Relationship between body mass index and spinal pathology in community-dwelling older adults.

PURPOSE: To clarify the relationship between body mass index (BMI) and spinal pathologies including spinal sagittal balance, back extensor strength (BES), paraspinal muscle mass, prevalent vertebral fracture, disc degeneration, Modic changes, low back pain, and quality of life (QOL) in community-dwelling older adults. METHODS: This study included 380 participants (age: ≥ 65 years, male/female: 152/228) from the Shiraniwa Study. Multivariate nonlinear regression analysis was used to investigate the relationship between BMI and sagittal vertical axis (SVA), BES, paraspinal muscle mass, visual analog scale (VAS) for low back pain, Oswestry Disability Index (ODI), and EuroQoL-5 Dimension (EQ5D) score after adjusting for sex, age, Hospital Anxiety and Depression Scale score, and Charlson Comorbidity Index. In addition, multiple logistic regression analysis was used to investigate the association between BMI and prevalent vertebral fracture, disc degeneration, and Modic changes. RESULTS: BMI was significantly correlated with SVA, BES, paraspinal muscle mass, VAS, ODI, and EQ5D score. The increase in BMI was associated with the deterioration of all outcomes, which accelerated when the BMI increased from approximately 22-23 kg/m2. Moreover, overweight/obesity was significantly correlated with disc degeneration and Modic changes. CONCLUSION: Increased BMI is significantly associated with spinal pathologies such as SVA, BES, paraspinal muscle mass, VAS, QOL, disc degeneration, and Modic changes. The findings suggest that measures for controlling overweight and obesity among older adults can play an important role in the prevention and treatment of spinal pathologies.

Trunk Muscle Mass Measured by Bioelectrical Impedance Analysis Reflecting the Cross-Sectional Area of the Paravertebral Muscles and Back Muscle Strength: A Cross-Sectional Analysis of a Prospective Cohort Study of Elderly Population.

Trunk muscles play an important role in supporting the spinal column. A decline in trunk muscle mass, as measured by bioelectrical impedance analysis (TMM-BIA), is associated with low back pain and poor quality of life. The purpose of this study was to determine whether TMM-BIA correlates with quantitative and functional assessments traditionally used for the trunk muscles. We included 380 participants (aged ≥ 65 years; 152 males, 228 females) from the Shiraniwa Elderly Cohort (Shiraniwa) study, for whom the following data were available: TMM-BIA, lumbar magnetic resonance imaging (MRI), and back muscle strength (BMS). We measured the cross-sectional area (CSA) and fat-free CSA of the paravertebral muscles (PVM), including the erector spinae (ES), multifidus (MF), and psoas major (PM), on an axial lumbar MRI at L3/4. The correlation between TMM-BIA and the CSA of PVM, fat-free CSA of PVM, and BMS was investigated. TMM-BIA correlated with the CSA of total PVM and each individual PVM. A stronger correlation between TMM-BIA and fat-free CSA of PVM was observed. The TMM-BIA also strongly correlated with BMS. TMM-BIA is an easy and reliable way to evaluate the trunk muscle mass in a clinical setting.

Relationship of back muscle and knee extensors with the compensatory mechanism of sagittal alignment in a community-dwelling elderly population.

Compensatory mechanisms, such as a decrease in thoracic spine kyphosis and posterior tilting or rotation of the pelvis, aim to achieve optimal alignment of the spine. However, the effect of muscle strength on these compensatory mechanisms has not been elucidated. This study aimed to investigate the impact of back muscle and lower extremity strength on compensatory mechanisms in elderly people. Overall, 409 community-dwelling elderly participants (164 men, 245 women) were included. Age, disc degeneration, and 2 or more vertebral fractures showed a significant increase of risk for sagittal vertical axis (SVA) deterioration. Conversely, stronger back, hip flexor, and knee extensor muscles reduced the risk for SVA deterioration. To investigate the association of each muscle's strength with compensatory mechanisms, 162 subjects with pelvic incidence-lumbar lordosis > 10° were selected. The linear regression model for thoracic kyphosis demonstrated a negative correlation with back muscle strength and positive correlation with vertebral fracture. The regression analysis for pelvic tilt demonstrated a positive correlation with knee extensor strength. Back, hip flexor, and knee extensor muscle strength were associated with sagittal spinal alignment. Back muscle strength was important for the decrease in thoracic kyphosis, and knee extensor strength was associated with pelvic tilt.

Predictors of dropout from cohort study due to deterioration in health status, with focus on sarcopenia, locomotive syndrome, and frailty: From the Shiraniwa Elderly Cohort (Shiraniwa) study.

BACKGROUND: Conditions of the elderly like sarcopenia, locomotive syndrome, and frailty have been attracting attention recently. However, the relationship of these 3 conditions and the difference in the magnitude of influence each has on deterioration in health status remain unclear. The purpose of this study was to investigate the prevalence and relationship of sarcopenia, locomotive syndrome, and frailty, and to clarify their influence on the dropout from cohort study due to deterioration in health status. METHODS: The 1st survey of the Shiraniwa Elderly Cohort (Shiraniwa) study was conducted in 2016. We examined 409 participants (aged ≥ 65 years; 164 males, 245 females) and assessed sarcopenia, locomotive syndrome, and frailty. Those who could not attend the 2nd survey (2017) due to deterioration in health status were defined as the Dropout group. We investigated the predictors of Dropout using multiple logistic regression analysis. RESULTS: The prevalence of sarcopenia, locomotive syndrome stage 2, and frailty were 4.4%, 40.1%, and 14.2%, respectively; 89.7% of participants with frailty were also diagnosed with locomotive syndrome stage 2. From the results of the 2nd survey, 46 people were classified into the Dropout group. Independent predictors of the Dropout were locomotive syndrome stage 2 (adjusted odds ratio [OR]: 2.42, 95% confidence interval [CI]: 1.11-5.31) and frailty (adjusted OR: 3.37, 95%CI: 1.56-7.30). CONCLUSIONS: Locomotive syndrome stage 2 was the most common condition in the elderly, and most people with frailty also had locomotive syndrome stage 2. Locomotive syndrome stage 2 and frailty independently influenced the dropout from cohort study due to deterioration in health status. These results suggest that screening for locomotive syndrome is useful for early detection of the elderly with a risk of deterioration in health status, and screening for frailty may contribute to detecting the elderly with higher risk of deterioration in health status.