European Journal of Clinical Nutrition (2016) 70, 85–90
© 2016 Macmillan Publishers Limited All rights reserved 0954-3007/16
www.nature.com/ejcn
ORIGINAL ARTICLE
Dietary patterns and bone mineral density in
Brazilian postmenopausal women with osteoporosis:
a cross-sectional study
NAG de França1, MBR Camargo2, M Lazaretti-Castro2, BSE Peters1 and LA Martini1
BACKGROUND/OBJECTIVES: The aim of this study was to investigate the association between dietary patterns and bone mineral
density (BMD) in postmenopausal women with osteoporosis.
SUBJECTS/METHODS: This cross-sectional study included 156 postmenopausal and osteoporotic Brazilian women aged over 45
years. BMD of lumbar spine, total femur (TF), femoral neck and of total body (TB), as well as body composition (fat and lean mass),
was assessed by dual-energy X-ray absorptiometry. Body mass index and lifestyle information were also obtained. Dietary intake
was assessed by using a 3-day food diary. Dietary patterns were obtained by principal component factor analysis. Adjusted multiple
linear regression analysis was applied in order to evaluate the predictive effect of dietary patterns on BMD. Significance was set at
Po 0.05.
RESULTS: Five patterns were retained: ‘healthy’, ‘red meat and refined cereals’, ‘low-fat dairy’, ‘sweet foods, coffee and tea’ and
‘Western’. The ‘sweet foods, coffee and tea’ pattern was inversely associated with TF BMD (β = − 0.178; 95% CI: − 0.039 to − 0.000)
and with TB BMD (β = − 0.320; 95% CI: − 0.059 to − 0.017) even after adjusting for energy and calcium intake, lean mass, age and
postmenopausal time.
CONCLUSIONS: A concomitant excessive consumption of sweet foods and caffeinated beverages appears to exert a negative effect
on BMD even when the skeleton already presents some demineralization. Food and beverage intake is a modifiable factor that
should not be neglected in the treatment of individuals with osteoporosis.
European Journal of Clinical Nutrition (2016) 70, 85–90; doi:10.1038/ejcn.2015.27; published online 25 March 2015
INTRODUCTION
Estimates for the year 2000 revealed approximately 9 million new
osteoporotic fractures worldwide, an increase of 25% since 1990,1
with osteoporosis affecting an estimated 200 million women
worldwide.2 In Brazil, the epidemiological Brazilian Osteoporosis
Study—BRAZOS (2010)3—revealed a self-reported prevalence of
15.1 and 12.8% of low-impact fractures among women and men,
respectively, placing a financial burden on the public health
system, as expenses with hospital admissions for osteoporotic
fractures account for 2% of total hospitalization expenditure
among the elderly.4
As osteoporosis is considered a public health problem with an
increasing prevalence, the development of strategies to improve
the treatment, prevent disease progression and ensure a better
quality of life for the patients is fundamental. Diet is recognized as
one of the modifiable factors that influence bone maintenance,
but only the role of specific micronutrients, most notably calcium
and vitamin D, is well elucidated.5 However, people consume
meals containing a combination of foods and nutrients, and thus
an examination of dietary patterns would more closely reflect the
real world by considering the overall eating pattern, and
the collinearity of nutrients and foods, which could better express
the true eating behavior.6
Dietary patterns reflect a blend of social, cultural, environmental
and economic aspects, and they are able to provide more
accessible recommendations.7 Previous studies have investigated
the association between dietary patterns and bone mineral
density (BMD) among different populations and age groups of
both sexes. Dietary patterns characterized by high intakes of
refined cereals, processed meats, fried foods (mainly French fries)
and sweet foods have been negatively associated with bone.8–13
These patterns consist of food related to increased levels of
inflammation (increase in inflammatory markers), which seems to
have a negative impact on the bone quality.14 On the other hand,
patterns with high amounts of fruit and vegetables have shown a
positive relationship with skeletal health.8,12,13,15–18 Although the
mechanisms involved in this relationship are still not clearly
elucidated, it is suggested that the possible positive effect on
bone is related to the alkalizing property and the presence of
bioactive compounds (such as antioxidants) in the composition
of these foods.19 These results are only pertinent to the risk of
developing osteoporosis; however, there is a lack of evidence to
confirm whether these results could be extended to osteoporotic
individuals, or even if dietary pattern can exert an effect on bone
when osteoporosis is already established.
