Predictors of 25-hydroxyvitamin D status among individuals with metabolic syndrome: a cross-sectional study

Predictors of 25-hydroxyvitamin D status among individuals with metabolic syndrome: a... Background: The risk of metabolic syndrome can be influenced by inadequate vitamin D levels, and exposure to sunlight is the main external source of vitamin D. The present study assessed the influence of environmental, biologi‑ cal, and nutritional factors in relation to seasonal 25‑ hydroxyvitamin D (25OHD) concentration in individuals with metabolic syndrome. Methods: This cross‑ sectional study enrolled 180 individuals with metabolic syndrome aged between 18 and 80 years. The 25OHD concentration was considered the dependent variable; independent variables included age, sex, skin color, use of sunscreen, skin type, sun exposure score, ultraviolet radiation index, geographic location, season, body mass index, waist:hip ratio, waist circumference, parathyroid hormone level, total serum calcium level, and cal‑ cium and vitamin D intake. Results: The average vitamin D in individuals evaluated in summer 32 ± 10 ng/mL was greater than in the winter 26 ± 8 ng/mL (p < 0.017). HDL‑ cholesterol was the only component of the MetS that differed significantly between the seasons (p < 0.001), showing higher concentrations in autumn 45 ± 8 mg/dL than in summer 35 ± 8 mg/dL. In the multiple regression model, gender, WHR, sun exposure score, and winter vs. summer explained 10% of the variation in 25OHD concentration (p = 0.004). Conclusions: Sex, waist:hip ratio, sun exposure, and summer season were predictors of 25OHD status among individuals with metabolic syndrome. HDL‑ cholesterol was the only component of metabolic syndrome that differed significantly between the seasons. Keywords: Metabolic syndrome, Vitamin D, Sun exposure, Seasonal variation Background Brazil, the prevalence rate of MetS has been reported at Metabolic syndrome (MetS) is characterized by the pres- around 29.6% in individuals aged 19–64 years [3]. ence of three or more cardiovascular risk factors, and Vitamin D deficiency can play a role in the physi - is usually related to the central deposition of fat as well opathology of risk factors for MetS and the components as insulin resistance [1]. Worldwide, it is estimated that thereof, including hypertension, atherogenic dyslipi- 30–40% of the population 65  years of age and older has demia, diabetes mellitus type 2, and central obesity [4, MetS, due to excessive weight during adulthood [2]. In 5]. A systematic review and meta-analysis of 99,745 par- ticipants reported statistically significant associations between decrease 25-hydroxyvitamin D (25OHD) levels *Correspondence: josivanlima@gmail.com in adult and elderly individuals, and an increase in cardi- Department of Clinical Medicine, Endocrine Unit, Federal University ovascular diseases, diabetes mellitus type 2 and MetS [6]. of Rio Grande do Norte, Natal, RN 59010‑180, Brazil Full list of author information is available at the end of the article © The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creat iveco mmons .org/licen ses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creat iveco mmons .org/ publi cdoma in/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Aquino et al. Diabetol Metab Syndr (2018) 10:45 Page 2 of 9 Several predictors are involved in changes in vitamin who were pregnant or lactating, those who had used glu- D status in chronic diseases, with seasonality being cur- cocorticoids in the past 3 months, those who were taking rently discussed as an important factor, because it has anti-epileptics or rifampin, and those had taken calcium an impact on the behavior and lifestyle of individuals [7]. or vitamin D supplementation in the past 30 days. For example, the winter season has a higher prevalence of MetS was diagnosed according to criteria from the MetS, and changes in the components thereof [7, 8]. Sea- National Cholesterol Education Program-Adult Treat- sonal variation in fasting blood glucose and blood pres- ment Panel III (NCEP-ATP III), which includes the sure was observed in Japanese individuals [9]. The effects presence of at least three of the following: waist circum- of climatic factors on plasma lipid levels have also been ference > 102 cm in men and > 88 cm in women; triglyc- reported in the literature [10]. eride levels ≥ 150 mg/dL; high-density lipoprotein (HDL) In addition to sun exposure, the serum concentration cholesterol level < 40  mg/dL in men and < 50  mg/dL in of 25OHD is also influenced by nutritional status, physi - women; blood pressure ≥ 130  mmHg or ≥ 85  mmHg, cal activity, diet, and skin pigmentation [11, 12]. Inad- and fasting blood glucose ≥ 100 mg/dL [19]. equate 25OHD was observed in overweight individuals, From August 2013 to December 2015, 3068 patient regardless of the degree of obesity [13]. Diet, especially medical records were screened; of these, 1199 were one that is lacking in vitamins and minerals, is consid- excluded for not meeting the inclusion criteria, and 1586 ered another risk factor for MetS [14]. patients were not included because they were not diag- Besides natural sources of vitamin D, fortified foods, nosed with MetS. Of the 283 individuals who met the nutritional supplements and medications, and sun expo- study inclusion criteria, 77 refused to participate in the sure are the main external sources of vitamin D [15]. study or were absent from the endocrinologist appoint- Ultraviolet-B (UVB) rays (wavelength 290–315 nm) from ment; and 26 individuals were lost due to absence of the sun are absorbed by 7-dehydrocholesterol (7-DHC) blood collection. Therefore, data collection was complete present inside epidermal cell plasma membranes, result- for 180 participants. ing in the production of the intracellular cis, cis pre-vita- min D , which is non-enzymatically isomerized, resulting Anthropometric assessment in vitamin D [16]. In this sense, compared to lighter skin, The anthropometric evaluation was performed using darker skin appears to be less efficient in the production body mass index (BMI), waist circumference (WC), and of pre-vitamin D , and subsequently, vitamin D , due to waist:hip ratio (WHR). The WC was measured as half the 3 3 the competition between melanin and the 7-DHC for distance between the iliac crest and the lower costal mar- photons of ultraviolet radiation [17, 18]. gin and classified according to the NCEP-ATP III criteria Therefore, taking into account the known predictors of [19]. The WHR was calculated using > 0.90 and > 0.85 as MetS, and the impact of seasonality thereof, this study the cut-off values for men and women, respectively [20]. aimed to assess the influence of the environmental, bio - logical, and nutritional factors in the seasonal changes of Blood pressure 25OHD among individuals with MetS. Systolic and diastolic blood pressure values were meas- ured during the clinical consultation, according to the Methods Brazilian Guidelines of Blood Pressure VI [21]. Study design A cross-sectional study was developed with adult and Food intake assessment elderly individuals of both sexes, 18–80 years of age, diag- Data regarding food intake were obtained using the 24 h nosed with MetS, and treated at the Endocrinology Clinic dietary recall method (R24h), applied twice, between of Onofre Lopes University Hospital (HUOL) of the Fed- 30 and 45  days. Diet analysis was performed using Vir- eral University of Rio Grande do Norte (UFRN), Natal, tual Nutri Plus 2.0 (Keeple Company São Paulo, Brazil) Brazil. The study was approved by the Research Ethics The composition of the culinary preparations was noted Committee of HUOL (CAAE n. 13699913.7.0000.5292) in the dietary records for later data capture. The average and the participants signed informed consent forms nutrient intakes were calculated as the mean of the intake indicating their agreement to participate in the research. values obtained from both R24h. The results of the die - Individuals with diabetes mellitus type 1 or type 2 who tary intake of vitamin D and calcium were expressed as used insulin were excluded, as well as those with altered IU/day and mg/day, respectively. renal or hepatic function (glomerular filtration rate esti - mated by modification of diet in renal disease < 60  mL/ Sun exposure min; hepatic transaminase levels higher than three times Sun exposure