A meta-analysis derived from source-data on the short-term effects of a glyconutrient supplement on bone mineral density.
One of the goals set forth in the National Institutes of Health's Office of Dietary Supplements, (ODS) 2004-2009 Strategic Plan, is to stimulate research on how dietary supplements can enhance the biomarkers of optimal health and improved performance. One area where dietary supplements offer a potential for improved performance and optimal health is in addressing the progressively declining state of Americans' bone health, a problem set forth in the U.S. Surgeon General's (SG) 2004 Bone Health Report to the Nation. The SG reported that inadequate nutrition, increasingly sedentary lifestyles, poor health literacy among adolescents, and an increasingly aging population, have "... placed America's bone health in jeopardy." To address this problem, the SG issued a "call to action" for the researchers and the healthcare industry to develop programs that can help reverse this trend by developing bone-health programs based on three fundamentals: (1) improved health literacy, (2) increased physical activity and (3) improved nutrition.
The objective of this paper was to conduct a meta analysis to assess the extent to which using glyconutritional supplements (GLC) led to improved bone health by maintaining or facilitating increased bone mineral density (BMD).
Design, Setting, and Participants
All subjects were free-living community-dwelling adults who were recruited for a variety of clinical trials over approximately the same time period, from the same population base, were tested by the same group of technicians using the DEXA technology, and had similar baseline body composition measurements.
Comparisons were made between BMD changes found in participants consuming glyconutritional supplements with expected changes and changes in placebo and control groups, as well as subjects using different dietary supplements in the researcher's database.
Main Outcome Measures
Measurements were obtained from 1,056 subjects who completed the same beginning and ending BMD test using the same Dual Energy X-ray Absorptiometry (DEXA) equipment. All data were adjusted to a common 75-day study period.
Within-group analyses of the group taking glyconutrients revealed that the age, gender and ethnic differences were highly consistent with the differences found by other investigators. In contrast to an expected or predicted decrease in BMD, all five groups increased their BMD during the study period, although, using a repeated measures t test, the within-group change in the CTL and DIS failed to reach statistical significance. The increase in BMD in the GLC was statistically greater (P <0.001) than that found in all groups, a difference magnified when adjusting for baseline differences in BMD. Analysis of a small randomized, placebo-controlled double-blinded five-group pilot study of ~ 10 participants per group revealed that while small decreases in BMD were found in the PLA, the three treatment groups showed increased BMD. The GLC group had 0.006 g/[cm.sup.2], 3.2% annualized change, although this increase failed to reach statistical significance. It was concluded that supplementation with glyconutrients when combined with a lifestyle behavior modification program could increase bone density.
These data suggest the intriguing possibility that consumption of glyconutrients with an accompanying behavior modification plan can lead to short-term increases in BMD. In addition to highly consistent within-group differences in age, gender and ethnicity, the increases in BMD found in the GLC were significantly greater than those found in the PLA, CTL and DS groups, in spite of the fact that the GLC group was older and lost more body weight than the other groups--differences that typically decrease BMD. It seems reasonable to conclude that the dietary supplements used in this study can lead to short-term increases in bone densities.
Declining bone health is a common, progressively debilitating skeletal change characterized by decreased bone density and disrupted bone architecture. It has been estimated that over 200 million people worldwide suffer from severely declining bone health, a number that continues to escalate among the world's increasingly aging population. (1) Using age and bone mass as predictors of fracture, it has been estimated that a 50-year old woman has about a 50% risk of fracture at some point in her life. (2) Declining bone health constitutes a major wellness problem in developed world countries, as well as causing a progressive decline in quality of life. (3) For example, nearly 1.3 million fractures occur per year in the United States, with a cost of treatment in excess of $10 billion per year--costs that are expected to more than double over the next 50 years unless effective programs of prevention and treatment can be developed. (4), (5)
