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Comparison of Dietary Behaviors and Health-Related Quality of Life of the Elderly Based on Their Household Type in Korea

Joo-Eun Lee*

Department of Food and Nutrition, Seowon University. Cheongju City, South Korea.

Vorresponding Author E-mail: joody88@hanmail.net

DOI : https://dx.doi.org/10.12944/CRNFSJ.12.2.10

Article Publishing History

Received: 07 Apr 2024

Accepted: 14 Jun 2024

Published Online: 27 Jun 2024

Plagiarism Check: Yes

Reviewed by: Krishan Kumar

Second Review by: Amany Salama

Final Approval by: Dr. Reema F. Tayyem

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Abstract:

This study analyzed the raw data from the 2021 National Health and Nutrition Survey conducted annually in Korea to investigate the dietary behavior, nutrient intake, and health-related quality of life of the elderly in the community based on their household type: single-person, couple, or non-couple family household. As a result of the study, based on the household type, significant differences were found in the frequency of breakfast, lunch, and dinner, as well as in the frequency of consuming vegetables and fruits (P<0.05, P<0.01, P<0.001). After analyzing the impact of household type on the depression and happiness levels of the surveyed elderly, it was found that the depression levels of elderly individuals in single-person households were significantly 1.279 times higher, while their feelings of happiness were 0.561 times lower compared to elderly individuals living with their family, including a spouse (P<0.05, P<0.001). In order to enhance the health-related quality of life for elderly individuals living alone with low income and education levels, it is essential to provide systematic management and support activities.

Keywords:

Dietary behavior; Elderly; Nutrient; Quality of life; Single-person household

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Lee J. E. Comparison of Dietary Behaviors and Health-Related Quality of Life of the Elderly Based on Their Household Type in Korea. Nutr Food Sci 2024; 12(2). doi : http://dx.doi.org/10.12944/CRNFSJ.12.2.10


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Lee J. E. Comparison of Dietary Behaviors and Health-Related Quality of Life of the Elderly Based on Their Household Type in Korea. Nutr Food Sci 2024; 12(2). Available from: https://bit.ly/45JnsIn


Introduction 

According to the World Health Organization (WHO), one in six people in the world will be over 60 by 2030. The global population over the age of 60 has increased from 1 billion in 2020 to 1.4 billion in 2022 and is expected to reach 2.1 billion by 2050. In particular, the number of people over the age of 80 is expected to triple to 426 million between 2020 and 2050. Therefore, it can be said that aging is already a global issue.1

Based on the results of the 2023 Census by the National Statistical Office of Korea, the proportion of elderly individuals aged 65 and older out of South Korea’s total population of 51.17 million is 18.2%. The percentage of the elderly population has been steadily increasing from 7.3% in 2000 to 11.3% in 2010, 13.2% in 2015, and 16.4% in 2020.2 Along with this, the proportion of single-person households in Korea is also increasing, accounting for 34.5% of households in 2022, which is a 4.7% increase from 2021. Among them, single-person households in their 60s (16.7%) were the third largest after those in their 20s (18.5%) and 30s (17.3%). Single-person households over the age of 65 accounted for 26.3% of the total number of households, comprising a significant portion of single-person households among the elderly.3 The increase in the elderly population and single-person households is believed to be attributed to the rise in life expectancy resulting from economic growth and advancements in medical technology, as well as the diversification of lifestyles influenced by various factors such as society and culture.4,5

The body’s physiological and pathological conditions change due to aging, which can deteriorate the function of muscles, bones, and teeth. In the case of elderly with multiple dysfunction, their nutritional status can affect immune or cognitive function, leading to poor wound healing and delayed recovery after surgery. Nutrition can affect the aging process, and if the elderly is left alone, many difficulties can arise in maintaining good nutrition. This can lead to indifference towards meals or a worsening appetite, so there is a need for more attention to their nutritional management.4

A study of the elderly has shown that dietary behavior, nutrition, and health status vary depending on their household type. It is said that elderly male in Japan who eat alone are 3.74 times more likely to skip meals than those who eat with others and are more likely to be underweight.5 In addition, elderly female who eat alone consumed less fresh fruit than them who ate together, and their intake of nutrients such as folic acid, total dietary fiber, potassium, and magnesium was significantly lower.6 The inadequate meal intake among elderly individuals who dine alone is significantly linked to their dental health. Moreover, the poorer is their dental health, the greater will be their consumption of protein and polyunsaturated fatty acids.6 In fact, malnourished elderly individuals experience significant issues with chewing compared to their well-nourished counterparts. Therefore, the management of cavities should not be overlooked in healthcare to prevent malnutrition among the elderly.6,7

