Abstract
-
Background
Sarcopenia is an age-related disease, and is assumed to be associated with systemic inflammation. We examined the relationship between the neutrophil-to-lymphocyte ratio (NLR), an easily accessible inflammatory marker, and sarcopenia in older adults.
-
Methods
This retrospective cross-sectional study, medical records of patients visiting a tertiary hospital’s health check-up center were analyzed. The study included older adults aged 60 and over, and who had their grip strength, skeletal muscle mass, and complete blood count with differential tests measured. In this study, sarcopenia was defined as the presence of both low muscle mass and weak grip strength according to the Asian Working Group for Sarcopenia 2019 criteria.
-
Results
Of the 2,385 participants, 74 participants (3.10%) had sarcopenia. The non-sarcopenia group was younger than the sarcopenia group (mean age, 65.8±5.4 vs. 73.2±7.5). The average NLR of participants without sarcopenia was 1.75±0.97 and the average NLR of participants with sarcopenia was 2.08±1.11 (P=0.004). The number of participants with sarcopenia increased across higher NLR quintile (P for trend=0.016), as well as those with low skeletal muscle mass (P for trend<0.001) and weak grip strength (P for trend=0.009).
-
Conclusions
Older adults with a high NLR may be considered for sarcopenia screening.
-
Key words: Aged · Hand strength · Lymphocytes · Neutrophils · Primary health care · Sarcopenia
GRAPHICAL ABSTRACT
INTRODUCTION
1. Sarcopenia
Sarcopenia is commonly observed during the aging process, which is associated with a reduction in muscle mass and strength.[
1] Sarcopenia is associated with negative health outcomes, such as falls, reduced physical activity, hospitalization, and death.[
2] Therefore, screening for sarcopenia is important in old age. To diagnose sarcopenia, muscle mass is measured using devices such as dual energy X-ray absorptiometry (DXA), bioelectrical impedance analysis (BIA), grip strength using a grip dynamometer, and physical performance by measuring walking speed or standing up speed from a chair. Due to a lack of time and tools, it is difficult to perform diagnostic tests for sarcopenia. It is not easy to identify individuals at a high-risk group for sarcopenia because the presence or absence of sarcopenia cannot be determined through only history taking or simple physical examination. Strength, assistance with walking, rising from a chair, climbing stairs, and falls (SARC-F) questionnaire is a simple questionnaire used for screening sarcopenia without any tools. However, the SARC-F questionnaire has high specificity but low sensitivity, and therefore has limited clinical utility.[
3]
Various mechanisms, including malnutrition, insufficient protein intake, low physical activity, hormonal changes, and chronic inflammation, are assumed to underlie sarcopenia.[
4–
6] Decreases in testosterone, insulin growth factor-1, and anabolic hormones (such as growth hormone) are associated with decreased muscle mass and decreased physical performance.[
5,
6] Multiple studies have reported an association between sarcopenia and systemic inflammation, and various inflammatory markers [
7,
8] such as interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and C-reactive protein (CRP) have been shown to contribute to muscle wasting.[
5,
9] In old-age-associated sarcopenia, pro-inflammatory cytokines and acute-phase proteins are increased, and the inflammatory markers are also higher than in younger age, which contribute to muscle catabolic mechanisms, apoptosis, and proteolysis.[
9] Although various inflammatory markers have been studied in relation to sarcopenia, most of these markers are difficult to measure in clinical settings. Therefore, we attempted to identify inflammatory markers that can be easily measured in a clinical setting.
The neutrophil-to-lymphocyte ratio (NLR) is an index of systemic inflammation.[
10] It is used as a prognostic marker for some diseases, including cancer [
11,
12] and cardiovascular diseases.[
13] However, the relationship between NLR and sarcopenia is not well established. Previous research has produced inconsistent findings regarding the relationship between NLR and sarcopenia. A cross-sectional study showed that NLR was higher in the sarcopenic group,[
14] while another study found NLR related with decrements in grip strength in old adults.[
15] However, other study found no association between sarcopenia and NLR using various other diagnostic criteria for sarcopenia. [
16] Additionally, in hemodialysis patients, one study observed that NLR was associated with sarcopenia risk only in overweight group, but no such association was found in non-overweight patients.[
17] If high-risk individuals for sarcopenia can be identified using routine laboratory tests, early intervention may help prevent sarcopenia-related complications and improve health outcomes in the older adults. As mentioned earlier, some previous studies showed associations between NLR and sarcopenia; however, several studies demonstrated correlations only in specific groups, and some research showed controversy. There have been few studies analyzing the relationship between sarcopenia and NLR specifically in healthy older adults. So, this study aimed to investigate the relationship between NLR and sarcopenia.
