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Malnutrition or nutritional risk is often found in elderly inpatients[1-2], primarily due to aging, effects of diseases and drugs, and inadequate dietary intake. Malnutrition or nutritional risk is associated with poor clinical outcomes, longer hospitalizations, a higher likelihood of hospital readmission, higher rates of mortality, and greater hospital expenditures[3-6]. Many nutritional screening or assessment tools are used in hospitals in order to recognize these patients as early as possible, facilitate earlier nutritional intervention, and improve health outcomes. The Nutritional Risk Screening (NRS 2002)[7] has been successfully implemented throughout Europe and is recommended for nutritional risk screening of hospitalized patients in China. The Subjective Global Assessment (SGA)[8] is widely used in nutritional assessment and has been recommended as the outcome measure in clinical trials[9-10]. The SGA score can predict health outcomes in elderly hospitalized patients[11]. NRS 2002 is used to identify nutritional risk, whereas SGA detects malnutrition, which is the greatest distinction between the two. They are similar because they both consider the metabolic stress of disease and changes in food intake, although NRS 2002 classifies metabolic stress using numerical scores, whereas SGA depends on the investigatora's experience to indicate the metabolic stress of disease[12]. SGA has questions related to the detection of chronic malnutrition; in contrast, NRS 2002 contains questions that indicate a more recent or acute change in nutritional status[13]. These assessment tools are closely related to body weight, particularly, the circumstances surrounding weight that can be determined in an accurate physical assessment conducted by trained staff. It is difficult to carry out such an assessment on every patient, as there are many hospitalized patients in China. Although malnutrition and nutritional risk cannot be assessed using a single parameter, the search is on for an indicator that is a simple and rapid measurement and can increase the accuracy of nutritional evaluation tools.
Patients with malnutrition or nutritional risk have lower hand grip strength (HGS). The potential explanation for this is that malnutrition can reduce protein synthesis, cause muscle fiber atrophy, and reduce muscle mass, further leading to decreased muscle function. Some studies hypothesized that the pathogenesis of impaired muscle function in malnutrition involves reduction of glycolytic enzyme[14-15], creatine[16], and mitochondrial complex activities[17], leading to reductions in muscle glycolysis, phosphocreatine, and oxidative phosphorylation, respectively. Additionally, muscle protein stores have been found to respond rapidly to restoration of nutrition[18]. Together, these mechanisms account for the ability of HGS to predict nutritional status. HGS, a commonly used tool for the assessment of muscle function, has been regarded as an indicator of nutritional status in recent reports[18-19]. HGS can also independently predict nutritional status and changes in nutritional status defined by the Patient-Generated Subjective Global Assessment (PG-SGA) score and category[19]. In addition, HGS may be useful for forecasting prognosis in patients with congestive heart failure[20]. HGS is a rapid, cost-effective nutrition assessment tool; to the best of our knowledge, there is no evaluation standard, and there are no cut-points for malnutrition or nutritional risk in elderly inpatients in China.
The present study aims to assess the nutritional status and the application of HGS in nutrition assessment of elderly inpatients at hospital admission. We anticipate that HGS will show a significant correlation with NRS 2002 and SGA scores and that a combination of the two can be used as an accurate predictor of nutrition status.
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The characteristics of the 1, 343 patients are shown in Table 1. There was no difference in age between men and women. Respiratory (14.59%), endocrinological (15.26%), neurological (22.93%), gastroenterological (11.39%), and cardiological (25.76%) diseases were common at hospital admission. BMI, WC, CC, and HGS; serum levels of TP, Cr, TG, TC, Hb, and CRP; and the number of internal medicine patients were significantly different between women and men.