The use of a dietary pattern approach to evaluate the
association between diet and bone health warrants further
studies, considering the wide variability in diets among different
countries. Furthermore, the study of this association may help
bridge the gap in knowledge of the influence of overall diet on
1
Department of Nutrition, School of Public Health, Sao Paulo University, Food and Nutrition Research Center-NAPAN, Sao Paulo, Brazil and 2Division of Endocrinology, School of
Medicine, Federal University of Sao Paulo, Sao Paulo, Brazil. Correspondence: Professor LA Martini, Department of Nutrition, School of Public Health, Sao Paulo University, Food
and Nutrition Research Center-NAPAN, Sao Paulo 01246-904, Brazil.
E-mail: [email protected]
Received 30 September 2014; revised 15 December 2014; accepted 26 January 2015; published online 25 March 2015
Dietary patterns in women with osteoporosis
NAG de França et al
86
osteoporosis treatment, providing data that may contribute to
improvements in osteoporotic patient care. Therefore, the aim of
the current study was to determine the dietary patterns of
postmenopausal women with osteoporosis using factor analysis,
and to investigate the association between these patterns
and BMD.
SUBJECTS AND METHODS
Study design and population
From among 363 individuals assessed at a specialized outpatient clinic of
the Federal University of Sao Paulo in Sao Paulo city, Brazil, for the
treatment of osteoporosis, only postmenopausal women aged over 45
years with at least 2 years of absence of menstrual cycles (menopause) and
undergoing osteoporosis follow-up for at least 3 months were selected.
Subjects with a history of renal failure, absorption disorders, current use of
glucocorticoids, current hyperparathyroidism and incomplete data were
excluded. Although it is known that corticosteroids and some illnesses, as
hyperparathyroidism, are a major cause of secondary osteoporosis, women
who were on steroid therapy in the past or those who already have been
treated for the disease were not excluded from the study because the
authors believe that the study’s purpose was not to investigate the cause
of osteoporosis but their current relationship with eating habits; thus, a
final total of 156 free-living women were eligible to take part in the study,
and they agreed to participate by signing an informed consent form.
All subjects formerly received or were receiving treatment for
osteoporosis with an approved medication, and/or calcium and/or vitamin
D supplementation. The study protocol was approved by the Federal
University of Sao Paulo Research Ethics Committee (0839/08), and
enrollment occurred between late autumn and late spring, from 2009
to 2012.
Bone mineral density measurement
Measurements for the determination of BMD (g/cm2) of the lumbar spine
(L1–L4), total femur (TF), femoral neck (FN) and total body (TB) were
conducted by using dual-energy X-ray absorptiometry (Discovery A, QDR
for Windows XP, Hologic, Inc., Bedford, MA, USA). The analyses were
performed by a highly trained technologist using the same technique for
all measurements to avoid disparities in size or position of regions of
interest, and the scan was determined on the basis of the height and
weight of the participant. BMD was assessed and analyzed according to
the recommendations of the Brazilian Society for Clinical Densitometry.20
Osteoporosis was defined as a BMD T-score for the TF and/or FN and/or
lumbar spine of ⩽ 2.5 SDs.21 The coefficients of variation (CVs) of lumbar
spine BMD and TF BMD was 0.8% and of FN BMD was 1.2%.
Table 1.
Dietary assessment and food grouping
Dietary intake was assessed by using a 3-day food diary in which the
participants were clearly instructed to record information on nonconsecutive days (2 weekdays and 1 weekend day) on their food and beverage
intake using household measures. Participants provided details on brand
names of food products, food preparation methods and any recipes used.
