Comparison of Absolute and Relative Grip Strength to Predict Incidence of Metabolic Syndrome: Eight-Year Follow-Up Study in Korea

Abstract

Background:

This study aimed to conduct an analysis of longitudinal study to investigate the association of absolute grip strength, and relative grip strength with incidence of metabolic syndrome.

Materials and Methods:

Participants who participated in the Korean Genome and Epidemiology Study, a chronic screening program conducted in Ahnseong-si, Gyeonggi-do, a primary survey conducted from 2013 to 2014 were selected. The presence of metabolic syndrome was classified using the standards of the International Diabetes Foundation following previous studies. Grip strength was measured using a JAMA 5030J1 (Saehan, Korea) and calculated the absolute grip strength and relative grip strength. To evaluate the relationship between the absolute grip strength, relative grip strength, and incidence of metabolic syndrome, independent hazard ratios (HRs) and 95% confidence intervals (CIs) for metabolic syndrome were calculated according to absolute and relative grip strength levels using a multivariate extended Cox regression model.

Results:

The incidence of metabolic syndrome was reduced by 38% (HR = 0.62, 95% CI = 0.43–0.88) for the high absolute grip strength group, compared to the low absolute grip strength group. Also, this study confirmed that the incidence of metabolic syndrome for mid relative grip strength and high relative grip strength groups were reduced by 27% (HR = 0.73, 95% CI = 0.55–0.98) and 55% (HR = 0.45, 95% CI = 0.32–0.64) respectively. Moreover, the incidence of metabolic syndrome was reduced by 45% (HR = 0.55, 95% CI = 0.37–0.82) and 57% (HR = 0.43, 95% CI = 0.29–0.65) for the low-level body mass index (BMI) group with high or low absolute grip strength, respectively. Finally, this study confirmed the association of sex, absolute grip strength, and relative grip strength according to age with incidence of metabolic syndrome was different.

Conclusion:

We observed that relative grip strength has a higher association with incidence of metabolic syndrome than absolute grip strength. Also, BMI has a higher association with metabolic syndrome than the absolute grip strength.

Introduction

Metabolic syndrome is closely associated with obesity and type 2 diabetes.¹ Also, it functions as a risk indicator for cardiovascular disease and has an impact on the incidence of cardiovascular disease and all-cause mortality worldwide.² According to National Health and Nutrition Examination Survey, metabolic syndrome prevalence of adults (age over 20) from 2017 to 2018 was 38.3%. The percentage of metabolic syndrome prevalence in male was 38.8% and the percentage of female was 37.7%. Also, the percentage of Asians was 31.2%.³ According to the national study from Korea, 69.8% have at least one risk factor of metabolic syndrome and 20.6% were diagnosed as metabolic syndrome (three to five risk factors). The prevalence of metabolic syndrome for male was higher than female 23% and 18%, respectively.⁴

Metabolic syndrome is known to be caused by complex factors. Grip strength is closely associated with metabolic syndrome, and its impact on metabolic syndrome has been a topic of research interest.⁵ Grip strength reflects the current physical fitness status and it is used as a marker indicating a reduction in the risk of diabetes with participation in repetitive exercise.⁶

On the contrary, sarcopenia, which refers to a decrease in muscle mass and strength, is related to metabolic syndrome due to the interaction among oxidative stress, mitochondrial dysfunction, and insulin resistance.⁷ However, recent studies adopted the method of normalizing muscle strength by body mass index (BMI, kg/m²) to evaluate muscle strength independent of body weight as muscle strength proportionally increases with body weight.⁸ According to previous studies, relative strength adjusted for body weight has been reported to excel in predicting disease states compared to absolute grip.⁹ Another study has also shown that relative grip strength is closely associated with the risk factors of cardiovascular diseases. Particularly, relative grip strength (measured grip strength divided by BMI) is a useful predictive factor for identifying the incidence of metabolic syndrome associated with decreased muscle mass.¹⁰

Research on the association between grip strength and metabolic syndrome has been consistently conducted. However, studies comparing the differences between absolute and relative grip strength in relationship to the incidence of metabolic syndrome are limited.¹¹ Previous studies have reported different associations of absolute grip strength and relative grip strength with the risk of metabolic syndrome.¹¹ However, the study could not establish a causal relationship between grip strength and metabolic syndrome as it was a cross-sectional study. Another previous study reported that relative grip strength, adjusted by BMI, had a higher correlation with metabolic syndrome compared to absolute grip strength.¹² However, it is unclear whether BMI level or absolute grip strength level is more important in reducing the incidence of metabolic syndrome associated with increased relative grip strength.

Therefore, this study aimed to conduct an analysis of longitudinal study to investigate the association of absolute grip strength and relative grip strength according to gender, age with incidence of metabolic syndrome. Also, this study will investigate if there is a relationship of interaction between absolute grip strength level and BMI level with incidence of metabolic syndrome.

