Secular Trend Analysis of NHANES Data Suggests Only Modest Increases in Health-Related Lifestyle Advice Delivered by Health Professionals
Bibliographic record
Abstract
Chronic non-communicable diseases are widespread in the US and exert a high burden on its society. Poor lifestyle habits contribute to this contemporary public health crisis. To address the prevalence of non-communicable diseases and related risk factors in Americans, we studied trends in US health professionals’ delivery of health-related lifestyle advice. The major aim was to identify trends and long-term directions in the predicted probability of lifestyle advice delivery. We conducted a secular trend analysis of 18 426 participant reports over 4 consecutive National Health and Nutrition Examination Survey cycles (2011-2018) to estimate the predict probability of their receiving specific lifestyle recommendations by a health professional. Lifestyle-related advice included: (1) sodium or salt intake monitoring; (2) physical activity or exercise encouragement; (3) fat or calorie intake monitoring; and (4) weight control within the last 12 months. In all 4 analyzed NHANES cycles combined, 24.79% (CI: 23.52-26.11) of participants received advice to reduce salt intake, 39.91% (CI: 38.67-41.16) were told to exercise and 30.01% (28.73-31.32) were advised to reduce fat/calories. Compared with 2011-2012, modest increases were observed in 2017-2018 across all lifestyle recommendations; about one-third of participants reported receiving advice to reduce sodium/salt/calories or control/lose weight. The predicted number of lifestyle recommendations received increased over the examined time frame (contrast for 2017-2018 vs 2011-2012: +0.23 (0.13-0.35), P < .001). Health professionals’ competency in delivering health-related lifestyle advice appears deficient warranting its prioritization given health promotion is an established accredited health professional competency comparable to drug prescription.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".