METHODS
1. Data source and study population
This was a retrospective cross-sectional study that analyzed the medical records of health check-up participants at the health check-up center of a tertiary hospital from April 2015 to October 2020. We selected patients who were ≥60 years of age, and who had their grip strength, skeletal muscle mass, complete blood count (CBC) with differential tests measured. Individuals with diseases that may affect CBC with differential tests (e.g., autoimmune diseases, blood cancer, anemia, thrombocytopenia, and eosinophilia) or who had any acute stage of infection were excluded.
2. Laboratory data
Blood tests such as CBC with differential tests, fasting glucose, glycated hemoglobin, aspartate aminotransferase, alanine aminotransferase, γ-glutamyl transferase, total cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, uric acid, high-sensitivity CRP (hsCRP) were performed. All tests, including blood tests, body composition measurements using BIA, and grip strength measurement, were performed after an overnight fast of at least 10 hr. The NLR was calculated by dividing the absolute neutrophil count by the absolute lymphocyte count. Some studies have reported cutoff values for specific populations, such as non-geriatric population [
18] or for specific diseases,[
19,
20] but there is no consensus on the cutoff value for the NLR. Therefore, in this study, trend analysis was performed by dividing NLR into five divisions.
Various criteria are available for diagnosing sarcopenia. In this study, the diagnostic criteria defined by the Asian Working Group for Sarcopenia (AWGS) 2019, which is the latest sarcopenia diagnostic criteria analyzed in Asian race, were used.[
21] Skeletal muscle mass was measured using a BIA machine, InBody 720 or InBody 770 (InBody, Seoul, Korea). The InBody 720 and InBody 770 can measure whole-body skeletal muscle mass but cannot directly measure appendicular skeletal muscle mass (ASM), which is the skeletal muscle mass of the extremities. In this study, ASM was obtained by multiplying whole-body skeletal muscle measured with InBody 720 or InBody 770 by a constant of 0.75.[
22] ASM divided by the square of the height was defined as the ASM index.
The diagnostic criteria for sarcopenia include low muscle mass, weak grip strength, and decreased physical performance. However, assessments of physical performance, such as the 6-meter gait speed test or the 5-time chair stand test, were not conducted at the health check-up center. Therefore, in this study, sarcopenia was defined as the presence of both low muscle mass and weak grip strength, excluding the evaluation of physical performance.
Skeletal muscle mass was analyzed to be low when the ASM index was <7.0 kg/m2 for men and <5.7 kg/m2 for women. The grip strength was measured using a hand dynamometer (Jamar 5030J1; Sammons Preston Rolyan, Bolingbrook, IL, USA). Participants’ grip strength in both hands was measured twice. Under the instructions of a trained nurse, the participants squeezed the dynamometer with maximum force for at least 3 sec. The grip strengths were measured twice for both hands and the measurement depicting the stronger grip strength was recorded and used for statistical analysis. Patients with hand pain or injuries were excluded from the study. Men with grip strength of less than 28 kg and women with grip strength of less than 18 kg were defined as having weak grip strength.
4. Covariates
Height, weight, BMI, and waist circumference were measured for all participants, and these were performed by a trained nurse. Height and weight were measured using a machine, and waist circumference was directly measured using a tape measure at the middle of the lowermost rib and uppermost pelvis. Social history (e.g., smoking, problem drinking, enough exercise, and underlying disease) was investigated using self-reported questionnaires and questionnaires completed by experienced nurses. Smoking was classified into current smoking, past smoking, and non-smoking. Drinking was classified as problem drinking when men consumed more than seven drinks per week and women consumed more than three drinks per week, according to the drinking standards of the elderly. Enough exercise was defined as 150 min or more of moderate-intensity exercise per week or 75 min of high-intensity exercise per week.