Materials and Methods

Study design and population

The study analyzed data from the Korean Genome and Epidemiology Study (KoGES), a large-scale cohort investigation, aimed at preventing chronic diseases such as diabetes, hypertension, osteoporosis, obesity, and metabolic syndrome by investigating health and lifestyle information of Koreans.¹³ This study targeted general adults who participated in the KoGES community-based cohort study. The study selected individuals aged 51 to 81, residing in Anseong City, Gyeonggi Province, for the second follow-up survey conducted between 2017 and 2018, following the baseline survey conducted in 2013–2014.

A total of 4,814 participants were recruited using various methods such as telephone, mail, and home visits. Among them, 1,074 individuals with metabolic syndrome (n = 1,056) or cardiovascular diseases (n = 18) and 774 participants who did not complete the second follow-up were excluded, leaving 2,966 subjects for the study. Again 2,030 individuals with missing variables influencing metabolic syndrome and grip strength were further excluded, resulting in a final sample of 936 participants. This study protocol received approval from the Institutional Review Boards of Korea University College of Medicine Ansan Hospital, the implementing institution for the community-based survey, and Seoul National University. The research objectives and details were explained to the participants. Subsequently, participants provided their informed consent by signing the research participation form (IRB No. E2112/001-009).

Metabolic syndrome

The presence of metabolic syndrome was classified according to the joint interim statement of the International Diabetes Federation criteria, based on previous studies. Central obesity (waist circumference ≥90 cm for male and ≥85 cm for female, in the case of Koreans), elevated triglycerides (≥150 mg/dL), reduced high-density lipoprotein (HDL) cholesterol (HDL <40 mg/dL for male and <50 mg/dL for female), elevated blood pressure (systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg or under antihypertensive treatment), and elevated fasting glucose (fasting blood glucose ≥100 mg/dL or under diabetes treatment) were considered as five factors. Participants having three or more of these factors were considered to have metabolic syndrome.¹⁴

Muscle strength

The grip strength test (measured in kilograms) is a relatively simple method with prompt results, and it is highly correlated with other measures of muscle strength. The JAMA 5030J1 dynamometer (Saehan, Korea) was used to measure the grip strength. Participants were seated in a chair with arms at a 90-degree angle while measuring grip strength. Three measurements were taken for both left and right hands, and the mean value was recorded. Following prior research that explicitly indicated the effectiveness of BMI-adjusted relative grip strength over absolute grip strength in predicting chronic diseases, the calculated absolute grip strength was converted into relative grip strength by dividing it by BMI (kg/m²) for use in analysis.¹⁵ The level of absolute and relative handgrip strength was categorized into three quantiles by gender.

To further examine the interaction between relative grip strength and obesity, we divided relative grip strength into two quantiles. Then, categorized individuals with low relative grip strength and a BMI of 25 kg/m² or higher as “Low/ ≥ 25 kg/m²” and those with low relative grip strength and a BMI below 25 kg/m² as “Low/ < 25 kg/m².” Similarly, individuals with high relative grip strength and a BMI of 25 kg/m² or higher as “High/ ≥ 25 kg/m²,” and those with high relative grip strength and a BMI below 25 kg/m² as “High/ < 25 kg/m²” for analysis.

Blood variables measurement

All participants were instructed to maintain a fasting state of at least 8 hr before serum collection for general blood tests. On the day of the examination, the blood samples were processed on-site using a centrifuge and then sent to the Seoul Clinical Laboratory. The ADVIA 1800 auto-analyzer (Siemens, USA) was used to obtain the results of the blood tests. The following variables related to metabolic syndrome obtained from the blood tests were utilized as research data: triglycerides, HDL cholesterol, blood glucose, high-sensitivity C-reactive protein (hs-CRP), serum creatinine, and insulin.

Serum sample processing and storage were conducted uniformly by the Genome Research Team of the Korea Centers for Disease Control and Prevention. The estimated glomerular filtration rate (eGFR), used as a continuous variable in the analysis, was calculated based on previous studies using the Modification of Diet in Renal Disease study formula [in mL/min per 1.73 m² = 175 × serum creatinine −1.154 × age −0.203 × (0.742 if female)], which relies on serum creatinine level.¹⁶

Questionnaire and other variables

One-on-one interviews were conducted by survey personnel. On the same day, the questionnaire was reviewed and modified to enhance the completeness of the survey. Physical measurements included height and weight.¹⁷ Height and weight were each measured once. To determine obesity levels, BMI was calculated as weight divided by height squared. According to the World Health Organization standards, individuals with a BMI <25 kg/m² were categorized as “normal weight,” while those with a BMI of 25 kg/m² or more were classified as “overweight and obese” for analysis.¹⁸ Muscle mass, which affects the hand grip strength, was assessed using the Zeus 9.9 device (Jawon Medical, Korea), and the measured values were utilized in the analysis.

