Type 2 diabetes is a major public health concern. Management of this condition has focused on behavior modification through diet and exercise interventions. A growing body of evidence has focused on temporality of dietary intake and exercise and potential effects on health. This review summarizes current literature that investigates the question “how does the timing of exercise relative to eating throughout the day effect postprandial response in adults?” Databases PubMed, Scopus, Cochrane Library, CINAHL, and SPORTDiscus were searched between March–May 2019. Experimental studies conducted in healthy adults (≥18 y) and those with type 2 diabetes were included. Full texts were examined by at least two independent reviewers. Seventeen studies with a total of 332 participants met the inclusion criteria. The primary finding supports that exercise performed post-meal regardless of time of day had a beneficial impact on postprandial glycemia. There was insufficient evidence regarding whether timing of exercise performed pre- vs. post-meal or vice versa in a day is related to improved postprandial glycemic response due to inherent differences between studies. Future studies focusing on the investigation of timing and occurrence of meal intake and exercise throughout the day are needed to inform whether there is, and what is, an optimal time for these behaviors regarding long-term health outcomes.

Background The integration of time with dietary patterns throughout a day, or temporal dietary patterns (TDPs), have been linked with dietary quality but relations to health are unknown. Objective The association between TDPs and selected health status indicators and obesity, type 2 diabetes (T2D), and metabolic syndrome (MetS) was determined. Methods The first-day 24-h dietary recall from 1627 nonpregnant US adult participants aged 20–65 y from the NHANES 2003–2006 was used to determine timing, amount of energy intake, and sequence of eating occasions (EOs). Modified dynamic time warping (MDTW) and kernel k-means algorithm clustered participants into 4 groups representing distinct TDPs. Multivariate regression models determined associations between TDPs and health status, controlling for potential confounders, and adjusting for the survey design and multiple comparisons (P <0.05/6). Results A cluster representing a TDP with evenly spaced, energy balanced EOs reaching ≤1200 kcal between 06:00 to 10:00, 12:00 to 15:00, and 18:00 to 22:00, had statistically significant and clinically meaningful lower mean BMI (P <0.0001), waist circumference (WC) (P <0.0001), and 75% lower odds of obesity compared with 3 other clusters representing patterns with much higher peaks of energy: 1000–2400 kcal between 15:00 and 18:00 (OR: 5.3; 95% CI: 2.8, 10.1), 800–2400 kcal between 11:00 and 15:00 (OR: 4.4; 95% CI: 2.5, 7.9), and 1000–2600 kcal between 18:00 and 23:00 (OR: 6.7; 95% CI: 3.9, 11.6). Conclusions Individuals with a TDP characterized by evenly spaced, energy balanced EOs had significantly lower mean BMI, WC, and odds of obesity compared with the other patterns with higher energy intake peaks at different times throughout the day, providing evidence that incorporating time with other aspects of a dietary pattern may be important to health status.

Background: Few attempts have been made to incorporate multiple aspects of physical activity (PA), including timing and volume, to classify patterns that link to health. Temporal PA patterns integrating time and activity counts were created to determine their association with health. Methods: PA accelerometry data obtained from the cross-sectional National Health and Nutrition Examination Survey 2003-2006 was used to pattern PA counts and time of activity from 1,999 nonpregnant adults with one random valid weekday of activity. Constrained dynamic time warping with Sakoe-Chiba band and kernel k-means clustering grouped participants to 4 clusters representing temporal PA patterns. Multivariate regression models controlling for potential confounders and adjusting for multiple comparisons (p<0.05/6) determined associations between clusters and health status indicators and conditions obesity, type 2 diabetes, and metabolic syndrome.Results: Participants in Cluster 2, represented by a temporal PA pattern with activity counts reaching >1.2e 5 counts/ h (cph) and tapering off through the day, had lower mean body mass index (BMI) (p<0.001), waist circumference (WC) (p<0.01), and 65% lower odds of obesity relative to normal weight status compared with participants in Cluster 1 with the lowest PA counts reaching 4.8e 4 cph from 6:00 to 23:00 (OR: 0.3; 95% CI: 0.2, 0.8). Cluster 3, characterized by a temporal PA pattern with activity counts reaching 9.6e 4 -1.2e 5 cph between 16:00 to 21:00, was associated with lower mean BMI (p<0.001) and WC (p<0.01), and 60% lower odds of obesity relative to normal weight status compared to Cluster 1 (OR: 0.4; 95% CI: 0.2, 0.8). Cluster 4 characterized by activity counts reaching 9.6e 4 cph between 8:00 to 11:00 was associated with lower BMI and WC compared to Cluster 1 (both p<0.05).Conclusions: U.S. adults with temporal PA patterns of higher activity counts ranging between 9.6e 4 ->1.2e 5 cph performed early (8:00 to 11:00), late (16:00 to 21:00), or throughout the day had signi cantly lower mean BMI and WC compared with adults with a temporal PA pattern of the lowest PA counts reaching 4.8e 4 cph from 6:00 to 23:00. Temporal PA patterns created by integrating time with PA counts throughout a day meaningfully link to health status.