was evaluated based on a weekly score the reference values), decompensated heart failure, those equivalent to the individual sun exposure for the previous Aquino et al. Diabetol Metab Syndr (2018) 10:45 Page 3 of 9 7  days. First, the daily score was obtained by measuring Lipid profiles were classified according to the NCEP- the amount of time that each individual spent outdoors ATPIII criteria [19]. The established criterion for fasting versus the amount of exposed skin. The weekly scores blood glucose levels was ≥ 100  mg/dL [1]. The reference were measured, and the resulting sum of these daily range for total serum calcium was 8.8–11  mg/dL, and scores was defined as the sun exposure. The use of sun - the reference interval for PTH levels was 11–67  pg/mL. screen in the last 7  days was also assessed. The scores The 25OHD levels were considered deficient, insufficient, ranged from zero (no exposure) to 56 (maximum expo- and sufficient for concentrations ≤ 20, ≥ 21 and ≤ 29, sure) [22]. and ≥ 30 ng/mL, respectively [28]. Skin pigmentation Statistical analysis Skin color was obtained by self-classification among the For the descriptive analysis of continuous variables, five categories adopted by the Brazilian Institute of Geog - mean ± standard deviation (SD), means (confidence raphy and Statistics (IBGE): black, mixed (“pardo” in offi - interval [CI]), or medians (interquartile interval) were cial Portuguese), white, yellow (Asian), and indigenous calculated as appropriate. The absolute and relative fre - (Native American) [23]. The skin types were classified quencies were calculated for binary and categorical according to Fitzpatrick (1988), who classified human variables. skin color into six categories, ranging from type I (fair) to There were missing data for PTH levels, total serum type VI (black) [24]. calcium, use of sunscreen, and skin color. Therefore, methods of multiple imputation data were applied, which Ultraviolet index and seasons follow three main steps: (a) imputation of missing data Data from the monitoring and recording of ultraviolet to obtain complete databases; (b) estimation based on index (UVI) in the city of Natal, RN, Brazil was obtained incomplete databases, and (c) a combination of methods. from the daily publications from the Laboratory of Tropi- Data were assumed to be missing at random [29]. cal Environmental Variables (LAVAT), of the National The 25OHD concentration variation throughout the Institute of Spatial Researches, Regional Center of the seasons was examined by one-way analysis of variance Northeast (INPE/CRN). The UVI was classified according (ANOVA). When the results were statistically signifi - to World Health Organization (WHO) guidelines [25] into cant, posthoc tests were performed to assess the differ - five categories according to UVI intensity: low, < 2; moder- ences among seasons. T-tests were used for independent ate, 3–5; high, 6–7; very high, 8–10, and extreme, ≥ 11. samples, followed by the correction of Bonferroni. For The participants were distributed in the spring, sum - the variables with imputed observations, the analysis mer, autumn, and winter seasons based on the half-life of between the seasons was performed using F tests (analog 25OHD corresponding to the 30 days preceding the date of ANOVA) of the univariate linear regression model. of the biochemical examination [26]. Thus, individual When the F test was significant, the P values of the participants were categorized into the respective seasons regression coefficients were also corrected by the Bonfer - based on the month into which this time interval fell. roni method. The potential predictors for the magnitude of the Biochemical tests 25OHD concentration were investigated using univariate Blood samples were collected from the participants after linear regression models and as well as multiple regres- an overnight fast (10–12  h) by standard venipuncture. sion (two or more predictor variables included in the Fasting blood glucose, HDL-cholesterol, triglyceride, model). and total calcium levels were measured by colorimetric In the univariate linear regression, 15 models were cre- tests using the test kit from the Wiener lab (Wiener lab ated using 25OHD concentration as a dependent vari- group, Argentina) and via the automated CMD800iX1 able and the other variables as predictors. In the multiple (Diamond Diagnostics, Holliston, MA, USA). Low-den- regression analysis, seven models were created using sity lipoprotein (LDL)-cholesterol levels were measured 25OHD levels as the dependent variable and the other as previously described [27]. variables as predictors, as follows: (1) gender, age, use The serum concentrations of the parathyroid (PTH) of sunscreen, sun exposure score, season, and WHR; (2) and insulin hormones were determined by chemilumi- gender, age, use of sunscreen, sun exposure score, season, nescent tests using a commercial analysis from Beck- and BMI; (3) gender, age, use of sunscreen, sun exposure ® ® man Coulter (Unicel DxI800 immunoassay system, score, season, and WC; (4) age, gender and region; (5) CA, USA). Serum concentrations of 25OHD were meas- season, UVI, sun exposure score, skin type, skin color, ured using the chemiluminescent Liaison test from kit and use of sunscreen; (6) total serum calcium and PTH DiaSorin (Saluggia, Italy). and (7) vitamin D and calcium intakes (Additional file 1). Aquino et al. Diabetol Metab Syndr (2018) 10:45 Page 4 of 9 The correlation between two variables was assessed number of MetS components between the seasons by determining Pearson correlation coefficients (r). For (Table 1). The most frequent components of MetS in the variables with imputed observations, the Pearson coef- participants were elevated WC (88%), elevated blood ficient was computed using the coefficient of simple lin - pressure (79%), low HDL-cholesterol (78%), elevated ear regression, considering the variables centered in their fasting blood glucose (75%), and high triglyceride levels averages and standardized by the sample standard devia- (54%). The HDL-cholesterol was the only component tion. Fisher’s exact test and its extensions were used to with significant variation among seasons, showing higher test the differences between proportions. The statistical concentrations in the autumn 45 ± 8 mg/dL and lower in significance assumed for all analysis was 5% (two-tailed, the summer 35 ± 8 mg/dL (Table 2). p < 0.05). All analyses were performed using Stata 14.0 Most of the individuals had mixed skin (67%), group (Stata Corporation, College Station, TX, USA). II skin type (32%), and did not use sunscreen (66%). The annual UVI average of 6.4 ± 1.8 was high. The UVI dif - Results fered significantly among seasons, especially between Characteristics of the participants winter and spring (p < 0.001), winter and summer Of the 180 total participants, 141 (78%) were female and (p = 0.001), spring and summer (p = 0.022), and spring 39 (22%) were male, with an average age of 50 ± 12 years. and autumn (p < 0.001), with index variations ranging There was no statistically significant variation in the from moderate to very high (Table 1). Table 1 Demographic, biological, and environmental characteristics of the individuals according to season Variables Seasons Total (n = 180) p Winter (n = 84) Spring (n = 50) Summer (n = 28) Autumn (n = 18) Gender 0.87 Female 66 (79) 39 (78) 23 (82) 13 (72) 141 (78) Male 18 (22) 11 (22) 5 (18) 5 (28) 39 (22) Age (years) 51 ± 13 49 ± 10 47 ± 13 54 ± 14 50 ± 12 0.22 a d Number of MetS components 0.33 3 components 43 (51) 21 (42) 10 (36) 6 (33) 80 (44) 4 components 29 (35) 16 (32) 13 (46) 6 (33) 64 (36) 5 components 12 (14) 13 (26) 5 (18) 6 (33) 36 (20) Self‑referred skin color 0.59 Black 6 (7) 4 (8) – – 10 (6) Mixed 51 (61) 26 (52) 17 (61) 15 (83) 109 (61) White 22 (26) 18 (36) 10 (36) 2 (11) 52 (29) Yellow 3 (5) 2 (4) 1 (4) 1 (6) 7 (3) Indigenous 1 (1) – – – 1 (1) Sunscreen 0.25 Do not use 51 (61) 37 (74) 17 (61) 14 (78) 120 (67) Always use 33 (39) 12 (24) 11 (39) 4 (22) 60 (33) a,e Skin type 0.29 I 7 (8) 5 (10) 2 (7) – 14 (8) II 30 (36) 13 (26) 10 (36) 4 (22) 57 (32) III 20 (24) 12 (24) 6 (21) 4 (22) 42 (23) IV 17 (20) 15 (30) 5 (18) 3 (17) 40 (22) V 10 (12) 5 (10) 5 (18) 7 (39) 27 (15) b,f UVI 5.5 ± 1.4 7.9 ± 2.2 6.8 ± 0.4 5.8 ± 0.4 6.4 ± 1.8 < 0.001 Data presented as n(%) Data presented as average ± standard deviation p, differences