Hyejin Yu; Sang-Jin Chung

doi:10.5720/kjcn.2026.00038

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Research Article
Association between nutrient intake and frailty status in Korean older adults: a cross-sectional study using the 9th (2022–2023) Korea National Health and Nutrition Examination Survey: Hyejin Yu^1),2), Sang-Jin Chung^3),†; Korean Journal of Community Nutrition 2026;31(2):153-164.
DOI: https://doi.org/10.5720/kjcn.2026.00038
Published online: April 30, 2026

¹⁾Ph. D. Student, Department of Foods and Nutrition, Kookmin University, Seoul, Korea

²⁾Officer, Korea Health Promotion Institute, Seoul, Korea

³⁾Professor, Department of Foods and Nutrition, Kookmin University, Seoul, Korea

†Corresponding author: Sang-Jin Chung Department of Foods and Nutrition, Kookmin University, 77 Jeongneung-ro, Seongbuk-gu, Seoul 02707, Korea Tel: +82-2-910-4777 Fax: +82-2-910-5249 Email: schung@kookmin.ac.kr

• Received: January 28, 2026 • Revised: March 12, 2026 • Accepted: April 3, 2026

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Abstract
INTRODUCTION
METHODS
RESULTS
DISCUSSION
NOTES
REFERENCES

Abstract

Objectives
This study evaluated the intake status of key macronutrients and micronutrients (calcium, magnesium, iron, and vitamin D) among Korean older adults and investigated their associations with frailty and its individual components.
Methods
Data from 1,246 participants (aged ≥ 65 years) in the 9th Korea National Health and Nutrition Examination Survey (2022–2023) were analyzed. Participants were classified into Robust, Pre-frail, and Frail groups based on a modified version of the Fried frailty phenotype (unintentional weight loss, exhaustion/fatigue, muscle weakness, slow gait speed, and low physical activity). Nutrient intake levels were categorized into tertiles. Multivariable logistic regression was used to estimate odds ratios (ORs) for frailty. Model 1 was adjusted for age, sex, and total energy intake. Model 2 included additional adjustments for socioeconomic factors (household composition, household income) and function-related factors (aerobic physical activity, chewing difficulty, and disease status).
Results
Total energy intake differed significantly across frailty groups in both Model 1 (P = 0.011) and Model 2 (P = 0.043). In the fully adjusted model, participants in the highest tertile of iron intake (T3) had 35% lower odds of frailty compared to those in the lowest tertile (T1) (OR = 0.65; 95% confidence interval [CI], 0.44–0.96). Iron intake maintained the strongest independent association with reduced odds of muscle weakness (T3 vs. T1: OR = 0.45; 95% CI, 0.28–0.71). Furthermore, higher protein intake per kilogram of body weight (T3) was significantly associated with lower odds of slow gait speed (OR = 0.53; 95% CI, 0.33–0.87) in the minimally adjusted model. Vitamin D, calcium, and magnesium were not significantly associated with overall frailty after full adjustment.
Conclusion
Insufficient intake of protein and iron is associated with increased odds of frailty and its functional components in Korean older adults. These findings underscore the critical need for evidence-based nutritional interventions and policy development to prevent and manage frailty at the population level.
Keywords: frailty; elderly; Korea; nutrient status; protein

INTRODUCTION

Globally, many countries—including Korea—are experiencing rapid demographic shifts driven by low birth rates and population aging. In 2025, Korea attained super-aged society status, with individuals aged 65 and older comprising 20.3% of the total population; this proportion is projected to reach 29.9% by 2035 and 40.1% by 2050 [1]. Japan reached this milestone in 2005 [2], and United Nations (UN) projections indicate that the global proportion of older adults will surpass 20% by 2070 [3]. These demographic shifts underscore an urgent need for comprehensive, multifaceted strategies to address the health and well-being of older adults at both national and international levels.

Frailty is characterized by heightened vulnerability to external stressors resulting from diminished physiological reserves with advancing age; it is a pivotal determinant of adverse health outcomes and increased morbidity [4, 5]. Importantly, frailty differs from inevitable physiological aging in that it is potentially reversible and preventable. Evidence indicates that frailty can be mitigated through modifiable lifestyle factors, such as improved nutritional intake, regular physical activity, and smoking cessation [5-7]. Nutritional management, in particular, is central to maintaining physical function and is essential for both the prevention and management of frailty.

According to the 2020 Dietary Reference Intakes for Koreans [8], a substantial proportion of individuals aged 75 and older consume protein below the estimated average requirement: 40.5% of males and 59.9% of females. Insufficient intake of key micronutrients, particularly calcium, is also more prevalent in this age group compared to other age cohorts [8]. Such nutritional deficiencies are mechanistically linked to frailty. Community-based research [9] has demonstrated that insufficient intakes of protein and vitamin D are associated with significantly increased risks of frailty, with odds ratios (ORs) of 2.4 and 1.6, respectively. Moreover, a systematic review [10] indicates that frailty risk is exacerbated by the combined effects of multiple micronutrient deficiencies. Calcium, magnesium, and iron are essential for neuromuscular signaling, skeletal integrity, and oxygen transport; inadequate intake can exacerbate muscle weakness and exhaustion, both clinical hallmarks of frailty [10]. A meta-analysis of over 30,000 participants further identified low serum vitamin D levels as an independent biomarker of frailty risk [11]. Collectively, these findings highlight the necessity of integrated nutritional management—addressing both the quantity and quality of protein intake and ensuring micronutrient balance—for effective frailty prevention.

Despite these insights, research specifically investigating the relationship between nutrient intake and frailty among Korean older adults remains limited. Building upon prior evidence [8-11], the present study aims to comprehensively assess the intake status of macronutrients and specific micronutrients (calcium, magnesium, iron, and vitamin D) in this population, utilizing data from the 9th Korea National Health and Nutrition Examination Survey (KNHANES IX, 2022–2023). Furthermore, it seeks to elucidate the associations between the intake levels of these nutrients and individual frailty components.

METHODS

Ethics statement

This study used data from the KNHANES Ⅸ (2022–2023). In KNHANES, written informed consent was obtained from all participants and/or their legal guardians. The KNHANES protocol was approved by the Research Ethics Review Committee of the Korea Disease Control and Prevention Agency (IRB Nos. 2018-01-03-4C-A and 2022-11-16-R-A). The present study was a secondary analysis of publicly available, de-identified KNHANES data; therefore, no additional ethical approval was sought, and additional informed consent was not required.

1. Study design

This investigation employed a cross-sectional design utilizing government-approved, nationally representative data. The study is reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (https://www.strobe-statement.org/).

