An age-related decline in the mass, strength, and function of skeletal muscle is associated with an increased risk of reduced physical capacity [1], poorer quality of life [2], and adverse health outcomes, such as metabolic disturbances [3], falls and fractures [4], and mortality [5] and places a high socioeconomic burden on older people [6]. The prevalence of sarcopenia is 5-13% in those aged 60-70 years worldwide [7], and in Korea, the prevalence was 4.6-14.5% in men and 6.7-14.4% in women aged 70 years and over [8]; thus, sarcopenia is a major medical issue.

A reduction in skeletal muscle strength is independently related to physical disability [9] and mortality [10]. Several studies have shown that skeletal muscle strength is a better indicator of individuals with functional impairment and frailty than skeletal muscle mass in older adults [10,11]. Therefore, a new entity of “possible sarcopenia” defined by low skeletal muscle strength has been emphasized to contribute to higher awareness and facilitate timely interventions for sarcopenia [12].

Several studies have examined protein intake among various factors influencing the decline in skeletal muscle strength [13,14], but the findings are inconsistent [15,16]. Furthermore, no studies have investigated the association between low amount of daily protein intake and skeletal muscle strength in older Koreans. Therefore, we evaluated whether daily protein intake is associated with skeletal muscle strength in Koreans aged 60 years and over, using data from the Korean National Health and Nutrition Examination Survey (KNHANES).

1. Study population

We used KNHANES data collected in 2014 and 2017. KNHANES is performed by the Korean Centres for Disease Control and Prevention at 3-year intervals to assess public health and to provide baseline data for the development, establishment, and evaluation of Korean public health policies. All KNHANES participants were non-institutionalised and aged ≥1 year; they are selected using a stratified, multi-stage, cluster probability sampling design to ensure that the sample is independent, homogeneous, and nationally representative. Data were collected using household interviews and anthropometric and biochemical measurements, and included a nutrition assessment. All protocols were approved by the Institutional Review Board of the Korean Centres for Disease Control and Prevention, and all participants provided informed consent at baseline.

In this cross-sectional study, we originally evaluated data on 8,608 adults ≥60 years of age selected from 31,207 KNHANES participants. We excluded participants with missing information or values for the major variables (n=2,105). Ultimately, data for 6,503 participants were analysed (Figure 1). The study was approved by the Institutional Review Board of the Catholic University of Korea (IRB approval number: VC19ZESI0213).

Figure 1. Study population: data from the 2014 and 2017 Korean National Health and Nutrition Examination Survey (KNHANES).

2. Dietary protein assessment

The participants’ dietary protein intake was assessed by trained dietitians using the 112-item semi-quantitative food frequency questionnaire (FFQ) [17], which is used to estimate nutrient intake from portion size and the frequency at which each food item was consumed during the previous year. The daily amount of protein consumed was estimated from the sum of the intake of each food item, based on the food composition tables of the Rural Development Administration, in combination with the nutrient database of the Korea Health Industry Development Institute [18]. Daily protein intake, defined as the amount of daily protein consumed per kilogram body weight, was classified into three categories: low (<0.8 g/kg body weight/day), moderate (0.8-1.2 g/kg/d), and high (>1.2 g/kg/d) protein intake [19].

3. Measuring handgrip strength

To evaluate skeletal muscle strength, the participants’ handgrip strength (HGS) was measured by trained examiners using a digital grip strength dynamometer (T.K.K. 5401, Takei Scientific Instruments, Niigata, Japan). The dynamometer measures up to 100.0 kg of force and has an adjustable grip span. Participants were asked to sit while looking forward with the elbow flexed at 90°, and squeeze the dynamometer continuously with full force until a value appeared on the liquid-crystal display. The HGS was measured three times alternately for each hand, starting with the dominant hand. The maximum value of the three measurements was used as the HGS. Possible sarcopenia was defined as an HGS <28 kg for men and <18 kg for women [12].

4. Other variables

Self-reported information regarding age, sex, alcohol consumption, smoking status, household income, extent of physical activity, and history of diabetes, hypertension, dyslipidemia, cardiovascular and cerebrovascular diseases, or any cancer was obtained.