between seasons. T-tests were used for independent samples, followed by the correction of Bonferroni and Fisher’s exact test and its extensions were used to test the differences between proportions Chi square test was used to compare the proportions of the number of components between stations e 21 Skin type according to Fitzpratrick UVI, Ultraviolet radiation index of the 30 days previous to the biochemical exam Aquino et al. Diabetol Metab Syndr (2018) 10:45 Page 5 of 9 The average BMI was 33 ± 7  kg/m ; 77 and 23% had In the multiple regression model, sex, WHR, sun expo- obesity and overweight, respectively. The average overall sure score, and season significantly influenced 25OHD WC was 106 ± 13 cm, indicating an increased risk for the status explaining 10% of the variation in 25OHD status development of diseases associated with obesity. BMI, (p = 0.001; Table 3). WHR, and WC did not show significant statistical differ - Men with MetS had 25OHD concentration 3.71  ng/ ences among the seasons (Table 2). mL higher than those of women in this study. A 1.0 increment in sun exposure score was associated with a Seasonal variations of the 25OHD 0.16  ng/mL increase in 25OHD concentration, and the The percentage of individuals with 25OHD deficiency season was an independent predictor of 25OHD status. and insufficiency was higher in the winter (72%) and lower in the summer (50%). The average 25OHD concen - Discussion tration was 5.59 ng/mL higher in the summer than in the In the present study, sex, WHR, sun exposure score, and winter (95% CI 1.81–9.38 ng/mL; p = 0.024). season were predictors of 25OHD status among indi- viduals with MetS. We found significantly higher serum Predictors of 25OHD concentration 25OHD concentrations in the summer compared to the In the simple linear regression model, a statistically winter. Summertime improvement of vitamin D status significant association with summer (p = 0.003) was was accompanied by certain improved cardiometabolic observed, explaining 4% of the variability in 25OHD sta- risk factors, notably serum triglycerides, total cholesterol tus. Sun exposure score was significantly associated with and BMI, in Iranian children [30]. We speculated that 25OHD status (p = 0.008). There was no statistically sig - the higher prevalence of inadequate 25OHD levels in the nificant association between 25OHD concentration and study population might be associated with MetS clinical the co-variables of age, sex, geographic location, skin conditions. color, skin type and use of sunscreen, UVI, BMI, WHR, The discovery of the inverse relationship between WC, total serum calcium, PTH, and dietary calcium, and WHR and 25OHD status suggested that a high fat con- vitamin D. centration in the abdominal region may interfere with Table 2 Anthropometric nutritional status, clinics, and dietary characteristics of the individuals according to the season Variables Seasons Total (n = 180) p Winter (n = 84) Spring (n = 50) Summer (n = 28) Autumn (n = 18) 2 a BMI (kg/m ) 32 ± 7 34 ± 6 35 ± 7 34 ± 8 33 ± 7 0.36 WHR 0.97 ± 0.1 0.97 ± 0.1 0.97 ± 0.1 0.97 ± 0.1 0.97 ± 0.1 0.91 WC (cm) 104 ± 14 107 ± 11 108 ± 14 106 ± 14 106 ± 13 0.39 Triglycerides (mg/dL) 164 (126–217) 172 (116–235) 148 (120–188) 163 (135–218) 162 (120–221) 0.81 a d HDL‑ cholesterol (mg/dL) 42 ± 9 37 ± 9 35 ± 8 45 ± 8 40 ± 9 < 0.001 Fasting blood glucose (mg/dL) 108 (94–130) 110 (96–125) 106 (95–119) 117 (105–140) 108 (96–129) 0.35 Systolic blood pressure (mm/Hg) 130 (120–140) 132 (122–140) 128 (120–140) 130 (122–140) 130 (120–140) 0.80 Diastolic blood pressure (mm/Hg) 84 (80–90) 89 (83–95) 87 (80–90) 90 (83–93) 87 (80–90) 0.15 a e 25OHD (ng/mL) 26 ± 8 29 ± 10 32 ± 10 30 ± 9 28 ± 9 0.014 a f Total serum calcium (mg/dL) 10.1 ± 0.7 9.9 ± 0.7 9.4 ± 0.5 9.8 ± 0.4 9.9 ± 0.7 < 0.001 PTH (pg/mL) 35 (25–51) 35 (22–48) 25 (17–34) 36 (20–41) 34 (22–47) 0.06 Vitamin D intake (IU/day) 109 (63–150) 82 (45–141) 80 (60–124) 91 (67–158) 90 (59–146) 0.28 Calcium intake (mg/day) 473 (315–632) 426 (254–560) 409 (245–639) 404 (297–524) 441 (294–593) 0.30 BMI body mass index, WHR waist:hip ratio, WC waist circumference; PTH parathyroid hormone Data presented as average ± standard deviation) Data presented as median (interquartile interval) p, difference among seasons. ANOVA was used to compare the variables throughout the seasons. For the variables with imputed observations, the analysis between seasons was performed using F tests (analog of ANOVA) p, for multiple comparisons: winter vs. spring (p = 0.007), winter vs. summer (p = 0.003), spring vs. autumn (p = 0.012), and summer vs. autumn (p = 0.004) p, for multiple comparisons: winter vs. spring (p = 0.378), winter vs. summer (p = 0.017), winter vs. autumn (p = 0.581), spring vs. summer (p > 0.99), spring vs autumn (p > 0.99), and summer vs. autumn (p > 0.99) p, for multiple comparisons: winter vs. spring (p = 0.67), winter vs. summer (p = 0.001), winter vs. autumn (p = 0.16), spring vs. summer (p = 0.012), spring vs. autumn (p > 0.99), and summer vs. autumn (p = 0.73) Aquino et al. Diabetol Metab Syndr (2018) 10:45 Page 6 of 9 Table 3 Multiple regression model for  the  prediction Because the Rio Grande do Norte state is a Brazilian of 25OHD concentrations (ng/mL) in individuals with MetS territory with high year-round solar radiation, 25OHD (n = 180) levels were expected to be sufficient in this population, regardless of the season [16]. In the period assessed in 25OHD (ng/mL) the current study, the average environmental UVI ranged a 2 Predictors Β SE 95% CI p R from moderate to high in every season, with significant Sun exposure score 0.164 0.06 0.05–0.28 0.006 0.104 differences between the moderate and high UVI in the Seasons winter and summer, respectively. However, 63% of the Winter (Ref.) individuals assessed in this study had inadequate 25OHD Spring 3.178 1.57 0.08–6.27 0.045 levels, the proportion of which increased in the winter. Summer 5.593 1.92 1.81–9.38 0.004 This finding emphasizes the essential roles of the seasons, Autumn 3.108 2.29 − 1.42–7.64 0.18 and sun exposure on the variability in 25OHD status. More recently, there has been a growing appreciation Sex 3.716 1.67 0.43–7.00 0.027 for the beneficial impact that sunlight has on the cardio - WHR − 25.080 11.23 − 47.26–2.89 0.027 vascular system, independent of vitamin D production. Age (years) 0.0001 0.56 − 0.11–0.11 0.10 Vitamin D could in these circumstances act as a marker Use of sunscreen for sunlight exposure and its postulated beneficial effects Do not use (Ref.) [34]. Always use 2.671 1.41 − 0.11–5.45 0.06 The seasonality of vitamin D status has been noted in Sometimes use − 3.91 8.91 − 21.52–13.69 0.66 other studies, in addition to reports on the incidence of β regression coefficient, SE standard error, CI confidence interval, Ref. reference group MetS and its related components [35]. In the present p, for multiple comparisons: winter vs. spring, winter vs. summer, winter vs. study, seasonal variation was observed in the concentra- autumn, spring vs. summer, spring vs. autumn, and summer vs. autumn tion of HDL-cholesterol, especially in the summer, where the lowest concentrations of this component were noted. vitamin D metabolism. This is explained by the liposol - A study of 1202 male Japanese subjects reported a higher uble nature of vitamin D, thus higher fat concentrations prevalence of MetS in the winter compared to that of the in the abdominal region favor the uptake of vitamin D to summer, with similar results for the MetS components the adipose tissue, resulting in inadequate 25OHD con- such as HDL-cholesterol, systolic and diastolic blood centrations. Miñambres et  al. found inadequate 25OHD pressure, and fasting blood glucose levels [7]. Summer status regardless of the level of obesity, a finding that sup - season was also positively associated with low HDL-C, ports the existence of this inverse correlation between and MetS in Chinese adults when summer–winter differ - higher abdominal adipose tissue concentration and inad- ences in components of MetS were investigated [36]. equate 25OHD [13]. We can attribute higher concentrations of 25OHD Few studies have assessed the influence of the seasons in the summer, along with lower concentrations of on 25OHD status among individuals living in cities in HDL-cholesterol, to the fact that 64% of individuals the northeastern regions of Brazil. Studies