The dental health problems of the elderly are often linked to malnutrition and acute or chronic diseases, which can lead to physical weakness and ultimately impact their quality of life. At this time, when considering factors related to quality of life (QoL) i.e. body mobility, self-care, daily activities, pain/discomfort, and anxiety/depression were all significantly correlated with oral health.8 Elderly individuals who reside with their families but eat alone are reported to have low awareness of their health conditions, inadequate nutrition, and impaired oral and cognitive functions.9 The nutritional status of the elderly living in the community varies significantly based on their gender, marital cohabitation, level of loneliness, and social support. In addition, the risk of malnutrition increased to 85.7% due to these factors, highlighting the need for management and careful attention to daily life for the nutrition of the elderly.10

Amid the growing interest and significance of promoting healthy living and enhancing the quality of life for the elderly in today’s aging society,11 it is meaningful to compare the dietary habits and health-related quality of life vary according to the type of family, such as single-person households, couples, or non-couple family households of the elderly. living in the community. This study can help to prepare various movements such as social support and institutional supplementation for a healthy life in old age.

Materials and Methods 

This study compared and analyzed whether dietary behavior, nutrition intake, and health-related quality of life vary according to the type of family among the elderly living in the community. The family types considered include single-person households, couples, and non-couple family households. 

Research participants and ethics review

This study analyzed 1,549 elderly male and female aged 65 or older who participated in health checkups, health surveys, and nutrition surveys conducted in 2021 as part of the National Health and Nutrition Survey, which is carried out annually by the Korea Centers for Disease Control and Prevention. Among them, cases with missing values were excluded.

According to the principles of the Helsinki Declaration, the participants were provided with a detailed explanation of the study and were asked to sign a written consent form. The data used in the study verified the researcher’s identity on the Korea Centers for Disease Control and Prevention website, explained the study’s purpose, and obtained the raw data from the National Health and Nutrition Survey. This study was conducted after obtaining approval from the Bioethics Review Committee of the Seowon university (1040820-202304-HR-004-02).

Survey contents

The National Health and Nutrition Survey includes health checkups, health surveys, and nutrition surveys as stipulated in Article 16 of the National Health Promotion Act in Korea.12 Health checkups were conducted in a mobile screening vehicle, while health surveys and nutrition surveys were carried out by an investigator visiting households in person to conduct interviews and surveys. The data used in this study include demographic characteristics such as household type, income, gender, age, and education level of elderly individuals aged 65 or older. In addition, BMI was calculated based on the height and weight measured during the physical examination. Health-related quality of life, mental health, and oral health conditions were identified through a self-administered survey. At this time, Body Mass Index (BMI) was classified according to the standards provided by the World Health Organization (WHO) and explanations specific to Asians.13,14 In the nutrition survey, intake of breakfast, lunch, and dinner, as well as fruits and vegetables, was investigated. Through the 24-hour recall method, nutritional components such as calories, carbohydrates, proteins, fats, vitamins, minerals, and moisture were analyzed based on the food intake from the day before the survey.

Data analysis

In this study, SPSS version 18.0 for Windows (Statistical Package for the Social Sciences, SPSS Inc., Chicago, IL, USA) was used for statistical analysis. The household types of elderly male and female aged 65 or older, who are the participants of this study, were classified into three categories: ‘single-person household’, ‘couple household’, and ‘non-couple family household’. Cross-analysis was conducted to identify differences in the distribution of gender, age, monthly income, education level, and BMI based on household type. In addition, after analyzing the frequency of breakfast, lunch, and dinner, as well as the frequency of fruit and vegetable intake, a cross-analysis was conducted to determine if there were differences in distribution based on household type. The food consumed by elderly male and female the day before the survey was analyzed for nutritional content using a 24-hour recall method. ANOVA was conducted to determine if daily calorie intake and average daily intake of moisture, carbohydrates, protein, omega-3 fatty acid, fiber, calcium, phosphorus, sodium, potassium, zinc, vitamin A, vitamin B group, vitamin C, and vitamin D vary by household type. Cross-analysis was conducted to determine if there is a difference in the distribution of health-related quality of life factors, such as chewing ability, stair climbing, activity ability, pain, memory, sleep habits, stress, depression, and happiness, based on household type. Health-related quality of life scores were adjusted based on gender, age, income, and education level to reduce their impact. After depression and happiness dividing by dichotomy, logistic regression analysis was conducted to assess the influence of activity, work difficulty, stress, pain, memory, sleep patterns, and household type.