Objectives The integration of time with dietary patterns throughout a day, or temporal dietary patterns (TDP), have been linked with dietary quality but links to health outcomes are unknown. TDP were created with the objective to examine their association with health status indicators including body mass index (BMI), waist circumference (WC), fasting plasma glucose, hemoglobin A1c, triglyceride, high-density lipoprotein cholesterol, total cholesterol, blood pressure, and chronic diseases obesity, diabetes, and metabolic syndrome in US adults 20–65 years. Methods The first-day 24-hour dietary recall from 1627 non-pregnant US adult participants of the cross-sectional National Health and Nutrition Examination Survey 2003–2006 was used to determine energy intake (kcal), time of intake (min), and sequence of intake occasions throughout the 24-hour day. Modified dynamic time warping coupled with kernel k-means algorithm, clustered participants into four groups representing distinct TDP. Multivariate regression models determined associations between TDP clusters and all outcomes, controlling for potential confounders, energy misreporting, and adjusting for multiple comparisons and the complex survey design (P &lt; 0.05/6). Results The cluster representing a TDP with proportionally equivalent average energy at three main eating occasions from 8:00 to 23:00 with peaks reaching 175 kcal at 9:00, 13:00, and 19:00, had statistically significant and clinically meaningful lower BMI (P &lt; 0.0001), WC (P &lt; 0.0001) and 75% lower odds of obesity compared to three other clusters representing distinct patterns of much higher average peak energy intake of 500 kcal at 13:00 (odds ratio (OR): 4.4; 95% confidence interval (CI)): 2.5, 7.9), 530 kcal at 18:00 (OR: 5.3; 95% CI: 2.8, 10.1), and 550 kcal at 20:00 (OR: 6.7; 95%CI: 3.9, 11.6). Conclusions A positive association of the TDP of moderate energy intake throughout the day with healthy weight outcomes supports previous findings of higher dietary quality among those with a similar TDP and provides unique evidence that incorporating time with other aspects of a dietary pattern are linked to health. Funding Sources Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health and Purdue University.

Objective: Few attempts to determine dietary patterns have incorporated concepts of time, specifically time and proportion of energy intake consumed throughout a day. A type of modified dynamic time warping (MDTW) was previously developed using an appropriate distance metric for patterning these aspects to determine temporal dietary patterns (TDP). This study further explores dynamic time warping (DTW) distance metrics including unconstrained DTW (UDTW), constrained DTW (CDTW), and MDTW with modern spectral clustering methods to optimize TDP related to dietary quality. MDTW was expected to create TDP with the strongest relationships to dietary quality and distinct visualization among U.S. adults 20-65y of the National Health and Nutrition Examination Survey 1999-2004.Methods: Proportional energy intake by time of day metrics were optimized to create TDP from complete day-one 24-hour dietary recalls using MDTW, UDTW with only a standard local constraint, and CDTW with standard local and global banding constraints, then clustered using spectral clustering. The association between each TDP distance metric clustering and mean dietary quality, as indicated by the 2005 Healthy Eating Index (HEI-2005), were determined using multiple linear regression controlled for potential confounders. Strength of association for each model was compared using adjusted R-squared. The results were also visualized to make qualitative comparisons.Results: Four clusters representing distinct TDP for each distance metric by spectral clustering were generated among participants. MDTW exhibited TDP clusters with strongest associations to HEI compared with the TDP clusters generated from unconstrained and constrained DTW, and visualization of the TDP clusters from MDTW supported the association.