conducted on were diagnosed as having more than three of the com- adults and elderly in the city of São Paulo, in the south- ponents of MetS, which represents greater metabolic eastern region of Brazil, reported results similar to those impairment. Changes in the lipid profile between the of our study [31, 32]. The positive association between seasons can be explained by a set of seasonal changes, the sun exposure score and 25OHD status can be such as blood hemodilution during the summer, and explained by the presence of 7-DHC in the plasma mem- blood hemoconcentration in winter, as well as changes brane of epidermal cells; it is a photosensitive molecule in eating habits, and physical activity [37]. The associa - that absorbs ultraviolet radiation with a wavelength from tion between low 25OHD status, and low HDL-choles- 290–315 nm. Following this absorption, the entire meta- terol concentrations has been discussed in some studies bolic pathway is initiated to activate vitamin D synthesis but are still controversial. Data from the Tromsø Study [8]. This discovery reinforces the utility of the assessment showed in adults a strong and positive association tool used in the study, which offered good accuracy to between serum 25(OH)D and HDL. However, the cause assess sun exposure. of this association still remains unknown [38, 39]. Sy et  al. reported that an increase of 25OHD concen- Our study did not focus on evaluating the association tration by approximately 10  ng/mL decreases the risk of among vitamin D and lipid profile or the other compo - developing MetS by 13%. An important point for further nents of the MetS. discussion is therefore the ideal 25OHD concentration The higher 25OHD levels in the male participants may for individuals with MetS [33]. have been due to the higher sun exposure than women Aquino et al. Diabetol Metab Syndr (2018) 10:45 Page 7 of 9 Conclusions (25 ± 13 vs. 21 ± 11). It is important to highlight that 66% In conclusion, sex, WHR, sun exposure and summer of the participants did not use sunscreen, which validates season were predictors of 25OHD status among indi- the results regarding sun exposure and 25OHD concen- viduals with MetS. In addition to this, HDL-cholesterol tration. A study that included 95,137 Korean individuals was the only component of the MetS that differed sig - analyzed 25OHD status according to sex, age, and season nificantly among the seasons. These results demonstrate also reported differences in 25OHD status, with higher the importance of considering these variables in clinical concentrations among the male participants [40]. interventions with vitamin D, and underscore the need The prevalence of inadequate micronutrient and for further development and updated guidelines for the macronutrient intakes was assessed previously in par- treatment of MetS. ticipants of the current study showing that 100, and 99% of the participants had inadequate vitamin D, and cal- Additional file cium intakes, respectively [41]. Therefore, evidently diet was not a significant external source of vitamin D that Additional file 1. Multiple regression model for the prediction of indi‑ contributed to the variation in 25OHD concentration, viduals with metabolic syndrome. according to the seasons. Skin color and skin type did not influence 25OHD con - Abbreviations centration, a finding discordant from those of previous MetS: metabolic syndrome; 25OHD: 25‑Hydroxyvitamin D; UVI: ultraviolet studies [15, 42]. However, in our study, skin color was radiation index; BMI: body mass index; WHR: waist:hip ratio; WC: waist circum‑ self-classified, which means that individuals subjectively ference; PTH: parathyroid hormone; 7‑DHC: 7‑Dehydrocholesterol; NCEP ‑ATP III: National Cholesterol Education Program‑Adult Treatment Panel III; LAVAT: classified themselves, leading to various potential biases; Laboratory of Tropical Environmental Variables; LDL: low‑ density lipoprotein; therefore, the reported skin color may not be the actual HDL: high‑ density lipoprotein. skin color. Authors’ contributions The studied participants were sampled from a location SLSA, LFCP, and JGL conceived and designed the experiments. SLSA, ATOC, with a steady and a high year-round solar radiation. This HTP, and EPSF performed the experiments. SLSA, APTF, SCVCL, and KCMS ana‑ observation might explain, at least in part, the smaller lyzed the data. SLSA, ATOC, HTP, EPSF, APTF, JGL, SCVCL, KCMS, and LFCP wrote the paper. All authors read and approved the final manuscript. magnitude of the coefficient of determination (10%) compared to previous investigations carried out in loca- Author details tions with larger variations in sunlight exposure among Postgraduate Nutrition Program, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal, RN 59078‑970, Brazil. Postgraduate seasons. Program in Health Sciences, Center for Health Sciences, Federal University Our study had some limitations, including its cross- of Rio Grande do Norte, Natal, RN 59012‑570, Brazil. Department of Nutri‑ sectional study design, in which the same individuals tion, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal, RN 59078‑970, Brazil. Department of Clinical Medicine, Endocrine Unit, were not assessed over the four seasons and the number Federal University of Rio Grande do Norte, Natal, RN 59010‑180, Brazil. of the participants in each season. Moreover, the ultravi- olet radiation and UVI measures reflected not only UVB Acknowledgements The authors thank Cínthia Regina Mendes Ferino and Mariana Pontes de radiation, but also UVA radiation. This correction may Sousa Santos for their assistance with data collection; the team of the Endocri‑ be performed in others studies considering assessments nology Clinic of the University Hospital Onofre Lopes for their partnership and for vitamin D3 production in human skin from outdoor attention to the research; the Laboratory of Tropical Environmental Variables (LAVAT ) of the National Institute of Spatial Researcher, Regional Center of the exposures as well as account related to different contribu - Northeast; Tiago Veiga Pereira for assistance with statistical analysis; and the tions of each action spectrum with changing solar zenith Improvement Coordination of Higher Education (CAPES) for the scholarship angle [43]. grant. In addition, given the unmatched design, we cannot Competing interests fully rule out that covariate imbalances might contribute The authors declare that they have no competing interests. to the observed associations. However, for the examined Availability of data and materials covariates, only two were considered statistically sig- The datasets used and/or analyzed during the current study are available from nificant in univariable models, and associations between the corresponding author on reasonable request. 25OHD and sunlight exposure score, seasons and body Consent for publication surface area were robust to adjustments for other covari- Not applicable. ates included in the model. Ethics approval and consent to participate The study was approved by the Research Ethics Committee of HUOL (CAAE n. 13699913.7.0000.5292). Aquino et al. Diabetol Metab Syndr (2018) 10:45 Page 8 of 9 Funding 17. Fajuyigbe D, Young AR. The impact of skin colour on human photobio‑ This work was supported by the National Council for Scientific and Techno ‑ logical responses. Pigment Cell Melanoma Res. 2016;29:607–18. https :// logical Development (Conselho Nacional de Desenvolvimento Científico e doi.org/10.1111/pcmr.12511 . Tecnológico, CNPq, Brazil; Grant No. 471761/2013‑3). 18. Libon F, Cavalier E, Nikkels AF. Skin color is relevant to vitamin D synthesis. Dermatology. 2013;227:250–4. https ://doi.org/10.1159/00035 4750. 19. National Cholesterol Education Program Adult Treatment Panel III. NCEP‑ Publisher’s Note ATP III). Expert panel on detection, evaluation, and treatment of high Springer Nature remains neutral with regard to jurisdictional claims in pub‑ blood cholesterol in adults. Executive summary of the third report of the lished maps and institutional affiliations. National Cholesterol Education Program (NCEP) expert panel on detec‑ tion, evaluation, and treatment of high blood cholesterol in adults (Adult Received: 2 April 2018 Accepted: 25 May 2018 Treatment Panel III. JAMA. 2001;285:2486–97. 20. World Health Organization ( WHO). 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Photochem Photobiol. 2008;84(5):1277–83. https ://doi.org/10.111 yvitamin D and serum lipids‑more than confounding? Eur J Clin Nutr. 1/j.1751‑1097.2008.00373 . 2018;72(4):526–33. Ready to submit your research ? Choose BMC and benefit from: fast, convenient online submission thorough peer review by experienced researchers in your field rapid publication on acceptance support for research data, including large and complex data types • gold Open Access which fosters wider collaboration and increased citations maximum visibility for your research: over 100M website views per year At BMC, research is always in progress. Learn more biomedcentral.com/submissions http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Diabetology & Metabolic Syndrome Springer Journals