Alcohol consumption was assessed by asking, “Are you someone who cannot drink alcohol or have never consumed alcohol?” Those who answered “yes” were categorized as “no drinking experience,” while those who answered “no” were further asked, “Are you currently drinking?” Those who answered “no” were categorized as “drank in the past,” and those who answered “yes” were classified as “currently a drinker for analysis.” Current smoking status was assessed by asking, “Have you smoked more than 5 packs (100 cigarettes) of cigarettes in your lifetime?” Those who answered “no” were categorized as “no smoking experience,” while those who answered “yes” were further asked, “Do you currently smoke?” Those who answered “no” were categorized as “have smoked in the past,” and those who answered “yes” were classified as “currently a smoker” for analysis.

Sleep duration was calculated as a continuous variable based on the responses to the questions: “On weekdays, how many hours of sleep do you typically get at night?” and “On weekends, around what time do you usually go to bed?” The daily sleep duration was calculated by using the formula [(weekday sleep duration × 5) + (weekend sleep duration × 2)]/7, and this value was utilized as a continuous variable for analysis. Participation in physical activity was determined by the question, “Do you engage in regular exercise that makes you sweat?” Those who answered “no” were categorized as “no regular exercise,” while those who answered “yes” were categorized as “regular exercise participation” for analysis.

Household income level was determined by asking, “What is the approximate monthly income of your household?” Responses indicating “Less than 500,000 won” and “500,000 won or more but less than 1 million won” were categorized as “Low.” Similarly, responses indicating “1 million won or more but less than 1.5 million won,” and “1.5 million won or more but less than 2 million won” were categorized as “Lower-middle.” Responses indicating “2 million won or more but less than 3 million won,” were categorized as “Middle.” Responses indicating “3 million won or more but less than 4 million won,” were categorized as “Upper-middle.” Responses indicating “4 million won or more but less than 6 million won,” and “more than 6 million won” were categorized as “High.”

Statistical analysis

STATA/IC 14.1 (StataCorp., College Station, TX) was used for statistical analysis. To examine the demographic characteristics of the participants, frequency analysis was conducted using the chi-square test, and descriptive analysis was conducted to calculate the mean value. Each variable was presented as a percentage or as mean and standard deviation (Tables 1 and 2). Furthermore, to determine the incidence density of metabolic syndrome among the observed participants, the number of person-years was calculated over the entire follow-up period and presented as person-years (Table 3).

Table 1.

Baseline Characteristics of Study Participants by Relative and Absolute Grip Strength

Characteristic of risk factor	Relative grip strength				Absolute grip strength
Characteristic of risk factor	Low (n = 311)	Middle (n = 312)	High (n = 313)	P-value	Low (n = 308)	Middle (n = 288)	High (n = 340)	P-value
Age (years)	67.62 ± 7.58	64.32 ± 7.76	59.89 ± 614	<0.001	68.92 ± 7.47	64.04 ± 7.26	59.33 ± 5.58	<0.001
Male (%)	48.23	48.40	48.24	0.999	48.70	51.39	45.29	0.309
Sleep time	6.52 ± 1.27	6.49 ± 1.31	6.48 ± 1.12	0.652	6.52 ± 1.27	6.42 ± 1.33	6.54 ± 1.10	0.872
Lean body mass (kg)	39.36 ± 7.56	40.68 ± 7.95	41.82 ± 7.66	<0.001	37.89 ± 6.80	40.76 ± 7.48	42.98 ± 8.09	<0.001
BMI (kg/m²)	24.74 ± 3.08	23.62 ± 2.64	22.18 ± 2.42	<0.001	23.07 ± 3.09	23.67 ± 2.79	23.78 ± 2.81	0.002
Income status (<1 million won)	56.27	39.42	23.00	<0.001	62.66	36.46	21.18	<0.001
eGFR (mL/min per 1.73 m²)	96.23 ± 23.06	97.31 ± 20.59	97.34 ± 19.87	0.515	96.29 ± 23.66	97.20 ± 21.22	97.37 ± 18.72	0.524
hs-CRP (mg/dL)	1.60 ± 3.18	1.13 ± 1.89	1.54 ± 5.53	0.846	1.61 ± 3.25	1.14 ± 2.01	1.50 ± 5.27	0.736
HOMA-IR	1.92 ± 0.99	1.82 ± 0.72	1.60 ± 0.64	<0.001	1.72 ± 0.75	1.82 ± 0.77	1.80 ± 0.89	0.277
Alcohol consumption (%)
None	50.48	47.12	45.05	0.001	51.95	45.83	45.00	<0.001
Former	12.86	8.97	5.11		12.01	11.11	4.41
Current	36.66	43.91	49.84		36.04	43.06	50.59
Smoking status (%)
None	62.70	63.46	64.22	0.027	64.61	59.03	66.18	0.114
Former	27.65	22.12	19.17		24.68	23.61	20.88
Current	9.65	14.42	16.61		10.71	17.36	12.94
Exercise participation (%)
None	77.81	67.63	58.47	<0.001	78.25	68.40	58.24	<0.001
Regular	22.19	32.37	41.53	<0.001	21.75	31.60	41.76	<0.001

BMI, body mass index; eGFR, estimated glomerular filtration rate; HOMA-IR, homeostatic model assessment for insulin resistance; hs-CRP, high-sensitivity C-reactive protein.

Table 2.

