ObjectiveThe Plants for Joints (PFJ) intervention significantly improved pain, stiffness, and physical function, and metabolic outcomes, in people with metabolic syndrome-associated osteoarthritis (MSOA). This secondary analysis investigated its effects on body composition.MethodIn the randomized PFJ study, people with MSOA followed a 16-week intervention based on a whole-food plant-based diet, physical activity, and stress management, or usual care. For this secondary analysis, fat mass, muscle mass, and bone mineral density were measured using dual-energy X-ray absorptiometry (DEXA) for all participants. Additionally, in a subgroup (n = 32), hepatocellular lipid (HCL) content and composition of visceral adipose tissue (VAT) were measured using magnetic resonance spectroscopy (MRS). An intention-to-treat analysis with a linear-mixed model adjusted for baseline values was used to analyse between-group differences.ResultsOf 66 people randomized, 64 (97%) completed the study. The PFJ group experienced significant weight loss (−5.2 kg; 95% CI –6.9, −3.6) compared to controls, primarily from fat mass reduction (−3.9 kg; 95% CI –5.3 to −2.5). No significant differences were found in lean mass, muscle strength, or bone mineral density between groups. In the subgroup who underwent MRI scans, the PFJ group had a greater reduction in HCL (−6.5%; 95% CI –9.9, 3.0) compared to controls, with no observed differences in VAT composition.ConclusionThe PFJ multidisciplinary intervention positively impacted clinical and metabolic outcomes, and appears to significantly reduce body fat, including liver fat, while preserving muscle mass and strength.
MULTIFILE
Background: The concept of Functional Independence (FI), defined as ‘functioning physically safe and independent from other persons, within one’s context”, plays an important role in maintaining the functional ability to enable well-being in older age. FI is a dynamic and complex concept covering four clinical outcomes: physical capacity, empowerment, coping flexibility, and health literacy. As the level of FI differs widely between older adults, healthcare professionals must gain insight into how to best support older people in maintaining their level of FI in a personalized manner. Insight into subgroups of FI could be a first step in providing personalized support This study aims to identify clinically relevant, distinct subgroups of FI in Dutch community-dwelling older people and subsequently describe them according to individual characteristics. Results: One hundred fifty-three community-dwelling older persons were included for participation. Cluster analysis identified four distinctive clusters: (1) Performers – Well-informed; this subgroup is physically strong, well-informed and educated, independent, non-falling, with limited reflective coping style. (2) Performers – Achievers: physically strong people with a limited coping style and health literacy level. (3) The reliant- Good Coper representing physically somewhat limited people with sufficient coping styles who receive professional help. (4) The reliant – Receivers: physically limited people with insufficient coping styles who receive professional help. These subgroups showed significant differences in demographic characteristics and clinical FI outcomes. Conclusions: Community-dwelling older persons can be allocated to four distinct and clinically relevant subgroups based on their level of FI. This subgrouping provides insight into the complex holistic concept of FI by pointing out for each subgroup which FI domain is affected. This way, it helps to better target interventions to prevent the decline of FI in the community-dwelling older population.
Purpose: For prevention of sarcopenia and functional decline in community dwelling older adults, a higher daily protein intake is needed in addition to increased exercise. A new e-health strategy for dietary counseling was usedwith the aim to increase total daily protein intake to optimal levels (minimal 1.2 g/kg/day, optimal 1.5 g/kg/day) through use of regular food products.Methods: The VITAMIN (VITal AMsterdam older adults IN the city) RCT included 245 community dwelling older adults (age ≥ 55y): control, exercise, and exercise plus dietary counseling (protein) group. The dietary counselingintervention was based on behavior change and personalization was offered by a dietitian coach, by use of face-to-face contacts and videoconferencing during a 6-month intervention. Dietary intake was measured by a 3d dietaryrecord at baseline, after 6-month intervention and 12-month follow-up. The primary outcome was average daily protein intake (g/kg/day). Sub-group analysis and secondary outcomes included daily protein distribution, sources,product groups. A Linear Mixed Models (LMM) of repeated measures was performed with STATA v13.Results: Mean age of the 224 subjects was 72.0(6.5) years, a BMI of 26.0(4.2) and 71% were female. The LMM showed a significant effect of time and time*group (p<0.001). The dietary counseling group showed higher protein intakethan either control (1.41 vs 1.13 g/kg/day; β +0.32; p<0.001) or exercise group (1.41 vs 1.11 g/kg/day; β +0.33; p<0.001) after 6-month intervention and 12-month follow-up (1.24 vs 1.05; β +0.23; p<0.001 | 1.24 vs 1.07 β +0.19;p<0.001). Additional analysis revealed the higher protein intake was fully accounted for by animal protein intake.Conclusions: This study shows digitally supported dietary counseling improves protein intake sufficiently incommunity dwelling older adults with use of regular food products. Protein intake increase by personalizedcounseling with e-health is a promising strategy for dietitians with the upcoming rising ageing population.Keywords: Ageing, Behavior change, Nutrition, Physical Functioning, Sarcopenia
Low back pain is the leading cause of disability worldwide and a significant contributor to work incapacity. Although effective therapeutic options are scarce, exercises supervised by a physiotherapist have shown to be effective. However, the effects found in research studies tend to be small, likely due to the heterogeneous nature of patients' complaints and movement limitations. Personalized treatment is necessary as a 'one-size-fits-all' approach is not sufficient. High-tech solutions consisting of motions sensors supported by artificial intelligence will facilitate physiotherapists to achieve this goal. To date, physiotherapists use questionnaires and physical examinations, which provide subjective results and therefore limited support for treatment decisions. Objective measurement data obtained by motion sensors can help to determine abnormal movement patterns. This information may be crucial in evaluating the prognosis and designing the physiotherapy treatment plan. The proposed study is a small cohort study (n=30) that involves low back pain patients visiting a physiotherapist and performing simple movement tasks such as walking and repeated forward bending. The movements will be recorded using sensors that estimate orientation from accelerations, angular velocities and magnetometer data. Participants complete questionnaires about their pain and functioning before and after treatment. Artificial analysis techniques will be used to link the sensor and questionnaire data to identify clinically relevant subgroups based on movement patterns, and to determine if there are differences in prognosis between these subgroups that serve as a starting point of personalized treatments. This pilot study aims to investigate the potential benefits of using motion sensors to personalize the treatment of low back pain. It serves as a foundation for future research into the use of motion sensors in the treatment of low back pain and other musculoskeletal or neurological movement disorders.
