The Association between Sweet Sugar Beverage Intakes and the Quality of Sleep in Working Age Adults
Notice bibliographique
Résumé
Background: This cross-sectional study investigates the relationship between daily sugar intake from sugar-sweetened beverages (SSBs) and sleep quality in working adults aged 18–45 years who do not have chronic illnesses or diagnosed sleep disorders. The primary objective is to determine whether high sugar consumption increases the risk of poor sleep when other risk factors are considered simultaneously. This study is significant as it adds to the growing body of evidence regarding the impact of dietary factors on sleep quality, highlighting the potential health implications of sugar consumption. Methods: Participants were selected using consecutive sampling, and the study was conducted at Jomtien Hospital in Chonburi Province, Thailand. Data collection involved three key components: general demographic and health information records, a validated Thai questionnaire assessing sweetened beverage consumption, and the Thai version of the Pittsburgh Sleep Quality Index (PSQI). Sugar intake from SSBs was categorized into two groups: high (≥ 50 grams/day) and low (< 50 grams/day). Sleep quality was classified as poor (PSQI > 5) or good (PSQI ≤ 5). The relationship between sugar intake and sleep quality was analyzed using logistic regression, and the results were presented as odds ratios (ORs) with corresponding 95% confidence intervals (CIs). Results: The study included 300 participants, 68% of whom were women, with an average age of 30 ± 7.6 years. A total of 58% of participants were found to have poor sleep quality. Those with poor sleep quality consumed an average of 131.9 ± 102.9 grams of sugar per day, compared to 99.8 ± 86.3 grams for those with good sleep quality, a difference that was statistically significant (p = 0.005). When sugar consumption was categorized, 79.3% of individuals in the high sugar consumption group (≥ 50 grams/day) had poor sleep quality, compared to 65.1% with good sleep quality in the same group. In contrast, 20.7% of individuals in the low sugar consumption group (< 50 grams/day) had poor sleep quality, compared to 34.9% with good sleep quality, also showing a statistically significant difference (p = 0.008). The crude odds ratio for high sugar consumption associated with poor sleep quality was 2.06 (95% CI: 1.22-3.45, p = 0.006). After adjusting for other variables, the odds ratio remained significant, with an adjusted OR of 2.02 (95% CI: 1.05-3.92, p = 0.036). Conclusion: The findings indicate that high sugar consumption from sugar-sweetened beverages is significantly associated with an increased risk of poor sleep quality (adjusted OR: 2.02, 95% CI: 1.05–3.92, p = 0.036). Based on these results, it is recommended that individuals experiencing sleep issues consider reducing their sugar intake. Future research should explore the mechanisms underlying this relationship and evaluate public health strategies aimed at reducing high sugar consumption.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».