Baseline Characteristics of Study Participants by Gender

Characteristic of risk factor	Total (N = 936)	Male (n = 452)	Female (n = 484)	P-value
Age (years)	63.94 ± 7.85	64.44 ± 7.64	63.47 ± 8.03	0.058
Sleep time	6.50 ± 1.23	6.54 ± 1.20	6.45 ± 1.27	0.247
Lean body mass (kg)	40.62 ± 7.78	47.00 ± 5.59	34.67 ± 3.81	<0.001
BMI (kg/m²)	23.51 ± 2.91	23.39 ± 2.72	23.62 ± 3.08	0.238
Absolute grip strength (kg)	28.11 ± 10.23	36.33 ± 7.87	20.44 ± 4.75	<0.001
Relative grip strength (kg/BMI)	1.20 ± 0.44	1.56 ± 0.34	0.87 ± 0.22	<0.001
Income status (<1 million won)	39.53	34.07	44.63	0.002
eGFR (mL/min per 1.73 m²)	96.96 ± 21.20	96.81 ± 20.35	97.10 ± 21.98	0.835
hs-CRP (mg/dL)	1.42 ± 3.85	1.73 ± 5.05	1.14 ± 2.15	0.019
HOMA-IR	1.78 ± 0.81	1.70 ± 0.70	1.85 ± 0.89	0.004
Alcohol consumption (%)
None	47.54	22.35	71.07	<0.001
Former	8.97	15.71	2.69
Current	43.48	61.95	26.24
Smoking status (%)
None	22.35	25.44	98.97	<0.001
Former	15.71	47.12	0.41
Current	61.95	27.43	0.62
Exercise participation (%)
None	67.95	66.15	69.63	0.255
Regular	32.05	33.85	30.37	0.255

Table 3.

Incidence Density and Hazard Ratio of Metabolic Syndrome According to Relative and Absolute Grip Strength

Characteristic of risk factors		MetS (N = 936)	Person-year	Incidence density ^a (95% CI)	Multivariable-adjusted HR (95% CI)
Absolute sgrip strength (kg)	Low	80	1,108.26	72.18 (57.98–89.86)	1.00 (Reference)
	Middle	83	1,024.61	81.00 (65.32–100.44)	0.83 (0.60–1.15)
	High	101	1,232.40	81.95 (67.43–99.60)	0.62 (0.43–0.88)
P-trend					0.001
Relative grip strength (kg/BMI)	Low	107	1,104.01	96.91 (80.18–117.13)	1.00 (Reference)
	Middle	102	1,128.94	90.35 (74.41–109.70)	0.73 (0.55–0.98)
	High	55	1,132.32	48.57 (37.29–63.26)	0.45 (0.32–0.64)
P-trend					<0.001
Grip strength × BMI level	Low/≥ 25 kg/m²	47	336.38	139.71 (104.97–185.95)	1.00 (Reference)
	Low/< 25 kg/m²	70	1,315.84	53.19 (42.08–67.24)	0.55 (0.37–0.82)
	High/≥ 25 kg/m²	78	523.36	149.03 (119.37–186.06)	0.84 (0.56–1.25)
	High/< 25 kg/m²	69	1,189.68	57.99 (45.80–73.43)	0.43 (0.29–0.65)
P-trend					0.001
Total		264	3,365.28	78.44	–

Multivariable-adjusted age, sex, sleep time, eGFR, hs-CRP, lean body mass, alcohol intake, smoking status, income status, HOMA-IR, exercise participation.

Incidence density = case/person-year × 1,000.

CI, confidence interval; HR, hazard ratio; MetS, metabolic syndrome.

To identify an appropriate analytical model for assessing the association between absolute grip strength, relative grip strength, and the incidence of metabolic syndrome, a log-rank test was conducted. The results indicated that for absolute grip strength, the hazard ratio (HR) for metabolic syndrome did not exhibit a consistent and parallel curve as time progressed, suggesting that the proportional hazard assumption was not met. This was confirmed by the log-rank test, which yielded a similar outcome in terms of significance level. Since all independent variables must satisfy the proportional hazard assumption for the Cox proportional hazards regression model to be appropriate when examining the incidence of metabolic syndrome in this study, it was determined that the current analytical model was not suitable due to the lack of proportional hazard assumption satisfaction.

Therefore, in cases where the proportional hazard assumption is not met, an extended multivariate Cox regression model was chosen for analysis. This model considered both time-fixed covariates (gender, sleep duration) and time-dependent covariates [age, regular physical activity participation, muscle mass, household income level, smoking status, alcohol consumption, hs-CRP, eGFR, homeostatic model assessment for insulin resistance (HOMA-IR)], aiming to minimize distorted results during data estimation.¹⁹

To investigate the association between absolute grip strength, relative grip strength measured during the baseline survey, and the incidence of metabolic syndrome, an extended multivariate Cox regression model was utilized. The model was used to calculate the independent HRs and 95% confidence intervals (CIs) for metabolic syndrome according to absolute and relative grip strength (Table 3). In addition, to compare the association between absolute and relative grip strength measured during the baseline survey and the incidence of metabolic syndrome across genders and age groups, an extended multivariate Cox regression model was used to calculate the HRs and 95% CIs for metabolic syndrome (Tables 4 and 5).