2. Study population

Data were sourced from the KNHANES IX (2022–2023). Of the initial 3,502 participants aged ≥ 65 years, exclusions were made for: (1) diagnosed chronic kidney disease (n = 479) due to its impact on nutrient metabolism; (2) missing data for any key variables, including frailty phenotype components, socioeconomic factors, function-related factors, or nutrient intake (n = 1,766), using a complete-case analysis to uphold data integrity; and (3) implausible energy intakes (≤ 500 or > 5,000 kcal/day; n = 11), which may bias nutritional analysis. After these exclusions, 1,246 participants remained for the final analysis.

3. Variables and measurements

1) Frailty assessment

Frailty was evaluated using the five criteria established by Fried et al. [12], adapted to accommodate the available variables in the KNHANES and following validated protocols from previous studies [13-16] to ensure methodological consistency. The five components assessed were: unintentional weight loss, exhaustion/fatigue, muscle weakness, slow gait speed, and low physical activity. Muscle weakness was defined according to the Asian Working Group for Sarcopenia (AWGS) 2019 guidelines [17], thereby enhancing physiological relevance for the Korean older adult population. Component definitions were as follows:

A. Unintentional weight loss: self-reported loss of ≥ 3 kg or more within the past year [13-15].

B. Exhaustion/fatigue: self-reported experience of feeling “very much” stress in daily life [13-15].

C. Muscle weakness: handgrip strength < 28 kg for males or < 18 kg for females, as defined by the AWGS 2019 guidelines [17].

D. Slow gait speed: assessed using the EuroQol-5 Dimension mobility dimension, where participants reported: “having some problems in walking about” or being “confined to bed” [13-15].

E. Low physical activity: walking < 120 minutes per week [15].

Based on these criteria, participants were classified as frail (≥ 3 criteria), pre-frail (1–2 criteria), or robust (0 criteria). For analyses examining the association between nutrient intake tertiles and frailty risk, the pre-frail and frail groups were combined into a non-robust category (≥ 1 criterion).

2) General characteristics

General characteristics were derived from the KNHANES health questionnaire and categorized as socioeconomic factors (household composition, household income) and function-related factors (aerobic physical activity, chewing difficulty, and disease status).

Household composition was classified as single-person or multi-person. Household income (quartiles), aerobic physical activity (active/inactive), and chewing difficulty (comfortable/uncomfortable) followed the original KNHANES definitions. Disease status was categorized as “absent” or “present,” with the latter defined as having at least one of the following: hypertension, diabetes, dyslipidemia, or obesity (BMI ≥ 25 kg/m² according to Korean criteria). Obesity was included due to its strong association with chronic metabolic disease. Grouping these factors enabled a comprehensive assessment of participants’ overall health status.

3) Nutrient intake

Dietary intake was assessed using 24-hour recall data, with a focus on nutrients frequently insufficient in older adults—protein, vitamin D, calcium, magnesium, and iron. For macronutrients, the percentage of total energy intake from carbohydrate, protein, and fat (E%) was calculated and compared with the acceptable macronutrient distribution ranges (AMDR) to assess adequacy. To characterize intake distribution, daily nutrient amounts were categorized into tertiles: lowest (T1), middle (T2), and highest (T3).

4. Statistical analysis

All statistical analyses were conducted using SAS software (version 9.4; SAS Institute Inc.), with statistical significance set at P < 0.05. The complex sampling design of KNHANES was addressed by applying integrated weights, strata, and clusters in accordance with the KNHANES multi-year data integration guidelines. For the combined 2022–2023 dataset, integrated weights were calculated. Specific sampling weights were assigned depending on the analysis: household and health interview/examination weights (wt_hs/itvex) and nutrition survey weights (wt_ntr) were used for analyses of general characteristics and nutrient intake, while integrated health and nutrition survey weights (wt_tot) were used for analyses involving associations with frailty components.

To compare characteristics across frailty groups, continuous variables were reported as means ± standard errors (SE) and assessed using complex samples linear regression. Categorical variables were presented as frequencies and percentages and compared using the Rao–Scott chi-square test. Row percentages were used to indicate the prevalence of each frailty status within subgroups.

Nutrient intakes across frailty groups were compared using two adjusted models. Model 1 was adjusted for age, sex, and total energy intake; Model 2 included further adjustments for socioeconomic factors (household composition, household income) and function-related factors (aerobic physical activity, chewing difficulty, disease status). Total energy intake was excluded from the covariates when analyzing energy intake or macronutrient energy contribution ratios (E%) to prevent over-adjustment, as it is inherently accounted for in these variables. Bonferroni correction was applied for post hoc comparisons.

Associations between nutrient intake tertiles and frailty risk, as well as its individual components, were evaluated using complex samples multiple logistic regression to estimate ORs and 95% confidence intervals (CIs). The lowest tertile (T1) served as the reference group for comparisons. While all nutritional variables—including the AMDR for macronutrients—were initially screened, analyses of individual frailty components focused on nutrients (such as protein, vitamin D, and iron, etc.) with established biological and statistical relevance for a more targeted investigation.

RESULTS

1. General characteristics

The distribution of participant characteristics by frailty status is detailed in Table 1. Among the 1,246 participants, 518 (41.6%) were classified as robust, 655 (52.6%) as pre-frail, and 73 (5.8%) as frail. The mean age was 72.3 years, with age increasing significantly across frailty groups (P < 0.0001). The prevalence of frailty was higher in those aged ≥ 75 years (9.4%) than in those aged 65–74 years (2.7%) (P < 0.0001). Frailty status differed significantly by sex (P < 0.001): males were more likely to be robust (50.4%), while females were more likely to be pre-frail (54.7%) or frail (6.5%). Notably, the prevalence of frailty in females (6.5%) was nearly double that observed in males (3.6%).

Regarding household composition, single-person households represented 31.5% of the robust, 61.3% of the pre-frail, and 7.2% of the frail groups (P < 0.0001). The proportion of frail participants was also significantly higher among those with lower household income (P < 0.0001).

Participants reporting chewing difficulty had a higher prevalence of frailty (9.1%) compared to those without chewing difficulty (3.4%) (P < 0.0001). Within the frail group, the proportions of individuals with aerobic physical inactivity and with at least one chronic disease were significantly higher than among physically active or disease-free participants (P < 0.05).

2. Nutrient intake

Table 2 summarizes daily nutrient intakes according to frailty status. In Model 1 (adjusted for age and sex), mean total daily energy intake was highest in the robust group (1,691.57 kcal), followed by the pre-frail (1,668.46 kcal) and frail (1,489.75 kcal) groups, with a significant difference among groups (P = 0.011). This trend persisted in Model 2, which additionally adjusted for socioeconomic (household composition, household income) and function-related factors (aerobic physical activity, chewing difficulty, disease status), remaining statistically significant (P = 0.043). The proportion of energy derived from carbohydrates (E%) was highest in the frail group (68.14%; P = 0.035 in Model 1), although this difference was not significant after full adjustment in Model 2 (P = 0.133). Notably, iron intake was lowest in the frail group (7.75 mg) compared to the pre-frail (9.04 mg) and robust (9.10 mg) groups, a difference that remained significant in both Model 1 (P < 0.001) and Model 2 (P = 0.001).

