Nutrient deficiency and physical inactivity in middle-aged adults with dynapenia and metabolic syndrome: results from a nationwide survey

Abstract

Background

This study examined the associations between dynapenia, metabolic syndrome (MetS), nutrient intake, and physical activity.

Methods

We used data from a cross-sectional study that included middle-aged men and women (40–64 years old) who participated in the Korea National Health and Nutrition Examination Survey (KNHANES) between 2014 and 2017. Patients (n = 4700) were categorized into four groups based on diagnosis of dynapenia and MetS: dynapenic MetS (DM), dynapenia alone (D), MetS alone (M), and non-dynapenia and non-MetS (NDNM). Dynapenia was defined as the lowest tertile of the BMI-adjusted handgrip strength. MetS was defined as central obesity plus two or more of the following features: elevated fasting plasma glucose, blood pressure, or triglycerides, or reduced HDL cholesterol. Nutrient intake and physical activity were assessed via questionnaires.

Results

In women, the DM group had a significantly lower intake of all nutrients except for total energy and carbohydrates compared to the NDNM group. In a model adjusted for age, osteoarthritis, and total energy intake, the DM group showed higher odds ratios (ORs) for not practicing resistance training (men: OR (95% confidence intervals (CI)) = 1.64 (1.22–2.20); women: OR (95% CI) = 2.26 (1.59–3.21)) and for engaging in physical activities below 600 metabolic equivalents of tasks per week (men: OR (95% CI) = 1.36 (1.05–1.78); women: OR (95% CI) = 1.29 (1.02–1.63)) than the NDNM group. The women in the DM group had significantly higher OR for leisure-related moderate (OR (95% CI) = 2.00 (1.49–2.68)) and vigorous (OR (95% CI) = 1.76 (1.10–2.82)) physical inactivity than in the NDNM group.

Conclusions

This study showed that the combination of dynapenia and MetS was associated with poor nutrient intake in women and low physical activity in both sexes. These findings provide a foundation for developing intervention strategies to address dynapenia and MetS.

Background

Muscle strength generally declines by 2–4% per year with age, and this loss occurs 2–5 times faster than the loss of muscle mass [1]. The primary causes of age-related decline in muscle strength include structural changes and damage to the nervous system, such as alterations in supraspinal centers, α-motor neuron excitability, antagonistic muscle activity, motor unit recruitment, and velocity coding, as well as musculoskeletal changes, such as reductions in fascicle length, tendon stiffness, and muscle density [2, 3]. In addition, lack of resistance training and insufficient protein intake can accelerate age-related decline in muscle strength. Furthermore, although decreased body weight and muscle mass are associated with decreased muscle strength, muscle strength can decline even if both body weight and muscle mass are maintained or increased [4]. Clark and Manini [3, 5] suggested that the loss of muscle mass and decline in muscle strength should be clearly distinguished and defined age-related decline in strength as “dynapenia,” which is a Greek word that means “loss of strength.” The decline in strength is an important variable in the diagnosis of physical geriatric syndromes such as sarcopenia [6] and frailty [7]. Muscle strength is assessed by measuring the handgrip strength (HGS). Reduced HGS is associated with nutrient deficiencies (particularly protein), obesity, disability, disease complications, and increased mortality. These associations between HGS and metabolic and disease conditions highlight a strong correlation between muscle strength decline and disease onset [8, 9].

Fatty infiltration of skeletal muscle causes inflammation, impaired leptin signaling, and mitochondrial dysfunction, which exacerbates muscle dysfunction and obesity, thereby increasing the risk of developing metabolic syndrome (MetS) [10]. A systematic review demonstrated that low HGS in older adults was linked to the development of MetS, particularly in abdominal obesity and insulin resistance [11]. A report published by the International Diabetes Federation [12] estimated global prevalence of MetS at 20–25% of the world’s adult population. The development of MetS is largely influenced by genetic susceptibility and aging; however, it is primarily caused by unhealthy lifestyle habits, such as physical inactivity and excessive consumption of foods high in fat and carbohydrates. These habits are likely to first lead to abdominal obesity, which subsequently increases the risk of developing insulin resistance, diabetes, hypertension, and hyperlipidemia [13, 14]. In addition, MetS is strongly associated with an increased incidence of cardiovascular disease (CVD) and higher mortality rates [15, 16].

Unhealthy lifestyle habits in middle age can accelerate the progression of MetS, turning it from an acute to a chronic condition in old age, making treatment and improvement increasingly difficult. Therefore, identifying the effects of the combination of dynapenia and MetS on nutrient intake and physical activity in middle-aged individuals can provide timely insights into the appropriate strategies for the treatment and improvement of both conditions before the onset of old age. To the best of our knowledge, no study has been conducted that investigated the effects of the combination of low muscle strength and MetS on nutrient intake and physical activity in middle-aged adults. Given our previous finding that dual comorbidities have a greater negative impact on health than a single comorbidity [17], we hypothesized that individuals with both dynapenia and MetS would demonstrate poorer nutrient intake and lower physical activity levels than those with either condition. Thus, the aim of this study was to investigate the effects of the combination of dynapenia and MetS on nutrient intake and physical activity in middle-aged Korean adults.

Methods

Study design and participants

The Korea National Health and Nutrition Examination Survey (KNHANES) is a study conducted by the Korean Ministry of Health and Welfare since 1998 that assesses the health and nutritional status of the non-institutionalized civilian population in Korea [18]. The survey is conducted using a representative sample of the Korean population selected through multistage cluster probability sampling. The KNHANES data are publicly available as anonymized digital data on the Korea Centers for Disease Control and Prevention (KCDC) website. The present study was conducted using data from the 6th (2013–2015) and 7th (2015–2018) survey cycles, specifically from 2014, 2015, and 2016.

Of the 23,080 participants included in the sixth and seventh KNHANES cycles, we extracted data from 8355 participants aged 40–64 years. A total of 3,655 participants were excluded from the analysis due to missing data from non-response or unmeasured variables in the KNHANES survey (including HGS, BMI, waist circumference, blood pressure, blood sampling, medical history, food intake, and physical activity). Additionally, individuals with extreme daily energy intake (≤ 500 kcal or ≥ 5000 kcal), which may lead to under- or overestimation in nutrient assessment, and pregnant women, whose data may be affected by physiological changes, were excluded. Ultimately, a total of 4700 participants (1860 men and 2840 women) were included in this study (Fig. 1).

Fig. 1.

Flow diagram for the study

The KNHANES was approved by the Institutional Review Board (IRB) of the KCDC, and written informed consent was obtained from all participants in accordance with the ethical principles outlined in the Declaration of Helsinki (IRB numbers: 6th cycle (2013-07CON-03-4C, 2013-12EXP-03-5C); 7th cycle (2018–01-03-P-A]). Ethical approval for the present study was obtained from the IRB of the National Agriculture and Food Research Organization (24-H044).

Measurements

Muscle strength

BMI was calculated as body weight (GL-6000–20; G-Tech International Co., Ltd., Gyeonggi-do, Korea) divided by height squared (seca 225; seca GmbH & Co. KG, Hamburg, Germany). HGS was measured using a digital dynamometer (TKK 5401; Takei Scientific Instruments Co., Ltd., Tokyo, Japan). The participants were instructed to stand with their feet hip-width apart and arms hanging naturally while facing straight ahead. During the measurement, the participants were asked to keep their elbows and wrists straight and to ensure that their arms did not touch their bodies. Each participant’s hands were alternately squeezed as hard as possible six times (three times each hand). In this study, HGS values were adjusted for BMI using the average of the maximum values for the right and left hands. Participants with amputations; fractures; paralysis of the arms, hands, or fingers; or those who had casts or bandages on their hands or wrists were excluded from the HGS measurements.