Other countries report similar statistics. Throughout the world, declining bone health is imposing a growing financial burden on health services, due to reduced mobility, hospitalization, nursing home requirements, and overall quality of life. (6) In the European Union, it is estimated that by 2050 problems associated with declining bone health will pose a major threat to healthcare services. (7) Similar problems are being experienced in the United Kingdom and Wales and are projected to result in $742 million per year in health-care costs. (8) In Italy, the progressive aging of the Italian population is also placing a growing threat to healthcare costs. (9) Declining bone health and its impact on wellness and quality of life is a significant health risk in China, (10) Japan, (11) Korea and Taiwan (12) and is predicted to become an increasing public burden. Although the incidence of problems associated with declining bone-health in Asia is currently lower than in western nations, their problems are expected to become more acute with aging Asian populations, an expected decrease in physical activity, and westernization of Asian lifestyles. The healthcare costs posed by this serious economic threat could cripple the future development of these countries. (13), (14) The disability from a hip fracture can be very severe over protracted periods of time. In a study of patients who were ambulatory prior to a hip fracture, 25% subsequently required long-term care. Six months after the fracture, only 15% of patients could walk across a room unaided, and 24% over the age of 50 died in the year following the fracture. (15) In the Fracture Intervention Trial over an average study period of 3.8 years, 6,459 women aged 55 to 81 years of age had significantly increased age-adjusted relative risk of dying following any clinical fracture. Hip fractures among a relatively healthy group of women increased the relative risk of dying almost six-fold and risk of spine fractures nine-fold, compared with fracture-free periods. Almost half of these deaths were within a year of fracture. (16), (17)
Pharmacological agents used to improve bone health include antiresorptive agents such as bisphosphonates, selective estrogen receptor modulators (SERM), ralozifene, and calcitonin; bone-forming agents such as flurode and parathyroid hormone; and, more recently, a new entity, strontium ranelate "... with proven anti-fracture efficacy..." which increases bone strength, formation, resorption and long term BMD. (19), (20), (21), (22), (23), (24), (25) However, despite compelling evidence that a variety of pharmaceutical agents reduce the incidence of new fractures from 30% to 50%, successful adherence to treatment regimens has been poor, even among women who have had previous fractures. In one study, only 25% of women with a history of fracture were using preventive therapy (1), a finding consistent with a study in France where only 35% of elderly patients adhered to treatment regimens following their first low-impact peripheral fracture. (26) Despite these treatment options to reduce the risk of fracture in patients with decreased BMD, few patients fully adhere to current therapies, (27) which is having a profound negative effect on the healthcare system. For example, it has been estimated that 10% of hospital admissions and 20% of nursing home admissions are related to poor adherence to treatment regimens. (28) In another study, a group of researchers examining a new pharmaceutical agent (Denosumab) concluded that one-year adherence rates for all therapies designed to improve bone health were less than 25%. This adherence rate is substantially lower than that for therapies for other asymptomatic conditions, such as hypertension (50 to 70 percent adherence). These researchers conclude that "... new treatment approaches that engender high adherence are needed." (29)
Even when new treatment approaches are developed, the cost of medication, the need for visits to physicians and concerns about the adverse effects of medication will still have a negative impact on adherence. One alternative to reducing these factors is to reduce the need for treatment programs and to reframe BMD as a continuum ranging from optimal health to disease. This goes beyond the almost universal recommendation that the use of pharmaceutical agents be accompanied by lifestyle changes in diet and exercise that are most likely to help maintain or slow down the loss of bone mass. These are changes that are recommended for people of all ages, including children and adolescents. (30) For a great number of people, declining bone-health is a geriatric disorder with a pediatric origin. Becoming aware of the risk factors for declining bone health and initiating early lifestyle changes will facilitate increases in BMD prior to the mid-thirties when bone mass is thought to reach its peak. (31) The NOF's suggestion is supported by a USDA study that found 85% of teenage girls, and 65% of boys do not consume sufficient calcium and bone building nutrients during the years when almost 90% of their bone growth takes place. When improved dietary and exercise habits are made, they have the added benefit of slowing down or reversing sarcopenia (age-associated atrophy of muscle mass) (32), (33), (34), (35), (36) and thereby reducing the risk of fractures.