3. Nutrient intake status and frailty risk

Table 3 displays the associations between nutrient intake tertiles and the odds of frailty. In Model 1 (adjusted for age, sex, and energy intake), participants in the highest tertile (T3) for protein intake per kilogram of body weight, vitamin D intake, and iron intake exhibited significantly lower odds of frailty compared to those in the lowest tertile (T1). However, after further adjustment for socioeconomic and function-related factors in Model 2, only the association with iron intake remained statistically significant. Specifically, participants in the highest iron intake tertile (≥ 9.8 mg/day) had 35% lower odds of frailty compared to those in the lowest tertile (< 6.3 mg/day) (OR = 0.65; 95% CI, 0.44–0.96; P = 0.031).

4. Nutrient intake and frailty-related criteria

Table 4 presents the ORs for individual frailty components according to nutrient intake tertiles. In Model 1, participants in the highest protein intake group (≥ 1.1 g/kg/day) had significantly lower odds of muscle weakness (OR = 0.58; 95% CI, 0.35–0.96; P = 0.036) and slow gait speed (OR = 0.53; 95% CI, 0.33–0.87; P = 0.011) compared to those in the lowest intake group. Additionally, higher total energy and vitamin D intakes were associated with reduced odds of slow gait speed, whereas higher calcium intake (T3) was linked to lower odds of muscle weakness. However, these associations were no longer significant in Model 2, which included additional adjustments for socioeconomic and function-related factors.

In contrast, iron intake maintained a consistent, independent association with muscle weakness. The highest iron intake tertile (T3) was associated with a 60% lower odds of muscle weakness in Model 1 (OR = 0.40; 95% CI, 0.25–0.64; P < 0.001) and a 55% lower odds in Model 2 (OR = 0.45; 95% CI, 0.28–0.71; P = 0.001). Although higher iron intake was also associated with a 44% reduction in the odds of slow gait speed in Model 1 (OR = 0.56; 95% CI, 0.36–0.86; P = 0.009), this association did not persist after full adjustment in Model 2.

DISCUSSION

This study examined the associations between macronutrient and key micronutrient (calcium, magnesium, iron, and vitamin D) intakes and frailty components among Korean older adults, utilizing nationally representative data from KNHANES IX (2022–2023).

A higher prevalence of frailty was observed among participants aged 75 years and older compared to those aged 65–74 years (P < 0.0001), consistent with global evidence that frailty risk increases with advancing age [18, 19]. This pattern likely reflects age-related declines in physiological reserves and heightened vulnerability to stressors characteristic of the aging process in the Korean population. The prevalence of frailty was also significantly higher in females (6.5%) than in males (3.6%) (P < 0.001), with the proportion of females increasing across frailty categories. These results corroborate previous evidence that, despite longer life expectancy, females are more susceptible to conditions such as sarcopenia and osteoporosis, which elevate frailty risk [20-23]. Additionally, as frailty status progressed, participants were more likely to be in single-person households, have lower income, be physically inactive, and experience chewing difficulties. These findings underscore that frailty results from a complex interplay of biological aging, socioeconomic factors, and health behaviors [18, 24, 25]. In particular, reduced masticatory efficiency limits dietary diversity [26, 27] and adversely affects nutrient intake.

Progression from robust to pre-frail and frail status was associated with significant reductions in total energy and micronutrient intake, especially iron. These lower intakes were associated with increased odds of frailty. Notably, participants in the highest protein intake tertile (≥ 1.1 g/kg/day) had 36% lower odds of frailty than those in the lowest tertile (< 0.8 g/kg/day) in Model 1. This aligns with the recommended protein intake for older adults (1.0–1.2 g/kg/day) [28, 29], highlighting the importance of adequate protein consumption. Conversely, the lowest tertile (< 0.8 g/kg/day) indicates that many female Korean older adults do not meet these recommendations, consistent with previous studies [8, 30, 31]. Furthermore, as frailty progressed, carbohydrate intake exceeded the recommended range (50%–65% of total energy intake) [32], with the frail group averaging above the 65% upper limit in both models (68.14% and 66.70%, respectively). Frailty prevalence was highest among those in the highest carbohydrate intake tertile, suggesting that frailty progression is linked to a macronutrient imbalance—an overreliance on carbohydrates relative to protein and fat. Such quantitative and qualitative dietary imbalances may promote involuntary weight loss and functional decline, creating a cycle that accelerates the progression of frailty [7, 33, 34]. Although protein intake is a recognized factor in frailty [35, 36], its independent association disappeared after full adjustment (Model 2), indicating substantial confounding by socioeconomic and functional variables. Thus, interventions should address both energy quantity and nutrient quality, with a focus on adequate protein intake to prevent frailty.

Among micronutrients, only iron intake remained independently associated with frailty after adjusting for all confounders. Although associations with protein and vitamin D were no longer significant in the fully adjusted model, participants in the highest iron intake tertile (T3) had 35% lower odds of frailty compared to those in the lowest tertile (T1). This enduring association suggests that iron deficiency may serve as an independent risk factor, not merely a consequence of reduced dietary or protein intake. Our findings also confirmed that lower iron intake was significantly associated with deficits in muscle strength and gait speed. These results are consistent with the Concord Health and Aging in Men Project, which found that higher iron intake reduced frailty risk by 48% even after controlling for dietary quality and protein intake [37]. Iron plays a distinct physiological role relative to protein, serving as a cofactor for mitochondrial oxidative phosphorylation and facilitating oxygen transport via hemoglobin and myoglobin [13, 37]. Consequently, iron deficiency can impair muscle bioenergetics and oxygen delivery, leading to fatigue and reduced gait speed before clinical anemia manifests [38, 39]. Thus, maintaining adequate iron status is essential for optimal physical function [40, 41] and serves as a key regulator that complements protein’s structural role in frailty prevention [37].

In the age- and sex-adjusted model, higher intakes of energy, protein, and vitamin D were associated with reduced risk of functional vulnerability, such as impaired gait and muscle weakness, consistent with previous studies [42-44]. However, these associations did not persist after full adjustment, suggesting the importance of multifaceted influences and nutrient interactions in maintaining physical function among older adults.

In summary, frailty prevention in older adults requires comprehensive nutritional strategies. While macronutrients like protein build the structural foundation for muscle, our results underscore the unique, independent role of iron in overall frailty and in functional domains such as muscle strength and gait speed. Although not all components of frailty were associated with nutrient intake, the sustained significance of iron underscores its central role in maintaining physical performance.