Information on alcohol consumption included the frequency of drinking days and the number of drinks consumed per day during the year preceding the KNHANES household interview. We used the Korean version of a “standard drink” (any drink that contains 10 g pure alcohol) [20]; alcohol consumption was classified into three categories: abstinence (no alcoholic drinks consumed within the last year), moderate drinking (≤14 standard drinks consumed by men and ≤7 by women per week), and heavy drinking (>14 standard drinks consumed by men and >7 by women per week). Cigarette smoking was divided into three categories based on current use: non-smoker, ex-smoker, and current smoker. Household income was divided into monthly equivalent household values (in quartiles), estimated as total income divided by the square root of the number of household members. Participants were asked about their extent of physical activity during the week preceding the interview; this was classified as low or not. Low-level activity was defined as ≤150 min of moderate-intensity exercise or ≤75 min of vigorous exercise per week [21]. Body weight and height were measured with the participants wearing light indoor clothing without shoes. Body weight and height were measured with the participants wearing light indoor clothing without shoes. Body mass index (BMI) was calculated as weight (kilograms) divided by height squared (meters squared). Venous blood samples were drawn from the study participants after fasting for 12 hours or overnight.

5. Statistical analyses

We used the SAS PROC SURVEY module, which considers strata, clusters, and weights, to analyse the data. All analyses were performed using the KNHANES sample weightings. Sex-specific features were evaluated using independent t-tests for continuous variables and chi-square test for dichotomous variables. Data are expressed as mean±standard error or percentages. Differences in HGS according to dietary protein intake were evaluated using analysis of covariance. The following were all used as covariates: age; alcohol consumption; smoking status; household income; physical activity level; BMI; daily total energy intake; history of diabetes, hypertension, dyslipidemia, cardiovascular and cerebrovascular diseases, or any cancer; and laboratory parameters, including serum creatinine, high sensitivity C-reactive protein levels, and lipid profiles including total cholesterol, high-density lipoprotein cholesterol, and triglyceride levels. The associations between dietary protein intake and HGS were analysed using multiple logistic regression after adjusting for covariates. All statistical analyses were performed using SAS (ver. 9.2; SAS Institute, Cary, NC, USA). A P value <0.05 was considered to reflect significance.

1. Characteristics of the study population by possible sarcopenia

This study examined data from 6,503 participants (2,935 men and 3,568 women). The prevalence of possible sarcopenia was 8.3% and 23.5% in men and women, respectively. Those with possible sarcopenia tended to be older, and had higher proportions of low-level activity, lower household income, lower proportion with dyslipidemia, higher proportion with stroke, were less obese, and lower daily energy intake, higher proportion of energy from carbohydrates, and lower proportions from protein and fat (Table 1).

Table 1 . Characteristics of the study population by possible sarcopenia.

	Men					Women
	Total	Possible sarcopenia				Total	Possible sarcopenia
		Yes	No	P value			Yes	No	P value
N	2,935	275	2,660	-		3,568	818	2,750	-
Age, years	69.0±0.1	75.9±0.4	68.4±0.1	<0.001		70.1±0.1	75.1±0.2	68.5±0.1	<0.001
Current smoking, %	22.7	17.1	23.1	0.077		2.6	3.2	2.5	0.003
Heavy drinking, %	35.9	14.4	37.4	<0.001		12.9	6.2	14.9	<0.001
Low physical activity, %	56.8	73.6	55.5	<0.001		67.5	81.4	63.6	<0.001
Low income, %	31.2	60.0	28.6	<0.001		44.0	60.6	39.0	<0.001
Education level, %
≤Elementary school	35.8	58.3	34.0	<0.001		65.7	84.8	60.4	<0.001
Middle or high school	43.8	31.9	44.7			27.8	13.3	31.8
≥College	20.4	9.8	21.3			6.5	1.9	7.8
Comorbidity, %
Diabetes	20.1	23.1	19.8	0.315		18.0	24.5	16.1	<0.001
Hypertension	48.5	47.8	48.6	0.844		50.9	58.8	48.5	<0.001
Dyslipidemia	22.1	12.6	23.0	<0.001		35.9	27.1	38.5	<0.001
Stroke	5.8	15.5	5.0	<0.001		4.0	6.0	3.4	0.003
Coronary artery disease	7.7	9.7	7.5	0.272		5.1	6.4	4.8	0.121
Cancer	5.4	6.7	5.3	0.528		4.4	4.7	4.3	0.703
Waist circumference, cm	86.4±0.2	84.0±0.7	86.6±0.2	<0.001		83.6±0.2	83.2±0.4	83.8±0.2	0.148
Body mass index, kg/m2	23.8±0.1	22.6±0.2	23.9±0.1	<0.001		24.4±0.1	24.0±0.1	24.6±0.1	0.001
Fasting glucose, mg/dL	109.7±0.6	109.8±2.9	109.6±0.7	0.963		106.0±0.6	107.6±1.3	105.6±0.6	0.148
Serum Cr, mg/dL	1.00±0.01	1.00±0.02	1.00±0.01	0.645		0.80±0.01	0.80±0.01	0.70±0.01	0.015
hsCRP, mg/dL	1.6±0.1	2.0±0.3	1.5±0.1	0.108		1.3±0.1	1.6±0.1	1.2±0.1	0.003
Total cholesterol, mg/dL	182.8±0.9	173.5±2.6	183.5±0.9	<0.001		194.3±0.8	190.6±1.8	195.3±0.9	0.021
Energy intake, kcal/d	1983.8±17.5	1615.2±44.3	2019.8±18.3	<0.001		1504.9±13.5	1312.5±27.1	1559.6±15.0	<0.001
Energy from
Carbohydrate, %	68.2±0.3	73.8±0.7	67.7±0.3	<0.001		73.3±0.3	76.1±0.5	72.5±0.3	<0.001
Fat, %	33.6±0.6	11.8±0.5	14.8±0.2	<0.001		24.9±0.4	12.3±0.3	14.9±0.2	<0.001
Protein, %	13.5±0.1	12.6±0.3	13.6±0.1	<0.001		13.1±0.1	12.3±0.2	13.3±0.1	<0.001
Protein intake, g/d	67.5±0.8	51.2±1.9	69.1±0.8	<0.001		49.7±0.6	41.0±1.1	52.1±0.6	<0.001
Handgrip strength, kg	35.8±0.2	21.9±0.2	37.0±0.2	<0.001		21.5±0.1	14.7±0.1	23.5±0.1	<0.001

