Association of Time-of-Day Energy Intake Patterns with Nutrient Intakes, Diet Quality, and Insulin Resistance

Abstract

Evidence shows time-of-day of energy intake are associated with health outcomes; however, studies of time-of-day energy patterns and their health implication are still lacking in the Asian population. This study aims to examine the time-of-day energy intake pattern of Chinese adults and to examine its associations with nutrient intakes, diet quality, and insulin resistance. Dietary data from three 24-h recalls collected during the 2015 China Health and Nutrition Survey (CHNS) were analyzed (n = 8726, aged ≥ 18 years). Time-of-day energy intake patterns were determined by latent class analysis (LCA). General Linear Models and Multilevel Mixed-effects Logistic Regression Models were applied to investigate the associations between latent time-of-day energy intake patterns, energy-adjusted nutrient intakes, diet quality score, and insulin resistance. Three time-of-day energy intake patterns were identified. Participants in the “Evening dominant pattern” were younger, had higher proportions of alcohol drinkers and current smokers. The “Evening dominant pattern” was associated with higher daily energy intake and a higher percentage of energy from fat (%) (p < 0.001), as well as higher insulin resistance risk (OR = 1.21; 95% CI: 1.05, 1.40), after adjusting for multivariate covariates. The highest diet quality score was observed in participants with “Noon dominant pattern” (p < 0.001). A higher proportion of energy in the later of the day was associated with insulin resistance in free-living individuals.

The Effect of Four Weeks Dietary Intervention with 8-Hour Time-Restricted Eating on Body Composition and Cardiometabolic Risk Factors in Young Adults

“…To strengthen the effect of TRE on weight loss, meal composition may be taken into account. Future studies should examine the effect of TRE in a larger sample over longer time periods to confirm our findings [ 34 ].…”

“…However, when we evaluated nutrient intake by meal, we found that the weight grain group had a significantly higher intake of saturated fat from dinner. According to previous findings, greater energy intake later in the day is significantly associated with lower insulin sensitivity [ 6 , 34 ] and night-time eating (25% or more of total energy consumed after 9 p.m.) is significantly associated with increased prevalence of metabolic syndrome [ 31 ]. Further investigations are needed to explore whether dietary quality or meal composition can enhance the positive effects of TRE on weight control and health outcomes.…”

Eating Earlier and More Frequently Is Associated With Better Diet Quality in Female Brazilian Breast Cancer Survivors Using Tamoxifen

“…Emerging studies have found that later eating and lower eating frequency are associated with poor diet quality 18,[21][22][23] and an increase in total energy intake. [24][25][26][27] In addition, skipping breakfast and higher evening food intake seem to be well established in the literature as important indicators of nutritional risk, with a substantial role in weight gain and obesity. 18,[28][29][30] Lower eating frequency has also been found to have a major role in obesity.…”

Trajectories of energy intake distribution and subsequent risk of hyperglycemia among Chinese adults: findings from the China Health and Nutrition Survey (1997–2018)

“…1 Estimated trajectory groups of energy intake distribution among Chinese adults. Lines with a diamond represent Group 1, labeled "Energy evenly distributed with steady trend group"; Lines with a square represent Group 2, labeled "Dinner and lunch energy dominant with relatively steady trend group"; Lines with a triangle represent Group 3, labeled "Dinner energy dominant with increasing trend and breakfast energy with declining trend group"; Lines with a point represent Group 4, labeled "breakfast and dinner energy dominant with increasing trend group" Table 1 Baseline characteristics by the four estimated latent trajectory groups Total physical activity [high (i.e., total physical activity days ≥ 7 days/week and total physical activity level ≥ 3000 METs-min/week), medium (i.e., total physical activity days ≥ 5 days/week and total physical activity level ≥ 600 METs-min/week), and low (i.e., physical activity not meeting the above medium and high grouping criteria) [17]]; community urbanicity index, calculated based on 12 multi-dimensional components including physical, social, cultural and economic environment of the community [18]; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; CDGI (2019)-A score, calculated based on 13 food-related components and 1 nutrient-related component reflecting compliance for meeting the Chinese Dietary Guidelines 2016 [19]; EI%, percentage of total energy intake setting by latent class analysis in a previous study [24]. However, none of these studies investigated secular trend of energy intake contribution from meals.…”

“…Using latent class analysis, Leech et al [ 11 ] examined temporal eating patterns of Australian adults based on whether or not an eating occasion occurred within each hour of the day. We also examined the time-of-day of energy intake pattern of Chinese adults in a cross-sectional setting by latent class analysis in a previous study [ 24 ]. However, none of these studies investigated secular trend of energy intake contribution from meals.…”