Association Between Self-Reported Protective Behavior and Heat-Associated Health Complaints Among Patients With Chronic Diseases in Primary Care: Results of the CLIMATE Pilot Cohort Study
Notice bibliographique
Résumé
BACKGROUND: As a result of climate change, exposure to high temperatures is becoming more common, even in countries with temperate climates. For patients with chronic diseases, heat poses significant health risks. Empowering patients is a crucial element in protecting the population from the adverse effects of heat. In this context, self-reports of protective behavior are often used to gain a mutual understanding of patients' issues. However, the extent to which self-reported behavior is associated with health complaints remains unclear. OBJECTIVE: This study aims to describe the association between light to moderate heat and health complaints in everyday life, and to analyze whether self-reported protective behavior and related psychosocial factors are linked to these complaints. METHODS: We conducted a pilot cohort study using internet climate data merged with an online survey of patients with chronic diseases recruited through general practitioner practices. Patients were eligible if they were 18 years or older and had at least one chronic disease. The heat was modeled using temperature and humidity data. Health complaints were assessed through up to 7 follow-up evaluations on the hottest day of each week during the observation period. Data were analyzed using 3 nested models with mixed effects multivariable linear regression, adjusting for random effects at the climate measuring station and participant levels. Model 1 included heat exposure, sociodemographic data, and chronic diseases. Model 2 added protective behavior and health literacy, while model 3 incorporated self-efficacy and somatosensory amplification (ie, the tendency to catastrophize normal bodily sensations such as insect bites). RESULTS: Of the 291 eligible patients, 61 (21.0%) participated in the study, providing 294 observations. On average, participants were 61 (SD 14) years old, and 31 (51%) were men. The most prevalent conditions were cardiovascular diseases (n=23, 38%) and diabetes mellitus (n=20, 33%). The most commonly reported symptoms were tiredness/fatigue (232/294 observations, 78.9%) and shortness of breath (142/294 observations, 48.3%). Compared with temperatures of 27°C or lower, a heat index between over 27°C and 32°C (β=1.02, 95% CI 0.08-1.96, P=.03) and over 32°C (β=1.35, 95% CI 0.35-2.35, P=.008) were associated with a higher symptom burden. Lower health literacy (β=-0.25, 95% CI -0.49 to -0.01, P=.04) and better self-reported protective behavior (β=0.65, 95% CI 0.29-1.00, P<.001) were also linked to increased symptom burden but lost statistical significance in model 3. Instead, lower self-efficacy (β=-0.39, 95% CI -0.54 to -0.23, P<.001) and higher somatosensory amplification (β=0.18, 95% CI 0.07-0.28, P=.001) were associated with a higher symptom burden. CONCLUSIONS: Compared with colder weather, light and moderate heat were associated with more severe health complaints. Symptom burden was lower in participants with higher self-efficacy and less somatosensory amplification. Self-reported protective behavior was not linked to a lower symptom burden. Instead, we found that patients who tended to catastrophize normal bodily sensations reported both better protective behavior and a higher symptom burden simultaneously. TRIAL REGISTRATION: ClinicalTrials.gov NCT05961163; https://clinicaltrials.gov/ct2/show/NCT05961163.
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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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».