Prediction Model for Identifying a High-Risk Group for Food Insecurity among Elderly South Koreans

doi:10.21203/rs.3.rs-4962048/v1

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Prediction Model for Identifying a High-Risk Group for Food Insecurity among Elderly South Koreans

https://doi.org/10.21203/rs.3.rs-4962048/v1

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This study aimed to identify the highest risk group for food insecurity in elderly South Koreans. A cross-sectional study was conducted using data from the 2022 Korea Community Health Survey. Subjects were divided into four groups; A: Sufficient quantity and variety of food, B: Sufficient quantity but not variety of food, C: Sometimes insufficient quantity and variety of food, and D: Often insufficient quantity and variety of food. Decision tree analysis was conducted to build a prediction model of food insecurity. Individuals who were not receiving basic livelihood assistance, were living with a family member, and had a diploma beyond college level were the highest proportion (75.8%) in Group A. For Group B, those who were not receiving basic livelihood assistance, were living alone, and had depression were the highest proportion (49.4%). In Group C, those who were receiving basic livelihood assistance, had no depression, and were living alone were the highest proportion (44.2%). Finally, those who were basic livelihood assistance, showed depression, and were living alone were the highest proportion of Group D (14.3%). The food insecurity of the elderly in South Korea is associated with basic livelihood assistance, depression, education level, and household type.

Health sciences/Health care

Health sciences/Risk factors

Food insecurity

Aged

Decision tree

Community Health Survey

Food insecurity is a state where people have inadequate access to nutritious food due to financial constraints (1). In other words, food insecurity can be defined as, when participants reported that their family sometimes or often did not receive enough food to eat, in the past year (2, 3). Increasing uncertainty around stable food supply due to global pandemics and natural disasters is exacerbating nutritional disparities across age, regions, and socioeconomic status, in an aspect as fundamental to life as food (4, 5).

Food insecurity is reported as the main cause threatening a healthy life. It not only leads to chronic diseases, such as obesity, diabetes, and high blood pressure but also has negative impact on mental health, such as depression and low self-esteem. Additionally, it is found to have a significant effect on social health, including low life satisfaction and experience of domestic violence (6, 7).

It is particularly dangerous for individuals aged 60 years and above as it increases the risk of severe health problems (8). It has been observed that the number of elderly people facing food insecurity in the U.S. has increased from 2.3 million to 5.3 million, since 2001, and is expected to rise to 8 million by 2050 due population growth (9). The issue of food security still remains a crucial concern for many underdeveloped and developing nations worldwide (10). Even in many advanced nations, poverty and hunger continue to affect socio-economically disadvantaged people (11). Other studies found that people experiencing food insecurity are at higher risk of chronic illnesses, mental health issues, physical limitations (12–14), a lower intake of nutrients, and less food diversity (14).

According to a recent survey, approximately 5% of elderly people in South Korea cannot afford to buy the food they want due to economic difficulties, leading to food insecurity (15). In particular, the proportion of single elderly households in the food insecurity groups are almost five times higher than that in the food-secure group (15). However, studies on food insecurity among elderly people in South Korea are rare. Hence, there is insufficient information on factors related to food insecurity among elderly people in South Korea. A study was conducted to examine the relationship between health-related lifestyle habits, nutrient intake statistics, and the occurrence of food insecurity among people aged 65 years or older (16). This study found that there were significant differences in the rate of food insecurity, based on sex, education level, living alone, and household composition including the presence of children. In addition, the group that experienced food insecurity was found to have mental health problems and nutritional deficiencies.

Food insecurity is a serious problem among elderly people in South Korea. However, only a study has mentioned it so far (17). Therefore, to address this issue, it is crucial to identify the groups that are at high-risk of experiencing food insecurity. This study aimed to use decision tree analysis to determine the high-risk group for food insecurity among elderly people in South Korea.

This study was conducted to explore and compare general characteristics and health-related characteristics between four groups according to food security; 1) Group A : Sufficient quantity and variety of food, 2) Group B : Sufficient quantity but not sufficient variety of food, 3) Group C: Sometimes insufficient quantity and variety of food, and 4) Group D: Often insufficient quantity and variety of food. Also, this study attempted to identify the high-risk group for food insecurity of elderly people in South Korea. The specific aims are as follows:

1) To compare general characteristics between the four groups.

2) To compare health-related characteristics between the four groups.

3) To build a prediction model of food security in the elderly.

4) To test validation of the prediction model of food security in the elderly.