Predictors of 25-hydroxyvitamin D status among individuals with metabolic syndrome: a cross-sectional study

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Medicine & Public Health; Diabetes; Metabolic Diseases; Endocrinology
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Abstract

Background: The risk of metabolic syndrome can be influenced by inadequate vitamin D levels, and exposure to sunlight is the main external source of vitamin D. The present study assessed the influence of environmental, biologi‑ cal, and nutritional factors in relation to seasonal 25‑ hydroxyvitamin D (25OHD) concentration in individuals with metabolic syndrome. Methods: This cross‑ sectional study enrolled 180 individuals with metabolic syndrome aged between 18 and 80 years. The 25OHD concentration was considered the dependent variable; independent variables included age, sex, skin color, use of sunscreen, skin type, sun exposure score, ultraviolet radiation index, geographic location, season, body mass index, waist:hip ratio, waist circumference, parathyroid hormone level, total serum calcium level, and cal‑ cium and vitamin D intake. Results: The average vitamin D in individuals evaluated in summer 32 ± 10 ng/mL was greater than in the winter 26 ± 8 ng/mL (p < 0.017). HDL‑ cholesterol was the only component of the MetS that differed significantly between the seasons (p < 0.001), showing higher concentrations in autumn 45 ± 8 mg/dL than in summer 35 ± 8 mg/dL. In the multiple regression model, gender, WHR, sun exposure score, and winter vs. summer explained 10% of the variation in 25OHD concentration (p = 0.004). Conclusions: Sex, waist:hip ratio, sun exposure, and summer season were predictors of 25OHD status among individuals with metabolic syndrome. HDL‑ cholesterol was the only component of metabolic syndrome that differed significantly between the seasons. Keywords: Metabolic syndrome, Vitamin D, Sun exposure, Seasonal variation Background Brazil, the prevalence rate of MetS has been reported at Metabolic syndrome (MetS) is characterized by the pres- around 29.6% in individuals aged 19–64 years [3]. ence of three or more cardiovascular risk factors, and Vitamin D deficiency can play a role in the physi - is usually related to the central deposition of fat as well opathology of risk factors for MetS and the components as insulin resistance [1]. Worldwide, it is estimated that thereof, including hypertension, atherogenic dyslipi- 30–40% of the population 65  years of age and older has demia, diabetes mellitus type 2, and central obesity [4, MetS, due to excessive weight during adulthood [2]. In 5]. A systematic review and meta-analysis of 99,745 par- ticipants reported statistically significant associations between decrease 25-hydroxyvitamin D (25OHD) levels *Correspondence: josivanlima@gmail.com in adult and elderly individuals, and an increase in cardi- Department of Clinical Medicine, Endocrine Unit, Federal University ovascular diseases, diabetes mellitus type 2 and MetS [6]. of Rio Grande do Norte, Natal, RN 59010‑180, Brazil Full list of author information is available at the end of the article © The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creat iveco mmons .org/licen ses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creat iveco mmons .org/ publi cdoma in/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Aquino et al. Diabetol Metab Syndr (2018) 10:45 Page 2 of 9 Several predictors are involved in changes in vitamin who were pregnant or lactating, those who had used glu- D status in chronic diseases, with seasonality being cur- cocorticoids in the past 3 months, those who were taking rently discussed as an important factor, because it has anti-epileptics or rifampin, and those had taken calcium an impact on the behavior and lifestyle of individuals [7]. or vitamin D supplementation in the past 30 days. For example, the winter season has a higher prevalence of MetS was diagnosed according to criteria from the MetS, and changes in the components thereof [7, 8]. Sea- National Cholesterol Education Program-Adult Treat- sonal variation in fasting blood glucose and blood pres- ment Panel III (NCEP-ATP III), which includes the sure was observed in Japanese individuals [9]. The effects presence of at least three of the following: waist circum- of climatic factors on plasma lipid levels have also been ference > 102 cm in men and > 88 cm in women; triglyc- reported in the literature [10]. eride levels ≥ 150 mg/dL; high-density lipoprotein (HDL) In addition to sun exposure, the serum concentration cholesterol level < 40  mg/dL in men and < 50  mg/dL in of 25OHD is also influenced by nutritional status, physi - women; blood pressure ≥ 130  mmHg or ≥ 85  mmHg, cal activity, diet, and skin pigmentation [11, 12]. Inad- and fasting blood glucose ≥ 100 mg/dL [19]. equate 25OHD was observed in overweight individuals, From August 2013 to December 2015, 3068 patient regardless of the degree of obesity [13]. Diet, especially medical records were screened; of these, 1199 were one that is lacking in vitamins and minerals, is consid- excluded for not meeting the inclusion criteria, and 1586 ered another risk factor for MetS [14]. patients were not included because they were not diag- Besides natural sources of vitamin D, fortified foods, nosed with MetS. Of the 283 individuals who met the nutritional supplements and medications, and sun expo- study inclusion criteria, 77 refused to participate in the sure are the main external sources of vitamin D [15]. study or were absent from the endocrinologist appoint- Ultraviolet-B (UVB) rays (wavelength 290–315 nm) from ment; and 26 individuals were lost due to absence of the sun are absorbed by 7-dehydrocholesterol (7-DHC) blood collection. Therefore, data collection was complete present inside epidermal cell plasma membranes, result- for 180 participants. ing in the production of the intracellular cis, cis pre-vita- min D , which is non-enzymatically isomerized, resulting Anthropometric assessment in vitamin D [16]. In this sense, compared to lighter skin, The anthropometric evaluation was performed using darker skin appears to be less efficient in the production body mass index (BMI), waist circumference (WC), and of pre-vitamin D , and subsequently, vitamin D , due to waist:hip ratio (WHR). The WC was measured as half the 3 3 the competition between melanin and the 7-DHC for distance between the iliac crest and the lower costal mar- photons of ultraviolet radiation [17, 18]. gin and classified according to the NCEP-ATP III criteria Therefore, taking into account the known predictors of [19]. The WHR was calculated using > 0.90 and > 0.85 as MetS, and the impact of seasonality thereof, this study the cut-off values for men and women, respectively [20]. aimed to assess the influence of the environmental, bio - logical, and nutritional factors in the seasonal changes of Blood pressure 25OHD among individuals with MetS. Systolic and diastolic blood pressure values were meas- ured during the clinical consultation, according to the Methods Brazilian Guidelines of Blood Pressure VI [21]. Study design A cross-sectional study was developed with adult and Food intake assessment elderly individuals of both sexes, 18–80 years of age, diag- Data regarding food intake were obtained using the 24 h nosed with MetS, and treated at the Endocrinology Clinic dietary recall method (R24h), applied twice, between of Onofre Lopes University Hospital (HUOL) of the Fed- 30 and 45  days. Diet analysis was performed using Vir- eral University of Rio Grande do Norte (UFRN), Natal, tual Nutri Plus 2.0 (Keeple