Prevalence and factors associated with sarcopenia among urban and rural Indian adults in middle age: A cross-sectional study from Western India
Why this work is in the frame
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Bibliographic record
Abstract
Sarcopenia is the age-related loss of muscle mass and function. India has 8.6% of the global elderly (>60 years) population, and this is expected to increase to 20% by 2050. Around 70% of Indians live in rural areas where lifestyle factors like diet and physical activity differ from urban areas. Understanding age, sex and location-specific sarcopenia prevalence in India is crucial. Thus, our aim was to assess the prevalence and determinants of sarcopenia in urban and rural community-dwelling men and women aged 40 years and older, representing the next generation of older Indian adults. This cross-sectional study included 745 adults (400 women) from urban and rural areas near Pune, Western India. Assessments included socio-demography, diet by-24-hr recall, physical activity, anthropometry (height, weight), muscle mass measurement by dual-energy X-ray absorptiometry, muscle strength (hand grip) & muscle function by Short Physical Performance Battery (SPPB). Sarcopenia was defined by Asian Working Group on Sarcopenia-2019 guidelines Mean age of participants was 53±7.6yrs. Overall prevalence of sarcopenia was 10% and of severe sarcopenia was 4.2%. Sarcopenia prevalence was higher in rural (14.8%) than urban (6.8%) participants and in men (12.5%) than women (8%, all p<0.05). Muscle mass, grip strength and SPPB score were all higher in urban than rural participants (p<0.05). Older age, rural residence, inadequate protein intake, and lower socio-economic status were independently associated with sarcopenia. In this middle-aged group, sarcopenia prevalence was similar to that observed in older Western populations, over 100% higher among rural than urban participants, and higher amongst men than women. Age, location, protein intake and socioeconomic status were factors associated with sarcopenia. Given this rapidly increasing population of older adults in India there is an urgent need to plan strategies for early sarcopenia diagnosis and management, especially in rural populations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it