Instead of focusing on prevention and treatment of osteoporosis, a more appropriate goal for the nutrition industry appears to be in the development of diet and exercise interventions to facilitate "structure and function" changes in BMD in order to facilitate optimal health. BMD is not a measure of osteoporosis any more than cholesterol is a measure of heart disease, or blood pressure is a measure of hypertension. As one researcher put it:
"We need to recognize that all of these values reflect a continuum of risk--the higher the blood pressure or lipid levels, or the lower the BMD, the greater the risk of the complication. At some point, the risk is high enough that an intervention [treatment] is warranted to lower risk. Inexpensive interventions, such as lifestyle alterations involving diet, exercise ... can be applied to lower risk in virtually everyone at even minimal risk." (37)
This is a lesson that both clinicians and researchers are learning about BMD, and is one that has been apparent in other diseases for some time. BMD is on a continuum ranging from optimal health to disease, and a far greater number of people have low BMD than have the disease of osteoporosis. For example, it is well-known that the probability of fracture is greater with osteoporosis than with osteopenia (low bone density) but, as one researcher points out, "Osteopenia is not a disease." (69) The World Health Organization added the term osteopenia to allow consistent communication comparison of prevalence of these conditions across populations and was not intended for use in making treatment decisions. (70) However, more healthcare dollars are spent on bone fractures among people with osteopenia than osteoporosis, because many more people have osteopenia than have osteoporosis. Thus, programs and products designed to reduce osteopenia may have a greater healthcare payoff than "treating" or "preventing" osteoporosis. It would also be consistent with the DSHEA act, with recommendations in NIH's Office of Dietary Supplements' (ODS) recent strategic plan, (38) and with the U.S. Surgeon General's (SG) "call to action" in the first-ever bone health report. (39)
In it's 2004 strategic plan, one of the ODS's five scientific goals is to stimulate research on (1) "...how dietary supplements moderate, alter, or enhance the... maintenance or lack of optimal health," and (2) "... validation of the accuracy, sensitivity, and specificity of unique biomarkers of dietary supplement effects on known endpoints and their surrogates associated with... optimal health, and improved performance." (38) [emphasis added] This emphasis on optimizing health is consistent with the previous discussion of using BMD as a measure of bone health as opposed to bone disease. Even more specifically, it is a direct response to the SG's report that "the absence of adequate nutrition during the adolescent critical bone-building years has placed America's bone health in jeopardy." To address this problem, the SG issued a "call to action" for the researchers and the healthcare industry to "...get started by taking action today in homes, health care settings, and communities across our nation. Remember, you are never too old or too young to improve your bone health." (39) The SG specifically encourages research designed to increase bone health through plans integrating: (1) improved diets, (2) increased physical activity, and (3) improved "health literacy."
Although the SG specifically calls for increased intake of calcium and vitamin D, in mid-February 2006, widespread media attention was directed toward a study reported in the New England Journal of Medicine (40) that raised doubts about the value of supplementation with calcium and vitamin D for bone health. While an editorial critique of the study in the same issue of the journal (41) pointed out a number of serious flaws in the study, the general consensus of this and other reviewers is that calcium and vitamin D are "only the ante for bone health" and the maintenance or attainment of optimal health must include other bone-building nutrients and increased physical activity.
In late 1994, we began measuring changes in body composition in people consuming glyconutritional supplements in several short-term studies that were subsequently integrated into the Nutraceutical-Intervention Longitudinal Trials. (42) The trials began with several short-term studies assessing body composition using underwater immersion testing (displacement method), which was soon replaced with the Dual Energy X-ray Absorptiometry (DEXA). DEXA also provided an assessment of bone mineral density (BMD) along with its body composition measurement. This manuscript is a meta analysis of all available studies on changes in DEXA-derived BMD in which participants used glyconutritional supplements and a pedometerbased behavior modification program (the LGWP) that incorporates the three components of bone health recommended by the SG. Comparisons are also provided between study groups within and outside the meta analysis where deemed appropriate.
Glyconutrients are not vitamins, minerals, amino acids or enzymes, but are in a class of their own as nutritional supplements. The ones used in this study were derived from the aloe vera plant and are being marketed by Mannatech, Inc., Coppell, Texas. They are classified as plant monosaccharide carbohydrates, eight of which are thought to be essential to human bodily functions: xylose, fucose, galactose, glucose, mannose, N-acetyglucosamine,, N-acetylgalactosamine, N-acetylneuraminic acid (a sialic acid). These glyconutrients combine with other molecules, including proteins and lipids, to form glycoforms or glycoconjugates which coat cell surfaces. When they combine with protein molecules, they form glycoproteins that coat the surface of every cell with a nucleus in the human body. When glyconutrients bind with lipids (fats) they form glycolipids which also adhere to the cell surface. Glyconutrients are thought to be the key to effective cellular communication and proper cell function
Measurements were obtained from 1,056 subjects who completed the same beginning and ending DEXA test. Each of these subjects participated in one of five study groups. Participants in all groups were provided with a detailed informed consent form and, prior to giving consent, were asked to review the study requirements with their personal physicians to ensure they had no medical conditions that would preclude their participation. Pregnant and lactating women were excluded and women who became pregnant during the study were asked to withdraw.
