Introduction
The single-person household is the fastest growing type of household in many regions of the world, due to changes in institutional arrangements, demographic behaviors, and labor migration in the past few decades [
1]. Not only widowed people, but also many young adults who have never been married, now live alone. The family structure in Korea has changed from the traditional large extended family to the nuclear family, due to industrialization and urbanization, and recently, the number of single-person households living alone in Korea has increased rapidly [
2]. According to the National Statistical Office, the percentage of single-person households has increased from 15.5% in 2000, to 29.3% in 2018, and is estimated to reach 34.3% by 2035 [
3]. Recently, the proportion of young adults living in single-person households has increased remarkably worldwide [
4].
According to the Korean National Health and Nutrition Examination Survey (KNHANES), the incidence of metabolic syndrome (MetS) has increased by 0.6% every 10 years since 1998 [
5]. Additionally, recent studies in Korea have found that single-person households are more susceptible than multi-person households to insufficient physical activity (PA) and unhealthy eating practices [
6]. The amount of PA has decreased, with a decrease in moderate PA and walking, without an increase in high-intensity PA [
7,
8]. Low levels of PA, in turn, contribute to the increase in MetS incidence.
In conjunction with social changes in Korea, the dietary behavior of Koreans has also changed rapidly. With increasing numbers of single-person households, eating alone has become a social concern. Some previous studies reported that eating alone was associated with various health problems. Eating alone was related to a reduced calorie intake and a less-varied diet [
9,
10], and it could be a direct risk factor for MetS [
11].
The level of PA, the degree of participation in exercise, and dietary and nutritional intakes have an impact on the risk for and prevalence of MetS. In a recent comparative analysis, among 66,211 older individuals (aged 60 years or more) in Korea, single-person households are considered to have worse overall health behaviors, such as exercise behaviors and nutritional behaviors, than multi-person households [
12]. According to KNHANES data (2013–2015) of 2903 subjects ≥ aged 65 years, single-person households had worse nutrient intake overall, and had an increased prevalence of MetS [
13].
Research on housing and MetS of young people, particularly young single-person households, has been scant internationally. Moreover, there have been few studies about household type-specific PA and energy intake in young adults according to the presence of MetS. Thus, it is essential to examine the relationship between these factors in a large population. However, even adequately-sized cohort studies evaluating the PA levels and energy intakes according to the household types and presence of MetS are not appropriate, because these factors may vary by young adults’ lifestyles and household types. Therefore, this study aimed to analyze the differences in PA levels and energy intake by household type and the presence of MetS in a young adult Korean population, based on data from the 7th Korea National Health and Nutrition Examination Survey (2016–2018).
Results
The average values of PA levels and energy intake factors are shown in Table
2 and the ORs for MetS and MetS components according to PA levels and energy intake are presented in Table
3. The ORs were adjusted for body mass index, smoking, household-type, and sex in model 2. We found that an “Active” PA level was associated with low HDL-C levels (OR = 0.76, 95%CI = 0.61–0.93). A PA level of “Very active” was associated with a lower MetS incidence (OR = 0.55, 95%CI = 0.39–0.77), larger waist circumference (OR = 0.64, 95%CI = 0.43–0.93), high triglyceride (TG) levels (OR = 0.69, 95%CI = 0.56–0.87), and low levels of high-density lipoprotein C (HDL-C) (OR = 0.72, 95%CI = 0.59–0.88). We also found that “Moderate energy intake” levels were associated with a larger waist circumference (OR = 1.46, 95%CI = 1.05–2.04) and high glucose levels (OR = 1.23, 95%CI = 1.02–1.63). “Higher energy intake” levels were associated with the high TG levels (OR = 1.33, 95%CI = 1.03–1.70), low HDL-C levels (OR = 0.77, 95%CI = 0.61–0.97), and high glucose levels (OR = 1.39, 95%CI = 1.01–1.92).
