‡25.0 kg/m2. (B) Abdominal obesity was defined as a waist circumference 85 cm. C and D were categorized into tertile 1 (T1) representing the lowest values, T2 the medium values, and T3 the highest values. P values were analyzed using c2 tests. *P < 0.05, yPtrend < 0.05. SMI, skeletal muscle mass index; TBF, total body fat percentage.
a covariate, and the findings from the cross-sectional study were not adjusted for age or other factors that could affect body zinc status. Additionally, zinc is highly concentrated in animal food sources such as the flesh and organs of mammals, fowl, crustaceans and fish, and a high intake of protein- and fat-rich foods could contribute to the elevation of serum zinc levels [31]. Therefore, we performed this analysis after adjusting for energy and fat intake per day. The mechanism underlying the positive association of serum zinc levels with TBF and abdominal obesity in Korean men is unclear, but it could be explained by certain factors. First, zinc has a stimulatory effect on lipogenesis, similar to the effects of insulin on lipid metabolism, which stimulates fatty acid and triacylglycerol synthesis in adipocytes and increases triglyceride uptake into fat tissues, suggesting that the insulinomimetic effects of zinc on adipose tissue might affect body fat accumulation [6,7,32]. Second, body zinc status is related to appetite [33,34]. It
has been reported that low zinc intake in zinc-deficient rats resulted in reduced carbohydrate consumption and decreased body fat [35]. One study with rats showed that oral zinc intake stimulated food intake through orexigenic peptides coupled to the afferent vagal nerve [36]. The mechanism by which zinc status affects appetite is unclear because the neurobiological regulation of appetite is complex. In an animal study, the release of neuropeptide Y (NPY) from terminals in the paraventricular nucleus of the hypothalamus of zinc-deficient animals was impaired significantly; thus, zinc deficiency might cause anorexia by inhibiting the release of NPY [37]. Third, zinc is an essential cofactor for antioxidant enzymes, such as glutathione peroxidase and superoxide dismutase, decreases the generation of reactive oxygen species, and activates metallothionein, which decreases the hydroxyl radical burden [38]. Visceral adiposity and TBF are related to chronic inflammation [39] and oxidative stress [40]. Therefore, as visceral adiposity and TBF increase, it is
Table 2 Mean serum zinc levels according to body composition factors Men
Women
Unadjusted BMI Underweight Normal weight Overweight Obese P value Waist circumference Abdominal obesity, no Abdominal obesity, yes P value SMIz Tertile 1 Tertile 2 Tertile 3 P value TBFz Tertile 1 Tertile 2 Tertile 3 P value
140.3 140.2 148.2 143 0.381
2.1 3 5.1 2.5
Model 1* 147 139.9 140 142.8 0.452
5.3 2.1 3 2.5
Model 2* 143.5 137.4 140.1 146.1 0.187
6.7 2.7 3.1 3.3
Unadjusted 131.4 129.1 129.8 126.8 0.425
2.3 3 3.5 2.6
Model 1* 127.5 131 129.8 128 0.669
3.6 2.3 3 2.7
Model 2* 129.7 129.5 129.9 127.5 0.933
4.9 2.3 3.2 3
139.8 ± 1.8y 146.5 ± 2.8 0.009
139.2 ± 1.8 146.9 ± 2.8 0.002
137.8 ± 2.2 152.1 ± 3.7 <0.001
130.2 2.1 128.7 2.2 0.536
129.5 2.1 130.1 2.3 0.791
127.4 2.1 132 2.6 0.151
142.9 2.4 141.6 2.7 140 2.4 0.6231
143.2 2.4 141.7 2.7 138.5 2.4 0.249
143 2.6 143.6 3.2 137.8 2.5 0.137
129.1 2.7 129.8 2.1 129.6 2.7 0.977
130.2 2.7 129.8 2.1 128.9 2.7 0.927
129.5 2.5 129.7 2.1 127.9 2.8 0.843
136.6 ± 2.2 142.4 ± 2.6 145.9 ± 2.2 <0.001
135.7 ± 2.2 142.5 ± 2.7 145.7 ± 2.3 <0.001
134.2 ± 2.8 142.0 ± 2.9 148 ± 2.7 0.001
128.4 2.7 129.3 2.3 130.8 2.7 0.751
127.5 2.7 129.8 2.3 131.8 2.6 0.467
127.8 3.1 128.1 2.1 131.3 2.5 0.453
BMI, body mass index; eGFR, estimated glomerular filtration rate; SMI, skeletal muscle mass index; TBF, total body fat percentage Values are expressed as means standard error * Model 1, adjusted for age; model 2, adjusted for age, alcohol consumption, smoking, physical activity, body weight, energy and fat intake per day, and eGFR levels. y Results in bold indicate statistical significance at the 0.05 level. z Tertile 1 represents the lowest values, tertile 2 medium values, and tertile 3 highest values.