Values are means±standard errors or percentages..

Cr, creatinine; hsCRP, high-sensitivity C-reactive protein..

2. Handgrip strength according to daily protein intake

Table 2 shows the mean of HGS by daily protein intake. In both men and women, HGS increased as daily protein intake increased (P for trend <0.001), but there were no significant differences in HGS according to daily protein intake after adjustment for age, smoking status, alcohol consumption, physical activity, household income, BMI, daily total energy intake, history of comorbidities, serum creatinine, high sensitivity C-reactive protein levels, and lipid profiles.

Table 2 . Mean handgrip strength according to daily protein intake.

Handgrip strength*	Daily protein intake†			P value	P for trend	P value‡	P for trend‡
	Low	Moderate	High
Men	34.4±0.3	36.3±0.2	36.8±0.3	<0.001	<0.001	0.624	0.731
Women	21.0±0.2	21.6±0.2	22.6±0.2	<0.001	<0.001	0.200	0.083

Values are means±standard errors..

*Handgrip strength was expressed as kilogram. ^†Dietary protein intake status was classified as low (<0.8 g/kg body weight/day), moderate (0.8-1.2 g/kg/d), and high (>1.2 g/kg/d) protein intake. ^‡Adjustment for age, smoking status, alcohol consumption, physical activity level, household income, body mass index, daily total energy intake, histories of diabetes, hypertension, dyslipidemia, cardio- and cerebrovascular diseases, or any cancer, and laboratory tests including serum creatinine, high sensitivity C-reactive protein levels, and lipid profiles..

3. Association between daily protein intake and possible sarcopenia

Table 3 shows the unadjusted, age-adjusted, and multivariate-adjusted odds ratios of possible sarcopenia according to daily protein intake. Low or high daily protein intake in both men and women were positively or negatively associated with possible sarcopenia, respectively, but the associations did not remain after adjustment for covariates. In both men and women, the prevalence of possible sarcopenia increased as daily protein intake decreased, but the trends disappeared after adjustment for covariates.

Table 3 . Association between daily protein intake and possible sarcopenia.

Daily protein intake*		Possible sarcopenia†
		Unadjusted	Model 1	Model 2	Model 3	Model 4
Men	Low	1.86 (1.33-2.58)	1.55 (1.10-2.17)	1.34 (0.89-2.03)	1.02 (0.57-1.84)	1.12 (0.56-2.23)
	Moderate	1	1	1	1	1
	High	0.59 (0.39-0.89)	0.76 (0.49-1.18)	0.90 (0.54-1.49)	1.19 (0.58-2.43)	1.55 (0.65-3.71)
	P for trend	<0.001	<0.001	0.046	0.781	0.987
Women	Low	1.38 (1.12-1.70)	1.08 (0.86-1.34)	0.86 (0.66-1.12)	0.76 (0.53-1.09)	0.71 (0.46-1.07)
	Moderate	1	1	1	1	1
	High	0.58 (0.42-0.79)	0.82 (0.59-1.13)	1.03 (0.72-1.49)	1.08 (0.68-1.72)	0.87 (0.50-1.52)
	P for trend	<0.001	0.088	0.446	0.299	0.450

Values are expressed as odds ratios (with 95% confidence intervals)..

