Longitudinal relationship between muscle mass and intramuscular adipose tissue of the quadriceps in older inpatients at different activities of daily living levels

Dietary factors may be associated with measures of ultrasound-derived skeletal muscle echo intensity

Skeletal muscle echo intensity (EI) is affected by ageing and physical activity; however, the effects of nutrition are less understood. The aim of this study was to explore whether habitual nutrient intake may be associated with ultrasound-derived EI. Partial least squares regression (PLSR) models were trained on an initial sample (n = 100, M = 45; F = 55; 38 ± 15 years) to predict EI of two quadriceps muscles from 19 variables, using the "jack-knife" function within the "pls" package (RStudio), which was then tested in an additional dataset (n = 30, M = 13; F = 17; 38 ± 16 years). EI was determined using B-mode ultrasonography of the rectus femoris (RF) and vastus lateralis (VL) and nutritional intake determined via 3-day weighed food diaries. Mean daily intake of specific nutrients were included as predictor variables with age, sex, and self-reported physical activity. PLSR training model 1 explained ∼52% and model 2 ∼46% of the variance in RF and VL EI, respectively. Model 1 also explained ∼35% and model 2 ∼30% of the variance in RF and VL EI in the additional testing dataset. Age and biological sex were associated with EI in both models (P < 0.025). Dietary protein (RF: β = -7.617, VL: β = -7.480), and selenium (RF: β = -7.144, VL: β = -4.775) were associated with EI in both muscles (P < 0.05), whereas fibre intake (RF: β = -5.215) was associated with RF EI only and omega-3 fatty acids (n-3/ω-3 FAs, RF: β = 3.145) with VL EI only (P < 0.05). Therefore, absolute protein, selenium, fibre, and n-3 FAs may be associated with skeletal muscle EI, although further mechanistic work is required before claiming causal inference.

Physical function decline predictors in nursing home residents using new national quality indicators

AIM

To determine the predictors of physical function (PF) decline among nursing home residents using items from the Long-term care Information system For Evidence (LIFE), a system launched in 2021 to ensure the quality of long-term care.

METHODS

The LIFE data of 1648 residents from 45 nursing homes in Japan were retrospectively collected in July 2021 (T0) and January 2022 (T1), including demographics, PF assessed by the Barthel index (BI), nutrition and oral health, and cognitive function. The Dementia Behavior Disturbance scale was used to assess the frequency of certain behaviors, such as "waking at midnight." The predictors of PF decline, defined as a decrease ≥5 in the BI score at T1 compared with that at T0, were determined using mixed-effects logistic regression analyses. PF at T0 was classified into high (>60 BI) and low (≤60 BI) groups.

RESULTS

The participants' mean age was 87.2 ± 7.1 years, and 45.3% experienced PF decline. The significant predictors of PF decline were age ≥ 90 years, body mass index <18.5 kg/m2 , dementia diagnosis, moderate and severe cognitive impairments, not vocalizing reciprocal exchanges at will, always "waking at midnight," and high PF at T0.

CONCLUSIONS

The LIFE items predicted PF decline among nursing home residents, suggesting that LIFE data can be used to ensure the quality of long-term care. Geriatr Gerontol Int 2024; 24: 123-132.