2.1 Study design

This was a cross sectional study using secondary data from the 2022 Community Health Survey (CHS) provided by the Korea Disease Control and Prevention Agency(KDCA).

2.2 Study data and participants

The subjects of the 2022 CHS were adults aged 19 years or older. To gather data, the KDCA enlists surveyors from all over the country. Data were collected from August 16 to October 31, 2022 by trained interviewers. The trained interviewers visited the households selected as samples and conducted a 1:1 interview using computer-assisted personal interviewing. From the 2022 CHS, there were 79,441 persons 65 years of age and older. Among them, those who did not answer a question about food security (n = 40) were excluded. The final number of participants was 79,401.

2.3 Measures

1) Food security

Food security was surveyed using a single question, “Which of the following most accurately describes your family’s food situation during the past year?” The following four responses were provided, and respondents were categorized into four groups according to the answers: 1) “There was sufficient food in terms of quantity and variety available for all household members in my family” (Group A), 2) “There was sufficient food in terms of quantity but limited variety available for all household members in my family” (Group B), 3) ”There was occasional food shortage due to lack of resources” (Group C), and 4) “There was frequent food shortage due to lack of resources” (Group D) (14).

2) Socio-demographic characteristics

Socio-demographic characteristics included age (young-old, old-old, oldest-old), sex (male, female), marital status (single, married), education level (≤ high school graduate, ≥college graduate), economic activity(working for more than 1 hour to earn income in the past week) (yes, no), residence area (city, province), household type (single, other), basic livelihood recipients (yes, no), household income (< 10,000won/month, ≥ 10,000won/month), household income changed by COVID-19 (decreased, no change, increased), life-satisfaction (low (1–5), high (6–10), quality of life (bad, good).

Age was divided into three groups; 1) young-old (65–74 years), 2) old—old (75–84), and 3) oldest-old (85 or older) (18). Life-satisfaction ranged from 1 to 10, with scores of 1–5 assigned to the low group and scores of 6–10 assigned to the high group. Quality of life was measured by EQ-5D. The EQ-5D index was calculated based on the Korean Centers for Disease Control and Prevention recommendation (19). Subjects who scored less than 50% of the EQ-5D were assigned to the ‘bad group’ and those exceeding 50% were assigned to the ‘good group’.

3) Health-related characteristics

Health-related characteristics include Body Mass Index (BMI, kg/m²) (underweight, normal, overweight, obese), drinking alcohol (yes, no), frequency of drinking (none, < 1/month, 1/month, 2–4/month, 2–3/week, 4/week), amount of drinking (at once) (1–2 cups, 3–4 cups, 5–6 cups, 7–9 cups, ≥ 10 cups), frequency of breakfast (None, 1–2/week, 3–4/week, 5–7/week), recognition of nutrition label (yes, no), interpretation of nutrition label (yes, no), use of nutrition label (yes, no), oral health status (bad, average, good), chewing (bad, average, good), experience of cognition dysfunction (yes, no), depression (PHQ-9) (yes, no), and subjective health status (bad, average, good).

BMI was calculated as weight (kg) divided by the height squared (m). Subjects were divided into four groups according to BMI, 1) underweight (< 18.5), 2) normal (18.5–24.9), 3) overweight (25.0-29.9), and obese (30 or higher)(20). Depression was assessed using the nine-item Patient Health Questionnaire (PHQ-9). A score of 10 or higher indicates depression (21).

2.4 Ethical Considerations

This study used secondary data provided by the Korea Disease Control and Prevention Agency. Therefore, this study was conducted with IRB exemption from the Institutional Review Board of the author (IRB No. 1041495-202403-HR-02-01).

2.5 Statistical analysis

This study used SPSS version 29.0 (SPSS Inc., Chicago, IL, USA) to analyze the data. To compare general and health-related characteristics, one-way analysis of variance (ANOVA) and chi-squared tests were used. Decision tree analysis was conducted to build a prediction model to verify the high-risk group of food insecurity in the elderly. A split-sample test was used to identify validation of the final decision tree model.

3.1 General characteristics

The results of comparison between the four groups according to status of food security are presented in Table 1. There were significant differences in age, sex, marital status, education level, economic activity, residence area, household type, basic livelihood recipients, household income, household income changes compared the previous year, subjective health status, life satisfaction, and quality of life between the four groups.