Table 2
Classification of physical activity levels and energy intake
Physical activity factors | MET min/Week (Mean ± SE) |
Inactive (0–249 MET min/week) | 39.6 ± 2.5 | 1354 | 40.0 ± 2.6 | 1255 | 35.4 ± 7.6 | 99 |
Somewhat active (250–499 MET min/week) | 406.9 ± 3.2 | 464 | 406.1 ± 3.3 | 428 | 415.9 ± 11.3 | 36 |
Active (500–999 MET min/week) | 750.7 ± 5.3 | 834 | 752.5 ± 5.8 | 746 | 739.2 ± 12.5 | 88 |
Very active (> 1000 MET min/week) | 2775.1 ± 100.2 | 1322 | 2754.4 ± 97.8 | 1190 | 2944.4 ± 345.2 | 132 |
Energy intake factors | Energy intake/EER (Mean ± SE) |
Lower energy intake (energy intake/EER < 0.8) | 0.6 ± 0.0 | 2067 | 0.6 ± 0.0 | 1884 | 0.5 ± 0.0 | 183 |
Moderate energy intake (0.8 ≤ energy intake/EER ≤ 1.2) | 1.0 ± 0.0 | 1288 | 1.0 ± 0.0 | 1163 | 1.0 ± 0.0 | 125 |
Higher energy intake (energy intake/EER > 1.2) | 1.5 ± 0.0 | 619 | 1.5 ± 0.0 | 572 | 1.4 ± 0.0 | 47 |
Table 3
Odds ratio (95% CI) for MetS and MetS components according to physical activity levels and energy intake
Model 1a |
Physical activity factors |
Inactive (n = 1354) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
Somewhat active (n = 464) | 0.79 (0.54–1.16) | 0.89 (0.64–1.23) | 0.69 (0.51–0.94)* | 0.80 (0.59–1.09) | 0.71 (0.48–1.05) | 0.84 (0.57–1.24) |
Active (n = 834) | 0.86 (0.64–1.16) | 0.927 (0.711–1.207) | 0.78 (0.62–0.97)* | 0.77 (0.63–0.94)* | 1.10 (0.83–1.46) | 0.99 (0.72–1.35) |
Very active (n = 1322) | 0.84 (0.63–1.12) | 1.02 (0.81–1.29) | 0.88 (0.72–1.08) | 0.74 (0.61–0.89)** | 1.15 (0.89–1.49) | 0.96 (0.75–1.22) |
Energy intake factors |
Lower energy intake (energy intake/EER < 0.8) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
Moderate energy intake (0.8 ≤ energy intake/EER ≤ 1.2) | 0.85 (0.66–1.10) | 0.77 (0.63–0.93)** | 0.92 (0.74–1.14) | 0.90 (0.76–1.07) | 0.90 (0.73–1.12) | 1.07 (0.84–1.36) |
Higher energy intake (energy intake/EER > 1.2) | 0.84 (0.62–1.13) | 0.77 (0.58–1.02) | 1.16 (0.93–1.46) | 0.68 (0.54–0.85)** | 0.86 (0.64–1.15) | 1.16 (0.86–1.55) |
Model 2b |
Physical activity factors |
Inactive (n = 1354) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
Somewhat active (n = 464) | 0.91 (0.58–1.41) | 1.10 (0.68–1.80) | 0.75 (0.53–1.06) | 0.80 (0.58–1.11) | 0.77 (0.51–1.18) | 0.92 (0.62–1.36) |
Active (n = 834) | 0.86 (0.59–1.24) | 1.05 (0.65–1.70) | 0.78 (0.60–1.01) | 0.76 (0.61–0.93)** | 1.12 (0.82–1.52) | 1.01 (0.74–1.39) |
Very active (n = 1322) | 0.55 (0.39–0.77)*** | 0.64 (0.43–0.93)* | 0.69 (0.56–0.87)** | 0.72 (0.59–0.88)** | 0.90 (0.67–1.19) | 0.81 (0.63–1.05) |
Energy intake factors |
Lower energy intake (energy intake/EER < 0.8) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
Moderate energy intake (0.8 ≤ energy intake/EER ≤ 1.2) | 1.20 (0.88–1.64) | 1.46 (1.05–2.04)* | 1.05 (0.83–1.32) | 1.02 (0.85–1.22) | 1.07 (0.86–1.35) | 1.23 (1.02–1.63)* |
Higher energy intake (energy intake/EER > 1.2) | 1.19 (0.81–1.75) | 1.58 (0.94–2.65) | 1.33 (1.03–1.70)* | 0.77 (0.61–0.97)* | 1.01 (0.71–1.42) | 1.39 (1.01–1.92)* |
The differences in variables considered risk factors for MetS, according to the presence or absence of MetS and according to households are presented in Table
4. In the total group, young individuals with MetS had significantly higher values of risk factors for MetS than did those in the non-MetS group (all variables,