Dual Energy X-ray Absorptiometry (DEXA)
All BMD measurements cited in these studies were derived from DEXA measured total body scans, the "gold standard" for BMD measurement. (43) DEXA involves the use of 2 x-ray beams that are aimed at the bone. A computer analyzes the amount of energy that passes through the bone and uses the measurement to calculate BMD. The test takes about 20 minutes and involves a low exposure to radiation. In addition to providing an accurate baseline BMD measurement, it is a valuable test for monitoring BMD changes over time. (43)
The test exposes the participant to 0.02 mR of radiation during each scan. This level of exposure can be compared to the 125mR/year that is normally received from non-medical background radiation (less than that one would receive in a transcontinental flight). DEXA has been found to be safe for children and adolescents (44) The average annual background radiation exposure associated with a DEXA scan is generally less than 1 day of natural background radiation exposure. Using estimates derived from total body irradiation, one DEXA test would increase the risk of cancer by less than 0.0001 %. (45) The National Council of Radiation Protection and Measurements has recommended maximum permissible radiation dose levels for various categories of individuals is 50,000 mSv/yr (5000 mR/yr). (46) The annual effective dose limit of infrequent exposure of the general public that would include children is 5,000 mSv/yr, which even with a series of 50 DEXA scans during a calendar year would be well below this annual limit for children. (45)
A number of studies have shown that DEXA correlates highly with actual skeletal mass, with a typical precision error for total body bone mineral content of less than 1%. In our own study of the accuracy of DEXA bone density, we found the error to be less than 1% (0.89%). (47), (48), (49), (50) In addition to being used to evaluate a variety of clinical disorders, DEXA's reliability makes it possible to monitor the effects of relatively small changes during short-term interventions. (51) It can also be used to measure total body bone density, which offers the advantage of providing an indication of density in the arms, legs, trunk, pelvis and spine. Studies over the last 5 years using DEXA have shown that it accurately measures fat and lean content in meat samples and animal carcasses. Dozens of studies have shown the DEXA compares well with non-invasive approaches such as neutron activation and hydro-densitometry. (52) Extensive reviews of the use of DEXA in the management of bone health and a detailed review of the physical concepts are presented elsewhere. (53)
A meta analysis was conducted of all weight loss studies in which participants completed beginning and ending DEXA tests in 60-to 90-day study periods during the same time frame as studies of glyconutritional supplements were conducted. Participants were randomly assigned to either non-intervention control groups, to groups in which they took dietary supplements, or to placebo groups.
Following a procedure that ensured high compliance in prior studies, (50) enrollees were asked to provide a "conditionally refundable" $100-$150 deposit that would be returned upon completion of all post-study tests, irrespective of their level of adherence to the protocol requirements. Participants were advised that their checks or credit card vouchers would not be processed unless they failed to complete the ending tests. After completing their baseline tests, participants were provided with a copy of their test report along with an explanation of how to read and interpret their results. The same procedure was followed upon completion of the ending tests. Participants were recruited from people responding to television and radio news stories describing the studies, from existing databases of people who had participated in previous studies, or were referred by people who enrolled in the studies. Once accumulated and entered into a database, all data were audited and verified by a team of three independent researchers. All tests were completed on one of two DEXA units by one of four technicians who received the same training and were supervised by the principal investigator.
The Living at Goal Weight Behavior Modification Program (LGWP)
With the exception of the non-intervention control groups, all participants were asked to use a pedometer-based behavior modification program. (47), (48) The Living at Goal Weight Plan (LGWP) asks participants not to follow a temporary diet, but rather to adhere to a dietary plan and physical activity level appropriate for their individual goal weight. Dietary intakes, nutritional profiles, and physical activity levels are based on the participant's fat-free mass (FFM) as measured by DEXA. The plan assumes that a participant will maintain initial FFM while depleting only excess body fat. Participants begin their program by practicing behaviors they must always maintain if they are to live at goal weight. Upon reaching goal weight, the participant just continues these behaviors. The traditional two-phase diet-maintenance model is abandoned and replaced with a maintenance-only model.
Participants were provided with a workbook outlining general procedures for living at goal weight, instructions and materials for estimating caloric and fat intake, and a daily log for calculation and recording of daily calorie balances. To monitor and encourage physical activity, participants wore a pedometer (49) and recorded the displayed daily number of steps taken. For activities that were not conducive to wearing a pedometer, participants were provided with a step-equivalent chart that enabled them to estimate the level of expenditure for that particular activity. That number was then added to the number of steps displayed on the pedometer.
The Meta Analysis Groups
Expected Change: To obtain an expected, or predicted change in BMD g/[cm.sup.2] for the 75-day duration of the study period for the gender and average age of study participants, data were obtained from three sources: the NOF, n=1,070, -0.0025; the manufacturer of the DEXA equipment (GE Lunar), n=2,833, -0.005; and from our data base, n=9503, -0.002. The average of these data is -0.0027 which is consistent with previously published studies.
Control: (CTL) (n=131) After completion of their baseline testing, participants in this group were randomly assigned to a non-intervention control group in which they were asked to pursue any program of their own choosing and to complete a second DEXA test at the end of the study period.
Dietary Supplements (DS): (n=191) Participants included a combination of three sub-groups who all followed the LGWP while taking three different dietary supplements.
