Ji-Sook Park; Hyeon-Mi Bae; Jung-Eun Yim

doi:10.5720/kjcn.2025.00283

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Research Article
Nutrition Quotient and nutrient intake among older adults in a rural Korean community: a cross-sectional study: Ji-Sook Park^1),*, Hyeon-Mi Bae^2),*, Jung-Eun Yim^1),2),†; Korean Journal of Community Nutrition 2025;30(6):397-409.
DOI: https://doi.org/10.5720/kjcn.2025.00283
Published online: December 31, 2025

¹⁾Department of Food and Nutrition, Changwon National University, Changwon, Korea

²⁾Interdisciplinary Program in Senior Human Ecology, Changwon National University, Changwon, Korea

†Corresponding author: Jung-Eun Yim Department of Food and Nutrition, Changwon National University, 20 Changwondaehak-ro, Uichang-gu, Changwon 51140, Korea Tel: +82-55-213-3517 Fax: +82-55-281-7480 Email: jeyim@changwon.ac.kr

These authors contributed equally to this work.

• Received: September 25, 2025 • Revised: October 28, 2025 • Accepted: November 6, 2025

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://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
Korea is experiencing rapid population aging, with older adults forming a large proportion of rural communities. Aging leads to physiological and functional declines, resulting in lower physical activity, poor diet quality, and higher risk of chronic diseases. Although the Nutrition Quotient for the Elderly (NQ-E) is a validated tool to assess dietary quality, few studies have applied it to rural populations. This study aimed to compare nutrient intake and NQ-E scores by age and sex and examine their associations with lifestyle factors.
Methods
This study investigated the relationship between nutrient intake and NQ-E scores among older adults in rural Korean community, considering age, sex, and lifestyle factors. A cross-sectional study was conducted with 79 community-dwelling older adults (24 male and 55 female; mean age: 76.3 years) residing in Geochang-gun, Gyeongsangnam-do, Korea. Participants were recruited from community centers and health posts between June 2024 and December 2024. Data collection included general characteristics, 24-hour dietary recalls, and NQ-E questionnaires.
Results
Female aged > 75 years had significantly lower intakes of energy, protein, fat, vitamin E, riboflavin, folate, and zinc than their male counterparts (P < 0.05). The mean NQ-E score was 55.01, which was lower than the national average reported for urban older adults (57.6). Participants with higher NQ-E grades had significantly higher intakes of dietary fiber, vitamin A, thiamine, riboflavin, niacin, potassium, and magnesium, and regular physical activity and dietary supplement use were positively associated with higher NQ-E grades (P < 0.01).
Conclusion
These findings suggest that older female in rural communities are particularly vulnerable to inadequate nutrient intake and lower dietary quality, and that the NQ-E is a useful screening tool for identifying nutritional risk in this population. Community-based nutrition interventions promoting physical activity, supplement use, and dietary diversity are warranted to improve dietary quality and support healthy aging.
Keywords: aging; rural population; nutritional status; diet records

INTRODUCTION

Korea is among the fastest-aging societies in the world. By 2025, the proportion of adults aged 65 years and older in Korea is projected to exceed 20%, classifying the nation as a super-aged society [1]. This figure is anticipated to reach 30% by 2036 and 40% by 2050 [2]. This rapid demographic shift is largely attributed to the significant increase in average life expectancy, from 62.2 years in 1970 to 83.5 years in 2020 [3].

Aging is associated with declines in basal metabolism, physiological function, and physical activity levels, which increase the vulnerability to multiple chronic conditions such as sarcopenia, anemia, fractures, cardiovascular diseases, cognitive decline, frailty, diabetes, and depression [4-7]. Consequently, many older adults face complex health challenges that require increased medical care and day-to-day support [8].

Maintaining optimal nutritional status is critical at any age; however, it is particularly important for older adults to reduce the risk of age-related diseases and functional decline. According to the 2017 Global Burden of Disease Study, inadequate dietary intake contributes to nearly 50% of mortality and 66% of disability-adjusted life years worldwide [9]. Similarly, a Korean longitudinal study demonstrated that poor dietary quality was associated with increased all-cause, cardiovascular, and cancer mortality [10]. However, the dietary habits of many older adults remain suboptimal and are often characterized by monotonous eating patterns [11]. In Korea, the prevalence of malnutrition among adults aged 65 years and older increased from 8.5% in 2013 to 22.8% in 2021 [12], and approximately 20% of this population consumes less than the recommended dietary allowance for major nutrients [13, 14].

Nutrient intake among older adults is influenced by physiological, economic, and sociocultural factors. Regional disparities also persist; urban residents generally report better health and dietary quality than those living in rural areas [15]. Data from the Korean National Health and Nutrition Examination Survey further indicates that rural populations often experience unbalanced diets, excessive carbohydrate intake, and insufficient fruit consumption, which may contribute to cardiometabolic disorders [16]. Rural regions in Korea have a disproportionately higher proportion of older adults than that of urban areas, often exceeding 30% of the local population [17]. This demographic imbalance amplifies the challenges of ensuring equitable healthcare, nutrition, and social support in rural communities [18].

The Nutrition Quotient (NQ) is a validated tool that comprehensively evaluates dietary quality and nutritional status across the life cycle [19]. In particular, the Nutrition Quotient for the Elderly (NQ-E) is a 19-item assessment designed for individuals aged 65 years and older, designed to evaluate balance, variety, moderation, and dietary behavior [20]. Nevertheless, most existing research have focused on urban populations or large-scale national surveys, with limited data on rural populations, who often face unique nutritional challenges.

Although several studies have examined the NQ in elderly populations, there is limited evidence exploring its relationship with nutrient intake and health status in rural communities. Older adults in rural communities often face additional barriers to maintaining adequate nutrition, including limited access to diverse foods, lower income levels, and reduced availability of support services [21, 22]. These challenges, together with age-related physiological and social changes, may increase the risk of nutritional inadequacy in this population [23]. However, there is a lack of research involving standardized tools, such as NQ-E, for examining how dietary quality and nutrient intake vary according to age and sex in rural older adults. Understanding these differences is essential to design targeted interventions that address the unique nutritional needs of this population.

Therefore, this study aimed to (1) compare nutrient intake and NQ scores by age and sex among older adults living in a rural Korean community and (2) examine the associations between dietary quality and lifestyle factors, such as physical activity levels and dietary supplement use. These findings provide a foundation for developing community-based nutritional strategies tailored to the needs of older adults living in rural areas.

METHODS

Ethics statement

The written informed consent was obtained from all participants for the survey. The survey procedures and protocols were approved by the Institutional Review Board (IRB No. 7001066-202402-BR-001).

1. Study design

This cross-sectional study analyzed data on nutrient intake and NQ scores among older adults aged ≥ 65 years residing in Geochang-gun, Gyeongsangnam-do, Korea, and was described in accordance with the STROBE guidelines (https://www.strobe-statement.org/).

2. Participants

This study recruited community-dwelling older adults aged 65 years and above residing in Geochang-gun, Gyeongsangnam-do. The participants were recruited through local community centers, public health posts, and senior welfare programs between June 2024 and December 2024. The target sample size was estimated using G*Power 3.1. Based on a one-way analysis of variance with four groups, assuming a medium effect size (f = 0.30), α = 0.05, and power = 0.80, the required sample size was calculated to be approximately 80 participants. A total of 79 older adults consented to participate in the study, including 24 male (30.4%) and 55 female (69.6%).

The eligible participants were community-dwelling older adults. Participants were independently living older adults who could perform daily activities without substantial assistance and were cognitively capable. Participants with hypertension, dyslipidemia, or other chronic conditions were not excluded, provided their conditions were stable and did not interfere with daily living activities. Patients diagnosed with cancer, chronic kidney failure, or liver cirrhosis, as well as individuals reporting implausible daily energy intake (< 500 kcal/day or > 5,000 kcal/day) were excluded from the analysis. All participants were informed about the purpose and procedures of the study, and written informed consent was obtained from the participants prior to enrollment.

3. General characteristics

Information on participants’ general characteristics was collected through a structured questionnaire. Trained researchers assisted participants who experienced difficulty completing the questionnaire to ensure accurate responses. Regular physical activity was defined according to the World Health Organization guidelines [24] for older adults. Participants were classified as physically active if they engaged in at least one type of recommended exercise, including aerobics, muscle-strengthening, balance, or multicomponent activities, performed on a regular basis. Those who did not participate in any of these activities were categorized as physically inactive. Marital status was categorized as married (including those currently married, separated, or widowed) and not married (including never married or divorced). Smoking status was defined as current smoker versus non-smoker, the latter referring to individuals who had abstained from smoking for at least one year.