Table 1. Baseline Characteristics of Study Subjects
Variables Men (n = 691) Women (n = 652) Total (n = 1, 343) P Value Age (years) 74.0 ± 6.1 73.6 ± 5.6 73.8 ± 5.9 0.286 Body Measurement Height (cm) 169.6 ± 5.9 157.5 ± 5.7 163.7 ± 8.3 < 0.001 Weight (kg) 69.2 ± 11.1 61.2 ± 11.6 65.3 ± 12.0 < 0.001 BMI (kg/m2) 24.1 ± 3.7 24.7 ± 4.4 24.3 ± 4.0 0.007 WC (cm) 91.3 ± 10.9 88.9 ± 11.4 90.1 ± 11.2 < 0.001 CC (cm) 34.5 ± 3.6 33.0 ± 3.7 33.8 ± 3.8 < 0.001 Left HGS (kg) 25.1 ± 8.4 15.4 ± 5.8 20.3 ± 8.8 < 0.001 Right HGS (kg) 26.5 ± 8.7 16.6 ± 6.1 21.7 ± 9.0 < 0.001 Optimal HGS (kg) 26.7 ± 8.6 16.6 ± 6.0 21.8 ± 9.0 < 0.001 Mean HGS (kg) 25.8 ± 8.3 15.9 ± 5.8 21.0 ± 8.7 < 0.001 Blood Biochemical Assays ALB (g/L) 38.44 ± 5.12 38.61 ± 5.07 38.52 ± 5.09 0.534 TP (g/L) 64.82 ± 7.23 66.46 ± 7.62 65.64 ± 7.46 < 0.001 BUN (mmol/L) 6.88 ± 5.32 6.67 ± 4.37 6.78 ± 4.88 0.447 Cr (μmol/L) 93.51 ± 55.0 84.81 ± 88.89 89.31 ± 73.42 0.031 TG (mmol/L) 1.29 ± 0.90 1.67 ± 1.88 1.48 ± 1.48 < 0.001 TC (mmol/L) 4.20 ± 2.21 4.73 ± 1.42 4.46 ± 1.89 < 0.001 Hb (g/L) 129.91 ± 21.04 119.52 ± 18.09 124.83 ± 20.32 < 0.001 CRP (mg/dL) -median (P25-P75) 2.1 (0.51-11.81) 2.53 (0.54-9.20) 2.3 (0.51-10.7) 0.675 Patients of internal medicine [n(%)] < 0.001 Respiratory 123 (17.80) 73 (11.20) 196 (14.59) Endocrinology 90 (13.02) 115 (17.64) 205 (15.26) Neurology 183 (26.48) 125 (19.17) 308 (22.93) Gastroenterology 78 (11.29) 75 (11.50) 153 (11.39) Cardiology 166 (24.03) 180 (27.61) 346 (25.76) Nephrology 26 (3.76) 38 (5.83) 64 (4.77) Rheumatology 25 (3.62) 46 (7.06) 71 (5.29) Note. Data are expressed as mean± SD or number (percentage) of subjects. Statistical significance of difference is calculated between men and women subjects. BMI: body mass index; HGS: handgrip strength; WC: waist circumference; CC: calf circumference; ALB: albumin; TP: total protein; Cr: creatinine; TG: triglyceride; TC: total cholesterol; Hb: hemoglobin; BUN: blood urea nitrogen; CRP: C-reactive protein. -
The classification of nutritional status by NRS 2002 showed that 63.81% of the population was at nutritional risk (men 69.75%, women 57.52%), while the classification of nutritional status by SGA showed that 28.22% were malnourished (men 25.57%, women 31.13%). Women were at a lower nutritional risk, but at a higher risk of being malnourished (Figure 1).
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The left HGS, right HGS, mean HGS, optimal HGS, BMI, WC, and CC and the serum levels of ALB, TG, and Hb of inpatients with malnutrition or nutritional risk were significantly lower than those of well-nourished inpatients, both male and female. However, in women, age and CRP were higher, and the serum level of TP was significantly lower in malnutrition or nutritional risk inpatients than in well-nourished inpatients (Table 2).
