Association of macronutrient consumption quality, food source and timing with depression among US adults: A cross-sectional study.

BACKGROUND: Growing evidence suggests that meal timing may influence dietary choices and mental health. Thus, this study examined the association between macronutrient consumption quality, food source, meal timing, and depression prevalence in Americans. METHODS: 23,313 National Health and Nutrition Survey participants from 2007 to 2016 were included in this cross-sectional study. Macronutrient intake was calculated for all day, dinner, and breakfast and subtypes into 4 classes. Based on the Patient Health Questionnaire, depression was defined as a 9-item score ≥ 10 on the PHQ-9. The correlation between macronutrients and depression prevalence was estimated with multivariable logistic regression models and isocaloric substitution effects. RESULTS: Low-quality carbohydrates (OR = 1.54, 95 % CI: 1.11, 2.12) were positively linked to depression compared with the lowest quartile, after adjusting for age and other covariates. In contrast, total high-quality carbohydrate (OR = 0.52, 95 % CI: 0.40, 0.66), total animal protein (OR = 0.60, 95 % CI: 0.45, 0.80), and total vegetable protein (OR = 0.61, 95 % CI: 0.43, 0.85) were negatively associated with depression was negatively associated. Replacing low-quality carbohydrates with high-quality carbohydrates throughout the day reduced the risk of depression by approximately 15 %. LIMITATIONS: Cross-sectional data. CONCLUSION: All in all, diet plays a crucial role in the prevention and treatment of depression. Especially in terms of macronutrient intake, high-quality, moderate intake can reduce the risk of depression. However, different subtypes of macronutrient consumption may have different effects on depression, so it becomes crucial to carefully consider the selection and combination of macronutrients.

Associations of the magnesium depletion score and magnesium intake with diabetes among US adults: an analysis of the National Health and Nutrition Examination Survey 2011-2018.

Objectives: The magnesium depletion score (MDS) is considered more reliable than traditional approaches for predicting magnesium deficiency in humans. We explored the associations of MDS and dietary magnesium intake with diabetes. Methods: We obtained data from 18,853 participants in the National Health and Nutrition Examination Survey 2011-2018. Using multivariate regression and stratified analysis, we investigated the relationships of both MDS and magnesium intake with diabetes. To compute prevalence ratios (PRs), we employed modified Poisson or log-binomial regression. We characterized the nonlinear association between magnesium intake and diabetes using restricted cubic spline analysis. Results: Participants with MDS ≥2 exhibited a PR of 1.26 (95% confidence interval [CI], 1.19 to 1.34) for diabetes. Per-SD increase in dietary magnesium intake was associated with a lower prevalence of diabetes (PR=0.91; 95% CI, 0.87 to 0.96). Subgroup analyses revealed a positive association between MDS ≥2 and diabetes across all levels of dietary magnesium intake, including the lowest (PR=1.35; 95% CI, 1.18 to 1.55), middle (PR=1.23; 95% CI, 1.12 to 1.35), and highest tertiles (PR=1.25; 95% CI, 1.13 to 1.37; pinteraction<0.001). Per-SD increase in magnesium intake was associated with lower diabetes prevalence in participants with MDS <2 (PR=0.92; 95% CI, 0.87 to 0.98) and those with MDS ≥2 (PR=0.91; 95% CI, 0.84 to 0.98; pinteraction=0.030). Conclusion: MDS is associated with diabetes, particularly among individuals with low magnesium intake. Adequate dietary magnesium intake may reduce diabetes risk, especially in those with high MDS.

Associations of sleeping, sedentary and physical activity with phenotypic age acceleration: a cross-sectional isotemporal substitution model.

BACKGROUND: Physical activity was believed to be associated with reduced aging among adults, while the competing nature of the physical activity and sedentary behavior has mainly been neglected in studies. We aimed to estimate the association of sleeping, sedentary behavior, and physical activity with aging among adults, considering the competing nature between variables of activity status. METHODS: A total of 5288 participants who were 20 years or older from the National Health and Nutrition Examination Survey were involved. The questionnaire was used to collect data regarding sociodemographics (age, sex, ethnicity/race, and education), and lifestyle behaviors (smoking, drinking). The Global Physical Activity Questionnaire was used to measure self-reported time for sedentary behavior, walking/bicycling, and moderate-to-vigorous physical activity (MVPA). The sleeping duration was obtained via interview. Phenotypic age acceleration (PhenoAgeAccel) was calculated as an aging index using nine chemistry biomarkers. Isotemporal substitution models using multivariable linear regression to examine the associations of sleeping, sedentary behavior, and physical activity with PhenoAgeAccel, stratified by MVPA (< 150 min/week, ≥ 150 min/week). RESULTS: Thirty minutes per day spent on sedentary behavior was positively associated with PhenoAgeAccel (ß = 0.07, 95% CI: 0.04, 0.11), and 30 min/day spent on leisure-time MVPA was adversely associated with PhenoAgeAccel (ß = - 0.55, 95% CI: - 0.73, - 0.38). Replacing 30 min/day sedentary behaviors with 30 min/day of MVPA (ß = -3.98, 95% CI: -6.22, -1.74) or 30 min/day of walking/bicycling (ß = -0.89, 95% CI: -1.10, -0.68) was adversely associated with PhenoAgeAccel. Substituting 30 min/day of walking/bicycling for 30 min/day of leisure-time MVPA was positively associated with PhenoAgeAccel (ß = 3.09, 95% CI: 0.93, 5.25). CONCLUSION: Sedentary behavior was positively associated with aging. Replacing sedentary behaviors with walking/bicycling or MVPA was adversely associated with aging among adults.