p < 0.001). The interaction between the presence or absence of MetS and household type (single- or multi-person) was statistically significant for waist circumference, TG, HDL-C, diastolic blood pressure (DBP), fasting blood glucose (all
p < 0.001). The Bonferroni post-hoc test showed the following group differences: Individuals with MetS living in multi-person households had significantly larger waist circumference, TG, DBP, fasting blood glucose (all
p < 0.001), but lower HDL-C (
p < 0.001), than their counterparts without MetS. Individuals with MetS who lived alone had significantly larger waist circumference, TG, HDL-C, DBP, and fasting blood glucose than those without MetS (all
p < 0.001). Individuals with MetS living as single persons had statistically significantly greater waist circumference and higher DBP (both
p < 0.01) than individuals with MetS living in multi-person households.
Table 4
Metabolic Syndrome Components
Waist circumference (cm) | Non-MetS MetS p-value | 77.9 ± 0.2 95.63 ± 0.5 < 0.001*** | 77.8 ± 0.2 95.2 ± 0.6† | 78.6 ± 0.7 99.3 ± 1.1†‡ | H M H × M | 62.542*** 1489.340*** 87.608*** | 0.000(0.006) 0.000(0.068) 0.000(0.008) | 1.000 1.000 1.000 |
TG (mg/dL) | Non-MetS MetS p-value | 102.8 ± 1.7 242.7 ± 9.5 < 0.001*** | 102.2 ± 1.9 243.5 ± 9.9† | 107.8 ± 2.9 236.1 ± 24.6† | H M H × M | 2.390 748.808*** 9.114*** | 0.092(0.000) 0.000(0.037) 0.000(0.001) | 0.485 1.000 0.976 |
HDL-C (mg/dL) | Non-MetS MetS p-value | 54.9 ± 0.3 40.9 ± 0.4 < 0.001*** | 55.0 ± 0.2 40.7 ± 0.4† | 53.8 ± 0.9 42.2 ± 1.4† | H M H × M | 0.022 552.453*** 22.619*** | 0.978(0.000) 0.000(0.027) 0.000(0.002) | 0.053 1.000 1.000 |
SBP (mmHg) | Non-MetS MetS p-value | 109.5 ± 0.3 123.0 ± 0.6 < 0.001*** | 109.1 ± 0.2 122.6 ± 0.7 | 112.4 ± 0.9 125.9 ± 2.3 | H M H × M | 176.024*** 451.997*** 0.485 | 0.000(0.017) 0.000(0.022) 0.485(0.616) | 1.000 1.000 0.130 |
DBP (mmHg) | Non-MetS MetS p-value | 72.6 ± 0.2 85.1 ± 0.5 < 0.001*** | 72.4 ± 0.2 84.6 ± 0.5† | 74.8 ± 0.6 88.6 ± 1.4†‡ | H M H × M | 43.256*** 629.397*** 61.583*** | 0.000(0.004) 0.000(0.030) 0.000(0.006) | 1.000 1.000 1.000 |
Fasting glucose (mg/dL) | Non-MetS MetS p-value | 90.3 ± 0.3 108.0 ± 1.5 < 0.001*** | 90.3 ± 0.3 108.5 ± 1.6† | 90.4 ± 0.5 104.2 ± 2.7† | H M H × M | 130.082*** 359.141*** 7.636*** | 0.000(0.013) 0.000(0.018) 0.000(0.001) | 1.000 1.000 0.948 |
The differences in PA levels according to the presence or absence of MetS and according to household type are presented in Table
5. In the total group, there was no significant difference in PA levels between young individuals with and without MetS. For the PA aspects of “Occupational vigorous” (
p < 0.05), “Transport” (
p < 0.05), and “Total PA” (
p < 0.01), there was a significant interaction between the presence or absence of MetS and household type. The Bonferroni post-hoc test showed the following group differences: Individuals with MetS living in multi-person households showed significantly higher “Occupational vigorous” PA (
p < 0.05) than their counterparts without MetS. Those with MetS who lived alone demonstrated significantly lower “Transport” and “Total” PA (all
p < 0.01) than their counterparts without MetS. There was no significant difference between those with MetS living in single-person households and those with MetS living in multi-person households.