Table 2. The Comparison HGS, Anthropometry and Blood Biochemical Assays of Different Nutrition Status of Study Subjects
Parameters NRS 2002 SGA ≥ 3 < 3 P Value B or C A P Value Men Left HGS (kg) 21.5 ± 8.3* 27.5 ± 7.6 < 0.001 20.1 ± 7.8* 26.7 ± 8.0 < 0.001 Right HGS (kg) 22.6 ± 8.4* 29.1 ± 7.9 < 0.001 21.5 ± 8.3* 28.7 ± 7.9 < 0.001 Mean HGS (kg) 22.0 ± 7.9* 28.3 ± 7.5 < 0.001 20.6 ± 7.7* 27.6 ± 7.7 < 0.001 Optimal HGS (kg) 22.8 ± 8.2* 29.3 ± 7.9 < 0.001 21.1 ± 7.8* 28.4 ± 8.1 < 0.001 Age (year) 75.9 ± 5.6* 72.7 ± 6.0 < 0.001 75.6 ± 6.4* 73.4 ± 5.9 < 0.001 BMI (kg/m2) 22.4 ± 4.0* 25.1 ± 3.0 < 0.001 21.9 ± 3.7* 24.8 ± 3.3 < 0.001 WC (cm) 87.3 ± 11.7* 93.9 ± 9.5 < 0.001 86.1 ± 11.2* 93.1 ± 10.2 < 0.001 CC (cm) 33.3 ± 3.8* 35.4 ± 3.2 < 0.001 32.4 ± 3.7* 35.3 ± 3.3 < 0.001 ALB (g/L) 37.2 ± 4.9* 39.2 ± 5.1 < 0.001 36.2 ± 5.4* 39.2 ± 4.8 < 0.001 TP (g/L) 64.3 ± 7.6 65.2 ± 7.0 0.105 64.1 ± 8.1 65.1 ± 6.9 0.128 TG (mmol/L) 1.09 ± 0.59* 1.42 ± 1.04 < 0.001 1.07 ± 0.56* 1.36 ± 0.98 < 0.001 TC (mmol/L) 4.02 ± 1.04 4.32 ± 2.70 0.094 3.99 ± 1.15 4.27 ± 2.46 0.161 HB (g/L) 125.7 ± 23.2* 132.5 ± 19.1 < 0.001 122.1 ± 23.7* 132.5 ± 19.4 < 0.001 CRP (mg/dL) -median (P25-P75) 2.57 (0.34-21.76) 2.06 (0.56-9.00) 0.514 1.72 (0.67-40.51) 2.10 (0.40-9.94) 0.072 Women Left HGS (kg) 13.1 ± 5.5* 16.9 ± 5.5 < 0.001 12.9 ± 5.4* 16.5 ± 5.6 < 0.001 Right HGS (kg) 14.0 ± 5.5* 18.3 ± 5.8 < 0.001 13.6± 5.6* 17.9 ± 5.8 < 0.001 Mean HGS (kg) 13.5 ± 5.4* 17.5 ± 5.5 < 0.001 13.2 ± 5.6* 17.2 ± 5.5 < 0.001 Optimal HGS (kg) 14.1 ± 5.6* 18.3 ± 5.7 < 0.001 13.6 ± 5.6* 18.0 ± 5.7 < 0.001 Age (year) 75.5 ± 5.5* 72.3 ± 5.4 < 0.001 75.0 ± 6.0* 73.0 ± 5.4 < 0.001 BMI (kg/m2) 22.7 ± 4.5* 26.0 ± 3.9 < 0.001 22.4 ± 4.4* 25.7 ± 4.0 < 0.001 WC (cm) 86.0 ± 12.1* 90.8 ± 10.4 < 0.001 84.9 ± 11.7* 90.6 ± 10.7 < 0.001 CC (cm) 31.6 ± 3.9* 33.9 ± 3.4 < 0.001 31.1 ± 3.9* 33.8 ± 3.3 < 0.001 ALB (g/L) 37.5 ± 5.3* 39.4 ± 4.7 < 0.001 37.3 ± 5.4* 39.2 ± 4.8 < 0.001 TP (g/L) 65.4 ± 7.9* 67.2 ± 7.3 0.003 64.8 ± 8.4* 67.2 ± 7.1 0.002 TG (mmol/L) 1.48 ± 1.38* 1.80 ± 2.14 0.039 1.42 ± 0.87* 1.78 ± 2.17 0.028 TC (mmol/L) 4.74 ± 1.76 4.73 ± 1.15 0.976 4.73 ± 1.94 4.74 ± 1.13 0.949 HB (g/L) 117.0 ± 19.7* 121.1 ± 16.8 0.005 115.7 ± 20.5* 121.2 ± 16.7 0.001 CRP (mg/dL) -median (P25-P75) 3.24 (0.60-13.45)* 1.90 (0.46-7.45) 0.039 3.70 (0.77-13.20)* 2.84 (0.55-8.31) 0.043 Note. Statistical significance of difference is calculated between different nutrition status, *P < 0.05. -
The multivariate logistic regression model showed that, in male subjects, according to NRS 2002, the odds ratio (OR) of optimal HGS was 0.93 (95% CI 0.90-0.97, P < 0.001), the age OR was 1.05 (95% CI 1.01-1.10, P = 0.018), and the BMI was 0.83 (95% CI 0.74-0.92, P = 0.001). According to SGA, the optimal HGS was 0.93 (95% CI 0.89-0.96, P < 0.001), the BMI was 0.87 (95% CI 0.77-0.99, P = 0.032), the ALB was 0.85 (95% CI 0.78-0.94, P = 0.001), and the TP was 1.07 (95% CI 1.01-1.13, P = 0.017). For female subjects, according to NRS 2002, the OR of optimal HGS was 0.93 (95% CI 0.89-0.98, P = 0.002), the age was 0.93 (95% CI 0.89-0.98, P = 0.002), and the BMI was 0.80 (95% CI 0.72-0.88, P < 0.001). According to SGA, the OR of optimal HGS was 0.93 (95% CI 0.88-0.98, P = 0.003), the BMI was 0.84 (95% CI 0.76-0.94, P = 0.001), and the CC OR was 0.90 (95% CI 0.82-0.99, P = 0.031). There was no significant difference in any other variable (Table 3).