These findings suggest that nutritional assessment and interventions in older adults should prioritize both qualitative and quantitative factors, specifically monitoring iron status as an independent target alongside total nutrient intake. Further longitudinal research is warranted to determine the impact of combined nutritional interventions on delaying frailty progression.

Limitations

Several limitations of this study should be acknowledged. First, the relatively small number of participants in the frail group (n = 73) may have reduced statistical power to detect more subtle associations and limited the generalizability of the results. Second, the cross-sectional study design precludes establishing causality, and the potential for reverse causality—where physical decline influences nutrient intake—cannot be excluded. Thus, longitudinal studies are warranted to clarify the observed temporal relationships. Third, dietary intake was assessed using a self-reported 24-hour recall method, introducing the risk of recall bias and potential discrepancies between reported and actual intake.

Despite these limitations, this study offers important contributions by providing a detailed analysis of frailty, subdivided into its individual components, and highlighting the critical role of nutrition in key physical function indicators—specifically, muscle strength (grip strength) and gait speed (walking speed). Drawing on integrated intervention frameworks from the United States [45] and Japan [46], and standardized nutritional screening policies in the United Kingdom [47] and Australia [48], there is a clear need for South Korea to establish a comprehensive intervention strategy. Such a strategy should integrate screening, service linkage, and functional indicator-based evaluation. The present findings provide foundational data to inform and guide public health policies targeting older adults in Korea.

Conclusion

Preventing or delaying frailty in older adults necessitates a multifaceted approach that extends beyond caloric supplementation alone. Comprehensive nutritional interventions and supportive policy measures should prioritize enhancing the quality of protein intake—to provide the structural basis for maintaining muscle mass—and optimizing iron status, which is a critical functional regulator of physical performance. Implementing such integrated strategies is essential for effectively preserving physical function and reducing the burden of frailty at the population level.

NOTES

CONFLICT OF INTEREST

There are no financial or other issues that might lead to conflict of interest.

FUNDING

None.

DATA AVAILABILITY

The data supporting the findings of this study are publicly available from the official KNHANES website (https://knhanes.kdca.go.kr/).

Table 1.

General characteristics of the study population

Variables	Total (n = 1,246)	Robust (n = 518)	Pre-frail (n = 655)	Frail (n = 73)	P-value¹⁾
Age (year)	72.3 ± 0.2	71.3 ± 0.3	72.9 ± 0.2	75.5 ± 0.7	< 0.0001
Age group (year)
65–74	789	375 (49.3)	391 (48.1)	23 (2.7)	< 0.0001
≥ 75	457	143 (35.2)	264 (55.3)	50 (9.4)
Sex
Male	571	276 (50.4)	272 (46.1)	23 (3.6)	< 0.001
Female	675	242 (38.7)	383 (54.7)	50 (6.5)
Household composition
Single-person households	273	82 (31.5)	169 (61.3)	22 (7.2)	< 0.0001
Multi-person households	973	436 (46.7)	486 (48.4)	51 (4.9)
Household income (quartile)
Low	541	172 (33.7)	326 (59.0)	43 (7.3)	< 0.0001
Middle low	388	176 (46.8)	195 (49.3)	17 (3.9)
Middle high	196	99 (51.4)	88 (44.2)	9 (4.4)
High	121	71 (58.0)	46 (37.7)	4 (4.3)
Aerobic physical activity²⁾
Inactive	835	289 (36.5)	481 (56.4)	65 (7.1)	< 0.0001
Active	411	229 (58.1)	174 (40.2)	8 (1.6)
Chewing difficulty
Not uncomfortable	843	398 (50.2)	413 (46.4)	32 (3.4)	< 0.0001
Discomfort	403	120 (30.6)	242 (60.3)	41 (9.1)
Disease status³⁾
Absent	261	134 (51.1)	112 (42.9)	15 (6.0)	0.033
Present	985	384 (42.1)	543 (52.9)	58 (5.0)

Mean ± SE, n, or n (%).

¹⁾P-values indicate overall differences across robust, pre-frail, and frail groups.

²⁾Aerobic physical activity was classified as “Active” (≥ 150 minutes of moderate-intensity activity, ≥ 75 minutes of vigorous-intensity activity, or an equivalent combination per week, where 1 minute of vigorous activity equals 2 minutes of moderate activity), and “Inactive” (not meeting these criteria).

³⁾Disease status was classified as “present” for participants diagnosed with at least one of the following: hypertension, diabetes, dyslipidemia, or those identified with obesity (body mass index ≥ 25 kg/m²).

Table 2.

Daily nutrient intakes by frailty group among older adults

Variables	Model 1¹⁾				Model 2¹⁾
Variables	Robust (n = 518)	Pre-frail (n = 655)	Frail (n = 73)	P-value²⁾	Robust (n = 518)	Pre-frail (n = 655)	Frail (n = 73)	P-value²⁾
Total energy intake (kcal/day)³⁾	1,691.57 ± 27.67^a	1,668.46 ± 28.40^a	1,489.75 ± 61.64^b	0.011	1,731.37 ± 39.16^a	1,738.84 ± 42.21^a	1,570.54 ± 66.40^b	0.043
Carbohydrate (E%)³⁾	64.88 ± 0.73^a	65.76 ± 0.54^ab	68.14 ± 1.12^b	0.035	64.26 ± 0.80^a	64.52 ± 0.74^ab	66.70 ± 1.14^b	0.133
Protein (E%)³⁾	14.72 ± 0.23^a	14.44 ± 0.18^a	13.96 ± 0.44^a	0.236	14.74 ± 0.25^a	14.75 ± 0.26^a	14.42 ± 0.44^a	0.756
Fat (E%)³⁾	19.01 ± 0.53^a	17.95 ± 0.42^ab	16.68 ± 0.87^b	0.040	19.36 ± 0.60^a	18.71 ± 0.55^ab	17.57 ± 0.85^b	0.149
Protein (g/kg/day)	0.99 ± 0.02^a	0.96 ± 0.01^a	0.97 ± 0.04^a	0.437	1.01 ± 0.02^a	1.01 ± 0.02^a	1.02 ± 0.04^a	0.976
Vitamin D (µg/day)	2.90 ± 0.22^a	2.69 ± 0.27^a	2.54 ± 0.37^a	0.650	3.38 ± 0.25^a	3.37 ± 0.37^a	3.21 ± 0.40^a	0.923
Calcium (mg/day)	515.27 ± 13.73^a	496.68 ± 13.01^a	471.96 ± 26.36^a	0.273	527.34 ± 17.81^a	527.64 ± 23.00^a	507.93 ± 28.95^a	0.750
Magnesium (mg/day)	324.17 ± 5.29^a	311.74 ± 4.92^a	308.41 ± 9.85^a	0.143	321.67 ± 6.48^a	314.24 ± 7.37^a	314.32 ± 10.65^a	0.545
Iron (mg/day)	9.10 ± 0.23^a	9.04 ± 0.25^a	7.75 ± 0.31^b	< 0.001	9.39 ± 0.30^a	9.57 ± 0.35^a	8.30 ± 0.36^b	0.001

Mean ± SE.