Table 5
Levels of physical activity
Occupational vigorous | Non-MetS MetS p-value | 76.7 ± 15.5 132.4 ± 47.8 0.271 | 65.1 ± 12.8 148.5 ± 53.5† | 176.0 ± 86.9 1.7 ± 1.7 | H M H × M | 3.765* 0.836 4.575* | 0.023(0.000) 0.361(0.000) 0.010(0.000) | 0.689 0.150 0.778 |
Occupational moderate | Non-MetS MetS p-value | 214.6 ± 23.9 234.7 ± 45.5 0.688 | 214.0 ± 25.0 251.8 ± 51.0 | 219.3 ± 61.2 95.6 ± 45.8 | H M H × M | 29.891*** 0.850 1.621 | 0.000(0.003) 0.357(0.000) 0.198(0.000) | 1.000 0.152 0.345 |
Transport | Non-MetS MetS p-value | 524.2 ± 17.6 474.2 ± 43.9 0.253 | 514.5 ± 17.6 490.2 ± 48.1 | 607.7 ± 69.5 344.0 ± 70.6†† | H M H × M | 26.954*** 9.888** 3.559* | 0.000(0.003) 0.002(0.000) 0.028(0.000) | 1.000 0.882 0.663 |
Recreational vigorous | Non-MetS MetS p-value | 212.9 ± 17.0 191.9 ± 39.6 0.628 | 209.3 ± 17.4 194.2 ± 44.6 | 243.5 ± 42.6 172.8 ± 68.3 | H M H × M | 30.567*** 3.324 0.991 | 0.000(0.003) 0.068(0.000) 0.371(0.000) | 1.000 0.446 0.224 |
Recreational moderate | Non-MetS MetS p-value | 181.8 ± 9.0 149.7 ± 23.2 0.206 | 183.0 ± 9.8 147.1 ± 23.8 | 171.1 ± 22.6 171.4 ± 55.2 | H M H × M | 10.371*** 1.648 0.243 | 0.000(0.001) 0.199(0.000) 0.784(0.000) | 0.988 0.250 0.088 |
Total physical Activity | Non-MetS MetS p-value | 1210.2 ± 48.5 1182.9 ± 105.8 0.812 | 1186.0 ± 46.6 1231.8 ± 116.1 | 1417.7 ± 168.0 785.4 ± 172.7†† | H M H × M | 64.415*** 9.312** 5.062** | 0.000(0.006) 0.002(0.000) 0.006(0.000) | 1.000 0.862 0.820 |
Table
6 shows the differences in energy intake according to the presence or absence of MetS and according to household type. In the total group, young individuals with MetS had significantly higher energy intake than those without MetS (total energy intake and protein intake,
p < 0.001; carbohydrate intake,
p < 0.05). For “Total energy intake”, “Protein intake”, “Fat intake” (all
p < 0.001), and for “Carbohydrate intake” (
p = 0.001), there was a significant interaction between the presence or absence of MetS and household type. The Bonferroni post-hoc test showed the following group differences: Individuals with MetS living in multi-person households had significantly higher total energy intake, protein intake, fat intake (all
p < 0.001), and carbohydrate intake (
p < 0.01) than those without MetS who lived in multi-person households. Persons with MetS who lived as single persons had significantly lower total energy intake (
p < 0.05) and fat intake (
p < 0.01) than those without MetS who lived alone. Those with MetS who lived alone had a significantly lower total energy intake and fat intake (
p < 0.01) than those with MetS who lived in a multi-person household.