Table 3. Multivariate Logistic Regression Analyses for Malnutrition or Nutrition Risk Stratified by Gender
Variable NRS 2002 SGA Standardized β OR (95% CI) P Value Standardized β OR (95% CI) P Value Men Optimal HGS -0.07 0.93 (0.90-0.97) < 0.001 -0.08 0.93 (0.89-0.96) < 0.001 Age 0.05 1.05 (1.01-1.10) 0.018 0.01 1.01 (0.96-1.06) 0.827 BMI -0.19 0.83 (0.74-0.92) 0.001 -0.14 0.87 (0.77-0.99) 0.032 WC -0.02 0.98 (0.94-1.01) 0.198 -0.01 0.99 (0.96-1.04) 0.786 CC 0.02 1.02 (0.92-1.12) 0.756 -0.10 0.90 (0.81-1.01) 0.086 ALB 0.06 0.94 (0.87-1.02) 0.162 -0.16 0.85 (0.78-0.94) 0.001 TP 0.01 1.01 (0.96-1.06) 0.608 0.07 1.07 (1.01-1.13) 0.017 TC -0.13 0.88 (0.68-1.13) 0.311 -0.18 0.84 (0.63-1.12) 0.236 Hb 0.01 1.01 (0.99-1.03) 0.116 0.01 1.01 (0.99-1.03) 0.314 CRP 0.01 1.01 (1.00-1.01) 0.190 0.01 1.01 (1.00-1.03) 0.140 Women Optimal HGS -0.07 0.93 (0.89-0.98) 0.003 -0.07 0.93 (0.88-0.98) 0.003 Age 0.07 0.93 (0.89-0.98) 0.002 0.03 0.93 (0.88-0.98) 0.157 BMI -0.23 0.80 (0.72-0.88) < 0.001 -0.17 0.84 (0.76-0.94) 0.001 WC 0.01 1.01 (0.98-1.04) 0.452 0.01 1.01 (0.98-1.05) 0.415 CC 0.03 0.97 (0.89-1.06) 0.505 -0.10 0.90 (0.82-0.99) 0.031 ALB -0.05 0.96 (0.89-1.03) 0.221 0.05 0.96 (0.89-1.04) 0.286 TP -0.01 0.99 (0.95-1.04) 0.743 -0.02 0.98 (0.94-1.03) 0.393 TC 0.02 1.03 (0.86-1.23) 0.792 0.05 1.07 (0.89-1.30) 0.476 Hb 0.01 1.01 (0.99-1.02) 0.238 0.00 1.00 (0.99-1.01) 0.902 CRP 0.00 1.00 (0.99-1.01) 0.451 0.00 1.00 (0.99-1.01) 0.771 Note. β: regression coefficient; OR: odds ratios; CI: confidence interval -
To determine the optimal HGS value to detect nutritional risk and malnutrition in men and women, we calculated the optimal HGS cut-off values by maximizing the Youden Index by sex and age (Table 4 and Figure 2). Based on the ROC curve of NRS 2002, we identified the optimal cut-off points as 27.5 kg (65-74 years) and 21.0 kg (75-90 years) for men and 17.0 kg (65-74 years) and 14.6 kg (75-90 years) for women. Likewise, for SGA, we determined the optimal cut-off points as 24.9 kg (65-74 years) and 20.8 kg (75-90 years) for men and 15.2 kg (65-74 years) and 13.5 kg (75-90 years) for women.
