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3 Department of Exercise and Nutrition Science, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY 14214; 4 Department of Epidemiology and Cancer Control, Division of Cancer Prevention and Population Sciences, Roswell Park Cancer Institute, Buffalo, NY 14263; 5 Department of Social and Preventive Medicine, School of Public Health and Health Professions and 6 Department of Gynecology-Obstetrics, School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY 14214
* To whom correspondence should be addressed. E-mail: jww{at}buffalo.edu.
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ABSTRACT |
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 TOP ABSTRACT IntroductionMethodsResultsDiscussionLITERATURE CITED |
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Introduction |
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TOPABSTRACTIntroductionMethodsResultsDiscussionLITERATURE CITED |
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50 y of age, including 30 million women, are affected by the disease (2). As the population ages, the number of individuals at risk for fracture increases and can result in a national economic burden. The need for prevention, early detection, and treatment of osteoporosis is crucial (3). Currently, the gold standard assessment for measuring bone mineral density (BMD) and predicting fracture risk is dual-energy X-ray absorptiometry (DXA) (4). It is a useful assessment for osteoporosis, especially if findings encourage individuals to modify lifestyle factors shown to prevent or treat the disease (5,6). An important modifiable factor associated with the increased risk of osteoporosis is low calcium intake (5,6). Calcium intake from either dietary and/or supplemental sources is a critical nutrient in attaining peak bone mass and for maintaining bone mass over time. Recently, trial evidence showed that calcium plus vitamin D intake can help prevent fracture in postmenopausal women, especially in women at older ages (7).
Data from the NHANES indicate that calcium intake in most postmenopausal women is below the current guidelines of 1200 mg total intake daily (8–10). Research published to date have been largely cross-sectional and have not provided data for dietary and supplement intake of calcium (11–14).
The objective of our study was to assess the influence of knowledge of DXA results on postmenopausal women's decision to increase dietary and/or supplemental calcium intake in an at-risk group of postmenopausal women with no prior knowledge of their bone density. We hypothesized that the results of an osteoporosis screening would influence calcium intake, and that the increase would be greatest among women with the worst T-scores.
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Methods |
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TOPABSTRACTIntroductionMethodsResultsDiscussionLITERATURE CITED |
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Baseline visit.
At baseline, participants completed questionnaires designed to obtain health history and known risk factors for osteoporosis and periodontal disease, current medication and supplement use, and a FFQ. Bone density was determined for the spine, hip, forearm, and total body using DXA (Hologic QDR-4500A). An oral health examination was also completed. Following the study visit, participants as well as their health care providers, were mailed a copy of their DXA results including a summary cover sheet. The cover sheet included a definition of T-score, T-score interpretation guidelines, T-score WHO definitions for normal bone, osteopenia, and osteoporosis, and the participant T-scores for 4 sites (anteroposterior spine, lateral spine, femoral neck, and total forearm). Based on WHO definitions, osteoporosis was defined as a T-score of 
–2.5, osteopenia as a T-score of <–1.0 to >–2.5, and normal with a T-score of –1.0 (16).
One year follow-up. One year after the baseline visit, participants were mailed a follow-up questionnaire assessing their activities following DXA screening. Questions were asked regarding prescription medication intake (17), dietary and lifestyle changes. The findings related to calcium intake are the focus of this paper. Participants were asked whether they had discussed the DXA results with their health care provider, whether they received recommendations from their provider regarding calcium intake, and whether they followed the recommendations. In those without a physician recommendation, participants were asked whether they personally decided to increase calcium intake. Participants returned completed questionnaires in an enclosed postage-paid envelope. To optimize response rate, a second mailing, postcard reminders, and telephone follow-up were done. Follow-up questionnaire data were combined with existing data from the Women's Health Initiative Observational Study and the Risk Factors for Osteoporosis and Oral Bone Loss Study to form the final data set for analyses. Response rate was excellent with 95% of women completing the follow-up questionnaire.
To assess the influence of an osteoporosis screening in a group of postmenopausal women unaware of their bone density status, participants with previous bone density screening, who were taking an FDA approved drug for prevention or treatment of osteoporosis at screening (other than hormone therapy), or who had a diagnosis of osteoporosis prior to participating in the study, were excluded from these study analyses. Women belonging to ethnicities other than Caucasian were excluded because the guidelines for prevention and treatment of osteoporosis primarily address Caucasian women. Also, after exclusions, the number of subjects belonging to ethnicities other than Caucasian was low (n = 22), which would not allow for meaningful analyses of ethnicities. The final analytic set included 923 women.
