RESUMO
A loss of skeletal muscle mass and an increase in intramuscular fat are known to occur as we enter middle and older age, but the expected changes or normative values have remained unknown. The primary reason for this is that imaging studies are difficult and expensive to conduct, and consequently, the sample sizes have remained small. The development of the UK Biobank which provides access to a large magnetic resonance imaging (MRI) data set of more than 50,000 participants provides an opportunity to finally address this question of normative values for each age group. The study's primary aim was to determine the age-related changes in thigh muscle composition (e.g., thigh fat-free muscle volume and intramuscular fat) between the ages of 45 and 84 years. The second aim was to analyse associations between thigh fat-free muscle volume and intramuscular fat with lifestyle behaviours (smoking, alcohol consumption, and physical activity), leg pain, and bone mineral density. Fifty thousand three hundred thirty-two participants were included in the study. Total fat-free thigh muscle declined between the ages of 45 and 84 years, while intramuscular fat of the thigh continued to increase. The changes were stable between these age groups. The mean volume of fat-free muscle ranged from 11.16 (SD: 1.40) to 13.26 L (SD: 1.85) in adult males and 7.60 (SD: 0.97) to 8.80 L (SD 1.29) in females between the ages of 45 and 84 years. For intramuscular fat, the change among women was from 6.94% (SD: 1.59) in the 45 to 54 years age bracket to 8.83% (SD: 1.92) in the 75 to 84 age bracket, while for men, it was 5.83% (SD: 1.30) in the 45 to 54 age bracket to 7.85% (SD 1.89) in the 75 to 84 age bracket. The total fat-free muscle volume and intramuscular fat percentage provided can be used for the purpose of reference standards or normative values for adults in the age groups provided. Fat-free muscle and intramuscular fat were found to be associated with a range of health, activity, and leg pain outcomes, and these should be investigated in a follow-up longitudinal imaging study.
RESUMO
BACKGROUND CONTEXT: The role of lumbar paraspinal muscle health in back pain (BP) is not straightforward. Challenges in this field have included the lack of tools and large, heterogenous datasets to interrogate the association between muscle health and BP. Computer-vision models have been transformative in this space, enabling the automated quantification of muscle health and the processing of large datasets. PURPOSE: To investigate the associations between lumbar paraspinal muscle health and age, sex, BMI, physical activity, and BP in a large, heterogenous dataset using an automated computer-vision model. DESIGN: Cross-sectional study. PATIENT SAMPLE: Participants from the UK Biobank with abdominal Dixon fat-water MRI (N=9,564) were included (41.8% women, mean [SD] age: 63.5 [7.6] years, BMI: 26.4 [4.1] kg/m2) of whom 6,953 reported no pain, 930 acute BP, and 1,681 chronic BP. OUTCOME MEASURES: Intramuscular fat (IMF) and average cross-sectional area (aCSA) were automatically derived using a computer-vision model for the left and right lumbar multifidus (LM), erector spinae (ES), and psoas major (PM) from the L1 to L5 vertebral levels. METHODS: Two-tailed partial Pearson correlations were generated for each muscle to assess the relationships between the muscle measures (IMF and aCSA) and age (controlling for BMI, sex, and physical activity), BMI (controlling for age, sex, and physical activity), and physical activity (controlling for age, sex, and BMI). One-way ANCOVA was used to identify sex differences in IMF and aCSA for each muscle while controlling for age, BMI, and physical activity. Similarly, one-way ANCOVA was used to identify between-group differences (no pain, acute BP, and chronic BP) for each muscle and along the superior-inferior expanse of the lumbar spine while controlling for age, BMI, sex, and physical activity (α=0.05). RESULTS: Females had higher IMF (LM mean difference [MD]=11.1%, ES MD=10.2%, PM MD=0.3%, p<.001) and lower aCSA (LM MD=47.6 mm2, ES MD=350.0 mm2, PM MD=321.5 mm2, p<.001) for all muscles. Higher age was associated with higher IMF and lower aCSA for all muscles (r≥0.232, p<.001) except for LM and aCSA (r≤0.013, p≥.267). Higher BMI was associated with higher IMF and aCSA for all muscles (r≥0.174, p<.001). Higher physical activity was associated with lower IMF and higher aCSA for all muscles (r≥0.036, p≤.002) except for LM and aCSA (r≤0.010, p≥.405). People with chronic BP had higher IMF and lower aCSA than people with no pain (IMF MD≤1.6%, aCSA MD≤27.4 mm2, p<.001) and higher IMF compared to acute BP (IMF MD≤1.1%, p≤.044). The differences between people with BP and people with no pain were not spatially localized to the inferior lumbar levels but broadly distributed across the lumbar spine. CONCLUSIONS: Paraspinal muscle health is associated with age, BMI, sex, and physical activity with the exception of the association between LM aCSA and age and physical activity. People with BP (chronic>acute) have higher IMF and lower aCSA than people reporting no pain. The differences were not localized but broadly distributed across the lumbar spine. When interpreting measures of paraspinal muscle health in the research or clinical setting, the associations with age, BMI, sex, and physical activity should be considered.