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Division of Human Nutrition and Epidemiology, Wageningen University, The Netherlands;
*
Dutch Dairy Foundation for Nutrition and Health, Utrecht, The Netherlands;
TNO Food and Nutrition Research, Zeist, The Netherlands
2To whom correspondence should be addressed. E-mail: rosalie.rutten{at}wur.nl.
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ABSTRACT |
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 TOP ABSTRACT SUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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KEY WORDS: • cobalamin • osteoporosis • multiple regression analysis • logistic analysis
Osteoporosis is a major problem in our contemporary society. Osteoporosis increases morbidity and dependence, which in turn decrease the quality of life and create a burden on health care costs (1 ). This problem will increase with the growing number of elderly people and will result in a higher number of osteoporotic fractures (2 ).
Most research on the treatment of osteoporosis is focused on hormone replacement therapy (HRT),3 which decreases bone resorption and should prevent postmenopausal bone loss. Unfortunately, estrogen therapeutic treatments have disadvantages such as an increased risk of breast and endometrial cancer (3 ). By contrast, dietary therapy of vitamin D and calcium is promising because it appears to have beneficial effects on bone mineral content (BMC) and bone mineral density (BMD) without serious adverse side effects (4 ,5 ).
Several nutrients positively influence bone-forming cells. Calcium and phosphorus mineralize the matrix formed by osteoblasts. Previous studies in which elderly people received a calcium supplement showed a reduced bone loss. This effect was especially observed in persons with low calcium intake (6 ). The combination of vitamin D and calcium causes a greater decrease in the function of the parathyroid and bone turnover and induces a higher gain of bone mineral density. This in turn decreases the incidence of hip fractures and other nonvertebral fractures in high risk populations (7 ).
It is hypothesized that, in addition to calcium and vitamin D, vitamin B-12 also influences BMC and BMD. In vitro studies have demonstrated that vitamin B-12 has a significant effect on osteoblast proliferation. Also alkaline phosphatase activity was increased in osteoblastic cells after stimulation with vitamin B-12. A minimum concentration of vitamin B-12 may be necessary for a positive effect on osteoblast proliferation (8 ). A few human studies have described an association of vitamin B-12 with BMC and BMD in humans. A study of Carmel et al. (9 ) reported that alkaline phosphatase and osteocalcin rose significantly in vitamin B-12–deficient patients after treatment with vitamin B-12, whereas they remained unchanged in the control group. Parsons et al. (10 ) found a lower bone mass in Dutch macrobiotic-fed adolescents than in control subjects. A macrobiotic diet could induce vitamin B-12 deficiency (11 ,12 ). Goerss et al. (13 ) described an increased risk of osteoporotic fractures in subjects with pernicious anemia; in another study with vegetarian women, BMD was predicted by vitamin B-12 intake and total body fat (14 ). These studies were conducted in subjects with specific health conditions.
Because subclinical vitamin B-12 deficiency is common in elderly people, it may play a role in bone health. Therefore, we investigated vitamin B-12 status in relation to BMD and BMC in a group of frail elderly people. If vitamin B-12 is related to bone health, then a decrease in the prevalence of vitamin B-12 deficiency may help to prevent osteoporosis in elderly people.
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SUBJECTS AND METHODS |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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Data were derived from a previous study in which frail elderly people were recruited to participate in a 17-wk trial to study the effects of nutrient-dense foods and physical exercise on nutritional and health status (15
). The study population consisted of 217 free-living Dutch frail elderly people. Frailty in this study was defined according to the following criteria: requirement of health care services (such as home care or meals-on-wheels), no regular exercise, body mass index (BMI) 
25 kg/m2 or recent weight loss. Other characteristics of the study population were age 
70 y; no use of multivitamin supplements and ability to understand the study procedures. If participants used a single supplement they were allowed to participate.
Complete data collected at baseline were available for 194 subjects. The research protocol was approved by the external Medical Ethical Committee of the Division of Human Nutrition and Epidemiology of the Wageningen University. All subjects gave their written informed consent.
Data collection
Anthropometry and bone composition. Body weight was measured to the nearest 0.05 kg on a digital scale (ED-6-T; Berkel, Rotterdam, Netherlands) and height to the nearest 0.001 m with a wall-mounted stadiometer. Subjects were wearing light underclothes. BMI was calculated as weight in kilograms divided by height in meters squared.