Placebo: (PLA) (n=239) Participants in this group followed the LGWP and took placebo capsules that contained dicalcium phosphate providing what is believed to be a non-therapeutic (<50 mg/d) amount of calcium.
Fitness Clubs: (FC) (n=127) Participants for this group were recruited from two fitness clubs in a national chain. They followed the (LGWP), consumed dietary supplements, and participated in an exercise program at the club 3 days per week. The program, supervised by a personal trainer, consisted of a 5-minute warm-up, 30 minutes of aerobic activity, and two sets of standardized resistance training. This group was provided with dietary supplements from the clubs in the form of a muscle-supporting protein/carbohydrate drink mix (1/d), chewable wafers for an energy snack (4-6/d), and a comprehensive vitamin/mineral/phytonutrient to help maintain FFM.
Glyconutrients: (GLC) (n=196) In addition to the LGWP, participants in this group were asked to consume three nutraceutical supplements with each meal. (54), (55), (56), (57), (58) These supplements consisted of two capsules comprised of the known natural saccharides required to complete glycoprotein and glycolipid synthesis. A dietary supplement caplet containing freeze-dried dioscorea species extract providing plant sterols as a precursor was also taken with each meal. Additionally, one capsule of phytonutrients derived from twelve species of freeze-dried, plant-matured, fruit and vegetable powder that were formulated into a dietary supplement capsule was added to meals.
In numerous studies, BMD has been found to decrease with advancing age and, although not as well-researched, with weight loss. Therefore, in addition to an expected small decline in BMD with age, weight loss would also tend to decrease BMD unless it was offset by increased physical activity and improved dietary habits. To confirm the expected age-and weight-related decrease in BMD, data were analyzed from the tests in our database. These data were also used to develop a predicted rate of decline during the 75-day study period. A third estimate was derived from a number of studies, including the National Osteoporosis Foundation's conclusion that BMD increases until age 33, remains constant until the early forties, and then declines at an accelerating rate averaging 1.0% a year for women and .8% for men. For example, if the BMD for a group was found to increase by .0034 g/[cm.sup.2] but the expected change was a decrease of -.0010 g/[cm.sup.2] the net change would be .0044 g/[cm.sup.2], not .0034 g/[cm.sup.2]. Data from our database were also analyzed to examine the relationship between BMD and body weight and FFM. BMD changes in all study groups were adjusted to the same 75-day study period and between-and within-group comparisons were made using students' t tests.
Figure 1 depicts the expected change in g/[cm.sup.2] for the average age and gender of study participants adjusted to a common 75-day study period along with the changes found in each of the five groups in the meta analysis.
Table 1 shows the results of the statistical comparisons that were made between the groups. As shown in lines 1-7 the groups are very similar on baseline body composition measurements. The one exception is baseline BMD (Line 4) in which the GLC, the oldest of the groups, had an expected lower BMD than any of the other four study groups-a difference that was statistically significant in all comparisons (P<0.001). To adjust for these differences, in addition to the changes in g/[cm.sup.2] shown in Table 1, an additional calculation is shown on Line 8 which reflects the commonly used "annualized % change" for each of the groups. This calculation reveals an even greater increase in BMD in the GLC as compared to the other four groups. Lines 10-14 show the P values for students' t tests between each of the study groups. In all between-group comparisons, the change in BMD for the GLC was statistically significant (P< 0.001). Additionally, the P values shown on the diagonal are from within-group repeated measures t tests showing that while the BMD change in the CTL and the DS failed to reach statistical significance (P=0.593 and 0.222, respectively), changes in the PLA, FC and GLC were all significant (P=0.031, 0.029 and < 0.001, respectively).