This method reduces the memory bias, provides detailed information
about the current food intake and allows estimates of usual intake.22 Food
and beverage quantities obtained from the 3-day food diary were
converted into grams and milliliters and computed using the Nutrition
Data System for Research software (NDS-R, 2007 version, University of
Minnesota, MN, USA).
To reduce the complexity of the data, the 270 individual food items
identified from the diary (in grams/day) were manually allocated into 13
food groups constructed according to the principles of similarity of
nutrient profiles or culinary usage of the foods (Table 1), and they were
subsequently used to identify the dietary patterns.
Confounding factor measurements
Factors that appear to be related to BMD and dietary patterns were
assessed, which included body weight, height, body fat, physical activity,
smoking habit, alcohol intake, history of bone fracture, supplement use,
postmenopausal time and current treatment received. Body weight was
measured to the nearest 0.1 kg by using a manual scale (Filizola, Sao Paulo,
Brazil), with the participants wearing light clothing and no footwear, and
height was measured to the nearest 0.1 cm with a wall-mounted
stadiometer (Tonelli, Criciuma, Brazil), after removal of footwear. Body
mass index was calculated by dividing the TB weight (kg) by height
squared (m2) and classified according to the World Health Organization
classification23 for participants aged under 60 years, and according to the
Pan American Health Organization24 for subjects aged 60 years or over.
Body fat (g) and lean mass (g) were obtained from the TB dual-energy
X-ray absorptiometry scan.
Age (in years, continuous), practice of physical activity, considering only
activities for recreation, sport, exercise or leisure performed for at least 10
continuous minutes (yes or no), current smoking and alcohol intake for the
last 3 months (yes or no for both), bone fracture since the age of 45 years
(yes or no), postmenopausal time (in years, continuous), calcium or vitamin
D supplementation in the last 3 months (yes or no) and the use of
bone-related medication (within the last 3 months) were obtained from a
two-page questionnaire.
Statistical analyses
The derivation of the dietary patterns was conducted by applying the
principal component factor analysis method. Principal component factor
The 13 food groupings used in the dietary pattern analysis
Foods group
Foods in the group
Fruit (fresh or dried) and juices
Apple, papaya, banana, tangerine, lemon, peach, grape, strawberry, lemonade,
melon, pineapple, watermelon, mango, pear, orange juice, star fruit, kiwi, acerola juice,
avocado, coconut, coconut water, cherimoya, melon juice, passion fruit juice, raisins, plum,
apricot, guava, fruit salad, persimmon.
Fruit-flavored drinks, cola and noncola soft drinks, light and diet soft drinks.
Light cream cheese, skimmed milk, semi-skimmed milk, white cheese, low-fat yogurt,
cottage cheese, ricotta cheese, light coffee cream.
High-fat yogurt, mozzarella cheese, cream cheese, parmesan cheese, whole milk, goat milk.
Whitefish, fresh sardines, canned sardines, canned tuna, salmon, snapper, codfish, mullet, shrimp.
Beef, hamburger, liver, jerked beef, pork, pork ribs.
Cakes, refined sugar, brown sugar, honey, jelly, chocolate, puddings, condensed milk, cappuccino,
cookies, mousse, dulce de leche, sugar cane beverage, ice cream, pies, shredded sweetened coconut,
chocolate drinks, jam, fruit desserts, chocolate syrup, panettone, canned fruit, baked candy.
Carrot, onion, pumpkin, endive, lettuce, peppers, zucchini, eggplant, okra, chard, chayote, cabbage,
tomatoes, spinach, garlic, olives, broccoli, beets, cauliflower, cabbage, fennel, kelp, chicory, celery,
pumpkin, parsley, cucumber, watercress, turnip, radish.
Potato, cassava, yams, sweet potato.