MetS

For the measurement of waist circumference, the participants were asked to lift their examination gowns to expose their bare torso, raise their arms comfortably, and stand upright with their feet together. The examiner measured waist circumference at the midpoint between the lower rib and the iliac crest without putting any pressure on the skin. Each measurement was recorded to the nearest 0.1 cm. Systolic and diastolic blood pressures were measured after at least 5 min of rest using a mercury sphygmomanometer (Baumanometer® Wall Unit 33 (0850); W.A. Baum Co., Inc., NY, USA). Each measurement was taken three times on the right upper arm with the participant seated.

Blood samples were collected from the median cubital vein or cephalic vein of each participant in the morning after they had fasted for at least 8 h. The blood sample in each tube in the mobile examination vehicle was preprocessed immediately after sample collection. The specimen transport box was kept refrigerated (2–8 °C) and delivered to the central analysis laboratory. All analyses were performed within 24 h of sample collection.

Total cholesterol (TC) and triglyceride (TG) levels were measured using enzymatic methods. The fasting plasma glucose (FPG) level was measured using the hexokinase UV method, whereas the high-density lipoprotein cholesterol (HDL-C) level was measured using the homogeneous enzymatic colorimetric method. Both FPG and HDL-C were measured utilizing an automated analyzer (Hitachi Automatic Analyzer 7600–210, Hitachi, Japan). The glycated hemoglobin (HbA1C) level was measured using high-performance liquid chromatography performed with an automated glycohemoglobin analyzer (Tosoh G8, Tosoh, Japan). Low-density lipoprotein cholesterol (LDL-C, mg/dL) was calculated using Friedewald’s method: LDL-C = TC − HDL-C − (TG/5) [19].

A history of diagnosis and treatment for type 2 diabetes, hypertension, dyslipidemia, and osteoarthritis, as well as smoking habits and alcohol consumption, was assessed using self-reported questionnaires.

Definitions of dynapenia and MetS

The diagnostic cut-off value for dynapenia (low muscle strength) have not yet been clearly established [20] and when diagnosing low muscle strength using HGS, international standards such as those from the European Working Group on Sarcopenia in Older People and Asian Working Group for Sarcopenia are commonly referenced. However, these criteria are based on individuals aged 65 and older, making them unsuitable for the study's target age group (40–64 years). Therefore, following previous studies on dynapenia, we defined dynapenia as the lowest tertile of BMI-adjusted HGS values [21, 22].

For MetS, we adhered to the International Diabetes Federation guidelines [12] for FPG, blood pressure, TG, and HDL-C. Abdominal obesity was defined using Korean waist circumference standards [23]. MetS was diagnosed when abdominal obesity (waist circumference ≥ 90 cm in men and ≥ 85 cm in women) cooccurred with at least two of the following: (1) elevated FPG (≥ 100 mg/dL) or previously diagnosed type 2 diabetes; (2) elevated systolic blood pressure (≥ 130 mmHg), diastolic blood pressure (≥ 85 mmHg), or treatment for previously diagnosed hypertension; (3) elevated TG (≥ 150 mg/dL); (4) low HDL-C (< 40 mg/dL in men, < 50 mg/dL in women) or a diagnosis of dyslipidemia by a physician with ongoing pharmacological treatment. Participants were then classified into four groups by dynapenia and MetS status: dynapenic MetS (DM), dynapenia alone (D), MetS alone (M), and non-dynapenia and non-MetS (NDNM).

Assessment of nutrient intake

The semi-quantitative Food Frequency Questionnaire (FFQ) estimates food and nutrient intake by assessing consumption frequency and average portion size. It has been validated and is widely used in large-scale epidemiological studies [24]. In this study, the FFQ developed by KNHANES was used to assess the frequency and quantity of food intake over the past year, allowing estimation of nutrient intake in the adult population of Korea [25]. The survey was conducted through face-to-face interviews conducted by trained interviewers and dietitians at the homes of the participants. Portion size per serving was demonstrated and explained using auxiliary tools such as measuring cups, measuring spoons, and two-dimensional models. The FFQ consists of 112 food items, nine frequency categories (three times a day, two times a day, once a day, 5–6 times a week, 2–4 times a week, once a week, 2–3 times a month, once a month, and rarely consumed), and three to four standard portion size categories (half of the standard portion (0.5), standard portion (1), one and a half times the standard portion (1.5), and double the standard portion (2)). For coffee and alcohol, if the consumption exceeded the preset categories, the frequency of intake and quantity consumed were recorded separately. For fruits, intake was distinguished based on whether they were consumed seasonally or year-round, with seasonal periods considered to be three months and converted to a year. Total nutrient intake was estimated by multiplying daily intake frequency by the portion size ratio and energy content for each item. Energy intake was calculated using the following formula: Kcal = daily intake frequency × portion size ratio × energy content per portion. The evaluated nutritional variables were as follows: total energy (kcal), protein (g), carbohydrate (g), fat (g), saturated fatty acids (SFA, g), monounsaturated fatty acids (MUFA, g), polyunsaturated fatty acids (PUFA, g), n-3 fatty acids (g), n-6 fatty acids (g), cholesterol (mg), fiber (g), calcium (mg), phosphorus (mg), iron (mg), sodium (mg), potassium (mg), vitamin A (μgRE), retinol (μg), carotene (μg), thiamine (mg), riboflavin (mg), niacin (mg), and vitamin C (mg).

Assessment of physical activity

Physical activity was assessed through a face-to-face interview performed using the Global Physical Activity Questionnaire (GPAQ), which was developed by the World Health Organization (WHO) [26]. The questionnaire records the frequency (days) and duration (h) of various types of physical activity, including work-related vigorous and moderate physical activity, leisure-related vigorous and moderate physical activity, walking, and resistance training, based on a typical week, while excluding weeks with unusual schedules. The interviewers explained to the participants that “vigorous physical activity” causes significant breathlessness or a very fast heartbeat, whereas “moderate physical activity” causes slight breathlessness or a moderately faster heartbeat. WHO 2020 physical activity guidelines [27] recommend that all adults engage in 150–300 min of moderate-intensity activity or 75–150 min of vigorous-intensity aerobic activity per week (equivalent to at least 600 metabolic equivalents of tasks; METs) to achieve health benefits. Following prior dose–response studies of physical activity and health outcomes [28], we calculated total METs using the following formula [29]: total METs (min/week) = ([vigorous physical activity days × vigorous physical activity min × 8.0 METs] + [moderate physical activity days × moderate physical activity min × 4.0 METs] + [walking days × walking min × 3.3 METs].

Statistical analyses

Owing to the non-normal distribution of characteristics and nutrient intake variables among the four groups, the non-parametric Kruskal–Wallis test was used for comparison of intergroup differences. The presence of osteoarthritis, smoking habits, alcohol consumption, and MetS were compared between the groups using the chi-square test. For multiple pairwise comparisons between each group, we applied the Dunn-Bonferroni correction as a post-hoc test for the Kruskal–Wallis analysis. In addition, post-hoc analysis of the chi-square test was performed with Bonferroni correction. Binary logistic regression analysis was performed to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for vigorous physical inactivity, moderate physical inactivity, not walking, not practicing resistance training, and achieving less than 600 METs in each group, with the NDNM group as the reference group.

To account for potential confounding factors and to ensure the validity of the observed associations between the coexistence of dynapenia and Mets with nutritional deficiencies and physical inactivity, covariates were deliberately selected based on evidence from previous epidemiological studies [17, 30]. The covariates included in the models were as follows: Model 1 included age and osteoarthritis; Model 2 included age, osteoarthritis, and total energy intake. For women, the number of participants who performed vigorous work-related physical activity (DM group, 0; D group, 5; M group, 2; NDNM group, 20) was uneven, making statistical comparisons between groups impossible. All statistical analyses were performed using SPSS version 29.0 (IBM Corp., Armonk, NY, USA), with the significance level set at p < 0.05.

