Why a shorter eating window may not mean better metabolic health

When people eat may matter as much as what they eat, as researchers uncover distinct daily eating patterns linked to striking differences in metabolic health.

Study: Later Energy Intake within a Shorter Eating Window is Associated with Adverse Metabolic Profiles among Korean Adults. Image Credit: neontetra1 / Shutterstock

Study: Later Energy Intake within a Shorter Eating Window is Associated with Adverse Metabolic Profiles among Korean Adults. Image Credit: neontetra1 / Shutterstock

In a recent nationally representative cross-sectional study published in The Journal of Nutrition, researchers investigated the associations between time-related eating patterns and metabolic syndrome (MetS) and obesity in Korean adults.

MetS and obesity are major risk factors for metabolic disease. The prevalence of MetS and obesity in Korea was 28.6% and 38%, respectively, in 2022. Diet has been posited as a significant modifiable determinant of these conditions. Research also suggests that chrononutrition, or the timing of eating, plays an important role in metabolic health.

Food intake helps synchronize circadian clocks, whereas eating at biologically inappropriate times may disrupt circadian rhythms. Human and animal studies link meal timing to MetS and obesity. In mice, feeding in the light phase, the typical resting phase, led to greater energy intake and weight gain than feeding in the dark phase.

In humans, delayed first meal intake is associated with higher fasting blood glucose (FBG), waist circumference (WC), and diastolic blood pressure (BP). However, most studies have relied on self-reported questionnaires to assess meal timing and have focused on individual aspects of eating behavior.

About the study

In the present study, researchers examined time-related eating patterns and their relationship with MetS and obesity in Korean adults. The study included participants from the seventh and eighth cycles of the Korean National Health and Nutrition Examination Survey conducted from 2016 to 2021. Participants who were pregnant or lactating, had been diagnosed with or were taking medication for hypertension, dyslipidemia, or diabetes, reported implausible energy intakes, or had missing dietary, metabolic, anthropometric, or covariate data were excluded.

Dietary intake was evaluated using a single 24-hour dietary recall; participants reported beverages and foods consumed on the preceding day, including timing, portion sizes, and ingredients. Nutrient and energy intakes were determined using a food composition database. The Korean Healthy Eating Index was used to assess diet quality. An eating occasion was defined as an eating or drinking episode that provided at least 50 kcal at a single time point and was separated from another occasion by more than 15 minutes. The team defined morning, midday, and evening eating as energy intake from 5 AM to 10:59 AM, 11 AM to 4:59 PM, and from 5 PM onwards, respectively.

The time from the first to the last eating occasion of the day defined the eating window, with the first eating occasion occurring at or after 5 AM. The time by which half of the total energy had been consumed was the caloric midpoint. MetS was defined as having at least three of the following: FBG ≥ 100 mg/dL, triglycerides ≥ 150 mg/dL, high-density lipoprotein cholesterol < 40 mg/dL (or < 50 for females), abdominal obesity (WC ≥ 90 cm [or ≥ 85 for females]), and high BP (systolic ≥ 130 mmHg or diastolic ≥ 85 mmHg). Obesity was described as having a body mass index (BMI) ≥ 25 kg/m2.

K-means clustering was applied to the eating window, the number of eating occasions, and the morning and evening energy proportions to derive time-related eating patterns. Logistic regression was performed to assess the associations between time-related eating patterns and MetS and obesity.

Analyses were adjusted for age, sex, education, income, marital status, alcohol consumption, shift work, smoking status, physical activity, sleep duration, total energy intake, BMI (where appropriate), and seasoned-food and prudent dietary patterns derived from factor analysis. Sensitivity analyses using the Korean Healthy Eating Index or specific dietary risk factors instead produced broadly consistent findings.

Findings

The team identified three time-related eating patterns: early, late-short, and grazing. Among nearly 17,000 participants, 36.2% showed an early eating pattern, 32.7% exhibited a grazing pattern, and 31.1% had a late-short pattern. The early pattern entailed the highest proportion of daily energy intake before 11 AM, the lowest after 5 PM, and the earliest caloric midpoint.

There was a relatively even distribution of energy intake in the early pattern. The grazing pattern was characterized by the longest eating window and the highest number of eating occasions. The late-short pattern had the lowest proportion of daily energy intake before 11 AM, the highest after 5 PM, the shortest eating window, the latest caloric midpoint, and the fewest eating occasions.

The late-short pattern was associated with increased odds of MetS and related risk factors, such as high BP, triglycerides, and FBG, compared to the early pattern. Meanwhile, grazing was associated with increased odds of high FBG and lower odds of abdominal obesity and obesity compared to the early pattern. Sex-stratified analyses yielded consistent results, and the main associations remained broadly consistent across sensitivity analyses.

Conclusions

Collectively, participants with the late-short eating pattern were more likely to have MetS and higher BP, FBG, and triglycerides than those with the early eating pattern. Further, participants with the grazing pattern had higher odds of elevated FBG and lower odds of abdominal obesity and obesity.

The authors cautioned that the cross-sectional design cannot establish causality and that the single 24-hour dietary recall may not reflect habitual eating patterns. Residual confounding and incomplete information on sleep timing may also have influenced the findings. 

Overall, the findings suggest that the distribution and timing of energy intake throughout the day are associated with metabolic health after accounting for diet quality and total energy intake.

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