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Table 3 Associations between serum zinc levels and body composition factors Men
Unadjusted BMI (kg/m2) WC (cm) SMI (%) TBF (%) Model 1y BMI (kg/m2) WC (cm) SMI (%) TBF (%) Model 2y BMI (kg/m2) WC (cm) SMI (%) TBF (%)
Women
b
SE
b
SE
P value
0.187 0.185 0.076 0.485*
0.337 0.121 0.418 0.188
0.578 0.128 0.854 0.010
0.529 0.178 0.417 0.294
0.333 0.134 0.582 0.261
0.114 0.185 0.470 0.262
0.184 0.262 0.368 0.538
0.331 0.122 0.426 0.184
0.579 0.033 0.388 0.004
0.288 0.061 0.075 0.458
0.331 0.150 0.631 0.272
0.385 0.683 0.905 0.094
1.003 1.074 0.419 0.831
0.963 0.293 0.547 0.296
0.299 <0.001 0.443 <0.001
0.581 0.241 0.190 0.527
0.809 0.305 0.653 0.308
0.473 0.431 0.770 0.089
P value
BMI, body mass index; eGFR, estimated glomerular filtration rate; SE, standard error; SMI, skeletal muscle mass index; TBF, total body fat percentage; WC, waist circumference * Results in bold indicate statistical significance at the 0.05 level. y Model 1, adjusted for age; model 2, adjusted for age, alcohol consumption, smoking, physical activity, body weight, energy and fat intake per day, and eGFR levels.
possible that serum zinc levels increase to cope with chronic inflammation and oxidative stress caused by elevated body fat. Although total body fat plays an important role in the development of metabolic abnormalities [41], it has been reported that abdominal obesity presenting as increased visceral adiposity is another major contributor to metabolic risk and CVD [42]. In the present study, subgroup analysis according to abdominal obesity revealed that men without abdominal adiposity but with high body fat had higher serum zinc levels than those with low to moderate body fat. However, in men with abdominal obesity, the serum zinc level in those with high body fat was similar to those who have low to moderate body fat. Thus, the positive relationship between TBF and serum zinc levels seen in men overall might be attenuated in men with abdominal obesity, suggesting that the men with high body fat and abdominal obesity may be relatively zinc deficient. Indeed, zinc supplementation prevents additional redox stress-associated damage and enhances cardiac function [43] and, hence, could have favorable effects in obesity, diabetes, and CVD. However, in a meta-analysis of 20 randomized controlled trials, zinc had a divergent effect on cholesterol metabolism related to insulin resistance, which is closely associated with abdominal obesity; in
healthy individuals, zinc supplementation was associated with a decrease in plasma high-density lipoprotein cholesterol (HDL-C) levels, but in those with type 2 diabetes mellitus, zinc supplementation showed an increased HDL-C, which contributed to a reduction in CVD risk [44]. Further studies are needed to determine whether additional dietary or supplemental zinc intake should be recommended in men with abdominal obesity and high body fat, and whether high zinc levels in men without abdominal obesity but with high body fat affect the risk for CVD. There were no significant associations in women between serum zinc levels and body composition factors. Consistent with these results, a cross-sectional study involving 580 Mexican women identified no associations between plasma zinc levels and TBF, BMI, and abdominal obesity after adjusting for age, crowding, and years of mother’s education [45]. However, in a study conducted without adjustment for covariates in 105 women, plasma zinc levels decreased as BMI increased [46]. There are several factors that could affect body composition in women in particular such as pregnancy, use of oral contraceptives, or altered sex hormone levels. Although we excluded pregnant women (n ¼ 9) from the analysis, we did not adjust for other covariates that might affect body composition in women because they were not measured or surveyed in the KNHANES. Therefore, additional studies are needed to clarify the association between body zinc status and body composition in women. A strength of this study was that the data were collected through a representative nationwide survey of the South Korean population. Additionally, this is the first study with Korean adults to investigate the associations between serum zinc levels and various body composition parameters. However, this study also had certain limitations. First, it was conducted using a crosssectional design. Second, the dietary patterns and the types of food as sources of zinc intake were not included as covariates because dietary zinc intake was not estimated in the KNHANES. The bioavailability of zinc is determined mostly by the amount of zinc as well as by phytate in the diet, which is a major inhibitor of zinc absorption. Therefore, not only total zinc intake but also the types of foods or dietary patterns should be considered when assessing dietary zinc intake [47], and further studies are warranted to clarify the associations between dietary zinc intake, serum zinc levels, and body composition factors. Third, other confounding conditionsdsuch as acute stress, infection, altered steroid hormone levels, weight loss, or muscle catabolism during illnessesdcan affect serum zinc levels but are not associated with the actual status of body zinc. However, these factors were not considered in this study. Finally, we did not consider other
Fig. 3. Serum zinc levels according to TBF tertiles and the presence of abdominal obesity. TBF was categorized into tertile 1 (T1) representing the lowest values, T2 the medium values, and T3 the highest values. Data are expressed as means standard error, and analyzed using analysis of covariance. (A and B) Abdominal obesity was defined as a waist circumference 90 cm (85 cm for women). *P < 0.05, yPtrend < 0.05. TBF, total body fat percentage.
