Diet can exert both analgesic and pronociceptive effects in acute and chronic pain models: a systematic review of preclinical studies.

BACKGROUND: Although diet is an essential aspect of human health, the link between diet and pain is still not well understood. Preclinical animal research provides information to understand underlying mechanisms that allow identifying the needs for human research. OBJECTIVES: This study aims to give a systematic overview of the current evidence from preclinical studies regarding the analgesic and pronociceptive effects of various diets in non-neuropathic, non-cancer, or non-visceral acute and chronic pain models. STUDY DESIGN: A systematic Review. SETTING: This study examined studies that investigate the analgesic and pronociceptive effects of various diets in non-neuropathic, non-cancer, or non-visceral acute and chronic pain models. METHODS: This review was conducted following the PRISMA guidelines and was registered in PROSPERO with the registration number CRD42019133473. The certainty of evidence was examined by a modified GRADE approach. RESULTS: After the screening process twenty-four eligible papers were included in this review. Nineteen studies examined acute pain, nine studies chronic inflammatory pain, and four studies assessed both acute and chronic pain models. LIMITATIONS: Due to the heterogeneity of the included studies, a meta-analysis was not included in this study. CONCLUSIONS: In animal models, excessive saturated, monounsaturated or omega-6 polyunsaturated fat ingestion and diets rich in fats and carbohydrates can decrease pain sensitivity in acute nociceptive pain, whereas it can induce mechanical allodynia and heat hyperalgesia in chronic inflammatory pain. Additionally, diets rich in anti-inflammatory ingredients, as well as a calorie-restricted diet can promote recovery from primary mechanical allodynia and heat hyperalgesia in chronic inflammatory pain.

Fitbit's accuracy to measure short bouts of stepping and sedentary behaviour: validation, sensitivity and specificity study.

Objective: This study aims to assess the suitability of Fitbit devices for real-time physical activity (PA) and sedentary behaviour (SB) monitoring in the context of just-in-time adaptive interventions (JITAIs) and event-based ecological momentary assessment (EMA) studies. Methods: Thirty-seven adults (18-65 years) and 32 older adults (65+) from Belgium and the Czech Republic wore four devices simultaneously for 3 days: two Fitbit models on the wrist, an ActiGraph GT3X+ at the hip and an ActivPAL at the thigh. Accuracy measures included mean (absolute) error and mean (absolute) percentage error. Concurrent validity was assessed using Lin's concordance correlation coefficient and Bland-Altman analyses. Fitbit's sensitivity and specificity for detecting stepping events across different thresholds and durations were calculated compared to ActiGraph, while ROC curve analyses identified optimal Fitbit thresholds for detecting sedentary events according to ActivPAL. Results: Fitbits demonstrated validity in measuring steps on a short time scale compared to ActiGraph. Except for stepping above 120 steps/min in older adults, both Fitbit models detected stepping bouts in adults and older adults with sensitivities and specificities exceeding 87% and 97%, respectively. Optimal cut-off values for identifying prolonged sitting bouts achieved sensitivities and specificities greater than 93% and 89%, respectively. Conclusions: This study provides practical insights into using Fitbit devices in JITAIs and event-based EMA studies among adults and older adults. Fitbits' reasonable accuracy in detecting short bouts of stepping and SB makes them suitable for triggering JITAI prompts or EMA questionnaires following a PA or SB event of interest.

Sedentary patterns and health outcomes in the oldest-old: a latent profile analysis.

Background: Sedentary behavior is most prevalent among those aged 80 years and above, referred to as the oldest-old. Current literature emphasizes the significance of sedentary behavior patterns, but further evidence is required to understand how these patterns relate to specific health outcomes and to identify at-risk profiles for tailored interventions in the oldest-old. Therefore, the aim of this study was to identify profiles of adults aged 80+ years based on their sedentary patterns and health outcomes, and to examine associations between profiles and socio-demographics. Methods: A cross-sectional study was conducted in Flanders (Belgium) from February 2021 to December 2022 recruiting 90 older adults (80+) through convenience sampling, employing word of mouth, social media and local service centers. Latent profile analysis identified device-based sedentary patterns and assessed their associations with physical and cognitive functioning, mental health-related quality of life (QoL), and social isolation. Associations of these profiles with socio-demographic factors were analyzed. Results: Three distinct profiles were identified: (1) the 'cognitively and physically frail' profile, (2) the 'healthy' profile and (3) the 'lower mental health-related QoL' profile. Those in the 'cognitively and physically frail' profile exhibited the least favorable sedentary pattern, and had a higher likelihood of residing in a nursing home. No significant differences were found for the other socio-demographic variables, being age, sex, educational degree and family situation. Conclusions: Three distinct profiles in the oldest-old population, based on cognitive and physical functioning, mental health-related QoL, and sedentary behavior patterns, were identified. Lower physical and cognitive functioning was associated with unhealthy sedentary patterns. Further research with larger samples is crucial to uncover potential links between socio-demographics and at-risk subgroups, enhancing our understanding of sedentary behavior and geriatric health outcomes in this population.