| Literature DB >> 34531652 |
Leo Delaire1, Aymeric Courtay1, Joannès Humblot1, Mathieu Fauvernier2,3, Marc Bonnefoy1,4,5.
Abstract
INTRODUCTION: Exercise and nutrition are the best targets to tackle mobility issues in community-dwelling older adults. As exercise response relies on multiple factors, improving the understanding of their interactions is a necessity to tailor effective preventive strategies. Based on a prevention care path designed for community-dwelling older adults with mobility disability risk, our main goal was to determine the predictive factors of the response to a multimodal intervention, combining structured exercise training and nutritional counselling. Thus, this study aimed to tailor prevention programs for non-responder participants.Entities:
Keywords: exercise; nutrition; prevention; responders profiles
Mesh:
Year: 2021 PMID: 34531652 PMCID: PMC8439386 DOI: 10.2147/CIA.S315112
Source DB: PubMed Journal: Clin Interv Aging ISSN: 1176-9092 Impact factor: 4.458
Figure 1Care path description. aWhen the participant could not attend the collective sessions.
Figure 2Participants flow.
Figure 3Training phases.
Odds Ratio of the Selected Model
| Predictors | OR a | CI b | |
|---|---|---|---|
| (Intercept) c | 0.80 | [0.44; 1.43] | 0.459 |
| BMI * Grip Strength | 0.98 | [0.96; 1.00] | 0.075 |
Notes: aOdds Ratio. bConfidence Interval 95%. cOdds. dShort Physical Performance Battery. eBody Mass Index. Significant interactions (p<0.05) are presented in bold.
Population Characteristics at Initial Assessment (n=103)
| Total n=103 | Women n=71 | Men n=32 | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Age, y | 81.9 ± 5.7 | 81.7 ± 6.2 | 82.3 ± 4.5 | |||||||||
| Weight, kg | 70.8 ± 15.0 | 62.3 ± 14.0 | 81.0 ± 11.9 | |||||||||
| Height, cm | 159 ± 17.4 | 157.3 ± 5.8 | 162.9 ± 30.3 | |||||||||
| BMI, kg/m2 a | 27.2 ± 4.8 | 26.8 ± 5.1 | 28.3 ± 4.0 | |||||||||
| SMI, kg/m2 b | – | 6.09 ± 1.05 | 8.43 ± 1.25 | |||||||||
| RAPA (/10) c | 2.7 ± 1.4 | 2.5 ± 1.4 | 3.1 ± 1.4 | |||||||||
| Fallers, n (%) d | 52 (50.5%) | 35 (49.3%) | 17 (53.1%) | |||||||||
| Number of falls per faller | 2.1 ± 2.2 | 2.3 ± 2.6 | 1.6 ± 1.3 | |||||||||
| Grip strength, kg | – | 15.8 ± 4.2 | 27.6 ± 7.3 | |||||||||
| Chair Stand Test, s | 14.3 ± 4.6 | 14.9 ± 4.8 | 12.8 ± 3.8 | |||||||||
| Gait speed, m/s | 0.91 ± 0.27 | 0.86 ± 0.28 | 1.03 ± 0.21 | |||||||||
| TUG, s | 14.5 ± 6.1 | 15.1 ± 6.8 | 13.3 ± 4.0 | |||||||||
| SPPB, /12 | 9.5 ± 1.9 | 9.1 ± 2.0 | 10.2 ± 1.6 | |||||||||
| Protein needs, g/per day | 74.7 ± 11.4 | 70.2 ± 9.6 | 85.4 ± 7.7 | |||||||||
| Protein intake, g/per day | 64.1 ± 13.1 | 60.5 ± 10.1 | 72.6 ± 15.4 | |||||||||
| Sarcopenia, n (%) e | NS | PS | S | SS | NS | PS | S | SS | NS | PS | S | SS |
| 38 (50.0%) | 2 (2.6%) | 11 (14.5%) | 25 (32.9%) | 23 (49.4%) | 1 (1.9%) | 7 (13.2%) | 22 (41.5%) | 15 (65.2%) | 1 (4.3%) | 4 (17.4%) | 3 (13.0%) | |
Notes: Quantitative variables are expressed as mean ± standard deviation, qualitative variables are expressed as count (percentage). aBody Mass Index. bEstimated Skeletal Muscle Index by bio impedance analysis (BIA). cRapid Assessment of Physical Activity questionnaire. dAt least one fall (traumatic or not) within the last 12 months. eDiagnosis was possible for 76 participants regarding EWGSOP2 algorithm; diagnosis was not possible when BIA was dysfunctional (n=15), and for participants with both BMI >31 and low physical performance (n=9).
Abbreviations: NS, no sarcopenia; PS, probable sarcopenia; S, sarcopenia; SS, severe sarcopenia.
Figure 4Prediction related to the selected model.