Impact of healthy lifestyle on the incidence and progression trajectory of mental disorders: A prospective study in the UK Biobank.

BACKGROUND: Healthier lifestyle decreased the risk of mental disorders (MDs) such as depression and anxiety. However, research on the effects of a comprehensive healthy lifestyle on their progression is lacking. METHODS: 385,704 individuals without baseline MDs from the UK Biobank cohort were included. A composite healthy lifestyle score was computed by assessing alcohol intake, smoking status, television viewing time, physical activity, sleep duration, fruit and vegetable intake, oily fish intake, red meat intake, and processed meat intake. Follow-up utilized hospital and death register records. Multistate model was used to examine the role of healthy lifestyle on the progression of specific MDs, while a piecewise Cox regression model was utilized to assess the influence of healthy lifestyle across various phases of disease progression. RESULTS: Higher lifestyle score reduced risks of transitions from baseline to anxiety and depression, as well as from anxiety and depression to comorbidity, with corresponding hazard ratios (HR) and 95 % confidence intervals (CI) of 0.94 (0.93, 0.95), 0.90 (0.89, 0.91), 0.94 (0.91, 0.98), and 0.95 (0.92, 0.98), respectively. Healthier lifestyle decreased the risk of transitioning from anxiety to comorbidity within 2 years post-diagnosis, with HR 0.93 (0.88, 0.98). Higher lifestyle scores at 2-4 years and 4-6 years post-depression onset were associated with reduced risk of comorbidity, with HR 0.93 (0.87, 0.99) and 0.92 (0.86, 0.99), respectively. LIMITATION: The generalizability to other ethnic groups is limited. CONCLUSION: This study observed a protective role of holistic healthy lifestyle in the trajectory of MDs and contributed to identifying critical progression windows.

The association between daytime napping and risk of type 2 diabetes is modulated by inflammation and adiposity: Evidence from 435 342 UK-Biobank participants.

BACKGROUND: Existing evidence concerning the relationship between daytime napping and type 2 diabetes (T2D) is inconsistent, and whether the effects of napping differ by body fat percentage (BFP) and C-reactive protein (CRP) is unclear. We aimed to investigate the association between daytime napping frequency and T2D risk and whether such an association was modified by BFP and CRP. METHODS: We included 435 342 participants free of diabetes from the UK Biobank. Participants were categorized as nonnappers, occasional nappers, and frequent nappers based on napping frequency, and BFP/CRP was divided into quartiles. Cox proportional hazards models were used. RESULTS: During a median follow-up of 9.2 years, 17 592 T2D cases occurred. Higher frequency of daytime napping was significantly associated with an increased risk of T2D. Compared with nonnappers, the adjusted hazard ratios (HRs) for occasional nappers and habitual nappers were 1.28 (95% confidence interval [CI]: 1.24-1.32) and 1.49 (95% CI: 1.41-1.57), respectively. There was a significant additive and multiplicative interaction (relative excess risk due to interaction [RERI] = 0.490, 95% CI 0.307-0.673; p for multiplicative interaction <.001) between napping and BFP, whereby a higher hazard of T2D associated with more frequent napping was greatest among participants in the highest BFP quartile (HR = 4.45, 95% CI: 3.92-5.06). The results for CRP were similar (RERI = 0.266, 95% CI: 0.094-0.439; p for multiplicative interaction <.001). CONCLUSIONS: Higher daytime napping frequency is associated with an increased T2D risk, and such relationships are modified by BFP and CRP. These findings underscore the importance of adiposity and inflammation control to mitigate diabetes risk.

Long-Term Visit-To-Visit Blood Pressure Variability and Risk of Diabetes Mellitus in Chinese Population: A Retrospective Population-Based Study.

Objectives: To examine the association between visit-to-visit blood pressure variability (BPV) and incident diabetes mellitus (DM) risk in a Chinese population. Methods: Data comes from China Health and Nutrition Survey (n = 15,084). BPV was estimated as the average real variability (ARV) using at least three BP measurements from the year preceding the event and was divided into quartiles. Participants were also categorized into 9 groups on the basis of combinations of systolic BPV (SBPV) and diastolic BPV (DBPV) tertiles. Cox proportional hazards regression models were used. Results: During a median follow-up of 16.8 years, 1,030 (6.8%) participants developed diabetes (incidence rate: 4.65/1,000 person-years). The HRs (95% CIs) for the highest quartile (vs. the lowest quartile) of SBPV and DBPV were 1.60 (1.30-1.97) and 1.37 (1.13-1.67), respectively. Participants with both highest SBPV and DBPV tertile had an ≈89% higher risk of DM (HR, 1.89; 95% CI, 1.47-2.42) compared with those in the both SBPV and DBPV tertile 1 group. Conclusion: Higher SBP ARV and DBP ARV were independently associated with increased risk of incident DM, which was augmented when both presented together.