¹⁾Model 1: Adjusted for age, sex, and total energy intake. Model 2: Model 1 plus adjustments for socioeconomic factors (household composition, household income) and function-related factors (aerobic physical activity, chewing difficulty, disease status).

²⁾P-values indicate overall differences across robust, pre-frail, and frail groups.

³⁾Total energy intake was excluded from the adjustment variables when analyzing energy intake or macronutrient energy proportions (E%) to prevent multicollinearity.

^abDifferent superscripts indicate significantly different means (P < 0.05, Bonferroni).

Table 3.

Associations between nutrient intake tertiles and the odds of frailty among older adults

Variables¹⁾	Category	Model 1²⁾	Model 2²⁾
Total energy intake (kcal/day)³⁾	T1 (< 1,306.6)	1.00 (ref.)	1.00 (ref.)
	T2 (1,306.6–<1,825.2)	0.83 (0.59–1.15)	0.86 (0.61–1.22)
	T3 (≥ 1,825.2)	0.78 (0.56–1.09)	0.92 (0.65–1.30)
Carbohydrate (E%)³⁾	T1 (< 61.2)	1.00 (ref.)	1.00 (ref.)
	T2 (61.2–<70.6)	1.12 (0.82–1.53)	1.09 (0.78–1.52)
	T3 (≥ 70.6)	1.35 (0.96–1.91)	1.13 (0.81–1.59)
Protein (E%)³⁾	T1 (< 12.8)	1.00 (ref.)	1.00 (ref.)
	T2 (12.8–<15.6)	0.87 (0.62–1.21)	1.02 (0.73–1.44)
	T3 (≥ 15.6)	0.83 (0.59–1.18)	1.00 (0.70–1.45)
Fat (E%)³⁾	T1 (< 14.2)	1.00 (ref.)	1.00 (ref.)
	T2 (14.2–<20.8)	0.76 (0.56–1.04)	0.92 (0.67–1.26)
	T3 (≥ 20.8)	0.72 (0.51–1.03)	0.84 (0.60–1.19)
Protein (g/kg/day)	T1 (< 0.8)	1.00 (ref.)	1.00 (ref.)
	T2 (0.8–<1.1)	0.70 (0.49–0.99)^*	0.79 (0.57–1.11)
	T3 ( ≥ 1.1)	0.64 (0.42–0.99)^*	0.80 (0.52–1.23)
Vitamin D (µg/day)	T1 (< 0.7)	1.00 (ref.)	1.00 (ref.)
	T2 (0.7–<2.7)	0.80 (0.55–1.17)	0.88 (0.61–1.26)
	T3 (≥ 2.7)	0.68 (0.47–0.97)^*	0.78 (0.55–1.11)
Calcium (mg/day)	T1 (< 348.7)	1.00 (ref.)	1.00 (ref.)
	T2 (348.7–<570.2)	0.99 (0.65–1.49)	1.06 (0.72–1.57)
	T3 (≥ 570.2)	0.87 (0.58–1.32)	1.08 (0.72–1.60)
Magnesium (mg/day)	T1 (< 248.1)	1.00 (ref.)	1.00 (ref.)
	T2 (248.1–<355.4)	0.80 (0.54–1.17)	0.87 (0.59–1.26)
	T3 (≥ 355.4)	0.78 (0.51–1.18)	0.92 (0.59–1.43)
Iron (mg/day)	T1 (< 6.3)	1.00 (ref.)	1.00 (ref.)
	T2 (6.3–<9.8)	0.83 (0.57–1.20)	0.88 (0.61–1.28)
	T3 (≥ 9.8)	0.53 (0.36–0.79)^**	0.65 (0.44–0.96)^*

Odds ratio (95% confidence interval).

The lowest tertile (T1) served as the reference group.

The non-robust group comprises the combined pre-frail and frail groups; the robust group is used as the reference category.

¹⁾Nutrients were categorized into tertiles (T1–T3) based on their distribution within the study population.

²⁾Model 1: Adjusted for age, sex, and total energy intake. Model 2: Model 1 plus adjustments for socioeconomic factors (household composition, household income) and function-related factors (aerobic physical activity, chewing difficulty, disease status).

³⁾Total energy intake was excluded from the adjustment variables when analyzing energy intake or macronutrient energy proportions (E%) to prevent multicollinearity.

^*P < 0.05,

^**P < 0.01.

Table 4.

Associations between nutrient intake tertiles and frailty-related criteria among older adults

