Vitamin D recommendations for Canadian elderly: an evaluation of adequacy of current clinical practices for nutrition and skeletal health
Notice bibliographique
Résumé
Vitamin D is a key nutrient in bone health. Seniors living in long-term care (LTC) facilities in Canada face a higher risk of deficiency as menus are often deficient in vitamin D and sunlight exposure is limited. Vitamin D status can be measured by serum 25-hydroxyvitamin D concentration (25(OH)D). Many seniors in Canada have low vitamin D status. The global objectives of this thesis were to: (1) assess vitamin D intake and association with biomarkers of bone health in older men in a LTC facility of the Montréal region (latitude: 46°N); (2) assess the impact of an 8-wk supplementation regimen of 2000 IU/d of vitamin D3 on 25(OH)D and markers of bone metabolism; (3) determine how much vitamin D3 is needed to sustain vitamin D status using vitamin D3 fortified foods. Study 1 tested the first objective. Food intake and sunlight exposure of 30 men were measured for 1 year. Food intake was measured with 3-d weighed food records. Biomarkers of bone metabolism (serum 25(OH)D, parathyroid hormone (PTH), calcium, phosphate, osteocalcin (OC) and C-terminal telopeptide of collagen type 1 (CTX)) were tested. Descriptive statistics and change over time were analyzed. A mean of 280±120 IU/d of vitamin D was consumed. In the winter months, over 30% of participants were below the 50 nmol/L of serum 25(OH)D concentrations suggested by the Institute of Medicine. Serum 25(OH)D rose by summer and declined in the fall. PTH was lower in the spring. CTX and OC were unchanged. Study 2 tested the second and third objectives with a 2 phase trial. First, a Loading Phase used 2000 IU/d vitamin D3 tablet supplementation (October to December; 8 weeks; RCT –8). A randomized controlled trial (RCT) followed (January to July; 24 weeks; RCT0–RCT24). Participants were randomized to 3 groups: Placebo group, 500 IU/d group or 1000 IU/d of vitamin D3. Vitamin D3 was given as bite size fortified foods. The Placebo group received identical unfortified foods. Biomarkers of bone metabolism (serum 25(OH)D, PTH, calcium, phosphate, OC, CTX, osteoprotegerin and RANKL) were measured at RCT –8, RCT0 and RCT24. At RCT0 and RCT24, peripheral dual-energy X-ray absorptiometry, peripheral quantitative computed tomography (pQCT) and handgrip strength were measured on the non-dominant forearm. Differences were tested using mixed model ANOVA for fixed effects of time and group and interactions of time by group.At RCT –8, mean vitamin D intakes and mean 25(OH)D concentrations were 494±380 IU/d and 56.9±13.3 nmol/L for the Placebo group, 769±526 IU/d and 54.6±15.0 nmol/L for the 500 IU/d group and 562±383 IU/d and 56.9±9.7 nmol/L for the 1000 IU/d group. The 2000 IU/d of vitamin D3 raised serum 25(OH)D to a mean value of 65 nmol/L in all groups. During the RCT, the 500 IU/d and 1000 IU/d groups maintained serum 25(OH)D above 65 nmol/L. In 8 weeks, the 25(OH)D concentration values of the Placebo group reverted back to the values of RCT –8. Biomarkers of bone metabolism were stable. The pQCT values declined over time in trabecular volumetric bone mineral density (vBMD) for the 500 IU/d group and in vBMD at the diaphysis for the 1000 IU/d group. Total bone area in the diaphysis improved and areal bone mineral density improved in the 1000 IU/d group. For all groups, muscle area declined over time and muscle density did not change. Handgrip strength was stable in the 1000 IU/d group. In conclusion, these studies suggest that vitamin D supplementation is needed to achieve and maintain healthy vitamin D status. The group getting 1000 IU/d of vitamin D3 improved cross-sectional bone area at 66% of the forearm diaphysis suggesting remodeling with incomplete mineralization. As handgrip strength was improved in the 1000 IU/d group, vitamin D3 could positively influence muscle strength and, possibly reduce the risk of falls and fractures. More research is needed to understand the relationships among vitamin D and musculoskeletal health in older men living in LTC.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,003 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».