4. Dietary assessment

Dietary intake was assessed using a single 24-hour dietary recall containing all foods and beverages consumed on the day prior to the survey visit. Participants recorded the types and amounts of foods and beverages consumed during breakfast, lunch, dinner, and snacks, and were asked whether dietary intake on that day reflected their usual dietary patterns. Trained researchers assisted with completing the recall process for participants who experienced difficulty in self-reporting.

During face-to-face interviews, researchers confirmed the names of foods, ingredients, and portion sizes consumed on the previous day using standardized food models, measuring spoons, measuring cups, and paper cups to ensure accuracy. Detailed information on ingredients, cooking methods, condiments and their amounts, as well as snacks, coffee, tea, and other items consumed between meals was verified to complete the 24-hour recall. The collected dietary data were analyzed for total daily energy and nutrient intake using CAN-Pro 6.0 (Computer-Aided Nutritional Analysis Program for Professionals, version 6.0, 2023; Korean Nutrition Society). The nutrient intake ratio (%) was calculated as the nutrient intake divided by the Dietary Reference Intakes for Koreans (KDRI) and multiplied by 100. The recommended nutrient intake (RNI) values were used as reference standards, and in cases where no RNI was available, the adequate intake values were applied.

5. Nutrition Quotient for Elderly

The NQ-E is a validated tool designed to provide a simple yet comprehensive assessment of dietary behavior and nutritional status in older adults. The NQ evaluates the quality and quantity of dietary intake by considering multiple dimensions, including adequacy of nutrient intake, balance between diet and physical activity, food safety and hygiene, and appropriate food choices and eating behaviors. Based on participants’ responses to the NQ-E questionnaire, individual scores were calculated and subsequently used to classify participants into corresponding NQ grades. The NQ-E, developed by the Korean Nutrition Society, consists of four domains encompassing 17 questions: 8 addressing dietary balance, 2 on dietary variety, and 7 on moderation. This study used the NQ-E questionnaire revised in 2021.

6. Statistical analysis

The collected data were analyzed using IBM SPSS Statistics (version 24.0; IBM Corp.). Basic statistics, including frequency, mean, and standard deviation, were determined for each survey item. Total energy intake, nutrient intake, and NQ scores were compared using independent samples t-tests. Because NQ grades are categorical variables, they were analyzed using the Chi-square test (χ² test). The Kruskal–Wallis test was conducted to examine differences among groups based on NQ-E classifications, followed by Dunn’s post-hoc test for pairwise comparisons. Statistical significance was set at P < 0.05.

RESULTS

1. General characteristics

The general characteristics of the participants are listed in Table 1. The study population consisted of 24 males (30.4%) and 55 females (69.6%), with a mean age of 76.33 years. Among the participants, 46 (58.2%) reported engaging in regular exercise, and 33 (41.8%) did not. Although most participants were married, 49 (62.0%) lived with family members, and 30 (38.0%) lived alone. In the multiple-response survey of medical history, hypertension was the most prevalent condition, followed by dyslipidemia and diabetes mellitus.

2. Dietary assessment

The nutrient intake stratified by age and sex is presented in Table 2. The participants were classified as young adults (65–74 years) and older adults (≥ 75 years) within each sex group. No significant differences in nutrient intake were observed between the two age groups within the same sex. However, significant sex-related differences were observed within the same age group. Females older adults had significantly lower intakes of energy, protein, fat, vitamin E, riboflavin, folate, and zinc than those of male older adults (P < 0.05). In contrast, no significant sex-related differences in nutrient intake were observed among young adults.

The ratio of nutrient intake relative to the KDRI is shown in Fig. 1. The participants were divided into four groups based on sex and age: males aged 65–74 years, males aged ≥ 75 years, females aged 65–74 years, and females aged ≥ 75 years. Significant differences were observed among the four groups in the intake ratios of vitamin A, vitamin E, riboflavin, folate, and zinc. Additionally, among rural adults aged 65 years and older in this study, the proportion of sodium intake was the highest, followed by carbohydrate intake. In contrast, the intakes of vitamins A and D, niacin, and calcium were insufficient relative to the KDRI.

3. Nutrition Quotient for Elderly

A comparison of the NQ-E scores and grades among the study participants is presented in Table 3. Among males, no significant differences were observed in the total NQ-E score or grade distribution between the young and older adult groups. However, among females, the young adult group showed significantly higher NQ-E total scores, moderation domain scores, and NQ-E grade distribution than those in the older adult group (P < 0.05). No significant sex-related differences in NQ-E scores or grade distribution were observed within the same age group.

The NQ-E item scores by age and sex are presented in Table 4. Among males, no significant differences were observed in NQ-E item scores between the young and older adult groups. However, among females, the young adult group showed significantly higher scores for nut intake and checking expiration dates and nutrition labeling. Within the young adult age group, females had significantly higher scores for fruit intake, whereas males had significantly higher scores for self-perceived health status. In contrast, no significant sex-related differences were observed within the older adult group.

4. Comparison of nutrition intake according to NQ-E grade distribution

A comparison of nutrient intake according to NQ-E grade is presented in Table 5. The participants were classified into three groups (high, moderate, and low grades). The analysis revealed no significant differences in energy intake among the groups; however, the intakes of fat, dietary fiber, vitamins A and D, thiamine, riboflavin, niacin, potassium, and magnesium were significantly lower in the low-grade group than in the moderate- and high-grade groups.

5. Comparison of general characteristics and NQ-E grade

A comparison of the general characteristics and NQ-E grade distribution among the study participants is presented in Table 6. The distribution of NQ-E grades differed significantly according to the exercise status, with participants engaging in more frequent exercise being classified into the high NQ-E grade group, whereas those who did not exercise were classified into the moderate NQ-E grade group. Similarly, the NQ-E grade distribution varied significantly according to supplement use, with supplement users being frequently classified in the high NQ grade group and non-users in the low NQ-E grade group. In contrast, no significant differences in NQ-E grade distribution were observed with respect to smoking status, employment status, living arrangement, or recent weight changes.

DISCUSSION

This study explored dietary quality among rural older adults, focusing on age- and sex-related differences. The lower NQ-E scores and nutrient intake observed in female aged ≥ 75 years indicate a higher risk of nutritional inadequacy, possibly associated with age-related declines in appetite, chewing ability, and food access [25]. These findings highlight the need for targeted nutritional interventions for the oldest age group, particularly among female residing in rural communities. The positive association between NQ-E scores and health-promoting behaviors such as regular exercise and supplement use underscores the importance of integrating lifestyle management into community-based nutrition programs to support healthy aging.

The average NQ score of the four groups in this study was 55.01, which was lower than the average scores of the Korean urban elderly population (57.6) [19] and elderly with poor oral health (58.7) [26]. However, this score was slightly higher than the NQ-E score reported for older adults living alone (50.14) [27]. Although this study did not include a comparison group of urban older adults, previous research suggests that nutrient intake among rural older adults tends to be poorer than that among urban older adults.

A previous study has reported malnutrition in older adults [28]. Furthermore, another study has reported that nutritional adequacy and diet quality decline with age, particularly among female [29]. Consistently, our study showed that nutrient intake was lower in female aged ≥ 75 years than in those aged 65–74 years, further supporting the evidence that older female are particularly vulnerable to nutritional inadequacy. Age-related physiological changes, reduced appetite, dental issues, and physical limitations may restrict both the quantity and variety of food intake [30]. Social and environmental factors, such as living alone or limited access to diverse foods, may further exacerbate these nutritional challenges [31]. These results highlight the need for targeted community-based nutrition programs that focus on older female and individuals with limited support to improve nutrient adequacy and dietary quality.

In this study, nutrient intake patterns differed significantly according to NQ-E grade, with participants in the low-grade group showing lower intakes of protein, dietary fiber, calcium, and several micronutrients. These findings indicate that the NQ-E grades effectively reflect differences in nutrient intake according to dietary quality among older adults living in rural areas, providing descriptive evidence of nutritional disparities within this population.