Table 4.

Hazard Ratio of Metabolic Syndrome According to Relative and Absolute Grip Strength by Gender

Characteristic of risk factor		Total HR (N = 936)	Male HR (n = 452)	Female HR (n = 484)
Absolute grip strength (kg)	Low	1.00 (Reference)	1.00 (Reference)	1.00 (Reference)
	Middle	0.83 (0.60–1.15)	1.18 (0.67–2.05)	0.64 (0.41–0.98)
	High	0.62 (0.43–0.88)	0.74 (0.39–1.40)	0.56 (0.36–0.88)
P-trend		0.007	0.228	0.011
Relative grip strength (kg/BMI)	Low	1.00 (Reference)	1.00 (Reference)	1.00 (Reference)
	Middle	0.75 (0.56–0.99)	0.71 (0.45–1.13)	0.75 (0.51–1.10)
	High	0.40 (0.28–0.58)	0.49 (0.28–0.83)	0.43 (0.26–0.69)
P-trend		<0.001	0.008	0.001
Grip strength × BMI level	Low/≥ 25 kg/m²	1.00 (Reference)	1.00 (Reference)	1.00 (Reference)
	Low/< 25 kg/m²	0.55 (0.37–0.82)	0.42 (0.21–0.81)	0.70 (0.43–1.15)
	High/≥ 25 kg/m²	0.84 (0.56–1.25)	0.84 (0.43–1.65)	0.79 (0.46–1.35)
	High/< 25 kg/m²	0.43 (0.29–0.65)	0.39 (0.19–0.78)	0.49 (0.29–0.83)
P-trend		0.001	0.055	0.013

Multivariable-adjusted age, sex, sleep time, eGFR, hs-CRP, lean body mass, alcohol intake, smoking status, income status, HOMA-IR, exercise participation.

Table 5.

Hazard Ratio of Metabolic Syndrome According to Relative and Absolute Grip Strength by Age

Characteristic of risk factor		Total HR (N = 1,987)	Age <65 HR (n = 510)	Age ≥ 65 HR (n = 426)
Absolute grip strength (kg)	Low	1.00 (Reference)	1.00 (Reference)	1.00 (Reference)
	Middle	0.83 (0.60–1.15)	0.78 (0.47–1.29)	0.91 (0.59–1.40)
	High	0.62 (0.43–0.88)	0.62 (0.39–0.99)	0.63 (0.34–1.15)
P-trend		0.007	0.042	0.165
Relative grip strength (kg/BMI)	Low	1.00 (Reference)	1.00 (Reference)	1.00 (Reference)
	Middle	0.75 (0.56–0.99)	0.78 (0.52–1.16)	0.75 (0.49–1.16)
	High	0.40 (0.28–0.58)	0.43 (0.28–0.67)	0.68 (0.37–1.26)
P-trend		<0.001	<0.001	0.148
Grip strength × BMI level	Low/≥ 25 kg/m²	1.00 (Reference)	1.00 (Reference)	1.00 (Reference)
	Low/< 25 kg/m²	0.55 (0.37–0.82)	0.45 (0.23–0.86)	0.65 (0.39–1.07)
	High/≥ 25 kg/m²	0.84 (0.56–1.25)	0.74 (0.42–1.29)	0.84 (0.41–1.72)
	High/< 25 kg/m²	0.43 (0.29–0.65)	0.34 (0.19–0.63)	0.76 (0.43–1.34)
P-trend		0.001	0.007	0.527

Multivariable-adjusted age, sex, sleep time, eGFR, hs-CRP, lean body mass, alcohol intake, smoking status, income status, HOMA-IR, exercise participation.

During the analysis of the extended multivariate Cox regression model, confounding variables, including age, gender, regular exercise participation, muscle mass, sleep duration, eGFR, hs-CRP, alcohol consumption, smoking status, income level, obesity level, and HOMA-IR, were adjusted for to assess their impact on metabolic syndrome, absolute grip strength, and relative grip strength. All significance levels were set at P < 0.05.

Results

The demographic characteristics of the participants are shown in Tables 1 and 2. In Table 1, the high relative grip strength group had lower age, BMI, HOMA-IR, and low-income level than the low relative grip strength group. They also had higher skeletal muscle mass, alcohol consumption rate, smoking rate, and regular physical activity participation rate. However, no significant differences were found in terms of gender, sleep duration, eGFR, and hs-CRP levels between the two groups. The results of absolute grip strength were similar to those of relative grip strength, except that no significant differences were found for HOMA-IR and smoking level.

In Table 2, compared to females, males exhibited a lower low-income rate and had lower HOMA-IR values. In addition, males had higher muscle mass, absolute grip strength, relative grip strength, hs-CRP, higher drinking rates, and smoking rates. There were no significant gender differences observed in other variables such as age, sleep duration, BMI, eGFR, and physical activity participation level.