Fig 1, A Meta-analysis Comparing Expected Changes in Bone Mineral Density with Historical Data From Five Different Groups: (1) A Control in which Subjects Were Free to Follow Any Program of Their Own Choosing, (2) Dietary Supplements, (3) Placebo, (4) Fitness Clubs, and (5) Glyconutritional Supplements Expected Change -0.003 Control Groups (N = 131) +0.001 Dietary Supplement Groups (N = 191) +0.002 Placebo Groups (N = 239) +0.003 Fitness Club Groups +0.004 Glyconutrient Groups (N = 196) +0.014 Note: Table is made from bar graph Table 1. Comparisons Between Baseline Measures and Changes in Bone Mineral Density (g/[cm.sup.2]) in Five Groups Participating in Weight Loss Programs With and Without Glyconutritional Supplements or Behavior Modification Plans Control Dietary Supplement (n=131) (n=191) 1 Baseline Mean StDev Mean StDev 2 Age 45.1 [+ or -] 12.4 43.7 [+ or -] 12.2 3 Scale Weight 178.0 [+ or -] 44.6 179.0 [+ or -] 35.7 4 BMD 1.211 [+ or -] 0.092 1.211 [+ or -] 0.085 4 %Fat 38.0% [+ or -] 10.9% 40.0% [+ or -] 8.1% 6 Fat Mass 68.9 [+ or -] 30.9 72.7 [+ or -] 23.8 7 Fat Free Mass 109.1 [+ or -] 24.7 106.3 [+ or -] 21.8 Changes in BMD during a 75-day study period shown as g/cm2 and % of annualized change 8 BMD Changes (g/cm2) 0.001 [+ or -] 0.018 0.002 [+ or -] 0.022 9 BMD % Annual Change 0.49% 1.11% P values from t-tests between- and within- groups changes in BMD Control Dietary Supplement 10 Control 0.593 (2) 0.643 (1) 11 Dietary Suppliments 0.222 (2) 12 Placebo 13 Fitness Club 14 Glyconutritients Placebo Fitness Club (n=239) (n=127) 1 Baseline Mean StDev Mean StDev 2 Age 44.4 [+ or -] 10.1 33.6 [+ or -] 12.2 3 Scale Weight 180.9 [+ or -] 47.8 162.0 [+ or -] 35.6 4 BMD 1.227 [+ or -] 0.087 1.204 [+ or -] 0.091 4 %Fat 39.4% [+ or -] 9.8% 33.3% [+ or -] 8.6% 6 Fat Mass 73.7 [+ or -] 33.2 54.7 [+ or -] 20.6 7 Fat Free Mass 107.2 [+ or -] 23.3 107.3 [+ or -] 24.7 Changes in BMD during a 75-day study period shown as g/cm2 and % of annualized change 8 BMD Changes (g/cm2 0.002 [+ or -] 0.017 0.003 [+ or -] 0.017 9 BMD % Annual Change 1.40% 1.98% P values from t-tests between- and within- groups changes in BMD Placebo Fitness Club 10 Control 0.408 (1) 0.249 (1) 11 Dietary Suppliments 0.780 (1) 0.517 (1) 12 Placebo 0.031 (2) 0.615 (1) 13 Fitness Club 0.029 (2) 14 Glyconutritients Glyconutrients (n=196) 1 Baseline Mean StDev 2 Age 48.1 [+ or -] 12.9 3 Scale Weight 175.8 [+ or -] 56.8 4 BMD 1.181 [+ or -] 0.099 4 %Fat 36.0% [+ or -] 11.5% 6 Fat Mass 67.2 [+ or -] 40.3 7 Fat Free Mass 108.6 [+ or -] 23 Changes in BMD during a 75-day study period shown as g/cm2 and % of annualized change 8 BMD Changes (g/cm2 0.011 [+ or -] 0.021 9 BMD % Annual Change 6.83% P values from t-tests between- and within- groups changes in BMD Glyconutrients 10 Control <0.001 (1) 11 Dietary Suppliments <0.001 (1) 12 Placebo <0.001 (1) 13 Fitness Club <0.001 (1) 14 Glyconutritients <0.001 (2)
Within-group baseline internal consistency
A total of 93.5% of participants in the glyco group completed the study suggesting the procedures used to increase compliance, including the deposit requirement, were highly effective. Additional comparisons were made between different subgroups (gender, age and ethnicity) of the glyco group to see if they were consistent with differences reported in other studies. With regard to gender, men (n=40) in the glyco group had the expected higher BMD (mean=1.198, SD=0.078) than women (n=156), (mean=1.152, SD=0.101) a difference that was significant (P=0.007). With regard to age, dichotomizing the group at age 47 yrs showed the expected differences with age: subjects < 48 yrs old (n=100) had a higher BMD (mean=1.198 SD=0.078) than subjects > 48 years old (n=96) (mean=1.123 SD=0.103), a difference that was also significant (P<.001). Also consistent with other studies were the data from a small number of Japanese-Americans (n=10) who enrolled in this study. Their average age (49.8 years) and percentage of women (60%) matched that of their non-Japanese American cohort and, consistent with other research, (11), (12) their mean BMD was below that of the non-Japanese American subjects. Thus, the consistency of these changes provides support for the internal validity of the glyco group.