Table 4. Gender-and Age-Specific ROC Curve of the Optimal HGS to Screen Malnutrition or Nutritional Risk on the Basis of SGA and NRS 2002 in Elderly Inpatients
Variable Age (year) AUC SE P 95% CI Cut-point (kg) Sensitivity (%) Specificity (%) Nutritional Risk/Malnutrition, n (%) Men NRS 65-74 0.734 0.027 < 0.001 0.678-0.786 27.5 69.1 63.6 155 (41.11) 2002 75-90 0.670 0.030 < 0.001 0.611-0.729 21.0 83.3 44.8 97 (30.89) SGA 65-74 0.761 0.029 < 0.001 0.703-0.819 24.9 78.0 58.5 113 (29.97) 75-90 0.715 0.032 < 0.001 0.653-0.777 20.8 81.8 54.3 91 (28.98) Women NRS 65-74 0.688 0.029 < 0.001 0.630-0.746 17.0 70.5 58.6 145 (38.46) 2002 75-90 0.687 0.032 < 0.001 0.624-0.750 14.6 69.3 62.8 132 (48.00) SGA 65-74 0.672 0.033 < 0.001 0.608-0.736 15.2 77.4 53.2 114 (30.24) 75-90 0.720 0.031 < 0.001 0.660-0.781 13.5 71.7 65.1 140 (50.91) Note. AUC: area under the curve; SE: standard error; CI: confidence interval.
doi: 10.3967/bes2017.108
Handgrip Strength as a Predictor of Nutritional Status in Chinese Elderly Inpatients at Hospital Admission
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Abstract:
Objective To assess nutritional status and define gender-and age-specific handgrip strength (HGS) cut-point values for malnutrition or nutritional risk in elderly inpatients. Methods A cross-sectional study of 1, 343 elderly inpatients was conducted in the Chinese PLA General Hospital. Nutrition Risk Screening (NRS 2002) and Subjective Global Assessment (SGA) were administered. Anthropometric measurements and blood biochemical indicators were obtained using standard techniques. The gender-and age-specific receiver operating characteristic (ROC) curves were constructed to evaluate the HGS for nutritional status by SGA and NRS 2002. Sensitivity, specificity, and areas under the curves (AUCs) were calculated. Results According to NRS 2002 and SGA, 63.81% of elderly inpatients were at nutritional risk and 28.22% were malnourished. Patients with higher HGS had an independently decreased risk of malnutrition and nutritional risk. The AUCs varied between 0.670 and 0.761. According to NRS 2002, the optimal HGS cut-points were 27.5 kg (65-74 years) and 21.0 kg (75-90 years) for men and 17.0 kg (65-74 years) and 14.6 kg (75-90 years) for women. According to SGA, the optimal HGS cut-points were 24.9 kg (65-74 years) and 20.8 kg (75-90 years) for men and 15.2 kg (65-74 years) and 13.5 kg (75-90 years) for women. Conclusion Elderly inpatients had increased incidence of malnutrition or nutritional risk. HGS cut-points can be used for assessing nutritional status in elderly inpatients at hospital admission in China. -