Rice, crackers, pasta, wheat bread, wheat flour, cheese bread, corn bread, potato bread,
pancakes, cornmeal, gnocchi, croutons, breakfast cereal, canned corn, couscous.
Pizza, chips, hotdog, French fries, pies, popcorn, baked and fried snacks.
Coffee, decaffeinated coffee, espresso, herbal tea, yerba mate.
Margarine, butter, mayonnaise.
Soft drinks and fruit drinks
Low-fat dairy
High-fat dairy
Fish and sea food
Beef and pork meat
Sweet foods
Vegetables
Tubers and tuberous roots
Refined cereals
Snacks, pizzas and pies
Coffee and tea
Fats
European Journal of Clinical Nutrition (2016) 85 – 90
© 2016 Macmillan Publishers Limited
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87
analysis method is a multivariate technique that evaluates the intercorrelations between the initial food variables and reduces food groups
into a smaller number of factors (patterns) that can explain variations in
the dietary intake. The number of factors retained was based on a
combination of food group components with an eigenvalue 41.0, the
percentage of variance criteria (sufficient factors to meet at least 60% of
variance explained)25 and examination of the breakpoint in the scree plot,
resulting in five factors retained for further analyses. The factors were
rotated by orthogonal transformation (Varimax option) to achieve a
simpler structure with a greater interpretability. Food groups with a factor
loading ⩾ 0.45 on a component were considered informative for interpretation of the dietary patterns.25 The factor scores for each pattern and
individual were determined by summing the intakes of each food group
weighted by the factor loading. The groups that had a negative factor
loading were also retained in order to determine the complexity of eating
habits.
Normality of continuous variables was assessed by the Kolmogorov–
Smirnov test. To investigate the predictive effect of dietary patterns on
BMD (dependent), Pearson’s correlation was conducted followed by
multiple linear regression analysis. The linear regression models included
the BMD at each evaluated site (lumbar spine, FN, TF and TB) as a
dependent variable and the dietary patterns (in scores) as independent
variables. The model was adjusted for energy intake (kcal), calcium intake
(mg), lean mass (g), height (cm) and postmenopausal time (years).
The principal component factor analysis was performed using SAS
Enterprise Guide, version 4.1 (SAS Institute, Inc., Cary, NC, USA), whereas
the correlation and regression analyses were performed using the SPSS
software, version 20.0 (SPSS, Chicago, IL, USA. The level of significance was
set at Po0.05.
RESULTS
General characteristics of the participants are presented in Table 2.
The participants had a mean age of 68.4 (9.0) years and body mass
index value of 25.9 (3.9) kg/m2 (according to body mass index
classification, 19% of the sample was underweight, 50% were
normal weight and 31% were overweight—table not shown), with
body fat altering only slightly. The average intake of calcium was
832.5 (442.7) mg, a very close value to the acceptable by the
estimated average requirements for women aged over 50 years
(1000 mg).26 Vitamin D ingested by diet was 4.4 (3.0) μg, bellow
the requirement of 10 μg.26 Most of the participants had less than
5 years of education (low educational level; 79%), did not exercise
(54%), did not smoke (91%) and were taking vitamin D or calcium
supplementation (85 and 53.2%, respectively). The main treatment
for osteoporosis was through the use of bisphosphonates (75%).
The factor-loading matrices for the five patterns retained are
shown in Table 3. The high positive loadings indicate strong
associations between food groups and patterns, whereas high
negative loadings indicate a strong negative relation. Patterns
were labeled according to the food groups with positive loadings.
Dietary pattern 1 showed heavy loadings on vegetables
(average intake of the entire sample: 87.4 ± 94.7 g/day; ranging
from 0–725 g/day), fruit (fresh and dried) and fresh juices
(251.6 ± 221.2 g/day; 0–1,166 g/day) and tubers and tuberous
roots (25.6 ± 54.7 g/day; 0–366.7 g/day) and was labeled ‘Healthy’.