Variables	Model 1¹⁾					Model 2¹⁾
Variables	Weight loss (220, 16.7%)	Muscle weakness (273, 18.3%)	Low physical activity (121, 9.5%)	Slow gait speed (454, 35.3%)	Exhaustion/fatigue (30, 2.3%)	Weight loss (220, 16.7%)	Muscle weakness (273, 18.3%)	Low physical activity (121, 9.5%)	Slow gait speed (454, 35.3%)	Exhaustion/fatigue (30, 2.3%)
Total energy intake (kcal/day)²⁾
T1 (< 1,306.6)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)
T2 (1,306.6–<1,825.2)	0.89 (0.61–1.30)	0.86 (0.59–1.26)	1.04 (0.57–1.90)	0.74 (0.53–1.02)	0.59 (0.22–1.59)	0.89 (0.61–1.29)	0.88 (0.60–1.31)	1.02 (0.56–1.86)	0.75 (0.54–1.05)	0.65 (0.24–1.76)
T3 ( ≥ 1,825.2)	0.89 (0.59–1.33)	0.69 (0.45–1.05)	1.06 (0.58–1.96)	0.61 (0.42–0.88)^**	1.36 (0.51–3.61)	0.88 (0.59–1.33)	0.78 (0.51–1.20)	1.10 (0.60–2.01)	0.71 (0.48–1.04)	1.56 (0.56–4.35)
Protein (g/kg/day)
T1 (< 0.8)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)
T2 (0.8–<1.1)	0.78 (0.52–1.17)	0.98 (0.65–1.50)	1.37 (0.82–2.29)	0.56 (0.40–0.78)^***	0.91 (0.35–2.40)	0.82 (0.54–1.23)	1.11 (0.74–1.65)	1.46 (0.89–2.38)	0.62 (0.44–0.86)	0.95 (0.37–2.42)
T3 (≥ 1.1)	1.27 (0.76–2.14)	0.58 (0.35–0.96)^*	0.93 (0.40–2.15)	0.53 (0.33–0.87)^*	0.82 (0.19–3.46)	1.37 (0.80–2.35)	0.70 (0.42–1.17)	1.01 (0.45–2.26)	0.68 (0.41–1.10)	0.89 (0.24–3.38)
Vitamin D (µg/day)
T1 (< 0.7)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)
T2 (0.7–<2.7)	1.05 (0.72–1.54)	0.79 (0.53–1.18)	0.68 (0.39–1.18)	0.81 (0.57–1.15)	0.84 (0.32–2.17)	1.05 (0.70–1.56)	0.87 (0.58–1.28)	0.69 (0.40–1.18)	0.93 (0.66–1.31)	0.84 (0.32–2.19)
T3 (≥ 2.7)	0.99 (0.67–1.48)	0.71 (0.45–1.11)	0.92 (0.53–1.57)	0.62 (0.44–0.88)^**	0.84 (0.30–2.37)	0.97 (0.65–1.46)	0.80 (0.51–1.25)	0.95 (0.56–1.62)	0.75 (0.52–1.07)	0.89 (0.33–2.35)
Calcium (mg/day)
T1 (< 348.7)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)
T2 (348.7–<570.2)	0.67 (0.45–1.01)	0.99 (0.68–1.44)	1.59 (0.86–2.93)	0.76 (0.53–1.08)	1.43 (0.51–3.97)	0.68 (0.45–1.01)	1.05 (0.73–1.51)	1.54 (0.84–2.82)	0.81 (0.58–1.13)	1.46 (0.52–4.08)
T3 (≥ 570.2)	1.00 (0.62–1.61)	0.55 (0.35–0.87)^*	1.32 (0.65–2.70)	0.67 (0.44–1.00)	1.73 (0.56–5.37)	1.04 (0.63–1.70)	0.65 (0.41–1.01)	1.37 (0.70–2.70)	0.83 (0.56–1.24)	1.98 (0.66–5.89)
Magnesium (mg/day)
T1 (< 248.1)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)
T2 (248.1–<355.4)	0.76 (0.50–1.17)	0.77 (0.54–1.09)	1.26 (0.69–2.29)	0.87 (0.61–1.23)	0.98 (0.31–3.10)	0.78 (0.51–1.18)	0.83 (0.58–1.20)	1.30 (0.70–2.41)	0.95 (0.67–1.34)	1.01 (0.33–3.09)
T3 (≥ 355.4)	0.79 (0.45–1.40)	0.65 (0.40–1.07)	1.30 (0.61–2.81)	0.71 (0.47–1.09)	1.82 (0.44–7.56)	0.83 (0.47–1.49)	0.73 (0.45–1.20)	1.38 (0.63–3.05)	0.86 (0.56–1.33)	2.02 (0.52–7.93)
Iron (mg/day)
T1 (< 6.3)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)
T2 (6.3–<9.8)	0.66 (0.43–1.01)	0.92 (0.60–1.05)	0.82 (0.49–1.37)	0.77 (0.53–1.14)	0.58 (0.18–1.87)	0.65 (0.43–1.00)	0.97 (0.63–1.50)	0.85 (0.50–1.45)	0.82 (0.56–1.21)	0.58 (0.18–1.86)
T3 (≥ 9.8)	0.61 (0.36–1.02)	0.40 (0.25–0.64)^***	0.73 (0.37–1.43)	0.56 (0.36–0.86)^**	1.41 (0.43–4.61)	0.62 (0.37–1.06)	0.45 (0.28–0.71)^***	0.81 (0.42–1.56)	0.72 (0.45–1.13)	1.55 (0.48–5.01)

Odds ratio (95% confidence interval).

The lowest tertile (T1) served as the reference group. The non-robust group comprises the combined pre-frail and frail groups; the robust group is used as the reference category.

Outcomes were defined as follows: 1) Weight loss: self-reported  3 kg loss in the past year; 2) muscle weakness: handgrip strength < 28 kg in males and < 18 kg in females; 3) low physical activity: < 120 minutes/week of walking time; 4) slow gait speed: difficulty walking or bedridden most of the day; 5) exhaustion: self-reported feeling “very much” stress in daily life. The numbers and percentages in parentheses under the column headers indicate the number and percentage of participants (n, %) exhibiting each component.

²⁾Total energy intake was excluded from the adjustment variables when analyzing energy intake or macronutrient energy proportions (E%) to prevent multicollinearity.

^*P < 0.05,

^**P < 0.01,

^***P < 0.001.

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Association between nutrient intake and frailty status in Korean older adults: a cross-sectional study using the 9th (2022–2023) Korea National Health and Nutrition Examination Survey

Korean J Community Nutr. 2026;31(2):153-164. Published online April 30, 2026

DOI: https://doi.org/10.5720/kjcn.2026.00038

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Association between nutrient intake and frailty status in Korean older adults: a cross-sectional study using the 9th (2022–2023) Korea National Health and Nutrition Examination Survey

Variables	Total (n = 1,246)	Robust (n = 518)	Pre-frail (n = 655)	Frail (n = 73)	P-value¹⁾
Age (year)	72.3 ± 0.2	71.3 ± 0.3	72.9 ± 0.2	75.5 ± 0.7	< 0.0001
Age group (year)
65–74	789	375 (49.3)	391 (48.1)	23 (2.7)	< 0.0001
≥ 75	457	143 (35.2)	264 (55.3)	50 (9.4)
Sex
Male	571	276 (50.4)	272 (46.1)	23 (3.6)	< 0.001
Female	675	242 (38.7)	383 (54.7)	50 (6.5)
Household composition
Single-person households	273	82 (31.5)	169 (61.3)	22 (7.2)	< 0.0001
Multi-person households	973	436 (46.7)	486 (48.4)	51 (4.9)
Household income (quartile)
Low	541	172 (33.7)	326 (59.0)	43 (7.3)	< 0.0001
Middle low	388	176 (46.8)	195 (49.3)	17 (3.9)
Middle high	196	99 (51.4)	88 (44.2)	9 (4.4)
High	121	71 (58.0)	46 (37.7)	4 (4.3)
Aerobic physical activity²⁾
Inactive	835	289 (36.5)	481 (56.4)	65 (7.1)	< 0.0001
Active	411	229 (58.1)	174 (40.2)	8 (1.6)
Chewing difficulty
Not uncomfortable	843	398 (50.2)	413 (46.4)	32 (3.4)	< 0.0001
Discomfort	403	120 (30.6)	242 (60.3)	41 (9.1)
Disease status³⁾
Absent	261	134 (51.1)	112 (42.9)	15 (6.0)	0.033
Present	985	384 (42.1)	543 (52.9)	58 (5.0)

