Temporal Dietary Patterns Are Associated with Obesity in US Adults

Temporal patterns of energy intake identified by the latent class analysis in relation to prevalence of overweight and obesity in Iranian adults

We aimed to identify temporal patterns of energy intake and investigate their association with adiposity. We performed a cross-sectional study of 775 adults in Iran. Information about eating occasions across the day was collected by three 24-h dietary recalls. Latent class analysis (LCA) was used to identify temporal eating patterns based on whether or not an eating occasion occurred within each hour of the day. We applied binary logistic regression to estimate the OR and 95 % CI of overweight and obesity (defined as BMI of 25-29·9 and ≥ 30 kg/m2, respectively) across temporal eating patterns while controlling for potential confounders. LCA grouped participants into three exclusive sub-groups named 'Conventional', 'Earlier breakfast' and 'Later lunch'. The 'Conventional' class was characterised by high probability of eating occasions at conventional meal times. 'Earlier breakfast' class was characterised by high probability of a breakfast eating occasion 1 h before the conventional pattern and a dinner eating occasion 1 h after the conventional pattern, and the 'Later lunch' class was characterised by a high probability of a lunch eating occasion 1 h after the conventional pattern. Participants in the 'Earlier breakfast' pattern had a lower likelihood of obesity (adjusted OR: 0·56, 95 % CI: 0·35, 0·95) as compared with the 'Conventional' pattern. There was no difference in the prevalence of obesity or overweight between participants in the 'Later lunch' and the 'Conventional' patterns. We found an inverse association between earlier eating pattern and the likelihood of obesity, but reverse causation may be a plausible explanation.

Higher energy consumption in the evening is associated with increased odds of obesity and metabolic syndrome: findings from the 2016-2018 Korea National Health and Nutrition Examination Survey (7th KNHANES)

OBJECTIVES

Chrono-nutrition emphasizes meal timing in preventing obesity and metabolic disorders. This study explores the impact of temporal dietary patterns (TDPs) on obesity and metabolic syndrome (MetS) in Korean adults aged 20 years to 65 years.

METHODS

We utilized dynamic time warping method and Kernel k-means clustering to investigate diet quality and the odds ratios (ORs) of obesity and MetS with different TDPs using data from the 7th Korea National Health and Nutrition Examination Survey.

RESULTS

Participants were divided into three groups based on relative energy intake over 24 hours. After adjusting for age and gender, Cluster 3 (with the highest proportion of energy intake in the evening) had the lowest Healthy Eating Index scores compared to other clusters. Following adjustment for key covariates, Cluster 3 showed the highest values for body mass index, waist circumference, blood pressure, total cholesterol, and triglycerides. Compared to Cluster 1 (with a lower proportion of energy intake in the evening), Cluster 2 and Cluster 3 had ORs for obesity of 1.12 (95% confidence interval [CI], 0.97 to 1.30) and 1.19 (95% CI, 1.03 to 1.37), respectively. For MetS, the ORs were 1.26 (95% CI, 1.08 to 1.48) and 1.37 (95% CI, 1.17 to 1.61) when comparing Cluster 2 and Cluster 3 to Cluster 1.

CONCLUSIONS

This study reveals that individuals with higher energy intake in the evening have increased odds of obesity and MetS, even after adjusting for major covariates, including age and total energy intake.

Chrononutrition during Pregnancy and Its Association with Maternal and Offspring Outcomes: A Systematic Review and Meta-Analysis of Ramadan and Non-Ramadan Studies

Much evidence suggests that food intakes and eating patterns are major determinants of the phase of peripheral circadian clocks, and desynchronization between them is thought to contribute to the development of metabolic disorders. However, much remains to be understood about how different dimensions of chrononutrition during pregnancy affect pregnant women's and their offspring's health outcomes. Therefore, we systematically reviewed and integrated all emerging evidence on chrononutrition during pregnancy (including meal skipping, meal frequency, night eating, and (Ramadan) fasting) and their relationships with maternal and offspring outcomes. The results suggest that meal skipping and night eating during pregnancy were generally associated with adverse pregnancy and birth outcomes, whereas no strong conclusion could be reached for meal frequency. In our meta-analysis, Ramadan fasting did not seem to be related with birth weight or gestational age at birth, but evidence for other mother-offspring outcomes was inconsistent. To further elucidate the effect of chrononutrition factors on maternal and offspring health outcomes, larger and well-conducted prospective cohort and interventional studies are needed. In addition, information on covariates such as physical activity, sleep, diet quality and quantity, fasting days, fasting period per day, and trimester exposure should also be collected and considered during analysis.