Statistical analysis.
The Statistical Package for the Social Sciences (SPSS), version 13.0 for Windows, was used for all analyses. Descriptive statistics were computed for demographic variables as well as T-score level (lowest of 4 sites reported), calcium supplement intake (mg/d), dietary calcium intake (mg/d), and other variables. Tests of significance included chi-square for categorical variables and ANOVA for continuous variables. Post hoc comparisons were performed to determine the individual associations found on these analyses using Scheffé (ANOVA) or individual chi-squared comparisons for categorical variables. For comparisons by change in calcium intake (yes/no), 2-sample t tests and chi-square tests were conducted. Univariate logistic regression models were developed to establish factors associated with a change in calcium intake that were further analyzed in a multivariate model. Factors assessed included age (y), BMI (kg/m2), number of current medications (prescription and over-the-counter), dietary calcium intake (mg/d) at baseline, calcium supplement intake (mg/d of elemental calcium; yes or no) at baseline, total calcium intake [dietary plus supplement (mg/d); <800 mg/d, 800–1200 mg/d, or >1200 mg/d] at baseline, T-score level (lowest of the femoral neck, lateral spine, anteroposterior spine, and total forearm T-scores), fracture history after 40 y of age (yes or no), family history of adult fracture (yes or no), cigarette smoking (never, former, current), education (high school, college, or graduate school), income ($50,000 or <$50,000), marital status (never married, divorced or separated, widowed, married, or living in a marriage-like relationship), routine medical care (>1/y vs. 1/y), hormone therapy use (never, former, or current), and follow-up consultation with a health care provider (yes or no). Variables assessed in the multivariate logistic regression model included those that were associated (P 0.20) with the outcome in univariate analyses. To establish the final predictive model, analyses were performed using a backward stepwise approach with variables significant at the P 0.05 level retained.
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Results |
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Discussion |
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TOPABSTRACTIntroductionMethodsResultsDiscussionLITERATURE CITED |
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It is of serious concern in our study that 84% of women who were unaware of their BMD status were found to have at least one site consistent with either osteopenia or osteoporosis according to WHO criteria. Therefore, these women did not know of their increased risk of osteoporosis-related fracture and were unlikely to have taken appropriate treatment measures for the disease.
Comparing our study to the NHANES III (1988–1994) results regarding osteoporosis prevalence in the general U.S. population, NHANES III estimates the prevalence of osteoporosis at the femoral neck in noninstitutionalized Caucasian women 50 y of age to be 20%, and the prevalence of osteopenia at the same site among the same population to be 52% (18). Using our study data for the femoral neck measures only, we found a lower prevalence of osteoporosis (8%) and a prevalence of osteopenia (52%), which compared similarly with NHANES III. However, because we measured several sites, the overall increased prevalence of osteopenia and osteoporosis in our study was higher.
Of women who had osteoporosis, 53% increased their calcium intake compared with 43% of those with osteopenia and only 24% of those with normal bone density. This is an important finding with public health implications for screening programs. An effective screening program must not only be predictive of future disease but also influence decisions about lifestyle behaviors for prevention and treatment of the disease. Although many women chose not to change their calcium intake, this may be mediated by the fact that many of these participants were consuming more than the daily recommended intake of 1200 mg/d of calcium.
Women with osteopenia were 
2.5 times as likely, and women with osteoporosis were 3.5 times as likely, to make changes to their calcium intake than women having normal T-score results. Of 523 women who did not make a change in their calcium intake, 30% were osteoporotic and 58% reported consulting a health care provider. It may be possible that those women received recommendations from their health care provider to initiate alternative treatment(s) and did so without also addressing other changes such as increasing calcium intake. High calcium intake combined with drug therapy significantly benefits bone mass than when it is taken alone; therefore, health care providers who recommend that women initiate drug therapy for osteoporosis without also recommending higher calcium intake, are a concern (19). Of note, 68% of 923 women in our study reported a follow-up consultation with a health care provider. Of those who consulted with their health care provider, 48% received a recommendation to start or increase their calcium intake, and 96% reported following this recommendation (data not shown).
