Association between dietary patterns and indices of bone mass in a sample of Mediterranean women

Nutrition 25 (2009) 165–171 www.elsevier.com/locate/nut

Applied nutritional investigation

Association between dietary patterns and indices of bone mass in a sample of Mediterranean women Meropi D. Kontogianni, Ph.D.a, Labros Melistas, M.Sc.a, Mary Yannakoulia, Ph.D.a, Ioannis Malagaris, B.Sc.a, Demosthenes B. Panagiotakos, Ph.D.a, and Nikos Yiannakouris, Ph.D.b,* b

a Department of Nutrition and Dietetics, Harokopio University, Athens, Greece Department of Home Economics and Ecology, Harokopio University, Athens, Greece

Manuscript received May 2, 2008; accepted July 28, 2008.

Abstract

Objective: A holistic dietary approach, examining the effect of dietary patterns in terms of chronic disease prevention and treatment, continuously gains more attention and may elucidate the association between diet and bone health. In the present study we examined whether adherence to a Mediterranean diet or other dietary patterns has any significant impact on indices of bone mass. Methods: Two hundred twenty adult Greek women were recruited. Lumbar spine bone mineral density and total body bone mineral content were determined by using dual x-ray absorptiometry. Food intake was assessed using 3-d food records and adherence to the Mediterranean diet was evaluated through a Mediterranean diet score. Principal components analysis was used for the identification of participants’ dietary patterns. Results: Adherence to a Mediterranean diet was not found to have any significant effect on indices of bone mass. Principal components analysis identified 10 dietary patterns explaining 80% of the variance in food intake. A pattern characterized by high consumption of fish and olive oil and low intake of red meat was positively associated with lumbar spine bone mineral density (P ⫽ 0.017) and total body bone mineral content (P ⫽ 0.048), after controlling for several confounders. Conclusion: Adherence to a Mediterranean dietary pattern was not associated with indices of bone mass in a sample of adult women, whereas adherence to a dietary pattern close to the Mediterranean diet, i.e., high consumption of fish and olive oil and low red meat intake, was positively related to bone mass, suggesting potential bone-preserving properties of this pattern throughout adult life. © 2009 Published by Elsevier Inc.

Keywords:

Bone mineral density; Dietary patterns; Fish intake; Mediterranean diet; Olive oil intake

Introduction Diet is one of the important modifiable factors for the development and maintenance of bone mass [1]. The nutrients of most obvious relevance to bone health are calcium and phosphorus because they compose roughly 80% to 90% of the mineral content of bone; protein is essential because it is incorporated into the organic matrix of bone for collagen structure upon which mineralization occurs; and other minerals, * Corresponding author. Tel.: ⫹30-210-954-9268; fax: ⫹30-210-9577050. E-mail address: [email protected] (N. Yiannakouris). 0899-9007/09/$ – see front matter © 2009 Published by Elsevier Inc. doi:10.1016/j.nut.2008.07.019

trace elements, and vitamins (e.g., vitamins D and K) are also crucial in carrying out reactions and metabolic processes in bone [2]. The most consistently followed approach thus far to examine potential relations between dietary intake and skeletal health was based on particular (or a variety of) nutrients. Although this traditional analysis has been valuable for the understanding of the effect of specific nutrients (e.g., calcium) on bone health, there is still a lot of missing information and several conceptual limitations. People consume meals consisting of several food items with a combination of nutrients; furthermore, complicated or cumulative intercorrelations and interactions between nutrients are inappropriately treated by this approach. It has therefore been suggested that a holistic