Results

Characteristics of the participants

Comparison of the ages of the participants indicated that the men in the D and DM groups and the women in the DM group were the oldest of the other groups (Table 1). The heights of men and women in the M and NDNM groups, respectively, were higher than the heights of men and women in the other groups. In addition, the weights of male and female participants in the DM and M groups, respectively, were higher than those of participants in the other groups. The DM and M groups had the highest HbA1C levels of all the groups. The men in the M group had higher TC levels than those in the D and NDNM groups, whereas the women in the D group had significantly higher TC and LDL-C levels than those in the NDNM group. Alcohol consumption in the NDNM group was higher than that in the DM group. Smoking habits were more common among men in the NDNM group than among men in the D group. The prevalence of osteoarthritis among men and women was significantly higher in the DM group than in the other groups. Men and women in the DM and D groups, respectively, had lower BMI-adjusted HGS values than those in the other groups. In addition, the DM and D groups had a higher proportion of participants who met the cutoff values for MetS-related variables (central obesity, FPG, TG, and HDL-C), indicating a well-differentiated distribution among the four groups. However, there was no significant difference between the groups in terms of the proportion of participants who met the blood pressure cutoff values for MetS.

Table 1.

Participant characteristics categorized according to dynapenia and metabolic syndrome

Men		Dynapenic metabolic syndromea (n = 294)		Dynapenia aloneb (n = 326)		Metabolic syndrome alonec (n = 264)		Non-dynapenia and non-metabolic syndromed (n = 976)		p-value
Variables (Unit)		Median	(IQR: Q1-Q3)	Median	(IQR: Q1-Q3)	Median	(IQR: Q1-Q3)	Median	(IQR: Q1-Q3)
Age (year)		55.0	(48.0–60.0)c, d	56.0	(48.0–60.0)c, d	51.0	(45.0–57.0)a, b	52.0	(45.0–57.0)a, b	< 0.01
Height (cm)		169.8	(165.9–174.0)c, d	166.3	(162.9–170.5)a, c, d	173.1	(169.7–177.0)a, b	170.2	(166.5–174.1)a, b	< 0.01
Body weight (kg)		81.0	(75.0–86.9) b, d	67.4	(62.9–72.9)a, c	79.3	(74.6–85.5) b, d	67.1	(61.7–71.9)a, c	< 0.01
HbA1C (%)		5.9	(5.6–6.4)b, c, d	5.6	(5.4–5.9)a, c, d	5.8	(5.5–6.1) a, b, d	5.5	(5.3–5.8)a, b, c	< 0.01
TC (mg/dL)		196.5	(166.0–219.0)	191.5	(171.0–213.0)c	197.5	(177.0–225.0)b, d	192.0	(169.0–217.0)c	0.03
LDL-C (mg/dL)		111.8	(80.2–135.1)	115.7	(91.8–133.1)	112.4	(90.1–140.0)	114.0	(93.8–135.7)	0.21
HGS/BMI (kgf/(kg/m2))		1.39	(1.28–1.48)c, d	1.45	(1.34–1.52) c, d	1.73	(1.65–1.84)a, b, d	1.85	(1.71–2.02)a, b, c	< 0.01
†Central obesity (yes, n (%))		294 (100)b, d		36 (11.0)a, c, d		264 (100)b, d		49 (5.0)a, b, c		< 0.01
†Elevated FPG (yes, n (%))		217 (73.8)b, d		155 (47.5)a, c, d		180 (68.2)b, d		374 (38.3)a, b, c		< 0.01
†Elevated blood pressure (yes, n (%))		293 (99.7)		323 (99.1)		261 (98.9)		971 (99.5)		0.56
†Elevated TG (yes, n (%))		207 (70.4)b, d		146 (44.8)a, c		193 (73.1)b, d		383 (39.2)a, c		< 0.01
†Reduced HDL-C (yes, n (%))		158 (53.7)b, d		97 (29.8)a, c		129 (48.9)b, d		256 (26.2)a, c		< 0.01
†Alcohol consumption (yes, n (%))		230 (78.2)d		264 (81.0)		227 (86.0)		845 (86.6)a		< 0.01
†Smoking habits (yes, n (%))		101 (34.4)		94 (28.8)d		95 (36.0)		384 (39.3)b		< 0.01
†Osteoarthritis (yes, n (%))		19 (6.5)d		8 (2.5)		7 (2.7)		25 (2.6)a		< 0.01
Frequency ofresistance training	(not practiced, n (%))	219 (74.5)d		221 (67.8)		193 (73.1)d		631 (64.7)a, c		0.02
	(1 time/wk, n (%))	5 (1.7)d		14 (4.3)		11 (4.2)		62 (6.4)a
	(2–3 times/wk, n (%))	34 (11.6)		42 (12.9)		28 (10.6)		136 (13.9)
	(4–5 times/wk, n (%))	36 (12.2)		49 (15.0)		32 (12.1)		147 (15.1)
Women		Dynapenic metabolic syndromea (n = 383)		Dynapenia aloneb (n = 564)		Metabolic syndrome alone c (n = 228)		Non-dynapenia and non-metabolic syndrome d (n = 1665)		p-value
Variables (Unit)		Median	(IQR: Q1-Q3)	Median	(IQR: Q1-Q3)	Median	(IQR: Q1-Q3)	Median	(IQR: Q1-Q3)
Age (year)		56.0	(50.0–61.0)b, c, d	54.0	(47.0–59.0)a, d	53.0	(47.0–59.0)a, d	50.0	(44.0–56.0)a, b, c	< 0.01
Height (cm)		155.6	(152.2–158.8)c, d	154.8	(151.1–158.2)c, d	159.4	(155.6–162.9)a, b, d	158.0	(154.6–161.5)a, b, c	< 0.01
Body weight (kg)		67.6	(63.4–73.5) b, c, d	57.1	(52.6–62.2) a, c, d	66.5	(62.4–71.2)a, b, d	55.2	(51.0–59.4)a, b, c	< 0.01
HbA1C (%)		5.8	(5.5–6.2)b, d	5.6	(5.4–5.8)a, c, d	5.8	(5.5–6.2)b, d	5.5	(5.3–5.7)a, b, c	< 0.01
TC (mg/dL)		199.0	(174.0–225.0)	200.5	(177.0–223.0)d	198.5	(173.3–219.0)	195.0	(173.0–218.0)b	< 0.01
LDL-C (mg/dL)		119.3	(97.0–144.6)	122.9	(100.7–143.4)d	117.7	(96.7–139.0)	116.6	(98.1–138.9)b	0.03
HGS/BMI (kgf/(kg/m2))		0.83	(0.74–0.90)c, d	0.88	(0.81–0.94)c, d	1.09	(1.03–1.19)a, b, d	1.17	(1.08–1.29)a, b, c	< 0.01
†Central obesity (yes, n (%))		383 (100)b, d		74 (13.1)a, c, d		228 (100)b, d		74 (4.4)a, b, c		< 0.01
†Elevated FPG (yes, n (%))		228 (59.5)b, d		136 (24.1)a, c		128 (56.1)b, d		368 (22.1)a, c		< 0.01
†Elevated blood pressure (yes, n (%))		382 (99.7)		559 (99.1)		227 (99.6)		1651 (99.2)		0.60
†Elevated TG (yes, n (%))		219 (57.2)b, d		166 (29.4)a, c, d		132 (57.9)b, d		342 (20.5)a, b, c		< 0.01
†Reduced HDL-C (yes, n (%))		282 (73.6)b, d		244 (43.3)a, c, d		179 (78.5)b, d		598 (35.9)a, b, c		< 0.01
†Alcohol consumption (yes, n (%))		238 (62.1)d		372 (66.0)		144 (63.2)		1151 (69.1)a		0.03
†Smoking habits (yes, n (%))		15 (3.9)		22 (3.9)		17 (7.5)		63 (3.8)		0.07
†Osteoarthritis (yes, n (%))		91 (23.8)b, c, d		76 (13.5)a, d		30 (13.2)a, d		102 (6.1)a, b, c		< 0.01
Frequency of resistance training	(not practiced, n (%))	342 (89.3) b, d		464 (82.3) a		197 (86.4) d		1308 (78.6) a, c		< 0.01
	(1 time/wk, n (%))	4 (1.0) d		8 (1.4) d		4 (1.8)		60 (3.6) a, b
	(2–3 times/wk, n (%))	21 (5.5) d		50 (8.9)		18 (7.9)		156 (9.4) a
	(4–5 times/wk, n (%))	16 (4.2) b, d		42 (7.4) a		9 (3.9) d		141 (8.5) a, c