5. Statistical analysis
For each NLR quintile, trends in the number of persons with sarcopenia, skeletal muscle mass below the cutoff, and grip strength below the cutoff were analyzed. The Jonckheere-Terpstra test was used to analyze the
P for trends. Odds ratios (ORs) were obtained using unadjusted univariate and adjusted multivariate logistic regression analyses to determine the association between skeletal muscle mass, grip strength, and NLR. To reduce the bias in logistic regression caused by a small number of people with sarcopenia, STATA’s FIRTHLOGIT module was used for the analysis (
https://ideas.repec.org/c/boc/bocode/s456948.html). This module applies the statistical technique proposed by Firth which implements penalized maximum likelihood estimation method.[
23]
All analyses were performed using STATA software (version 15.0; Stata Corp., College Station, TX, USA), and a P value less than or equal to 0.05 was considered statistically significant.
RESULTS
In the total of 2,385 participants, 74 participants (3.10%) had sarcopenia. (
Table 1). The non-sarcopenia group was younger than the sarcopenia group (mean age, 65.8±5.4 vs. 73.2±7.5), and there was no significant gender difference between the two groups. Without sarcopenia, mean grip strength was 36.6±6.9 kg for men and 22.0±4.4 kg for women, the mean ASM index was 7.79±0.68 kg for men, 6.35±0.52 kg for women. In the sarcopenia group, the mean grip strength was 23.4±3.4 kg for men, 14.7±2.6 kg for women. The mean ASM index was 6.49±0.66 kg for men and 5.37±0.26 kg for women. The average NLR of participants without sarcopenia was 1.75±0.97 and the average NLR of participants with sarcopenia was 2.08±1.11 (
P=0.004). Among the blood tests, hsCRP was 0.1±0.46 for participants with non-sarcopenia, and 0.34±1.07 for those with sarcopenia (
P=0.023), but both was within normal limit. Total leukocytes, neutrophils, and monocytes were also significantly different between the two groups. There were no significant differences in the prevalence of underlying diseases and the blood tests related to diabetes, dyslipidemia, or liver enzymes between the two groups. All anthropometric data collected differed between the groups (
P<0.001). There were no statistically significant differences in smoking, drinking, or sufficient exercise.
The body composition across the quintiles based on NLR is presented in
Table 2. The average NLR values for each quintile were 0.93±0.16, 1.29±0.08, 1.59±0.09, 1.97±0.13, and 3.04±1.43. The number of participants with sarcopenia increased as the NLR increased (
P for trend=0.016). The number of participants with low skeletal muscle mass (
P for trend<0.001) and weak grip strength (
P for trend= 0.009) also showed an increasing trend according to the NLR. As the NLR increased, age showed an increasing trend (
P for trend<0.001).
Table 3 shows the results of the multivariate analysis of sarcopenia based on NLR. Sarcopenia and NLR were statistically significantly correlated in the unadjusted model (Model 1), and the adjusted model for age and gender (Model 2), and adjusted model for age, gender, underlying diseases (diabetes, hypertension, dyslipidemia), and social history (sufficient exercise, problem drinking, and smoking) (Model 3) (unadjusted OR, 1.19; 95% confidence interval [CI], 1.05–1.33; model 2 OR, 1.18; 95% CI, 1.01–1.37; model 3 OR, 1.19; 95% CI, 1.02–1.39).
To adjust for age as a strong confounding variable, we conducted additional analyses. First, we included an age-squared variable to adjust for non-linear effects of age. Even with this adjustment, significant correlations remained between NLR and sarcopenia defined by muscle mass and handgrip strength (
Supplementary Table 1). However, when we performed subgroup analysis by dividing participants into two age groups, 60 to 69 years and 70 years or older, no significant correlation between NLR and sarcopenia was observed (
Supplementary Table 2).
We used Youden index estimation to determine the optimal cutoff value for screening sarcopenia, and found the estimated cutoff value for NLR was 2.25, with a sensitivity of 0.34 and specificity of 0.82. The area under receiver operating characteristic curve of NLR for screening sarcopenia was 0.5933, indicating limited predictive value.
