Factors Affecting the Obesity Levels of Older Koreans Living Alone

Abstract

This study investigated factors related to the obesity levels of older Koreans living alone. It used data from the Korean Longitudinal Study of Aging. Its participants comprised 819 people aged 65 years and older, living alone in Korea. Multiple logistic regression was performed to analyze the factors related to managing obesity at the individual, social, and environmental levels. In the obese group, social interaction was a significant factor on social level, whereas in the overweight group, regular exercise, social interaction, and region were the significant factors at the individual, social, and environmental levels, respectively. It was found that different approaches were needed depending on the level of obesity. In addition, this study identified that it was appropriate to approach the obesity management of older people living alone, in terms of individual, social, and environmental systems, based on the ecological perspective.

Keywords

ecological perspective obesity older people

Background

According to Korea’s “2018 Statistics on the Aged,” people aged 65 years or more comprised 7.3 million and accounted for 14.3% of the total population, which is expected to rise to 41% in about 40 years (Statistics Korea, 2018). This phenomenon attracts close public attention since an increase in the population of older people and their health problems affect the country. Among the many health problems that older people face, it is important to look for ways to manage obesity because it is a major factor affecting numerous chronic diseases, including cardiovascular disease that occurs in this population (Jensen & Hsiao, 2010). There is an urgent need to develop countermeasures as 29.5% of those aged 65 or older in Korea have a body mass index (BMI) of 25.0 or higher (Ministry of Health and Welfare & Korea Institute for Health and Social Affairs, 2017).

While diet control and exercise are generally important for weight management, there is less research on the target of older people (Chau et al., 2008). Therefore, a systematic approach is needed because older people may experience psychological difficulties and physical health problems caused by obesity (Batsis et al., 2021). In later adulthood, increasing the walking pace may control weight (Wennman et al., 2021); however, various approaches to weight control and obesity management should be considered for older adults who have a limited range of movement due to arthritis and those who find it difficult to control their weight through diet (Elia, 2001; Han et al., 2011; Molino et al., 2016; Wannamethee & Atkins, 2015). As an approach to various aspects of weight management (Stark et al., 2017), it is appropriate to use ecological models that have been actively applied to theories related to the development of children (Bronfenbrenner & Morris, 2006) and widely used recently in research on older people, who need a diverse approach (Melchiorre et al., 2016). Furthermore, it is an appropriate model for physical activity because it suggests a broad view from which a variety of factors can be systematically considered (Richard et al., 2011).

The ecological model suggests that, for human development, individuals must interact with the ecological environment, which is composed of systems at four different levels: microsystem, mesosystem, macrosystem, and exosystem (Bronfenbrenner & Morris, 2006). Although it has been stated that these levels could be modified when applying the ecological model to health behavior in the field of social science, the emphasis has been placed on the consideration of the organization, community, and public policy, such as the environment (McLeroy et al., 1988). Among individual factors, cohabitation and spousal support affect older people’s health behaviors (Y. S. Kim, 2014), which is a major factor affecting their health status (J. G. Kim, 2011). While such approaches should also consider the social factors affecting older people’s weight management, considering their support system is also necessary because many of them do not live with family members. Moreover, environmental factors need to be considered because the place of residence (urban or rural areas) and the ability to participate in physical activities are among the factors that affect older people’s level of obesity.

This study analyzed the factors influencing obesity at the individual, social, and environmental levels in older people living alone, from an ecological perspective. The results of this study might serve as a basis for further development of related programs.

Methods

Design and Sample

This cross-sectional study adopted an ecological perspective and used data from the Sixth Korean Longitudinal Study of Aging [KLoSA] panel to identify the factors that influenced the obesity levels of older people who lived alone. It randomly surveyed a nationally representative sample aged 45 and over, to establish social and economic policies related to older people. It was first conducted in 2006 with biennial follow-up waves since then. The Sixth KLoSA panel successfully surveyed 7,893 of the 9,913 eligible people, including 4,552 individuals aged above 65. Of these, 897 living in a single-person household were identified; furthermore, among them, the 819 who responded with their obesity information were selected, and 78 were excluded (51 whose BMI data were unavailable and 27 who did not provide information on their quality of life [QoL] and smoking). Thus, this study’s participants finally comprised 819 people aged above 65, living alone in Korea.

