Composite Meal-Related Behaviors and Health Indicators: Insight from Large-Scale Nationwide Data on Korean Adults

<b>Objectives:</b> Multidimensional dietary patterns provide a more comprehensive assessment of meal-related behavior than single behaviors, yet evidence on their variation across adulthood and association with health factors relevant to healthy aging is limited. This study examined meal-related behavior pattern distribution by age and identified predictors of unhealthy patterns. <b>Methods:</b> Data from 47,332 adults aged ≥ 18 years in the Korea National Health and Nutrition Examination Survey (2014-2022) were analyzed. Participants were divided into three age groups: young adults (18-39 years), middle-aged adults (40-64 years), and older adults (≥65 years). Within each age group, participants were further classified into three categories based on their adherence to three key meal-related behaviors: High adherence (all three behaviors: regular breakfast, shared mealtimes, and infrequent eating out), Moderate adherence (two behaviors), or Low adherence (one or none). Group differences in sociodemographic, clinical variables, nutrient intake, biochemical markers, and lifestyle factors were tested using ANOVA and Pearson's chi-square, and predictors were identified with multinomial logistic regression. <b>Results</b>: Older adults most frequently showed the High adherence group (51.1%) but had the lowest prevalence of shared mealtimes (66.3%), suggesting social vulnerabilities despite healthy individual habits. Young adults had the highest Low pattern prevalence, which was primarily driven by infrequent breakfast and frequent eating out. Across all ages, poorer patterns were consistently associated with living alone, prolonged sedentary time, and adverse metabolic profiles. Middle-aged adults exhibited moderate adherence to healthy behaviors but showed the highest prevalence of chronic disease. In older adults, poorer patterns were associated with lower intakes of energy, carbohydrate, protein, and dietary fiber intake, alongside higher rates of living alone and sedentary behavior. <b>Conclusions:</b> Composite meal-related behaviors differed across age groups as follows: Young adults most frequently exhibited low adherence, middle-aged adults showed moderate adherence but bore the highest burden of chronic diseases, while older adults demonstrated high breakfast adherence and low frequency of eating out, but faced nutritional insufficiency and social vulnerability. These findings suggest the need for personalized interventions for each age group.

Authors

Institutions

Publication Details

Journal
Nutrients
Published
2025-09-17
DOI
https://doi.org/10.3390/nu17182982
Citations
1
Primary Topic
Obesity, Physical Activity, Diet
Type
article
Field-Weighted Citation Impact
1.88

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Composite Meal-Related Behaviors and Health Indicators: Insight from Large-Scale Nationwide Data on Korean Adults

Seongryu Bae, Hyuntae Park
1 citations
Nutrients
Obesity, Physical Activity, Diet
1.88
article

Composite Meal-Related Behaviors and Health Indicators: Insight from Large-Scale Nationwide Data on Korean Adults

Seongryu Bae, Hyuntae Park
article en
1 citations

Abstract

<b>Objectives:</b> Multidimensional dietary patterns provide a more comprehensive assessment of meal-related behavior than single behaviors, yet evidence on their variation across adulthood and association with health factors relevant to healthy aging is limited. This study examined meal-related behavior pattern distribution by age and identified predictors of unhealthy patterns. <b>Methods:</b> Data from 47,332 adults aged ≥ 18 years in the Korea National Health and Nutrition Examination Survey (2014-2022) were analyzed. Participants were divided into three age groups: young adults (18-39 years), middle-aged adults (40-64 years), and older adults (≥65 years). Within each age group, participants were further classified into three categories based on their adherence to three key meal-related behaviors: High adherence (all three behaviors: regular breakfast, shared mealtimes, and infrequent eating out), Moderate adherence (two behaviors), or Low adherence (one or none). Group differences in sociodemographic, clinical variables, nutrient intake, biochemical markers, and lifestyle factors were tested using ANOVA and Pearson's chi-square, and predictors were identified with multinomial logistic regression. <b>Results</b>: Older adults most frequently showed the High adherence group (51.1%) but had the lowest prevalence of shared mealtimes (66.3%), suggesting social vulnerabilities despite healthy individual habits. Young adults had the highest Low pattern prevalence, which was primarily driven by infrequent breakfast and frequent eating out. Across all ages, poorer patterns were consistently associated with living alone, prolonged sedentary time, and adverse metabolic profiles. Middle-aged adults exhibited moderate adherence to healthy behaviors but showed the highest prevalence of chronic disease. In older adults, poorer patterns were associated with lower intakes of energy, carbohydrate, protein, and dietary fiber intake, alongside higher rates of living alone and sedentary behavior. <b>Conclusions:</b> Composite meal-related behaviors differed across age groups as follows: Young adults most frequently exhibited low adherence, middle-aged adults showed moderate adherence but bore the highest burden of chronic diseases, while older adults demonstrated high breakfast adherence and low frequency of eating out, but faced nutritional insufficiency and social vulnerability. These findings suggest the need for personalized interventions for each age group.

NutrientsVol. 17(18)
Dong-A University (KR)
Korea Disease Control and Prevention Agency
Openalex Percentile: Top 12%
Obesity, Physical Activity, Diet
1.88
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.