Health-Promoting Lifestyle Behaviour: A Determinant for Noncommunicable Diseases Risk Factors Among Employees in a Nigerian University
Bibliographic record
Abstract
INTRODUCTION: Overweight, hyperglycaemia and hypertension are risk factors for development of cardiovascular diseases that have the highest mortality and morbidity rates among noncommunicable diseases (NCDs) globally. The aim of this study was to examine the health-promoting lifestyle behaviour that determine risk factors for Noncommunicable diseases among university employees in Nigeria. METHODS: We conducted a cross-sectional survey among university employees in Nigeria. Data were collected from 280 employees in the university by means of a questionnaire that consisted of three sections. Collected data were analysed using IBM-SPSS version 25. RESULTS: Good physical activity lifestyle behaviour (adjusted odds ratio [aOR] = 2.1, 95% CI: [1.1–3.9]) and good health responsibility lifestyle behaviour (aOR = 2.4, 95% CI: [1.2–4.9]) were statistically significant predictors of normal body mass index. Also, good health-promoting lifestyle profile (HPLP) (aOR = 3.1, 95% CI: [1.3–7.6]) was a statistically significant predictor of normal waist–hip ratio. However, there is no statistically significant relationship between HPLP and random blood sugar or between HPLP and blood pressure. CONCLUSION: The findings from the study reveal that good health-promoting lifestyle behaviour especially health responsibility, physical activity and stress management behaviour are determinant of overweight and obesity which are major risk factors for development of cardiovascular diseases, type II diabetes and some form of cancer. Hence, to reduce the risk of developing noncommunicable diseases, there is a need to develop an intervention to improve university employee’s health-promoting lifestyle.
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How this classification was reachedexpand
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 | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".