For Group A, the young-old group accounted for the highest proportion (60.2%). The oldest-old group accounted for the highest proportion in Group D (15.9%). Over 50% were female and lived provincially, for all groups (p < .001). For each group, most subjects were married(p < .001). All four groups showed a higher proportion of individuals with education levels below high school graduation compared to those with a college degree or higher (p < .001). Group D had the highest percentage of below high school graduation (97.1%) (p < .001). Group A had the highest rate of economic activity (45.4%), and Group D had the highest proportion of people who were not economically active (81.2%) (p < .001). More than 80% of subjects in Group A lived with family members, whereas, 54.6% of subjects in Group D lived alone (p < .001). Group D had the highest proportion of basic livelihood recipients at 36.7% (p < .001). Group A had the highest monthly income with a mean of 262.3 million won (p < .001). The life satisfaction score of six or more was highest in Group A at 64.4%, and lowest in Group D at 22.1% (p < .001). For quality of life, 68.8% in Group A had a good quality of life, however, 70.7% of Group D had a bad quality of life (p < .001).

Table 1

Comparison of General characteristics (N = 79,401)
Characteristics	Categories	A group (n = 39,207, 49.4)	B group (n = 32,747, 41.2)	C group (n = 6,404, 8.1)	D group (n = 1,043, 1.3)	p-value
Characteristics	Categories	N(%) or M ± SD				p-value
Age	Young-old (65–74)	23615(60.2)	16229(49.6)	2727(42.6)	436(41.8)	< .001
	Old-old (75–84)	12564(32)	12911(39.4)	2782(43.4)	441(42.3)
	Oldest-old (≥ 85)	3028(7.7)	3607(11)	895(14)	166(15.9)
Sex	Male	18000(45.9)	13252(40.5)	2310(36.1)	384(36.8)	< .001
Sex	Female	21207(54.1)	19495(59.5)	4094(63.9)	659(63.2)	< .001
Marital status	Single	184(0.5)	234(0.7)	125(2)	30(2.9)	< .001
Marital status	Married	39018(99.5)	32511(99.3)	6277(98.0)	1012(97.1)	< .001
Education level	≤High school	33863(86.4)	30938(94.5)	6201(96.8)	1013(97.1)	< .001
Education level	≥College graduate	5344(13.6)	1809(5.5)	203(3.2)	30(2.9)	< .001
Economic activity	Yes	17803(45.4)	13151(40.2)	1745(27.2)	196(18.8)	< .001
Economic activity	No	21403(54.6)	19595(59.8)	2659(72.8)	847(81.2)	< .001
Residence area	City	16957(43.2)	13737(41.9)	3035(47.4)	3035(47.4)	< .001
Residence area	Province	22250(56.8)	19010(58.1)	3369(52.6)	3369(52.6)	< .001
Household type	Single	7248(18.5)	10043(30.7)	3132(48.9)	569(54.6)	< .001
Household type	Other	31959(81.5)	22704(69.3)	3272(51.1)	474(45.4)	< .001
Basic livelihood recipients	Yes	947(2.4)	2806(8.6)	1771(27.7)	383(36.7)	< .001
Basic livelihood recipients	No	38251(97.6)	29937(91.4)	4632(72.3)	660(63.3)	< .001
Household income (10,000won, month)		262.3 ± 237.5	145.1 ± 131.5	82.2 ± 60.9	68.5 ± 48.6	< .001
Household income changes by COVID-19	Decrease	8645(22.1)	8263(25.3)	1625(25.4)	285(27.3)	< .001
	No change	28036(71.5)	23170(70.8)	4561(71.2)	706(67.7)
	Increase	2509(6.4)	1288(3.9)	218(3.4)	52(5.0)
Life satisfaction	Low (0–5)	13975(35.6)	17391(53.1)	4433(69.2)	812(77.9)	< .001
Life satisfaction	High(6–10)	25232(64.4)	15356(46.9)	1971(30.8)	231(22.1)	< .001
Quality of life	Bad(< 50%)	12231(31.2)	14856(45.4)	3940(61.5)	730(70)	< .001
Quality of life	Good(≥ 50%)	26976(68.8)	17891(54.6)	2464(38.5)	313(30)	< .001

3.2 Comparison of Health-related Characteristics

Comparison of health-related characteristics between the four groups are shown in Table 2. There were significant differences in BMI, drinking alcohol, frequency of drinking, quantity of drinking, frequency of breakfast, recognition of nutrition label, interpretation of nutrition label, use of nutrition label, oral health status, chewing, experience of cognitive dysfunction, depression, use of health facilities, and health status between the four groups.