Results 

Demographic characteristics of the elderly according to the type of household

Table 1 shows the results of an examination to determine if the demographic characteristics of 1,549 elderly male and female aged 65 or older differ in distribution based on household type. Out of the 1,549 people surveyed, 424 (27.4%) lived in single-person households, 760 (49.1%) were married couples, and 365 (23.6%) were non-couple family households. In terms of gender, 674 (43.5%) were male, and 875 (56.5%) were female. Regarding age, 487 (31.4%) were 65 to 69 years old, 416 (26.9%) 70 to 74, 309 (19.9%) 75 to 79, and 337 (21.8%) were 80 years old or older. In terms of monthly income, 471 people (30.8%) earned less than 1 MW (million won), 431 people (28.1%) earned 1 MW or more but less than 2 MW, 218 people (14.2%) earned 2 MW or more but less than 3 MW, and 410 people (26.8%) earned 3 MW or more. In terms of education level, 615 (44.7%) graduated from elementary school or lower, 282 (20.5%) graduated from middle school, 295 (21.5%) graduated from high school, and 183 (13.3%) graduated from college or higher. In terms of BMI, 43 individuals (3.0%) had a BMI below 18.5, 482 individuals (34.1%) had a BMI between 18.5 and less than 23, 350 individuals (24.8%) had a BMI between 23 and less than 25, 470 individuals (33.3%) had a BMI between 25 and less than 30, and 67 individuals (4.7%) had a BMI of 30 or higher.

As a result of analyzing the distribution according to the family type on the general matters of the survey subjects, there were significant differences in gender, age, monthly income, and education level (P<0.01, P<0.001). The proportion of female was high in single-person households and non-couple family households, and the income was less than 1 million won in single-person households, with the lowest income. In terms of education level, single-person households were most often under graduation from elementary school with low educational level.

Table 1: Demographic characteristics of the elderly based on the type of household.

Characteristics

N (%) Single-person household Couple household Non-couple family household
Gender

Male

674(43.5)1) 95(23.9) 416(55.2)

163(41.0)

Female 875(56.5)1) 302(76.1) 338(44.8)

235(59.0)

χ2-value2) = 104.707

P = 0.000***

Age

65-69

487(31.4) 102(25.7) 238(31.6) 147(36.9)
70-74 416(26.9) 92(23.2) 220(29.2)

104(26.1)

75-79

309(19.9) 89(22.4) 162(21.5) 58(14.6)
≥ 80 337(21.8) 114(28.7) 134(17.8)

89(22.4)

χ2-value = 33.871

P = 0.000***

Average monthly income3)

(MW (million won))

<1 471(30.8) 263(67.6) 159(21.3) 49(12.4)

1≤~<2

431(28.1) 79(20.3) 282(37.9) 70(17.7)
2≤~<3 218(14.2) 30(7.7) 125(16.8)

63(15.9)

≥ 3 410(26.8) 17(4.4) 179(24.0)

214(54.0)

χ2-value = 485.943

P = 0.000***

Education level3)

≤ Elementary school

615(44.7) 187(55.1) 284(41.9) 144(40.8)
Graduated middle school 282(20.5) 57(16.8) 147(21.5)

78(22.1)

Graduated high school

295(21.5) 61(18.0) 153(22.4) 81(22.9)
≥ College 183(13.3) 34(10.1) 99(14.2)

50(14.2)

χ2-value = 26.734

P = 0.001**

BMI3)

<18.5

43(3.0) 8(2.2) 18(2.6) 17(4.7)
18.5≤-<23 482(34.1) 135(36.4) 228(33.5)

119(33.1)

23≤-<25

350(24.8) 94(25.3) 184(27.0) 72(20.0)
25≤-<30 470(33.3) 121(32.6) 215(31.6)

134(37.2)

≥30 67(4.7) 13(3.5) 36(5.3)

18(5.0)

χ2-value = 14.152

P = 0.078
Total 1,549(100.0) 424(100.0) 760(100.0)

365(100.0)

Note: 1)Total is 100%, 2)Chi-square test, 3)Include missing data(no response).

Analysis of dietary behavior by household type 

Table 2 shows the dietary behaviors of the surveyed elderly based on household type. The frequency of breakfast among the elderly surveyed in this study was 1,425 (91.9%) who ate five to seven times a week, followed by 50 (3.4%) who did not eat at all. As for the frequency of lunch, 1,400 people (90.3%) ate lunch five to seven times a week, followed by 67 people (4.3%) who ate three to four times a week. The frequency of dinner was 1,481 people (95.5%) five to seven times a week, followed by 40 people (2.6%) three to four times a week. The frequency of vegetable consumption was as follows: 1,231 people (75.7%) reported consuming vegetables three times a day, 340 people (21.0%) reported consuming them twice a day, and 52 people (3.2%) reported consuming them once a day. The frequency of fruit consumption was as follows: 583 people (35.8%) consumed fruit once a day, 380 people (23.4%) ate fruit 3 to 4 times a week, 206 people (12.7%) consumed fruit 1 to 2 times a week, and 191 people (11.7%) ate fruit 1 to 3 times a month.

After analyzing the distribution of dietary behaviors based on household type, significant differences were found in the frequency of breakfast, lunch, and dinner consumption, as well as in the intake of vegetables and fruits (P<0.05, P<0.01, P<0.001).