166

M. D. Kontogianni et al. / Nutrition 25 (2009) 165–171

dietary approach, which examines the effect of dietary patterns in terms of chronic disease prevention and treatment, compared with the assessment of single nutrients, foods, or food groups may be more valuable approach in studying associations between diet and biological markers [3,4]. Data from the Framingham Study [5,6] showed that participants who habitually ate a diet based on fruit, vegetables, milk, and cereals had a significantly denser bone mass than those whose diet was characterized by high consumption of salty snacks, pizza, and soda or high consumption of meat, bread, and potatoes. Okubo et al. [7] evaluated associations between dietary patterns and bone mineral density (BMD) in Japanese farmwomen and found that a “healthy” pattern, described by high intakes of green and dark yellow vegetables, mushrooms, fish and shellfish, and fruit, was positively related to BMD. Moreover, the effect of vegetarian dietary patterns on skeletal health has been studied; lacto-ovo vegetarians appear to have normal bone mass when compared with omnivores [8], whereas a more recent review concluded that the scientific findings consistently support the hypothesis that vegans do have lower BMD than their non-vegan counterparts [9]. Lin et al. [10] found that the Dietary Approaches to Stop Hypertension (DASH) diet, which is rich in fruits, vegetables, and low-fat dairies, reduced serum osteocalcin by 8 –11% and C-terminal telopeptide of type I collagen by 16 –18%, and a low sodium intake reduced calcium excretion in the DASH diet and control groups and serum osteocalcin in the DASH group. To our knowledge, the Mediterranean diet, a pattern rich in plant foods and olive oil, low in meat and dairy products, and with moderate intake of alcohol, has not been evaluated with regard to bone mass. Hence, the aim of the present study was to examine whether adherence to the Mediterranean diet or other dietary patterns has any significant impact on bone mass maintenance in a sample of adult Greek women.

Materials and methods Subjects For this study, 220 Greek women were consecutively enrolled (mean age 48 ⫾ 12 y) through an advertisement in a local magazine. After being informed of the purpose and procedures of the study, all subjects signed an informed consent form. The study protocol was approved by the ethics committee of Harokopio University. The participants were apparently healthy on physical examination. Data on general health status, medication, and smoking habits were collected using an interviewer-administered questionnaire. Twenty-four women were excluded from the present analysis because they were receiving medication that could influence bone mass (e.g., corticosteroids, ␤-blockers, diuretics), were diabetic, or were on a weight-reducing diet. None of the subjects had been exposed to hormonal replace-

ment therapy for menopause and only three received oral contraceptives. None of the participants was receiving medical treatment (e.g., calcium, vitamin D, calcitonin, bisphosphonates, anti–vitamin K agents) that could influence BMD. In the final sample, 13 women reported regular use of thyroid medication, but no other established endocrine or rheumatic disease was reported. Menstruation status was recorded; women were classified as premenopausal if they had regular menses, perimenopausal if they had irregular menses, and postmenopausal if they had ceased menstruating for at least 12 mo (Table 1). Anthropometry and bone densitometry Anthropometric and bone densitometry measurements were performed in all study participants. Body weight and height were measured using a scale and a wall-mounted stadiometer to the nearest 0.5 kg and 0.5 cm, respectively, and body mass index (BMI; kilograms per square meter) was calculated. Total body bone mineral content (TBBMC; grams) and BMD (grams per square centimeter) at the lumbar spine (L2–L4) were determined with a dual x-ray absorptiometric total body scanner (Model DPX, Lunar Corp., Madison, WI, USA; software version 4.7e). Body composition measurements were performed for all subjects by the same trained investigator. Dietary assessment Dietary intake was assessed using 3-d food records. Subjects were asked to record the type and amount of foods and beverages consumed for 2 consecutive weekdays and 1 Table 1 Descriptive statistics of study participants by menstruation status* Variable

Premenopausal Peri-/postmenopausal (n ⫽ 100) (n ⫽ 96)

Age (y) BMI (kg/m2) Waist circumference (cm) Spine bone mineral density (L2–L4) (g/cm2) Total body bone mineral content (g) Physical activity level Mediterranean diet score (0–55) Bone mass status† Normal Osteopenic/osteoporotic Smoking status Never Former Current

38.01 ⫾ 8.66 26.23 ⫾ 5.16 80.07 ⫾ 10.94 1.20 ⫾ 0.14

56.72 ⫾ 6.40§ 28.98 ⫾ 5.00§ 87.82 ⫾ 11.09§ 1.05 ⫾ 0.15§

2630 ⫾ 283

2312 ⫾ 303§

1.51 ⫾ 0.21 24.44 ⫾ 6.58

1.43 ⫾ 0.20‡ 26.32 ⫾ 5.63‡

84.0 16.0

38.5§ 61.5§

42.0 8.0 50.0

53.1 9.4 37.5

BMI, body mass index * Values are means ⫾ SDs or frequency percentage. † As defined by World Health Organization cutoff points [11]. ‡ P ⬍ 0.05 between groups. § P ⬍ 0.001 between groups.