Variables	Model 1¹⁾				Model 2¹⁾
Variables	Robust (n = 518)	Pre-frail (n = 655)	Frail (n = 73)	P-value²⁾	Robust (n = 518)	Pre-frail (n = 655)	Frail (n = 73)	P-value²⁾
Total energy intake (kcal/day)³⁾	1,691.57 ± 27.67^a	1,668.46 ± 28.40^a	1,489.75 ± 61.64^b	0.011	1,731.37 ± 39.16^a	1,738.84 ± 42.21^a	1,570.54 ± 66.40^b	0.043
Carbohydrate (E%)³⁾	64.88 ± 0.73^a	65.76 ± 0.54^ab	68.14 ± 1.12^b	0.035	64.26 ± 0.80^a	64.52 ± 0.74^ab	66.70 ± 1.14^b	0.133
Protein (E%)³⁾	14.72 ± 0.23^a	14.44 ± 0.18^a	13.96 ± 0.44^a	0.236	14.74 ± 0.25^a	14.75 ± 0.26^a	14.42 ± 0.44^a	0.756
Fat (E%)³⁾	19.01 ± 0.53^a	17.95 ± 0.42^ab	16.68 ± 0.87^b	0.040	19.36 ± 0.60^a	18.71 ± 0.55^ab	17.57 ± 0.85^b	0.149
Protein (g/kg/day)	0.99 ± 0.02^a	0.96 ± 0.01^a	0.97 ± 0.04^a	0.437	1.01 ± 0.02^a	1.01 ± 0.02^a	1.02 ± 0.04^a	0.976
Vitamin D (µg/day)	2.90 ± 0.22^a	2.69 ± 0.27^a	2.54 ± 0.37^a	0.650	3.38 ± 0.25^a	3.37 ± 0.37^a	3.21 ± 0.40^a	0.923
Calcium (mg/day)	515.27 ± 13.73^a	496.68 ± 13.01^a	471.96 ± 26.36^a	0.273	527.34 ± 17.81^a	527.64 ± 23.00^a	507.93 ± 28.95^a	0.750
Magnesium (mg/day)	324.17 ± 5.29^a	311.74 ± 4.92^a	308.41 ± 9.85^a	0.143	321.67 ± 6.48^a	314.24 ± 7.37^a	314.32 ± 10.65^a	0.545
Iron (mg/day)	9.10 ± 0.23^a	9.04 ± 0.25^a	7.75 ± 0.31^b	< 0.001	9.39 ± 0.30^a	9.57 ± 0.35^a	8.30 ± 0.36^b	0.001

Variables¹⁾	Category	Model 1²⁾	Model 2²⁾
Total energy intake (kcal/day)³⁾	T1 (< 1,306.6)	1.00 (ref.)	1.00 (ref.)
	T2 (1,306.6–<1,825.2)	0.83 (0.59–1.15)	0.86 (0.61–1.22)
	T3 (≥ 1,825.2)	0.78 (0.56–1.09)	0.92 (0.65–1.30)
Carbohydrate (E%)³⁾	T1 (< 61.2)	1.00 (ref.)	1.00 (ref.)
	T2 (61.2–<70.6)	1.12 (0.82–1.53)	1.09 (0.78–1.52)
	T3 (≥ 70.6)	1.35 (0.96–1.91)	1.13 (0.81–1.59)
Protein (E%)³⁾	T1 (< 12.8)	1.00 (ref.)	1.00 (ref.)
	T2 (12.8–<15.6)	0.87 (0.62–1.21)	1.02 (0.73–1.44)
	T3 (≥ 15.6)	0.83 (0.59–1.18)	1.00 (0.70–1.45)
Fat (E%)³⁾	T1 (< 14.2)	1.00 (ref.)	1.00 (ref.)
	T2 (14.2–<20.8)	0.76 (0.56–1.04)	0.92 (0.67–1.26)
	T3 (≥ 20.8)	0.72 (0.51–1.03)	0.84 (0.60–1.19)
Protein (g/kg/day)	T1 (< 0.8)	1.00 (ref.)	1.00 (ref.)
	T2 (0.8–<1.1)	0.70 (0.49–0.99)^*	0.79 (0.57–1.11)
	T3 ( ≥ 1.1)	0.64 (0.42–0.99)^*	0.80 (0.52–1.23)
Vitamin D (µg/day)	T1 (< 0.7)	1.00 (ref.)	1.00 (ref.)
	T2 (0.7–<2.7)	0.80 (0.55–1.17)	0.88 (0.61–1.26)
	T3 (≥ 2.7)	0.68 (0.47–0.97)^*	0.78 (0.55–1.11)
Calcium (mg/day)	T1 (< 348.7)	1.00 (ref.)	1.00 (ref.)
	T2 (348.7–<570.2)	0.99 (0.65–1.49)	1.06 (0.72–1.57)
	T3 (≥ 570.2)	0.87 (0.58–1.32)	1.08 (0.72–1.60)
Magnesium (mg/day)	T1 (< 248.1)	1.00 (ref.)	1.00 (ref.)
	T2 (248.1–<355.4)	0.80 (0.54–1.17)	0.87 (0.59–1.26)
	T3 (≥ 355.4)	0.78 (0.51–1.18)	0.92 (0.59–1.43)
Iron (mg/day)	T1 (< 6.3)	1.00 (ref.)	1.00 (ref.)
	T2 (6.3–<9.8)	0.83 (0.57–1.20)	0.88 (0.61–1.28)
	T3 (≥ 9.8)	0.53 (0.36–0.79)^**	0.65 (0.44–0.96)^*