Dietary pattern 2, with high loadings for refined cereals and baked
products with refined cereals (230.9 ± 129.9 g; 0–786 g/day) and
beef and pork meat (59.2 ± 70.3 g/day; 0–450 g/day), was labeled
‘Red meat and refined cereals’. Dietary pattern 3 had heavy
loadings on low-fat dairy products and was labeled ‘Low-fat dairy’
(125.9 ± 201.2 g/day; 0–1,019.5 g/day). Dietary pattern 4, with high
loadings for sugar, sugary products (42.8 ± 74.9 g/day; 0–502.5 g/
day) and coffee and tea (138.5 ± 149.3 g/day; 0–1,008.9 g/day), was
labeled ‘Sweet foods, coffee and tea’. Dietary pattern 5 showed
heavy loadings on fats (9.0 ± 19.2 g; 0–207.1 g/day), snacks, pizzas,
pies (30.0 ± 97.1 g/day; 0–823.3 g/day) and soft drinks and fruit
drinks (59.3 ± 136.6 g/day; 0–1,164.9 g/day), and it was labeled
‘Western’. Overall, the five dietary patterns accounted for 60.4% of
the variance in food intakes.
© 2016 Macmillan Publishers Limited
Table 2. General characteristics of the osteoporotic postmenopausal
women studied (n = 156)
Postmenopausal women
with osteoporosis
Age (years)
Weight (kg)
Body mass index (kg/m2)
Body fat (%)
Postmenopausal time (years)
Energy intake (kcal)
Carbohydrate intake (% of total calories)
Fat intake (% of total calories)
Protein intake (% of total calories)
Calcium intake (mg)
Vitamin D intake (μg)
Lumbar spine BMD (g/cm2)
Lumbar spine BMD (T-score)
Femoral neck BMD (g/cm2)
Femoral neck BMD (T-score)
Total femur BMD (g/cm2)
Total femur BMD (T-score)
Total BMD (g/cm2)
Total BMD (T-score)
Fracture (yes)a (%)
Educational level
⩽ 5 years (%)
5–8 years (%)
48 years (%)
Physical activity (yes) (%)
Smoking (yes) (%)
Alcohol intake (yes) (%)
Vitamin D supplementation (yes) (%)
Calcium supplementation (yes) (%)
Bisphosphonates (%)
68.4 (9.0)
60.4 (10.1)
25.9 (3.9)
36.0 (5.5)
22.2 (10.1)
1627 (580)
52.2 (9.1)
30.5 (7.1)
18.4 (5.1)
832.5 (442.7)
4.4 (3.0)
0.745 (0.118)
− 2.8 (1.1)
0.648 (0.092)
− 1.8 (0.8)
0.742 (0.109)
− 1.6 (0.9)
0.945 (0.115)
− 1.8 (1.3)
42.9
78.8
15.4
5.8
46.2
9.0
0.0
85.3
53.2
75.0
Abbreviation: BMD, bone mass density. Continuous variables are expressed
as mean (standard deviation) and categorical variables as percentages.
a
After age 45.
Table 4 shows the results for the linear regression conducted
between the dietary patterns and BMD at each evaluated site.
‘Sweet foods, coffee and tea’ was the only pattern that showed a
significant correlation with BMD. As it was inversely associated
with TF BMD (β = − 0.206; 95% CI: − 0.042– − 0.004) and with TB
BMD (β = − 0.321; 95% CI: − 0.059– − 0.017), this dietary pattern
was considered as a negative independent predictor of BMD.
DISCUSSION
Although there are numerous studies exploring the relationships
between dietary patterns and BMD, the present study is unique in
that it conducted such an evaluation among postmenopausal
women who already presented with osteoporosis. The main
finding showed that the ‘sweet foods, coffee and tea’ pattern was
inversely correlated with BMD (in femur and TB) for the overall
sample. Comparisons of our results with previous findings are
hampered by differences in protocols, food habits of the studied
populations, food groups formed and in the dietary patterns
identified.9,12,13,15,27 Furthermore, previous studies have evaluated
the risk factors for the incidence of osteoporosis, in contrast with
the present study, which involved osteoporotic women. However,
some similarities can be observed with the dietary patterns
derived in other studies and their relationships with BMD.