Company São Paulo, Brazil) Brazil. The study was approved by the Research Ethics The composition of the culinary preparations was noted Committee of HUOL (CAAE n. 13699913.7.0000.5292) in the dietary records for later data capture. The average and the participants signed informed consent forms nutrient intakes were calculated as the mean of the intake indicating their agreement to participate in the research. values obtained from both R24h. The results of the die - Individuals with diabetes mellitus type 1 or type 2 who tary intake of vitamin D and calcium were expressed as used insulin were excluded, as well as those with altered IU/day and mg/day, respectively. renal or hepatic function (glomerular filtration rate esti - mated by modification of diet in renal disease < 60  mL/ Sun exposure min; hepatic transaminase levels higher than three times Sun exposure was evaluated based on a weekly score the reference values), decompensated heart failure, those equivalent to the individual sun exposure for the previous Aquino et al. Diabetol Metab Syndr (2018) 10:45 Page 3 of 9 7  days. First, the daily score was obtained by measuring Lipid profiles were classified according to the NCEP- the amount of time that each individual spent outdoors ATPIII criteria [19]. The established criterion for fasting versus the amount of exposed skin. The weekly scores blood glucose levels was ≥ 100  mg/dL [1]. The reference were measured, and the resulting sum of these daily range for total serum calcium was 8.8–11  mg/dL, and scores was defined as the sun exposure. The use of sun - the reference interval for PTH levels was 11–67  pg/mL. screen in the last 7  days was also assessed. The scores The 25OHD levels were considered deficient, insufficient, ranged from zero (no exposure) to 56 (maximum expo- and sufficient for concentrations ≤ 20, ≥ 21 and ≤ 29, sure) [22]. and ≥ 30 ng/mL, respectively [28]. Skin pigmentation Statistical analysis Skin color was obtained by self-classification among the For the descriptive analysis of continuous variables, five categories adopted by the Brazilian Institute of Geog - mean ± standard deviation (SD), means (confidence raphy and Statistics (IBGE): black, mixed (“pardo” in offi - interval [CI]), or medians (interquartile interval) were cial Portuguese), white, yellow (Asian), and indigenous calculated as appropriate. The absolute and relative fre - (Native American) [23]. The skin types were classified quencies were calculated for binary and categorical according to Fitzpatrick (1988), who classified human variables. skin color into six categories, ranging from type I (fair) to There were missing data for PTH levels, total serum type VI (black) [24]. calcium, use of sunscreen, and skin color. Therefore, methods of multiple imputation data were applied, which Ultraviolet index and seasons follow three main steps: (a) imputation of missing data Data from the monitoring and recording of ultraviolet to obtain complete databases; (b) estimation based on index (UVI) in the city of Natal, RN, Brazil was obtained incomplete databases, and (c) a combination of methods. from the daily publications from the Laboratory of Tropi- Data were assumed to be missing at random [29]. cal Environmental Variables (LAVAT), of the National The 25OHD concentration variation throughout the Institute of Spatial Researches, Regional Center of the seasons was examined by one-way analysis of variance Northeast (INPE/CRN). The UVI was classified according (ANOVA). When the results were statistically signifi - to World Health Organization (WHO) guidelines [25] into cant, posthoc tests were performed to assess the differ - five categories according to UVI intensity: low, < 2; moder- ences among seasons. T-tests were used for independent ate, 3–5; high, 6–7; very high, 8–10, and extreme, ≥ 11. samples, followed by the correction of Bonferroni. For The participants were distributed in the spring, sum - the variables with imputed observations, the analysis mer, autumn, and winter seasons based on the half-life of between the seasons was performed using F tests (analog 25OHD corresponding to the 30 days preceding the date of ANOVA) of the univariate linear regression model. of the biochemical examination [26]. Thus, individual When the F test was significant, the P values of the participants were categorized into the respective seasons regression coefficients were also corrected by the Bonfer - based on the month into which this time interval fell. roni method. The potential predictors for the magnitude of the Biochemical tests 25OHD concentration were investigated using univariate Blood samples were collected from the participants after linear regression models and as well as multiple regres- an overnight fast (10–12  h) by standard venipuncture. sion (two or more predictor variables included in the Fasting blood glucose, HDL-cholesterol, triglyceride, model). and total calcium levels were measured by colorimetric In the univariate linear regression, 15 models were cre- tests using the test kit from the Wiener lab (Wiener lab ated using 25OHD concentration as a dependent vari- group, Argentina) and via the automated CMD800iX1 able and the other variables as predictors. In the multiple (Diamond Diagnostics, Holliston, MA, USA). Low-den- regression analysis, seven models were created using sity lipoprotein (LDL)-cholesterol levels were measured 25OHD levels as the dependent variable and the other as previously described [27]. variables as predictors, as follows: (1) gender, age, use The serum concentrations of the parathyroid (PTH) of sunscreen, sun exposure score, season, and WHR; (2) and insulin hormones were determined by chemilumi- gender, age, use of sunscreen, sun exposure score, season, nescent tests using a commercial analysis from Beck- and BMI; (3) gender, age, use of sunscreen, sun exposure ® ® man Coulter (Unicel DxI800 immunoassay system, score, season, and WC; (4) age, gender and region; (5) CA, USA). Serum concentrations of 25OHD were meas- season, UVI, sun exposure score, skin type, skin color, ured using the chemiluminescent Liaison test from kit and use of sunscreen; (6) total serum calcium and PTH DiaSorin (Saluggia, Italy). and (7) vitamin D and calcium intakes (Additional file 1). Aquino et al. Diabetol Metab Syndr (2018) 10:45 Page 4 of 9 The correlation between two variables was assessed number of MetS components between the seasons by determining Pearson correlation coefficients (r). For (Table 1). The most frequent components of MetS in the variables with imputed observations, the Pearson coef- participants were elevated WC (88%), elevated blood ficient was computed using the coefficient of simple lin - pressure (79%), low HDL-cholesterol (78%), elevated ear regression, considering the variables centered in their fasting blood glucose (75%), and high triglyceride levels averages and standardized by the sample standard devia- (54%). The HDL-cholesterol was the only component tion. Fisher’s exact test and its extensions were used to with significant variation among seasons, showing higher test the differences between proportions. The statistical concentrations in the autumn 45 ± 8 mg/dL and lower in significance assumed for all analysis was 5% (two-tailed, the summer 35 ± 8 mg/dL (Table 2). p < 0.05). All analyses were performed using Stata 14.0 Most of the individuals had mixed skin (67%), group (Stata Corporation, College Station, TX, USA). II skin type (32%), and did not use sunscreen (66%). The annual UVI average of 6.4 ± 1.8 was high. The UVI dif - Results fered significantly among seasons, especially between Characteristics of the participants winter and spring (p < 0.001), winter and summer Of the 180 total participants, 141 (78%) were female and (p = 0.001), spring and summer (p = 0.022), and spring 39 (22%) were male, with an average age of 50 ± 12 years. and autumn (p < 0.001), with index variations ranging There was no statistically significant variation in the from moderate to very high (Table 1). Table 1 Demographic, biological, and environmental characteristics of the individuals according to season Variables Seasons Total (n = 180) p Winter (n = 84) Spring (n = 50) Summer (n = 28) Autumn (n = 18) Gender 0.87 Female 66 (79) 39 (78) 23 (82) 13 (72) 141 (78) Male 18 (22) 11 (22) 5 (18) 5 (28) 39 (22) Age (years) 51 ± 13 49 ± 10 47 ± 13 54 ± 14 50 ± 12 0.22 a d Number