p-values from Kruskal–Wallis (K-W) test and † Chi-square test. Significantly different (p < 0.05) from the: ^a Dynapenic metabolic syndrome group, ^b Dynapenia group, ^c Metabolic syndrome group, and ^d Non-dynapenia and non-metabolic syndrome group

Post hoc tests for multiple pairwise comparisons between each group were performed using Kruskal–Wallis analysis with Dunn–Bonferroni correction and Chi-square test with Bonferroni correction. IQR interquartile range, Q quartile (Q1: 25th percentile, Q3: 75th percentile), HbA1C glycated hemoglobin, TC Total cholesterol, LDL-C low density lipoprotein cholesterol, HGS hand grip strength, BMI body mass index, FPG fasting plasma glucose, TG triglyceride, HDL-C high density lipoprotein cholesterol, n number of participants, wk week Cutoff criteria for each component of metabolic syndrome: Central obesity (waist circumference > 90 cm for men, > 85 cm for women), elevated FPG ≥ 100 mg/dL or previously diagnosed type 2 diabetes, elevated systolic blood pressure ≥ 130 mmHg or diastolic blood pressure ≥ 85 mmHg or treatment for previously diagnosed hypertension, elevated TG (≥ 150 mg/dL or specific treatment for this lipid abnormality, reduced HDL-C < 40 mg/dL in men, < 50 mg/dL in women or specific treatment for this lipid abnormality

Nutrient intakes

The total energy intake of the men in the D group was significantly lower than that of the men in the M group, whereas the women in the D group had a significantly lower energy intake than the women in the NDNM group (Table 2). The men in the D group had significantly lower protein and fat intake (including SFA, MUFA, PUFA, and n-3 and n-6 fatty acids) than the men in the M and NDNM groups. The women in the D and DM groups had significantly lower protein intakes than women in the NDNM group. Compared with the NDNM group, the M group had the highest fat intake (including SFA, MUFA, PUFA, n-3, and n-6 fatty acid cholesterol), followed by the D group and the DM group.

Table 2.