The results of the association between absolute grip strength, relative grip strength, and the incidence of metabolic syndrome are shown in Table 3. The incidence rates per 1,000 persons for different levels of absolute grip strength were 72.18 for the low level, 81.00 for the moderate level, and 81.95 for the high level, showing minimal differences. However, after adjusting for various confounding variables such as age and gender, the group with high absolute grip strength showed a 38% reduction in the HR for incidence of metabolic syndrome compared to the group with low absolute grip strength (HR = 0.62, 95% CI = 0.43–0.88). The incidence rates per 1,000 persons for different levels of relative grip strength were 96.91 for the low level, 90.35 for the moderate level, and 48.57 for the high level, indicating a substantial decrease in the incidence rate with higher grip strength levels.

After adjusting for various confounding variables such as age and gender, the groups with moderate and high relative grip strength exhibited a 27% (HR = 0.73, 95% CI = 0.55–0.98) and 55% (HR = 0.45, 95% CI = 0.32–0.64) reduction in the HR for incidence of metabolic syndrome, respectively, compared to the group with low relative grip strength. Additionally, when considering the association between absolute grip strength and BMI levels, the incidence rates per 1,000 persons were as follows: for the high BMI group with low absolute grip strength (Low/ ≥ 25 kg/m²), 139.71; for the low BMI group with low absolute grip strength (Low/ < 25 kg/m²), 53.19; for the high BMI group with high absolute grip strength (High/ ≥ 25 kg/m²), 149.03; and for the low BMI group with high absolute grip strength (High/ < 25 kg/m²), 57.99.

The result indicates a substantial decrease in incidence rates in the low or high absolute grip strength groups within the low BMI group (Low/ < 25 kg/m² or High/ < 25 kg/m²). Furthermore, the low or high absolute grip strength groups within the low BMI group (Low/ < 25 kg/m² or High/ < 25 kg/m²) exhibited a respective 45% (HR = 0.55, 95% CI = 0.37–0.82) and 57% (HR = 0.43, 95% CI = 0.29–0.65) reduction in the HR for the incidence of metabolic syndrome compared to the low absolute grip strength group with high BMI (Low/ ≥ 25 kg/m²).

The results of the association between gender, absolute grip strength, relative grip strength, and the incidence of metabolic syndrome are shown in Table 4. For males, the association between absolute grip strength and the incidence of metabolic syndrome was not statistically significant. However, the high relative grip strength group exhibited a 51% reduction (HR = 0.49, 95% CI = 0.28–0.83) in the HR for incidence of metabolic syndrome compared to the low relative grip strength group. In addition, within the low BMI group with either low or high absolute grip strength (Low/ < 25 kg/m² or High/ < 25 kg/m²), the HR for incidence of metabolic syndrome was reduced by 58% (HR = 0.42, 95% CI = 0.21–0.81) and 61% (HR = 0.39, 95% CI = 0.19–0.78), respectively, compared to the low absolute grip strength group with high BMI (Low/ ≥ 25 kg/m²).

Females in the moderate or high absolute grip strength groups, the HR for incidence of metabolic syndrome was reduced by 36% (HR = 0.64, 95% CI = 0.41–0.98) and 34% (HR = 0.56, 95% CI = 0.36–0.88), respectively, compared to the low grip strength group. Furthermore, in the high relative grip strength group, the HR for incidence of metabolic syndrome was reduced by 57% (HR = 0.43, 95% CI = 0.26–0.69) compared to the low relative grip strength group. In addition, within the low BMI group with high absolute grip strength (High/ < 25 kg/m²), the HR for incidence of metabolic syndrome was reduced by 51% (HR = 0.49, 95% CI = 0.29–0.83) compared to the low absolute grip strength group with high BMI (Low/ ≥ 25 kg/m²).

The results of the association between age, absolute grip strength, relative grip strength, and the incidence of metabolic syndrome are shown in Table 5. In the group aged younger than 65 years, high absolute grip strength and high relative grip strength were associated with 38% (HR = 0.62, 95% CI = 0.39–0.99) and 57% (HR = 0.43, 95% CI = 0.28–0.67) decrease in the incidence HR of metabolic syndrome compared to the low absolute grip strength and low relative grip strength groups. Furthermore, within the low BMI group with low absolute grip or high absolute grip strength (Low/ < 25 kg/m² or High/ < 25 kg/m²), the HR of incidence of metabolic syndrome was reduced by 55% (HR = 0.45, 95% CI = 0.23–0.86) and 66% (HR = 0.34, 95% CI = 0.19–0.63), respectively, when compared to those with low absolute grip strength with high BMI levels (Low/ ≥ 25 kg/m²).

For the group aged 65 years and older, there were no significant associations between absolute grip strength, relative grip strength, BMI levels, and the incidence of metabolic syndrome.