DISCUSSION
In this study, NLR was significantly associated with sarcopenia, low skeletal muscle mass, and weak grip strength in individuals undergoing health check-ups, even after adjusting for several confounding variables.
Several studies have been conducted to examine the relationship between sarcopenia and NLR. A study investigated the relationship between NLR and sarcopenia by comparing the average NLR values between sarcopenic and non-sarcopenic participants aged over 60 years, and found no significant differences between the groups.[
16] In a cross-sectional study conducted on hemodialysis patients, NLR was associated with the risk of sarcopenia.[
24] In a cross-sectional study conducted on the general population in the U.S., higher NLR quartiles were associated with sarcopenia and mortality.[
25] These findings are consistent with the results of our study. Not only has the association between NLR and the prevalence of sarcopenia been reported, but studies have also examined its relationship with frailty and malnutrition, which are closely related to sarcopenia. A cross-sectional study of older women residing in nursing homes found a negative correlation between NLR and frailty.[
26] A cross-sectional study suggested negative relationships between NLR and good nutritional status.[
27] This suggests that NLR is not only associated with sarcopenia but may also be linked to the overall health status related to sarcopenia.
Multiple studies have reported an association between sarcopenia and systemic inflammation, and various inflammatory markers [
7,
8] such as IL-6, TNF-α, and CRP have been shown to contribute to muscle wasting.[
5,
9] In old-age-associated sarcopenia, pro-inflammatory cytokines and acute-phase proteins are increased, and the inflammatory markers are also higher than in younger age, which contribute to muscle catabolic mechanisms, apoptosis, and proteolysis.[
9] Although various inflammatory markers have been studied in relation to sarcopenia, most of these markers are difficult to measure in clinical settings. Therefore, we attempted to identify inflammatory markers that can be easily measured in a clinical setting.
If a cutoff value is established, it becomes more applicable for clinical settings. Therefore, we sought to identify an NLR cutoff value for screening sarcopenia. Although the AUC of NLR was quite low, limiting its acceptability, we estimated the cutoff value of NLR to be 2.25. Several studies have discussed cutoff values for NLR to predict sarcopenia, but with varying results. The NLR cutoff value for predicting sarcopenia in patients undergoing maintenance hemodialysis was 3.28,[
28] while for hospitalized cancer patients, it was 6.5.[
29] For hospitalized renal cell carcinoma patients, the NLR cutoff value for predicting sarcopenia risk was 2.88.[
30] However, we thought these patient groups had higher NLR values compared to our participants because they were suffering from severe illnesses which can affect inflammatory markers. In this study, the inflammatory markers we measured were NLR and CRP, with CRP remaining within normal reference ranges despite statistical significance. For NLR, although there is no established meaningful cutoff, various NLR values have been proposed as cutoff values for predicting different diseases, which are generally slightly higher than the cutoff we calculated.[
19] This indicates that the NLR in this study, like CRP, may be below the pathological range. This suggests that the inflammatory markers change associated with sarcopenia in healthy population are subtle and may represent early pathological changes rather than overt clinical inflammation. However, we thought the NLR difference in our study may be meaningful because there was a significant trend between increasing NLR and decreasing muscle strength and skeletal muscle mass, we believed NLR had a significant correlation with these factors.
This study targeted older adults who voluntarily underwent health check-ups, resulting in participants who were relatively healthy, physically capable, and financially secure. The prevalence of sarcopenia is higher in frail or institutionalized older people, and adverse outcomes (e.g., fall fractures, hospitalization, mortality) are more serious when sarcopenia occurs in these populations. Therefore, the exclusion of this population is a limitation of our study. However, screening for sarcopenia in healthy older adults also has its own advantages. For example, preventive interventions for sarcopenia can be proactively implemented to prevent functional decline in healthy older adults and delay the progression of sarcopenia before it interferes with daily activities. Sarcopenia interventions may have positive effects on physical function, and some studies have reported limited improvements in muscle strength and muscle mass.[
31,
32] Therefore, preventive interventions for sarcopenia targeting healthy older adults are estimated to be more cost-effective than intervening in already frail older adults.
