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Determinants of serum levels of vitamin D: a study of life-style, menopausal status, dietary intake, serum calcium, and PTH

  • Leila Shirazi1, 2Email author,
  • Martin Almquist2, 3,
  • Johan Malm4,
  • Elisabet Wirfält5 and
  • Jonas Manjer2, 6
BMC Women's Health201313:33

DOI: 10.1186/1472-6874-13-33

Received: 16 January 2013

Accepted: 26 June 2013

Published: 15 August 2013

Abstract

Background

Low blood levels of vitamin D (25-hydroxy D3, 25OHD3) in women have been associated with an increased risk of several diseases. A large part of the population may have suboptimal 25OHD3 levels but high-risk groups are not well known. The aim of the present study was to identify determinants for serum levels of 25OHD3 in women, i.e. factors such as lifestyle, menopausal status, diet and selected biochemical variables.

Methods

The study was based on women from the Malmö Diet and Cancer Study (MDCS), a prospective, population-based cohort study in Malmö, Sweden. In a previous case–control study on breast cancer, 25OHD3 concentrations had been measured in 727 women. In these, quartiles of serum 25OHD3 were compared with regard to age at baseline, BMI (Body Max Index), menopausal status, use of oral contraceptives or menopausal hormone therapy (MHT) , life-style (e.g. smoking and alcohol consumption), socio-demographic factors, season, biochemical variables (i.e. calcium, PTH, albumin, creatinine, and phosphate), and dietary intake of vitamin D and calcium. In order to test differences in mean vitamin D concentrations between different categories of the studied factors, an ANOVA test was used followed by a t-test. The relation between different factors and 25OHD3 was further investigated using multiple linear regression analysis and a logistic regression analysis.

Results

We found a positive association between serum levels of 25OHD3 and age, oral contraceptive use, moderate alcohol consumption, blood collection during summer/ autumn, creatinine, phosphate, calcium, and a high intake of vitamin D. Low vitamin D levels were associated with obesity, being born outside Sweden and high PTH levels.

Conclusions

The present population-based study found a positive association between serum levels of 25OHD3 and to several socio-demographic, life-style and biochemical factors. The study may have implications e. g. for dietary recommendations. However, the analysis is a cross-sectional and it is difficult to suggest Lifestyle changes as cause- effect relationships are difficult to assess.

Background

Low blood levels of vitamin D (25-hydroxy D3, 25OHD3) in women have been associated with an increased risk of hypertension [1], myocardial infarction [2], sudden cardiac death [3], depression [4], diabetes [5], obesity [6], fracture [7] and cancer [8, 9]. However, determinants of levels of 25OHD3 are not well known, and few studies have examined the impact of lifestyle, and menopausal status, dietary and biochemical factors on vitamin D status. Furthermore, a large part of the population in northern countries might suffer from suboptimal 25OHD3 levels because of inadequate exposure to sunlight [10], due to geographical location [11], cultural differences [12], and race [13, 14].

Sun exposure plays a central role in vitamin D metabolism as vitamin D is formed in the skin under the influence of UV light [15], and there is a well-known seasonal variation with lowest levels during the winter [16]. The other source of vitamin D is from the diet, but the association between dietary intake and serum 25OHD3 levels has not been extensively investigated [17]. Sun exposure and diet may indeed be affected by socioeconomic factors and life-style; for instance low vitamin D levels have been noted among low income groups [18], and among individuals with heavy alcohol consumption [19]. However, apart from this, few studies have reported on vitamin D in relation to life-style and menopausal status. Vitamin D metabolism is closely related to PTH, calcium and phosphate [20].

This study is based on data from the Malmö Diet and Cancer Study (MDCS), a prospective, population-based cohort study in Malmö, Sweden [21]. At baseline, 17,035 women answered a questionnaire on life-style, reproductive life and socio-demographic factors. An important part of the examination was a dietary assessment and collection of blood samples [22].

The aim of the present study was to identify determinants for serum levels of 25OHD3 in women, i.e. factors such as lifestyle, menopausal status, diet and selected biochemical variables.

Methods

The malmö diet and cancer study

The Malmö Diet and Cancer Study (MDCS) is a prospective, population-based cohort study in Malmö, Sweden’s third largest city with about 300,000 inhabitants. The main aim of the MDCS was to estimate the potential association between dietary factors and malignancy [23]. All women in Malmö born 1923–1950 were invited and the baseline examination took place between 1991 and 1996. The majority of women were born in Sweden or other Nordic countries. Finally, 17,035 women participated, corresponding to a participation rate of approximately 40%.

Baseline examination

All participants completed a questionnaire on socio-economic factors (e.g. education, occupation, country of birth), life-style (e.g. smoking, alcohol consumption, use of oral contraceptives (OC) and menstrual status), and for women also menopausal status. Smoking status was classified as current, never or ex-smoking. An open ended question assessed use of medications. For the purpose of the present analysis, menopausal hormone therapy (MHT) was classified into two categories: non-users and current users. Women were classified as pre- or peri/ postmenopausal using information on previous gynaecologic surgery and last menstruation as previously described in detail [24]. Anthropometric measurements were performed and Body Mass Index (BMI) was calculated (kg/m2). BMI was classified as underweight <20, normal weight ≥ 20 - <25, overweight ≥25 - <30, and obesity ≥30. Season was classified as “spring” (March-April), “summer” (May-August), “autumn” (September-October) and “winter” (November-February), based on the date of the baseline examination.

Dietary data

Dietary data was obtained through a modified diet history consisting of (a) a 168-item dietary questionnaire for assessment of the consumption frequencies and portion sizes of regularly eaten foods (i.e. sandwiches, cakes and cookies, fruit, breakfast cereals, milk and yoghurt, coffee, tea, candy, snacks etc.) and the general meal pattern, (b) a 7 day menu-book for registration of cooked lunch and dinner meals, cold beverages including alcohol, drugs, natural remedies and nutrient supplements, and c) a one-hour diet history interview [25]. The food intake information was converted to nutrient intake data using the nutrient information available in the MDCS Food and Nutrient Database. This database, specifically developed for the MDCS, originates from PC KO ST2 -93 of the Swedish National Food Administration. The average daily intake of total energy and nutrients was calculated. The procedure has been previously described in detail [26]. The relative validity of the diet history method has previously been examined with 18 days of weighed food records collected during one year as the reference [25]. In women, the energy-adjusted validation correlation coefficients were for calcium 0.65 and for total energy intake 0.54, when administrating the diet history prior to the reference method.

This study examined the following nutrient variables: total energy (kcal), vitamin D (μg) and calcium (mg). Separate analyses were performed for intake related to food, and total intake including supplements. In order to adjust for energy, the residual method was applied using log-transformed variables of total energy, vitamin D and calcium intakes [26]. Four different variables were created by regressing the log-transformed variables separated on total energy intake: (1) vitamin D-dietary; (2) vitamin D-total (i.e. dietary and supplement); (3) calcium-dietary; and (4) calcium-total. The residuals were saved for each variable, and individuals were categorized into five categories (quintiles). The limits for the original variables were given for each quintile.

Alcohol consumption was divided into five categories: zero, low (<15 g alcohol/day), medium (15-30 g alcohol/day), high (>30 g alcohol/day), and infrequent use. The amount per day was obtained from the menu book. Participants with zero consumption in the menu book and with no consumption during the previous thirty days or previous year according to the questionnaire were categorized as zero consumers [27]. Participants with zero consumption in the menu book but reporting alcohol consumption during the previous thirty days or previous year were regarded as infrequent users. For example a glass of wine (12 centilitres) corresponds to 15 grams pure alcohol.

Study population

The present study is based on data from female controls from a previous nested case–control study within the MDCS [22]. In that study, cases were women with incident breast cancer; controls were selected from MDCS subjects at risk at the time of disease occurrence of the case. Cases and controls were matched for age, calendar time of blood sampling, and menopausal [28] status. Out of 738 controls, 11 had no data on 25OHD3 concentrations and were excluded. Thus, the present study is based on data from 727 women.

Blood samples and laboratory methods

Blood samples were drawn at baseline in non-fasting subjects by a trained nurse and plasma and serum separated within 1 hour. The samples were subsequently stored in a biological bank at −80°C before analysis [23]. Serum was retrieved from un-thawed samples in the MDCS bio-bank was analysed for 25OHD3, PTH, calcium, phosphate, creatinine and albumin. 25OHD3 was analysed with high pressure liquid chromatography (HPLC) and PTH with the Immulite® 2000 Intact PTH immunoassay (Diagnostic Products Corporation, Los Angeles, CA). Total calcium was analysed by neutral carrier ion-selective electrode [29], albumin by rate immunonephelometry [28], phosphate by a colorimetric method by complexing with ammoniummolybdate and creatinine by the Jaffé method. These analyses were carried out with the Synchron LX System (Beckman Coulter Inc., Brea, CA.). Inter-assay CVs were for 25OHD3 8.5% at 70 nmol/L and 7.1% at 210 nmol/L, for PTH 4% at 5.9 pmol/L and at 40.3 pmol/L, for calcium 2% at 2.00 mmol/L and at 3.10 mmol/L, for albumin 4% at 25 g/L and 2% at 48 g/L, for creatinine 12% at 34 μmol/L and 4% at 129 μmol/L, and for phosphate 3% at 0.66 mmol/L and 5% at 2.5 mmol/L. The Clinical Chemistry laboratory at Skåne University Hospital Malmö is accredited by Swedac (The Swedish Board for Accreditation and Conformity Assessment) and takes part in the external quality assurance program of Instand e.V., Düsseldorf, Germany.