of MetS components 0.33 3 components 43 (51) 21 (42) 10 (36) 6 (33) 80 (44) 4 components 29 (35) 16 (32) 13 (46) 6 (33) 64 (36) 5 components 12 (14) 13 (26) 5 (18) 6 (33) 36 (20) Self‑referred skin color 0.59 Black 6 (7) 4 (8) – – 10 (6) Mixed 51 (61) 26 (52) 17 (61) 15 (83) 109 (61) White 22 (26) 18 (36) 10 (36) 2 (11) 52 (29) Yellow 3 (5) 2 (4) 1 (4) 1 (6) 7 (3) Indigenous 1 (1) – – – 1 (1) Sunscreen 0.25 Do not use 51 (61) 37 (74) 17 (61) 14 (78) 120 (67) Always use 33 (39) 12 (24) 11 (39) 4 (22) 60 (33) a,e Skin type 0.29 I 7 (8) 5 (10) 2 (7) – 14 (8) II 30 (36) 13 (26) 10 (36) 4 (22) 57 (32) III 20 (24) 12 (24) 6 (21) 4 (22) 42 (23) IV 17 (20) 15 (30) 5 (18) 3 (17) 40 (22) V 10 (12) 5 (10) 5 (18) 7 (39) 27 (15) b,f UVI 5.5 ± 1.4 7.9 ± 2.2 6.8 ± 0.4 5.8 ± 0.4 6.4 ± 1.8 < 0.001 Data presented as n(%) Data presented as average ± standard deviation p, differences between seasons. T-tests were used for independent samples, followed by the correction of Bonferroni and Fisher’s exact test and its extensions were used to test the differences between proportions Chi square test was used to compare the proportions of the number of components between stations e 21 Skin type according to Fitzpratrick UVI, Ultraviolet radiation index of the 30 days previous to the biochemical exam Aquino et al. Diabetol Metab Syndr (2018) 10:45 Page 5 of 9 The average BMI was 33 ± 7  kg/m ; 77 and 23% had In the multiple regression model, sex, WHR, sun expo- obesity and overweight, respectively. The average overall sure score, and season significantly influenced 25OHD WC was 106 ± 13 cm, indicating an increased risk for the status explaining 10% of the variation in 25OHD status development of diseases associated with obesity. BMI, (p = 0.001; Table 3). WHR, and WC did not show significant statistical differ - Men with MetS had 25OHD concentration 3.71  ng/ ences among the seasons (Table 2). mL higher than those of women in this study. A 1.0 increment in sun exposure score was associated with a Seasonal variations of the 25OHD 0.16  ng/mL increase in 25OHD concentration, and the The percentage of individuals with 25OHD deficiency season was an independent predictor of 25OHD status. and insufficiency was higher in the winter (72%) and lower in the summer (50%). The average 25OHD concen - Discussion tration was 5.59 ng/mL higher in the summer than in the In the present study, sex, WHR, sun exposure score, and winter (95% CI 1.81–9.38 ng/mL; p = 0.024). season were predictors of 25OHD status among indi- viduals with MetS. We found significantly higher serum Predictors of 25OHD concentration 25OHD concentrations in the summer compared to the In the simple linear regression model, a statistically winter. Summertime improvement of vitamin D status significant association with summer (p = 0.003) was was accompanied by certain improved cardiometabolic observed, explaining 4% of the variability in 25OHD sta- risk factors, notably serum triglycerides, total cholesterol tus. Sun exposure score was significantly associated with and BMI, in Iranian children [30]. We speculated that 25OHD status (p = 0.008). There was no statistically sig - the higher prevalence of inadequate 25OHD levels in the nificant association between 25OHD concentration and study population might be associated with MetS clinical the co-variables of age, sex, geographic location, skin conditions. color, skin type and use of sunscreen, UVI, BMI, WHR, The discovery of the inverse relationship between WC, total serum calcium, PTH, and dietary calcium, and WHR and 25OHD status suggested that a high fat con- vitamin D. centration in the abdominal region may interfere with Table 2 Anthropometric nutritional status, clinics, and dietary characteristics of the individuals according to the season Variables Seasons Total (n = 180) p Winter (n = 84) Spring (n = 50) Summer (n = 28) Autumn (n = 18) 2 a BMI (kg/m ) 32 ± 7 34 ± 6 35 ± 7 34 ± 8 33 ± 7 0.36 WHR 0.97 ± 0.1 0.97 ± 0.1 0.97 ± 0.1 0.97 ± 0.1 0.97 ± 0.1 0.91 WC (cm) 104 ± 14 107 ± 11 108 ± 14 106 ± 14 106 ± 13 0.39 Triglycerides (mg/dL) 164 (126–217) 172 (116–235) 148 (120–188) 163 (135–218) 162 (120–221) 0.81 a d HDL‑ cholesterol (mg/dL) 42 ± 9 37 ± 9 35 ± 8 45 ± 8 40 ± 9 < 0.001 Fasting blood glucose (mg/dL) 108 (94–130) 110 (96–125) 106 (95–119) 117 (105–140) 108 (96–129) 0.35 Systolic blood pressure (mm/Hg) 130 (120–140) 132 (122–140) 128 (120–140) 130 (122–140) 130 (120–140) 0.80 Diastolic blood pressure (mm/Hg) 84 (80–90) 89 (83–95) 87 (80–90) 90 (83–93) 87 (80–90) 0.15 a e 25OHD (ng/mL) 26 ± 8 29 ± 10 32 ± 10 30 ± 9 28 ± 9 0.014 a f Total serum calcium (mg/dL) 10.1 ± 0.7 9.9 ± 0.7 9.4 ± 0.5 9.8 ± 0.4 9.9 ± 0.7 < 0.001 PTH (pg/mL) 35 (25–51) 35 (22–48) 25 (17–34) 36 (20–41) 34 (22–47) 0.06 Vitamin D intake (IU/day) 109 (63–150) 82 (45–141) 80 (60–124) 91 (67–158) 90 (59–146) 0.28 Calcium intake (mg/day) 473 (315–632) 426 (254–560) 409 (245–639) 404 (297–524) 441 (294–593) 0.30 BMI body mass index, WHR waist:hip ratio, WC waist circumference; PTH parathyroid hormone Data presented as average ± standard deviation) Data presented as median (interquartile interval) p, difference among seasons. ANOVA was used to compare the variables throughout the seasons. For the variables with imputed observations, the analysis between seasons was performed using F tests (analog of ANOVA) p, for multiple comparisons: winter vs. spring (p = 0.007), winter vs. summer (p = 0.003), spring vs. autumn (p = 0.012), and summer vs. autumn (p = 0.004) p, for multiple comparisons: winter vs. spring (p = 0.378), winter vs. summer (p = 0.017), winter vs. autumn (p = 0.581), spring vs. summer (p > 0.99), spring vs autumn (p > 0.99), and summer vs. autumn (p > 0.99) p, for multiple comparisons: winter vs. spring (p = 0.67), winter vs. summer (p = 0.001), winter vs. autumn (p = 0.16), spring vs. summer (p = 0.012), spring vs. autumn (p > 0.99), and summer vs. autumn (p = 0.73) Aquino et al. Diabetol Metab Syndr (2018) 10:45 Page 6 of 9 Table 3 Multiple regression model for  the  prediction Because the Rio Grande do Norte state is a Brazilian of 25OHD concentrations (ng/mL) in individuals with MetS territory with high year-round solar radiation, 25OHD (n = 180) levels were expected to be sufficient in this population, regardless of the season [16]. In the period assessed in 25OHD (ng/mL) the current study, the average environmental UVI ranged a 2 Predictors Β SE 95% CI p R from moderate to high in every season, with significant Sun exposure score 0.164 0.06 0.05–0.28 0.006 0.104 differences between the moderate and high UVI in the Seasons winter and summer, respectively. However, 63% of the Winter (Ref.) individuals assessed in this study had inadequate 25OHD Spring 3.178 1.57 0.08–6.27 0.045 levels, the proportion of which increased in the winter. Summer 5.593 1.92 1.81–9.38 0.004 This finding emphasizes the essential roles of the seasons, Autumn 3.108 2.29 − 1.42–7.64 0.18 and sun exposure on the variability in 25OHD status. More recently, there has been a growing appreciation Sex 3.716 1.67 0.43–7.00 0.027 for the beneficial impact that sunlight has on the cardio - WHR − 25.080 11.23 − 47.26–2.89 0.027 vascular system, independent of vitamin D production. Age (years) 0.0001 0.56 − 0.11–0.11 0.10 Vitamin D could in these circumstances act as a marker Use of sunscreen for sunlight exposure and its postulated beneficial effects Do not use (Ref.) [34]. Always use 2.671 1.41 − 0.11–5.45 0.06 The seasonality of vitamin D status has been noted in Sometimes use − 3.91 8.91 − 21.52–13.69 0.66 other studies, in addition to reports on the incidence of β regression coefficient, SE standard error, CI confidence interval, Ref. reference group MetS and its related components [35]. In the present p, for multiple comparisons: winter vs. spring, winter vs. summer, winter vs. study, seasonal variation was observed in the concentra- autumn, spring vs. summer, spring vs. autumn, and summer vs. autumn tion of HDL-cholesterol, especially in the summer, where the lowest concentrations of this component were noted. vitamin D metabolism. This is explained by the liposol - A study of 1202 male Japanese subjects reported a higher uble nature of vitamin D, thus higher fat concentrations prevalence of MetS in the winter compared to that of the in the abdominal region favor the uptake of vitamin D to summer, with similar results for the MetS components the