Background/Objectives: Sleep health has been associated with diet quality, but the relationship between chrononutrition patterns and multidimensional sleep health is unclear. This study identifies chrononutrition patterns among U.S. adults and examines their associations with multidimensional sleep health. Methods: This cross-sectional analysis used data from the 2017–2020 National Health and Nutrition Examination Survey. Chrononutrition behaviors were assessed using two 24 h dietary recalls. Latent profile analysis was used to identify chrononutrition profiles. Multivariable survey regression models determined the associations between chrononutrition patterns and sleep health dimensions. Results: The sample included 5228 subjects with a median age of 49 years. Of the sample, 52% of the participants were female, and 65% were White. In adjusted models, each additional hour between wake time and first instance of eating was associated with a 19% increase in the odds of poor timing (sleep midpoint < 2:00 a.m. or >4:00 a.m.; 95% CI: 1.07–1.33) and a 21% increase in poor duration (9 h/night; 95% CI: 1.09–1.33). Each additional hour between last eating and bedtime was associated with 9% higher odds of poor duration (95% CI: 1.03–1.16). A one-hour longer eating window was associated with 10% lower odds of poor timing (95% CI: 0.84–0.98). We identified five chrononutrition profiles: Typical Eating (reference), Early Finished Eating, Later Heavy Eating, Extended Window Eating, and Restricted Window Eating. The Later Heavy Eating profile exhibited 96% higher odds of poor timing (95% CI: 1.09–3.51) and the Restricted Window Eating profile had 94% higher odds of poor duration (95% CI: 1.10–3.43). Conclusions: These findings highlight the importance of unique chrononutrition patterns in relation to multidimensional sleep health. We provide a framework for future studies to identify personalized chrononutrition interventions and their role in improving sleep health.

Introduction: Obesity is associated with cardiometabolic diseases, and chrononutrition has become a novel weight loss strategy. However, few have characterized chrononutrition patterns among people attempting weight loss. This study characterizes chrononutrition patterns in a nationally representative sample of U.S. adults who attempted weight loss in the past year through dietary modifications by weight change and adiposity. Methods: This cross-sectional analysis utilizes NHANES 2017–2020 data. Chrononutrition patterns were assessed using 24 h dietary recalls. Participants self-reported weight loss attempts in the past year and if they tried using diet modification. Weight change (loss, maintenance, and gain) was defined based on differences in current weight and weight one year prior. We used latent profile analysis and descriptive statistics. Results: The sample included 2107 participants who attempted weight loss in the past year through diet modification (median age 47; 58% women and 62% white). Individuals who gained weight (vs. loss) had longer hours between waketime and the first eating (1.78 vs. 1.62 h, p = 0.024), consumed a lower proportion of calories later in the day (43% vs. 52%, p < 0.001), and ate less frequently (5.20 vs. 5.43 episodes, p = 0.008). Participants with obesity had the shortest eating window (11.77 vs. 12.22 h, p = 0.02) despite a longer delay between waketime and the first eating (1.80 vs. 1.29 h, p < 0.001) and lower eating frequency (5.16 vs. 5.97, p < 0.001). Conclusions: Variations in eating timing, eating episodes, and caloric distribution suggest that chrononutrition may play a role in personalized weight management strategies.

Purpose: Nighttime fasting intervals (NFIs; i.e., the longest period between the last eating episode of the day and the first of the next day) are associated with depressive symptoms in non-pregnant populations. However, this chrono-nutrition indicator has rarely been explored in the perinatal period, when individuals experience dramatic physiological and psychological changes. We explored potential associations between NFIs and depressive symptoms during the perinatal period. Methods: This secondary analysis included 232 individuals with pre-pregnancy body mass index (BMI) ≥25 kg/m ² . Participants were assessed during early-pregnancy, mid-pregnancy, and at 6-months postpartum. NFIs and breakfast time were estimated from 24-hour dietary recall interviews, and depressive symptoms were self-reported using the Center for Epidemiologic Studies Depression Scale. NFIs were categorized into three classifications to represent short, middle, and long NFIs. Longitudinal associations were evaluated using mixed effects linear models with interaction terms between NFIs and each timepoint. Results: NFIs remained largely stable at the group level across the three study visits (M [SD] = 12.7 [2.75] hours). Although NFIs were not significantly associated with depressive symptoms, long NFIs showed geometric mean ratio of 0.84 (95% CI: 0.64 to1.11) relative to middle NFIs at mid-pregnancy. Conclusions: NFIs and depression were not associated among this perinatal sample. Future studies should explore circadian eating patterns (e.g., the timing of the last eating episode relative to dim-light melatonin onset), different timepoints (e.g., late pregnancy), and pregnant individuals across the weight spectrum.

Was not provided for this article.