The inverse association between BMD and dietary patterns with
high loadings for sweet foods was previously shown by Tucker
et al.13 in elderly adults from the Framingham Osteoporosis Study.
The mean BMD in the ‘candy group’ was significantly lower for the
Ward’s area, FN and radius (P o 0.001) among men, and for radius
European Journal of Clinical Nutrition (2016) 85 – 90
Dietary patterns in women with osteoporosis
NAG de França et al
88
Table 3.
Factor-loading matrix for the five dietary patterns identified among the 156 osteoporotic postmenopausal women
Vegetables
Fruit and fresh juices
Tubers and tuberous roots
Fats
Fish and sea food
High-fat dairy
Low-fat dairy
Sweet foods
Coffee and tea
Snacks, pizzas and pies
Refined cereals
Beef and pork meat
Soft drinks and fruit drinks
Percentage of variance (%)
‘Healthy’
‘Red meat and refined cereals’
‘Low-fat dairy’
‘Sweet foods, coffee and tea’
‘Western’
0.768
0.608
0.568
—
—
—
—
—
—
—
—
—
—
19.2
—
—
—
—
− 0.472
—
—
—
—
—
0.726
0.666
—
13.9
—
—
—
—
—
− 0.762
0.829
—
—
—
—
—
—
10.8
—
—
—
—
—
—
—
0.736
0.816
—
—
—
—
8.7
—
—
—
0.547
—
—
—
—
—
0.746
—
—
0.554
7.8
Table 4.
Results of adjusted linear regression analysis (β-coefficient), and 95% confidence interval of the dietary patterns (score values) and body
mineral density (g/cm2)
Dietary patterns
‘Healthy’
‘Red meat and refined cereals’
‘Low-fat dairy’
‘Sweet foods, coffee and tea’
‘Western’
Lumbar spine BMD
β (95% CI)
− 0.002
− 0.094
0.141
− 0.066
0.069
(−0.022
(−0.031
(−0.003
(−0.030
(−0.012
to
to
to
to
to
0.021)
0.010)
0.035)
0.014)
0.028)
Femoral neck BMD
β (95% CI)
0.164
− 0.005
− 0.069
− 0.155
0.099
(−0.002
(−0.016
(−0.021
(−0.031
(−0.007
to
to
to
to
to
0.032)
0.015)
0.009)
0.002)
0.025)
Total femur BMD
β (95% CI)
0.184
0.038
− 0.067
− 0.206*
0.052
Total body BMD
β (95% CI)
(0.001 to 0.038)
(−0.014 to 0.022)
(−0.024 to 0.010)
(−0.042 to − 0.004)
(−0.012 to 0.023)
0.087
− 0.019
0.113
− 0.321*
0.039
(−0.011
(−0.023
(−0.006
(−0.059
(−0.016
to
to
to
to
to
0.032)
0.018)
0.032)
−0.017)
0.025)
Abbreviations: BMD, bone mineral density; CI, confidence interval. *Po0.05. Adjusted for energy intake (kcal), calcium intake (mg), lean mass (g), height (cm)
and postmenopausal time (years).
among women (P = 0.004). Similar results were obtained by
Hardcastle et al.12 and Park et al.,27 who also found negative
correlations between patterns rich in sweet foods and bone
health. Both of the studies indicated a negative predictive impact
of sugary food intake on the risk of developing osteoporosis.
