IS PHYSICAL ACTIVITY (PA) BEHAVIOR ANOTHER CASUALTY OF DEPRIVED NEIGHBORHOODS IN PERSONS WITH SYSTEMIC LUPUS ERYTHEMATOSUS (SLE)?
Bibliographic record
Abstract
PV076 / #248 Poster Topic: AS10 - Environment and SLE Background/Purpose SLE, a chronic inflammatory, autoimmune disease with pervasive self-reported fatigue, negatively impacts most individuals with SLE. Because of its recognized benefits in improving oxygen capacity and endurance, physical activity (PA) is one modifiable lifestyle behavior to help reduce fatigue in patients with SLE who are typically not physically active and afraid to exercise. Recent research suggests a role for Social Determinants of Health (SDOH) in identifying environmental impact on medical care and conditions. The Area Deprivation Index (ADI), a composite score which ranks geographical areas of the US based on environmental living conditions, measures neighborhood resources and can estimate SDOH. Lupus Intervention Fatigue Trial (LIFT) is a 12-month phase II randomized, parallel group, single blind 2-arm investigator-initiated trial, comparing effectiveness of a motivational interviewing program intervention combining diet and physical activity strategies vs an educational program control arm to reduce fatigue in persons with lupus ( NCT02653287 ). This ancillary analysis assessed the correlation between objectively measured PA behavior and ADI disadvantage of the participant’s home at the LIFT baseline visit. Methods All LIFT participants met criteria: ≥18 years of age, BMI: 18-40 kg/m2, ambulate household distances (50 ft), classification criteria for SLE per American College of Rheumatology (ACR) or Systemic Lupus International Collaborating Clinics (SLICC). Accelerometers were worn for 7 consecutive days during waking hours to measure daily PA minutes and were categorized as sedentary minutes (<100 counts), light PA (LPA) minutes (100-2019 counts), and moderate-vigorous PA (MVPA) minutes (2020+ counts). Valid PA monitoring was defined as at least 4 days of 10+ hours of accelerometer wear. Weekly MVPA minutes were calculated as mean daily MVPA minutes times 7. The ADI uses nine-digit zip codes to calculate a national ranking score on a scale from 0-100 (low to high deprivation rank). Descriptive statistics were calculated, and the associations between ADI and PA minutes (all categories) were estimated using Spearman correlation. Results Among 160 LIFT participants, mean (SD) age was 43.3 (13) years; 92% identify as female with 52% participants self-identifying as White, 33% Black/African American, 8% Asian, 1% Hawaiian/Pacific Islander, and 5% unknown/not reported; 95% having some college education. The mean (SD) for the following were BMI 27 (5), [disease activity measure] SLEDAI 2.9 (3.1), SLICC/Damage 1.2 (1.6), and ADI 34.7 (21.4), respectively. The total PA daily mean (SD) minutes were 262.3 (83.4); mean (SD) daily minutes category were sedentary 582.8 (92.8), LPA 242.2 (75.5), and MVPA 20.1 (19.6). Thirty-two percent met PA guidelines (≥150 minutes/week of MVPA). Mean daily MVPA minutes correlated with ADI rank, r= -0.20, p= 0.01 (Table 1). Table 1. Spearman Correlations Between PA Measures and ADI in Baseline LIFT Participants (n=160) Conclusions This analysis documents that only 32% of LIFT participants met weekly PA guidelines of > 150 minutes of MVPA at baseline. Mean MVPA minutes were negatively correlated with ADI rank suggesting those participants living in higher ADI deprivation areas had lower MVPA minutes. Future analyses are planned to assess changes in PA between baseline & 6-month visit in the intervention and control groups in LIFT by ADI rank or if other interventions are necessary.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".