| Literature DB >> 16768802 |
Paula Gardiner1, Charles Woods, Kathi J Kemper.
Abstract
BACKGROUND: Although many health care professionals (HCPs) in the United States have been educated about and recommend dietary supplements, little is known about their personal use of dietary supplements and factors associated with their use.Entities:
Mesh:
Year: 2006 PMID: 16768802 PMCID: PMC1526756 DOI: 10.1186/1472-6882-6-21
Source DB: PubMed Journal: BMC Complement Altern Med ISSN: 1472-6882 Impact factor: 3.659
Frequency of vitamin, mineral and other dietary supplements
| N = 1249 | ||
| N | % of respondents using | |
| 942 | 75 | |
| Multivitamins | 762 | 60 |
| Vitamin B | 382 | 31 |
| C Vitamin | 373 | 30 |
| E Vitamin | 286 | 23 |
| Folate model | 187 | 15. |
| D Vitamin | 192 | 15 |
| Niacin, B3 | 95 | 8 |
| Vitamin K | 74 | 6 |
| Lutein | 49 | 4 |
| 567 | 45 | |
| Calcium | 495 | 40 |
| Magnesium | 158 | 13 |
| Iron | 122 | 10 |
| Chromium | 64 | 5 |
| 438 | 35 | |
| Fish oil | 302 | 24 |
| Glucosamine | 152 | 12 |
| Co Q 10 | 128 | 10 |
| Alpha linoleic acid | 75 | 6 |
| MSM – in plants | 61 | 5 |
| DHEA | 32 | 3 |
| Melatonin | 41 | 3 |
| SAM-e | 17 | 1 |
| Creatine | 8 | .6 |
Respondents baseline characteristics for commonly used vitamins minerals and other dietary supplements *
| N | 1249 | 754 | 495 | 382 | 373 | 295 | 286 | 192 | 187 |
| 60% | 40% | 31% | 30% | 24% | 23% | 15% | 15% | ||
| ≤30 | 406 (32.5) | 33 | 31 | 22 | 28 | 12 | 15 | 11 | 10 |
| 31–40 | 202 (16.2) | 16 | 38 | 23 | 26 | 24 | 14 | 12 | 12 |
| 41–50 | 328 (26.3) | 25 | 43 | 32 | 27 | 27 | 27 | 15 | 15 |
| >50 | 313 (25.1) | 25 | 49 | 45 | 38 | 35 | 35 | 24 | 23 |
| P = .85 | P < .001 | P < .001 | P < .001 | P < .001 | P < .001 | P < .001 | P < .001 | ||
| Male | 316 (25) | 22 | 19 | 28 | 31 | 25 | 23 | 10 | 11 |
| Female | 933 (75) | 78 | 47 | 31 | 30 | 23 | 23 | 17 | 16 |
| P < .001 | P < .001 | P = .17 | P = .70 | p = .50 | P = .96 | P = .01 | P = .04 | ||
| African American | 57 (4.6) | 4 | 16 | 32 | 26 | 18 | 26 | 11 | 11 |
| Asian/P.I. | 95 (7.6) | 7 | 32 | 16 | 19 | 16 | 9 | 12 | 8 |
| Caucasian | 1035 (82.9) | 84 | 42 | 32 | 31 | 24 | 24 | 16 | 16 |
| Native American | 3 (0.2) | 4 | 67 | 33 | 33 | 0 | 33 | 33 | 33 |
| Declined | 59 (4.7) | .3 | 27 | 34 | 36 | 29 | 25 | 20 | 12 |
| P = .711 | P < .001 | P = .03 | P = .13 | P = .15 | P = .03 | P = .41 | P = .19 | ||