Table 2: Dietary behaviors according to the elderly’s household type

Characteristics

N (%) Single-person household Couple household Non-couple family household

Frequency of breakfast for a week

Not at all

50(3.4)1) 11(2.8) 20(2.6)

19(5.5)

1~2 times/week

40(2.6)1) 14(3.3) 11(1.4) 15(4.1)
3~4 times/week 34(2.2)1) 16(3.8) 8(1.1)

10(2.7)

5~7 times/week 1,425(91.9)1) 383(90.1) 721(94.9)

321(87.7)

χ2-value2) = 25.655

P = 0.000***

Frequency of lunch for a week

Not at all

53(3.5) 19(4.7) 24(3.2) 10(3.0)

1~2 times/week

29(1.9) 10(2.4) 13(1.7)

6(1.5)

3~4 times/week 67(4.3) 34(8.0) 20(2.6)

13(3.5)

5~7 times/week

1,400(90.3) 361(84.9) 703(92.5)

336(92.0)

χ2-value = 23.664

P = 0.001**

Frequency of dinner for a week

Not at all

10(0.8) 5(1.4) 3(0.4) 2(0.8)
1~2 times/week 18(1.2) 4(0.9) 8(1.1)

6(1.6)

3~4 times/week

40(2.6) 19(4.5) 13(1.7) 8(2.2)
5~7 times/week 1,481(95.5) 396(93.2) 736(96.8)

349(95.4)

χ2-value = 13.356

P = 0.038*

Frequency of eating vegetables

3~4 times/week

1(0.1) 0(0.0) 0(0.0)

1(0.3)

5~6 times/week

1(0.1) 1(0.2) 0(0.0) 0(0.0)
1 time/day 52(3.2) 23(5.2) 12(1.5)

17(4.3)

2 times/day

340(21.0) 126(28.9) 129(16.2) 85(21.9)
3 times/day 1,231(75.7) 288(65.6) 655(82.3)

288(73.5)

χ2-value = 53.021

P = 0.000***

Frequency of eating fruits

<1 times/month

90(5.8) 41(9.5) 34(4.6) 15(4.0)
2~3 times/month 127(8.2) 45(10.7) 52(7.0)

30(7.9)

1 time/week

197(12.7) 56(13.2) 93(12.3) 48(12.8)
2~4 times/week 363(23.4) 96(22.6) 174(22.9)

93(25.3)

5~6 times/week

51(3.3) 18(4.3) 23(3.0) 10(2.8)
1 time/day 555(35.8) 114(26.9) 308(40.6)

133(36.2)

2 times/day

138(8.9) 43(10.3) 61(8.0) 34(8.9)
3 times/day 28(1.9) 10(2.5) 11(1.6)

7(2.0)

χ2-value = 43.245

P = 0.000***

Total

1,549(100.0) 424(100.0) 760(100.0)

365(100.0)

Note: 1)Total is 100%, 2)Chi-square test, 3)Include missing data(no response)

Nutrient intake among female elderly by household type

Table 3 shows the results of analyzing the average intake of each nutrient per day according to the household type of female elderly people surveyed. The average energy intake of elderly women was 1,370.25 kcal and the water intake was 766.88 g. The average intake of carbohydrates was 231.78 g, and the average intake of protein was 49.07 g. The average intake of omega-3 fatty acids was 1.65 g, and the average intake of dietary fiber was 24.70 g.

Among the mineral intake, the average daily calcium intake of the elderly women was 428.69 mg, 834.69 mg of phosphorus, and 2,451.74 mg of sodium. Potassium was 2,341.42 mg, and iron was consuming an average of 7.43 mg. In terms of vitamin intake, the average daily vitamin A intake of the elderly women was 316.67 μgRE and vitamin D was 2.21 μg. Thiamine was 0.84 mg, riboflavin was 1.07 mg per day, and vitamin C was 60.94 mg.

When comparing the average nutrient intake based on the household type of surveyed elderly female, significant differences in distribution were observed for all nutrients except for vitamin C and D (P<0.05, P<0.01, P<0.001). Female elderly individuals living in single-person households showed significantly lower intake of calcium and vitamin A compared to female elderly individuals in other types of households (P<0.05, P<0.01).

Table 3: Nutrient intake of female elderly according to household type

Total Single-person
household
Couple
household
Non-couple
family
household
P-value1)
Energy

(kcal)

1,370.25
±531.030
1,291.94a2)±489.4773) 1,461.86b2)
±524.361
1,328.44a
±553.171

0.000***

Water(g)

766.88
±481.358
713.66a
±470.698
848.64b
±484.496
717.78a
±474.871
0.000***
Carbohydrate(g) 231.78
±89.421
219.90a
±83.289
246.33b
±88.920
224.74a
±92.248

0.000***

Protein(g)

49.07
±25.770
45.51a
±23.907
53.69b
±27.362
46.69a
±24.624
0.000***
Fat(g) 26.16
±22.150
26.89
±20.160
24.99
±18.165
28.85
±19.321

0.051

n-34)(g)

1.65
±1.973
1.55a
±1.913
1.86b
±2.051
1.49a
±1.916
0.032*
Fiber(g) 24.70±12.902 22.14a
±11.406
27.20b
±12.972
23.85a
±13.384