The obvious shortcoming of any meta analysis of independent studies that were conducted at different times is the absence of randomized assignment to each of the study groups. To address this issue, we conducted a 60-day pilot study in which subjects were randomly assigned to a placebo group (n=12) or to one of five subgroups using different dietary supplements (n=54). Before randomizing subjects, we added a third arm in which we randomly assigned 10 participants to a group in which they used the same glyconutrient supplements and LGWP as the GLC in the meta analysis. Data from all participants was adjusted to a common 75-day study period and data for the five subgroups were combined into a single group. A comparison of changes in BMD in the placebo group, the two dietary supplement groups and the expected change in BMD for the study period is shown in Figure 2. The placebo group lost BMD (-0.013, SD= 0.010 g/[cm.sup.2]) as did the dietary supplement group (-0.003, SD=0.016 g/[cm.sup.2]), while the glyconutrient group gained BMD (+0.008, SD=0.017 g/cm2).
Fig 2. A Comparison of Changes in Bone Mineral Density Between a Placebo Group, a Group Taking Differenct Dietary Supplements and a Group Taking Glyconutritional Supplements Using a Randomized Placebo-Controlled Double-Blinded Protocol Expected Change -0.003 Placebo Groups N = 12 -0.013 Dietary Supplement Groups N = 54 -0.003 Glyconutrient Groups N = 10 +0.008 Note: Table is made from bar graph
Although the increase in BMD in the glyconutrient group in this study was less than that found in the meta analysis (0.011 vs. 0.008 g/[cm.sup.2]), it was significantly greater (P=0.002) than the placebo group in spite of the small number of participants in these two groups. It was also greater than the dietary supplement group, although only at the P=.06 level of significance. The group taking five different dietary supplements also achieved a significantly greater (P=0.035) increase in BMD than the placebo group.
A bone-health plan study
An additional study enrolled 126 subjects to compare changes in BMD between subjects following the AlgaeCal Bone-health Plan with (n=61) (71) and without (n=65) taking glyconutrients supplements. Additionally, all subjects provided self-reported product usage and completed an anonymous reporting of their compliance, that allowed for classification of subjects into compliant and non-compliant sub-groups. The results of this study are shown in Figure 3.
Fig 3. Comparison of Annualized Changes in Bone Mineral Density For Compaliant and Non-Compliant Subjects Following the AlgaeCal Bone-Health Plan With and Without Glyconutritional Supplements Compliant Subjects AlgaeCal Bone-Health Plan Without Glyconutrients 2.3% AlgaeCal Bone-Health Plan With Glyconutrients 3.7% Non-Compliant Subjects AlgaeCal Bone-Health Plan Without Glyconutrients -0.8% AlgaeCal Bone-Health Plan With Glyconutrients -1.3% Note: Table is made from bar graph
Using a repeated-measure analysis, both compliant groups had a significant annualized increase in BMD; P=0.006 for those following the plan without glyconutrients and P=0.001 for those following the plan while taking glyconutrients. Although the compliant group following the plan taking glyconutrients achieved a 3.7% annualized increase in BMD versus a 2.3% increase in those following the plan without glyconutrients, this difference was not statistically significant (P=0.162).
All groups had increases in BMD during the study period, as compared to the expected decrease suggested by normative data. A within-group repeated measures t test as shown on the diagonal was not significant for the CTL and DS, but was significant for the other three groups, including the PLA. This raises a question as to why the PLA experienced an increase in BMD while virtually all other studies on BMD changes have found little or no change in placebo groups. (29), (59), (60), (61) Positive changes in BMD in the PLA could be attributed to the effects of being in a clinical trial, but are more likely due to the feedback of their test results and to the effects of following the LGWP--neither of which were provided to the control or placebo groups in other studies.
Comparisons within the GLC reveal the highly significant differences between men and women and younger and older subjects in BMDs. It is consistent with an extensive body of research on the effects of gender and aging on BMD: BMDs were greater in men than in women and, for both genders, BMD was found to decline with age. Also consistent with other studies were the data from a small number of Japanese-Americans who enrolled in this study. Thus, these baseline data suggest that the BMDs for this group of participants were highly consistent with previous research findings.
Comparisons of the average age of the GLC (48.1 yrs) with the other four groups approached significance with the CTL (P=0.064), and was significantly greater than the other groups: DS (P=0.004), PLA (P=0.003) and FC (P < .001). Since BMD declines at an increasing rate with advancing age. (62), (63) the GLC, which consisted of an older population, would be expected to have a more difficult time maintaining or increasing their BMD than the other groups.
While a number of different statistics could be used other than students' t tests, it is doubtful that any different statistical analysis would change any of the conclusions one would draw about the differences between the GLC and the other groups. In fact, an analysis of covariance adjusting for the older age of the GLC would magnify the increases reported. Furthermore, examination of the weight loss in the five groups revealed that the GLC lost more scale weight than did any of the other four groups. This too would be in opposition to the changes observed in the GLC. Thus, the changes observed in the GLC occurred in spite of three influences that worked against these increases: the baseline greater age, the decline in scale weight observed, and the expected declines in BMD that would occur during the 75-day study period.
