Self-Reported Sitting Time in New York City Adults, The Physical Activity and Transit Survey, 2010–2011
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Recent studies have demonstrated the negative health consequences associated with extended sitting time, including metabolic disturbances and decreased life expectancy. The objectives of this study were to characterize sitting time in an urban adult population and assess the validity of a 2-question method of self-reported sitting time. METHODS: The New York City Health Department conducted the 2010-2011 Physical Activity and Transit Survey (N = 3,597); a subset of participants wore accelerometers for 1 week (n = 667). Self-reported sitting time was assessed from 2 questions on time spent sitting (daytime and evening hours). Sedentary time was defined as accelerometer minutes with less than 100 counts on valid days. Descriptive statistics were used to estimate the prevalence of sitting time by demographic characteristics. Validity of sitting time with accelerometer-measured sedentary time was assessed using Spearman's correlation and Bland-Altman techniques. All data were weighted to be representative of the New York City adult population based on the 2006-2008 American Community Survey. RESULTS: Mean daily self-reported sitting time was 423 minutes; mean accelerometer-measured sedentary time was 490 minutes per day (r = 0.32, P < .001). The mean difference was 49 minutes per day (limits of agreement: -441 to 343). Sitting time was higher in respondents at lower poverty and higher education levels and lower in Hispanics and people who were foreign-born. CONCLUSION: Participants of higher socioeconomic status, who are not typically the focus of health disparities-related research, had the highest sitting times; Hispanics had the lowest levels. Sitting time may be accurately assessed by self-report with the 2-question method for population surveillance but may be limited in accurately characterizing individual-level behavior.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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