M. D. Kontogianni et al. / Nutrition 25 (2009) 165–171

weekend day. Clear instructions were given to them on how to record the quantity of food eaten using standard household measurements. The frequency of several food groups’ consumption was then approximately quantified in terms of number of servings per day. The food groups evaluated were dairy products (low and full fat), fruits, vegetables, cereals (non-refined and refined), potatoes, legumes, red meat and products, poultry, fish, and nuts. Frequency of olive oil consumption (times per day) and the daily consumption of sweets and alcoholic beverages, coffee, soft drinks, and fruit juices (milliliters per day) were also recorded. To evaluate adherence to the Mediterranean diet, a Mediterranean diet score was used [12,13]. Briefly, the index includes ascertainment of nine major food groups (i.e., non-refined cereals, potatoes, fruits, vegetables, legumes, fish, red meat and products, poultry, full-fat dairies) and olive oil and alcohol intakes. Using discrete scores from 0 to 5, assigned to the frequency of consumption of foods based on the recommendations of the Greek Ministry of Health [14], a total score, ranging from 0 to 55, was calculated for each subject. Higher scores indicate better adherence to the Mediterranean dietary pattern. For the assessment of low energy reporting, the ratio energy intake/basal metabolic rate (EI/BMR) was determined for each subject. BMR was estimated using the Schofield equations for the prediction of BMR [15], adopted by the 2004 Food and Agriculture Organization/World Health Organization/United Nations University (FAO/ WHO/UNU) report [16]. Participants with an EI/BMR ⬍1.04 were classified as “low-energy reporters” based on the cutoff limits proposed by Goldberg et al. [15]. “Normal-

167

energy reporters” or “non–low-energy reporters” were participants with an EI/BMR ⱖ1.04. Physical activity assessment Assessment of physical activity was performed through a brief self-reported questionnaire (the Harokopio Physical Activity Questionnaire), which collects the previous week’s self-reported physical activity [17]. The Harokopio Physical Activity Questionnaire examines the time spent in light-, moderate-, and high-intensity activities and also requires sleeping to be recorded. The questionnaire is based on the metabolic equivalents of all activities of the previous week, including activities at work, leisure time, and rest or sleep, thus allowing the prediction of mean daily energy expenditure. Physical activity level and total energy expenditure were estimated, as were energy expenditures spent at home, at work, and at leisure time. Statistical analysis Continuous variables are presented as means ⫾ standard deviations and categorical variables are presented as absolute frequencies. The Kolmogorov-Smirnov test was used to test for the normality of distributions. Two-sample t test was used to compare normally distributed continuous variables between premenopausal and peri-/postmenopausal women. To obtain dietary patterns the principal components analysis (PCA) was used [18]. The PCA is a multivariate technique that evaluates the intercorrelations between the initial food variables. Thus, using this method, dietary patterns and

Table 2 Score coefficients derived from principal components analysis regarding foods, food groups, and beverages consumed* Component† 1 Cereals Fruits Nuts Vegetables Legumes Fish Red meat and products Poultry Dairy Olive oil Alcoholic beverages Coffee Sweets Fruit drinks Soft drinks Explained variance (%)

‡

0.754 0.048 0.256 ⫺0.107 ⫺0.012 ⫺0.100 0.335‡ ⫺0.011 0.742‡ 0.395‡ 0.040 0.033 0.006 ⫺0.010 ⫺0.021 10.8

2

3

4

5

6

7

8

9

10

⫺0.016 0.779‡ ⫺0.280 0.702‡ 0.082 ⫺0.016 ⫺0.056 0.097 ⫺0.025 0.381‡ ⫺0.005 ⫺0.076 ⫺0.038 0.081 0.048 10.1

0.059 ⫺0.167 0.202 0.249 0.031 0.867‡ ⫺0.311‡ ⫺0.247 ⫺0.215 0.470‡ 0.024 0.005 ⫺0.049 ⫺0.038 0.028 8.7

⫺0.021 ⫺0.005 0.387‡ 0.130 ⫺0.092 ⫺0.118 ⫺0.510‡ 0.855‡ ⫺0.025 ⫺0.039 0.028 ⫺0.008 ⫺0.015 ⫺0.015 ⫺0.017 8.2

⫺0.067 ⫺0.238 ⫺0.055 0.265 0.043 0.004 0.284 0.106 0.136 0.187 0.918‡ 0.019 0.035 0.019 0.051 7.7

⫺0.115 0.084 0.171 0.021 0.937‡ 0.021 ⫺0.307 ⫺0.194 0.130 0.076 0.036 ⫺0.016 0.060 ⫺0.064 ⫺0.088 6.8