Statistical methods

Serum levels of 25OHD3 were normally distributed. The cohort subjects were ranked into quartiles based on serum levels of 25OHD3. Different quartiles of serum 25OHD3 were compared with regard to age at baseline (continuous and as categories in five-year intervals), life-style, BMI (continuous and categorical), menopausal status, socio-demographic factors, season, biochemical variables, and dietary intakes.

Means of serum 25OHD3 were calculated in different categories of all factors mentioned above. Confidence intervals were chosen as an estimation of the accuracy of the estimated means. In order to examine differences in mean vitamin D concentrations between different categories of the studied factors, ANOVA was used followed by a Bonferroni t-test, thus multiplying the obtained p-values with the number of comparisons. All tests were two-sided and a p-value of 0.05 was considered statistically significant. Missing values constituted less than 1% for all factors.

Serum 25OHD3 levels were dichotomized into low (≤75 nmol/L) and high (>75 nmol/L), i.e., the cut-off indicating the minimum level previously estimated to be sufficient [30]. Odds ratios with 95% confidence intervals (CI) were estimated for high versus low concentrations, in relation to each of the studied factors, using a logistic regression analysis. In a second model, the odds ratios for high versus low concentrations were adjusted for age, season and storage time. Age has previously been related to vitamin D levels and there is a well-known seasonal variation in vitamin D levels [31]. The potential effect of biological degradation is not well known and this justified the inclusion of storage time in the final model. In a sensitivity analysis, a third model included adjustment for total dietary vitamin D intake (entered as quintiles).

The relation between different factors and 25OHD3 was further investigated using multiple linear regression analysis. All categorical variables in the linear regression analysis were recorded and entered as multiple categorical variables with values as 0 or 1. Partial regression coefficients (βi) with 95% confidence intervals, adjusted for age, season and storage time, were reported. All statistical analyses were performed using SPSS version 17.0.

Results

In this cross-sectional study on 727 women, mean age at blood sampling was 56.9 years (range: 41–73 years), 74% were postmenopausal, 91% were born in Sweden, mean BMI was 25.5 kg/m2 (SD: 16.61 – 50.19), and the mean level of 25OHD3 was 88.3 nmol/L (SD: 18–173).

Co-variates used in the multivariate analyses, (i.e., age at baseline, season and storage time), were all examined in relation to 25OHD3 concentrations and presented below. There was no significant association between storage time and 25OHD3 concentrations. The odds of high 25OHD3 concentration, adjusted for age and season, were for storage time as a continuous variable: 0.98 (0.87-1.09). The linear regression analysis showed an adjusted regression coefficient for storage time of −0.59 (−1.97 to 0.79). That is, there was no strong association between storage time and 25OHD3 levels.

Age, life-style, menopausal status, season, and socio-demographic factors

Vitamin D quartiles 3 and 4 were characterised by a relatively large proportion of women >65 years old Table 1. The positive association between age and high vitamin D levels was confirmed with a trend of increase in vitamin D levels observed in older women in the analyses of mean 25OHD3 in different age categories, Table 2, and in the continuous linear regression analysis, Table 3. There was also a positive association between vitamin D levels and use of OC in all analyses, Tables 1, 2, and 3. Women with relatively high 25OHD3 levels were less often overweight or obese, and this negative association was also seen comparing mean levels in different BMI categories, Table 2, in the dichotomised logistic regression analysis, and in the linear regression analysis, Table 3.
Table 1

Distribution of serum vitamin D quartiles in relation to reproductive history, life-style factors and season

Factor

Serum vitamin D quartile [nmol/L]

1 [18–69]

2 [70–86]

3 [87–104]

4 [105–173]

All

n = 179

n = 187

n = 177

n = 184

n = 727

Column percent*; mean (SD) in italics

Age (years)

56.2 (7.3)

56.2 (7.9)

58.1 (7.2)

57.2 (7.2)

56.9 (7.2)

 ≤50

27.9

23.5

18.1

19.6

22.3

 >50 – ≤55

22.3

23.0

18.6

26.1

22.6

 >55 – ≤60

19.0

20.3

21.5

16.8

19.4

 >60 – ≤65

17.9

21.9

20.9

19.6

20.1

 >65

12.8

11.2

20.9

17.9

15.7

BMI (kg/m2)

26.7 (4.96)

25.5 (4.5)

25.1 (3.4)

24.6 (3.4)

25.5 (4.2)

 <20

5.0

6.4

4.5

6.5

5.6

 ≥20 – <25

39.1

44.9

48.6

52.2

46.2

 ≥25 – <30

34.6

34.2

40.1

33.7

35.6

 ≥30

21.2

14.4

6.8

7.6

12.5

Oral contraception

 No

52.5

52.9

51.4

44.6

50.3

 Yes

47.5

47.1

48.6

55.4

49.7

Menopausal status

 Pre

30.7

26.7

21.5

23.9

25.7

 Peri/post

69.3

73.3

78.5

76.1

74.3

MHT** (n = 537)

 No

77.4

86.1

72.7

76.4

78.1

 Yes

21.0

13.9

26.6

23.6

21.3

Smoking status

 Never

40.8

43.3

42.9

41.3

42.1

 Current

29.6

24.1

29.4

27.7

27.6

 Ex

29.6

32.6

27.7

31.0

30.3

Alcohol consumption

 Zero

11.7

6.4

7.9

5.4

7.8

 <15 g/day

58.7

68.4

61.6

62.5

62.9

 15 – 30 g/day

12.8

11.2

16.9

14.1

13.8

 >30 g/day

3.9

1.1

2.8

3.3

2.8

 Infrequent

12.8

12.8

10.7

14.7

12.8

Baseline season

 Spring

43.6

25.1

27.1

14.1

27.4

 Summer

14.5

22.5

31.1

43..5

27.9

 Autumn

15.6

22.5

20.3

23.4

20.5

 Winter

26.3

29.9

21.5

19.0

24.2

Education

 O-level college

67.0

66.3

67.8

71.7

68.2

 A-level college

10.1

7.0

7.9

6.5

7.8

 University

22.9

26.7

24.3

21.7

23.9

Socio-economic index

 Manual

39.1

35.8

35.6

40.2

37.7

 Non-manual

53.1

51.3

59.9

53.8

54.5

 Employer

7.3

12.8

4.5

6.0

7.7

Born in Sweden

 Yes

83.2

91.4

93.8

92.9

90.4

 No

16.8

8.6

6.2

7.1

9.6

* Due to missing values, percentages do not always add up to 100%. ** Only in peri/postmenopausal.

Table 2

Mean serum vitamin D levels in relation to reproductive history, life–style factors and season

Factor

No.

Mean (95% CI)

T–test (p–value*)

ANOVA (p–value)

Age (years)

 ≤50

162

84.4 (80.3–88.6)

Ref.

 >50 – ≤55

164

88.6 (84.3–92.8)

0.10

 >55 – ≤60

141

87.7 (83.0–92.5)

0.29

 >60 – ≤65

146

88.5 (84.6–92.5)

0.13

 >65

114

93.6 (88.3–98.9)

0.01

0.107

BMI (kg/m2)

 <20

41

93.2 (83.6–102.8)

0.62

 ≥20 – <25

336

91.0 (88.1–93.9)

Ref.

 ≥25 – <30

259

87.9 (84.6–91.1)

0.16

 ≥30

91

77.3 (71.7–82.9)

<0.001

<0.001

Oral contraception

 No

366

86.9 (84.2–89.5)

Ref.

 Yes

361

89.7 (86.8–92.6)

0.011

0.011

Menopausal status

 Pre

187

85.0 (81.1–88.8)

Ref.

 Peri/Post

540

89.4 (87.1–91.7)

0.056

0.056

MHT** (n = 537)

 No

422

89.2 (86.6–91.8)

Ref.

 Yes

115

90.8 (85.7–95.9)

0.57

0.27

Smoking status

 Never

306

87.9 (85.0–90.8)

Ref.

 Current

201

87.3 (83.3–91.3)

0.813

 Ex

220

89.7 (86.0–93.4)

0.443

0.635

Alcohol consumption

 Zero

57

80.3 (72.8–87.8)

Ref.

 <15 g/day

457

88.9 (86.4–91.4)

0.025

 15 – 30 g/day

100

89.5 (84.8–94.3)

0.032

 >30 g/day

20

82.7 (66.3–99.1)

0.762

 Infrequent

93

89.7 (83.9–95.5)

0.049

0.169

Baseline season

 Spring

199

78.6 (74.8–82.4)

Ref.