In addition, the relatively large number of participants (2,385 participants) were a strong point of this study. NLR, while requiring further validation and established cutoff value, may be considered as an exploratory parameter for sarcopenia in primary care due to its accessibility. Although DXA is the gold standard for muscle mass measurement, few primary care institutions are equipped with DXA devices. BIA is relatively widespread in primary care institutions because it is smaller and less expensive than DXA. Using BIA instead of DXA for muscle mass analysis is an advantage of this study because it is suitable for use in primary care institutions. In addition, previous studies have reported that muscle mass measured using BIA is highly correlated with muscle mass measured using DXA.[
33,
34] Muscle mass measured using BIA had a certain bias compared to that measured using DXA. BIA tends to underestimate fat mass and overestimate lean mass compared with DXA.[
35] However, bias was not a problem because this study defined the evaluation standard for skeletal muscle mass using the AWGS 2019 BIA cutoff values.
This study had a few limitations. As a retrospective analysis of data from a single tertiary hospital’s health checkup center, establishing a causal relationship between NLR and sarcopenia was challenging. While this center included handgrip strength measurements and muscle mass assessment using BIA, which is not standard practice in most health check-up centers, it did not perform the short physical performance battery (SPPB) or other physical function measurements. Consequently, we were unable to evaluate participants with low physical performance, potentially leading to underdiagnosis of sarcopenia cases. This may explain why our study identified fewer individuals with sarcopenia compared to other studies.[
36,
37] This created a substantial imbalance between sarcopenic and non-sarcopenic groups, potentially affecting statistical robustness. To address this issue, we employed the FIRTHLOGIT module, which applies penalized maximum likelihood estimation to reduce bias in generalized linear models with rare events, although this approach cannot fully resolve the underlying imbalance. This study analyzed the correlation between low muscle mass, weak grip strength, and NLR. Further studies on physical performance will clarify the causal relationship between sarcopenia and NLR.
In conclusion, higher NLR was associated with an increased prevalence of sarcopenia, reduced skeletal muscle mass, and reduced grip strength. This relation appeared even after adjusting for confounding variables such as age and gender. Therefore, older adults with a high NLR may be considered for sarcopenia screening.
DECLARATIONS
-
Funding
The authors received no financial support for this article.
-
Ethics approval and consent to participate
This study was performed in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board (IRB) of the Clinical Research Ethics Committee of Jeju National University Hospital (IRB no. 2023-09-001).
-
Conflict of interest
No potential conflict of interest relevant to this article was reported.
Supplementary Information
Table 1General characteristics of participants by sarcopenic status
Table 1
|
Non-sarcopenia (N=2,311) |
Sarcopenia (N=74) |
P-value |
|