Measures

The participants’ BMI was assessed using their self-reported data of height and weight. It was calculated as weight (kg) divided by the height squared (m²), and classified according to its value into the following four groups: a BMI value of 18.5 or less was underweight, 18.5 to 22.9 was normal weight, 23 to 24.9 was overweight, and 25 or more was obese (M. H. Seo et al., 2019).

At the individual level, 19 factors were examined using the 10-item Center for Epidemiological Studies Depression scale [CES-D-10]: gender, age, education level, residency type, subjective socio-economic status, marital status, employment, perceived health status, QoL, number of chronic diseases, Activities of Daily Living [ADL], Instrumental Activities of Daily Living [IADL], regular exercise, alcohol, smoking, public and private insurance, perception using the Mini–Mental State Examination [MMSE], and depression. The status of variables—gender, age, education level, residency type, subjective socio-economic status, marital status, employment, perceived health status, QoL, number of chronic diseases, regular exercise, alcohol, smoking, and public and private insurance—was required to be self-reported (Korea Employment & Information Service [KEIS], 2018). In addition, ADL, IADL, MMSE, and CES-D-10 were evaluated through previously developed tools. ADL was measured using seven questions on self-care tasks like clothing, washing the face, bathing, eating, going out of the room, using the restroom, and regulating urine and bowel movements (KEIS, 2018). IADL was measured using 10 questions on grooming, doing housework, preparing meals, doing laundry, going out (short distance), using transportation, buying goods, managing money, using the telephone, and taking medicines (KEIS, 2018). MMSE used 19 questions for assessing whether various intellectual activities related to thinking and learning were facilitated (KEIS, 2018). Depression was measured with the Korean version of CES-D-10, using the Boston form with 10 dichotomously scored items (KEIS, 2018). The social level comprised three factors: the frequency of people’s social interactions, the organizations to which they belong, and religion. The frequency of social interactions and community activities were assessed based on their daily, weekly, and monthly numbers. In addition, their residential location was categorized as metropolitan, urban, and rural, and assessed at the environmental level.

Conceptual Framework

The ecological model involves the stages of human development and was initially used primarily to describe children’s characteristics (Bronfenbrenner & Morris, 2006). It classifies the environment surrounding humans into the microsystem, mesosystem, exosystem, and macrosystem, which are viewed as influencing and receiving each other (Bronfenbrenner & Morris, 2006). However, it has recently served as the basis for explaining the target characteristics of different age groups (LeBlanc & Jacelon, 2018). A previous study applied it to identify the factors affecting vulnerable people, particularly older people (Schiamberg et al., 2011). In this study, we categorized the three levels based on ecological perspectives adopted by previous studies (Pan et al., 2009; Thornton et al., 2017): individual, social, and environmental levels. The framework established in this study is shown in Figure 1.

Figure 1.

Conceptual framework.

We propose the following three hypotheses based on the ecological perspective (Thornton et al., 2017): (a) individual level was related to the obesity level of older adults living alone (Rai et al., 2019), (b) social level was related to the obesity level of older adults living alone (Blanchard et al., 2005), and (c) environmental level was related to the obesity level of older adults living alone (Carlson et al., 2012).

Data Analysis

Data were analyzed using the STATA 16.0 program, and descriptive statistics were calculated for the participants’ general characteristics and the individual, social, and environmental level factors. While chi-square analysis was performed to compare each factor based on its obesity level, multiple logistic regression analysis was performed to assess the factors’ association with the obesity level.

Ethical Consideration

The Sixth KLoSA data used in this study were collected after obtaining Statistics Korea’s approval and obtaining consent from the KEIS’s target people. In addition, approval for an exempt review was obtained from the University’s Institutional Review Board (IRB No. 1044396-201910-HR-179-01).

Results

General Characteristics

The participants’ general characteristics are shown in Table 1. For obesity levels, the normal-weight group had the most members (n = 358, 43.7%). At the individual level, there were statistical differences based on the levels of obesity: number of chronic diseases (χ² = 16.15, p = .013), IADL (χ² = 4.07, p = .006), exercise (χ² = 10.89, p = .012), and BMI (χ² = 1395.34, p < .001). At the social level, the frequency of social interactions (χ² = 17.50, p = .042) and community activities (χ² = 23.02, p = .006) showed statistical differences. Finally, statistically significant differences in residential location (χ² = 26.00, p < .001) were found at the environmental level.