Key words:
- Handgrip strength /
- Elderly inpatients /
- Nutrition assessment /
- Nutrition status /
- Malnutrition
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Table 1. Baseline Characteristics of Study Subjects
Variables Men (n = 691) Women (n = 652) Total (n = 1, 343) P Value Age (years) 74.0 ± 6.1 73.6 ± 5.6 73.8 ± 5.9 0.286 Body Measurement Height (cm) 169.6 ± 5.9 157.5 ± 5.7 163.7 ± 8.3 < 0.001 Weight (kg) 69.2 ± 11.1 61.2 ± 11.6 65.3 ± 12.0 < 0.001 BMI (kg/m2) 24.1 ± 3.7 24.7 ± 4.4 24.3 ± 4.0 0.007 WC (cm) 91.3 ± 10.9 88.9 ± 11.4 90.1 ± 11.2 < 0.001 CC (cm) 34.5 ± 3.6 33.0 ± 3.7 33.8 ± 3.8 < 0.001 Left HGS (kg) 25.1 ± 8.4 15.4 ± 5.8 20.3 ± 8.8 < 0.001 Right HGS (kg) 26.5 ± 8.7 16.6 ± 6.1 21.7 ± 9.0 < 0.001 Optimal HGS (kg) 26.7 ± 8.6 16.6 ± 6.0 21.8 ± 9.0 < 0.001 Mean HGS (kg) 25.8 ± 8.3 15.9 ± 5.8 21.0 ± 8.7 < 0.001 Blood Biochemical Assays ALB (g/L) 38.44 ± 5.12 38.61 ± 5.07 38.52 ± 5.09 0.534 TP (g/L) 64.82 ± 7.23 66.46 ± 7.62 65.64 ± 7.46 < 0.001 BUN (mmol/L) 6.88 ± 5.32 6.67 ± 4.37 6.78 ± 4.88 0.447 Cr (μmol/L) 93.51 ± 55.0 84.81 ± 88.89 89.31 ± 73.42 0.031 TG (mmol/L) 1.29 ± 0.90 1.67 ± 1.88 1.48 ± 1.48 < 0.001 TC (mmol/L) 4.20 ± 2.21 4.73 ± 1.42 4.46 ± 1.89 < 0.001 Hb (g/L) 129.91 ± 21.04 119.52 ± 18.09 124.83 ± 20.32 < 0.001 CRP (mg/dL) -median (P25-P75) 2.1 (0.51-11.81) 2.53 (0.54-9.20) 2.3 (0.51-10.7) 0.675 Patients of internal medicine [n(%)] < 0.001 Respiratory 123 (17.80) 73 (11.20) 196 (14.59) Endocrinology 90 (13.02) 115 (17.64) 205 (15.26) Neurology 183 (26.48) 125 (19.17) 308 (22.93) Gastroenterology 78 (11.29) 75 (11.50) 153 (11.39) Cardiology 166 (24.03) 180 (27.61) 346 (25.76) Nephrology 26 (3.76) 38 (5.83) 64 (4.77) Rheumatology 25 (3.62) 46 (7.06) 71 (5.29) Note. Data are expressed as mean± SD or number (percentage) of subjects. Statistical significance of difference is calculated between men and women subjects. BMI: body mass index; HGS: handgrip strength; WC: waist circumference; CC: calf circumference; ALB: albumin; TP: total protein; Cr: creatinine; TG: triglyceride; TC: total cholesterol; Hb: hemoglobin; BUN: blood urea nitrogen; CRP: C-reactive protein. Table 2. The Comparison HGS, Anthropometry and Blood Biochemical Assays of Different Nutrition Status of Study Subjects