Comparison of nutrient intake according to dynapenia and metabolic syndrome

Men	Dynapenic metabolic syndromea (n = 294)		Dynapenia aloneb (n = 326)		Metabolic syndrome alone c (n = 264)		Non-dynapenia and non-metabolic syndrome d (n = 976)		p-value
Variables (Unit)	Median	(IQR: Q1-Q3)	Median	(IQR: Q1-Q3)	Median	(IQR: Q1-Q3)	Median	(IQR: Q1-Q3)
Total energy (kcal)	2091.5	(1656.8–2539.9)	1964.8	(1579.9–2403.5)c	2134.9	(1732.0–2668.5)b	2083.6	(1675.4–2487.2)	< 0.01
Protein (g)	61.3	(46.8–84.0)	56.8	(43.8–77.2)c, d	64.1	(47.6–82.3)b	63.1	(48.8–79.1)b	0.01
Carbohydrate (g)	325.0	(264.4–397.7)	317.0	(261.6–379.2)	333.1	(269.8–399.8)	331.3	(272.9–392.1)	0.12
Fat (g)	33.6	(21.0–48.7)	30.8	(19.4–45.5)c, d	36.1	(23.8–49.2)b	34.0	(24.0–48.6)b	< 0.01
SFA (g)	9.8	(6.3–14.3)	8.8	(5.4–13.2)c, d	10.1	(6.8–13.6) b	9.8	(6.8–13.9)b	< 0.01
MUFA (g)	10.4	(6.3–15.1)	9.3	(5.8–14.3)c, d	10.7	(7.0–14.8)b	10.4	(7.2–15.0)b	0.01
PUFA (g)	8.8	(6.0–12.8)	8.5	(5.2–11.9) c, d	9.6	(6.3–13.9)b	9.1	(6.4–12.7)b	< 0.01
n-3 FA(g)	1.1	(0.7–1.6)	1.0	(0.6–1.5)c, d	1.2	(0.8–1.7)b	1.1	(0.8–1.6)b	< 0.01
n-6 FA (g)	7.9	(5.3–11.3)	7.6	(4.7–10.7) c, d	8.6	(5.6–12.6)b	8.2	(5.6–11.2)b	< 0.01
Cholesterol (mg)	201.3	(126.5–322.5)	186.3	(107.7–292.4)	211.1	(126.1–319.0)	210.9	(132.1–309.1)	0.08
Fiber (g)	19.7	(14.7–26.5)	18.5	(13.2–24.1)	19.6	(15.0–27.2)	19.5	(14.8–24.8)	0.06
Calcium (mg)	437.8	(301.9–590.0)	401.5	(288.0–565.8)	450.1	(326.7–592.4)	437.5	(316.1–574.1)	0.07
Phosphorus (mg)	955.4	(738.5–1273.2)	900.7	(683.6–1177.4)c	988.4	(770.7–1266.0)b	968.7	(770.1–1208.1)	0.03
Iron (mg)	13.3	(10.3–17.7)	12.8	(9.2–16.8)c	14.0	(10.6–18.2)b	13.6	(10.6–17.0)	0.02
Sodium (mg)	3192.7	(2196.6–4418.7)b	2806.1	(1884.7–4090.1)a, c, d	3313.3	(2426.1–4368.5)b	3134.2	(2246.2–4084.1)b	< 0.01
Potassium (mg)	2550.6	(1942.2–3551.3)	2383.0	(1768.4–3281.6)d	2605.0	(2018.5–3447.1)	2604.5	(2050.0–3297.1)b	0.02
Vitamin A (μgRE)	515.2	(367.6–794.9)	499.9	(321.4–723.7)c, d	570.0	(400.1–782.9)b	558.8	(387.0–766.1)b	< 0.01
Retinol (μg)	63.5	(34.9–102.9)	58.9	(29.6–96.8)d	63.7	(38.1–102.7)	66.4	(40.0–102.8)b	0.05
Carotene (μg)	2672.7	(1846.5–4019.0)	2541.2	(1586.7–3729.2)c, d	2890.4	(1954.9–4097.8)b	2843.0	(1910.1–3925.7)b	< 0.01
Thiamine (mg)	1.73	(1.36–2.32)	1.67	(1.29–2.15)c	1.82	(1.42–2.31)b	1.79	(1.41–2.18)	0.04
Riboflavin (mg)	1.17	(0.84–1.65)	1.08	(0.76–1.58)c, d	1.27	(0.88–1.66)b	1.19	(0.88–1.60)b	< 0.01
Niacin (mg)	12.1	(9.3–17.1)	12.0	(8.9–15.9)c	13.2	(10.0–17.2)b	12.9	(9.9–16.2)	0.02
Vitamin C (mg)	77.83	(50.0–128.5)	80.88	(46.1–129.2)	82.43	(51.7–134.9)	87.06	(53.8–137.3)	0.20
Women	Dynapenic metabolic syndromea (n = 383)		Dynapenia aloneb (n = 564)		Metabolic syndrome alone c (n = 228)		Non-dynapenia and non-metabolic syndrome d (n = 1665)		p-value
Variables (Unit)	Median	(IQR: Q1-Q3)	Median	(IQR: Q1-Q3)	Median	(IQR: Q1-Q3)	Median	(IQR: Q1-Q3)
Total energy (kcal)	1543.3	(1210.5–1919.7)	1530.8	(1197.4–1929.3)d	1613.9	(1323.0–1943.1)	1639.5	(1300.3–2024.1)b	< 0.01
Protein (g)	48.6	(36.0–62.7)d	49.0	(38.5–64.8)d	52.0	(38.8–65.6)	53.7	(41.5–69.2)a, b	< 0.01
Carbohydrate (g)	275.1	(212.7–343.1)	264.0	(206.0–329.1)	274.4	(225.8–336.9)	274.1	(216.5–341.1)	0.13
Fat (g)	23.8	(14.9–34.8)b, d	26.8	(17.8–37.4)a, d	27.8	(17.3–39.0)d	29.8	(20.9–42.5)a, b, c	< 0.01
SFA (g)	6.6	(4.1–9.5)b, d	7.3	(4.8–10.9)a, d	7.8	(4.5–10.6)d	8.4	(5.6–11.9)a, b, c	< 0.01
MUFA (g)	7.0	(3.9–10.4)b, d	7.9	(5.1–11.3)a, d	7.9	(4.9–11.7)d	8.8	(6.0–12.9)a, b, c	< 0.01
PUFA (g)	6.8	(4.3–10.0)b, d	7.4	(5.2–11.0)a, d	7.6	(4.8–11.2)d	8.3	(6.0–11.9)a, b, c	< 0.01
n-3 FAs (g)	0.9	(0.5–1.3)d	0.9	(0.7–1.4)d	1.0	(0.7–1.4)	1.1	(0.7–1.5) a, b	< 0.01
n-6 FA (g)	5.9	(3.8–8.8)b, d	6.6	(4.5–9.7)a, d	6.7	(4.3–9.8)d	7.4	(5.3–10.5)a, b, c	< 0.01
Cholesterol (mg)	152.2	(80.3–243.2)b, d	171.4	(101.2–274.2)a, d	158.8	(87.5–265.3)d	193.2	(116.5–292.8)a, b, c	< 0.01
Fiber (g)	18.1	(13.6–23.9)d	18.9	(14.1–24.4)	19.5	(14.8–24.0)	19.9	(14.8–25.6) a	0.01
Calcium (mg)	368.3	(258.4–532.3)d	397.4	(282.5–546.5)	402.7	(281.4–560.1)	418.6	(304.1–565.9)a	< 0.01
Phosphorus (mg)	806.0	(596.2–1047.7)d	821.2	(640.4–1079.9)d	861.4	(657.7–1077.5)	877.8	(682.1–1105.6)a, b	< 0.01
Iron (mg)	11.6	(8.7–15.1)d	11.5	(9.0–15.0)d	12.4	(9.7–15.2)	12.5	(9.6–15.9)a, b	< 0.01
Sodium (mg)	2481.9	(1676.9–3435.1)d	2495.7	(1795.9–3469.4)d	2623.6	(1813.4–3614.6)	2687.9	(1983.4–3679.2)a, b	< 0.01
Potassium (mg)	2319.7	(1684.8–3169.9)d	2411.0	(1895.5–3357.4)	2512.8	(1965.0–3253.6)	2550.3	(1974.8–3318.9)a	< 0.01
Vitamin A (μgRE)	519.2	(321.2–711.4)d	526.9	(375.7–761.4)	561.3	(404.2–792.1)	566.4	(409.3–791.4)a	< 0.01
Retinol (μg)	51.4	(28.0–84.3)b, d	62.7	(34.3–100.2)a	55.3	(31.0–95.9)d	68.7	(41.0–104.7)a, c	< 0.01
Carotene (μg)	2690.3	(1690.9–3731.9)d	2640.7	(1875.7–4002.7)	2916.0	(1936.4–4113.3)	2849.0	(2010.7–4088.2)a	< 0.01
Thiamine (mg)	1.46	(1.16–1.89)d	1.49	(1.15–1.92)d	1.57	(1.25–1.91)	1.59	(1.25–2.00)a, b	< 0.01
Riboflavin (mg)	0.96	(0.65–1.37)d	1.04	(0.74–1.43)d	1.04	(0.74–1.43)	1.09	(0.80–1.48)a, b	< 0.01
Niacin (mg)	10.1	(7.5–13.1)d	10.4	(8.1–13.7)d	11.0	(8.5–14.1)	11.3	(8.8–14.5)a, b	< 0.01
Vitamin C (mg)	96.50	(54.2–159.3)b, d	110.41	(69.6–164.0)a	106.73	(62.0–164.7)	114.34	(72.6–174.6)a	< 0.01

p-values from Kruskal–Wallis (K-W) test. Significantly different (p < 0.05) from the: ^a Dynapenic metabolic syndrome group, ^b Dynapenia group, ^c Metabolic syndrome group, and ^d Non-dynapenia and non-metabolic syndrome group Post hoc tests for multiple pairwise comparisons between each group were performed Kruskal–Wallis analysis with Dunn–Bonferroni correction

IQR interquartile range, Q quartile (Q1: 25th percentile, Q3: 75th percentile), n number of participants, SFA saturated fatty acids, MUFA monounsaturated fatty acids, PUFA polyunsaturated fatty acids, FA fatty acids

The men in the D group had significantly lower phosphorus, iron, thiamine, and niacin intakes than the men in the M group and significantly lower potassium and retinol intakes than the men in the NDNM group. The vitamin A, carotene, and riboflavin intakes of the D group were significantly lower than those of the M and NDNM groups. Additionally, the sodium intake of the D group was significantly lower than that of the DM, M, and NDNM groups. The fiber, calcium, potassium, vitamin A, and carotene intakes of women in the DM group were significantly lower than those of women in the NDNM group. The phosphorus, iron, sodium, thiamine, riboflavin, and niacin intakes of the DM and D groups were significantly lower than those of the NDNM group. Additionally, the retinol and vitamin C intakes of the DM group were significantly lower than those of the D and NDNM groups.

Physical activity

Table 3 presents the ORs for physical inactivity in men and women. For leisure-related moderate physical inactivity, women in the DM group (Crude: OR (95% CI) = 2.21 (1.66–2.94); Model 1: OR (95% CI) = 2.00 (1.49–2.68); Model 2: OR (95% CI) = 2.00 (1.49–2.68)), the D group (Crude: OR (95% CI) = 1.42 (1.14–1.77); Model 1: OR (95% CI) = 1.33 (1.07–1.66); Model 2: OR (95% CI) = 1.32 (1.05–1.64)), and the M group (Crude: OR (95% CI) = 1.87 (1.33–2.64); Model 1: OR (95% CI) = 1.79 (1.27–2.52); Model 2: OR (95% CI) = 1.78 (1.26–2.52)) had significantly higher ORs than women in the NDNM group. However, there was no significant difference in leisure-related moderate physical inactivity between the groups among men participants.

Table 3.