| Physician | 256 (20.5) | 18 | 34 | 33 | 29 | 32 | 26 | 18 | 19 |
| Dietician | 137 (10.97) | 11 | 54 | 6 | 17 | 24 | 16 | 12 | 12 |
| Nurse | 203 (16.3) | 19 | 48 | 45 | 34 | 28 | 36 | 19 | 19 |
| PA & NP | 73 (5.8) | 6 | 51 | 45 | 38 | 37 | 26 | 22 | 19 |
| Pharmacist | 41 (3.3) | 3 | 46 | 20 | 24 | 32 | 20 | 15 | 12 |
| Student | 458 (36.7) | 37 | 35 | 28 | 32 | 14 | 17 | 13 | 12 |
| Residents & fellows | 81 (6.5) | 6 | 27 | 19 | 23 | 20 | 14 | 9 | 14 |
| P = .02 | P < .001 | P < .001 | P < .001 | P < .001 | P < .001 | P = .08 | P = .09 | ||
| Yes | 587 (47) | 45 | 43 | 30 | 28 | 23 | 24 | 16 | 14 |
| No | 662 (53) | 55 | 36 | 31 | 32 | 24 | 22 | 15 | 16 |
| P = .15 | P = .01 | P = .85 | P = .13 | P = .54 | P = .37 | P = .78 | p = .35 | ||
| Average 65.8 ± 10.7 | |||||||||
| High | 402 (32) | 35 | 52 | 38 | 32 | 36 | 26 | 19 | 22 |
| Medium | 483 (39) | 39 | 37 | 31 | 30 | 23 | 23 | 14 | 14 |
| Low | 364 (29) | 26 | 30 | 21 | 28 | 11 | 19 | 13 | 8 |
| P = .007 | P < .001 | P < .001 | P = .47 | P < .001 | P = .07 | P = .07 | P < .001 | ||
| Low | 387 (31) | 30 | 27 | 24 | 29 | 22 | 26 | 27 | 26 |
| Medium | 289 (23) | 25 | 23 | 25 | 26 | 23 | 26 | 24 | 23 |
| High | 275 (22) | 22 | 23 | 25 | 23 | 24 | 21 | 20 | 24 |
| Extremely high | 297 (24) | 23 | 27 | 26 | 22 | 31 | 26 | 29 | 28 |
| P = .12 | P = .08 | P = .01 | P = .30 | P < .001 | P = .09 | P = .21 | P = .29 | ||
| Yes | 667 (57) | 56 | 43 | 34 | 30 | 30 | 25 | 18 | 19 |
| No | 510 (43) | 44 | 35 | 25 | 29 | 16 | 20 | 11 | 11 |
| P = .55 | P = .002 | P = .001 | P = .70 | P < .001 | P = .04 | P < .001 | P < .001 |
*(15 % or > of the sample size).
Amongst health care professionals, factors associated with individual use of vitamins and minerals; adjusted multivariate logistic regression***
| Male * | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Females | 1.3 (.93–1.7) | 3.4 (2.4–4.8) | 2.3 (1.4–3.8) | .99 (.74–1.4) | .88 (.60–1.3) | 2.3 (1.4–.3.8) | 1.8 (1.2–2.9) | .88 (.60–1.3) |
| Physician * | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Nutritionist | 1.3 (.80–2.1) | 1.6 (.99–2.6) | .47 (.24 .92) | .56 (.32.99) | .67 (.37–1.2) | .47 (.24–.92) | .56 (.29–1.1) | .94 (.55–2.2) |
| Nurse | 2.3 (1.4–3.6) | 1.5 (.96–2.5) | .73 (.41–1.3) | .1.2 (.75–2.0) | 1.6 (1.0–2.7) | .73 (.41–1.3) | 1.1 (.61–1.9) | 1.3 (.81–2.2) |