Discussion

Despite adjusting for various factors affecting metabolic syndrome and grip strength, high absolute grip strength and high relative grip strength were still associated with a reduction in the incidence of metabolic syndrome. Furthermore, regardless of absolute grip strength, low BMI level was associated with a reduction in incidence of metabolic syndrome. For male, higher relative grip strength was associated with a reduction in the incidence of metabolic syndrome, while for female, higher absolute and relative grip strength were associated with a reduction in incidence of metabolic syndrome. Moreover, differences were observed in the association between gender, BMI levels, and absolute grip strength with the incidence of metabolic syndrome. For individuals aged younger than 65 years, high absolute grip strength and high relative grip strengths were associated with a decrease in incidence of metabolic syndrome, and regardless of absolute grip strength, low BMI was associated with a reduction in the incidence of metabolic syndrome.

The decline in muscle strength is a crucial health indicator for older adults. It is associated with increased risks of sarcopenia, coronary artery disease, falls, and mortality. Therefore, as muscle strength progressively decreases with age, standardized muscle strength assessment in older adults is recommended.²⁰ Among the methods for assessing muscle strength, grip strength is a convenient and suitable measurement tool for clinically evaluating the overall neuromuscular system in older adults.²¹ Muscle strength indicates the capacity to maintain (skeletal) muscle mass, which is known to reduce the incidence of various diseases.²² While muscle mass significantly affects muscle strength, muscle strength is independently associated with mobility, functional status, and mortality in older adults,²³ which suggests that the functional capacity of muscles, such as relative strength, could predict age-related sarcopenia.

Moreover, higher grip strength levels are associated with reduced waist circumference, body fat percentage, and risk of cardiovascular-related diseases.²⁴ Age-related sarcopenia has been associated with oxidative stress, inflammatory responses, end products of glycation, and increased insulin resistance associated with diabetes.²⁵ The definition of sarcopenia has been based on absolute grip strength.¹¹ However, recent research has shifted interest toward relative grip strength, which adjusts for body mass.⁸ Relative grip strength, after adjusting for body mass, is far superior to absolute grip strength in predicting health conditions, mobility, and quality of life.^9,26 Relative grip strength has an association with metabolic syndrome, whereas absolute grip strength did not show an association.¹¹ Increased relative grip strength lowers intramuscular triglycerides, decreases insulin resistance, and reduces the incidence of metabolic syndrome and cardiovascular diseases.^27,28

The mechanisms underlying the incidence of metabolic syndrome development by high muscle strength are not yet fully elucidated. However, according to previous studies, skeletal muscles play a critical role in regulating the overall body metabolism.²⁹ Individuals with higher muscle strength levels tend to be more physically active,¹⁶ and vigorous muscle contractions have a significant impact on improving blood glucose transport capacity and insulin resistance associated with metabolic syndrome.³⁰

The reason why relative grip strength in Table 3 exhibited a greater reduction in the risk of metabolic syndrome compared to absolute grip strength is because relative grip strength considers intramuscular fat accumulation, unlike absolute grip strength. According to previous studies, absolute grip strength has an inconsistent association with body fat, whereas BMI has a static association with it, suggesting that individuals who are overweight or obese tend to have higher muscle mass.³¹ Individuals with higher intramuscular fat accumulation, due to higher body weight, might have lower muscle quality, which can lead to increased insulin resistance.³² In fact, the results shown in Table 1 in this study are consistent with the previous results. HOMA-IR was significantly lower in the high relative grip strength group than in the low relative grip strength group, while there was no significant difference between the groups in absolute grip strength.

Consequently, individuals with lower intramuscular fat accumulation and better muscle quality are more likely to possess the capacity to generate better muscle strength.³¹ Therefore, the increase in relative grip strength can be attributed to the correction of obesity-related factors that trigger intramuscular fat accumulation,¹² making it more effective in predicting the incidence of metabolic syndrome compared to the increase in absolute grip strength due to weight gain.³¹ This suggests that relative grip strength, which accounts for intramuscular fat accumulation, is a more effective predictor of the risk of metabolic syndrome than absolute grip strength in the context of obesity-related factors.¹¹

Furthermore, as shown in Table 3, individuals with lower BMI levels consistently demonstrate a reduced risk of developing metabolic syndrome, irrespective of their absolute grip strength levels, in contrast to those with higher BMI levels and lower absolute grip strength. It highlights that the impact of BMI on metabolic syndrome outweighs that of muscle strength. According to previous studies, as BMI levels increase, the association between grip strength and the risk of type 2 diabetes gradually decreases since the detrimental effect of obesity on diabetes risk prevails over the beneficial effect of muscle strength.³³

Moreover, BMI most accurately reflects current body fat status, and previous research has shown that even among obese individuals, a high amount of muscle mass and strength does not exhibit significant associations with metabolic health due to the accumulation of intramuscular fat.³¹ Therefore, the increased risk of metabolic syndrome due to higher BMI levels has a greater impact than the reduction in metabolic syndrome risk attributed to muscle strength.³³

In Table 4, unlike women, relative grip strength was associated with the risk of metabolic syndrome in men, while absolute grip strength did not show any association. This is likely because men have higher grip strength than women, which is associated with higher body weight. According to previous research, body weight and muscle strength exhibit a positive correlation.³⁴ Furthermore, in this study, male had significantly higher average body weight by 9.15 kilograms and absolute grip strength by 15.9 kilograms compared to female in Table 2. The difference was statistically significant. An increase in body weight resulting in higher body fat can elevate risk of metabolic syndrome.³⁵