0.159 ⫺0.053 0.300 ⫺0.021 0.073 ⫺0.055 0.220 0.016 ⫺0.238 0.116 0.023 ⫺0.009 0.907‡ 0.119 0.084 6.3

⫺0.121 0.015 0.172 0.133 ⫺0.072 ⫺0.016 ⫺0.160 ⫺0.078 0.189 ⫺0.202 0.019 ⫺0.020 0.110 0.932‡ ⫺0.093 5.9

0.018 ⫺0.141 ⫺0.293 0.060 ⫺0.020 0.007 0.063 0.023 0.013 ⫺0.044 0.017 0.970‡ ⫺0.010 ⫺0.032 0.061 5.7

⫺0.112 0.060 0.256 0.015 ⫺0.084 0.064 0.042 ⫺0.027 0.154 ⫺0.197 0.046 0.064 0.079 ⫺0.090 0.931‡ 5.1

* Score coefficients are similar to the correlation coefficients. † Description of components: 1, high intake of dairy, cereals, red meat and olive oil; 2, high intake of vegetables, fruits, and olive oil; 3, high intake of fish and olive oil and low intake of red meat and red meat products; 4, high intake of poultry and nuts and low intake of red meat and its products; 5, high alcohol intake; 6, high legume intake; 7, high sweet intake; 8, high fruit drink intake; 9, high coffee intake; 10, high soft drink intake. ‡ Foods with the highest correlation (⬎0.30) with the respective component.

168

M. D. Kontogianni et al. / Nutrition 25 (2009) 165–171

behaviors are revealed in an uncorrelated way. The food, food groups, or beverages used in all analyses are presented in Table 2. The orthogonal rotation (varimax option) was used to derive optimal non-correlated components (dietary patterns). To decide the number of components retained, the proportion of the variance in consumption explained by the components was used. In particular, 10 of the 16 components were retained because they explained 80% of the consumption’s variance. Based on the principle that the component scores are interpreted similarly to correlation coefficients (thus, higher absolute values indicate that the food variable contributes most to the construction of the component), the food components (patterns) were named according to scores of the foods that correlated most with the component (scores ⬎0.3). Furthermore, multiple regression analyses using backward elimination procedure were used (P for removing a variable ⱖ0.1) to test the relation among lumbar spine BMD, TBBMC, and the Mediterranean diet score or the dietary patterns derived from the PCA, after adjustment for several potential confounders, including age (in years, continuous), BMI (kilograms per square meter, continuous), menstruation status (pre- versus peri-/postmenopausal), smoking status (never, former, current smokers, categorically), physical activity level (continuous), and being a normal-energy reporter (yes versus no). Standardized ␤-coefficients and R2 values are reported. Data were analyzed by using SPSS 11.0 (SPSS, Inc., Chicago, IL, USA).

this population, even when analysis was restricted to normal-energy reporters. Potential associations between dietary patterns and indices of bone mass were explored using PCA. Ten components were extracted explaining 80% of the total variance in food intake. The score coefficients for the 10 food components (patterns) are presented in Table 2. As higher absolute values indicate that the food variable contributes more to the development of the component, the following components were derived: a pattern high in dairy, cereals, red meat, and olive oil consumption (component 1); a pattern rich in vegetables, fruits, and olive oil (component 2); a pattern characterized by high consumption of fish and olive oil and low intake of red meat and products (component 3); a pattern characterized by high consumption of poultry and nuts and low intake of red meat and red meat products (component 4); and patterns that represented alcohol consumption (component 5), legume consumption (component 6), sweets consumption (component 7), fruit drink consumption (component 8), coffee consumption (component 9), and soft drink consumption (component 10). Associations between these extracted components and bone mass parameters were then evaluated. Multiple linear regression models fitted to data for lumbar spine BMD and TBBMC were performed and the models are presented in Table 3. Data were controlled for age, menstruation status, BMI, smoking status, physical activity level, and low-energy Table 3 Multiple regression analysis models exploring the association of food components with spine BMDL2–L4 and TBBMC