Research gaps and opportunities in precision nutrition: an NIH workshop report

Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On 11-12 January 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The workshop proceeded in 3 parts: part I covered many aspects of genetics and physiology that mediate the links between nutrient intake and health conditions such as cardiovascular disease, Alzheimer disease, and cancer; part II reviewed potential contributors to interindividual variability in dietary exposures and responses such as baseline nutritional status, circadian rhythm/sleep, environmental exposures, sensory properties of food, stress, inflammation, and the social determinants of health; part III presented the need for systems approaches, with new methods and technologies that can facilitate the study and implementation of precision nutrition, and workforce development needed to create a new generation of researchers. The workshop concluded that much research will be needed before more precise nutrition recommendations can be achieved. This includes better understanding and accounting for variables such as age, sex, ethnicity, medical history, genetics, and social and environmental factors. The advent of new methods and technologies and the availability of considerably more data bring tremendous opportunity. However, the field must proceed with appropriate levels of caution and make sure the factors listed above are all considered, and systems approaches and methods are incorporated. It will be important to develop and train an expanded workforce with the goal of reducing health disparities and improving precision nutritional advice for all Americans.

The Discovery of Data-Driven Temporal Dietary Patterns and a Validation of Their Description Using Energy and Time Cut-Offs

Data-driven temporal dietary patterning (TDP) methods were previously developed. The objectives were to create data-driven temporal dietary patterns and assess concurrent validity of energy and time cut-offs describing the data-driven TDPs by determining their relationships to BMI and waist circumference (WC). The first day 24-h dietary recall timing and amounts of energy for 17,915 U.S. adults of the National Health and Nutrition Examination Survey 2007−2016 were used to create clusters representing four TDPs using dynamic time warping and the kernel k-means clustering algorithm. Energy and time cut-offs were extracted from visualization of the data-derived TDPs and then applied to the data to find cut-off-derived TDPs. The strength of TDP relationships with BMI and WC were assessed using adjusted multivariate regression and compared. Both methods showed a cluster, representing a TDP with proportionally equivalent average energy consumed during three eating events/day, associated with significantly lower BMI and WC compared to the other three clusters that had one energy intake peak/day at 13:00, 18:00, and 19:00 (all p < 0.0001). Participant clusters of the methods were highly overlapped (>83%) and showed similar relationships with obesity. Data-driven TDP was validated using descriptive cut-offs and hold promise for obesity interventions and translation to dietary guidance.

Evaluation of the Chrononutrition Profile - Questionnaire in an online community sample of adults

Chrononutrition (i.e., circadian timing of food intake) has been linked to indicators of health status such as body weight and insulin resistance. A measure of general chrononutrition patterns, the Chrononutrition Profile - Questionnaire, has been developed and preliminary evidence of validity and reliability of the measure has been documented in a homogenous group of undergraduates. However, this measure has not yet been validated in an online, community-based sample. The present study therefore aimed to evaluate the validity of the Chrononutrition Profile - Questionnaire in a web-based community sample. Analyses suggested that the Chrononutrition Profile - Questionnaire displays acceptable validity for use in diverse community samples of adults, with moderate to strong correlations (r = 0.39-0.91) between the Chrononutrition Profile - Questionnaire and measures of dietary intake and sleep. This measure is suitable for use in a variety of settings, by stakeholders and scientists, and may contribute to future development of health behavior interventions and research programs centered around chrononutrition.

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

AIMS

Few studies have examined the secular trend of the energy intake distribution, and its effect on future risk of hyperglycemia. This study aims to describe trajectories of energy intake distribution over 12 years and relate them to subsequent risk of hyperglycemia over 9 years of follow-up.

METHODS

Our study used ten waves of data from the CHNS survey, a population-based longitudinal survey in China, ongoing since 1989. We examined a cohort of adult participants who were free from diabetes but had at least three waves of dietary data from 1997 to 2009. We assessed energy intake using three consecutive 24 h recalls. We used these data to identify trajectory groups of energy intake distribution by multi-trajectory model based on energy intake proportions of breakfast, lunch, and dinner. We followed up participants for hyperglycemia, diabetes, and impaired fasting glucose for 9 years from 2009 to 2018. Outcomes were ascertained with fasting glucose, serum HbA1c, and self-report of diabetes and/or glucose-lowering medication. We estimated relative risk (RR) for hyperglycemia, diabetes, and impaired fasting glucose by identified trajectory groups using multilevel mixed-effects modified Poisson regression with robust (sandwich) estimation of variance. Gender difference was additionally examined.