adipose tissue, resulting in inadequate 25OHD con- such as HDL-cholesterol, systolic and diastolic blood centrations. Miñambres et  al. found inadequate 25OHD pressure, and fasting blood glucose levels [7]. Summer status regardless of the level of obesity, a finding that sup - season was also positively associated with low HDL-C, ports the existence of this inverse correlation between and MetS in Chinese adults when summer–winter differ - higher abdominal adipose tissue concentration and inad- ences in components of MetS were investigated [36]. equate 25OHD [13]. We can attribute higher concentrations of 25OHD Few studies have assessed the influence of the seasons in the summer, along with lower concentrations of on 25OHD status among individuals living in cities in HDL-cholesterol, to the fact that 64% of individuals the northeastern regions of Brazil. Studies conducted on were diagnosed as having more than three of the com- adults and elderly in the city of São Paulo, in the south- ponents of MetS, which represents greater metabolic eastern region of Brazil, reported results similar to those impairment. Changes in the lipid profile between the of our study [31, 32]. The positive association between seasons can be explained by a set of seasonal changes, the sun exposure score and 25OHD status can be such as blood hemodilution during the summer, and explained by the presence of 7-DHC in the plasma mem- blood hemoconcentration in winter, as well as changes brane of epidermal cells; it is a photosensitive molecule in eating habits, and physical activity [37]. The associa - that absorbs ultraviolet radiation with a wavelength from tion between low 25OHD status, and low HDL-choles- 290–315 nm. Following this absorption, the entire meta- terol concentrations has been discussed in some studies bolic pathway is initiated to activate vitamin D synthesis but are still controversial. Data from the Tromsø Study [8]. This discovery reinforces the utility of the assessment showed in adults a strong and positive association tool used in the study, which offered good accuracy to between serum 25(OH)D and HDL. However, the cause assess sun exposure. of this association still remains unknown [38, 39]. Sy et  al. reported that an increase of 25OHD concen- Our study did not focus on evaluating the association tration by approximately 10  ng/mL decreases the risk of among vitamin D and lipid profile or the other compo - developing MetS by 13%. An important point for further nents of the MetS. discussion is therefore the ideal 25OHD concentration The higher 25OHD levels in the male participants may for individuals with MetS [33]. have been due to the higher sun exposure than women Aquino et al. Diabetol Metab Syndr (2018) 10:45 Page 7 of 9 Conclusions (25 ± 13 vs. 21 ± 11). It is important to highlight that 66% In conclusion, sex, WHR, sun exposure and summer of the participants did not use sunscreen, which validates season were predictors of 25OHD status among indi- the results regarding sun exposure and 25OHD concen- viduals with MetS. In addition to this, HDL-cholesterol tration. A study that included 95,137 Korean individuals was the only component of the MetS that differed sig - analyzed 25OHD status according to sex, age, and season nificantly among the seasons. These results demonstrate also reported differences in 25OHD status, with higher the importance of considering these variables in clinical concentrations among the male participants [40]. interventions with vitamin D, and underscore the need The prevalence of inadequate micronutrient and for further development and updated guidelines for the macronutrient intakes was assessed previously in par- treatment of MetS. ticipants of the current study showing that 100, and 99% of the participants had inadequate vitamin D, and cal- Additional file cium intakes, respectively [41]. Therefore, evidently diet was not a significant external source of vitamin D that Additional file 1. Multiple regression model for the prediction of indi‑ contributed to the variation in 25OHD concentration, viduals with metabolic syndrome. according to the seasons. Skin color and skin type did not influence 25OHD con - Abbreviations centration, a finding discordant from those of previous MetS: metabolic syndrome; 25OHD: 25‑Hydroxyvitamin D; UVI: ultraviolet studies [15, 42]. However, in our study, skin color was radiation index; BMI: body mass index; WHR: waist:hip ratio; WC: waist circum‑ self-classified, which means that individuals subjectively ference; PTH: parathyroid hormone; 7‑DHC: 7‑Dehydrocholesterol; NCEP ‑ATP III: National Cholesterol Education Program‑Adult Treatment Panel III; LAVAT: classified themselves, leading to various potential biases; Laboratory of Tropical Environmental Variables; LDL: low‑ density lipoprotein; therefore, the reported skin color may not be the actual HDL: high‑ density lipoprotein. skin color. Authors’ contributions The studied participants were sampled from a location SLSA, LFCP, and JGL conceived and designed the experiments. SLSA, ATOC, with a steady and a high year-round solar radiation. This HTP, and EPSF performed the experiments. SLSA, APTF, SCVCL, and KCMS ana‑ observation might explain, at least in part, the smaller lyzed the data. SLSA, ATOC, HTP, EPSF, APTF, JGL, SCVCL, KCMS, and LFCP wrote the paper. All authors read and approved the final manuscript. magnitude of the coefficient of determination (10%) compared to previous investigations carried out in loca- Author details tions with larger variations in sunlight exposure among Postgraduate Nutrition Program, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal, RN 59078‑970, Brazil. Postgraduate seasons. Program in Health Sciences, Center for Health Sciences, Federal University Our study had some limitations, including its cross- of Rio Grande do Norte, Natal, RN 59012‑570, Brazil. Department of Nutri‑ sectional study design, in which the same individuals tion, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal, RN 59078‑970, Brazil. Department of Clinical Medicine, Endocrine Unit, were not assessed over the four seasons and the number Federal University of Rio Grande do Norte, Natal, RN 59010‑180, Brazil. of the participants in each season. Moreover, the ultravi- olet radiation and UVI measures reflected not only UVB Acknowledgements The authors thank Cínthia Regina Mendes Ferino and Mariana Pontes de radiation, but also UVA radiation. This correction may Sousa Santos for their assistance with data collection; the team of the Endocri‑ be performed in others studies considering assessments nology Clinic of the University Hospital Onofre Lopes for their partnership and for vitamin D3 production in human skin from outdoor attention to the research; the Laboratory of Tropical Environmental Variables (LAVAT ) of the National Institute of Spatial Researcher, Regional Center of the exposures as well as account related to different contribu - Northeast; Tiago Veiga Pereira for assistance with statistical analysis; and the tions of each action spectrum with changing solar zenith Improvement Coordination of Higher Education (CAPES) for the scholarship angle [43]. grant. In addition, given the unmatched design, we cannot Competing interests fully rule out that covariate imbalances might contribute The authors declare that they have no competing interests. to the observed associations. However, for the examined Availability of data and materials covariates, only two were considered statistically sig- The datasets used and/or analyzed during the current study are available from nificant in univariable models, and associations between the corresponding author on reasonable request. 25OHD and sunlight exposure score, seasons and body Consent for publication surface area were robust to adjustments for other covari- Not applicable. ates included in the model. Ethics approval and consent to participate The study was approved by the Research Ethics Committee of HUOL (CAAE n. 13699913.7.0000.5292). Aquino et al. Diabetol Metab Syndr (2018) 10:45 Page 8 of 9 Funding 17. Fajuyigbe D, Young AR. The impact of skin colour on human photobio‑ This work was supported by the National Council for Scientific and Techno ‑ logical responses. 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Diabetology & Metabolic SyndromeSpringer Journals

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