Table 1.

General Characteristics (N = 819).

Variables		Obesity level n (%)				χ²	P
Variables		Obesity (n = 225, 27.5%)	Overweight (n = 179, 21.8%)	Normal weight (n = 358, 43.7%)	Underweight (n = 57, 7.0%)	χ²	P
Individual factors
Age	≤80	140 (17.1)	99 (12.1)	194 (23.7)	27 (3.3)	5.77	.124
Age	>80	85 (10.4)	80 (9.8)	164 (20.0)	30 (3.7)	5.77	.124
Gender	Male	32 (3.9)	32 (3.9)	61 (7.5)	8 (1.0)	1.40	.706
Gender	Female	193 (23.6)	147 (18.0)	297 (36.3)	49 (6.0)	1.40	.706
Education level	Elementary	161 (19.7)	126 (15.4)	280 (34.2)	49 (6.0)	15.15	.087
	Middle	35 (4.3)	19 (2.3)	36 (4.4)	3 (0.4)
	High	22 (2.7)	27 (3.3)	33 (4.0)	5 (0.6)
	Undergraduate	7 (0.9)	7 (0.9)	9 (1.1)	0 (0.0)
Residency type	House	138 (6.9)	107 (13.1)	245 (29.9)	41 (5.0)	6.51	.089
Residency type	Apartment	87 (10.6)	72 (8.8)	113 (13.8)	16 (2.0)	6.51	.089
Subjective socio-economic status	Above middle	136 (16.6)	118 (14.4)	254 (31.0)	40 (4.9)	7.24	.065
Subjective socio-economic status	Low	89 (10.9)	61 (7.5)	104 (12.7)	17 (2.1)	7.24	.065
Employment	Yes	25 (3.1)	25 (3.2)	61 (7.5)	6 (1.0)	4.69	.196
Employment	No	200 (24.4)	153 (18.7)	297 (36.3)	51 (6.2)	4.69	.196
Perceived health status	Good	34 (4.2)	23 (2.8)	44 (5.4)	5 (0.6)	10.08	.121
	Moderate	98 (12.0)	77 (9.4)	140 (17.1)	16 (2.0)
	Bad	93 (11.4)	79 (9.7)	174 (21.3)	36 (4.4)
Quality of life	Good	29 (3.5)	23 (2.8)	53 (6.5)	10 (1.2)	3.68	.720
	Moderate	117 (14.3)	91 (11.1)	197 (24.1)	27 (3.3)
	Bad	79 (9.7)	65 (7.9)	358 (43.7)	57 (7.0)
Number of chronic diseases	None	17 (2.1)	23 (2.8)	66 (8.1)	9 (1.1)	16.15	.013
	1	66 (8.1)	49 (6.0)	108 (13.2)	15 (1.8)
	Above 2	142 (17.3)	107 (13.1)	184 (22.5)	33 (4.0)
ADL		0.2 ± 0.1	0.2 ± 0.1	0.2 ± 0.1	0.6 ± 0.2	2.57	0.053
IADL		0.6 ± 0.1	0.6 ± 0.2	0.9 ± 0.1	1.7 ± 0.4	4.07	0.006
Exercise	Regular exercise	80 (9.8)	52 (6.4)	90 (11.0)	10 (1.2)	10.89	.012
Exercise	Irregular exercise	145 (17.7)	127 (15.5)	268 (32.7)	47 (5.7)	10.89	.012
Alcohol	Non-drinker	40 (4.9)	34 (4.2)	57 (7.0)	8 (1.0)	8.30	.217
	Ex-drinker	21 (2.6)	32 (3.9)	55 (6.7)	9 (1.1)
	Drinker	164 (20.2)	113 (13.8)	246 (30.0)	40 (4.9)
Smoking	Non-smoker	192 (23.4)	147 (18.0)	294 (35.9)	43 (5.3)	6.79	.341
	Ex-smoker	26 (3.2)	23 (2.8)	40 (4.9)	11 (1.3)
	Smoker	7 (0.9)	9 (1.1)	24 (2.9)	3 (0.4)
Private insurance	Yes	25 (3.1)	19 (2.3)	29 (3.5)	4 (0.5)	2.17	.537
Private insurance	No	200 (24.4)	160 (19.5)	329 (40.2)	53 (6.5)	2.17	.537
Depression score		3.5 ± 0.2	3.8 ± 0.2	4.0 ± 0.1	4.2 ± 0.4	2.05	0.105
Body mass index (kg/m²)		27.0 ± 0.1	23.9 ± 0.0	21.1 ± 0.1	17.4 ± 0.2	1395.34	<.001
Social factors
Frequency of social interaction	Daily	87 (10.6)	54 (6.6)	132 (16.1)	10 (1.2)	17.50	.042
	Weekly	92 (11.2)	84 (10.3)	130 (15.9)	27 (3.3)
	Monthly	29 (3.5)	26 (3.2)	66 (8.1)	12 (1.5)
	Rare	17 (2.1)	15 (1.8)	30 (3.7)	8 (1.0)
Frequency of community activities	Daily	37 (4.5)	26 (3.2)	51 (6.2)	3 (0.4)	23.02	.006
	Weekly	58 (7.1)	48 (5.9)	93 (11.4)	14 (1.7)
	Monthly	48 (5.9)	49 (6.0)	56 (6.8)	8 (1.0)
	Rare	82 (10.0)	56 (6.9)	158 (19.3)	32 (3.9)
	No	99 (12.1)	103 (12.6)	195 (23.8)	27 (3.3)
Environmental factors
Residential location	Metropolitan	88 (10.7)	79 (9.7)	129 (15.8)	19 (2.3)	26.00	<.001
	Urban	83 (10.1)	50 (6.1)	83 (10.1)	15 (1.8)
	Rural	54 (6.6)	50 (6.1)	146 (17.8)	23 (2.8)