Age |
65.8±5.4 |
73.2±7.5 |
<0.001 |
|
|
Women |
1,025 (44.4) |
35 (47.3) |
0.616 |
|
|
Anthropometric data |
|
Height (cm) |
161.0±8.2 |
156.8±8.4 |
<0.001 |
|
Weight (kg) |
66.3±10.5 |
56.3±8.9 |
<0.001 |
|
BMI (kg/m2) |
25.5±3.0 |
22.8±2.5 |
<0.001 |
|
Waist circumference (cm) |
87.7±8.3 |
83.5±8.6 |
<0.001 |
|
Grip strength (kg) |
30.1±9.4 |
19.3±5.3 |
<0.001 |
|
Appendicular skeletal muscle mass (kg) |
7.15±0.94 |
5.96±0.76 |
<0.001 |
|
Fat mass (%) |
31.2±7.2 |
32.8±8.0 |
0.574 |
|
|
NLR-related laboratory data |
|
WBC |
5,434±1,626 |
5,950±1,984 |
0.008 |
|
Neutrophil |
3,007±1,308 |
3,541±1,683 |
0.001 |
|
Lymphocyte |
1,832±534 |
1,806±540 |
0.685 |
|
Monocyte |
401±137 |
450±142 |
0.003 |
|
Platelet |
232,898±54,053 |
239,311±61,409 |
0.317 |
|
NLR |
1.75±0.97 |
2.08±1.11 |
0.004 |
|
|
Social history |
|
Smoke |
|
|
0.330 |
|
Nonsmoker |
1,104 (47.8) |
39 (52.7) |
|
|
Ex-smoker |
656 (28.4) |
13 (17.6) |
|
|
Current smoker |
285 (12.3) |
9 (12.2) |
|
|
Problem drink |
449 (19.4) |
8 (10.8) |
0.064 |
|
Exercise |
1,439 (62.3) |
40 (54.1) |
0.152 |
|
|
Underlying disease |
|
Diabetes |
340 (14.7) |
15 (20.3) |
0.186 |
|
Hypertension |
860 (37.2) |
30 (40.5) |
0.560 |
|
Dyslipidemia |
696 (30.1) |
17 (23.0) |
0.187 |
|
|
Other laboratory data |
|
Fasting glucose (mg/dL) |
104.2±23.3 |
105.7±26.6 |
0.593 |
|
HbA1c (%) |
6.0±0.9 |
6.1±1.2 |
0.412 |
|
Insulin (μU/mL) |
6.8±7.3 |
6.7±4.4 |
0.942 |
|
HOMA-IR |
1.8±1.9 |
1.8±1.4 |
0.924 |
|
AST (IU/L) |
28.8±14.7 |
29.7±14.4 |
0.591 |
|
ALT (IU/L) |
28.0±18.1 |
26.9±18.0 |
0.612 |
|
GGT (IU/L) |
38.4±47.9 |
33.0±22.5 |
0.331 |
|
Uric acid (mg/dL) |
5.5±1.4 |
5.6±1.7 |
0.351 |
|
Total cholesterol (mg/dL) |
190.3±40.4 |
186.1±36.9 |
0.377 |
|
Triglyceride (mg/dL) |
107.1±60.8 |
107.3±57.6 |
0.975 |
|
HDL-cholesterol (mg/dL) |
55.1±14.3 |
55.4±17.6 |
0.903 |
|
LDL-cholesterol (mg/dL) |
117.6±36.1 |
110.2±33.2 |
0.083 |
|
hsCRP (mg/L) |
0.10±0.46 |
0.34±1.07 |
0.002 |
Table 2Comparison of body composition according to each quintile divided by neutrophil-to-lymphocyte ratio
Table 2
|
Quintile |
<20% |
20–40% |
40–60% |
60–80% |
≥80% |
P for trend |
|
NLR |
0.93±0.16 |
1.29±0.08 |
1.59±0.09 |
1.97±0.13 |
3.04±1.43 |
<0.001 |
|
Sarcopenia |
9 (1.89) |
15 (3.14) |
13 (2.73) |
12 (2.52) |
25 (5.24) |
0.016 |
|
Low muscle mass |
42 (8.81) |
50 (10.48) |
55 (11.53) |
68 (14.26) |
85 (17.82) |
<0.001 |
|
Weak grip strength |
56 (11.74) |
76 (15.93) |
75 (15.72) |
73 (15.30) |
90 (18.87) |
0.009 |
Table 3Multivariate analysis of sarcopenia according to neutrophil-to-lymphocyte ratio
Table 3
|
Model 1 |
Model 2 |
Model 3 |
|
|
|
|
OR (95% CI) |
P-value |
OR (95% CI) |
P-value |
OR (95% CI) |
P-value |
|
NLR |
1.19 (1.05–1.33) |
0.004 |
1.18 (1.01–1.37) |
0.034 |
1.19 (1.02–1.39) |
0.030 |
|
|
Age |
|
|
1.18 (1.14–1.22) |
<0.001 |
1.18 (1.14–1.23) |
<0.001 |
|
|
Sex |
|
|
1.22 (0.76–1.98) |
0.408 |
1.86 (0.87–3.94) |
0.108 |
|
|
Diabetes |
|
|
|
|
1.93 (1.01–3.69) |
0.046 |
|
|
Hypertension |
|
|
|
|
0.71 (0.40–1.24) |
0.228 |
|
|
Dyslipidemia |
|
|
|
|
0.64 (0.34–1.20) |
0.167 |
|
|
Exercise |
|
|
|
|
0.73 (0.43–1.24) |
0.239 |
|
|
Smoke |
|
|
|
|
1.30 (0.76–2.21) |
0.334 |
|
|
Alcohol |
|
|
|
|
0.92 (0.40–2.13) |
0.844 |
|
|
hsCRP (mg/L) |
|
|
|
|
1.12 (0.88–1.44) |
0.353 |
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