In the balance domain, differences in food group scores by age and sex suggest that both older female and younger male had limited intake of certain food groups, such as nuts, fruits, and dairy products. These findings indicate that the overall balance scores were particularly low in this rural population, suggesting limited dietary variety and a potential risk for inadequate intake of key nutrients such as calcium, protein, and unsaturated fatty acids [15, 26]. Consistent with these findings, our study revealed that calcium intake was inadequate when expressed as a percentage of DRI.

Previous studies in Korea reported low balance domain scores (approximately 46 points) among community-dwelling older adults using the NQ-E [19]. Similarly, a large study in rural China found that older adults had significantly lower dietary diversity than their urban counterparts [32]. In line with these findings, the present study showed particularly low balance scores among rural older adults, suggesting limited dietary variety and a potential risk of inadequate intake of key nutrients such as calcium, protein, and unsaturated fatty acids. Consistent with this, calcium intake was inadequate when expressed as a percentage of the DRI.

In the moderation domain, across age and sex groups showed relatively high intake frequencies of sweet snacks and sugar-sweetened beverages compared to fatty snacks or baked products. These patterns suggest that excessive intake of added sugars, rather than high-fat snacks, may be a more prominent dietary concern in this rural population, underscoring the need for targeted interventions to reduce sugar intake while promoting healthier alternatives. Moreover, all four groups consumed more than 150% of the KDRI for carbohydrates, indicating the need for closer attention to the overall carbohydrate consumption in this population.

In the practice domain, both age and sex differences were observed. Younger adults tended to show greater attention to nutrition labels and stronger self-awareness of health, indicating higher engagement in healthy dietary behaviors than older groups. Male generally reported higher awareness of their own health, suggesting possible gender-related differences in health perception and behavior. These patterns may reflect variations in health literacy and access to nutrition information across demographic groups.

Across all groups, balance scores were lower than practice scores, indicating relatively weaker performance in dietary balance among rural older adults [20]. However, the balance domain of the NQ-E reflects not only dietary diversity but also the adequacy of food group and nutrient intake. The observed pattern in this study is consistent with national data showing that balance scores are generally lower than other domain scores among older adults in Korea [19, 20, 26]. Therefore, the lower balance scores in this population should not be interpreted as a problem unique to rural communities but rather as part of a broader trend in the elderly population. Continuous efforts to improve dietary balance, including education on food group adequacy and nutrient diversity, remain essential for promoting healthy aging [5, 19].

The observed association between higher NQ-E scores and both regular physical activity and dietary supplement use indicates that health-promoting behaviors are positively associated with dietary quality. This finding is consistent with previous studies showing that physically active older adults and those using dietary supplements have higher nutrient adequacy and healthier dietary patterns [33, 34]. Therefore, integrating lifestyle strategies, such as promoting physical activity along with nutrition education, may be an effective approach to support healthy aging and prevent nutrition-related chronic conditions in this population.

Although many studies have reported that older adults living alone or with lower income tend to have poorer dietary intake [27, 28], no significant differences in NQ grade distribution were observed according to living arrangements among older adults in this rural community. Although income was not assessed, employment status showed no association with NQ grade distribution. All participants in this study were independently functioning, which may suggest that their dietary quality is less affected by income or living conditions. These findings highlight the need for future studies comparing dietary quality according to functional independence among older adults.

Limitations

This study had several limitations that should be considered when interpreting the findings. The small sample size may have limited statistical power and prevented the detection of true differences or associations. Consequently, the generalizability of the findings may be restricted. Second, dietary intake was assessed using a single 24-hour recall, which may not fully capture habitual dietary patterns. Third, data were collected between June and December, and seasonal variations in food availability and dietary habits may have influenced nutrient intake. Additionally, as a small-scale cross-sectional study, causal inferences between dietary quality and related characteristics cannot be established. Despite these limitations, this study provides valuable baseline data on the dietary quality of rural older adults using the NQ-E and 24-hour recalls to examine associations with demographic and lifestyle factors.

Future research should adopt longitudinal designs with larger and more diverse samples to validate these findings and explore causal pathways. The inclusion of psychosocial, economic, and environmental factors will provide a more comprehensive understanding of the determinants of dietary quality among older adults. Intervention studies are warranted to evaluate the effectiveness of tailored community-based nutrition programs in improving dietary quality and preventing nutrition-related chronic conditions in this population.

Conclusion

This study examined nutrient intake, dietary quality, and lifestyle factors among older adults in rural Korea. Female aged 75 years and older showed lower intakes of key nutrients and lower NQ-E scores than younger groups, indicating greater nutritional vulnerability. Regular physical activity and supplement use were associated with higher dietary quality. These findings highlight the need for community-based nutrition programs that improve access to diverse, nutrient-rich foods and promote balanced diets to support healthy aging in rural populations.

NOTES

CONFLICT OF INTEREST

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

FUNDING

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. RS-2023-00242278).

DATA AVAILABILITY

Research data is available upon request to the corresponding author.

Fig. 1.

Comparison of mean percentages of dietary reference intakes for Korean (KDRI) by age and sex. ^*The four groups showed significant differences in the ratio of nutrient intake relative to the KDRI.

Table 1.

General characteristics of participants

Variable	Value
Sex
Male	24 (30.4)
Female	55 (69.6)
Age (year)	76.33 ± 6.54
65–74	35 (44.3)
≥ 75	44 (55.7)
Regular exercise
Do exercise	46 (58.2)
Do not exercise	33 (41.8)
Smoking
Yes	8 (10.1)
No	71 (89.9)
Married
Yes	78 (98.7)
No	1 (1.3)
Employment
Yes	58 (73.4)
No	21 (26.6)
Housemate
With family	49 (62.0)
Alone	30 (38.0)
Change in body weight (3 months)
Yes	14 (17.7)
No	65 (82.3)
Food allergy
≥ 1	4 (5.1)
0	75 (94.9)
Supplement intake
≥ 1	51 (64.6)
0	28 (35.4)
Medical history (multiple responses)
None	7 (8.9)
Cardiovascular diseases	9 (11.4)
Arteriosclerosis	1 (1.2)
Hypertension	50 (63.3)
Dyslipidemia	27 (34.1)
Diabetes mellitus	18 (22.8)
Gastrointestinal diseases	5 (6.3)
Respiratory diseases	4 (5.1)

n (%) or Mean ± SD.

Table 2.