 Summer

203

99.0 (95.2–102.7)

<0.001

 Autumn

149

89.6 (85.8–93.5)

<0.001

 Winter

176

85.7 (81.8–89.6)

0.011

<0.001

Education

 O–level college

496

89.3 (86.9–91.7)

Ref.

 A–level college

57

83.4 (75.8–91.0)

0.128

 University

174

87.0 (83.0–91.0)

0.324

0.236

Socio–economic index

 Manual

274

89.0 (85.6–92.5)

Ref.

 Non–manual

396

88.5 (85.9–91.1)

0.796

 Employer

56

83.9 (77.3–90.5)

0.221

0.158

Born in Sweden

 Yes

657

89.3 (87.2–91.4)

Ref.

 No

70

78.6 (72.0 –85.3)

0.002

0.00

* Compared to reference (p–value). ** Only in peri/postmenopausal.

Table 3

Crude and adjusted odds ratios (OR) for high (> 75 nmol/L) vs . low (≤75 nmol/L) vitamin D levels, and regression coefficients (βi) from multiple regression analysis, in relation to reproductive history, life–styles factors and season

Factor

Low (n)

High (n)

Crude OR (95% CI)

Adjusted*OR (95% CI)

βi (95% CI)

Adjusted* βi (95% CI)

Age (years)

 ≤50

59

103

1.00

1.00

Baseline

Baseline

 >50 – ≤55

53

111

1.20 (0.76–1.90)

1.18 (0.73–1.92)

4.13 (–1.78 to 10.0)

4.10 (–1.73 to 9.94)

 >55 – ≤60

49

92

1.08 (0.67–1.72)

0.99 (0.60–1.64)

3.31 (–2.83 to 9.46)

2.25 (–3.84 to 8.33)

 >60 – ≤65

42

104

1.42 (0.88–2.29)

1.49 (0.89–2.49)

4.12 (–1.97 to 10.2)

5.05 (–1.02 to 11.1)

 >65

31

83

1.53 (0.91–2.59)

1.44 (0.84–2.48)

9.14 (2.61 to 15.7)

8.03 (1.73 to 14.3)

BMI (kg/m2)

 <20

12

29

0.80 (0.45–1.86)

0.97 (0.46–2.04)

1.12 (–3.25 to 5.50)

1.47 (–2.73 to 5.68)

 ≥20– <25

92

244

1.00

1.00

Baseline

Baseline

 ≥25– <30

82

177

0.26 (0.57–1.16)

0.79 (0.55–1.14)

−1.55 (–3.74 to 0.63)

−1.73 (–3.84 to 0.39)

 ≥30

48

43

0.34 (0.21–0.54)

0.31 (0.19–0.52)

−6.84 (–9.97 to –3.72)

−6.98 (–10.0 to –3.94)

Oral contraception

 No

126

240

1.00

1.00

Baseline

Baseline

 Yes

108

253

1.23 (0.90–1.68)

1.49 (1.04–2.13)

2.84 (–1.13 to 6.80)

5.40 (1.17 to 9.62)

Menopausal status

 Pre

67

120

1.00

1.00

Baseline

Baseline

 Peri/post

167

373

1.25 (0.88–1.77)

1.22 (0.70–2.12)

4.42 (–0.12 to 8.95)

3.62 (–3.10 to 10.3)

MHT** (n = 537)

 No

135

287

1.00

1.00

Baseline

Baseline

 Yes

30

85

1.33 (0.84–2.12)

1.37 (0.85–2.23)

−1.52 (–4.53 to 1.48)

−1.55 (–4.50 to 1.40)

Smoking status

 Never

97

209

1.00

1.00

Baseline

Baseline

 Ex

66

135

0.95 (0.65–1.39)

1.06 (0.71–1.58)

−0.58 (–5.44 to 4.28)

0.85 (–3.91 to 5.62)

 Current

71

149

0.97 (0.67–1.41)

1.03 (0.70–1.52)

1.81 (–2.93 to 6.54)

2.42 (–2.18 to 7.03)

Alcohol consumption

 Zero

25

32

1.00

1.00

Baseline

Baseline

 <15 g/day

311

315

1.73 (0.99–3.03)

1.92 (1.07–3.45)

8.60 (1.10 to 16.1)

9.31 (2.05 to 16.6)

 15 – 30 g/day

30

70

1.82 (0.93–3.58)

2.16 (1.06–4.41)

9.20 (0.34 to 18.1)

10.7 (2.03 to 19.3)

 >30 g/day

8

12

1.17 (0.42–3.30)

1.44 (0.48–4.33)

2.38 (–11.5 to 16.3)

4.51 (–9.01 to 18.0)

 Infrequent

29

64

1.72 (0.87–3.41)

2.01 (0.99–4.08)

9.41 (0.42 to 18.4)

10.9 (2.21 to 19.5)

Baseline season

 Spring

95

104

1.00

1.00

Baseline

Baseline

 Summer

39

164

3.84 (2.46–6.00)

3.89 (2.48–6.12)

20.3 (15.2 to 25.5)

20.1 (14.9 to 25.2)

 Autumn

39

110

2.58 (1.63–4.08)

2.52 (1.59–4.00)

11.0 (5.45 to 16.6)

10.5 (4.94 to 16.1)

 Winter 

61

115

1.72 (1.14–2.61)

1.71 (1.12–2.60)

7.04 (1.72 to 12.4)

6.80 (1.47 to 12.1)

Education

 O–level college

158

338

1.00

1.00

Baseline

Baseline

 A–level college

23

34

0.69 (0.39–1.21)

0.70 (0.39–1.27)

−5.87 (–13.3 to 1.61)

−5.63 (–12.9 to 1.62)

 University 

53

121

1.07 (0.73–1.55)

1.17 (0.78–1.74)

−2.31 (–7.02 to 2.40)

−1.10 (–5.77 to 3.57)

Socio–economic index

 Manual

93

181

1.00

1.00

Baseline

Baseline

 Non–manual

120

276

1.18 (0.85–1.64)

1.24 (0.88–1.75)

−0.37 (–4.57 to 3.83)

0.20 (–3.87 to 4.27)

 Employer

20

36

0.93 (0.51–1.69)

0.88 (0.47–1.65)

−4.91 (–12.7 to 2.94)

−4.97 (–12.6 to 2.62)

Born in Sweden

 Yes

200

457

1.00

1.00

Baseline

Baseline

 No

34

36

0.46 (0.28–0.76)

0.44 (0.26–0.74)

−10.6 (–17.3 to –3.96)

−10.5 (–16.9 to –4.08)

* Adjusted for age, season and time in freezer. ** Only in peri/postmenopausal.

The association between 25OHD3 and alcohol showed a bimodal pattern where 25OHD3 quartiles 1 and 4 had the highest percentage of high consumers (>30 g/day), Table 1. Correspondingly, women who reported no alcohol consumption or were high consumers had low 25OHD3 levels, Table 2, and this pattern was confirmed in the dichotomised analysis and in the continuous analysis, Table 3.

The highest concentration of 25OHD3 was seen during the summer and in the autumn, Table 1. This was confirmed in both the logistic regression analysis and in the linear regression analysis, Table 3. Women with relatively low vitamin D levels were more often born abroad, Table 1. This association was confirmed in the dichotomised analysis and in the continuous analysis, Table 3. Vitamin D was not associated with menopausal status, use of MHT, smoking status, education and socio-economic index in this study.

Most results were similar following inclusion of dietary intake of total vitamin D in the logistic regression analysis, but the OR s for oral contraception changed from 1.49 (1.04-2.13) to 1.40 (0.97-2.02), for Born in Sweden from 0.44 (0.26-0.74) to 0.51 (0.30-0.89 and for menopausal status from 1.22 (0.70-2.12) to 1.28 (0.72-2.25).