Results Descriptive characteristics of the study participants by menstruation status are presented in Table 1. Because there were only 16 perimenopausal women, we decided to include them in the postmenopausal group. Compared with premenopausal women, peri- and postmenopausal women were older, exhibited higher levels of BMI and waist circumference, and had lower spine BMD (P ⬍ 0.001), TBBMC (all Ps ⬍ 0.001), and physical activity level (P ⫽ 0.01). Their mean Mediterranean diet score was also higher (P ⫽ 0.04). The association between adherence to Mediterranean diet and bone mass was evaluated using multiple regression analysis to control for successively introduced potential confounders. Several independent variables were entered in the regression models, including Mediterranean diet index, age, menstruation status, BMI, smoking status, and physical activity level. The only variable that was significantly related to lumbar BMD was menstruation status (standardized ␤-coefficient ⫽ ⫺0.406, P ⬍ 0.001, for the peri-/postmenopausal group), which explained 16.5% of the variance. With regard to TBBMC, age was the only significant predictor (standardized ␤-coefficient ⫽ ⫺0.523, P ⬍ 0.001) explaining 27.4% of the TBBMC variance. Adherence to the Mediterranean diet was not related to the indices of bone mass in

Variables*

Age (y) Menstruation status (pre- versus peri-/ postmenopausal) Food component 1 Food component 2 Food component 3 Food component 4 Food component 5 Food component 6 Food component 7 Food component 8 Food component 9 Food component 10 R2 of model

BMDL2–L4

TBBMC

Standardized ␤-coefficient

P

Standardized ␤-coefficient

P

⫺0.213 ⫺0.265

0.06 0.02

⫺0.547 ⫺0.131

⬍0.001 0.22

0.094 0.011 0.185 0.054 ⫺0.041 ⫺0.061 ⫺0.090 0.063 0.024 0.227 0.207

0.22 0.89 0.02 0.49 0.61 0.43 0.24 0.41 0.77 0.13

0.083 0.021 0.140 0.002 ⫺0.023 ⫺0.047 ⫺0.051 0.014 0.045 0.176 0.291

0.25 0.77 0.05 0.98 0.76 0.52 0.48 0.85 0.55 0.18

BMDL2–L4, lumbar bone mineral density; TBBMC, total body bone mineral content * Also adjusted for BMI, smoking status, physical activity level, and low energy reporting. Description of components: 1, high intake of dairy, cereals, red meat, and olive oil; 2, high intake of vegetables, fruits, and olive oil; 3, high intake of fish and olive oil and low intake of red meat and red meat products; 4, high intake of poultry and nuts and low intake of red meat and its products; 5, high alcohol intake; 6: high legume intake; 7, high sweet intake; 8, high fruit drink intake; 9, high coffee intake; 10, high soft drink intake.

M. D. Kontogianni et al. / Nutrition 25 (2009) 165–171

reporting. Food component 3 was positively associated with lumbar spine BMD (standardized ␤-coefficient ⫽ 0.185, P ⫽ 0.02) and with TBBMC (standardized ␤-coefficient ⫽ 0.140, P ⫽ 0.05).

Discussion To our knowledge, the present study is the first to explore potential associations between adherence to the Mediterranean diet and indices of bone health, revealing no significant effect of this dietary pattern on indices of bone (i.e., lumbar spine BMD and TBBMC). However, adherence to a dietary pattern with some of the features of the Mediterranean diet, i.e., rich in fish and olive oil and low in red meat and products, was positively associated with the aforementioned indices of bone mass in our sample of adult women. The Mediterranean diet, as described by the dietary index used, is a pattern characterized by high intake of fruits, vegetables, legumes and non-refined cereals, fish, and olive oil, low intake of red meat and full-fat dairy products, and moderate consumption of poultry and alcoholic beverages [13]. Although such a pattern includes food groups (i.e., fruits and vegetables) that have been associated with a protective effect on bone health [19,20], it also includes increased quantities of acid-producing foods, such as non-refined cereals and legumes, which may alter the acid– base balance and therefore not allow the beneficial effects of alkali foods [21], such as fruits and vegetables, to be expressed. Moreover, according to the index that was applied, full-fat dairy products were considered as a food group with a negative impact on overall health, a consideration that is not appropriate for bone mass. The PCA revealed that a dietary pattern with some of the Mediterranean diet features, i.e., high fish and olive oil consumption and low red meat intake, was significantly associated with greater BMD at the lumbar spine, and with TBBMC, after controlling for several confounders. Previous research on the impact of fish oils, rich in ␻-3 fatty acids, on skeletal biology has shown consistent and reproducible beneficial effects on bone metabolism and bone/joint diseases, associated in part with downregulating prostaglandin E2 formation, as evidenced in in vivo and in vitro experiments [22]. Dietary supplementation with ␻-3 fatty acids also reduces the production of interleukin-1 and tumor necrosis factor in response to an endotoxin stimuli [23], whereas in vitro models using a preosteoblastic cell line, MC3T3-E1, indicated a greater production of the bone-formation markers alkaline phosphatase and osteocalcin after 48 h of treatment with eicosapentaenoic acid than after treatment with arachidonic acid [24]. Recently, a positive correlation between phospholipid ␻-3 fatty acid concentrations, especially docosahexanoic acid, and changes in BMD at the spine was found between ages 16 and 22 y in a cohort of 78 healthy young men [25]. In the same study, a negative association was also found between higher ratios of ␻-6/␻-3 fatty acids and spinal BMD accrual between ages 16 and 22 y. Similar findings have been also observed in a cohort