Total energy intake (kcal) | Non-MetS MetS p-value | 2149.0 ± 19.4 2396.7 ± 58.9 < 0.001*** | 2137.8 ± 21.1 2443.6 ± 67.9††† | 2250.1 ± 56.5 2012.1 ± 130.6†‡ | H M H × M | 102.233*** 0.200 28.101*** | 0.000(0.011) 0.654(0.000) 0.000(0.003) | 1.000 0.073 1.000 |
Carbohydrate intake (kcal) | Non-MetS MetS p-value | 1173.0 ± 11.2 1236.5 ± 24.4 0.021* | 1170.8 ± 12.2 1244.0 ± 26.2†† | 1193.3 ± 26.9 1174.9 ± 85.8 | H M H × M | 0.237 0.252 7.335** | 0.789(0.000) 0.616(0.000) 0.001(0.001) | 0.087 0.079 0.939 |
Protein intake (kcal) | Non-MetS MetS p-value | 324.5 ± 3.8 362.4 ± 9.8 < 0.001*** | 323.4 ± 4.2 367.1 ± 11.2††† | 334.4 ± 9.2 323.5 ± 23.3 | H M H × M | 160.606*** 0.886 25.2218*** | 0.000(0.018) 0.347(0.000) 0.000(0.003) | 1.000 0.156 1.000 |
Fat intake (kcal) | Non-MetS MetS p-value | 523.9 ± 8.8 567.1 ± 23.1 0.090 | 517.4 ± 9.2 580.9 ± 26.6††† | 581.9 ± 25.2 453.9 ± 41.2††‡ | H M H × M | 278.513*** 7.183** 30.312*** | 0.000(0.030) 0.007(0.000) 0.000(0.003) | 1.000 0.764 1.000 |
Discussion
This study investigated differences in PA levels and energy intake by household-type and the presence of MetS in a young adult Korean population, to understand the relationships among these factors. We found that components of MetS, such as a large waist circumference, hyperlipidemia, low HDL-C levels, and high fasting blood glucose levels, can be improved by higher PA levels (Very active: 2775.1 ± 100.2 MET min/week) as compared with inactivity (0–249 MET min/week). Low HDL-C levels could also be improved by increased PA levels (Active: 500–999 MET min/week) as compared with inactivity. In addition, hyperlipidemia, low HDL-C, and high glucose levels can be improved by lower energy intake (0.8 < EER) as compared with higher energy intake (EER > 1.2). Large waist circumference and high glucose were also improved in those with lower energy intake as compared with those with moderate energy intake (0.8 ≤ EER ≤ 1.2). In the total group, there was no significant difference between MetS and non-MetS groups in terms of PA levels. This result was similar to that in multi-person households, except for the “Occupational vigorous” category. However, in single-person households, the MetS group had lower levels of “Transport” and “Total physical activity” than the non-MetS group. Investigating the differences in energy intake according to the presence or absence of MetS and according to household type showed that, in the total group, the MetS group had significantly higher total energy intake, carbohydrate intake, and protein intake levels than the non-MetS group. In multi-person households, the MetS group had significantly higher total energy intake, carbohydrate intake, fat intake, and protein intake than the non-MetS group. However, in single-person households, the MetS group had significantly lower total energy intake and fat intake than the non-MetS group. In particular, individuals with MetS who lived in single-person households had lower total energy intake and fat intake than those with MetS who lived in multi-person households. Taken together, our results showed the need for different approaches of implementing PA and nutrition strategies according to household type in order to prevent MetS.