Biochemical variables

Women with relatively high 25OHD3 levels had more often high albumin levels, Table 4, but the association did not reach statistical significance when 25OHD3 levels were compared in different albumin quartiles, Table 5, or in the dichotomised analysis, Table 6. However, there was a statistically significant positive association in the linear regression analysis, Table 6. 25OHD3 was also positively associated with creatinine, phosphate and calcium in all analyses, Tables 4, 5, and 6; although the association was borderline significant concerning phosphate in the adjusted dichotomised analysis, Table 6. In all analyses, there was an inverse association between 25OHD3 and PTH concentrations, Tables 4, 5, and 6. All crude and adjusted analyses were similar.
Table 4

Serum vitamin D quartiles in relation to biochemical parameters and dietary intake

 

Serum vitamin D quartile [nmol/L]

1 [18–69] n = 179

2 [70–86] n = 187

3 [87–104] n = 177

4 [105–173] n = 184

All n = 727

Column percent*

Albumin

 1 (30.0–39.0)

30.2

25.7

26.0

23.4

26.3

 2 (39.1–40.9)

21.2

24.6

20.3

23.9

22.6

 3 (41.0–42.2)

22.9

26.7

31.6

20.1

25.3

 4 (42.3–50.3)

22.9

22.5

21.5

32.1

24.8

Creatinine

 1 (42–58)

30.2

27.8

26.0

20.1

26.0

 2 (59–64)

22.3

24.6

24.3

21.2

23.1

 3 (65–71)

28.5

24.6

23.2

24.5

25.2

 4 (72–130)

16.2

22.5

26.0

33.7

24.6

Phosphate

 1 (0.66–1.07)

29.6

21.4

24.9

23.9

24.9

 2 (1.08–1.19)

29.6

26.7

24.9

19.0

25.0

 3 (1.20–1.32)

23.5

20.3

28.8

24.5

24.2

 4 (1.33–2.00)

14.5

31.0

20.9

32.1

24.8

PTH

 1 (0.38–2.63)

22.3

17.6

26.0

33.7

24.9

 2 (2.64–3.55)

18.4

27.3

29.9

22.3

24.5

 3 (3.56–4.89)

23.5

28.3

21.5

25.0

24.6

 4 (4.90–30.60)

34.1

25.1

22.6

18.5

25.0

Calcium

 1 (2.18–2.34)

35.8

26.2

22.6

24.5

27.2

 2 (2.35–2.38)

19.6

24.6

23.2

17.4

21.2

 3 (2.39–2.44)

26.8

23.5

27.7

26.1

26.0

 4 (2.45–2.77)

15.1

24.6

26.0

32.1

24.5

Vitamin D– dietary

 1 (0.83–7.19)

30.2

16.6

15.8

17.4

19.9

 2 (2.67–10.17)

21.8

21.4

16.9

20.1

20.1

 3 (2.66–11.86)

15.6

25.1

21.5

17.4

19.9

 4 (3.54–12.57)

19.0

17.1

21.5

22.8

20.1

 5 (5.14–22.83)

13.4

19.8

24.3

22.3

19.9

Calcium– dietary

 1 (275.8–1203.8)

21.8

19.3

16.9

21.7

19.9

 2 (435.5–1712.1)

19.0

23.0

19.2

19.0

20.1

 3 (460.7–1669.4)

17.3

18.7

23.7

20.1

19.9

 4 (636.6–2399.4)

21.2

16.6

22.6

20.1

20.1

 5 (779.5–2791.5)

20.7

22.5

17.5

19.0

19.9

Vitamin D–total**

 1 (0.83–9.31)

31.8

16.0

16.9

15.2

19.9

 2 (2.66–11.86)

20.7

25.7

12.4

21.2

20.1

 3 (3.97–12.57)

18.4

18.2

23.2

20.1

19.9

 4 (4.84–16.55)

12.8

20.9

24.3

22.3

20.1

 5 (6.47–37.01)

16.2

19.3

23.2

21.2

19.9

Calcium–total**

 1 (275.8–1203.8)

22.9

18.7

15.8

22.3

19.9

 2 (435.5–1712.1)

17.9

23.0

23.2

16.3

20.1

 3 (532.6–2089.9)

18.4

19.8

20.9

20.7

19.9

 4 (723.5–2399.4)

22.3

17.1

19.8

21.2

20.1

 5 (782.7–2986.8)

18.4

21.4

20.3

19.6

19.9

* Due to missing values, percentages do not always add up to 100%. ** Intake from diet and supplements.

Table 5

Mean serum vitamin D levels in relation to biochemical parameters and dietary intake

Factor

No.

Mean (95% CI)

T–test (p–value*)

ANOVA (p–value)

Albumin

 1

191

87.0 (82.5–91.6)

Ref.

 2

164

91.2 (86.4–95.9)

0.344

 3

184

88.7 (84.1–93.3)

0.730

 4

180

91.7 (87.0–96.4)

0.058

0.076

Creatinine

 1

189

88.4 (84.0–92.9)

Ref.

 2

168

88.2 (83.5–92.8)

0.337

 3

183

87.1 (82.2–91.9)

0.581

 4

179

94.5 (89.8–99.2)

0.001

0.003

Phosphate

 1

181

89.8 (84.3–95.3)

Ref.

 2

182

83.5 (79.3–87.8)

0.177

 3

176

91.3 (86.7–95.8)

0.308

 4

180

93.5 (89.1–97.8)

0.012

<0.001

PTH

 1

181

95.3 (90.3–100.3)

Ref.

 2

178

89.7 (85.5–93.8)

0.035

 3

179

89.0 (84.4–93.6)

0.029

 4

182

84.5 (79.7–89.3)

<0.001

0.002

Calcium

 1

198

86.6 (82.1–91.1)

Ref.

 2

154

85.7 (81.0–90.3)

0.425

 3

189

90.9 (86.1–95.8)

0.067

 4

178

93.8 (89.2–98.3)

<0.001

0.001

Vitamin D–dietary

 1

145

81.1 (76.5 – 85.6)

Ref.

 2

146

86.7 (82.3 – 91.1)

0.08

 3

145

88.3 (84.1 – 92.6)

0.02

 4

146

92.1 (87.4 – 96.7)

0.001

 5

145

93.1 (88.9 – 97.4)

<0.001

0.001

Calcium–dietary

 1

145

87.3 (82.7 – 91.9)

Ref.

 2

146

88.2 (83.8 – 92.6)

0.79

 3

145

90.1 (85.7 – 94.6)

0.39

 4

146

88.0 (83.4 – 92.7)

0.83

 5

145

87.6 (83.4 – 91.9)

0.92

0.92

Vitamin D–total**

 1

145

79.9 (75.3 – 84.6)

Ref.

 2

146

86.0 (81.8 – 90.2)

0.06

 3

145

90.9 (86.2 – 95.7)

0.001

 4

146

93.5 (89.2 – 97.8)

<0.001

 5

145

90.9 (86.7 – 95.0)

0.001

<0.001

Calcium–total**

 1

145

87.6 (82.8 – 92.3)

Ref.

 2

146

87.4 (83.2 – 91.7)

0.97

 3

145

89.4 (84.8 – 94.0)

0.59

 4

146

88.2 (83.6 – 92.8)

0.85

 5

145

88.8 (84.7 – 92.9)

0.70

0.97

* Compared to reference (p-value). ** Intake from diet and supplements.

Table 6

Crude and adjusted odds ratios (OR) for high (> 75 nmol/L) vs . low (≤75 nmol/L) vitamin D levels, and regression coefficients (βi) from multiple regression analysis, in relation to biochemical parameters and dietary intake

Factor

Low (n)

High (n)

Crude OR (95% CI)

Adjusted*OR (95% CI)

βi (95% CI)

Adjusted* βi \(95% CI)

Albumin

 1

68

123

1.00

1.00

Baseline

Baseline

 2

50

114

1.26 (0.81–1.97)

1.15 (0.72– 1.83)

2.66 (–3.02 to 8.34)

1.55 (–3.92 to 7.02)

 3

55

129

1.30 (0.84–2.00)

1.22 (0.78– 1.92)

0.94 (–4.57 to 6.45)

0.18 (–5.13 to 5.48)

 4

56

124

1.22 (0.79–1.89)

1.27 (0.81– 2.00)

5.59 (0.05 to 11.13)

6.73 (1.39 to 12.1)

Creatinine

 1

66

123

1.00

1.00

Baseline

Baseline

 2

55

113

1.10 (0.71– 1.71)

1.07 (0.68– 1.68)

2.40 (–3.23 to 8.02)

2.47 (–2.93 to 7.86)

 3

69

114

0.89 (0.58–1.35)

0.84 (0.54– 1.30)

1.61 (–3.89 to 7.11)

1.38 (–3.90 to 6.66)

 4

39

140

1.93 (1.21– 3.06)

1.70 (1.05– 2.76)

9.11 (3.58 to 14.6)

6.97 (1.57 to 12.4)

Phosphate

 1

62

119

1.00

1.00

Baseline

Baseline

 2

69

113

0.85 (0.56–1.31)

0.75 (0.48– 1.18)

−3.79 (–9.34 to 1.76)

−4.71 (–10.0 to 0.58)

 3

54

122

1.18 (0.76–1.83)

1.12 (0.71– 1.78)

3.04 (–2.56 to 8.64)

2.81 (–2.54 to 8.16)

 4

44

136

1.61 (1.02–2.55)

1.54 (0.96– 2.48)

7.33 (1.77 to 12.9)

6.93 (1.63 to 12.2)

PTH

 1

51

130

1.00

1.00

Baseline

Baseline

 2

45

133

1.16 (0.73–1.85)

1.26 (0.77– 2.05)

−5.83 (–11.4 to –0.23)

−4.76 (–10.1 to 0.62)

 3

56

123

0.86 (0.55–1.36)

0.83 (0.52– 1.32)

−6.28 (–11.9 to –0.70)

−6.71 (–12.1 to –1.34)

 4

77

105

0.54 (0.35–0.83)

0.59 (0.37– 0.93)

−11.8 (–17.3 to –6.22)

−9.96 (–15.3 to –4.61)

Calcium

 1

80

118

1.00

1.00

Baseline

Baseline

 2

47

107

1.55 (0.99–2.41)