0.000***

Calcium (mg)

428.69
±275.274
384.41a
±254.416
467.27b
±282.593
419.05ab
±276.806
0.001**
Phosphorus (mg) 834.69
±397.593
763.26a
±365.063
913.94b
±414.758
801.12a
±387.701

0.000***

Sodium (mg)

2,451.74
±1,560.065
2,241.93a
±1,511.543
2,827.55b
±1,837.484
2,201.55a
±1,452.871
0.000***
Potassium (mg) 2,341.42
±1,258.096
2,136.93a
±1,153.996
2,586.12b
±1,250.784
2,226.38a
±1,296.957

0.000***

Iron (mg)

7.43±4.900 6.88a
±4.823
8.23b
±5.191
6.97a
±4.524
0.000***
VitaminA (μgRE) 316.67
±314.998
287.14a
±276.486
350.95b
±363.478
301.19ab
±280.895

0.028*

Thiamine (mg)

0.84
±0.467
0.78a
±0.407
0.91b
±0.481
0.80a
±0.484
0.001**
Riboflavin (mg) 1.07
±0.651
0.96a
±0.576
1.17b
±0.669
1.03a
±0.668

0.000***

Niacin (mg)

8.45
±5.107
7.74a
±4.177
9.27b
±5.601
8.07a
±5.051
0.000***
VitaminD (μg) 2.21
±3.892
1.98
±3.091
2.44
±4.458
2.14
±3.751

0.343

Vitamin C (mg)

60.94
±83.178
54.76
±58.207
67.61
±76.303
58.25
±102.604

0.139

Note: 1)One-Way ANOVA test was used, 2)a,b: different letters mean significant difference between groups by Scheffe’s multiple range test, 3)Mean±SD, 4)n-3:n-3 fatty acid, *P<0.05, ** P <0.01, *** P <0.001.

Nutrient intake among female elderly by household type

Table 4 shows the results of analyzing the average intake of each nutrient per day according to the household type of male elderly. The average energy intake of elderly male was 1,781.97 kcal, and the average daily intake of water was 951.79 g. The daily intake of carbohydrates was 284.74 g, and the average intake of protein was 64.90 g. The average daily intake of omega-3 fatty acids was 1.93 g, and dietary fiber was 29.37 g. In minerals, the daily average intake of calcium was 514.95 mg, and the intake of phosphorus was 1,060.38 mg. The average intake of sodium was 3,420.90 mg, potassium was 2,826.21 mg, and iron was 9.73 mg. The average daily intake of vitamin A was 358.75 μgRE, and vitamin D was 3.08 μg. Thiamine was 1.08 mg, riboflavin 1.37 mg, and vitamin C was 64.30 mg.

When comparing the average intake of nutrients among elderly male surveyed based on household type, significant differences were observed in the intake of water and omega-3 fatty acids (P<0.05, P<0.01). Male elderly in single households showed significantly lower omega-3 fatty acid intake compared to male elderly individuals living in other households (P<0.01).

Table 4: Nutrient intake of male elderly according to household type

Total Single-person household Couple household Non-couple family household P-value1)
Energy

(kcal)

1,781.97
±618.660
1,714.45
±610.3772)
1,795.21
±617.168
1,793.11
±629.449

0.487

Water(g)

951.79
±557.757
824.79a3)
±562.441
979.79b3)
±541.954
956.92a
±590.150
0.039*
Carbohydrate(g) 284.74
±90.725
276.39
±90.530
288.45
±89.762
279.74
±93.531

0.355

Protein(g)

64.90
±32.353
61.40
±30.406
66.20
±31.782
65.41
±35.155
0.455
Fat(g) 35.18
±24.614
32.44
±20.725
37.89
±25.309
34.86
±24.887

0.206

n-34)(g)

1.93
±2.079
1.37a
±1.157
2.28b
±1.921
1.94b
±2.800
0.002**
Fiber(g) 29.37
±13.927
27.04
±13.209
30.12
±13.482
28.79
±15.454

0.109

Calcium (mg)

514.95
±300.464
511.68
±333.075
524.81
±283.334
514.08
±325.884
0.910
Phosphorus (mg) 1,060.38
±466.782
995.57
±501.717
1,072.41
±453.100
1,071.27
±480.509

0.312

Sodium (mg)

3,420.90
±2,039.560
3,550.06
±2,382.582
3,368.72
±1,957.692
3,483.26
±2,028.988
0.656
Potassium (mg) 2,826.21
±1,327.100
2,640.90
±1,415.206
2,888.80
±1,283.272
2,771.75
±1,383.227

0.198

Iron (mg)

9.73±6.663 9.17
±6.231
10.74
±6.201
9.06
±8.066
0.570
VitaminA (μgRE) 358.75

±345.838

299.87
±240.089
388.20
±363.745
367.32
±350.502

0.125

Thiamine (mg)