Furthermore, based on other previous studies, when resistance training was conducted on overweight adults, an increase in muscle strength was observed, but no significant positive changes were observed in metabolic risk factors. This indicates that the metabolic risks due to weight gain have a greater impact on metabolic syndrome compared to the increase in muscle strength.³⁶ Therefore, the high grip strength in male, with higher average body weight than female, may be attributed to weight gain,³⁴ and the positive impact of grip strength on reducing the risk of developing metabolic syndrome is offset by the negative impact of high body weight on metabolic health.³³

Furthermore, in Table 4, only female in the low BMI group with high grip strength showed a reduced risk of developing metabolic syndrome, suggesting that female may benefit more from the positive effects of high muscle strength on metabolic syndrome than male. Lifestyle habits, including smoking and alcohol consumption, are critical factors associated with incidence of metabolic syndrome and are closely associated with obesity.³⁷ We observed that the current alcohol consumption rate, a factor influencing metabolic syndrome, was ∼2.3 times higher in male (61.95%) than in female (26.24%), and the current smoking rate was about 44 times higher in male (27.43%) than in female (0.62%).

We confirmed results consistent with previous research indicating that males are more exposed to unhealthy lifestyle.³⁸ Consequently, because females are less affected by the negative impact of unhealthy lifestyle habits, such as smoking and alcohol consumption, on obesity and metabolic syndrome,^37,38 a protective effect of higher grip strength is observed at lower BMI levels in female.

The lack of associations between absolute grip strength, relative grip strength, BMI levels, and grip strength interactions in individuals aged 65 and older in Table 5 is due to the greater influence of metabolic syndrome risk factors caused by aging, which outweigh the impact of muscle strength. Aging is considered a biological process characterized by detrimental physiological and metabolic changes associated with the increase in age.³⁹ According to one study, aging cells induce oxidative stress, including increased levels of reactive oxygen species and mitochondrial dysfunction.⁴⁰ This oxidative stress increases insulin resistance and accelerates the development of metabolic syndrome.⁴¹ Therefore, in individuals aged 65 and older, various metabolic syndrome risk factors such as increased oxidative stress, insulin resistance, and mitochondrial dysfunction associated with aging are likely to be increased, potentially offsetting the positive impact of grip strength.^40,41

This longitudinal study has provided meaningful insights into the associations between metabolic syndrome and absolute grip strength, relative grip strength, stratified by gender and age groups. However, there are several limitations to consider.

First, we were unable to adjust for dietary variables that might influence metabolic syndrome. Nevertheless, to enhance the reliability of this study, we controlled lifestyle factors such as smoking, alcohol consumption, and physical activity, as well as blood variables, including HOMA-IR, hs-CRP, and eGFR, which are known to influence metabolic syndrome. Future research should explore how daily dietary intake independently affects the associations between absolute grip strength, relative grip strength, and the incidence of metabolic syndrome. Second, our study focused on middle-aged individuals residing in specific regions of South Korea. Consequently, there is a limitation in generalizing the findings to represent the entire South Korean population.

Future studies should consider the need to compare and confirm the associations between metabolic syndrome and absolute grip strength, relative grip strength, in a nationwide cohort study involving the entire population. Third, as this study only examined grip strength as an indicator of upper-body muscle strength, we could not assess the associations between metabolic syndrome and muscle strength levels in other areas, such as the abdominal or lower body muscle strength. Future research should investigate the impact of muscle strength levels in the upper body, lower body, and core muscles on metabolic syndrome separately.

Conclusion

This study observed that relative grip strength and BMI levels, respectively, have a stronger association with the risk of metabolic syndrome incidence than absolute grip strength. In addition, the study confirmed different associations with metabolic syndrome and gender, age-specific absolute grip strength, relative grip strength, BMI levels, and absolute grip strength. The decrease in muscle strength due to aging is associated with an increased risk of metabolic syndrome. Relative grip strength is more valuable than absolute grip strength in predicting metabolic syndrome. Therefore, to prevent metabolic syndrome incidence, continuous monitoring of relative grip strength and promoting national-level physical activity programs to enhance muscle strength and reduce body fat is considered necessary.

Footnotes

Acknowledgments

Data in this study were from the KoGES (6635-302), National Institute of Health, Korea Disease Control and Prevention Agency, Republic of Korea.

Authors' Contributions

Conceptualization: D.Y.P. and Y.S.K. Data curation: D.Y.P. Formal analysis: D.Y.P. Methodology: D.Y.P., J.W.R., and Y.S.K. Visualization: D.Y.P. Writing—original draft: D.Y.P. and J.W.R. Writing—review and editing: D.Y.P., J.W.R., and Y.S.K.

Author Disclosure Statement

The authors have no conflicts of interest to declare for this study.

Funding Information

No competing financial interests exist.

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