Women who had lower daily calcium supplement intake were more likely to change their calcium intake after screening. Interestingly, women who reported greater use of calcium supplements were 1.5 times as likely to make a change in their calcium intake (data not shown). A possible explanation for this association could be that women who, prior to screening, were already taking precautions for osteoporosis by maintaining preventive health behaviors would also be inclined to enhance those health behaviors especially if their BMD test results were below normal. It may also be that those who were already taking supplements at baseline may be more likely to take more.
An important finding is that women who discussed their BMD results with a health care provider were 3.5 times more likely to change their calcium intake after osteoporosis screening. This indicates the importance of health care providers in making health-related recommendations, including lifestyle modifications. Rubin and Cummings (11) concluded that results of BMD testing can greatly influence postmenopausal women's decisions to increase calcium intake and these decisions are greatly influenced by a discussion of results with a physician. In our study, women with osteopenia or osteoporosis were more likely to consult with their health care provider, which increased the likelihood of recommendations for prevention and/or treatment of the disease that women were more inclined to follow.
Several variables were tested in univariate analyses and not found to be associated with a change in calcium intake in our study. Age was not associated with women making a change in calcium intake after osteoporosis screening. Marci et al. (13) also found that age, education, and history of osteoporosis, were not associated with starting calcium supplements. In addition, Rubin and Cummings (11) found that education was not associated with behavioral changes. Education was not associated with change in our study, which involved a group of highly educated women, although it could be predicted that more highly educated women would be more likely to initiate or change health behaviors associated with disease. Perhaps age itself is not associated with calcium intake. Also, highly educated women may be more knowledgeable about osteoporosis, and by previously following preventive measures for the disease, they do not feel the need to change their behaviors.
In multivariate analysis, the T-score level was found to be an independent predictor of change in calcium intake among postmenopausal women. After adjusting for other variables, the point estimates for T-score categories remained nearly identical to the unadjusted OR. This finding shows that T-score level is a strong and significant predictor of change in calcium intake.
The association of screening results on postmenopausal women's decisions to increase calcium intake have been well demonstrated in previous studies, of which the study by Rubin and Cummings (11) was the first. They found that women with below-normal BMD were 3 times as likely to start or increase calcium supplementation and increase their consumption of milk or calcium-rich food. Marci et al. (13) found that BMD results were the most significant predictor of changes in calcium intake, and, in a recent study by Rohr et al. (14), there was a significant increase in calcium-supplement intake in postmenopausal women with low BMD. Other studies report an increase in calcium intake after screening; however, these studies had a limited baseline evaluation and therefore no assessment of change (20–22), they did not use DXA the gold standard for BMD measurement (20,23), and they had a study population that included premenopausal women (20,22,12).
We acknowledge several limitations in our study. First, our study was restricted to a Caucasian, self-referred population; therefore, results can be generalized only to this group. Another limitation associated with this type of study, was that the women who chose to participate in this health-oriented study were well-educated, with most having completed college or graduate school education. As a response to their DXA results, these women may be more likely to change their calcium intake, which may affect study results. It is not clear whether less-educated women would have made similar changes. There is also a possible bias arising from self-reports of dietary and supplemental calcium intake in both the baseline and follow-up questionnaires. This may have resulted in an overestimation and/or underestimation of calcium intake among women. Our study did not evaluate a change in vitamin D intake, which, when combined with calcium, has been shown to improve bone mineral density (7,24).
Despite these limitations, our study had a number of strengths. To our knowledge, it is the first study to examine the influence of osteoporosis screening on dietary and calcium-supplement intake of postmenopausal women in a population sample of this size and with this completeness of personal characteristics, demographics, and dietary intake at baseline and follow-up. Our study also used a sample of women who did not undergo screening because of their risk of osteoporosis or physician referral. Future research may expand the outcomes to determine whether other behavioral changes might be associated with bone density screening, including change in vitamin D intake and exercise.
In conclusion, this study demonstrated that many postmenopausal women are unaware of their bone density status. Knowledge of bone density and T-score was a strong and independent predictor of increased calcium intake. Discussing DXA results with a health care provider does appear to increase the likelihood of calcium increase as well. This study provides evidence that osteoporosis screening and, importantly, physician-initiated education play imperative roles in influencing health behaviors that can prevent further bone loss and fracture.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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2 Author disclosures: K. M. McLeod, S. E. McCann, P. J. Horvath, and J. Wactawski-Wende, no conflicts of interest.
Manuscript received 4 April 2007. Initial review completed 9 May 2007. Revision accepted 30 May 2007.
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LITERATURE CITED |
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