1.08
±0.603
0.07
±0.747
0.07
±0.553
1.11
±0.635
0.762
Riboflavin (mg) 1.37
±0.765
1.36
±0.784
1.38
±0.744
1.37
±0.813

0.978

Niacin (mg)

11.33
±6.350
10.86
±7.071
11.69
±5.944
11.32
±6.956
0.590
VitaminD (μg) 3.08
±4.958
2.79
±3.675
3.17
±5.336
3.01
±4.590

0.768

Vitamin C (mg)

64.30
±76.479
63.96
±89.410
64.77
±79.940
63.22
±71.837

0.976

Note: 1)One-Way ANOVA test was used, 2Mean±SD, 3)a,b: different letters mean significant difference between groups by Scheffe’s multiple range test, 4)n-3:n-3 fatty acid, *p<0.05, **p<0.01, ***p<0.001.

Health related quality of life according to the elderly’s household type

Table 5 shows the results of analyzing the differences in frequency and distribution of health-related quality of life based on the household type of the surveyed elderly. Of the total 1,549 elderly people surveyed, 715 (46.2%) reported having good chewing ability, 548 (35.3%) reported it as bad, and 286 (18.4%) reported it as moderate. 689 people (44.5%) responded that climbing the stairs was moderate, 498 people (32.1%) reported it as bad, and 362 people (23.4%) reported it as good. The activity level was high for 839 people (54.3%), while 523 people (33.9%) reported a moderate level, and 182 people (11.8%) reported a low level. In terms of pain levels, mild pain was reported by the highest number, with 763 people (49.3%). No pain was experienced by 466 people (30.1%), while severe pain was reported by 320 people (20.7%). In terms of sleep habits, 706 people (45.3%) reported sleeping well, 600 (39.0%) reported it slightly difficult to sleep, and 243 (15.7%) had difficulty falling asleep. In terms of depression, 849 people (54.8%) were not depressed at all, 578 people (37.3%) were slightly depressed, and 122 people (7.9%) were very depressed. As for the feeling of happiness, 797 people (51.6%) said they were always happy, 583 people (37.7%) said they were sometimes happy, and 165 people were not happy.

As a result of analyzing whether there is a difference in the distribution of responses to health-related quality of life according to household type, significant differences were shown in all seven quality of life (P<0.05, P<0.01, P<0.001). Couple households were most likely to report good (or always) chewing ability, activity level, sleep habits, and happiness. And the most common response was that they were not depressed at all. In single-person households, chewing ability and activity level were poor, while extreme pain and poor sleep habits were higher compared to couple or family households. Single-person households had higher rates of depression compared to couple or family households, and their level of happiness was lower.

Table 5: Health related quality of life according to the elderly’s household type

Characteristics

N (%) Single-person household Couple household

Non-couple family household

Chewing ability

Bad

548(35.3)1) 175(41.3) 245(32.2) 128(35.0)
Normal 286(18.4)1) 74(17.4) 145(19.4)

67(18.3)

Good

715(46.2)1) 175(41.3)

370(48.7)

170(46.7)

χ2-value2) = 9.742

P = 0.045*

Climbing stairs

Bad

498(32.1) 136(32.1) 251(33.0)

111(30.4)

Normal

689(44.5) 172(40.6) 357(47.0)

160(43.8)

Good 362(23.4) 116(27.4) 152(20.0)

94(25.8)

χ2-value = 10.549

P = 0.032*

Activity level3)

Low

182(11.8) 69(16.4) 84(11.1) 29(7.9)
Normal 523(33.9) 148(35.2) 232(30.6)

143(39.1)

High

839(54.3) 204(48.5) 441(58.3)

194(53.0)

χ2-value = 22.895

P = 0.000***

Pain

Severe pain

320(20.7) 118(27.8) 127(16.7) 75(20.5)
Mild pain 763(49.3) 179(42.2) 393(51.7)

191(52.3)

No pain 466(30.1) 127(30.0) 240(31.6)

99(27.1)

χ2-value = 23.817

P = 0.000***

Sleeping habits

Difficult to sleep

243(15.7) 85(20.1) 109(14.4)

49(13.6)

Slightly difficult to sleep

600(39.0) 154(36.4) 299(39.4)

149(40.9)

Sleeping well

706(45.3) 185(43.5) 352(46.3)

167(45.5)

χ2-value = 9.696

P = 0.046*

A feeling of depression

Very depressed

122(7.9) 47(11.1) 57(7.5)

18(4.9)

Slightly depressed

578(37.3) 164(38.7) 273(35.8)

142(38.8)

Not depressed at all

849(54.8) 213(50.2) 430(56.7)

205(56.3)

χ2-value = 12.844

P = 0.012*

A feeling of happiness3)

Not happy

165(10.7) 64(15.1) 69(9.3) 31(8.5)
Sometimes 583(37.7) 165(39.0) 283(37.6)

134(36.6)

Always happy

797(51.6) 194(45.9) 403(53.1)

188(51.9)

χ2-value = 15.099

P = 0.005**

Total

1,549(100.0) 424(100.0) 760(100.0)

365(100.0)

Note: 1)Total is 100%, 2)Chi-square test, 3)Include missing data(no response). 