Objective: We examined cross-sectional associations between mid-pregnancy food intake indicators and prenatal depressive symptomatology. Methods: This secondary analysis of the Comparison of Two Screening Strategies for Gestational Diabetes (GDM2) trial (N = 716) examined five domains of mid-pregnancy food intake (direct timing, energy timing, meal/snack structure, meal energy distribution, and diet quality) derived from 24 h dietary recalls. Depressive symptoms were measured with the Edinburgh Postnatal Depression Scale (EPDS). Generalized linear models examined associations between food intake indicators and both total and high (EPDS ≥ 13) depressive symptoms. Results: The mean (SD) EPDS score was 6.3 (4.9); a total of 12.4% (n = 89) of subjects had high depressive symptoms. Eating frequency (exp(B) = 1.084 [1.021, 1.151], p = 0.008), snack frequency (exp(B) = 1.063 [1.004, 1.126], p = 0.037), nighttime snacking frequency (exp(B) = 1.060 [1.003, 0.121], p = 0.040), and total daily energy intake (exp(B) = 1.058 [1.002, 1.118], p = 0.044) were positively associated with total depressive symptoms. Energy intake from breakfast (PR = 1.178 [1.029, 1.349], p = 0.017) was associated with higher prevalence of high depressive symptoms. Energy intake from dinner (PR = 0.809 [0.695, 0.943], p = 0.007), a later timing of the first eating episode (PR = 0.830 [0.699, 0.986], p = 0.034) and the first energy quartile (PR = 0.837 [0.702, 0.998], p = 0.048) were associated with lower prevalence of high depressive symptoms. Conclusions: These findings extend the prior chrononutrition–depression literature to the prenatal period, implicating eating frequency, energy intake, and meal energy timing and distribution in depressive symptomatology during pregnancy, and warrant further longitudinal investigation.

Aim: Examine cross-sectional associations between mid-pregnancy food intake indicators and prenatal depressive symptomatology. Methods: This secondary analysis of the Comparison of Two Screening Strategies for Gestational Diabetes trial (N = 718) examined domains of mid-pregnancy food intake (direct timing, energy timing, meal/snack structure, meal energy distribution, diet quality) derived from 24-hour dietary recalls. Depressive symptoms were measured with the Edinburgh Postnatal Depression Scale (EPDS). Generalized linear models examined associations between food intake indicators, total, and high (EPDS ≥13) depressive symptoms. Results: Mean (SD) EPDS score was [6.3 (4.9)]; 12.4% (n = 89) had high depressive symptoms. Eating frequency (B = 0.08 [0.02, 0.14], p = 0.009), snack frequency (B = 0.06 [0.00, 0.12], p = 0.040), nighttime snacking frequency (B = 0.06 [0.00, 0.11], p = 0.041), and total daily energy intake (B = 0.06 [0.01, 0.12], p = 0.031) were positively associated with total depressive symptoms. Energy intake from breakfast (PR = 1.2 [1.0, 1.3], p = 0.017) was associated with a higher prevalence of high depressive symptoms. Energy intake from dinner (PR = 0.81 [0.69, 0.94], p = 0.007), later timing of the first eating episode (PR = 0.83 [0.70, 0.99], p = 0.034) and first energy quartile (PR = 0.84 [0.70, 1.0], p = 0.048), were associated with a lower prevalence of high depressive symptoms. Conclusion: These findings extend prior chrononutrition-depression literature to the prenatal period, implicating eating frequency, energy intake, and meal energy timing and distribution in depressive symptomatology during pregnancy, warranting further longitudinal investigation. Key Messages: Eating frequency, snacking, nighttime snacking, and longer eating windows were positively associated with increased prevalence of depressive symptomatology within the prenatal period. Each of these results align with previous literature in general adult or postpartum populations and extend to prenatal populations specifically. These results suggest the role of circadian misalignment (potentially via mechanisms including nocturnal cortisol response, serotonin and dopamine dysregulation, systemic inflammation, and delayed melatonin production) in prenatal psychopathology. Importantly, the potential bidirectional nature of food intake and depression cannot be overlooked. Total energy consumed per day, percentage of energy from breakfast and dinner, as well as later timing of initial energy intake and first caloric quartile were positively associated with prenatal depression. Additionally, particular indicators of dietary quality and macronutrient percentages (e.g., percentage of energy obtained from fat), were not significantly associated with prenatal depression. These findings call for future research to explore nuance regarding macronutrient consumption, energy intake percentages, meal timing regularity, and the possible implications of emotionally responsive eating in the relationship between food intake and prenatal depression The current study is exploratory in nature, being the first to explore a robust range of food intake indicators and their relationship to depressive symptomatology in the prenatal period. As prenatal depression is a strong predictor of worsening mental health during postpartum, it is important that future research test a priori hypotheses regarding food intake indicators and prenatal depression longitudinally in order to determine both temporal precedence and validate the associations found within our study. If validated, multiple domains of food intake may potentially provide modifiable behaviors that can protect against depression during the prenatal period.