Daily nutrient intake in participants by age and sex

Variables	Total (n = 79)	Male (n = 24)		P-value¹⁾	Female (n = 55)		P-value²⁾	P-value³⁾	P-value⁴⁾
Variables	Total (n = 79)	Young adults (n = 13)	Older adults (n = 11)	P-value¹⁾	Young adults (n = 22)	Older adults (n = 33)	P-value²⁾	P-value³⁾	P-value⁴⁾
Energy (kcal)	1,515.63 ± 420.44	1,761.47 ± 475.77	1,667.27 ± 374.10	0.60	1,511.33 ± 448.08	1,371.11 ± 341.30	0.19	0.13	0.02
Carbohydrate (g)	241.08 ± 67.45	264.49 ± 95.63	258.34 ± 54.66	0.85	236.00 ± 70.12	229.50 ± 54.94	0.70	0.32	0.14
Protein (g)	59.01 ± 20.81	63.45 ± 18.86	65.98 ± 21.47	0.17	61.30 ± 25.4	53.42 ± 17.09	0.76	0.15	0.02
Fat (g)	59.02 ± 20.81	63.46 ± 18.86	65.99 ± 21.47	0.76	61.30 ± 25.46	53.43 ± 17.10	0.17	0.79	0.05
Energy distribution
% Carbohydrate	-	60.21 ± 10.98	62.68 ± 7.55	0.53	63.21 ± 9.10	67.57 ± 7.81	0.06	0.39	0.08
% Protein	-	20.90 ± 6.44	19.85 ± 6.74	0.70	19.02 ± 6.42	16.05 ± 6.23	0.07	0.46	0.09
% Fat	-	14.62 ± 2.82	15.64 ± 2.60	0.37	15.97 ± 3.24	15.53 ± 2.85	0.60	0.22	0.91
Fiber (g)	24.42 ± 9.92	25.55 ± 12.51	25.73 ± 9.10	0.97	25.71 ± 10.43	22.69 ± 8.85	0.25	0.97	0.33
Vitamin A (μg RAE)	257.79 ± 158.50	203.51 ± 140.08	282.16 ± 163.85	0.22	302.30 ± 173.91	241.39 ± 150.32	0.17	0.09	0.45
Vitamin D (μg)	1.64 ± 1.89	2.29 ± 2.48	2.01 ± 1.75	0.76	1.28 ± 1.64	1.50 ± 1.83	0.65	0.16	0.42
Vitamin E (mg)	12.53 ± 6.44	12.56 ± 6.26	15.70 ± 8.22	0.30	13.66 ± 6.83	10.70 ± 5.19	0.07	0.64	0.02
Vitamin C (mg)	74.48 ± 44.89	68.86 ± 50.92	71.35 ± 36.83	0.89	68.14 ± 46.24	81.97 ± 44.84	0.27	0.97	0.48
Thiamine (mg)	1.10 ± 0.40	1.25 ± 0.49	1.14 ± 0.32	0.52	1.12 ± 0.43	1.02 ± 0.35	0.31	0.42	0.31
Riboflavin (mg)	1.25 ± 0.51	1.24 ± 0.44	1.61 ± 0.55	0.08	1.25 ± 0.45	1.14 ± 0.54	0.43	0.93	0.02
Niacin (mg NE)	6.57 ± 3.40	7.20 ± 4.48	7.50 ± 3.23	0.86	6.80 ± 3.15	5.86 ± 3.15	0.28	0.75	0.14
Folic acid (μg DFE)	300.66 ± 149.11	267.62 ± 120.89	379.12 ± 163.33	0.07	307.65 ± 186.80	282.85 ± 120.66	0.55	0.49	0.04
Vitamin B₁₂ (μg)	3.24 ± 5.63	3.10 ± 2.97	3.59 ± 2.45	0.67	2.22 ± 1.90	3.87 ± 8.28	0.36	0.29	0.91
Calcium (mg)	545.87 ± 273.93	585.81 ± 335.29	539.79 ± 209.41	0.70	552.67 ± 224.11	527.63 ± 305.05	0.74	0.73	0.90
Phosphorus (mg)	992.06 ± 315.90	1,079.64 ± 340.97	1,055.69 ± 334.05	0.86	1,030.16 ± 322.02	910.95 ± 290.57	0.16	0.67	0.17
Sodium (mg)	4,451.17 ± 1,965.99	4,578.45 ± 2,038.26	5,135.32 ± 1,578.63	0.47	4,520.27 ± 2,620.29	4,126.92 ± 1,516.42	0.48	0.95	0.06
Potassium (mg)	2,892.98 ± 1,112.79	3,274.20 ± 1,353.47	2,941.71 ± 871.86	0.49	3,027.44 ± 1,234.83	2,636.92 ± 976.37	0.20	0.58	0.36
Magnesium (mg)	297.73 ± 144.27	312.98 ± 143.63	310.71 ± 121.58	0.97	315.88 ± 192.39	275.29 ± 114.85	0.33	0.96	0.39
Iron (mg)	11.06 ± 4.21	11.93 ± 5.16	11.92 ± 4.01	0.99	11.01 ± 4.48	10.47 ± 3.77	0.63	0.58	0.28
Zinc (mg)	6.45 ± 2.95	6.49 ± 2.38	8.00 ± 4.20	0.28	6.75 ± 2.44	5.71 ± 2.87	0.17	0.76	0.04

Mean ± SD.

μg RAE, micrograms of retinol activity equivalents; mg NE, milligrams of niacin equivalents; μg DFE, micrograms of dietary folate equivalents.

¹⁾Male group.

²⁾Female group.

³⁾Young adult male and female groups.

⁴⁾Older adult male and female groups.

Table 3.

Comparison of balance, moderation, dietary practice, and NQ-E score across age and sex groups

Variables	Total (n = 79)	Male (n = 24)		P-value¹⁾	Female (n = 55)		P-value²⁾	P-value³⁾	P-value⁴⁾
Variables	Total (n = 79)	Young adults (n = 13)	Older adults (n = 11)	P-value¹⁾	Young adults (n = 22)	Older adults (n = 33)	P-value²⁾	P-value³⁾	P-value⁴⁾
NQ-E score	54.34 ± 12.98	54.98 ± 17.23	51.74 ± 12.58	0.61	58.62 ± 10.86	52.09 ± 12.33	0.05	0.45	0.93
Balance	44.50 ± 16.57	43.29 ± 19.63	42.04 ± 16.41	0.87	49.51 ± 15.83	42.45 ± 15.86	0.11	0.31	0.94
Moderation	52.62 ± 30.48	49.05 ± 41.15	49.41 ± 25.27	0.98	65.43 ± 29.57	46.54 ± 26.40	0.02	0.18	0.75
Practice	70.30 ± 12.96	75.07 ± 14.32	67.65 ± 14.15	0.22	70.99 ± 11.01	68.84 ± 13.28	0.53	0.35	0.80
Grade
Upper grade	28 (35.4)	5 (38.5)	2 (18.2)	0.43	12 (54.5)	9 (27.3)	0.03	0.10	0.75
Moderate grade	33 (41.8)	4 (30.8)	6 (54.5)		9 (40.9)	14 (42.4)
Low grade	18 (22.8)	4 (30.8)	3 (27.3)		1 (4.5)	10 (30.3)
χ² value				0.14			1.56	4.42	0.14

Mean ± SD.

NQ-E, Nutrition Quotient for the Elderly.

¹⁾Male group.

²⁾Female group.

³⁾Young adult male and female groups.

⁴⁾Older adult male and female groups.

Table 4.

Comparison of NQ-E scores for each item by age and sex of the participants

Item	Variables	Male (n = 24)		P-value¹⁾	Female (n = 55)		P-value²⁾	P-value³⁾	P-value⁴⁾
Item	Variables	Young adults (n = 13)	Older adults (n = 11)	P-value¹⁾	Young adults (n = 22)	Older adults (n = 33)	P-value²⁾	P-value³⁾	P-value⁴⁾
Balance (8)	Intake frequency of fruits	30.77 ± 35.58	34.09 ± 23.11	0.79	59.09 ± 35.81	43.94 ± 32.49	0.11	0.03	0.28
	Intake frequency of milk or dairy products	21.15 ± 30.36	25.00 ± 33.54	0.77	34.09 ± 30.42	40.15 ± 37.47	0.51	0.23	0.24
	Intake frequency of fish or shellfish	40.38 ± 19.20	45.45 ± 18.77	0.52	35.23 ± 23.98	37.88 ± 26.61	0.71	0.51	0.31
	Intake frequency of eggs	75.00 ± 32.27	63.64 ± 37.69	0.43	63.64 ± 32.48	52.27 ± 35.56	0.23	0.32	0.37
	Intake frequency of beans or bean products	51.92 ± 36.03	61.36 ± 30.34	0.50	38.64 ± 33.39	49.24 ± 39.27	0.30	0.28	0.36
	Intake frequency of nuts	23.08 ± 34.55	20.45 ± 26.97	0.84	34.09 ± 42.64	11.36 ± 25.84	0.03	0.44	0.32
	Intake frequency of cooked rice with mixed grains	55.77 ± 46.94	29.55 ± 36.77	0.15	72.73 ± 37.72	52.27 ± 45.66	0.08	0.25	0.11
	Intake frequency of water	75.00 ± 30.62	75.00 ± 22.36	≥ 0.99	67.05 ± 23.64	68.18 ± 24.43	0.86	0.39	0.42
Moderation (2)	Intake frequency of sweetened snacks or beverages	46.15 ± 45.47	45.45 ± 29.19	0.96	64.77 ± 33.33	44.70 ± 29.82	0.02	0.17	0.94
Moderation (2)	Intake frequency of greasy baked products or snacks	71.15 ± 35.13	79.55 ± 21.85	0.50	70.45 ± 35.05	60.61 ± 32.49	0.29	0.95	0.08
Practice (7)	Efforts to have healthy eating habits	63.46 ± 26.25	59.09 ± 30.15	0.71	72.73 ± 29.79	60.61 ± 22.56	0.09	0.36	0.86
	Checking of expiration date and nutrition labeling	67.31 ± 35.92	65.91 ± 30.15	0.92	86.36 ± 21.45	66.67 ± 34.04	0.01	0.06	0.95
	Washing hands practices before eating meals	90.38 ± 21.74	86.36 ± 17.19	0.62	97.73 ± 10.66	91.67 ± 18.40	0.13	0.19	0.40
	Difficulty in chewing foods	78.85 ± 26.70	63.64 ± 30.34	0.20	75.00 ± 29.88	62.88 ± 32.55	0.17	0.70	0.95
	Depressive condition	76.92 ± 25.94	65.91 ± 28.00	0.33	62.50 ± 31.58	69.70 ± 30.46	0.40	0.17	0.72
	Degree of sound sleep	75.00 ± 27.00	65.91 ± 23.11	0.39	62.50 ± 32.50	74.24 ± 28.29	0.16	0.25	0.38
	Level of awareness of one’s own health	73.08 ± 16.01	68.18 ± 16.17	0.46	53.41 ± 19.36	59.85 ± 21.60	0.26	0.01	0.19

Mean ± SD.