169

of older, community-dwelling adults [26]: an increased ratio of dietary ␻-6 (from vegetable oils, poultry, meat, milk, eggs, and most processed foods) to ␻-3 (from fish, nuts, seeds and some vegetables) fatty acids was significantly associated with a lower hip BMD in men and in women and a lower lumbar spine BMD in women. In addition, results from the National Health and Nutrition Examination Survey III revealed that saturated fat (the main fat of animal foods) intake was negatively associated with bone density, and the strongest effects were seen among men ⬍50 y old [27]. Concerning monounsaturated fatty acids, a positive association between BMD and monounsaturated fat, derived mostly from olive oil, has been reported in a sample of Greek men and women [28]. The investigators discussed the influence that vitamin E, abundant in olive oil, exerts on prostaglandin levels and therefore on bone formation and resorption. Furthermore, a dose–response protective effect of oleuropain, an olive oil polyphenol, has been found on bone mass in an experimental in vivo model of bone loss in rats [29]. As mentioned earlier, recent studies have shown a positive association between fruit and vegetable intake in the developing skeleton [30 –32]; however, with regard to the adult female skeleton, findings are less consistent. Some studies have supported a positive association [33–35], whereas others have failed to show any impact in crosssectional [20] or longitudinal [34] design. Our results did not reveal any association, because the second food component, rich in fruits, vegetables and olive oil, did not show any significant correlation with bone mass. This may be attributed to the general high intake of this food group and to the diversity of fruits and vegetables consumed. People all over the Mediterranean traditionally eat a variety of plants, some of them locally grown or of wild species [36 –38], with diverse content in dietary fibers, phytoestrogens, antioxidants, and other micronutrients, and this diversity in nutrients may also exert diverse effects on bone mass. In our study, food consumption data were obtained through 3-d food records. The dietary record method has the potential to provide quantitatively accurate information on food consumed during the recording period. It is often regarded as a “gold standard” or “reference method” against which other dietary assessment tools are validated [39]. Among its advantages, it relies to a lesser extent on memory recall so the problem of omission is lessened and it is more likely to provide a detailed description of the type and portion of the food consumed. Records were not weighed, therefore missing information with regard to amounts of food consumed still exists; however, not weighing all foods eaten may affect to a lesser extent food intake compared with the changes in habitual food intake due to participation burden when weighed food records are expected [40]. Among the limitation of our study is its cross-sectional design. Observational studies of diet– disease associations cannot fully explore lifetime dietary intake or dietary change and cannot completely exclude confounding if a dietary pattern

170

M. D. Kontogianni et al. / Nutrition 25 (2009) 165–171

co-varies with a more healthy diet (e.g., more calcium) or another healthy lifestyle pattern (e.g., more exercise). Therefore, causal relations cannot be established. Moreover, the results of dietary pattern analysis strongly depend on the population derived and may show significant differences according to genetic, environmental, and cultural backgrounds. The PCA method has some limitations that stem from some subjective decisions that investigators make during the analysis of the data [41]. The validity and reproducibility of the dietary patterns identified in the present study need to be further explored in other population samples.

Conclusion 〈 dietary pattern characterized by high consumption of fish and olive oil and low red meat intake was associated with higher BMD and TBBMC in our sample of adult women, suggesting potential bone-preserving properties of this eating pattern throughout adult life.