Association between physical inactivity and the combination of dynapenia and metabolic syndrome

Men	Crude OR	(95% CI)	p-value	† Model 1 OR	(95% CI)	p-value	‡ Model 2 OR	(95% CI)	p-value
Work-related moderate physical inactivity
Non-dynapenia and non-metabolic syndrome		1.00 (reference)
Dynapenic metabolic syndrome	1.03	(0.67–1.58)	0.90	0.93	(0.60–1.44)	0.75	0.96	(0.62–1.48)	0.85
Dynapenia	1.35	(0.86–2.11)	0.20	1.20	(0.76–1.89)	0.44	1.19	(0.75–1.87)	0.46
Metabolic syndrome	0.88	(0.57–1.34)	0.55	0.88	(0.57–1.35)	0.57	0.90	(0.59–1.38)	0.63
Work-related vigorous physical inactivity
Non-dynapenia and non-metabolic syndrome		1.00 (reference)
Dynapenic metabolic syndrome	0.67	(0.29–1.56)	0.36	0.59	(0.25–1.38)	0.22	0.62	(0.26–1.46)	0.27
Dynapenia	1.21	(0.44–3.28)	0.71	1.03	(0.38–2.83)	0.95	1.02	(0.37–2.80)	0.97
Metabolic syndrome	0.69	(0.29–1.67)	0.41	0.69	(0.29–1.68)	0.42	0.71	(0.29–1.73)	0.46
Leisure-related moderate physical inactivity
Non-dynapenia and non-metabolic syndrome		1.00 (reference)
Dynapenic metabolic syndrome	1.17	(0.88–1.54)	0.27	1.10	(0.83–1.46)	0.50	1.12	(0.85–1.49)	0.42
Dynapenia	1.26	(0.96–1.65)	0.09	1.17	(0.89–1.54)	0.25	1.16	(0.89–1.53)	0.28
Metabolic syndrome	1.03	(0.77–1.37)	0.86	1.03	(0.77–1.37)	0.83	1.05	(0.79–1.40)	0.75
Leisure-related vigorous physical inactivity
Non-dynapenia and non-metabolic syndrome		1.00 (reference)
Dynapenic metabolic syndrome	1.45	(1.02–2.06)	0.04	1.30	(0.91–1.86)	0.15	1.35	(0.94–1.92)	0.10
Dynapenia	1.27	(0.92–1.76)	0.15	1.12	(0.80–1.55)	0.51	1.10	(0.79–1.54)	0.56
Metabolic syndrome	1.18	(0.84–1.67)	0.35	1.19	(0.84–1.69)	0.32	1.22	(0.86–1.73)	0.26
Not walking
Non-dynapenia and non-metabolic syndrome		1.00 (reference)
Dynapenic metabolic syndrome	1.28	(0.92–1.79)	0.15	1.26	(0.90–1.76)	0.19	1.28	(0.91–1.79)	0.15
Dynapenia	1.35	(0.98–1.86)	0.06	1.32	(0.96–1.83)	0.09	1.31	(0.95–1.81)	0.10
Metabolic syndrome	1.07	(0.75–1.54)	0.71	1.07	(0.75–1.54)	0.70	1.09	(0.76–1.57)	0.64
Not practicing resistance training
Non-dynapenia and non-metabolic syndrome		1.00 (reference)
Dynapenic metabolic syndrome	1.60	(1.19–2.14)	< 0.01	1.61	(1.20–2.16)	< 0.01	1.64	(1.22–2.20)	< 0.01
Dynapenia	1.15	(0.88–1.50)	0.30	1.16	(0.89–1.52)	0.27	1.15	(0.88–1.51)	0.30
Metabolic syndrome	1.49	(1.10–2.01)	0.01	1.49	(1.10–2.01)	0.01	1.51	(1.11–2.04)	< 0.01
< 600 METs (min/week)
Non-dynapenia and non-metabolic syndrome		1.00 (reference)
Dynapenic metabolic syndrome	1.37	(1.05–1.78)	0.02	1.34	(1.03–1.75)	0.03	1.36	(1.05–1.78)	0.02
Dynapenia	1.24	(0.97–1.60)	0.09	1.20	(0.93–1.55)	0.15	1.19	(0.92–1.54)	0.18
Metabolic syndrome	0.88	(0.67–1.15)	0.35	0.88	(0.67–1.16)	0.36	0.89	(0.68–1.17)	0.41
Women	Crude OR	(95% CI)	p-value	† Model 1 OR	(95% CI)	p-value	‡ Model 2 OR	(95% CI)	p-value
Work-related moderate physical inactivity
Non-dynapenia and non-metabolic syndrome		1.00 (reference)
Dynapenic metabolic syndrome	1.26	(0.82–1.93)	0.29	1.07	(0.69–1.67)	0.76	1.07	(0.69–1.67)	0.76
Dynapenia	1.13	(0.79–1.60)	0.50	1.00	(0.70–1.44)	0.98	1.00	(0.70–1.43)	0.99
Metabolic syndrome	1.18	(0.70–2.00)	0.53	1.09	(0.64–1.85)	0.74	1.09	(0.64–1.85)	0.75
Leisure-related moderate physical inactivity
Non-dynapenia and non-metabolic syndrome		1.00 (reference)
Dynapenic metabolic syndrome	2.21	(1.66–2.94)	< 0.01	2.00	(1.49–2.68)	< 0.01	2.00	(1.49–2.68)	< 0.01
Dynapenia	1.42	(1.14–1.77)	< 0.01	1.33	(1.07–1.66)	0.01	1.32	(1.05–1.64)	0.02
Metabolic syndrome	1.87	(1.33–2.64)	< 0.01	1.79	(1.27–2.52)	< 0.01	1.78	(1.26–2.52)	< 0.01
Leisure-related vigorous physical inactivity
Non-dynapenia and non-metabolic syndrome		1.00 (reference)
Dynapenic metabolic syndrome	2.13	(1.35–3.35)	< 0.01	1.76	(1.10–2.81)	0.02	1.76	(1.10–2.82)	0.02
Dynapenia	1.70	(1.19–2.42)	< 0.01	1.50	(1.05–2.16)	0.03	1.49	(1.04–2.13)	0.03
Metabolic syndrome	1.98	(1.13–3.47)	0.02	1.81	(1.03–3.19)	0.04	1.81	(1.03–3.19)	0.04
Not walking
Non-dynapenia and non-metabolic syndrome		1.00 (reference)
Dynapenic metabolic syndrome	1.32	(0.98–1.76)	0.07	1.27	(0.94–1.73)	0.12	1.27	(0.94–1.72)	0.12
Dynapenia	1.00	(0.76–1.31)	1.00	0.98	(0.75–1.29)	0.89	0.97	(0.74–1.28)	0.84
Metabolic syndrome	1.33	(0.92–1.91)	0.12	1.31	(0.91–1.88)	0.15	1.30	(0.91–1.88)	0.15
Not practicing resistance training
Non-dynapenia and non-metabolic syndrome		1.00 (reference)
Dynapenic metabolic syndrome	2.28	(1.61–3.21)	< 0.01	2.26	(1.59–3.22)	< 0.01	2.26	(1.59–3.21)	< 0.01
Dynapenia	1.27	(0.99–1.62)	0.06	1.26	(0.99–1.62)	0.06	1.26	(0.98–1.61)	0.07
Metabolic syndrome	1.73	(1.17–2.58)	< 0.01	1.73	(1.16–2.58)	< 0.01	1.73	(1.16–2.57)	< 0.01
< 600 METs (min/week)
Non-dynapenia and non-metabolic syndrome		1.00 (reference)
Dynapenic metabolic syndrome	1.32	(1.06–1.65)	0.01	1.29	(1.03–1.63)	0.03	1.29	(1.02–1.63)	0.03
Dynapenia	1.17	(0.97–1.42)	0.10	1.15	(0.95–1.40)	0.15	1.14	(0.94–1.39)	0.18
Metabolic syndrome	1.16	(0.88–1.53)	0.30	1.15	(0.87–1.51)	0.34	1.14	(0.86–1.51)	0.35