NQ-E, Nutrition Quotient for the Elderly.

¹⁾Male group.

²⁾Female group.

³⁾Young adult male and female groups.

⁴⁾Older adult male and female groups.

Table 5.

Daily nutrient intake based on NQ-E grade in participants

Variables	Total (n = 79)	NQ-E grade			P-value
Variables	Total (n = 79)	Upper (n = 28)	Moderate (n = 33)	Low (n = 18)	P-value
Energy (kcal)	1,515.63 ± 420.44	1,582.06 ± 385.97	1,508.89 ± 399.68	1,424.66 ± 507.57	0.47
Carbohydrate (g)	241.08 ± 67.45	240.50 ± 60.06	241.53 ± 58.75	241.16 ± 92.98	0.99
Protein (g)	59.01 ± 20.81	65.48 ± 20.91	57.58 ± 20.80	51.15 ± 18.36	0.06
Fat (g)	59.02 ± 20.81	65.34 ± 21.28	57.95 ± 20.59	51.16 ± 18.36	0.07
Fiber (g)	24.42 ± 9.92	28.68 ± 10.00^a	22.05 ± 8.36^c	22.16 ± 10.70^b	0.02
Vitamin A (μg RAE)	257.79 ± 158.50	326.57 ± 152.15^a	245.99 ± 161.39^b	172.45 ± 117.04^c	0.01
Vitamin D (μg)	1.64 ± 1.89	1.04 ± 1.31^a	1.66 ± 1.76^ab	2.54 ± 2.52^b	0.03
Vitamin E (mg)	12.53 ± 6.44	14.12 ± 6.20	12.21 ± 6.73	10.63 ± 5.99	0.19
Vitamin C (mg)	74.48 ± 44.89	84.62 ± 41.12	68.32 ± 47.36	69.99 ± 45.52	0.33
Thiamine (mg)	1.10 ± 0.40	1.24 ± 0.47^a	1.08 ± 0.31^b	0.93 ± 0.34^c	0.02
Riboflavin (mg)	1.25 ± 0.51	1.45 ± 0.42^a	1.22 ± 0.56^b	1.01 ± 0.47^c	0.01
Niacin (mg NE)	6.57 ± 3.40	7.48 ± 3.35^a	6.81 ± 3.43^b	4.71 ± 2.85^c	0.02
Folic acid (μg DFE)	300.66 ± 149.11	350.63 ± 160.02	284.90 ± 135.42	251.82 ± 140.38	0.06
Vitamin B₁₂ (μg)	3.24 ± 5.63	3.73 ± 8.68	2.67 ± 2.28	3.53 ± 3.88	0.75
Calcium (mg)	545.87 ± 273.93	636.46 ± 310.16	484.90 ± 255.08	516.72 ± 217.71	0.08
Phosphorus (mg)	992.06 ± 315.90	1,092.84 ± 270.65	962.29 ± 331.28	889.88 ± 324.72	0.08
Sodium (mg)	4,451.17 ± 1,965.99	4,742.14 ± 2,178.69	4,397.21 ± 1,847.47	4,097.50 ± 1,868.94	0.55
Potassium (mg)	2,892.98 ± 1,112.79	3,351.06 ± 1,219.59^a	2,662.15 ± 891.34^b	2,603.61 ± 1,134.05^c	0.02
Magnesium (mg)	297.73 ± 144.27	358.17 ± 177.60^a	260.58 ± 98.62^c	271.82 ± 132.99^b	0.02
Iron (mg)	11.06 ± 4.21	12.54 ± 4.32	10.42 ± 3.85	9.94 ± 4.25	0.06
Zinc (mg)	6.45 ± 2.95	7.22 ± 2.51	6.48 ± 3.37	5.20 ± 2.44	0.07

Mean ± SD.

NQ-E, Nutrition Quotient for the Elderly; NQ, Nutrition Quotient; μg RAE, micrograms of retinol activity equivalents; mg NE, milligrams of niacin equivalents; μg DFE, micrograms of dietary folate equivalents.

^a–cDifferent superscript letters within the same row indicate significant differences among groups at P < 0.05 by the Kruskal–Wallis test with Dunn’s post-hoc test.

Table 6.

Analysis of NQ-E grade distribution according to general characteristics

Item	Variables	Total (n = 79)	NQ-E grade			P-value
Item	Variables	Total (n = 79)	Upper (n = 28)	Moderate (n = 33)	Low (n = 18)	P-value
Exercise	Do exercise	46 (58.2)	26 (92.9)	17 (51.5)	3 (16.7)	< 0.01
Exercise	Do not exercise	33 (41.8)	2 (7.1)	16 (48.5)	15 (83.3)
Smoking	Yes	8 (10.1)	1 (3.6)	4 (12.1)	3 (16.7)	0.31
Smoking	No	71 (89.9)	27 (96.4)	29 (87.9)	15 (83.3)
Employment	Yes	58 (73.4)	20 (71.4)	26 (78.8)	12 (66.7)	0.62
Employment	No	21 (26.6)	8 (28.6)	7 (21.2)	6 (33.3)
Housemate	With family	49 (62.0)	21 (75.0)	19 (57.6)	9 (50.0)	0.18
Housemate	Alone	30 (38.0)	7 (25.0)	14 (42.4)	9 (50.0)
Change in body weight	Yes	14 (17.7)	3 (10.7)	7 (21.2)	4 (22.2)	0.48
Change in body weight	No	65 (82.3)	25 (89.3)	26 (78.8)	14 (77.8)
Medical history	≥ 1	72 (91.1)	23 (82.1)	31 (93.9)	18 (100)	0.09
Medical history	0	7 (8.9)	5 (17.9)	2 (6.1)	-
Drug	≥ 1	71 (89.9)	25 (89.3)	28 (84.8)	18 (100)	0.25
Drug	0	8 (10.1)	3 (10.7)	5 (15.2)	-
Allergy	≥ 1	4 (5.1)	2 (7.1)	1 (3.0)	1 (5.6)	0.76
Allergy	0	75 (94.9)	26 (92.9)	32 (97.0)	17 (94.4)
Supplement intake	≥ 1	51 (64.6)	22 (78.6)	23 (69.7)	6 (33.3)	0.01
Supplement intake	0	28 (35.4)	6 (21.4)	10 (30.3)	12 (66.7)

n (%).

NQ-E, Nutrition Quotient for the Elderly.