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trace elements, such as copper, that could affect body zinc status, because the elemental minerals were not measured in the KNHANES. Conclusion Serum zinc concentrations were positively associated with both abdominal obesity and total body fat in men overall. In men without abdominal obesity, serum zinc levels of those with the highest total body fat were higher than in those with low to medium values of total body fat; however, there was no positive relationship between serum zinc levels and total body fat in men with abdominal obesity. The findings suggest that serum zinc concentrations might be associated with the quantity and distribution of body fat in Korean men. Further sex-specific studies are needed to determine whether the associations between serum zinc concentrations and body fat status affect the development or prevention of CVD. References [1] Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2014;384:766–81. [2] Neeland IJ, Ayers CR, Rohatgi AK, Turer AT, Berry JD, Das SR, et al. Associations of visceral and abdominal subcutaneous adipose tissue with markers of cardiac and metabolic risk in obese adults. Obesity 2013;21:E439–47. [3] Janssen I, Heymsfield SB, Ross R. Low relative skeletal muscle mass in older persons is associated with functional impairment and physical disability. J Am Geriatr Soc 2002;50:889–96. [4] Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: report of the European Working Group on Sarcopenia in Older People. Age Ageing 2010;39:412–23. [5] MacDonald RS. The role of zinc in growth and cell proliferation. J Nutr 2000;130:1500s–8s. [6] Yoshikawa Y, Ueda E, Kojima Y, Sakurai H. The action mechanism of zinc complexes with insulinomimetic activity in rat adipocytes. Life Sci 2004;75:741–51. [7] Ilouz R, Kaidanovich O, Gurwitz D, Eldar-Finkelman H. Inhibition of glycogen synthase kinase-3 beta by bivalent zinc ions: insight into the insulin-mimetic action of zinc. Biochem Biophys Res Commun 2002;295:102–6. [8] Chen MD, Lin PY, Cheng V, Lin WH. Zinc supplementation aggravates body fat accumulation in genetically obese mice and dietary-obese mice. Biol Trace Elem Res 1996;52:125–32. [9] Huang L, Yu YY, Kirschke CP, Gertz ER, Lloyd KK. Znt7 -deficient mice display reduced body zinc status and body fat accumulation. J Biol Chem 2007;282:37053–63. [10] Padmavathi IJ, Kishore YD, Venu L, Ganeshan M, Harishankar N, Giridharan NV, et al. Prenatal and perinatal zinc restriction: effects on body composition, glucose tolerance and insulin response in rat offspring. Exp Physiol 2009;94:761–9. [11] Arsenault JE, Lopez de Romana D, Penny ME, Van Loan MD, Brown KH. Additional zinc delivered in a liquid supplement, but not in a fortified porridge, increased fat-free mass accrual among young Peruvian children with mild-to-moderate stunting. J Nutr 2008;138:108–14. [12] Abdollahi M, Abdollahi Z, Fozouni F, Bondarianzadeh D. Oral zinc supplementation positively affects linear growth, but not weight, in children 6-24 months of age. Int J Prev Med 2014;5:280–6. [13] Imdad A, Bhutta ZA. Effect of preventive zinc supplementation on linear growth in children under 5 years of age in developing countries: a metaanalysis of studies for input to the lives saved tool. BMC Public Health 2011;11:S22. [14] Brown KH, Peerson JM, Baker SK, Hess SY. Preventive zinc supplementation among infants, preschoolers, and older prepubertal children. Food Nutr Bull 2009;30:S12–40. [15] Ozata M, Mergen M, Oktenli C, Aydin A, Sanisoglu SY, Bolu E, et al. Increased oxidative stress and hypozincemia in male obesity. Clin Biochem 2002;35:627–31. [16] Singh RB, Beegom R, Rastogi SS, Gaoli Z, Shoumin Z. Association of low plasma concentrations of antioxidant vitamins, magnesium and zinc with high body fat per cent measured by bioelectrical impedance analysis in Indian men. Magnes Res 1998;11:3–10.
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