Our results contribute to emerging evidence that PA levels and energy intake are associated with MetS components [
22,
23]. We found that the prevalence of MetS factors was significantly lower among those with “Very active” PA levels as compared to those with an “Inactive” PA level. Young adults who were very active had a 45% lower prevalence of MetS. Similar to our study, Sisson et al. [
24] found that men and women with higher levels of sedentary behavior than physical activity in the US had a 66% higher prevalence of MetS. Those with moderate physical activity (75–180 min/day) had a 29% lower prevalence of MetS, according to data of 4327 adults obtained in the NHANES from 2007 to 2010 [
25]. Moreover, among 410 subjects, aged 18–74 years, subjects with heavy PA levels (based on the Lipid Research Clinics questionnaire) had a 40% lower prevalence of MetS than subjects with light PA levels [
26]. Regular PA has been shown to increase HDL-C in a linear dose-response manner [
27]. In addition, intense PA levels could reduce triglyceride levels [
27]. These findings confirmed that MetS risk factors are driven largely by PA levels, and the sedentary lifestyle increases the risk of developing Mets in adults.
With respect to energy intake, we found that the MetS risk factors had significantly higher values in individuals with moderate or higher energy intake (vs. those with a lower energy intake). Those with a moderate energy intake had a 46% higher prevalence of having a large waist circumference and a 23% higher prevalence of having high fasting glucose levels. Moreover, those with a higher energy intake had a 33% higher prevalence of high triglyceride, 23% lower prevalence of low LDL-C, and 39% higher prevalence of high fasting glucose levels. Similar to our study, 7081 men aged 30 years and older, who overate more than 4 times a week, had a 141% higher prevalence of MetS [
28]. According to the data from the 2007–2012 KNHANES, from 20,515 Korean adults, a high carbohydrate intake (380.8 ± 4.7 g) resulted in a 32% higher prevalence of elevated TG and a 32% higher prevalence of MetS in men, and a 26% higher prevalence of elevated TG and 31% higher prevalence of MetS in women [
29]. Moreover, according to a cross-sectional study (6737 males and 8845 females) from the 2008–2011 KNHANES, a high carbohydrate intake was associated with a higher prevalence of MetS in males, and a high carbohydrate intake combined with a low fat intake was associated with MetS in females [
23]. In addition, according to a study of 3-year KNHANES data, from 2012 to 2014, the prevalence of MetS was positively correlated with carbohydrate intake in an adult population, as assessed by the 24-h recall questionnaire [
30]. These findings confirm that MetS is driven largely by a high nutrient energy intake, particularly that derived from carbohydrates, as young individuals with MetS had a higher carbohydrate intake than those without MetS in this study.
We found that there was no significant difference in PA levels between those with and those without MetS in the total group. However, the MetS group had a higher total energy intake, carbohydrate intake, and protein intake than those without MetS. The results of our study were very similar to those of previous studies on old adults. A higher percentage of energy intake was associated with a higher incidence of MetS, mostly due to abdominal obesity and hypertriglyceridemia in old adults [
31,
32]. The prevalence of MetS has increased rapidly in Asia in recent years, and several studies have demonstrated stronger associations between dietary carbohydrate intake and metabolic disease [
33,
34]. The 2007–2012 National Health and Nutrition Examination Survey studies showed that a high carbohydrate intake is associated with metabolic abnormalities (Ha et al., 2018). According to a cross-sectional study performed in 2018 (6737 males and 8845 females), the risk of MetS increased proportionally with the carbohydrate intake proportion [
29]. As Korean adults consume more carbohydrates than adults in other regions, stronger associations of dietary carbohydrate with MetS were observed in this study. In addition, studies on the Korean population and a meta-analysis of observational studies have revealed that total, red, and processed meat consumption is associated with a high risk of MetS [
35]. Additionally, in a review of epidemiological evidence, dietary protein appeared to increase the risk of MetS [
36]. Korean eating habits have changed from a traditional diet focused on vegetables to a western diet focused on meat in recent years. Taken together, MetS in young individuals is more likely to be linked to energy intake than to PA levels.