A possible explanation for the negative effect of glucose intake
could be related to increased glycemia, which appears to be
associated with changes in bone mineral homeostasis.28 A highsucrose diet produces hyperinsulinemia, which in turn could induce
hypercalciuria by inhibiting renal tubular resorption of calcium,
affecting the quality of bone mineralization.29 There has been little
discussion concerning the effects of hyperglycemia on skeletal
integrity. Chronically elevated glucose even for short periods during
the lifetime could be deleterious for the skeleton, particularly during
growth and peak bone mass formation.30 Once an adequate bone
formation is essential to attenuate the deleterious effects associated
with aging, any change in peak bone mass could lead to the
development of osteoporosis and/or to an increased risk of
fractures in adulthood.31,32 However, it is emphasized that the
present study did not investigate lifetime dietary habits of the
women studied, which does not allow making any inference about
the impact of glycemic peaks on late bone demineralization.
According to the World Health Organization (2002),33 sugar
consumption should not exceed 10% of total energy per day;
however, the new draft guideline proposes a reduction to below
5%,34 as the consumption of free sugars may result in reduced
intake of foods containing more nutritionally adequate calories,
leading to an unhealthy diet and increased risk of noncommunicable diseases.33 Among our sample, the average intake of sugar
and sugary foods group was 42.8 g/day (74.9 g/day), accounting
for 28.6 g of added sugar, which implies 7% of the total average
energy intake. This value is in agreement with the current
recommendation, but it is above the new draft. Furthermore, the
added sugar reached 165 g, which is an excessive intake and
European Journal of Clinical Nutrition (2016) 85 – 90
could lead to the negative effects on bone. The results from our
sample were similar to the findings reported by Bueno et al.35
showing an average intake of 8.5% (33.4 g) in a sample of 622
elderly individuals, with significant differences between the sexes
(7.8% for men vs 8.7% for women; P o 0.05). Taken together, these
results hypothesized that consumption of added sugar is a
common food habit among elderly individuals, especially women.
The ‘sweet foods, coffee and tea’ pattern also contains
caffeinated beverages. Results of investigations into the negative
impact of caffeine on bone are conflicting. Current evidence
suggests that its detrimental effect on BMD might only occur in
susceptible individuals (that is, inadequate calcium intake,
osteoporosis predisposition, old age), where it has been suggested
that caffeine consumption could decrease calcium absorption
and/or increase excretion of calcium in this group.36 Rapuri et al. 37
showed that intakes of more than 300 mg of caffeine (≈514 g of
brewed coffee) accelerate bone loss at the spine in elderly
postmenopausal women, with greater risk among those with the
tt genetic variant of the vitamin D receptor. Although the average
intake of caffeine among the sample as a whole was 48.2 mg, daily
caffeine intake ranged from 0 to 332 mg. It is also suggested that
caffeine could have a deleterious effect on osteoblasts by
inducing apoptosis via a mitochondria-dependent pathway.38
These apoptotic biochemical changes could be a result of an
intracellular oxidative stress stimulated by caffeine, leading to a
loss of BMD.38 Furthermore, there are several observations indicating an adverse effect of caffeine on glucose
metabolism.39–41 Petrie et al.40 showed a significantly attenuation
of whole-body insulin sensitivity in obese, nondiabetic persons,
after acute caffeine ingestion, with no evidence over beta cell
secretion. The inconsistent results about caffeine indicate that also
other coffee constituents may have unfavorable skeletal effects.
Recently, in a study with female rats, Folwarczna et al.42 observed
a negative impact on bone associated to the presence of
© 2016 Macmillan Publishers Limited
Dietary patterns in women with osteoporosis
NAG de França et al
trigonelline (a bitter alkaloid related to the production of aroma
compounds), according to the estrogen status. The trigonelline
administration worsened the mineralization of the vertebra and
the strength of the tibial metaphysis, and decreased the width of
femoral trabeculae in ovariectomized (estrogen-deficient) Wistar
rats, suggesting that the possible detrimental effect of this alkaloid
may be stronger in postmenopausal women.42 Thereby, the
consumption of caffeinated beverage combined with sugar could
exacerbate the detrimental effect on bone through a synergic
relationship.