REFERENCES

1. Shrivastava SR, Shrivastava PS, Ramasamy J. Health-care of elderly: determinants, needs and services. Int J Prev Med 2013; 4(10): 1224-1225. PubMed PMC
2. Ministry of Data and Statistics. 2024 Statistics on the elderly [Internet]. Statistics Korea; 2024 [cited 2025 Aug 10]. Available from: https://kostat.go.kr/board.es?mid=a10301010000&bid=10820&act=view&list_no=432917
3. Hong J, Yi S, Yoon T. The impact of the COVID-19 pandemic on life expectancy by the level of area deprivation in South Korea. Front Public Health 2023; 11: 1215914.Article PubMed PMC
4. Tak YJ, Lee JG, Yi YH, Kim YJ, Lee S, Cho BM, et al. Association of handgrip strength with dietary intake in the Korean population: findings based on the Seventh Korea National Health and Nutrition Examination Survey (KNHANES VII-1), 2016. Nutrients 2018; 10(9): 1180.Article PubMed PMC
5. Kim EK, Kim H, Vijayakumar A, Kwon O, Chang N. Associations between fruit and vegetable, and antioxidant nutrient intake and age-related macular degeneration by smoking status in elderly Korean men. Nutr J 2017; 16(1): 77.Article PubMed PMC PDF
6. Kim TS, Chung JW. Associations of dietary riboflavin, niacin, and retinol with age-related hearing loss: an analysis of Korean National Health and Nutrition Examination Survey data. Nutrients 2019; 11(4): 896.Article PubMed PMC
7. Bruins MJ, Van Dael P, Eggersdorfer M. The role of nutrients in reducing the risk for noncommunicable diseases during aging. Nutrients 2019; 11(1): 85.Article PubMed PMC
8. Wu J, Zhang H, Shao J, Chen D, Xue E, Huang S, et al. Healthcare for older adults with multimorbidity: a scoping review of reviews. Clin Interv Aging 2023; 18: 1723-1735. Article PubMed PMC Link
9. GBD 2017 Diet Collaborators. Health effects of dietary risks in 195 countries, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2019; 393(10184): 1958-1972. PubMed PMC
10. Kim HR. Quality of diet and nutritional intake and mortality risk among South Korean adults based on 12-year follow-up data. Korean J Community Nutr 2016; 21(4): 354-365. Article Link
11. Kheirouri S, Alizadeh H. Dietary diversity and cognitive performance in older adults: a systematic review. BMC Neurol 2025; 25(1): 144.Article PubMed PMC PDF
12. Sustainable Development Goals. Korea SDG indicator 2.1.1 - proportion of undernourished population [Internet]. Statistics Korea; 2025 [cited 2025 Sep 01]. Available from: https://kostat-sdg-kor.github.io/sdg-indicators/2-1-1/
13. Bloom I, Edwards M, Jameson KA, Syddall HE, Dennison E, Gale CR, et al. Influences on diet quality in older age: the importance of social factors. Age Ageing 2017; 46(2): 277-283. Article PubMed PMC
14. Host A, McMahon AT, Walton K, Charlton K. Factors influencing food choice for independently living older people-a systematic literature review. J Nutr Gerontol Geriatr 2016; 35(2): 67-94. Article PubMed
15. Lee Y, Choi Y, Park HR, Song KH, Lee KE, Yoo CH, et al. Comparative analysis of dietary behavior and nutrient intake of elderly in urban and rural areas for development of “Village Lunch Table” program: based on 2014 Korea National Health and Nutrition Examination Survey data. J Nutr Health 2017; 50(2): 171-179. Article Link
16. Ha K, Song Y, Kim HK. Regional disparities in the associations of cardiometabolic risk factors and healthy dietary factors in Korean adults. Nutr Res Pract 2020; 14(5): 519-531. Article PubMed PMC Link
17. Son S, Lee HS. The characteristics of population distribution and change in rural areas: 1995-2020. J Korean Geogr Soc 2021; 56(6): 607-622.
18. Hong N, Kim KJ, Lee SJ, Kim CO, Kim HC, Rhee Y, et al. Cohort profile: Korean Urban Rural Elderly (KURE) study, a prospective cohort on ageing and health in Korea. BMJ Open 2019; 9(10): e031018. Article PubMed PMC
19. Chung MJ, Kwak TK, Kim HY, Kang MH, Lee JS, Chung HR, et al. Development of NQ-E, Nutrition Quotient for Korean elderly: item selection and validation of factor structure. J Nutr Health 2018; 51(1): 87-102. Article Link
20. Lim YS, Lee JS, Hwang JY, Kim KN, Hwang HJ, Kwon S, et al. Revision of Nutrition Quotient for Elderly in assessment of dietary quality and behavior. J Nutr Health 2022; 55(1): 155-173. Article Link
21. Park EO. A comparison of community health status by region and an investigation of related factors using community health indicators. J Korean Acad Community Health Nurs 2012; 23(1): 31-39. Article
22. Lee JH. The regional health inequity, and individual and neighborhood level health determinants. Health Soc Welf Rev 2016; 36(2): 345-384. Article
23. Kim DJ. Socioeconomic status, area deprivation and health behavior gaps. Health Welf Policy Forum 2018; 260: 30-38.
24. World Health Organization (WHO). WHO guidelines on physical activity and sedentary behavior. WHO; 2020.
25. Ahn Y, Lee Y, Park H, Song K. Gender and age group differences in nutrition intake and dietary quality of Korean adults eating alone: based on Korean National Health and Nutrition Examination Survey Data, 2013-2016. Nutr Res Pract 2021; 15(1): 66-79. Article PubMed Link
26. Yi NY, Choi JH. Evaluation of the nutrient quotient for the elderly (NQ-E) using congregate meal services according to their oral health conditions. Nutr Res Pract 2022; 16(5): 628-645. Article PubMed PMC Link
27. Gang G, Lee MJ, Choi EH, Lee HL, Lee HY, Chang HJ, et al. Evaluation on the Nutrition Quotient scores of elderly people living alone in Korea. Nutrients 2023; 15(17): 3750.Article PubMed PMC
28. Ramic E, Pranjic N, Batic-Mujanovic O, Karic E, Alibasic E, Alic A. The effect of loneliness on malnutrition in elderly population. Med Arh 2011; 65(2): 92-95. PubMed
29. Ahn Y, Lee Y, Park H, Song K. Gender and age group differences in nutrition intake and dietary quality of Korean adults eating alone: based on Korean National Health and Nutrition Examination Survey data, 2013-2016. Nutr Res Pract 2021; 15(1): 66-79. Article PubMed Link
30. Clegg ME, Godfrey A. The relationship between physical activity, appetite and energy intake in older adults: a systematic review. Appetite 2018; 128: 145-151. Article PubMed
31. Jang W, Kim M, Kim Y. Association between living alone with frailty among elderly Korean men. J Nutr Health 2025; 58(1): 77-86. Article Link
32. Deng C, Vicerra PMM. Household structure and dietary diversity among older adults in rural and urban China: a cross-sectional study. BMC Public Health 2024; 24(1): 3004.Article PubMed PMC PDF
33. Shim JE, Kim SJ, Kim K, Hwang JY. Spatial disparity in food environment and household economic resources related to food insecurity in rural Korean households with older adults. Nutrients 2018; 10(10): 1514.Article PubMed PMC
34. Kim H, Park SG. Effect of a single multi-vitamin and mineral supplement on nutritional intake in Korean Elderly: Korean National Health and Nutrition Examination Survey 2018-2020. Nutrients 2023; 15(7): 1561.Article PubMed PMC

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Nutrition Quotient and nutrient intake among older adults in a rural Korean community: a cross-sectional study

Korean J Community Nutr. 2025;30(6):397-409. Published online December 31, 2025

DOI: https://doi.org/10.5720/kjcn.2025.00283

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Nutrition Quotient and nutrient intake among older adults in a rural Korean community: a cross-sectional study

Fig. 1. Comparison of mean percentages of dietary reference intakes for Korean (KDRI) by age and sex. *The four groups showed significant differences in the ratio of nutrient intake relative to the KDRI.

Fig. 1.

Nutrition Quotient and nutrient intake among older adults in a rural Korean community: a cross-sectional study

Variable	Value
Sex
Male	24 (30.4)
Female	55 (69.6)
Age (year)	76.33 ± 6.54
65–74	35 (44.3)
≥ 75	44 (55.7)
Regular exercise
Do exercise	46 (58.2)
Do not exercise	33 (41.8)
Smoking
Yes	8 (10.1)
No	71 (89.9)
Married
Yes	78 (98.7)
No	1 (1.3)
Employment
Yes	58 (73.4)
No	21 (26.6)
Housemate
With family	49 (62.0)
Alone	30 (38.0)
Change in body weight (3 months)
Yes	14 (17.7)
No	65 (82.3)
Food allergy
≥ 1	4 (5.1)
0	75 (94.9)
Supplement intake
≥ 1	51 (64.6)
0	28 (35.4)
Medical history (multiple responses)
None	7 (8.9)
Cardiovascular diseases	9 (11.4)
Arteriosclerosis	1 (1.2)
Hypertension	50 (63.3)
Dyslipidemia	27 (34.1)
Diabetes mellitus	18 (22.8)
Gastrointestinal diseases	5 (6.3)
Respiratory diseases	4 (5.1)