This study analyzed household-specific PA according to the presence or absence of MetS in young adults. There was no significant difference across PA categories in multi-person households except for the “Occupational vigorous” category. In contrast, transport and total PA were significantly lower in the MetS group than in the non-MetS group in single-person households. Numerous studies in recent decades have shown that higher PA levels have a favorable impact on each of the MetS components [
37‐
39]. In a cross-sectional evaluation of PA and metabolic risk among individuals with a family history of type 2 diabetes, it was suggested that increasing the total amount of PA in sedentary and overweight individuals had beneficial effects on MetS risk [
40]. An analysis of MetS in Korean adults, identified MetS risk factors as a lack of walking and flexibility exercises in single-person households [
41]. Although living alone does not equate to a lack of a social network or support, social support is important for engaging in healthy behaviors, including PA [
42,
43]. Support from family [
44] and friends [
45] has also been shown to correlate positively with PA. Single-person households without social support could promote a decrease in total PA, which can serve as a potential risk factor for an increased incidence of MetS.
This study also analyzed household-specific dietary intake according to the presence or absence of MetS in young adults. The total energy intake, carbohydrate intake, protein intake, and fat intake were significantly higher in the MetS group than in the non-MetS group in indivuals living in multi-person households. In contrast, the total energy intake and fat intake were significantly lower in the MetS group than in the non-MetS group in individuals living in single-person households. Morever, the total energy intake and fat intake were significantly lower in individuals with MetS who lived alone than in those with MetS who lived in multi-person households. Multi-person households presented a similar tendency to the total group in terms of energy intake: those with MetS tended to have a higher energy intake, as mentioned above, whereas those living alone presented the opposite tendency. According to the 2020 Dietary Reference Intakes for Koreans [
46], the recommended energy intake for men aged 19–49 is about 2550 cal, and for women aged 19–49, it is about 1950 cal. The single-person household data in this study represented both men and women. Thus, they consumed relatviely lower amounts of energy than recommended by the guidelines, but were not at a deficient level. Thus, we cautiously speculate that MetS in young adults in single-person households is more likely to be linked to lower PA levels than to energy intake.
MetS is caused by lifestyle factors, such as PA, diet, and weight, and it is reported that the risk of MetS can be reduced by increasing PA levels and by engaging in balanced eating habits [
47‐
49]. In this study, we found that there are household-specific aspects to the PA levels and energy intake according to the presence or absence of MetS in young adults. This information can be used as a basis for preparing countermeasures through education on PA and nutrition, and by providing nutrition guidance for young adults with MetS according to the household type. Such practical measures are urgently needed to reduce the incidence of MetS among young Korean adults.
This study’s results should be interpreted with consideration of the following limitations. First, we evaluated young adults with MetS, but did not consider the timing of MetS development or the duration of MetS. Second, the amount of PA was not assessed using heart rate measurements or using an accelerometer, but was quantified based on survey findings, which are prone to errors. Third, this study reported simple differences without identifying the causality underlying the relationships between PA and nutrition. Finally, the data generated by using the 24-h-recall may not represent long-term dietary habits. Twenty-four-hour recall is essentially a retrospective method of diet assessment, where an individual is interviewed about their food and beverage consumption during the previous day or the preceding 24 h. However, a single 24-h-recall may not be representative of the habitual diet at an individual level. Accordingly, in this study, a total of 467 low-reporters and 47 over-reporters were found among females, and a total of 264 low-reporters and 62 over-reporters were found among males. Nevertheless, the strength of this study was that it analyzed the PA levels and energy intake of single-person households according to the prevalence of MetS among young adults for the first time. Most of the previous studies that investigated the relationship between metabolic syndrome, PA levels, and energy intake mainly targeted old adults. In particular, this study classified them by the types of households and investigated the PA levels and energy intake of single-person households. Therefore, our results can contribute to the ongoing research on the relationship between MetS and health behaviors.
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