Body composition was determined by dual energy X-ray analysis (Lunar DPX-L, whole body scanner; Radiation, Madison, WI). For all subjects, the fast scan mode was used. The total body scan gave information on fat mass, lean mass, total BMC, BMD of the whole body and T-scores. T-scores reflect the BMD values compared with a young healthy adult reference group and are expressed in SD. T-scores are used for classification in diagnostic categories when screening for osteoporosis (16
). The categories are: normal (more than -1 SD), osteopenia (between -1 SD and -2.5 SD) and osteoporosis ( -2.5 SD).
Questionnaires. A questionnaire filled out by an interviewer obtained information on age, sex, marital status, education, living conditions, disease, number of fractures in the last 5 y, medicine and supplement use. Supplement intake was not included in the dietary intake. Physical activity was assessed using the validated Physical Activity Scale for Elderly (PASE) (17 ,18 ), slightly adjusted for Dutch elderly people (18 ). A 3-d estimated dietary record was used to obtain the energy and calcium intake. Details of the questionnaires used are given by De Jong et al. (15 ).
Blood sampling and laboratory analysis. Blood samples from fasting subjects were collected between 0700 and 0900 h at home for all indicators, except for homocysteine (Hcy). For Hcy analysis, 0.5 mL EDTA-treated blood from nonfasting subjects was collected in our research center at 1200 h and put on ice immediately before further processing. All samples were measured within one run by HPLC-fluorometry with a CV of 3.5%. Of the fasting blood samples, 1.5 mL EDTA-treated blood was preserved for analyses of vitamin B-12 and folate by ion-capture IMx (Abbott Laboratories, Abbott Park, IL). Between-run CV were <5% and <10%, respectively. Methylmalonic acid (MMA) was measured in 0.5 mL plasma by stable-isotope-dilution capillary gas chromatography-mass spectrometry. The between-assay CV was 9%. 25-Hydroxy vitamin D was analyzed in a 0.5 mL serum sample for vitamin D with a between-run CV of 5–10% (19 ). The cut-off value for vitamin D deficiency is <30 nmol/L (20 ). For parathyroid hormone (PTH) analysis, 0.2 mL plasma was determined in duplicate with a chemiluminescence immunometric assay kit (Nichols Institute Diagnostics, San Juan Capistrano, CA).
Data analysis. All statistical analyses were performed by SAS System for Windows, release 6.12 (SAS Institute, Cary, NC). Means and SD, percentages or medians (and their 10th and 90th percentiles) for the total study population were calculated. All analyses were performed for men and women separately, which is the general practice in studies related to BMC and BMD because men and women have a different body composition.
Three different approaches were used to investigate the association of vitamin B-12 status with BMC and BMD. The first approach used Scheffé’s ANOVA procedure to examine differences in mean plasma vitamin B-12 and MMA concentration among groups of subjects having osteoporosis, osteopenia or normal bone health (based on T-scores).
In the second approach forward, backward and stepwise multiple regression analyses with variables possibly related to BMC or BMD were conducted to determine which variables were independent and significant predictors of BMC and BMD for men and women. Forward, backward and stepwise multiple regression analyses revealed the same significant variables explaining the variance of BMC and BMD. The newly composed models with only the variables that were significantly related to BMC and BMD in the forward, backward and stepwise analyses are shown.
In the third approach, prevalence odds ratios (POR) for osteoporosis were calculated. First, subjects with osteopenia or normal bone health were categorized in the normal bone health group for the remaining analyses. This was done because only a small, nonsignificant difference was found in plasma vitamin B-12 concentration between the two groups. Then, three categories of vitamin B-12 concentration were created on the basis of the tertiles of vitamin B-12 concentration in the normal bone health group: vitamin B-12–deficient ( 210 pmol/L), marginal vitamin B-12 concentration (210 < plasma vitamin B-12 320 pmol/L) and normal vitamin B-12 status (> 320 pmol/L). Because there are no generally accepted cut-off points to categorize people with a deficient, marginal or normal vitamin B-12 status, we decided to use these tertiles instead of the cut-off points used or proposed in the literature. The prevalence of osteoporosis was calculated for each of these categories. Prevalence of osteoporosis in the marginal and deficient vitamin B-12 groups was compared with the normal vitamin B-12 group by calculating the odds ratio with multiple logistic regression, i.e., the POR.