| PA and NP | 1.1 (.64–2.0) | 1.1 (.63–2.0) | .78 (.39–1.6) | 1.4 (.79–2.5) | 1.6 (.87–2.9) | .78 (.39–1.6) | .73 (.35–1.5) | 1.3 (.73 –2.4) |
| Pharmacist | .88 (.43–1.8) | 1.6 (0.78–3.5) | .77 (.29–2.1) | .91 (.40 2.1) | .81 (.33 2.0) | .77 (.29–2.1) | .67 (.24–1.9) | .99 (.43–2.2) |
| Student | 1.4 (.87–2.2) | 1.7 (1.05–2.7) | .96 (.52–1.8) | 1.9 (1.2–3.1) | 1.1 (.66–2.0) | .96 (.52–1.8) | 1.2 (.64–2.2) | 1.0 (.60–1.7) |
| Resident | .83 (.47–1.4) | .79 (0.42–1.5) | .35 (.12–.95) | .89 (.47–1.7) | .57 (.47–1.7) | .35 (.12–.96) | .82 (.36–1.8) | .74 (.37–1.5) |
| ≤30* | 1 | 1.0 | 1 | 1 | 1 | 1 | 1 | |
| 31–40 | .88 (.58–1.3) | 1.1 (0.72–1.7) | .75 (.40–1.4) | 1.1 (.70–1.7) | .93 (.53–1.6) | .75 (.40–1.4) | .93 (.50–1.7) | 1.5 (.89–2.5) |
| 41–50 | .78 (.50–1.1) | 1.4 (0.9– 2.1) | 1.1 (.58–1.9) | 1.5 (.93–2.3) | 2.0 (1.2–3.3) | 1.1 (.58–1.9) | 1.1 (.59–2.0) | 1.6 (.95–2.7) |
| >50 | .82 (.53–1.3) | 2.0 (1.3–3.1) | 2.1 (1.1–3.8) | 2.2 (1.4–3.5) | 2.4 (1.4–4.1) | 2.1 (1.1–3.8) | 2.3 (1.3–4.1) | 2.5 (1.5–4.2) |
| Low* | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Medium | 1.4 (1.04 – 1.9) | 1.3 (.97–1.9) | 1.1 (.68 1.7) | 1.7 (.84 1.6) | 1.2 (.83 1.8) | 1.1 (.68 1.7) | 1.7 (1.05–2.7) | 1.9 (1.3–3.9) |
| High | 2.0 (1.4–2.8) | 2.7 (1.9–3.9) | 1.4 (.87–2.2) | 1.4 (.97–2.0) | 1.4 (.93–2.1) | 1.4 (.87–2.2) | 2.7 (1.6–4.4) | 3.4 (2.2 –5.3) |
| Low | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Medium | 1.4 (1.0– 1.9) | 1.1 (.76–1.5) | 1.2 (.77–1.9) | 1.3 (.90–1.8) | 1.4 (.97–2.1) | 1.2 (.77–1.9) | 1.02 (.64–1.6) | 1.3 (.88–2.0) |
| High | 1.1 (.76–1.5) | .98 (.69–1.4) | .95 (.59–1.5) | 1.2 (.82–1.7) | 1.1 (.72–1.6) | .96 (.60–1.6) | 1.05 (.66–1.7) | 1.4 (.90–2.0) |
| Extremely high | .96 (.68–1.4) | 1.1 (.75–1.6) | 1.3 (.80–2.1) | 1.0 (.68–1.5) | 1.3 (.84–1.9) | 1.3 (.80–2.1) | 1.2 (.74–1.9) | 1.5 (1.0–2.3) |
| No * | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Yes | .97 (.73–1.3) | 1.34 (1.0–1.8) | 1.7 (1.2–2.6) | 1.1 (.81–1.5) | 1.1 (.78–1.5) | 1.7 (1.2–2.6) | 1.7 (1.1–2.5) | 1.4 (.97–1.9) |
*The race/ethnicity variable did not show any positive association for other dietary supplement use in the multivariable analysis.
**The geographic variable showed a positive association (1.6 [1.2–2.2]) for fish oil and 1.3 [1.02 1.7] for multivitamin use in the multivariable analysis.
***Adjusted odds ratio with 95% confidence interval (N = 1176)