1.66 (1.04 –2.64)

2.19 (–3.50 to 7.88)

2.80 (–2.63 to 8.24)

 3

57

132

1.57 (1.03–2.39)

1.64 (1.05– 2.54)

5.10 (–0.29 to 10.5)

5.79 (0.63 to 11.0)

 4

45

133

2.00 (1.29–3.12)

2.18 (1.37– 3.47)

10.2 (4.78 to 15.7)

11.1 (5.79 to 16.3)

Vitamin D–dietary

 1

68

77

1.00

1.00

Baseline

Baseline

 2

51

95

1.65 (1.03– 2.64)

1.70 (1.04– 2.78)

5.64 (–0.57 to 11.9)

5.35 (–0.64 to 11.3)

 3

36

109

2.67 (1.63– 4.40)

2.92 (1.74– 4.91)

7.29 (1.07 to 13.5)

7.50 (1.50 to 13.5)

 4

41

105

2.26 (1.39–3.68)

2.52 (1.51– 4.19)

11.0 (4.82 to 17.2)

11.5 (5.47 to 17.5)

 5

38

107

2.28 (1.52–.07)

2.68 (1.58– 4.57)

12.1 (5.86 to 18.3)

11.8 (5.58 to 17.9)

Calcium–dietary

 1

53

92

1.00

1.00

Baseline

Baseline

 2

48

98

1.18 (0.73–1.91)

1.20 (0.73– 1.99)

0.87 (–5.41 to 7.16)

0.90 (–5.16 to 6.95)

 3

39

106

1.57 (0.95–2.58)

1.63 (0.97– 2.73)

2.79 (–3.51 to 9.08)

3.08 (–2.98 to 9.13)

 4

46

100

1.25 (0.77–2.04)

1.36 (0.82– 2.27)

0.71 (–5.58 to 7.00)

1.26 (–4.81 to 7.34)

 5

48

97

1.16 (0.72–1.89)

1.23 (0.74– 2.03)

0.30 (–6.00 to 6.60)

0.67 (–5.40 to 6.74)

Vitamin D–total**

 1

70

75

1.00

1.00

Baseline

Baseline

 2

46

100

2.03 (1.26–3.27)

2.05 (1.25– 3.38)

6.08 (–0.12 to 12.3)

5.63 (–0.31 to 11.6)

 3

39

106

2.54 (1.55–4.14)

3.01 (1.79– 5.05)

11.0 (4.80 to 17.2)

12.1 (6.09 to 18.0)

 4

40

106

2.47 (1.52–4.03)

2.96 (1.76– 4.99)

13.5 (7.36 to 19.7)

14.8 (8.81 to 20.8)

 5

39

106

2.54 (1.55– 4.14)

2.84 (1.69– 4.78)

10.9 (4.72 to 17.1)

11.5 (5.50 to 17.5)

Calcium–total**

 1

55

90

1.00

1.00

Baseline

Baseline

 2

46

100

1.33 (0.82–2.16)

1.36 (0.82– 2.26)

−0.13 (–6.42 to 6.15)

−0.15 (–6.19 to 5.90)

 3

41

104

1.55 (0.95–2.54)

1.63 (0.97– 2.71)

1.82 (–4.48 to 8.12)

2.46 (–3.61 to 8.53)

 4

49

97

1.21 (0.75–1.96)

1.34 (0.81– 2.22)

0.63 (–5.65 to 6.92)

1.68 (–4.39 to 7.75)

 5

43

102

1.45 (0.89–2.37)

1.52 (0.91– 2.52)

1.22 (–5.07 to 7.52)

1.43 (–4.63 to 7.50)

* Adjusted for age, season and time in freezer for all factors in the table. ** Intake from diet and supplements.

Dietary intake

High serum concentrations of 25OHD3 were associated with a high intake of vitamin D, Table 4. This finding was confirmed comparing 25OHD3 levels in different categories of vitamin D intake, Table 5, and in both the dichotomised and continuous analysis, Table 6. The use of dietary intake of vitamin D from the diet alone, or from diet and supplements, showed similar results. Contrary to this, there was no statistically significant association between intake of Calcium and 25OHD3 levels, Tables 4, 5, and 6.

Discussion

This cross-sectional study including 727 females found that serum levels of 25OHD3 are positively associated with age, oral contraceptive use, moderate alcohol consumption, and blood collection during summer / autumn, a high dietary intake of vitamin D and serum concentrations of creatinine, phosphate and calcium. Serum levels of 25OHD3 were inversely associated with obesity, being born outside Sweden and with serum levels of PTH.

A positive association between serum levels of 25OHD3 and advanced age has previously also been reported by Moan et al. [32]. However, others have found vitamin D deficiency to be more prevalent among elderly people [33], which could be caused by poor production in the skin [34], decreased intestinal absorption [35], and/or impaired renal function [36]. A reason for the difference between our and most previous studies may be that the current study only included females up until the age of 72 years, and deficiency related to high age may not be apparent until later. Another possible reason to the results seen in the present study may be that older women in this cohort consume relatively more vitamin D. We found no association between menopausal status and serum levels of 25OHD3, although postmenopausal women had slightly higher levels.

A positive association between the use of OC and serum level of 25OHD3 was found in the present study and there was also a tendency for a positive association between MHT and high serum levels of 25OHD3. This is in line with several previous studies on 25OHD3 in relation to OC and other exogenous oestrogens [3741]. A potential explanation may be that oestrogen increases the levels of 25OHD3-binding proteins [42].

We found no strong association between socioeconomic status and serum levels of 25OHD3, although serum levels of 25OHD3 were slightly higher in women with a non-manual vs. a manual employment.

The present study shows a positive association between high serum levels of 25OHD3 and moderate alcohol consumption, as opposed to high alcohol consumption and zero consumption. This observation is in accordance with a recent study finding that moderate alcohol consumers have a relatively high intake of vitamin D as compared to zero-consumers [43]. Differences with regard to dietary intake may be an explanation behind the low vitamin D levels in zero-consumers, for example vegetarians may have a relatively low intake of vitamin D [44] and it is possible to hypothesize that they consume less alcohol as compared to other groups. In general, the concentration of vitamin D has shown to be reduced among high consumers of alcohol. This could be due to a variation in the dietary intake of vitamin D during different drinking periods with marked reduction during hard-drinking weeks [45].

Another factor closely related to alcohol consumption is smoking, but in the present study there was no association between smoking habits and serum levels of 25OHD3, and smoking is not likely to explain the association seen in the present analysis.

We found that obesity was associated with relatively low serum levels of 25OHD3 and this is similar with several other studies [4649]. A potential explanation is that poor dietary habits are related to increased BMI [50], and this may also lead to a lower intake of vitamin D in obese women as shown by Tidwell et al. [51]. Adipose tissue contains vitamin D receptors which hypothetically could lead to a sequestration of serum levels of 25OHD3 in obese individuals [52]. Moreover, obesity is more prevalent among people with lower education level [53], and this may be an indirect explanation for the results in this study as women with a manual vs. non-manual work had slightly lower serum levels of 25OHD3. However, educational levels per se as measured in the current study were not associated with serum levels of 25OHD3.

Women born abroad had lower serum levels of 25OHD3 in our report. Different geographical locations [54] and ethnic backgrounds [55, 56] have, indeed, been correlated to the vitamin D level. Possible explanations could be related to cultural tradition with traditional dress style other than western dress [57], colour of the skin because darker skin has less capacity to make vitamin D from sunlight [58, 59], or a genetic impact on serum vitamin D status probably through the skin synthesis of vitamin D [60]. Another explaining factor is variation in vitamin D intake between different ethnic groups as vitamin D intake is comparatively high in Scandinavian countries [61]. In this group ultraviolet light may not be the only key in the prevention of different condition but the role of dietary vitamin D intake, supplement vitamin D and calcium come into play [6264]. In our study, the highest levels of serum 25OHD3 were seen during the summer and in the autumn and these are in agreement with previous studies [6569]. This is also to be expected as during this season the solar UV radiation reaches adequate levels to have a sufficient vitamin D production (ibid).

We found a positive association between serum levels of 25OHD3, creatinine, phosphate and calcium, and an inverse association with PTH. This has also been seen in other studies [70], and follows the à priori hypothesis given the physiology for vitamin D metabolism. A sufficient concentration of vitamin D [71], is essential for bone mineralization and bone turnover [72] and to maintain an optimal vitamin D level requires a close physiological cooperation between vitamin D, calcium and PTH levels [73, 74].

The positive association between intake of vitamin D and levels of 25OHD3 in this study was expected and has also been reported by others [75, 76]. There was no strong association between calcium intake and levels of 25OHD3 and this has been reported by others [77].