Greater than 50% of subjects had normal BMI for all groups (p < .001). The proportion of subjects drinking alcohol (68.9%) was the highest in Group A (p < .001). Approximately 50% of subjects from all groups drink 1–2 cups of alcohol at once (p < .001). The majority of subjects in the four groups have breakfast 3–4 times per week (p < .001). The proportion of subjects who recognize, interpret, and use the nutrition label was highest in Group A (p < .001). Group D had the highest rate of bad oral health (68.7%) and chewing (62.2%) (p < .001). Group A had the highest rate of good oral health (22.2%) (p < .001). Group B showed the highest rate of good condition in chewing (39.6%) (p < .001). Almost 50% of subjects in Group D experienced cognitive dysfunction (49.9%) and did not use health facilities (56%) (p < .001). The highest proportion of depression (24.3%) and bad health status (66.9%) was in Group D (p < .001).

Table 2

Health related characteristics
Characteristics	Categories	A group (n = 39207, 49.4)	B group (n = 32747, 41.2)	C group (n = 6404, 8.1)	D group (n = 1043, 1.3)	p-value
Characteristics	Categories	N(%) or M ± SD				p-value
Body Mass Index (kg/m²)	Underweight	1552(4.1)	1797(5.8)	455(7.4)	78(7.8)	< .001
	Normal	26016(68.2)	21480(68.3)	4103(66.9)	669(66.7)
	Overweight	9733(25.5)	7439(23.6)	1402(22.9)	231(23.0)
	Obesity	867(2.3)	753(2.4)	169(2.8)	25(2.5)
Drinking alcohol	Yes	27026(68.9)	21560(65.8)	3985(62.2)	636(61)	< .001
Drinking alcohol	No	12180(31.1)	11187(34.2)	2419(37.8)	407(39)	< .001
Frequency of drinking	None	10736(39.7)	10112(19)	2124(53.3)	375(59)	< .001
	< 1/month	4669(17.3)	3593(16.7)	639(16)	82(12.9)
	1/month	2338(8.7)	1637(7.6)	280(7)	34(5.3)
	2–4/month	3803(14.1)	2436(11.3)	346(8.7)	63(9.9)
	2–3/week	2984(11)	1892(8.8)	312(7.8)	39(6.1)
	4/week	2496(9.2)	1890(8.8)	284(7.1)	43(6.8)
Amount of drinking	1-2cups	8304(51)	6157(53.8)	986(53)	114(43.7)	< .001
	3-4cups	3683(22.6)	2584(22.6)	402(21.6)	66(25.3)
	5-6cups	1383(8.5)	916(8)	137(7.4)	19(7.3)
	7-9cups	2202(13.5)	1399(12.2)	256(13.8)	45(17.2)
	≥ 10cups	718(4.4)	392(3.4)	80(4.3)	17(6.5)
Frequency of breakfast	None	409(1)	469(1.4)	157(2.5)	32(3.1)	< .001
	1–2/week	934(2.4)	1077(3.3)	297(4.6)	59(5.7)
	3–4/week	36433(92.9)	29943(91.4)	5605(87.5)	860(82.5)
	5–7/week	1430(3.6)	1258(3.8)	344(5.4)	92(8.8)
Recognition of nutrition label	Yes	15632(40)	9695(29.7)	1428(22.4)	207(19.9)	< .001
Recognition of nutrition label	No	23473(60)	22926(70.3)	4954(77.6)	835(80.1)	< .001
Interpretation of nutrition label	Yes	5599(35.8)	3019(31.1)	474(33.2)	64(30.9)	< .001
Interpretation of nutrition label	No	10030(64.2)	6673(68.9)	954(66.8)	143(69.1)	< .001
Use of nutrition label	Yes	4447(79.5)	2259(74.9)	346(73)	48(76.2)	< .001
Use of nutrition label	No	1149(20.5)	758(25.1)	128(27)	15(23.8)	< .001
Oral health status	Bad	16207(41.3)	17451(53.3)	4201(65.6)	717(68.7)	< .001
	Average	14283(36.4)	10552(32.2)	1568(24.5)	242(23.2)
	Good	8716(22.2)	4743(14.5)	634(9.9)	84(8.1)
Chewing	Bad	22267(56.8)	13749(42)	1882(29.4)	242(23.2)	< .001
	Average	6412(16.4)	6028(18.4)	1042(16.3)	152(14.6)
	Good	10528(26.9)	12969(39.6)	3480(54.3)	649(62.2)
Experience of cognitive dysfunction	Yes	12314(31.4)	12646(38.6)	3186(49.8)	520(49.9)	< .001
Experience of cognitive dysfunction	No	26883(68.6)	20091(61.4)	3211(50.2)	522(50.1)	< .001
Depression (PHQ-9, score 10)	Yes	1128(2.9)	1897(5.8)	865(13.6)	252(24.3)	< .001
Depression (PHQ-9, score 10)	No	37977(97.1)	30682(94.2)	5498(86.4)	783(75.7)	< .001
Use of health facilities	Yes	20057(51.2)	17181(52.5)	3049(47.6)	458(44)	< .001
Use of health facilities	No	19145(48.8)	15560(47.5)	3354(52.4)	584(56)	< .001
Subjective health status	Bad	10988(28)	13677(41.8)	3720(58.1)	698(66.9)	< .001
	Average	16144(41.2)	12512(38.2)	1881(29.4)	238(22.8)
	Good	12074(30.8)	6558(20)	803(12.5)	107(10.3)