P-value from the Binomial logistic regression analysis, OR Odds ratios, 95% CI 95% Confidence intervals, MET metabolic equivalent of task, ^†Model 1: Adjusted for age and osteoarthritis, ^‡Model 2: Adjusted for age, osteoarthritis, and total energy intake

Regarding leisure-related vigorous physical inactivity, the crude OR for men in the DM group compared to the NDNM group was 1.45 (95% CI: 1.02–2.06). In addition, the ORs for women in the DM group (Crude: OR (95% CI) = 2.13 (1.35–3.35); Model 1: OR (95% CI) = 1.76 (1.10–2.81); Model 2: OR (95% CI) = 1.76 (1.10–2.82)), the D group (Crude: OR (95% CI) = 1.7 (1.19–2.42); Model 1: OR (95% CI) = 1.50, (1.05–2.16); Model 2: OR (95% CI) = 1.49 (1.04–2.13)), and the M group (Crude: OR (95% CI) = 1.98 (1.13–3.47); Model 1: OR (95% CI) = 1.81 (1.03–3.19), Model 2: OR (95% CI) = 1.81 (1.03–3.19))were significantly higher than that of women in the NDNM group.

Regarding not practicing resistance training, the men in the DM group (Crude: OR (95% CI) = 1.60 (1.19–2.14); Model 1: OR (95% CI) = 1.61 (1.20–2.16); Model 2: OR (95% CI) = 1.64 (1.22–2.20)) and the M group (Crude: OR (95% CI) = 1.49 (1.10–2.01); Model 1: OR (95% CI) = 1.49 (1.10–2.01); Model 2: OR (95% CI) = 1.51 (1.11–2.04)) had higher ORs than the men in the NDNM group. In addition, the ORs for women in the DM group (Crude: OR (95% CI) = 2.28 (1.61–3.21); Model 1: OR (95% CI) = 2.26 (1.59–3.22); Model 2: OR (95% CI) = 2.26 (1.59–3.21)) and the M group (Crude: OR (95% CI) = 1.73 (1.17–2.58); Model 1: OR (95% CI) = 1.73 (1.16–2.58); Model 2: OR (95% CI) = 1.73 (1.16–2.57)) were higher than that of women in the NDNM group.

Regarding achieving < 600 METs (min/week), both men (Crude: OR (95% CI) = 1.37 (1.05–1.78); Model 1: OR (95% CI) = 1.34 (1.03–1.75); Model 2: OR (95% CI) = 1.36 (1.05–1.78)) and women (Crude: OR (95% CI) = 1.32 (1.06–1.65); Model 1: OR (95% CI) = 1.29 (1.03–1.63); Model 2: OR (95% CI) = 1.29 (1.02–1.63)) in the DM group had significantly higher ORs than those in the NDNM group.

Discussion

In this study, the combination of dynapenia and MetS was associated with poor nutritional status only in women, whereas the risk of physical inactivity was significantly higher in both men and women. Energy imbalance due to inadequate nutrient intake and reduced physical activity contributes to the onset of MetS and impaired protein homeostasis in skeletal muscle. Muscle protein synthesis is stimulated by dietary amino acids and physical activity, while insufficient protein intake inhibits muscle protein synthesis, weakens muscle function, and exacerbates chronic diseases [31, 32]. Conversely, excessive protein intake (> 35% of total energy or > 5 g/kg/day) may lead to hyperaminoacidemia, hyperinsulinemia, and hyperammonemia [33]. According to a meta-analysis, the minimum recommended dietary allowance of protein needed to maintain nitrogen balance in healthy young adults is 0.8 g/kg/day [34]; our calculations indicated that women in the DM group consumed approximately 5.5 g less protein than recommended. A previous study suggested that consuming 25–30 g of high-quality protein per meal (75–90 g/day) is ideal for maximizing muscle protein synthesis [35]. The D and DM groups consumed significantly less protein than that consumed by the NDNM group (D: men 56.8 g, women 49.0 g; DM: women 48.6 g). Insufficient protein intake was more closely linked to dynapenia than to MetS, particularly in women. The recommended protein intake for improving muscle function is 1.0–1.2 g/kg/day for healthy older adults, 1.2–1.5 g/kg/day for individuals with chronic diseases, and up to 2.0 g/kg/day for those with severe illnesses or malnutrition [36]. Therefore, consuming an appropriate amount of high-quality protein based on an individual's health status, along with physical activity, will improve skeletal muscle function, enhance insulin sensitivity, and reduce white adipose tissue accumulation, thereby reducing the risk of developing MetS [37].

Fat infiltration of skeletal muscle reduces insulin sensitivity, promotes inflammation, and diminishes muscle strength [38]. Excessive SFA intake raises TC, LDL-C, and blood pressure and induces insulin resistance, thereby increasing the risk of MetS and CVD [39, 40]. Replacing SFA with MUFA or PUFA may be more effective for preventing MetS and CVD than simply reducing overall fat intake [41]. However, while higher vegetable fat intake may reduce MetS risk, no clear links have been observed between individual fat types (SFA, PUFA, or MUFA) or cholesterol and MetS [42]. Data from KNHANES showed that individuals with MetS consumed a higher proportion of energy from carbohydrates and less from fat compared to healthy controls [43]. In the present study, men in the M group consumed more total fat than women, while carbohydrate intake did not differ by sex. Interestingly, women in the DM group had the lowest total fat intake, suggesting that, despite coexisting dynapenia and MetS, their dietary habits were driven more by dynapenia-related malnutrition than by the overeating tendencies linked to MetS. Discrepancies among previous studies may reflect differences in dietary patterns due to factors such as race, age, education, and socioeconomic status [43].

Micronutrients, including vitamins C, D, and E and carotenoids, improve muscle strength by regulating protein metabolism and neuromuscular function, particularly through controlling oxidative stress and reducing inflammation [44–48]. Increased inflammation and oxidative stress also contribute to obesity, insulin resistance, and MetS [48]. In this study, women with both dynapenia and MetS consumed significantly fewer micronutrients than other participants, highlighting the link between micronutrient intake, muscle function, and MetS. Vitamin C’s antioxidant and anti-inflammatory effects help prevent muscle damage and enhance muscle mass and strength [47], and high vitamin C intake combined with physical activity can reduce MetS risk [49]. Vitamin A, obtained from animal-based foods, plays a key role in metabolism, immune function, and tissue differentiation [50], and higher intakes of vitamins A and C have been associated with reduced MetS risk in women but not in men [51]. Consistent with these findings, women in the DM group had significantly lower retinol and vitamin C intake. Conversely, men in the DM and M groups had elevated sodium intake, a factor linked to obesity, hypertension [52], insulin resistance, dyslipidemia, and MetS [53]. Importantly, none of the participants exceeded the recommended daily sodium intake (6000 mg) for hypertension prevention [54].

Sex-specific differences emerged in this study, likely ascribed to physiological variations between men and women. Women typically have a higher body fat percentage and lower muscle mass than men. Moreover, women primarily rely on lipid metabolism for energy during physical activity, whereas men depend more on carbohydrates [55, 56]. As women age, declining estrogen levels and increased oxidative stress accelerate losses of muscle mass and bone density more rapidly than in men [57]. Menopausal hormonal changes, particularly reduced estrogen levels, are associated with decreased energy and protein intake and increased appetite, potentially contributing to muscle loss and nutritional deficiencies [58]. Sociobehavioral factors may further influence these differences: women often engage in dietary restraint behaviors influenced by social norms emphasizing thinness and health consciousness, resulting in low energy and protein intake [59]. Individuals with dynapenic-abdominal obesity, particularly those with a thin body type, tend to have a lower dietary intake than that of those with generalized obesity. The reduced nutrient intake observed among women in the DM and D groups suggests that their dietary patterns reflect dynapenia more than MetS. Therefore, a balanced diet that ensures sufficient intake of macronutrients, such as protein and fat, as well as micronutrients, should be considered when addressing the nutrient deficiencies in women with the combination of dynapenia and MetS and in both men and women with dynapenia.