Note. ADL = activities of daily living; IADL = instrumental activities of daily living.

Factors Affecting the BMI of Older People According to Their Obesity Levels

Obese older people

Factors affecting the BMI of obese older people (n = 225) were analyzed using hierarchical multiple logistic regression analysis (Table 2). Variable inflation factors [VIFs] for all the variables ranged from 1.06 to 4.62. In Model 1—individual level—no factors showed significant statistical differences. However, in Model 2—individual and social levels—there were significant factors at the social level relating to the frequency of social interactions: daily (β = −0.50, p < .001), weekly (β = −0.33, p = .017), and monthly (β = −0.32, p = .002). In Model 3—individual, social, and environmental levels—significant factors were seen at the social level with regard to the frequency of social interactions: daily (β = −0.45, p = .001), weekly (β = −0.29, p = .037), and monthly (β = −0.30, p = .005).

Table 2.

Factors Affecting the Obesity Level of Obese People (n = 225).

Variables	Model 1. Individual level					Model 2. Individual and social levels					Model 3. Individual, social, and environment levels					VIF
Variables	B	SE	β	t	p	B	SE	β	t	p	B	SE	β	t	p	VIF
(Constant)	26.89	0.16	–	166.94	<.001	28.38	0.44	–	65.16	<.001	28.21	0.46	–	61.28	>.001	–
No. of chronic diseases = none [reference]
No. of chronic diseases = 1	−1.00	0.81	−0.08	−1.23	.22	−0.93	0.81	−0.08	−1.15	.253	−0.92	0.81	−0.08	−1.14	.256	1.14
No. of chronic diseases ≥ 2	−0.27	0.36	−0.05	−0.75	.457	−0.36	0.36	−0.07	−1.00	.317	−0.36	0.36	−0.07	−1	.317	1.09
Regular exercise = none [reference]
Regular exercise = yes	0.33	0.25	0.09	1.28	.201	0.37	0.26	0.10	1.43	.153	0.34	0.26	0.09	1.33	.184	1.2
IADL	0.56	0.37	0.10	1.5	.136	0.38	0.36	0.07	1.04	.299	0.34	0.36	0.06	0.96	.339	1.06
Social interactions = rare [reference]
Social interactions = daily						−1.81	0.48	−0.50	–3.75	<.001	−1.63	0.49	−0.45	–3.33	.001	4.58
Social interactions = weekly						−1.17	0.49	−0.33	–2.40	.017	−1.02	0.49	−0.29	–2.10	.037	4.62
Social interactions = monthly						−1.69	0.55	−0.32	–3.08	.002	−1.57	0.55	−0.30	–2.86	.005	2.71
Community activity = rare [reference]
Community activity = daily						0.69	0.38	0.15	1.80	.073	0.64	0.39	0.13	1.65	.100	1.64
Community activity = weekly						−0.51	0.32	−0.13	−1.57	.119	−0.53	0.32	−0.13	−1.64	.102	1.59
Community activity = monthly						−0.28	0.33	−0.06	−0.84	.401	−0.32	0.33	−0.07	−0.97	.336	1.46
Residential location = metropolitan [reference]
Residential location = urban											0.34	0.26	0.09	1.32	.188	1.27
Residential location = rural											−0.27	0.30	−0.07	−0.91	.362	1.32
	F = 1.23, p = .299,R² = .0219, Adj. R² = .0041					F = 2.98, p = .002,R² = .1221, Adj. R² = .0810					F = 2.88, p = .001,R² = .1402, Adj. R² = .0916