3.3 Prediction model of food security

A prediction model of food security in elderly Korean people is shown in Fig. 1. There was a significant difference in food security of elderly Korean people according to whether they were basic livelihood recipients (Chi-square = 6597, p < .001). For those who were no basic livelihood recipients (Node 1), household type affected food security (Chi-square = 2445, p < .001). For those living with other family members (Node 3), there was a significant difference in food security according to education level (Chi-square = 1069, p < .001). The proportion of food security for single people (Node 4) was different based on the presence or absence of depression (Chi-square = 491, p < .001).

The proportion of food security in basic livelihood recipients (Node 2) was different based on the presence or absence of depression (Chi-square = 170, p < .001). For those who had no depression (Node 5), the proportion of food security was affected by experience of cognitive dysfunction (Chi-square = 47, p < .001). For those who showed depression (Node 6), household type affected food security (Chi-square = 11, p < .001).

In the final prediction model, for Group A, those who were not basic livelihood recipients, lived with a family member, and were at least college graduates had the highest proportion of food security (75.8%). However, those who were basic livelihood recipients, had depression, and lived alone had the lowest proportion of food security (6.5%). Those in Group B group who were not basic livelihood recipients, lived alone, and had depression showed the highest proportion of food security (49.4%). Conversely, those who were not basic livelihood recipients, lived with family members, and were at least college graduates showed the lowest proportion of food security (22.7%). Those in Group C, those who were basic livelihood recipients, had no depression, and lived alone showed the highest proportion of food security (44.2%). However, those who were not basic livelihood recipients, lived with family members, and were at least college graduates had the lowest proportion of food security (1.3%). For Group D, those who were not basic livelihood recipients, lived with family members, and had a diploma above a college graduate had the lowest proportion of food security (0.1%). In contrast, those who were basic livelihood recipients, had depression, and lived alone showed the highest proportion of food security(14.3%).

3.4 Validation of prediction model

To determine the validity of the prediction model, a split sample test was conducted. The results of validity testing are presented in Table 3. The risk estimate of the test data was 0.45. This result was not significantly different to the result from the training data (0.46). This means that the precision of classification can be assumed to be 54%. This result shows that the prediction model of this study showed high generalizability.

Table 3

Validation of prediction model
Method	Method	Risk Estimate	Standard Error
Split-sample test	Training	.45	.002
Split-sample test	Test	.46	.002

Food security encompasses the concepts of usefulness, accessibility, and utility of food, meaning that society always has sufficient and safe quality food available in a socially acceptable manner to allow the pursuit of a vibrant and healthy life (22, 23). However, research on food security for elderly people in South Korea is inadequate. Therefore, this study was conducted to explore food security for elderly people in South Korea, and to establish a predictive model to identify high-risk groups for food insecurity, using 2022 Community Health Survey data.

From this study, it was found that those who were not basic livelihood recipients, lived with family member, and had a diploma above a college graduate are most likely to have a sufficient quantity and variety of food. In contrast, those who were basic livelihood recipients, had depression, and lived alone were most likely to not have a sufficient quantity and variety of food.

A previous study found that a low education level can lead to food insecurity in elderly people (24). However, continuous education can help individuals escape food insecurity, even for those with low academic achievement. Studies have shown that education programs for managing food insecurity have had positive outcomes, even for non-elderly people (25, 26). One study specifically developed an education program that provided food selection and food resource management skills, resulting in a decrease in the risk of food insecurity (25). However, there is currently no education program for elderly individuals experiencing food insecurity in South Korea. Effective education programs for the elderly should be developed following suggestions from previous studies. It was suggested that program delivery methods and socio-demographic characteristics of the subjects should be considered in order to provide effective education.