The combination of physical activity with adequate nutrient intake or dietary modifications is considered the most effective strategy for improving muscle strength [60] and alleviating MetS [61]. Inactivity and sedentary behavior significantly increase the risk of serious diseases, such as heart disease, diabetes, and MetS, contributing to heightened mortality rates [62]. In the present study, both men and women in the DM and M groups showed a high risk of not engaging in resistance training and exhibited low physical activity levels (< 600 METs/week). These findings highlight the strong association between MetS and inactivity, underscoring the need for increased physical activity to manage both dynapenia and MetS. While moderate exercise generally benefits health, different exercise types and intensities may have distinct effects on dynapenia and MetS. While age-related declines in muscle strength are inevitable, high-intensity resistance training, performed 2–3 times per week, has been shown to significantly enhance muscle mass, strength, and insulin sensitivity in older adults [63]. Specifically, resistance training targets type II muscle fibers, which are most susceptible to age-related atrophy, while aerobic exercise primarily improves cardiovascular and metabolic health [63, 64]. A cross-sectional study in middle-aged adults found that both moderate and vigorous physical activities, including brisk walking, cycling, and jogging, reduce MetS risk, with greater benefits observed at higher intensities [64]. Resistance exercise, in particular, stimulates muscle protein synthesis more effectively than aerobic exercise, thereby improving muscle mass, strength, and insulin sensitivity [65]. Engaging in approximately 60 min of moderate-intensity physical activity daily, or combining resistance and aerobic exercises, can alleviate insulin resistance, improve adipokine profiles (e.g., adiponectin and leptin), and prevent obesity and MetS [61]. In line with this, a previous study reported that 0–500 MET-minutes per week of moderate-intensity activity reduced MetS prevalence by 15.5%, while the same amount of vigorous-intensity activity led to a 37.1% reduction [66]. Interventions combining resistance and aerobic exercise may be particularly beneficial for individuals at risk of dynapenia and MetS. In this study, men in the DM group showed increased risk of vigorous leisure inactivity, whereas women in the DM, M, and D groups faced high risks of both moderate and vigorous leisure inactivity. These associations remained significant after adjusting for age, osteoarthritis, and total energy intake. Our results, consistent with previous research, show that the effects of physical activity on dynapenia and MetS depend on exercise intensity and frequency. Notably, physical inactivity was significantly associated not only with the combined condition (DM) but also with dynapenia alone (D) and MetS alone (M), a different perspective, this may indicate that differences in sample sizes across these groups could have affected the statistical power. Future studies with larger and more balanced sample sizes are needed to confirm these findings. Taken together, these findings highlight that structured resistance training paired with regular aerobic exercise in enhancing muscle function and metabolic health. Moreover, engaging in even moderate physical activity, rather than a sedentary lifestyle, is essential for preventing and managing dynapenia and MetS.

The main strength of this study is the use of data from a large-scale epidemiological survey (KNHANES) conducted by the Korean Ministry of Health and Welfare, which enabled the examination of the association between the combination of dynapenia and MetS with nutrient intake and physical activity in middle-aged individuals. However, this study has several limitations. First, although KNHANES used a complex, multistage stratified cluster sampling design with appropriate weights to ensure national representativeness, the population was limited to middle-aged adults in Korea; thus, generalizability to other countries with different demographic, cultural, or ethnic backgrounds is uncertain. Future studies should include participants from diverse age groups and ethnicities to validate and extend these findings. Second, nutrient intake was estimated via FFQ covering the past year, which may introduce recall bias despite expert interviews; memory errors regarding food types, quantities, and frequencies cannot be completely ruled out. We chose the FFQ because dynapenia and MetS are influenced more by long-term dietary patterns than by short-term intake; nonetheless, future research using alternative dietary assessment tools is needed to evaluate short-term effects. Third, physical activity was assessed using the WHO-validated GPAQ [67], but as a self-reported measure, it remains vulnerable to response bias, duplicate reporting, and multicollinearity despite providing clear examples. Future studies should incorporate one-on-one interviews or objective tools (e.g., accelerometers for step counts) to obtain more precise activity data and bolster validity. Fourth, LDL-C levels were estimated using the Friedewald equation, which can be inaccurate when triglycerides exceed 400 mg/dL; direct measurement from blood samples is recommended to improve accuracy. Fifth, the cross-sectional design precludes causal inference between dynapenia and MetS; longitudinal studies are required to clarify their causal relationships.

Conclusions

This study demonstrated that the combination of dynapenia and MetS is associated with significantly lower overall nutrient intake, excluding total energy and carbohydrate intakes, in women only. In addition, this study demonstrated that the combination of dynapenia and MetS was significantly associated with the risk of physical inactivity. Specifically, the combination of dynapenia and MetS was linked to a higher risk of not practicing resistance training, leisure-related vigorous physical inactivity, and physical activity below 600 METs per week in both men and women. Moreover, an increased risk of leisure-related moderate physical inactivity was also observed in women only. Additionally, this study showed that dynapenia alone was associated with poorer nutrient intake than MetS alone. Furthermore, the results showed that individuals with MetS had a significantly higher risk of physical inactivity than those with dynapenia. The findings of this study will help facilitate the development of intervention programs aimed at preventing and improving comorbidities diagnosed based on low muscle strength, such as dynapenia, sarcopenia, frailty, and MetS, with an emphasis on balanced energy intake and physical activity. Additionally, the findings of this study can serve as foundational data for the conceptualization of future longitudinal studies aimed at examining the causal relationship between dynapenia and MetS.

Abbreviations

MetS

Metabolic syndrome

OR

Odds ratios

CI

Confidence intervals

HGS

Handgrip strength

CVD

Cardiovascular disease

KNHANES

Korea national health and nutrition examination survey

KCDC

Korea centers for disease control and prevention

BMI

Body mass index

IRB

Institutional review board

TC

Total cholesterol

TG

Triglyceride

FPG

Fasting plasma glucose

HDL-C

High-density lipoprotein cholesterol

HbA1C

Glycated hemoglobin

LDL-C

Low-density lipoprotein cholesterol

FFQ

Food frequency questionnaire

SFA

Saturated fatty acids

MUFA

Monounsaturated fatty acids

PUFA

Polyunsaturated fatty acids

GPAQ

Global physical activity questionnaire

WHO

World health organization

METs

Metabolic equivalents of tasks

DM

Dynapenic MetS

D

Dynapenia alone

M

MetS alone

NDNM

Non-dynapenia and non-MetS

Authors' contributions

Mijin Kim: Conceptualization, Data curation, Methodology, Visualization, Writing - original draft. Toshiro Kobori: Conceptualization, Supervision, Validation, Project administration, Writing - review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by a Grant-in-Aid for Scientific Research from Japan (grant number 23K16784).

Data availability

The datasets used in this study can be accessed through Korean National Health and Nutrition and Examination Survey of the Korea Centers for Disease Control and Prevention at https://knhanes.kdca.go.kr/knhanes/eng/main.do.

Declarations

Ethics approval and consent to participate

The study was conducted in accordance with the principles of the Declaration of Helsinki and approved by the IRBs of the KCDC (IRB numbers for the 6th cycle: 2013-07CON-03-4C, 2013-12EXP-03-5C; IRB number for the 7th cycle [2018–01-03-P-A]) and the National Agriculture and Food Research Organization (24-H044). Informed consent was obtained from all subjects involved in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.