Note. VIF = vaiable inflation factor; IADL = instrumental activities of daily living.

Overweight older people

Factors affecting the BMI of overweight older people (n = 178) were analyzed using a hierarchical multiple logistic regression analysis (Table 3). The VIFs of all variables ranged from 1.04 to 4.83. In Model 1, regular exercise showed a significant statistical difference (β = 0.22, p = .004) at the individual level. In Model 2, there were two significant factors: regular exercise (β = 0.19, p = .010) at the individual level and frequency of social interactions at the social level (daily: β = −0.43, p = .005; weekly: β = −0.46, p = .004; and monthly: β = −0.29, p = .014). In Model 3, there were significant factors at all levels: Regular exercise (β = 0.18, p = .015) at the individual level; frequency of social interactions: daily (β = −0.43, p = .005), weekly (β = −0.48, p = .002), and monthly (β = −0.34, p = .005) at the social level; and residential location: urban (β = −0.19, p = .021) at the environmental level.

Table 3.

Factors Affecting the Obesity Level of Overweight People (n = 178).

Variables	Model 1. Individual level					Model 2. Individual and social levels					Model 3. Individual, social, and environment levels					VIF
Variables	B	SE	β	t	p	B	SE	β	t	p	B	SE	β	t	p	VIF
(Constant)	23.80	0.05	–	438.87	<.001	24.22	0.15	–	160.54	<.001	24.37	0.16	–	151.09	>.001	–
No. of chronic diseases = none [reference]
No. of chronic diseases = 1	−0.17	0.17	−0.73	−0.97	.335	−0.33	0.17	−0.15	−1.91	.057	−0.29	0.17	−0.13	−1.69	.093	1.16
No. of chronic diseases ≥ 2	0.08	0.13	0.05	0.61	.540	0.07	0.12	0.04	0.57	.567	0.08	0.12	0.05	0.63	.531	1.04
Regular exercise = none [reference]
Regular exercise = yes	0.26	0.09	0.22	2.89	.004	0.23	0.09	0.19	2.62	.010	0.22	0.09	0.18	2.47	.015	1.09
IADL	−0.05	0.13	−0.03	−0.41	.685	−0.10	0.13	−0.06	−0.78	.437	−0.10	0.13	−0.06	−0.77	.444	1.16
Social interactions = rare [reference]
Social interactions = daily						−0.51	0.18	−0.43	−2.83	.005	−0.51	0.18	−0.43	−2.85	.005	4.56
Social interactions = weekly						−0.50	0.17	−0.46	−2.93	.004	−0.53	0.17	−0.48	−3.12	.002	4.83
Social interactions = monthly						−0.46	0.18	−0.29	−2.48	.014	−0.53	0.19	−0.34	−2.84	.005	2.9
Community activity = rare [reference]
Community activity = daily						0.23	0.15	0.14	1.46	.146	0.18	0.15	0.11	1.17	.245	1.89
Community activity = weekly						−0.08	0.12	−0.07	−0.69	.492	−0.11	0.12	−0.09	−0.91	.366	1.86
Community activity = monthly						0.18	0.11	0.15	1.66	.099	0.17	0.11	0.14	1.60	.112	1.60
Residential location = metropolitan [reference]
Residential location = urban											−0.23	0.10	−0.19	−2.34	.021	1.29
Residential location = rural											−0.18	0.10	−0.15	−1.91	.057	1.24
	F = 2.48, p = .047,R² = .0543, Adj. R² = .0324					F = 2.88, p = .002,R² = .1471, Adj. R² = .0961					F = 3.03, p < .001,R² = .1806, Adj. R² = .1210

Note. VIF = vaiable inflation factor; IADL = instrumental activities of daily living.