Our study has several methodological strengths. Serum samples were collected in a standardized way and stored at −80°C, laboratory methods had low CVs, and there were a relatively large number of subjects, i.e., good statistical power. The inclusion of both life-style factors and biochemical parameters are additional strengths. However, some methodological questions need to be discussed. It may be questioned whether it is appropriate to use a single determination for levels of vitamin D. However, it is reassuring that a recent cohort study that measured 25OHD3 at 2 times, 3 years apart, found a high correlation between levels. Information on life-style and diet was collected using various questionnaires and this may lead to misclassification. However, validity and reproducibility is high for both the socioeconomic questionnaire and the dietary assessment method [23, 25].

The results were adjusted for age, season and storage time, and these factors ought not to have confounded the results. It was considered appropriate to adjust only for these factors, as we wanted to identify groups with low vs. high vitamin D levels, rather than to determine what factors that affected vitamin D levels the most. Concerning dietary factors, the residual method was used, which takes into account differences with regard to total energy intake, i.e. the amount of the total dietary intake.

A valid question is whether the associations observed in this cohort can be representative of the whole population. Although in this study only 40% of the populations have participated and as we have no information about exposure to the studied risk factors in women outside this cohort, observed means and the prevalence for studied factors may not be applicable to all age groups or to the general population. However, as there was a wide distribution of 25OHD3 and other determinants, it was possible to make internal comparisons between subjects. We consider that our estimations of odds ratios were less sensitive to a potential selection bias.

Conclusions

The present population-based cohort study including 727 females found a positive association between serum levels of 25OHD3 and age, oral contraceptive use, moderate alcohol consumption, blood collection during summer/ autumn, creatinine, phosphate, calcium, and a high intake of vitamin D. Low vitamin D levels were associated with obesity, being born outside Sweden and high PTH levels. The study may have implications e. g. for dietary recommendations. However, the analysis is a cross-sectional study and it is difficult to suggest lifestyle recommendations as cause- effect relationships are not clear.

Declarations

Acknowledgement

Financial support was received from The Swedish Research Council (K2007-69X- 20487-01-3), The Gunnar Nilsson Cancer Foundation, The Ernhold Lundström Foundation, The Einar and Inga Nilsson Foundation, The Malmö University Hospital Cancer Research Fund, The Malmö University Hospital Funds and Donations, The Crafoord Foundation, The Region of Skåne, and The Mossfelt Foundation. Ethical approval was given for all projects included in the article (LU 51–90, LU 639–03, Dnr 652/2005 and Dnr 23/2007).

Authors’ Affiliations

(1)
Department of Surgery, Ystad Hospital
(2)
Department of Clinical Sciences Malmö Surgery, Lund University
(3)
Department of Surgery, Skåne University Hospital
(4)
Department of Laboratory Medicine, Section for clinical chemistry, Lund University
(5)
Department of Clinical Sciences Malmö Nutritional Epidemiology, Lund University
(6)
Department of Plastic Surgery, Skåne University Hospital