BMD is an important predictor of fractures.43 According to a
classic meta-analysis conducted by Marshall et al, the risk of hip
and total fractures increases 2.6-fold and 1.6-fold, respectively, for
each standard deviation decrease in BMD.44 Hip, which includes
the proximal femur, accounts for the main site for fractures,
causing acute pain, loss of function and usually leading to
hospitalization with a complicate recovery.45 It is estimated that
the strength of bone decreases about 2–12% per decade in
postmenopausal women, with an average age for hip fractures
about 80 years.45 Thus, as the ‘sweet foods, coffee and tea’ pattern
showed an inverse relationship with TF BMD (β: -0.206; 95%
CI: − 0.042 – − 0.004), it is suggested that this dietary habit could
increase the risk for latest fracture in hip. Data from the National
Health and Nutrition Examination Survey (NHANES 2005–2008)46
determine the TF BMD cutoff for women between 60 and 69 years
as 0.855 ± 0.126 g/cm2, classifying our sample between the 15th
and 25th percentile (0.742 ± 0.109 g/cm2). Thereby, a decrease of
-0.206 g/cm2 associated with the ‘Sweet foods, coffee and tea’
pattern would imply a more prominent demineralization in this
site, significantly accelerating the risk of late fractures.
Most dietary pattern studies have shown a positive association
between a diet rich in fruit and/or vegetables and bone
health.8,12,13,16–18 This same association was not observed in our
sample, may be because the influence of these foods is too low to
detect in a small sample. However, the authors consider that the
intake of fruit and vegetables is supported by the beneficial effect
of their antioxidant content47 and alkalizing property.48
Furthermore, no correlation was detected between the ‘low-fat
dairy’ pattern and BMD in our study. This nonsignificant association
may be because the sample comprised osteoporotic women who
had already received some orientation to consume higher amounts
of dairy, leading to less remarkable results. Average intake from the
dairy group was 5 portions/day (data not shown), considering 120
kcal/dairy portion,49 representing a level of consumption above the
recommendation of 3 dairy portions/day proposed by the Food
Guide for the Brazilian Population49 and an adequate calcium intake
(832.5 mg). It should also be emphasized that, although the
participants had received or were receiving treatment for
osteoporosis, they were not instructed to make changes in their
overall diet. This suggests that the specific orientations to increase
calcium intake, mainly by increasing dairy consumption, may be
insufficient to ensure a protective effect on bone.
Besides sample size, the present study has several other
limitations. First, this study used a cross-sectional approach,
precluding the inference of a causal relationship. Second, as the
participants were recruited from a specialized outpatient clinic in
Sao Paulo city, our sample was not representative of postmenopausal women with osteoporosis in general. Finally, the minimal
nutritional orientation received may have exerted some influence
on the results.
The dietary pattern approach a posteriori is based on current
data, enabling examination of the multidimensionality of the total
diet50 and may have major implications for public health, as it is
more readily interpreted and translated to the daily diet of the
population. In addition, the approach provides underlying knowledge of human feeding practices,6 elucidated in the present
study in the form of an inverse association between the ‘Sweet
foods, coffee and tea’ pattern and BMD (in femur and TB).
© 2016 Macmillan Publishers Limited
CONCLUSIONS
A concurrent excessive consumption of sweet foods and
caffeinated beverages showed a negative effect on BMD even
when the skeleton already presented demineralization. Food and
beverage intake is a modifiable factor that should not be
neglected in osteoporosis treatment. The findings of the present
study suggest that dietary orientations for osteoporotic individuals
should not be limited to calcium and vitamin D intake, but extend
to encompass the overall diet.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
ACKNOWLEDGEMENTS
We thank Wesley Rodrigues dos Santos and Anatoli Yambartsev, PhD, from the
Institute of Mathematics and Statistics of Sao Paulo University, for the dietary pattern
analysis, and the funding organization São Paulo Research Foundation (Fundação de
Amparo à Pesquisa do Estado de São Paulo (FAPESP)).
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