Temporal trends and age-period-cohort analysis of depression in U.S. adults from 2013 to 2022.

BACKGROUND: In the United States, the lifetime prevalence of depression in the US population is 20.6 %. We aimed to understand the temporal trends in the prevalence of depression among adults in the United States during the period 2013-2022 as well as the effects of age, period, and cohort effects on the prevalence of depression. METHODS: Data from 3,139,488 participants in the U.S. Behavioral Risk Factor Surveillance System (BRFSS) from 2013 to 2022 were used in this study. The joinpoint regression model was used to calculate annual percentage change (APC) and average annual percentage change (AAPC) to learn about the time trends in the prevalence of depression. Age-period-cohort models were used to estimate the effects of age, period, and birth cohort effects on the prevalence of depression. RESULTS: The prevalence of depression among adults in the United States showed an overall increasing trend from 2013 to 2022. The rate of increase was greater in males than females, with AAPC values of 1.44 % (95 % CI: 0.32-2.18), and 1.23 % (95 % CI: 0.32-2.25), respectively. Regarding the age effect, the risk of depression among adults in the United States generally showed an increasing and then decreasing trend with age. The risk of developing the condition reached its maximum at 50-54 years (RR = 1.28, 95 % CI = 1.26-1.30). Regarding the period effect, the risk of depression among US adults was higher during 2018-2022 than during 2013-2017. The overall cohort effect for depression prevalence was a higher risk for those born later, with a maximum RR of 1.51 (95 % CI: 1.47-1.54). CONCLUSION: The prevalence of adult depression in the United States is showing an increasing trend. Middle-aged people and those born later in life deserve more attention as high-risk groups. It is recommended that the condition burden of depression be reduced with the promotion of healthy lifestyles, the promotion of interpersonal communication, as well as enhanced mental health education and mental health literacy.

Body mass index mediates the association between four dietary indices and phenotypic age acceleration in adults: a cross-sectional study.

Background: Diet and body mass index (BMI) are widely recognized as being closely associated with aging. However, it remains unclear which dietary indices are associated with aging, and the extent to which BMI mediates the relationship between diet and aging. Therefore, this study investigates the mediating role of BMI in the association between various dietary indices and phenotypic age acceleration (PhenoAgeAccel). Methods: Data were sourced from the National Health and Nutrition Examination Survey (NHANES), using two 24 hour recall interviews to compute four dietary indices: the Dietary Inflammatory Index (DII), Healthy Eating Index-2020 (HEI-2020), Alternative Healthy Eating Index-2010 (AHEI-2010), and Composite Dietary Antioxidant Index (CDAI). Linear regression analyses and mediation analyses assessed the associations between dietary indices and PhenoAgeAccel and the mediating effects of BMI. Z-score transformations (zDII, zHEI-2020, zAHEI-2010, and zCDAI) were used to ensure comparability between different dietary indices. Results: After adjusting for covariates, the zHEI-2020, zAHEI-2010, and zCDAI were negatively associated with PhenoAgeAccel (P < 0.05), with ß values being -0.36, -0.40, and -0.41, respectively. The zDII was positively associated with PhenoAgeAccel (P < 0.001) with a ß value of 0.70. Mediation analyses suggested that BMI significantly mediated the relationships between these dietary indices and PhenoAgeAccel. The mediation proportions were 23.7% for zDII, 43.3% for zHEI-2020, 24.5% for zAHEI-2010, and 23.6% for zCDAI. Conclusions: This study indicates that all dietary indices and BMI were significantly associated with PhenoAgeAccel. In addition, BMI exhibited the highest mediation proportion in the relationship between HEI-2020 and PhenoAgeAccel.