References

  1. Forman JP, Curhan GC, Taylor EN: Plasma 25-hydroxyvitamin D levels and risk of incident hypertension among young women. Hypertension. 2008, 52 (5): 828-832. 10.1161/HYPERTENSIONAHA.108.117630.View ArticlePubMedPubMed CentralGoogle Scholar
  2. Lee JH, Gadi R, Spertus JA, Tang F, O'Keefe JH: Prevalence of vitamin D deficiency in patients with acute myocardial infarction. Am J Cardiol. 2011, 107 (11): 1636-1638. 10.1016/j.amjcard.2011.01.048.View ArticlePubMedPubMed CentralGoogle Scholar
  3. Pilz S, Marz W, Wellnitz B, Seelhorst U, Fahrleitner-Pammer A, Dimai HP, Boehm BO, Dobnig H: Association of vitamin D deficiency with heart failure and sudden cardiac death in a large cross-sectional study of patients referred for coronary angiography. J Clin Endocrinol Metab. 2008, 93 (10): 3927-3935. 10.1210/jc.2008-0784.View ArticlePubMedGoogle Scholar
  4. Jorde R, Sneve M, Figenschau Y, Svartberg J, Waterloo K: Effects of vitamin D supplementation on symptoms of depression in overweight and obese subjects: randomized double blind trial. J Intern Med. 2008, 264 (6): 599-609. 10.1111/j.1365-2796.2008.02008.x.View ArticlePubMedGoogle Scholar
  5. Pittas AG, Dawson-Hughes B: Vitamin D and diabetes. J Steroid Biochem Mol Biol. 2010, 121 (1–2): 425-429.View ArticlePubMedPubMed CentralGoogle Scholar
  6. Foss YJ: Vitamin D deficiency is the cause of common obesity. Med Hypotheses. 2009, 72 (3): 314-321. 10.1016/j.mehy.2008.10.005.View ArticlePubMedGoogle Scholar
  7. Bahlous A, Farjallah N, Bouzid K, Klouz A, Mohsni A, Sahli H, Lakhal M, Sallami S, Abdelmoula J: Hypovitaminosis D in Tunisian osteoporotic postmenopausal women and the relationship with bone fractures. Tunis Med. 2009, 87 (3): 188-190.PubMedGoogle Scholar
  8. Chen P, Hu P, Xie D, Qin Y, Wang F, Wang H: Meta-analysis of vitamin D, calcium and the prevention of breast cancer. Breast Cancer Res Treat. 2010, 121 (2): 469-477. 10.1007/s10549-009-0593-9.View ArticlePubMedGoogle Scholar
  9. Yin L, Grandi N, Raum E, Haug U, Arndt V, Brenner H: Meta-analysis: longitudinal studies of serum vitamin D and colorectal cancer risk. Aliment Pharmacol Ther. 2009, 30 (2): 113-125. 10.1111/j.1365-2036.2009.04022.x.View ArticlePubMedGoogle Scholar
  10. Burgaz A, Akesson A, Michaelsson K, Wolk A: 25-hydroxyvitamin D accumulation during summer in elderly women at latitude 60 degrees N. J Intern Med. 2009, 266 (5): 476-483. 10.1111/j.1365-2796.2009.02125.x.View ArticlePubMedGoogle Scholar
  11. Lips P: Worldwide status of vitamin D nutrition. J Steroid Biochem Mol Biol. 2010, 121 (1–2): 297-300.View ArticlePubMedGoogle Scholar
  12. Mygind A, Traulsen JM, Norgaard LS, Bissell P: The ambiguity of ethnicity as risk factor of vitamin D deficiency–a case study of Danish vitamin D policy documents. Health Policy. 2011, 102 (1): 56-63. 10.1016/j.healthpol.2011.05.012.View ArticlePubMedGoogle Scholar
  13. Benitez-Aguirre PZ, Wood NJ, Biesheuvel C, Moreira C, Munns CF: The natural history of vitamin D deficiency in African refugees living in Sydney. Med J Aust. 2009, 190 (8): 426-428.PubMedGoogle Scholar
  14. Greene-Finestone LS, Berger C, de Groh M, Hanley DA, Hidiroglou N, Sarafin K, Poliquin S, Krieger J, Richards JB, Goltzman D: 25-Hydroxyvitamin D in Canadian adults: biological, environmental, and behavioral correlates. Osteoporosis international: a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2011, 22 (5): 1389-1399. 10.1007/s00198-010-1362-7.View ArticleGoogle Scholar
  15. Holick MF: Vitamin D: importance in the prevention of cancers, type 1 diabetes, heart disease, and osteoporosis. Am J Clin Nutr. 2004, 79 (3): 362-371.PubMedGoogle Scholar
  16. Daly RM, Gagnon C, Lu ZX, Magliano DJ, Dunstan DW, Sikaris KA, Zimmet PZ, Ebeling PR, Shaw JE: Prevalence of vitamin D deficiency and its determinants in Australian adults aged 25 years and older: A national, population-based study. Clin Endocrinol (Oxf). 2012, 77 (1): 26-35. 10.1111/j.1365-2265.2011.04320.x.View ArticleGoogle Scholar
  17. Jaaskelainen T, Knekt P, Marniemi J, Sares-Jaske L, Mannisto S, Heliovaara M, Jarvinen R: Vitamin D status is associated with sociodemographic factors, lifestyle and metabolic health. Eur J Nutr. 2013, 52 (2): 513-25. 10.1007/s00394-012-0354-0.View ArticlePubMedGoogle Scholar
  18. Weaver SP, Passmore C, Collins B, Fung E: Vitamin D, sunlight exposure, and bone density in elderly African American females of low socioeconomic status. Fam Med. 2010, 42 (1): 47-51.PubMedGoogle Scholar
  19. Bjorneboe GA, Johnsen J, Bjorneboe A, Morland J, Drevon CA: Effect of heavy alcohol consumption on serum concentrations of fat-soluble vitamins and selenium. Alcohol Alcohol Suppl. 1987, 1: 533-537.PubMedGoogle Scholar
  20. Sutton AL, MacDonald PN: Vitamin D: more than a "bone-a-fide" hormone. Mol Endocrinol. 2003, 17 (5): 777-791. 10.1210/me.2002-0363.View ArticlePubMedGoogle Scholar
  21. Berglund G, Elmstahl S, Janzon L, Larsson SA: The Malmo diet and cancer study, design and feasibility. J Intern Med. 1993, 233 (1): 45-51. 10.1111/j.1365-2796.1993.tb00647.x.View ArticlePubMedGoogle Scholar
  22. Almquist M, Bondeson AG, Bondeson L, Malm J, Manjer J: Serum levels of vitamin D, PTH and calcium and breast cancer risk-a prospective nested case–control study. International journal of cancer Journal international du cancer. 2010, 127 (9): 2159-2168. 10.1002/ijc.25215.View ArticlePubMedGoogle Scholar
  23. Manjer J, Elmstahl S, Janzon L, Berglund G: Invitation to a population-based cohort study: differences between subjects recruited using various strategies. Scand J Public Health. 2002, 30 (2): 103-112.View ArticlePubMedGoogle Scholar
  24. Almquist M, Manjer J, Bondeson L, Bondeson AG: Serum calcium and breast cancer risk: results from a prospective cohort study of 7,847 women. Cancer Causes Control. 2007, 18 (6): 595-602. 10.1007/s10552-007-9001-0.View ArticlePubMedGoogle Scholar
  25. Riboli E, Elmstahl S, Saracci R, Gullberg B, Lindgarde F: The Malmo Food Study: validity of two dietary assessment methods for measuring nutrient intake. Int J Epidemiol. 1997, 26 (Suppl 1): S161-S173.View ArticlePubMedGoogle Scholar
  26. Mattisson I, Wirfalt E, Gullberg B, Berglund G: Fat intake is more strongly associated with lifestyle factors than with socio-economic characteristics, regardless of energy adjustment approach. Eur J Clin Nutr. 2001, 55 (6): 452-461. 10.1038/sj.ejcn.1601205.View ArticlePubMedGoogle Scholar
  27. Wallström P: Diet, lifestyle, antioxidants, and biomarkers of cancer risk. An epidemiological report from the Malmö Diet and Cancer cohort. Thesis. 2002, Malmö: Lund UniversityGoogle Scholar
  28. Pinnell AE, Northam BE: New automated dye-binding method for serum albumin determination with bromcresol purple. Clin Chem. 1978, 24 (1): 80-86.PubMedGoogle Scholar
  29. Anker P, Wieland E, Ammann D, Dohner RE, Asper R, Simon W: Neutral carrier based ion-selective electrode for the determination of total calcium in blood serum. Anal Chem. 1981, 53 (13): 1970-1974. 10.1021/ac00236a005.View ArticlePubMedGoogle Scholar
  30. Vieth R, Bischoff-Ferrari H, Boucher BJ, Dawson-Hughes B, Garland CF, Heaney RP, Holick MF, Hollis BW, Lamberg-Allardt C, McGrath JJ, et al: The urgent need to recommend an intake of vitamin D that is effective. Am J Clin Nutr. 2007, 85 (3): 649-650.PubMedGoogle Scholar
  31. Chesney RW, Rosen JF, Hamstra AJ, Smith C, Mahaffey K, DeLuca HF: Absence of seasonal variation in serum concentrations of 1,25-dihydroxyvitamin D despite a rise in 25-hydroxyvitamin D in summer. J Clin Endocrinol Metab. 1981, 53 (1): 139-142. 10.1210/jcem-53-1-139.View ArticlePubMedGoogle Scholar
  32. Moan J, Lagunova Z, Lindberg FA, Porojnicu AC: Seasonal variation of 1,25-dihydroxyvitamin D and its association with body mass index and age. J Steroid Biochem Mol Biol. 2009, 113 (3–5): 217-221.View ArticlePubMedGoogle Scholar
  33. Nakamura K, Nashimoto M, Hori Y, Yamamoto M: Serum 25-hydroxyvitamin D concentrations and related dietary factors in peri- and postmenopausal Japanese women. Am J Clin Nutr. 2000, 71 (5): 1161-1165.PubMedGoogle Scholar
  34. Tsiaras WG, Weinstock MA: Factors influencing vitamin D status. Acta Derm Venereol. 2011, 91 (2): 115-124.View ArticlePubMedGoogle Scholar
  35. Bhutto A, Morley JE: The clinical significance of gastrointestinal changes with aging. Curr Opin Clin Nutr Metab Care. 2008, 11 (5): 651-660. 10.1097/MCO.0b013e32830b5d37.View ArticlePubMedGoogle Scholar
  36. Vieth R, Ladak Y, Walfish PG: Age-related changes in the 25-hydroxyvitamin D versus parathyroid hormone relationship suggest a different reason why older adults require more vitamin D. J Clin Endocrinol Metab. 2003, 88 (1): 185-191. 10.1210/jc.2002-021064.View ArticlePubMedGoogle Scholar
  37. Sowers MR, Wallace RB, Hollis BW, Lemke JH: Parameters related to 25-OH-D levels in a population-based study of women. Am J Clin Nutr. 1986, 43 (4): 621-628.PubMedGoogle Scholar
  38. van Hoof HJ, van der Mooren MJ, Swinkels LM, Rolland R, Benraad TJ: Hormone replacement therapy increases serum 1,25-dihydroxyvitamin D: A 2-year prospective study. Calcif Tissue Int. 1994, 55 (6): 417-419. 10.1007/BF00298554.View ArticlePubMedGoogle Scholar
  39. Thane CW, Bates CJ, Prentice A: Oral contraceptives and nutritional status in adolescent British girls. Nutr Res. 2002, 22 (4): 449-462. 10.1016/S0271-5317(02)00356-1.View ArticleGoogle Scholar
  40. Nesby-O'Dell S, Scanlon KS, Cogswell ME, Gillespie C, Hollis BW, Looker AC, Allen C, Doughertly C, Gunter EW, Bowman BA: Hypovitaminosis D prevalence and determinants among African American and white women of reproductive age: third National Health and Nutrition Examination Survey, 1988–1994. Am J Clin Nutr. 2002, 76 (1): 187-192.PubMedGoogle Scholar
  41. Gagnon C, Baillargeon JP, Desmarais G, Fink GD: Prevalence and predictors of vitamin D insufficiency in women of reproductive age living in northern latitude. Eur J Endocrinol. 2010, 163 (5): 819-824. 10.1530/EJE-10-0441.View ArticlePubMedGoogle Scholar