Model 1, adjusted for age; Model 2, adjusted for age, body mass index, and total energy intake; Model 3, adjusted for all items in model 2 plus smoking status, alcohol consumption, physical activity, educational level, household income, and history of comorbidities; Model 4, adjusted for all items in model 3 plus serum creatinine, high-sensitivity C-reactive protein, total cholesterol, high-density lipoprotein cholesterol, and triglycerides levels..

*Dietary protein intake status was classified as low (<0.8 g/kg body weight/day), moderate (0.8–1.2 g/kg/d), and high (>1.2 g/kg/d) protein intake. ^†Possible sarcopenia was defined as a handgrip strength <28 kg for men and <18 kg for women..

We investigated the association between the amount of daily protein consumed and the reduction in skeletal muscle strength in older Koreans. HGS increased with daily protein intake, and the dietary protein consumption was negatively associated with the prevalence of possible sarcopenia in both men and women. However, there were no differences in the daily protein intake and HGS value or possible sarcopenia prevalence after adjustment for covariates.

Possible sarcopenia predicts physical disability and mortality in older adults [9,10]. Muscle mass is responsible for muscle strength, but maintaining or gaining skeletal muscle mass does not completely prevent declines in muscle strength [22]. Therefore, it is important to identify the factors that affect the development of sarcopenia in older adults. Such factors include aging, physical inactivity, inadequate nutrition, and comorbid diseases/conditions [13,14]. There are few studies on the effects of protein intake on skeletal muscle strength and the results are inconsistent. Several prospective studies have shown that higher protein intake is associated with a reduction in the loss of muscle strength and function [23], but no differences according to protein supplementation were observed in muscle strength compared with a placebo group in a randomised controlled trial of 116 older adults [24]. A meta-analysis revealed that protein supplementation alone, without concomitant nutritional or exercise interventions, did not increase muscle strength [16], which was similar to our results.

In this study, we found no association between daily total protein intake and possible sarcopenia in older Koreans. Several factors may explain the lack of association. We evaluated the relationship between protein intake and muscle strength, independent of the potential concurrent effects of several factors by adjusting the covariates, including a ‘physical activity’ variable. Studies have confirmed the effects of exercise/physical activity on muscle strength [25], and a close interaction of physical activity, protein intake, and muscle strength [26]. However, the relationship between protein intake and muscle health has been inconsistent [16,27]. Further studies of the concurrent effects of protein intake and physical activity on skeletal muscle strength are needed in older Koreans. An even distribution of protein intake across meals [28], high-quality protein containing indispensable amino acids [29], or the source of the dietary protein [30] might affect skeletal muscle health, but these factors were not included in this study. Therefore, additional research should consider the association between total daily protein, and the distribution, quality, and source of dietary protein consumed on muscle strength.

The data used in this study were collected from a nationally representative survey in South Korea which is the first cross-sectional study of older Koreans to investigate the association between the amount of dietary protein consumed and possible sarcopenia. In addition, we analysed the KNHANES data, including the protein intake estimated by the semi-quantitative FFQ, which is a reliable and valid instrument for estimating nutrient intake in the Korean population and specific sociodemographic information was used to adjust for confounding factors. However, this study had some limitations. First, it had a cross-sectional design. Second, the relationships of mealtime distribution of protein intake, and the quality or source of dietary protein, and possible sarcopenia were not assessed because these were not measured in KNHANES. Third, we included only Koreans; therefore, it is unclear whether our findings can be generalised to other ethnicities. In conclusion, there were no associations between daily protein intake, HGS, and possible sarcopenia prevalence in older Koreans. Further studies focusing on the interactions of protein intake with other factors, such as physical activity are needed to evaluate the relationship between the amount of protein intake and possible sarcopenia.

Statistical consultation was supported by the Department of Biostatistics of the Catholic Research Coordinating Center.

The authors declare no conflict of interest.

HN Kim and SW Song conceived the study; HN Kim and SW Song analysed and interpreted the data; HN Kim wrote the manuscript; SW Song supervised writing of the paper and provided critical revisions; HN Kim and SW Song read and approved the final manuscript.