Discussion

This study explored the factors affecting the obesity levels of older Korean people living alone and had two key points.

First, since this study was conducted according to a theoretical framework based on the ecological perspective, its results could be interpreted at each level. At the individual level, the number of chronic diseases, IADL, exercise, and BMI differed across obesity levels, probably because chronic health vulnerabilities and IADL may have affected older people’s movements and exercise (Porter Starr et al., 2016). At the social level, the frequency of both social and community activities differed based on obesity levels. To reduce obesity, older people should increase their physical activity, for which increasing social connectedness is helpful (Volpe et al., 2016). Finally, at the environmental level, obesity levels differed per residential location. A review of the relationship between the environment and health revealed that the environment influences physical activity and weight loss (Renalds et al., 2010).

Second, this study’s results indicate that developing a variety of health promotion programs should be considered for older people living alone, depending on their obesity levels; this supports the results of previous studies. Since the participants were classified according to their obesity levels, and the factors affecting BMI were explored, especially among older adults in the obese and overweight groups, it can provide useful, practical strategies. It will also be beneficial for developing specialized interventions to address the influencing factors characteristic of these participants.

In the group of obese older people, the frequency of social interactions at the social level was the group determinant of their BMI factors. Since BMI reduction was the most significant (β = −0.45, p = .001) when there was daily social interaction, community-level approaches should be implemented to increase the social interaction frequency of older people living alone. In South Korea, a home delivery meal service is operated for low-income older people. Providing food helps improve nutrition and affords the advantage of the delivery volunteer being able to check the older clients’ well-being (S. Seo et al., 2013). Benchmarking these programs would be effective for the BMI management of older people living alone as well as to increase the number of those eligible for such benefits. In addition, educating volunteers to check on older people’s well-being and increasing the frequency of social interactions through daily meetings could further enhance the program’s effectiveness.

The overweight groups reported more prominent factors than obese groups relating to regular exercise at the individual level, social interaction frequency at the social level, and urban dwelling at the environmental level. This result suggests that interventions should be developed by considering additional factors before overweight older people living alone become obese. Although regular exercise effectively prevents obesity (Cieślak et al., 2016), a different result was obtained in this study. Thus, relevant research is needed in the future so that those who have become overweight may realize the need for exercising regularly. There was also a difference in BMI, depending on the place of residence. This could indicate differences in the distributions of infrastructure for walking and exercise facilities depending on residential area (Azevedo & Vartanian, 2015).

Health care Implications

The health care implications in this study can be considered in terms of theory and practice. From the theoretical viewpoint, the results show that the ecological perspective applies to weight management in obese older people living alone. In addition, from a practical viewpoint, our results indicate that tailored health care interventions should be developed after considering the factors affecting obesity levels. It is necessary for obese older adults living alone to use community resources to increase their social interaction. Providing exercise programs at community centers will increase the number of social interactions and provide the beneficial effects of exercise. Similarly, overweight older people living alone can also be offered programs to exercise regularly along with an increase in social interaction. In addition, it is necessary to develop programs considering older people’s location of residences. This is because, simple exercises such as walking are easier in rural than in metropolitan areas.

Limitations

This study has some limitations. First, since it was a cross-sectional study, future studies should adopt a longitudinal design that would help determine the influencing factors more accurately by associating BMI changes with changes in influencing factors. Second, since the environment is one of the major variables affecting overweight groups’ BMI, it is necessary to consider environment differences when applying the results to other countries. Third, participants’ self-reported data of height and weight were used for BMI calculations. Finally, this study used secondary data analysis and was conducted with a limited number of variables; other factors need to be considered in further studies.

Conclusion

This study was conducted to explore the factors related to the obesity level of older Koreans living alone, based on the ecological approach. In the obese group, social interaction frequency at the social level was the main factor affecting BMI. In addition, the overweight group’s influential factors on BMI were regular exercise, social interaction frequency, and urban residence at the individual, social, and environmental levels, respectively. We believe that our results have laid the groundwork for applying an ecological perspective to obesity management in older people living alone, and suggest that obesity levels should be distinguished in future approaches.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

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

Ethical Approval

IRB review exemption in Gachon University Institutional Review Board (1044396-201910-HR-179-01).

ORCID iDs

Ka Young Kim

Wonjung Noh

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