  42. Rejnmark L, Lauridsen AL, Brot C, Vestergaard P, Heickendorff L, Nexo E, Mosekilde L: Vitamin D and its binding protein Gc: long-term variability in peri- and postmenopausal women with and without hormone replacement therapy. Scand J Clin Lab Invest. 2006, 66 (3): 227-238. 10.1080/00365510600570623.View ArticlePubMedGoogle Scholar
  43. Fawehinmi TO, Ilomaki J, Voutilainen S, Kauhanen J: Alcohol consumption and dietary patterns: the FinDrink study. PLoS One. 2012, 7 (6): e38607-10.1371/journal.pone.0038607.View ArticlePubMedPubMed CentralGoogle Scholar
  44. Crowe FL, Steur M, Allen NE, Appleby PN, Travis RC, Key TJ: Plasma concentrations of 25-hydroxyvitamin D in meat eaters, fish eaters, vegetarians and vegans: results from the EPIC-Oxford study. Public Health Nutr. 2011, 14 (2): 340-346. 10.1017/S1368980010002454.View ArticlePubMedGoogle Scholar
  45. Bjorneboe GE, Johnsen J, Bjorneboe A, Rousseau B, Pedersen JI, Norum KR, Morland J, Drevon CA: Effect of alcohol consumption on serum concentration of 25-hydroxyvitamin D3, retinol, and retinol-binding protein. Am J Clin Nutr. 1986, 44 (5): 678-682.PubMedGoogle Scholar
  46. Wortsman J, Matsuoka LY, Chen TC, Lu Z, Holick MF: Decreased bioavailability of vitamin D in obesity. Am J Clin Nutr. 2000, 72 (3): 690-693.PubMedGoogle Scholar
  47. Pasco JA, Henry MJ, Nicholson GC, Brennan SL, Kotowicz MA: Behavioural and physical characteristics associated with vitamin D status in women. Bone. 2009, 44 (6): 1085-1091. 10.1016/j.bone.2009.02.020.View ArticlePubMedGoogle Scholar
  48. Lagunova Z, Porojnicu AC, Lindberg F, Hexeberg S, Moan J: The dependency of vitamin D status on body mass index, gender, age and season. Anticancer Res. 2009, 29 (9): 3713-3720.PubMedGoogle Scholar
  49. Thuesen B, Husemoen L, Fenger M, Jakobsen J, Schwarz P, Toft U, Ovesen L, Jorgensen T, Linneberg A: Determinants of vitamin D status in a general population of Danish adults. Bone. 2012, 50 (3): 605-610. 10.1016/j.bone.2011.12.016.View ArticlePubMedGoogle Scholar
  50. Sonestedt E, Wirfalt E, Gullberg B, Berglund G: Past food habit change is related to obesity, lifestyle and socio-economic factors in the Malmo Diet and Cancer Cohort. Public Health Nutr. 2005, 8 (7): 876-885.View ArticlePubMedGoogle Scholar
  51. Tidwell DK, Valliant MW: Higher amounts of body fat are associated with inadequate intakes of calcium and vitamin D in African American women. Nutr Res. 2011, 31 (7): 527-536. 10.1016/j.nutres.2011.06.005.View ArticlePubMedGoogle Scholar
  52. Earthman CP, Beckman LM, Masodkar K, Sibley SD: The link between obesity and low circulating 25-hydroxyvitamin D concentrations: considerations and implications. Int J Obes (Lond). 2012, 36 (3): 387-96. 10.1038/ijo.2011.119.View ArticleGoogle Scholar
  53. Hermann S, Rohrmann S, Linseisen J, May AM, Kunst A, Besson H, Romaguera D, Travier N, Tormo MJ, Molina E, et al: The association of education with body mass index and waist circumference in the EPIC-PANACEA study. BMC Publ Health. 2011, 11: 169-10.1186/1471-2458-11-169.View ArticleGoogle Scholar
  54. Macdonald HM, Mavroeidi A, Fraser WD, Darling AL, Black AJ, Aucott L, O'Neill F, Hart K, Berry JL, Lanham-New SA, et al: Sunlight and dietary contributions to the seasonal vitamin D status of cohorts of healthy postmenopausal women living at northerly latitudes: a major cause for concern?. Osteoporosis international: a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2011, 22 (9): 2461-2472. 10.1007/s00198-010-1467-z.View ArticleGoogle Scholar
  55. Kaykhaei MA, Hashemi M, Narouie B, Shikhzadeh A, Rashidi H, Moulaei N, Ghavami S: High prevalence of vitamin D deficiency in Zahedan, southeast Iran. Ann Nutr Metab. 2011, 58 (1): 37-41. 10.1159/000323749.View ArticlePubMedGoogle Scholar
  56. Hagenau T, Vest R, Gissel TN, Poulsen CS, Erlandsen M, Mosekilde L, Vestergaard P: Global vitamin D levels in relation to age, gender, skin pigmentation and latitude: an ecologic meta-regression analysis. Osteoporosis international: a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2009, 20 (1): 133-140. 10.1007/s00198-008-0626-y.View ArticleGoogle Scholar
  57. Batieha A, Khader Y, Jaddou H, Hyassat D, Batieha Z, Khateeb M, Belbisi A, Ajlouni K: Vitamin D status in Jordan: dress style and gender discrepancies. Ann Nutr Metab. 2011, 58 (1): 10-18. 10.1159/000323097.View ArticlePubMedGoogle Scholar
  58. Johnson MA, Davey A, Park S, Hausman DB, Poon LW: Age, race and season predict vitamin D status in African American and white octogenarians and centenarians. J Nutr Health Aging. 2008, 12 (10): 690-695.PubMedPubMed CentralGoogle Scholar
  59. Jacobs ET, Alberts DS, Foote JA, Green SB, Hollis BW, Yu Z, Martinez ME: Vitamin D insufficiency in southern Arizona. Am J Clin Nutr. 2008, 87 (3): 608-613.PubMedPubMed CentralGoogle Scholar
  60. Snellman G, Melhus H, Gedeborg R, Olofsson S, Wolk A, Pedersen NL, Michaelsson K: Seasonal genetic influence on serum 25-hydroxyvitamin D levels: a twin study. PLoS One. 2009, 4 (11): e7747-10.1371/journal.pone.0007747.View ArticlePubMedPubMed CentralGoogle Scholar
  61. Lips P: Vitamin D status and nutrition in Europe and Asia. J Steroid Biochem Mol Biol. 2007, 103 (3–5): 620-625.View ArticlePubMedGoogle Scholar
  62. Brock K, Huang WY, Fraser DR, Ke L, Tseng M, Stolzenberg-Solomon R, Peters U, Ahn J, Purdue M, Mason RS, et al: Low vitamin D status is associated with physical inactivity, obesity and low vitamin D intake in a large US sample of healthy middle-aged men and women. J Steroid Biochem Mol Biol. 2010, 121 (1–2): 462-466.View ArticlePubMedPubMed CentralGoogle Scholar
  63. Alissa EM, Qadi SG, Alhujaili NA, Alshehri AM, Ferns GA: Effect of diet and lifestyle factors on bone health in postmenopausal women. J Bone Miner Metab. 2011, 29 (6): 725-735. 10.1007/s00774-011-0274-8.View ArticlePubMedGoogle Scholar
  64. Dawodu A, Kochiyil J, Altaye N: Pilot study of sunlight exposure and vitamin D status in Arab women of childbearing age. East Mediterr Health J. 2011, 17 (7): 570-574.PubMedGoogle Scholar
  65. Nanri A, Foo LH, Nakamura K, Hori A, Poudel-Tandukar K, Matsushita Y, Mizoue T: Serum 25-hydroxyvitamin d concentrations and season-specific correlates in Japanese adults. J Epidemiol. 2011, 21 (5): 346-353. 10.2188/jea.JE20100161.View ArticlePubMedPubMed CentralGoogle Scholar
  66. Kashi Z, Saeedian F, Akha O, Gorgi MH, Emadi S, Zakeri H: Vitamin D deficiency prevalence in summer compared to winter in a city with high humidity and a sultry climate. Endokrynol Pol. 2011, 62 (3): 249-251.PubMedGoogle Scholar
  67. Brustad M, Edvardsen K, Wilsgaard T, Engelsen O, Aksnes L, Lund E: Seasonality of UV-radiation and vitamin D status at 69 degrees north. Photochem Photobiol Sci. 2007, 6 (8): 903-908. 10.1039/b702947k.View ArticlePubMedGoogle Scholar
  68. Sambrook PN, Cameron ID, Chen JS, Cumming RG, Durvasula S, Herrmann M, Kok C, Lord SR, Macara M, March LM, Mason RS, Seibel MJ, Wilson N, Simpson JM: Does increased sunlight exposure work as a strategy to improve vitamin D status in the elderly: a cluster randomised controlled trial. Osteoporosis international: a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2012 Feb, 23 (2): 615-24. 10.1007/s00198-011-1590-5.View ArticleGoogle Scholar
  69. Webb AR, Kift R, Durkin MT, O'Brien SJ, Vail A, Berry JL, Rhodes LE: The role of sunlight exposure in determining the vitamin D status of the U.K. white adult population. Br J Dermatol. 2010, 163 (5): 1050-1055. 10.1111/j.1365-2133.2010.09975.x.View ArticlePubMedGoogle Scholar
  70. Bates CJ, Carter GD, Mishra GD, O'Shea D, Jones J, Prentice A: In a population study, can parathyroid hormone aid the definition of adequate vitamin D status? A study of people aged 65 years and over from the British National Diet and Nutrition Survey. Osteoporosis international: a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2003, 14 (2): 152-159.Google Scholar
  71. Holick MF: Vitamin D: evolutionary, physiological and health perspectives. Curr Drug Targets. 2011, 12 (1): 4-18. 10.2174/138945011793591635.View ArticlePubMedGoogle Scholar
  72. Rejnmark L, Vestergaard P, Brot C, Mosekilde L: Increased fracture risk in normocalcemic postmenopausal women with high parathyroid hormone levels: a 16-year follow-up study. Calcif Tissue Int. 2011, 88 (3): 238-245. 10.1007/s00223-010-9454-0.View ArticlePubMedGoogle Scholar
  73. Steingrimsdottir L, Gunnarsson O, Indridason OS, Franzson L, Sigurdsson G: Relationship between serum parathyroid hormone levels, vitamin D sufficiency, and calcium intake. JAMA. 2005, 294 (18): 2336-2341. 10.1001/jama.294.18.2336.View ArticlePubMedGoogle Scholar
  74. Saliba W, Barnett O, Rennert HS, Lavi I, Rennert G: The relationship between serum 25(OH)D and parathyroid hormone levels. Am J Med. 2011, 124 (12): 1165-1170. 10.1016/j.amjmed.2011.07.009.View ArticlePubMedGoogle Scholar
  75. Kruger MC, Schollum LM, Kuhn-Sherlock B, Hestiantoro A, Wijanto P, Li-Yu J, Agdeppa I, Todd JM, Eastell R: The effect of a fortified milk drink on vitamin D status and bone turnover in post-menopausal women from South East Asia. Bone. 2010, 46 (3): 759-767. 10.1016/j.bone.2009.10.036.View ArticlePubMedGoogle Scholar
  76. Dinizulu T, Griffin D, Carey J, Mulkerrin E: Vitamin D supplementation versus combined calcium and vitamin D in older female patients - an observational study. J Nutr Health Aging. 2011, 15 (8): 605-608. 10.1007/s12603-011-0094-5.View ArticlePubMedGoogle Scholar
  77. Lowe NM, Ellahi B, Bano Q, Bangash SA, Mitra SR, Zaman M: Dietary calcium intake, vitamin D status, and bone health in postmenopausal women in rural Pakistan. J Health Popul Nutr. 2011, 29 (5): 465-470.View ArticlePubMedPubMed CentralGoogle Scholar
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