We decided a priori to include the continuous variables weight and age as confounders in the adjusted logistic regression model. Weight instead of lean mass and fat mass was chosen because it had the highest correlation with BMD (r = 0.54). Based on the literature (21 ), age was considered to be a confounding factor, although the coefficient of the two vitamin B-12 categories changed only slightly after adjustment for age. Calcium intake was included in the adjusted logistic regression model because the ß coefficient for vitamin B-12 changed > 5% when calcium intake was entered after weight (data not shown).
POR for osteoporosis for women and men with normal, intermediate or high MMA or homocysteine status were also calculated but did not differ significantly. The three categories of MMA and homocysteine concentration were again created on the basis of the tertiles of MMA and homocysteine concentrations in the normal bone health group.
Of the participants, 11% had been using supplements in the past year before the interview took place. Eleven participants had been using a B complex, one woman used a vitamin D supplement and six participants used a calcium supplement. To exclude an effect of supplement use on our results, all analyses were repeated with only the participants who had not been using supplements. No differences were observed between these results and our main results (all participants), i.e., the results were the same for both analyses (including the significant results). In addition, we repeated the analyses and adjusted for supplement use. This alteration also did not change our results. Therefore, we show here only the results of all participants without exclusion of or adjustment for supplement use. The level of significance was P < 0.05 for all analyses.
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RESULTS |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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The mean age of 194 participants included in the analyses of the study was 78 y. Most of the participants (74%) were women. The physical activity score was similar for men and women (Table 1 ). Almost 70% of the participants were living alone. The majority of the study population reported one or more diseases (89%) and use of medicine(s) (73%). Of the participants, 11% were single supplement users. Only 11% currently smoked. Self-reported fractures in the last 5 y tended (P = 0.233) to be more frequent in women (16%) than in men (7%).
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All body composition variables were significantly lower in women than in men, except for body fat mass, which was significantly higher. Apart from a higher vitamin B-12 and lower Hcy concentration in women than in men, there were no significant differences in biochemical variables between men and women. Forty-four percent had a vitamin D deficiency. Due to practical reasons, biochemical values were not available for all participants (Table 1) .
Vitamin B-12 and MMA concentrations in the different screening categories for osteoporosis (approach 1).
According to the WHO screening categories (16 ) for osteoporosis, 36 participants were classified as having osteoporosis, 6 men and 30 women. Nineteen men and 69 women were considered to have osteopenia and 25 men and 45 women were classified as normal. Women in the osteoporosis category had a significantly lower vitamin B-12 concentration than women in the normal and osteopenia categories. The MMA concentration was slightly higher in the osteoporosis category for women than in the other two categories. In men, no significant differences were found among the three categories for vitamin B-12 and MMA (Table 2 ). Hcy concentrations were not different in the three screening categories for osteoporosis (data not shown). In addition, no significant differences were observed in vitamin D concentrations among the three screening categories for osteoporosis.
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The relationship of BMC and BMD with biochemical, anthropometric and lifestyle variables was explored using multiple regression models. For both women and men, BMC and BMD were explained mainly by weight (Table 3 for women and Table 4 for men). A relatively small proportion of the variance of BMC and BMD was accounted for by vitamin B-12 and energy intake in women, as indicated by the adjusted R2, which ranged from 1.3 to 3.1%. BMC and BMD had a total R2 of 46 and 22%, respectively. In men, BMC (R2 = 53%) and BMD (R2 = 25%) were explained positively by weight and height (only for BMD), and negatively by smoking.
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Prevalence odds ratios for osteoporosis (approach 3).
Participants were divided into three vitamin B-12 groups: normal, marginal and deficient. The prevalence of osteoporosis was 6% in women in the normal vitamin B-12 group (n = 34). In the marginal (n = 48) and deficient vitamin B-12 groups (n = 30), prevalences in women were 25 and 37%, respectively. The overall mean prevalence for women was 22%. The prevalence of osteoporosis in men was 10% in the normal group (n = 10), 40% in the marginal (n = 14) and 5% in the deficient group (n = 22). The overall mean prevalence for men was 13%.
Compared with the normal vitamin B-12 group, the POR for osteoporosis in women was 4.5 [95% confidence interval (CI): 0.8;24.8] times higher in the marginal vitamin B-12 group and 6.9 (95% CI:1.2;39.4) times higher in the deficient vitamin B-12 group after adjustment for weight, calcium intake and age (Table 5 ). The POR for osteoporosis in men were not significantly increased in the marginal and deficient vitamin B-12 groups compared with the normal vitamin B-12 group. The POR of increased MMA or Hcy were not increased significantly in men or women (data not shown).