RESULTS

A total of 4417 participants were included. Four trajectory groups were identified, characterized and labeled by "Energy evenly distributed with steady trend group" (Group 1), "Dinner and lunch energy dominant with relatively steady trend group" (Group 2), "Dinner energy dominant with increasing trend and breakfast energy with declining trend group" (Group 3), and "breakfast and dinner energy dominant with increasing trend group" (Group 4). During 48,091 person-years, 1053 cases of incident hyperglycemia occurred, 537 cases of incident diabetes occurred, and 516 cases of impaired fasting glucose occurred. Compared with Group 1, Group 3 was associated with higher subsequent risk of incident hyperglycemia in 9 years of follow-up (RR = 1.28, 95% CI = 1.02, 1.61). No association was found for incident diabetes and impaired fasting glucose. Among males, Group 3 was associated with higher risk of incident hyperglycemia in 9 years of follow-up (RR = 1.44, 95% CI = 1.07, 1.94). No relationship was found in females.

CONCLUSIONS

Energy intake distribution characterized by over 40% of energy intake from dinner with a rising trend over years was associated with higher long-term risk of hyperglycemia in Chinese adults.

Joint temporal dietary and physical activity patterns: associations with health status indicators and chronic diseases

BACKGROUND

Diet and physical activity (PA) are independent risk factors for obesity and chronic diseases including type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS). The temporal sequence of these exposures may be used to create patterns with relations to health status indicators.

OBJECTIVES

The objectives were to create clusters of joint temporal dietary and PA patterns (JTDPAPs) and to determine their association with health status indicators including BMI, waist circumference (WC), fasting plasma glucose, glycated hemoglobin, triglycerides, HDL cholesterol, total cholesterol, blood pressure, and disease status including obesity, T2DM, and MetS in US adults.

METHODS

A 24-h dietary recall and random day of accelerometer data of 1836 participants from the cross-sectional NHANES 2003-2006 data were used to create JTDPAP clusters by constrained dynamic time warping, coupled with a kernel k-means clustering algorithm. Multivariate regression models determined associations between the 4 JTDPAP clusters and health and disease status indicators, controlling for potential confounders and adjusting for multiple comparisons.

RESULTS

A JTDPAP cluster with proportionally equivalent energy consumed at 2 main eating occasions reaching ≤1600 and ≤2200 kcal from 11:00 to 13:00 and from 17:00 to 20:00, respectively, and the highest PA counts among 4 clusters from 08:00 to 20:00, was associated with significantly lower BMI (P < 0.0001), WC (P = 0.0001), total cholesterol (P = 0.02), and odds of obesity (OR: 0.2; 95% CI: 0.1, 0.5) than a JTDPAP cluster with proportionally equivalent energy consumed reaching ≤1600 and ≤1800 kcal from 11:00 to 14:00 and from 17:00 to 21:00, respectively, and high PA counts from 09:00 to 12:00.

CONCLUSIONS

The joint temporally patterned sequence of diet and PA can be used to cluster individuals with meaningful associations to BMI, WC, total cholesterol, and obesity. Temporal patterns hold promise for future development of lifestyle patterns that integrate additional temporal and contextual activities.

Trajectories of Energy Intake Distribution and Risk of Dyslipidemia: Findings from the China Health and Nutrition Survey (1991-2018)

Few studies have examined the secular trend of energy intake distribution. This study aims to describe trajectories of energy intake distribution and determine their association with dyslipidemia risk. Data of 2843 adult participants from the China Health and Nutrition Survey (CHNS) were analyzed. Trajectory groups of energy intake distribution were identified by multi-trajectory model over 27 years. Multilevel mixed-effects modified Poisson regression with robust estimation of variance was used to calculate risk ratio for incident dyslipidemia in a 9-year follow-up. Four trajectory groups were identified: "Energy evenly distributed group" (Group 1), "Lunch and dinner energy dominant group" (Group 2), "Dinner energy dominant group" (Group 3), "breakfast and dinner energy dominant group" (Group 4). Compared with Group 1, Group 3 was associated with higher risk of dyslipidemia (RR = 1.48, 95% CI = 1.26, 1.75), hypercholesterolemia (RR = 1.96, 95% CI = 1.37, 2.81) and high low-density lipoproteins cholesterols (LDL-C) (RR = 2.41, 95% CI = 1.82, 3.20). A U-shape was observed between cumulative average proportion of dinner energy and dyslipidemia risk (p for non-linear = 0.01), with stronger relationship at 40% and above. Energy intake distribution characterized by higher proportion of dinner energy, especially over 40% was associated with higher dyslipidemia risk in Chinese adults.

Dietary patterns related to total mortality and cancer mortality in the United States

Purpose

This study investigated the association between dietary patterns, total mortality, and cancer mortality in the United States.

