US Adults Practicing Healthy Lifestyles Before and During COVID-19: Comparative Analysis of National Surveys
Bibliographic record
Abstract
BACKGROUND: Practicing healthy lifestyles can reduce the risk to develop noncommunicable diseases and the related mortality. Studies showed that practicing healthy lifestyles could enhance disease-free life expectancy and preserve bodily functions. However, engagement in healthy lifestyle behavior was suboptimal. OBJECTIVE: This study aimed to define individuals' lifestyle characteristics before and during COVID-19 and determine the factors associated with practicing a healthy lifestyle. This cross-sectional study was conducted using data from the 2019 and 2021 Behavioral Risk Factor Surveillance System surveys. METHODS: US individuals aged ≥18 years were interviewed via phone call. Healthy lifestyles were assessed through corresponding questions regarding the maintenance of optimal body weight, physical activity, daily consumption of at least five portions of fruits and vegetables, current smoking status, and alcohol consumption. Missing data were imputed using a package in the R statistical software. The effects of practicing a healthy lifestyle on cases without missing data and those with imputation were reported. RESULTS: There were 550,607 respondents (272,543 and 278,064 from 2019 and 2021, respectively) included in this analysis. The rates of practicing a healthy lifestyle were 4% (10,955/272,543) and 3.6% (10,139/278,064) in 2019 and 2021, respectively. Although 36.6% (160,629/438,693) of all 2021 respondents had missing data, the results of the logistic regression analysis for cases without missing data and those with imputation were similar. Of the cases with imputation, women (odds ratio [OR] 1.87) residing in urban areas (OR 1.24) with high education levels (OR 1.73) and good or better health status (OR 1.59) were more likely to practice healthier lifestyles than young individuals (OR 0.51-0.67) with a low household income (OR 0.74-0.78) and chronic health conditions (OR 0.48-0.74). CONCLUSIONS: A healthy lifestyle should be strongly promoted at the community level. In particular, factors associated with a low rate of practice of healthy lifestyles should be targeted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".