References [1] Kitchin B, Morgan S. Nutritional considerations in osteoporosis. Curr Opin Rheumatol 2003;15:476 – 80. [2] Ilich JZ, Kerstetter JE. Nutrition in bone health revisited: a story beyond calcium. J Am Coll Nutr 2000;19:715–37. [3] Jacques PF, Tucker KL. Are dietary patterns useful for understanding the role of diet in chronic disease? Am J Clin Nutr 2001;73:1–2. [4] Hu FB. Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol 2002;13:3–9. [5] Tucker KL, Hannan MT, Chen H. Diet pattern groups are related to bone mineral density among adults: the Framingham study. J Bone Miner Res 2000;15:S222. [6] Tucker KL, Chen H, Hannan MT, Cupples LA, Wilson PW, Felson D, Kiel DP. Bone mineral density and dietary patterns in older adults: the Framingham Osteoporosis Study. Am J Clin Nutr 2002;76: 245–52. [7] Okubo H, Sasaki S, Horiguchi H, Oguma E, Miyamoto K, Hosoi Y, et al. Dietary patterns associated with bone mineral density in premenopausal Japanese farmwomen. Am J Clin Nutr 2006;83:1185–92. [8] New S. Do vegetarians have a normal bone mass? Osteoporos Int 2004;15:679 – 88. [9] Smith AM. Veganism and osteoporosis: a review of the current literature. Int J Nurs Pract 2006;12:302– 6. [10] Lin PH, Ginty F, Appel LJ, Aickin M, Bohannon A, Garnero P, et al. The DASH diet and sodium reduction improve markers of bone turnover and calcium metabolism in adults. J Nutr 2003;133:3130 – 6. [11] World Health Organization Study Group on Assessment of Fracture Risk and its Application to Screening for Postmenopausal Osteoporosis. Assessment of fracture risk and its application to screening for postmenopausal osteoporosis: report of a World Health Organization study group. 843 ed. Geneva: World Health Organization; 1994. [12] Panagiotakos DB, Pitsavos C, Stefanadis C. Dietary patterns: a Mediterranean diet score and its relation to clinical and biological markers of cardiovascular disease risk. Nutr Metab Cardiovasc Dis 2006;16: 559 – 68. [13] Panagiotakos DB, Pitsavos C, Arvanity F, Stefanadis C. Adherence to the Mediterranean food pattern predicts the prevalence of hypertension, hypercholesterolemia, diabetes and obesity, among healthy adults; the accuracy of the MedDietScore. Prev Med 2007;44:335– 40.