Variables	Total (n = 79)	Male (n = 24)		P-value¹⁾	Female (n = 55)		P-value²⁾	P-value³⁾	P-value⁴⁾
Variables	Total (n = 79)	Young adults (n = 13)	Older adults (n = 11)	P-value¹⁾	Young adults (n = 22)	Older adults (n = 33)	P-value²⁾	P-value³⁾	P-value⁴⁾
Energy (kcal)	1,515.63 ± 420.44	1,761.47 ± 475.77	1,667.27 ± 374.10	0.60	1,511.33 ± 448.08	1,371.11 ± 341.30	0.19	0.13	0.02
Carbohydrate (g)	241.08 ± 67.45	264.49 ± 95.63	258.34 ± 54.66	0.85	236.00 ± 70.12	229.50 ± 54.94	0.70	0.32	0.14
Protein (g)	59.01 ± 20.81	63.45 ± 18.86	65.98 ± 21.47	0.17	61.30 ± 25.4	53.42 ± 17.09	0.76	0.15	0.02
Fat (g)	59.02 ± 20.81	63.46 ± 18.86	65.99 ± 21.47	0.76	61.30 ± 25.46	53.43 ± 17.10	0.17	0.79	0.05
Energy distribution
% Carbohydrate	-	60.21 ± 10.98	62.68 ± 7.55	0.53	63.21 ± 9.10	67.57 ± 7.81	0.06	0.39	0.08
% Protein	-	20.90 ± 6.44	19.85 ± 6.74	0.70	19.02 ± 6.42	16.05 ± 6.23	0.07	0.46	0.09
% Fat	-	14.62 ± 2.82	15.64 ± 2.60	0.37	15.97 ± 3.24	15.53 ± 2.85	0.60	0.22	0.91
Fiber (g)	24.42 ± 9.92	25.55 ± 12.51	25.73 ± 9.10	0.97	25.71 ± 10.43	22.69 ± 8.85	0.25	0.97	0.33
Vitamin A (μg RAE)	257.79 ± 158.50	203.51 ± 140.08	282.16 ± 163.85	0.22	302.30 ± 173.91	241.39 ± 150.32	0.17	0.09	0.45
Vitamin D (μg)	1.64 ± 1.89	2.29 ± 2.48	2.01 ± 1.75	0.76	1.28 ± 1.64	1.50 ± 1.83	0.65	0.16	0.42
Vitamin E (mg)	12.53 ± 6.44	12.56 ± 6.26	15.70 ± 8.22	0.30	13.66 ± 6.83	10.70 ± 5.19	0.07	0.64	0.02
Vitamin C (mg)	74.48 ± 44.89	68.86 ± 50.92	71.35 ± 36.83	0.89	68.14 ± 46.24	81.97 ± 44.84	0.27	0.97	0.48
Thiamine (mg)	1.10 ± 0.40	1.25 ± 0.49	1.14 ± 0.32	0.52	1.12 ± 0.43	1.02 ± 0.35	0.31	0.42	0.31
Riboflavin (mg)	1.25 ± 0.51	1.24 ± 0.44	1.61 ± 0.55	0.08	1.25 ± 0.45	1.14 ± 0.54	0.43	0.93	0.02
Niacin (mg NE)	6.57 ± 3.40	7.20 ± 4.48	7.50 ± 3.23	0.86	6.80 ± 3.15	5.86 ± 3.15	0.28	0.75	0.14
Folic acid (μg DFE)	300.66 ± 149.11	267.62 ± 120.89	379.12 ± 163.33	0.07	307.65 ± 186.80	282.85 ± 120.66	0.55	0.49	0.04
Vitamin B₁₂ (μg)	3.24 ± 5.63	3.10 ± 2.97	3.59 ± 2.45	0.67	2.22 ± 1.90	3.87 ± 8.28	0.36	0.29	0.91
Calcium (mg)	545.87 ± 273.93	585.81 ± 335.29	539.79 ± 209.41	0.70	552.67 ± 224.11	527.63 ± 305.05	0.74	0.73	0.90
Phosphorus (mg)	992.06 ± 315.90	1,079.64 ± 340.97	1,055.69 ± 334.05	0.86	1,030.16 ± 322.02	910.95 ± 290.57	0.16	0.67	0.17
Sodium (mg)	4,451.17 ± 1,965.99	4,578.45 ± 2,038.26	5,135.32 ± 1,578.63	0.47	4,520.27 ± 2,620.29	4,126.92 ± 1,516.42	0.48	0.95	0.06
Potassium (mg)	2,892.98 ± 1,112.79	3,274.20 ± 1,353.47	2,941.71 ± 871.86	0.49	3,027.44 ± 1,234.83	2,636.92 ± 976.37	0.20	0.58	0.36
Magnesium (mg)	297.73 ± 144.27	312.98 ± 143.63	310.71 ± 121.58	0.97	315.88 ± 192.39	275.29 ± 114.85	0.33	0.96	0.39
Iron (mg)	11.06 ± 4.21	11.93 ± 5.16	11.92 ± 4.01	0.99	11.01 ± 4.48	10.47 ± 3.77	0.63	0.58	0.28
Zinc (mg)	6.45 ± 2.95	6.49 ± 2.38	8.00 ± 4.20	0.28	6.75 ± 2.44	5.71 ± 2.87	0.17	0.76	0.04

Variables	Total (n = 79)	Male (n = 24)		P-value¹⁾	Female (n = 55)		P-value²⁾	P-value³⁾	P-value⁴⁾
Variables	Total (n = 79)	Young adults (n = 13)	Older adults (n = 11)	P-value¹⁾	Young adults (n = 22)	Older adults (n = 33)	P-value²⁾	P-value³⁾	P-value⁴⁾
NQ-E score	54.34 ± 12.98	54.98 ± 17.23	51.74 ± 12.58	0.61	58.62 ± 10.86	52.09 ± 12.33	0.05	0.45	0.93
Balance	44.50 ± 16.57	43.29 ± 19.63	42.04 ± 16.41	0.87	49.51 ± 15.83	42.45 ± 15.86	0.11	0.31	0.94
Moderation	52.62 ± 30.48	49.05 ± 41.15	49.41 ± 25.27	0.98	65.43 ± 29.57	46.54 ± 26.40	0.02	0.18	0.75
Practice	70.30 ± 12.96	75.07 ± 14.32	67.65 ± 14.15	0.22	70.99 ± 11.01	68.84 ± 13.28	0.53	0.35	0.80
Grade
Upper grade	28 (35.4)	5 (38.5)	2 (18.2)	0.43	12 (54.5)	9 (27.3)	0.03	0.10	0.75
Moderate grade	33 (41.8)	4 (30.8)	6 (54.5)		9 (40.9)	14 (42.4)
Low grade	18 (22.8)	4 (30.8)	3 (27.3)		1 (4.5)	10 (30.3)
χ² value				0.14			1.56	4.42	0.14

Item	Variables	Male (n = 24)		P-value¹⁾	Female (n = 55)		P-value²⁾	P-value³⁾	P-value⁴⁾
Item	Variables	Young adults (n = 13)	Older adults (n = 11)	P-value¹⁾	Young adults (n = 22)	Older adults (n = 33)	P-value²⁾	P-value³⁾	P-value⁴⁾
Balance (8)	Intake frequency of fruits	30.77 ± 35.58	34.09 ± 23.11	0.79	59.09 ± 35.81	43.94 ± 32.49	0.11	0.03	0.28
	Intake frequency of milk or dairy products	21.15 ± 30.36	25.00 ± 33.54	0.77	34.09 ± 30.42	40.15 ± 37.47	0.51	0.23	0.24
	Intake frequency of fish or shellfish	40.38 ± 19.20	45.45 ± 18.77	0.52	35.23 ± 23.98	37.88 ± 26.61	0.71	0.51	0.31
	Intake frequency of eggs	75.00 ± 32.27	63.64 ± 37.69	0.43	63.64 ± 32.48	52.27 ± 35.56	0.23	0.32	0.37
	Intake frequency of beans or bean products	51.92 ± 36.03	61.36 ± 30.34	0.50	38.64 ± 33.39	49.24 ± 39.27	0.30	0.28	0.36
	Intake frequency of nuts	23.08 ± 34.55	20.45 ± 26.97	0.84	34.09 ± 42.64	11.36 ± 25.84	0.03	0.44	0.32
	Intake frequency of cooked rice with mixed grains	55.77 ± 46.94	29.55 ± 36.77	0.15	72.73 ± 37.72	52.27 ± 45.66	0.08	0.25	0.11
	Intake frequency of water	75.00 ± 30.62	75.00 ± 22.36	≥ 0.99	67.05 ± 23.64	68.18 ± 24.43	0.86	0.39	0.42
Moderation (2)	Intake frequency of sweetened snacks or beverages	46.15 ± 45.47	45.45 ± 29.19	0.96	64.77 ± 33.33	44.70 ± 29.82	0.02	0.17	0.94
Moderation (2)	Intake frequency of greasy baked products or snacks	71.15 ± 35.13	79.55 ± 21.85	0.50	70.45 ± 35.05	60.61 ± 32.49	0.29	0.95	0.08
Practice (7)	Efforts to have healthy eating habits	63.46 ± 26.25	59.09 ± 30.15	0.71	72.73 ± 29.79	60.61 ± 22.56	0.09	0.36	0.86
	Checking of expiration date and nutrition labeling	67.31 ± 35.92	65.91 ± 30.15	0.92	86.36 ± 21.45	66.67 ± 34.04	0.01	0.06	0.95
	Washing hands practices before eating meals	90.38 ± 21.74	86.36 ± 17.19	0.62	97.73 ± 10.66	91.67 ± 18.40	0.13	0.19	0.40
	Difficulty in chewing foods	78.85 ± 26.70	63.64 ± 30.34	0.20	75.00 ± 29.88	62.88 ± 32.55	0.17	0.70	0.95
	Depressive condition	76.92 ± 25.94	65.91 ± 28.00	0.33	62.50 ± 31.58	69.70 ± 30.46	0.40	0.17	0.72
	Degree of sound sleep	75.00 ± 27.00	65.91 ± 23.11	0.39	62.50 ± 32.50	74.24 ± 28.29	0.16	0.25	0.38
	Level of awareness of one’s own health	73.08 ± 16.01	68.18 ± 16.17	0.46	53.41 ± 19.36	59.85 ± 21.60	0.26	0.01	0.19