Methods

We identified the four major dietary patterns at baseline from 13,466 participants of the NHANES III cohort using principal component analysis (PCA). Dietary patterns were categorized into ‘prudent’ (fruits and vegetables), ‘western’ (red meat, sweets, pastries, oils), ‘traditional’ (red meat, legumes, potatoes, bread), and ‘fish and alcohol’. We estimated hazard ratios for total mortality, and cancer mortality using Cox regression models.

Results

A total of 4,963 deaths were documented after a mean follow-up of 19.59 years. Higher adherence to the ‘prudent’ pattern was associated with the lowest risk of total mortality (5th vs. 1st quintile HR 0.90, 95% CI 0.82–0.98), with evidence that all-cause mortality decreased as consumption of the pattern increased. No evidence was found that the ‘prudent’ pattern reduced cancer mortality. The ‘western’ and the ‘traditional’ patterns were associated with up to 22% and 16% increased risk for total mortality (5th vs. 1st quintile HR 1.22, 95% CI 1.11–1.34; and 5th vs. 1st quintile HR 1.16, 95% CI 1.06–1.27, respectively), and up to 33% and 15% increased risk for cancer mortality (5th vs. 1st quintile HR 1.33, 95% CI 1.10–1.62; and 5th vs. 1st quintile HR 1.15, 95% CI 1.06–1.24, respectively). The associations between adherence to the ‘fish and alcohol’ pattern and total mortality, and cancer mortality were not statistically significant.

Conclusion

Higher adherence to the ‘prudent’ diet decreased the risk of all-cause mortality but did not affect cancer mortality. Greater adherence to the ‘western’ and ‘traditional’ diet increased the risk of total mortality and mortality due to cancer.

Temporal physical activity patterns are associated with obesity in U.S. adults

Few attempts have been made to incorporate multiple aspects of physical activity (PA) to classify patterns linked with health. Temporal PA patterns integrating time and activity counts were created to determine their association with health status. Accelerometry data from the National Health and Nutrition Examination Survey 2003-2006 was used to pattern PA counts and time of activity from 1999 adults with one weekday of activity. Dynamic time warping and kernel k-means clustering partitioned 4 participant clusters representing temporal PA patterns. Multivariate regression models determined associations between clusters and health status indicators and obesity, type 2 diabetes, and metabolic syndrome. Cluster 1 with a temporal PA pattern of the lowest activity counts reaching 4.8e4 cph from 6:00-23:00 was associated with higher body mass index (BMI) (β = 2.5 ± 0.6 kg/m2, 95% CI: 1.0, 4.1), higher waist circumference (WC) (β = 6.4 ± 1.3 cm, 95% CI: 2.8, 10.0), and higher odds of obesity (OR: 2.4; 95% CI: 1.3, 4.4) compared with Cluster 3 with activity counts reaching 9.6e4-1.2e5 cph between 16:00-21:00. Cluster 1 was also associated with higher BMI (β = 1.5 ± 0.5 kg/m2, 95% CI: 0.1, 2.8) and WC (β = 3.6 ± 1.3 cm, 95% CI: 0.1, 7.0) compared to Cluster 4 with activity counts reaching 9.6e4 cph between 8:00-11:00. A Temporal PA pattern with the lowest PA counts had significantly higher mean BMI and WC compared to temporal PA patterns of higher activity counts performed early (8:00-11:00) or late (16:00-21:00) throughout the day. Temporal PA patterns appear to meaningfully link to health status.

Expanding the Capabilities of Nutrition Research and Health Promotion Through Mobile-Based Applications

Mobile-based applications are popular and prevalently used in the US population. Applications focusing on nutrition offer platforms for quantifying and changing behaviors to improve dietary intake. Such behavior changes can intervene in the relation of diet to promote health and prevent disease. Mobile applications offer a safe and convenient way to collect user data and share it back to users, researchers, and to health care providers. Other lifestyle factors like activity, sleep, and sedentary behavior, can also be quantified and included in investigations of how lifestyle is related to health. Yet, challenges in the assessment offered through mobile applications and effectiveness to change behavior still remain, including rigorous evaluation, demonstration of successful health improvement, and participant engagement. The data mobile applications generate, however, expands opportunities for discovery of the integrated and time-based nature of various daily activities in relation to health. This article is a summary of a symposium at Nutrition 2020 Live Online on the role of mobile applications as a tool for nutrition research and health promotion. The types and capabilities of mobile applications, challenges in their evaluation and use in research, and opportunities for the data they generate along with a specific example, are reviewed.

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

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.