The Ministry of Health and Welfare in South Korea has made significant efforts to expand basic livelihood security to support those in need. However, it is important to assess whether the support provided is sufficient for recipients to obtain sufficient and varied food for their health. The result of this study shows that basic livelihood recipients were the most affected by food insecurity. Despite receiving government economic benefits, many still face food insecurity. Therefore, the support range should be adjusted periodically, considering social and economic circumstances. Additionally, continuous monitoring is required to ensure a healthy diet.

Another study reported that living alone can result in poor dietary intake, including insufficient food or a lack of variety in the diet (28). In South Korea, the number of elderly people who live alone is continually increasing. Therefore, it is crucial for community health providers to investigate and address food insecurity among the elderly who live alone.

Similar to the results of this study, a previous study found that food insecurity is significantly affected by depression in the elderly(28). Conversely, another study found that food insecurity in the elderly contributed to depression (29). It has also been shown that food insecurity is significantly related to more severe depressive symptoms (30). The results of these studies show that further studies are required to establish a clear causal relationship between food security and depression. Furthermore, supplying nutrient-efficient food and providing nutritional education with a focus on mental health recovery for food-insecure elderly people is essential (16).

It should be noted that the accessibility and sufficiency of grocery stores offering healthy food in the community, as well as the availability of grocery store services and transportation options, are important factors that were not considered in this study. Also, further studies should consider the impact of chronic diseases and immobility on food insecurity in the elderly(26). These factors play a crucial role in ensuring food security in nutritionally vulnerable populations, particularly the elderly(31, 32).

A previous study found that elderly people experiencing food insecurity are more likely to attempt suicide compared to those who have secure access to food (27). As food insecurity poses a serious threat to the lives of elderly people, it is crucial to invest in nutrition programs that improve food security and provide healthy food assistance to those who face high rates of food insecurity (33).

This study has some limitations. First, the study used a single question to assess food security, which, although validated in a previous study, may not be sufficient to confirm food security. Second, since it was a cross-sectional study, it did not account for changes in living circumstances over time. Therefore, longitudinal studies should be conducted to explore changes in food security based on changes in living circumstances. Third, the low number of studies on food security in the elderly makes it difficult to accurately compare the outcomes of the studies. Finally, as the study used secondary data, there may have been insufficient factors considered to fully assess food security in the elderly.

A model was constructed to predict food security of elderly people aged 65 years and above, identifying high-risk groups and providing basic data for developing intervention strategies and policies to ensure community-based food security. It has been discovered that those who are basic livelihood recipients, suffer from depression, and live alone are most likely to not have sufficient food. Conversely, those who are not basic livelihood recipients, live with family members, and have educational qualifications beyond college are more likely to have sufficient quality and variety of food. To develop effective policies and programs for managing food security in elderly people, factors such as basic livelihood recipients, depression, education, household type, and oral health status should all be considered. Furthermore, additional studies are required to identify other crucial factors related to food security in the elderly, which can help promote their health.

Competing interests statement

None

Funding

None

Author Contribution

Study concept and design: HMH; acquisition of data: HMH; analysis and interpretation of data: HMH; drafting of the manuscript: HMH ; critical revision of the manuscript: HMH; statistical analysis: HMH; obtained funding: HMH; administrative, technical, or material support: HMH; and study supervision: HMH.

Acknowledgement

None

Data Availability

2022 CHS was public data provided by the Korea Centers for Disease Control and Prevention. Data can be obtained from https://chs.kdca.go.kr/chs/rdr/rdrInfoDownMain.do after receiving approval from the institution and datasets used and /or analyzed during the current study are available from the corresponding author on reasonable request.

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No competing interests reported.

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Prediction Model for Identifying a High-Risk Group for Food Insecurity among Elderly South Koreans

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Version 1

Abstract

Figures

Ⅰ. Introduction

Ⅱ. Materials and Methods

2.1 Study design

2.2 Study data and participants

1) Food security

2) Socio-demographic characteristics

3) Health-related characteristics

2.4 Ethical Considerations

2.5 Statistical analysis

Ⅲ. Results

3.1 General characteristics

3.2 Comparison of Health-related Characteristics

3.3 Prediction model of food security

3.4 Validation of prediction model

Ⅳ. Discussion

Ⅴ. Conclusion

Declarations

Funding

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

Supplementary Files

Status:

Version 1