[14] Ministry of Health, Supreme Scientific Health Council. Dietary guidelines for adults in Greece. Arch Hellenic Med 1999;16:516 –24. [15] Goldberg GR, Black AE, Jebb SA, Cole TJ, Murgatroyd PR, Coward WA, Prentice AM. Critical evaluation of energy intake data using fundamental principles of energy physiology: 1. Derivation of cut-off limits to identify under-recording. Eur J Clin Nutr 1991;45:569 – 81. [16] FAO/WHO/UNU. Human energy requirements: report of a joint FAO/WHO/UNU expert consultation. Rome: FAO; 2004. [17] Kollia M, Kavouras SA, Gioxari A, Maraki M, Sidossis LS. Development, validity and reliability of the Harokopio Physical Activity Questionnaire in Greek adults. In: Proceedings of the 8th Panhellenic Congress on Nutrition and Dietetics. Athens, Greece: Abstract Book; 2006, p. 130 –1. [18] Mardia KV, Kent JT, Bibby JM. Multivariate Analysis. 1st ed. New York: Academic Press; 1979. [19] New SA, Robins SP, Campbell MK, Martin JC, Garton MJ, BoltonSmith C, et al. Dietary influences on bone mass and bone metabolism: further evidence of a positive link between fruit and vegetable consumption and bone health. Am J Clin Nutr 2000;71:142–51. [20] Prynne CJ, Mishra GD, O’Connell MA, Muniz G, Laskey MA, Yan L, et al. Fruit and vegetable intakes and bone mineral status: a cross sectional study in 5 age and sex cohorts. Am J Clin Nutr 2006;83: 1420 – 8. [21] New SA. Acid– base homeostasis and the skeleton: is there a fruit and vegetable link to bone health? In: New SA, Bonjour JP, editors. Nutritional aspects of bone health. London: Royal Society of Chemistry; 2003, p. 291–311. [22] Watkins BA, Li Y, Lippman HE, Seifert MF. Omega-3 polyunsaturated fatty acids and skeletal health. Exp Biol Med 2001;226:485–97. [23] Endres S, Ghorbani R, Kelley VE, Georgilis K, Lonnemann G, van der Meer JW, et al. The effect of dietary supplementation with n-3 polyunsaturated fatty acids on the synthesis of interleukin-1 and tumor necrosis factor by mononuclear cells. N Engl J Med 1989;320: 265–71. [24] Watkins BA, Li Y, Lippman HE, Feng S. Modulatory effect of n-3 polyunsaturated fatty acids on osteoblast function and bone metabolism. Prostaglandins Leukot Essent Fatty Acids 2003;68:387–98. [25] Högström M, Nordström P, Nordström A. N-3 fatty acids are positively associated with peak bone mineral density and bone accrual in healthy men: the NO2 Study. Am J Clin Nutr 2007;85:803–7. [26] Weiss LA, Barrett-Connor E, von Mühlen D. Ratio of n-6 to n-3 fatty acids and bone mineral density in older adults: the Rancho Bernardo Study. Am J Clin Nutr 2005;81:934 – 8. [27] Corwin RL, Hartman TJ, Maczuga SA, Graubard BI. Dietary saturated fat intake is inversely associated with bone density in humans: analysis of NHANES III. J Nutr 2006;136:159 – 65. [28] Trichopoulou A, Georgiou E, Bassiakos Y, Lipworth L, Lagiou P, Proukakis C, Trichopoulos D. Energy intake and monounsaturated fat in relation to bone mineral density among women and men in Greece. Prev Med 1997;26:395– 400. [29] Puel C, Mathey J, Agalias A, Kati-Coulibaly S, Mardon J, Obled C, et al. Dose–response study of effect of oleuropein, an olive oil polyphenol, in an ovariectomy/inflammation experimental model of bone loss in the rat. Clin Nutr 2006;25:859 – 68. [30] Tylavsky FA, Holliday K, Danish R, Womack C, Norwood J, Carbone L. Fruit and vegetable intake is an independent predictor of bone mass in early pubertal children. Am J Clin Nutr 2004;79:311–7. [31] McGartland CP, Robson PJ, Murray LJ, Cran GW, Savage MJ, Watkins DC, et al. Fruit and vegetable consumption and bone mineral density: the Northern Ireland Young Hearts Project. Am J Clin Nutr 2004;80:1019 –23. [32] Vatanparast H, Baxter-Jones A, Faulkner RA, Bailey DA, Whiting SJ. Positive effects of fruit and vegetable consumption and calcium intake on bone mineral accrual in boys during growth from childhood to adolescence: the University of Saskatchewan Pediatric Bone Mineral Accrual Study. Am J Clin Nutr 2005;82:700 – 6.

M. D. Kontogianni et al. / Nutrition 25 (2009) 165–171 [33] New SA, Bolton-Smith C, Grubb DA, Reid DM. Nutritional influences on mineral density: a cross-sectional study in premenopausal women. Am J Clin Nutr 1997;65:1831–9. [34] Tucker KL, Hannan MT, Chen H, Cupples LA, Wilson PW, Kiel DP. Potassium, magnesium and fruit and vegetable intakes are associated with greater bone mineral density in elderly men and women. Am J Clin Nutr 1999;69:727–36. [35] Macdonald HM, New SA, Golden MHN, Campbell MK, Reid DM. Nutritional associations with bone loss during the menopausal transition: evidence for a beneficial effect of calcium, alcohol, and fruit and vegetable nutrients and of a detrimental effect of fatty acids. Am J Clin Nutr 2004;79:155– 65. [36] Simopoulos AP. The Mediterranean diets: what is so special about the diet of Greece? The scientific evidence. J Nutr 2001;131(suppl):3065S–73.

171

[37] Willett WC, Sacks F, Trichopoulou A, Drescher G, Ferro-Luzzi A, Helsing E, Trichopoulos D. Mediterranean diet pyramid: a cultural model for healthy eating. Am J Clin Nutr 1995;61(suppl): 1402S– 6. [38] Schaffer S, Schmitt-Schillig S, Müller WE, Eckert GP. Antioxidant properties of Mediterranean food plant extracts: geographical differences. J Physiol Pharmacol 2005;56(suppl 1):115–24. [39] Thompson FE, Byers T. Dietary assessment resource manual. J Nutr 1994;11(suppl):2245S–317. [40] Rutishauser IH. Dietary intake measurements. Public Health Nutr 2005;8(suppl 7A):1100 –7. [41] McCann SE, Weiner J, Graham S, Freudenheim JL. Is principal components analysis necessary to characterise dietary behaviour in studies of diet and disease? Public Health Nutr 2001;4:903– 8.