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DISCUSSION |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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Population.
Although only frail elderly people >70 y old were eligible for participation, one exception was made (one woman was 66 y old). Compared with the apparently healthy Dutch elderly, the health profile of our frail elderly was poorer. Their mean body weight (66 kg) was lower than that reported in the SENECA study (70 kg) (22 ), in which prevalences of self-reported disease (89%), osteoporosis (22%) and vitamin D deficiency (44%) were much higher than prevalences among apparently healthy Dutch elderly, namely, 54% for diseases (23 ), 7% for osteoporosis (24 ) and 29% for vitamin D deficiency (25 ). Because of their poorer nutritional status, an association of vitamin B-12 status with BMC and BMD might be detected earlier in these frail elderly people.
Methods.
In this study, BMC and BMD were measured by dual-energy X-ray absorptiometry. This method is considered to be accurate and precise in comparison to in vivo or in vitro multiple component methods (26 ). We used the fast scan mode. Data from others did not indicate a difference between fast and medium scan modes (27 ).
The results of BMC and BMD were interpreted together, with size-correction for BMD by predefined indices. According to Prentice et al. (28 ), such correction may cause misinterpretation when identifying determinants of bone mass and fracture risk. Still, many research groups use BMD as a valuable tool for assessing fracture risk and clinical management. We used both BMC and BMD as dependent variables; therefore, we assume that it is justified to use BMD as well in this context.
Classification by T-scores of total body mineral density gives a good indication of bone health (29 ,30 ) because of a high correlation between total body BMD and BMD of other regions, such as femur. In this study, these criteria were used for both women and men, because there are no specified and defined criteria for men. The use of T-scores, however, remains questionable for men because the scores were originally designed to classify female subjects.
There are indications that diabetes or rheumatoid arthritis might be associated with bone health (31 ,32 ). It is not likely that these diseases interfered with our results because diabetes (n = 11) and rheumatoid arthritis (n = 35) were evenly distributed among the three screening categories for osteoporosis. Alcohol intake has also been associated with osteoporosis (33 ). Because alcohol intake was very low in our study, we could not examine its relationship to BMC and BMD.
Data on energy intake were obtained from 3-d dietary records. This method was selected because of its extensive and structured approach to assess energy intake in elderly people. Although it may underestimate true dietary intake in elderly people (34 ), its influence on our results is assumed to be mainly of a systematic nature because many factors affect underreporting; therefore, it should not affect our results. In addition, underreporting should be similar for all participants.
The physical activity level was determined with the Physical Activity Scale for Elderly. The PASE has been validated by the doubly-labeled water method and confirmed as a reasonably valid method with which to classify healthy elderly people into categories of physical activity (18 ).
Results of vitamin B-12 status in relation to (indicators of) bone health.
The results supporting our hypothesis of vitamin B-12 in relation to (indicators of) bone health emerge from the three different approaches applied in this study. The first indication of a relationship between vitamin B-12 and bone health evolved from differences we observed in vitamin B-12 levels among three screening categories for osteoporosis in women. In men, no significant differences in vitamin B-12, MMA and Hcy concentrations were found.
In our second approach, plasma vitamin B-12 explained the variance of BMD (3.1%) in women in our multiple regression models. Peak bone mass is determined up to 60–80% by genetic factors, age and sex; other modifiable factors can explain only the remaining 20–40%. A small increase or decrease in these factors may have an influence on fracture incidence, e.g., a decrease of BMD of 0.05 g/cm2 is associated with an odds ratio of 1.5 for hip fracture (35 ). Barr et al. (14 ) examined a similar relationship and found that total body fat and vitamin B-12 intake explained 24% of spinal BMD in premenopausal vegetarian and nonvegetarian women.
The multiple regression models for BMC showed similar results. Again plasma vitamin B-12 levels explained a small but significant part of the variance (1.3%) of BMC in women, but not in men. Before our study, we decided to stratify by gender. Biologically, the gender variable is an effect modifier of body composition. In general, data from studies of body composition are analyzed separately for women and men because of the large differences. These differences are natural and independent of our study. In addition, different variables explained the variance of BMC and BMD for women and men. These variables are also of different magnitude. This strengthens our opinion that the gender variable acts as a biological effect modifier of body composition. However, no significant interactions (indicating effect modification) (P = 0.17 and P = 0.37) were observed between gender and plasma vitamin B-12 in the regression of BMC and BMD, respectively. This implies that there are no direct indications of vitamin B-12 influencing BMC or BMD differently in men and women. It is likely that the small sample size of men precluded the ability to observe an association between vitamin B-12 status and BMC or BMD in men.