The effect of health-related quality of life on depression and happiness

Table 6 shows the results of logistic regression analysis after dichotomizing depression and happiness to assess the influence of health-related quality of life and household types on the depression and happiness levels of the surveyed elderly. As stress, pain, and difficulty in working increased, depression also significantly increased by 3.611 times, 1.595 times, and 1.467 times, respectively (P < 0.001). As activity level, memory, and sleep habits deteriorated, depression increased significantly to 1.320 times, 1.609 times, and 1.847 times (P<0.01, P<0.001). Happiness significantly decreased by 0.574 times as stress increased (p<0.001), and decreased by 0.410 times, 0.516 times, and 0.690 times as activity level, sleep habits, and chewing ability deteriorated (P<0.001). The depression levels among elderly in single-person households was 1.279 times higher than that of the elderly living with their families, including couples, while the feeling of happiness was 0.561 times lower (P<0.05, P<0.001). 

Table 6: The effect of health-related quality of life and household type on depression and happiness

Variables1)

Adjusted

OR2)

95% CI2)

P-value

<Depression>

Stress

No 1

Yes

3.611 2.950-4.419

0.000***

Pain

No 1
Yes 1.595 1.303-1.952

0.000***

Activity level

High 1
Low 1.320 1.093-1.595

0.004**

Difficulty of work

No 1
Yes 1.467 1.198-1.797

0.000***

Memory

Good 1
Bad 1.609 1.300-1.99

0.000***

Sleeping habits

Good 1
Bad 1.847 1.547-2.205

0.000***

Family type

Non-single 1
Single 1.279 1.034-1.581

0.023*

<Happiness>

Stress

No 1
Yes 0.574 0.443-0.745

0.000***

Activity level

High

1
Low 0.410 0.318-0.527

0.000***

Sleeping habits

Good

1
Bad 0.516 0.405-0.659

0.000***

Chewing ability

Good 1
Bad 0.690 0.567-0.840

0.000***

Family type

Non-single 1
Single 0.561 0.411-0.765

0.000***

1)Display only significant variables. 2)OR and 95% CI was calculated by using adjusted factors (gender, age, household income, education).

Discussion

In this study, we analyzed the results of the 2021 National Health and Nutrition Survey and compared how dietary behavior, nutrition intake, and health-related quality of life vary depending on the household type of the elderly in the community. Out of the 1,549 male and female elderly surveyed, 27.4% lived in single-person households, with a significantly higher proportion of females in this category. In the case of elderly male, the proportion of family household, including couples, was higher than that of single-person households. Elderly in single-person households tended to have lower income and education levels compared to those living with their families. It is said that elderly people living alone for various reasons, such as bereavement or divorce, can experience economic difficulties and social isolation. They are also more likely to be exposed to malnutrition and chronic diseases.15-17 Malnutrition or physical illness can adversely affect an individual’s mental health, leading to reduced satisfaction with social relationships and the surrounding environment, ultimately resulting in a poor quality of life.18,19 Considering the demographic characteristics of the elderly by household type, social support should be provided for poor single-person households.

As per the dietary behavior survey based on household type, couple households showed a higher intake of breakfast, lunch, and dinner compared to single-person families or non-couple family households. In addition, the frequency of vegetable and fruit consumption in single-person households was lower than that in family households, including couples. It is said that elderly male and female living alone in Japan not only often eat alone, but also consume fewer vegetables and fruits, and are more likely to skip meals.5 In this study, 18% of the elderly who participated in the Oklahoma Older Americans Act Nutrition Program (OANP) in the United States were classified as being at high nutritional risk, and eating alone as the primary reason was reported in more than 50% of them. Elderly individuals who live alone often eat by themselves and consume fewer vegetables, fruits, and dairy products compared with them living together.20 In a cohort study of male and female in their 50s and older in 10 European countries, unmarried women or widows without spouses were found to consume a limited variety and quantity of vegetables and fruits. It is said that social contact with friends and others has a significant impact on this. In addition, it has been reported that male elderly individuals living alone had significantly lower diversity and intake of vegetables.21 According to two cohort studies conducted at Japanese health centers, the risk of cardiovascular disease decreased significantly by 0.81 times with increased fruit intake compared to vegetables.22 A cohort study in the United States reported that the higher the consumption of fruits and vegetables, the more significantly cardiovascular disease decreased by 0.88 times. Among them, the intake of green leafy vegetables had the most pronounced effect.23 In this way, meal skipping or eating alone in single-person households can be linked to nutritional problems. Particularly, the varied consumption of vegetables and fruits was closely associated with chronic diseases such as cardiovascular diseases in both Eastern and Western cultures.24 Therefore, nutrition management tailored to the growing elderly population will be necessary. This can be achieved by identifying elderly individuals who live alone or skip meals, and encouraging them to consume a variety of foods, including vegetables and fruits.