Variables	Model 1¹⁾					Model 2¹⁾
Variables	Weight loss (220, 16.7%)	Muscle weakness (273, 18.3%)	Low physical activity (121, 9.5%)	Slow gait speed (454, 35.3%)	Exhaustion/fatigue (30, 2.3%)	Weight loss (220, 16.7%)	Muscle weakness (273, 18.3%)	Low physical activity (121, 9.5%)	Slow gait speed (454, 35.3%)	Exhaustion/fatigue (30, 2.3%)
Total energy intake (kcal/day)²⁾
T1 (< 1,306.6)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)
T2 (1,306.6–<1,825.2)	0.89 (0.61–1.30)	0.86 (0.59–1.26)	1.04 (0.57–1.90)	0.74 (0.53–1.02)	0.59 (0.22–1.59)	0.89 (0.61–1.29)	0.88 (0.60–1.31)	1.02 (0.56–1.86)	0.75 (0.54–1.05)	0.65 (0.24–1.76)
T3 ( ≥ 1,825.2)	0.89 (0.59–1.33)	0.69 (0.45–1.05)	1.06 (0.58–1.96)	0.61 (0.42–0.88)^**	1.36 (0.51–3.61)	0.88 (0.59–1.33)	0.78 (0.51–1.20)	1.10 (0.60–2.01)	0.71 (0.48–1.04)	1.56 (0.56–4.35)
Protein (g/kg/day)
T1 (< 0.8)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)
T2 (0.8–<1.1)	0.78 (0.52–1.17)	0.98 (0.65–1.50)	1.37 (0.82–2.29)	0.56 (0.40–0.78)^***	0.91 (0.35–2.40)	0.82 (0.54–1.23)	1.11 (0.74–1.65)	1.46 (0.89–2.38)	0.62 (0.44–0.86)	0.95 (0.37–2.42)
T3 (≥ 1.1)	1.27 (0.76–2.14)	0.58 (0.35–0.96)^*	0.93 (0.40–2.15)	0.53 (0.33–0.87)^*	0.82 (0.19–3.46)	1.37 (0.80–2.35)	0.70 (0.42–1.17)	1.01 (0.45–2.26)	0.68 (0.41–1.10)	0.89 (0.24–3.38)
Vitamin D (µg/day)
T1 (< 0.7)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)
T2 (0.7–<2.7)	1.05 (0.72–1.54)	0.79 (0.53–1.18)	0.68 (0.39–1.18)	0.81 (0.57–1.15)	0.84 (0.32–2.17)	1.05 (0.70–1.56)	0.87 (0.58–1.28)	0.69 (0.40–1.18)	0.93 (0.66–1.31)	0.84 (0.32–2.19)
T3 (≥ 2.7)	0.99 (0.67–1.48)	0.71 (0.45–1.11)	0.92 (0.53–1.57)	0.62 (0.44–0.88)^**	0.84 (0.30–2.37)	0.97 (0.65–1.46)	0.80 (0.51–1.25)	0.95 (0.56–1.62)	0.75 (0.52–1.07)	0.89 (0.33–2.35)
Calcium (mg/day)
T1 (< 348.7)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)
T2 (348.7–<570.2)	0.67 (0.45–1.01)	0.99 (0.68–1.44)	1.59 (0.86–2.93)	0.76 (0.53–1.08)	1.43 (0.51–3.97)	0.68 (0.45–1.01)	1.05 (0.73–1.51)	1.54 (0.84–2.82)	0.81 (0.58–1.13)	1.46 (0.52–4.08)
T3 (≥ 570.2)	1.00 (0.62–1.61)	0.55 (0.35–0.87)^*	1.32 (0.65–2.70)	0.67 (0.44–1.00)	1.73 (0.56–5.37)	1.04 (0.63–1.70)	0.65 (0.41–1.01)	1.37 (0.70–2.70)	0.83 (0.56–1.24)	1.98 (0.66–5.89)
Magnesium (mg/day)
T1 (< 248.1)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)
T2 (248.1–<355.4)	0.76 (0.50–1.17)	0.77 (0.54–1.09)	1.26 (0.69–2.29)	0.87 (0.61–1.23)	0.98 (0.31–3.10)	0.78 (0.51–1.18)	0.83 (0.58–1.20)	1.30 (0.70–2.41)	0.95 (0.67–1.34)	1.01 (0.33–3.09)
T3 (≥ 355.4)	0.79 (0.45–1.40)	0.65 (0.40–1.07)	1.30 (0.61–2.81)	0.71 (0.47–1.09)	1.82 (0.44–7.56)	0.83 (0.47–1.49)	0.73 (0.45–1.20)	1.38 (0.63–3.05)	0.86 (0.56–1.33)	2.02 (0.52–7.93)
Iron (mg/day)
T1 (< 6.3)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)
T2 (6.3–<9.8)	0.66 (0.43–1.01)	0.92 (0.60–1.05)	0.82 (0.49–1.37)	0.77 (0.53–1.14)	0.58 (0.18–1.87)	0.65 (0.43–1.00)	0.97 (0.63–1.50)	0.85 (0.50–1.45)	0.82 (0.56–1.21)	0.58 (0.18–1.86)
T3 (≥ 9.8)	0.61 (0.36–1.02)	0.40 (0.25–0.64)^***	0.73 (0.37–1.43)	0.56 (0.36–0.86)^**	1.41 (0.43–4.61)	0.62 (0.37–1.06)	0.45 (0.28–0.71)^***	0.81 (0.42–1.56)	0.72 (0.45–1.13)	1.55 (0.48–5.01)

Table 1. General characteristics of the study population

Mean ± SE, n, or n (%).

P-values indicate overall differences across robust, pre-frail, and frail groups.

Aerobic physical activity was classified as “Active” (≥ 150 minutes of moderate-intensity activity, ≥ 75 minutes of vigorous-intensity activity, or an equivalent combination per week, where 1 minute of vigorous activity equals 2 minutes of moderate activity), and “Inactive” (not meeting these criteria).

Disease status was classified as “present” for participants diagnosed with at least one of the following: hypertension, diabetes, dyslipidemia, or those identified with obesity (body mass index ≥ 25 kg/m²).

Table 2. Daily nutrient intakes by frailty group among older adults

Mean ± SE.

Model 1: Adjusted for age, sex, and total energy intake. Model 2: Model 1 plus adjustments for socioeconomic factors (household composition, household income) and function-related factors (aerobic physical activity, chewing difficulty, disease status).

P-values indicate overall differences across robust, pre-frail, and frail groups.

Total energy intake was excluded from the adjustment variables when analyzing energy intake or macronutrient energy proportions (E%) to prevent multicollinearity.

Different superscripts indicate significantly different means (P < 0.05, Bonferroni).

Table 3. Associations between nutrient intake tertiles and the odds of frailty among older adults

Odds ratio (95% confidence interval).

The lowest tertile (T1) served as the reference group.

The non-robust group comprises the combined pre-frail and frail groups; the robust group is used as the reference category.

Nutrients were categorized into tertiles (T1–T3) based on their distribution within the study population.

Total energy intake was excluded from the adjustment variables when analyzing energy intake or macronutrient energy proportions (E%) to prevent multicollinearity.

P < 0.05,

P < 0.01.

Table 4. Associations between nutrient intake tertiles and frailty-related criteria among older adults

Odds ratio (95% confidence interval).

The lowest tertile (T1) served as the reference group. The non-robust group comprises the combined pre-frail and frail groups; the robust group is used as the reference category.

Total energy intake was excluded from the adjustment variables when analyzing energy intake or macronutrient energy proportions (E%) to prevent multicollinearity.

P < 0.05,

P < 0.01,

***

P < 0.001.