The positive changes in the GLC cannot, of course, be attributed solely to the glyconutrient supplements since participants were also asked to increase their physical activity levels and to improve their diets with the accompanying LGWP. However, the increases in BMD in the GLC were significantly greater than the increases in BMD in the PLA and the DS groups who received the same LGWP, thus increasing the confidence of the efficacy of the glyconutrient supplements.
We have previously shown that the same glyconutritionals and LGWP used in this study led to improved lean-to-fat ratios, including increases in fat-free mass FFM, (42), (48) a finding consistent with studies suggesting there is a positive relationship between muscle mass and BMD. (64) Thus, increases in FFM could expect to be accompanied by increases in BMD, and at least one researcher has suggested that improved strength, physical fitness, and weight can offset the expected age-related decline in femoral neck-bone mass. (65) Additionally, in studies of males undergoing testosterone therapy, androgen administration decreased body fat and increased FFM and BMD, (66), (67) a finding consistent with our data. Skeletal fragility is also associated with muscle weakness or sarcopenia (age-related reduction in muscle mass) and osteopenia, neither of which are disease states but are risk factors for bone fractures. A supplementation regimen that could increase both FFM and BMD could be an important addition to pharmacological treatment programs. Furthermore, since BMD increases in this study were observed in pre- and post-menopausal women, this regimen may be able to facilitate higher levels of BMD before age-related declines begin to occur, which is the primary goal of interventions to improve bone-health.
These data suggest the intriguing possibility that consumption of glyconutrients with an accompanying behavior modification plan can lead to short-term increases in BMD. In addition to highly consistent within-group differences in age, gender and ethnicity, the increases in BMD found in the GLC were significantly greater than those found in the PLA, CTL and DS groups, in spite of the fact that the GLC group was older and lost more body weight than the other groups (differences that typically decrease BMD). Caution is warranted in interpreting these data since study participants, although recruited independently and simultaneously, were not randomly assigned to the study groups. Clearly, we need further research to see if the increases in BMD shown here can be replicated in subsequent studies, studied for longer periods, and examined when integrated into pharmacologic treatment plans. Nonetheless, it seems reasonable to conclude that the dietary supplements used in this study can lead to short-term increases in bone densities.
About the Authors
Gilbert R. Kaats, PhD. Dr. Kaats is a Fellow of the American College of Nutrition and the American College of Sports Medicine; and a Fellow, Diplomate and Member of the Clinical Nutrition Advisory Board of the American Association of Integrative Medicine.
Dr. Kaats has been conducting clinical trials and research and development on health-enhancing products and technologies for the past 32 years. He has amassed a national database containing over 22,000 DEXA measurements of total body composition (lean, fat and bone density). Many of these subjects in the database also have corresponding measurements of a 43-panel blood test as well as pedometer-based physical activity levels and self-reported quality of life inventories. Much of this work is summarized in his recent book, Restructuring Body Composition: How the Kind, Not the Amount, of Weight Loss Defines a Pathway to Optimal Health. Taylor Publishing, Dallas, Texas, 2008. Although not involved with the marketing of pedometers, his book is available for sale for $29.95 (210.824.4200). Dr. Kaats is currently CEO/President of Integrative Health Technologies, a public company trading under the symbol IHTI. For more information, see the Company's website, www.ihtglobal.com.
Samuel C. Keith is IHTI's CIO and has been intimately involved in all research and compilation of the database.
Patti L. Keith is IHTI's Clinical Research Coordinator and has been with the company for over 20 years supervising clinical trials and research and development.
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(71.) HealthTech Products, LLC., San Antonio, Texas, (210) 274-6193 firstname.lastname@example.org
The dietary supplements used in the "glyco group" were supplied by Mannatech Inc., Coppell, Texas. (972) 471-7400
by: Gilbert R. Kaats, PhD, FACN, Samuel C. Keith. BBA and Patti L. Keith, BBA
Health and Medical Research Center, San Antonio, TX
* This meta-analysis was conducted by combining all original BMD data from the original source documents as opposed the traditional method of combining only the outcome means and standard deviations of like studies.
[C] Portions of this article have been reprinted with permission from Kaats GR. Restructuring Body Composition: How the Kind, not the Amount of Weight Loss Defines a Pathway to Optimal Health. 2008 Taylor Publishing Co., Dallas, TX.
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|Author:||Kaats, Gilbert R.; Keith, Samuel C.; Keith, Patti L.|
|Article Type:||Clinical report|
|Date:||Dec 1, 2008|
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