In men, BMC was explained by weight, height and smoking. It has been shown before that weight and height have a positive influence on BMC. Smoking has a negative influence on bone density and fracture risk (36 –38 ). Our results are consistent with these earlier outcomes.
Calcium intake did not contribute to the total explained variance of BMC and BMD in the complete model, nor did vitamin B-12 concentration. This might have been due to the strong correlation (r = 0.39, P < 0.0001) between calcium intake and vitamin B-12 concentration in women. Therefore, vitamin B-12 concentration could be a marker for calcium intake. On the other hand, the POR for osteoporosis in women was significantly higher in the deficient group even after adjusting for weight, calcium intake and age. This implies that vitamin B-12 concentration might in fact be associated with bone health. The observed association might not be causal, yet vitamin B-12 might be a marker for another (unknown) factor.
According to our third approach, the prevalence of osteoporosis in the marginal and deficient vitamin B-12 groups was higher than that in the normal group for women but not for men. The POR for osteoporosis in women was significantly higher in the deficient group even after adjusting for weight, calcium intake and age.
No other studies have reported the association of plasma vitamin B-12 concentration with BMC and BMD in elderly people. In addition to that, little is known about the association in other groups, such as patients with pernicious anemia, which is regarded as a risk factor for osteoporosis (8 ). In our study, plasma vitamin B-12 seemed to be associated with BMC and BMD in women. There might be a similar clinical effect in men that we were not able to detect. This may be due to the low number of participating men, especially the low number of men (n = 6) classified as osteoporotic. Due to the design of the original study, it was not necessary to recruit more men. Furthermore, it might be that men are less sensitive to an effect of vitamin B-12 deficiency on their bone health. This is speculative because we do not know how vitamin B-12 affects BMC and BMD. Kim et al. (8 ) found that alkaline phosphatase activity (associated with osteoblasts) was increased by vitamin B-12 in a concentration-dependent manner in an in vitro study. They suggested that clinical vitamin B-12 deficiency might be associated with defective functional maturation of osteoblasts. Mulder and Snelder (39 ) showed that supplements of vitamin B-12 and calcium had a positive effect on the BMD of the spine and hip in pernicious, osteoporotic patients (n = 15).
In our study neither significant differences in the MMA concentrations among the three screening categories for osteoporosis (Table 3) nor significant POR for women with different MMA status were found. This might be explained by differences in variation and distribution of the concentrations of vitamin B-12 and MMA. MMA had a narrower concentration range than vitamin B-12; as a consequence, significant results were more difficult to detect. The correlation between vitamin B-12 and MMA in our study was -0.33 (P < 0.001). Forty-eight of 158 people had a deficient vitamin B-12 concentration (<210 pmol/L). Of these 48 people, 32 had also a high concentration for MMA when a cut-off value >0.35 µmol/L was used (15 ). This indicates that MMA is indeed a good marker for vitamin B-12 deficiency. According to the review by Klee (40 ), many groups now recognize MMA and Hcy tests as the most sensitive and specific markers of functional vitamin B-12 deficiency. Usually, MMA increases as a result of deficient or subnormal vitamin B-12.
In conclusion, our study showed that plasma vitamin B-12 is associated with (indicators of) bone health in frail elderly women. This could not be shown, however, in frail elderly men. These results might indicate that the role of vitamin B-12 is most obvious in persons with marginal or poor bone health. In women, the prevalence of osteoporosis was higher in the marginal and deficient vitamin B-12 groups than in the normal vitamin B-12 group. In the future, different populations with different vitamin B-12 status should be investigated. The cause-effect relationship between vitamin B-12 and bone health should be examined. With this improved understanding of the relationship of vitamin B-12 to BMC and BMD, further research should be focused on the effect of extra (supplemental) vitamin B-12 on bone health.
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FOOTNOTES |
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3 Abbreviations used: BMC, bone mineral content; BMD, bone mineral density; BMI, body mass index; CI, confidence interval; Hcy, homocysteine; HRT, hormone replacement therapy; MMA, methylmalonic acid; PASE, Physical Activity Scale for Elderly; POR, prevalence odds ratio; PTH, parathyroid hormone.
Manuscript received 7 July 2002. Initial review completed 14 August 2002. Revision accepted 20 November 2002.
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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