Effect of obesity on spinal loads during load-reaching activities: A subject- and kinematics-specific musculoskeletal modeling approach

The relationship between weight-adjusted-waist index and suicidal ideation: evidence from NHANES

BACKGROUND

Amidst growing evidence of the intricate link between physical and mental health, this study aims to dissect the relationship between the waist-to-weight index (WWI) and suicidal ideation within a representative sample of the US population, proposing WWI as a novel metric for suicide risk assessment.

METHODS

The study engaged a sample of 9500 participants in a cross-sectional design. It employed multivariate logistic and linear regression analyses to probe the association between WWI and suicidal ideation. It further examined potential nonlinear dynamics using a weighted generalized additive model alongside stratified analyses to test the relationship's consistency across diverse demographic and health variables.

RESULTS

Our analysis revealed a significant positive correlation between increased WWI and heightened suicidal ideation, characterized by a nonlinear relationship that persisted in the adjusted model. Subgroup analysis sustained the association's uniformity across varied population segments.

CONCLUSIONS

The study elucidates WWI's effectiveness as a predictive tool for suicidal ideation, underscoring its relevance in mental health evaluations. By highlighting the predictive value of WWI, our findings advocate for the integration of body composition considerations into mental health risk assessments, thereby broadening the scope of suicide prevention strategies.

Effect of low back pain on the kinetics and kinematics of the lumbar spine - a combined in vivo and in silico investigation

Lifting is a significant risk factor for low back pain (LBP). Different biomechanical factors including spinal loads, kinematics, and muscle electromyography (EMG) activities have previously been investigated during lifting activities in LBP patients and asymptomatic individuals to identify their association with LBP. However, the findings were contradictory and inconclusive. Accurate and subject-specific prediction of spinal loads is crucial for understanding, diagnosing, planning tailored treatments, and preventing recurrent pain in LBP patients. Therefore, the present study aimed to estimate the L5-S1 compressive and resultant shear loads in 19 healthy and 17 non-specific chronic LBP individuals during various static load-holding tasks (holding a 10 kg box at hip, chest, and head height) using full-body and personalized musculoskeletal models driven by subject-specific in vivo kinematic/kinetic, EMG, and physiological cross-sectional areas (PCSAs) data. These biomechanical characteristics were concurrently analyzed to identify potential differences between the two groups. Statistical analyses showed that LBP had almost no significant effect on the range of motion (trunk, lumbar, pelvis), PCSA, and EMG. There were no significant differences (p > 0.05) in the predicted L5-S1 loads. However, as the task became more demanding, by elevating the hand-load from hip to head, LBP patients experienced significant increases in both compressive (33 %, p = 0.00) and shear (25 %, p = 0.02) loads, while asymptomatic individuals showed significant increases only in compressive loads (30 %, p = 0.01). This suggests that engaging in more challenging activities could potentially magnify the effect of LBP on the biomechanical factors and increase their discrimination capacity between LBP and asymptomatic individuals.

Evaluation of ground reaction forces and centers of pressure predicted by AnyBody Modeling System during load reaching/handling activities and effects of the prediction errors on model-estimated spinal loads

Full-body and lower-extremity human musculoskeletal models require feet ground reaction forces (GRFs) and centers of pressure (CoPs) as inputs to predict muscle forces and joint loads. GRFs/CoPs are traditionally measured via floor-mounted forceplates that are usually restricted to research laboratories thus limiting their applicability in real occupational and clinical setups. Alternatively, GRFs/CoPs can be estimated via inverse dynamic approaches as also implemented in the Anybody Modeling System (AnyBody Technology, Aalborg, Denmark). The accuracy of Anybody in estimating GRFs/CoPs during load-handling/reaching activities and the effect of its prediction errors on model-estimated spinal loads remain to be investigated. Twelve normal- and over-weight individuals performed total of 480 static load-handling/reaching activities while measuring (by forceplates) and predicting (by AnyBody) their GRFs/CoPs. Moreover, the effects of GRF/CoP prediction errors on the estimated spinal loads were evaluated by inputting measured or predicted GRFs/CoPs into subject-specific musculoskeletal models. Regardless of the subject groups (normal-weight or overweight) and tasks (load-reaching or load-handling), results indicated great agreements between the measured and predicted GRFs (normalized root-mean-squared error, nRMSEs < 14% and R2 > 0.90) and between their model-estimated spinal loads (nRMSEs < 14% and R2 > 0.83). These agreements were good but relatively less satisfactory for CoPs (nRMSEs < 17% and 0.57 < R2 < 0.68). The only exception, requiring a more throughout investigation, was the situation when the ground-foot contact was significantly reduced during the activity. It appears that occupational/clinical investigations performed in real workstation/clinical setups with no access to forceplates may benefit from the AnyBody GRF/CoP prediction tools for a wide range of load-reaching/handling activities.