In this study, the analysis of nutritional intake of elderly male and female showed that couple households had higher daily intake of calories, carbohydrates, proteins, omega-3 fatty acid, moisture, fiber, calcium, phosphorus, sodium, potassium, iron, minerals, and vitamins A, B, C, and D than single-person households or non-couple family households. This phenomenon was significant in most nutrients (excluding vitamins C and D) for elderly female, while male elderly only showed significance in moisture and omega-3 fatty acid. In terms of nutrient intake, elderly male and female living in single-person households consumed a smaller amount of nutrients compared to those in other households. Compared to ‘the 2020 Dietary Reference Intakes for Koreans’, the nutrients lacking were calories, water, calcium, potassium, A, C, and D for both male and female elderly per day, and sodium was excessive.25 A study of elderly individuals over 60 years of age living alone revealed insufficient total energy and calcium intake in both male and female. In particular, their physical health is closely related to the decrease in the intake of vitamins A and C.26 A three-year follow-up study of individuals aged 60 or older living in the community found that the daily intake of calories, carbohydrates, proteins, fats, and fiber among socially vulnerable elderly males, such as those living alone, was significantly lower than that of elderly females or socially stable elderly males.27 Elderly individuals living alone often dine by themselves, and the older they get, the less inclined they are to purchase groceries or prepare meals.18,21 It can be challenging for older individuals to consume a diverse range of foods due to several reasons. Taking Asian table setting as an example, if the elderly is unable to eat balanced meals such as “staple foods (grains), main dishes (protein foods such as fish, lean meat, eggs, beans, etc.), and side dishes (vegetables)”, there is a greater likelihood of a lack of nutrient intake. In particular, Asian elderly individuals with traditional eating habits, who primarily consume grains, may tend to focus their daily calorie intake on carbohydrates. This lowers the intake rate of protein and fat, and consequently, the intake of vitamins and minerals can also decrease.28 Therefore, it is necessary to plan and promote ways to encourage the elderly in single-person households to consume a variety of foods to prevent nutritional imbalances.

As a result of analyzing the difference in quality of life distribution based on the household type in this study, elderly individuals living with couples exhibited high levels of chewing ability, activity level, sleep habits, and happiness, and low levels of depression. On the other hand, the elderly living in single-person households exhibited low chewing ability and activity levels. There were more cases of extreme pain and poor sleep habits among the elderly living alone compared to those living with family members or couples. Furthermore, elderly individuals living alone experienced high levels of depression and low levels of happiness. In addition to gender, age, income, and education level, the presence or absence of cohabiting families, including spouses, has a significant impact on the quality of daily life for the elderly.29 However, aside from these demographic characteristics, it is true that physical health factors, such as frailty, also have a significant influence on the quality of life of the elderly.30 In this study, physical pain, activity level, difficulty working, memory, and sleep habits have a significant effect on depression and happiness. Especially, dental health become a prerequisite for eating food and is closely related to the nutritional intake of the elderly. It is important to keep in mind that dental health care should be prioritized for the elderly to promote healthy eating habits and ensure a happy life.7 To enhance the health-related quality of life for elderly individuals living alone, it appears crucial to systematically support overall nutrition management and daily routine.

Conclusion

This study investigated how the elderly’s dietary behavior, nutrient intake, and health-related quality of life vary depending on the type of single-person household, couple or family living together. Single-person households had the lowest consumption of vegetables and fruits. Elderly female living alone had significantly lower calcium and vitamin A intake, while elderly male in single households had significantly lower omega-3 fatty acid intake. Single-person households experienced higher levels of depression compared to other types of households, and their overall happiness was lower. It is necessary to recognize that elderly individuals living alone may have inadequate meals and nutrition, which can lead to a decline in health-related quality of life and happiness. Therefore, appropriate support and management should be provided. This study is limited in its analysis of dietary behavior, nutrient intake, and health-related quality of life due to the use of generalized data from the annual National Health and Nutrition Survey conducted in Korea. In future studies, there is a need for research that thoroughly examines the internal and external factors influencing eating behavior and quality of life among the elderly in specific regions or particular population groups.

Acknowledgement

The author acknowledges the help re­ceived from the scholars whose articles are cited and in­cluded in references of this manuscript. The author is also grateful to authors / editors / publishers of all those articles, journals and books from where the literature for this article has been reviewed and discussed.

Funding Sources

The author received no financial support for the research, authorship, and/or publication of this article.

Conflict of Interest

The author declares no conflict of interest.

Data availability

The manuscript incorporates all datasets produced or examined throughout this research study.

Ethics statement

The document accurately and thoroughly presents the authors&#39; original research and analysis.

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