Variables	Total (n = 79)	NQ-E grade			P-value
Variables	Total (n = 79)	Upper (n = 28)	Moderate (n = 33)	Low (n = 18)	P-value
Energy (kcal)	1,515.63 ± 420.44	1,582.06 ± 385.97	1,508.89 ± 399.68	1,424.66 ± 507.57	0.47
Carbohydrate (g)	241.08 ± 67.45	240.50 ± 60.06	241.53 ± 58.75	241.16 ± 92.98	0.99
Protein (g)	59.01 ± 20.81	65.48 ± 20.91	57.58 ± 20.80	51.15 ± 18.36	0.06
Fat (g)	59.02 ± 20.81	65.34 ± 21.28	57.95 ± 20.59	51.16 ± 18.36	0.07
Fiber (g)	24.42 ± 9.92	28.68 ± 10.00^a	22.05 ± 8.36^c	22.16 ± 10.70^b	0.02
Vitamin A (μg RAE)	257.79 ± 158.50	326.57 ± 152.15^a	245.99 ± 161.39^b	172.45 ± 117.04^c	0.01
Vitamin D (μg)	1.64 ± 1.89	1.04 ± 1.31^a	1.66 ± 1.76^ab	2.54 ± 2.52^b	0.03
Vitamin E (mg)	12.53 ± 6.44	14.12 ± 6.20	12.21 ± 6.73	10.63 ± 5.99	0.19
Vitamin C (mg)	74.48 ± 44.89	84.62 ± 41.12	68.32 ± 47.36	69.99 ± 45.52	0.33
Thiamine (mg)	1.10 ± 0.40	1.24 ± 0.47^a	1.08 ± 0.31^b	0.93 ± 0.34^c	0.02
Riboflavin (mg)	1.25 ± 0.51	1.45 ± 0.42^a	1.22 ± 0.56^b	1.01 ± 0.47^c	0.01
Niacin (mg NE)	6.57 ± 3.40	7.48 ± 3.35^a	6.81 ± 3.43^b	4.71 ± 2.85^c	0.02
Folic acid (μg DFE)	300.66 ± 149.11	350.63 ± 160.02	284.90 ± 135.42	251.82 ± 140.38	0.06
Vitamin B₁₂ (μg)	3.24 ± 5.63	3.73 ± 8.68	2.67 ± 2.28	3.53 ± 3.88	0.75
Calcium (mg)	545.87 ± 273.93	636.46 ± 310.16	484.90 ± 255.08	516.72 ± 217.71	0.08
Phosphorus (mg)	992.06 ± 315.90	1,092.84 ± 270.65	962.29 ± 331.28	889.88 ± 324.72	0.08
Sodium (mg)	4,451.17 ± 1,965.99	4,742.14 ± 2,178.69	4,397.21 ± 1,847.47	4,097.50 ± 1,868.94	0.55
Potassium (mg)	2,892.98 ± 1,112.79	3,351.06 ± 1,219.59^a	2,662.15 ± 891.34^b	2,603.61 ± 1,134.05^c	0.02
Magnesium (mg)	297.73 ± 144.27	358.17 ± 177.60^a	260.58 ± 98.62^c	271.82 ± 132.99^b	0.02
Iron (mg)	11.06 ± 4.21	12.54 ± 4.32	10.42 ± 3.85	9.94 ± 4.25	0.06
Zinc (mg)	6.45 ± 2.95	7.22 ± 2.51	6.48 ± 3.37	5.20 ± 2.44	0.07

Item	Variables	Total (n = 79)	NQ-E grade			P-value
Item	Variables	Total (n = 79)	Upper (n = 28)	Moderate (n = 33)	Low (n = 18)	P-value
Exercise	Do exercise	46 (58.2)	26 (92.9)	17 (51.5)	3 (16.7)	< 0.01
Exercise	Do not exercise	33 (41.8)	2 (7.1)	16 (48.5)	15 (83.3)
Smoking	Yes	8 (10.1)	1 (3.6)	4 (12.1)	3 (16.7)	0.31
Smoking	No	71 (89.9)	27 (96.4)	29 (87.9)	15 (83.3)
Employment	Yes	58 (73.4)	20 (71.4)	26 (78.8)	12 (66.7)	0.62
Employment	No	21 (26.6)	8 (28.6)	7 (21.2)	6 (33.3)
Housemate	With family	49 (62.0)	21 (75.0)	19 (57.6)	9 (50.0)	0.18
Housemate	Alone	30 (38.0)	7 (25.0)	14 (42.4)	9 (50.0)
Change in body weight	Yes	14 (17.7)	3 (10.7)	7 (21.2)	4 (22.2)	0.48
Change in body weight	No	65 (82.3)	25 (89.3)	26 (78.8)	14 (77.8)
Medical history	≥ 1	72 (91.1)	23 (82.1)	31 (93.9)	18 (100)	0.09
Medical history	0	7 (8.9)	5 (17.9)	2 (6.1)	-
Drug	≥ 1	71 (89.9)	25 (89.3)	28 (84.8)	18 (100)	0.25
Drug	0	8 (10.1)	3 (10.7)	5 (15.2)	-
Allergy	≥ 1	4 (5.1)	2 (7.1)	1 (3.0)	1 (5.6)	0.76
Allergy	0	75 (94.9)	26 (92.9)	32 (97.0)	17 (94.4)
Supplement intake	≥ 1	51 (64.6)	22 (78.6)	23 (69.7)	6 (33.3)	0.01
Supplement intake	0	28 (35.4)	6 (21.4)	10 (30.3)	12 (66.7)

Table 1. General characteristics of participants

n (%) or Mean ± SD.

Table 2. Daily nutrient intake in participants by age and sex

Mean ± SD.

μg RAE, micrograms of retinol activity equivalents; mg NE, milligrams of niacin equivalents; μg DFE, micrograms of dietary folate equivalents.

Male group.

Female group.

Young adult male and female groups.

Older adult male and female groups.

Table 3. Comparison of balance, moderation, dietary practice, and NQ-E score across age and sex groups

Mean ± SD.

NQ-E, Nutrition Quotient for the Elderly.

Male group.

Female group.

Young adult male and female groups.

Older adult male and female groups.

Table 4. Comparison of NQ-E scores for each item by age and sex of the participants

Mean ± SD.

NQ-E, Nutrition Quotient for the Elderly.

Male group.

Female group.

Young adult male and female groups.

Older adult male and female groups.

Table 5. Daily nutrient intake based on NQ-E grade in participants

Mean ± SD.

a–c

Different superscript letters within the same row indicate significant differences among groups at P < 0.05 by the Kruskal–Wallis test with Dunn’s post-hoc test.

Table 6. Analysis of NQ-E grade distribution according to general characteristics