Parameters NRS 2002 SGA ≥ 3 < 3 P Value B or C A P Value Men Left HGS (kg) 21.5 ± 8.3* 27.5 ± 7.6 < 0.001 20.1 ± 7.8* 26.7 ± 8.0 < 0.001 Right HGS (kg) 22.6 ± 8.4* 29.1 ± 7.9 < 0.001 21.5 ± 8.3* 28.7 ± 7.9 < 0.001 Mean HGS (kg) 22.0 ± 7.9* 28.3 ± 7.5 < 0.001 20.6 ± 7.7* 27.6 ± 7.7 < 0.001 Optimal HGS (kg) 22.8 ± 8.2* 29.3 ± 7.9 < 0.001 21.1 ± 7.8* 28.4 ± 8.1 < 0.001 Age (year) 75.9 ± 5.6* 72.7 ± 6.0 < 0.001 75.6 ± 6.4* 73.4 ± 5.9 < 0.001 BMI (kg/m2) 22.4 ± 4.0* 25.1 ± 3.0 < 0.001 21.9 ± 3.7* 24.8 ± 3.3 < 0.001 WC (cm) 87.3 ± 11.7* 93.9 ± 9.5 < 0.001 86.1 ± 11.2* 93.1 ± 10.2 < 0.001 CC (cm) 33.3 ± 3.8* 35.4 ± 3.2 < 0.001 32.4 ± 3.7* 35.3 ± 3.3 < 0.001 ALB (g/L) 37.2 ± 4.9* 39.2 ± 5.1 < 0.001 36.2 ± 5.4* 39.2 ± 4.8 < 0.001 TP (g/L) 64.3 ± 7.6 65.2 ± 7.0 0.105 64.1 ± 8.1 65.1 ± 6.9 0.128 TG (mmol/L) 1.09 ± 0.59* 1.42 ± 1.04 < 0.001 1.07 ± 0.56* 1.36 ± 0.98 < 0.001 TC (mmol/L) 4.02 ± 1.04 4.32 ± 2.70 0.094 3.99 ± 1.15 4.27 ± 2.46 0.161 HB (g/L) 125.7 ± 23.2* 132.5 ± 19.1 < 0.001 122.1 ± 23.7* 132.5 ± 19.4 < 0.001 CRP (mg/dL) -median (P25-P75) 2.57 (0.34-21.76) 2.06 (0.56-9.00) 0.514 1.72 (0.67-40.51) 2.10 (0.40-9.94) 0.072 Women Left HGS (kg) 13.1 ± 5.5* 16.9 ± 5.5 < 0.001 12.9 ± 5.4* 16.5 ± 5.6 < 0.001 Right HGS (kg) 14.0 ± 5.5* 18.3 ± 5.8 < 0.001 13.6± 5.6* 17.9 ± 5.8 < 0.001 Mean HGS (kg) 13.5 ± 5.4* 17.5 ± 5.5 < 0.001 13.2 ± 5.6* 17.2 ± 5.5 < 0.001 Optimal HGS (kg) 14.1 ± 5.6* 18.3 ± 5.7 < 0.001 13.6 ± 5.6* 18.0 ± 5.7 < 0.001 Age (year) 75.5 ± 5.5* 72.3 ± 5.4 < 0.001 75.0 ± 6.0* 73.0 ± 5.4 < 0.001 BMI (kg/m2) 22.7 ± 4.5* 26.0 ± 3.9 < 0.001 22.4 ± 4.4* 25.7 ± 4.0 < 0.001 WC (cm) 86.0 ± 12.1* 90.8 ± 10.4 < 0.001 84.9 ± 11.7* 90.6 ± 10.7 < 0.001 CC (cm) 31.6 ± 3.9* 33.9 ± 3.4 < 0.001 31.1 ± 3.9* 33.8 ± 3.3 < 0.001 ALB (g/L) 37.5 ± 5.3* 39.4 ± 4.7 < 0.001 37.3 ± 5.4* 39.2 ± 4.8 < 0.001 TP (g/L) 65.4 ± 7.9* 67.2 ± 7.3 0.003 64.8 ± 8.4* 67.2 ± 7.1 0.002 TG (mmol/L) 1.48 ± 1.38* 1.80 ± 2.14 0.039 1.42 ± 0.87* 1.78 ± 2.17 0.028 TC (mmol/L) 4.74 ± 1.76 4.73 ± 1.15 0.976 4.73 ± 1.94 4.74 ± 1.13 0.949 HB (g/L) 117.0 ± 19.7* 121.1 ± 16.8 0.005 115.7 ± 20.5* 121.2 ± 16.7 0.001 CRP (mg/dL) -median (P25-P75) 3.24 (0.60-13.45)* 1.90 (0.46-7.45) 0.039 3.70 (0.77-13.20)* 2.84 (0.55-8.31) 0.043 Note. Statistical significance of difference is calculated between different nutrition status, *P < 0.05. Table 3. Multivariate Logistic Regression Analyses for Malnutrition or Nutrition Risk Stratified by Gender
Variable NRS 2002 SGA Standardized β OR (95% CI) P Value Standardized β OR (95% CI) P Value Men Optimal HGS -0.07 0.93 (0.90-0.97) < 0.001 -0.08 0.93 (0.89-0.96) < 0.001 Age 0.05 1.05 (1.01-1.10) 0.018 0.01 1.01 (0.96-1.06) 0.827 BMI -0.19 0.83 (0.74-0.92) 0.001 -0.14 0.87 (0.77-0.99) 0.032 WC -0.02 0.98 (0.94-1.01) 0.198 -0.01 0.99 (0.96-1.04) 0.786 CC 0.02 1.02 (0.92-1.12) 0.756 -0.10 0.90 (0.81-1.01) 0.086 ALB 0.06 0.94 (0.87-1.02) 0.162 -0.16 0.85 (0.78-0.94) 0.001 TP 0.01 1.01 (0.96-1.06) 0.608 0.07 1.07 (1.01-1.13) 0.017 TC -0.13 0.88 (0.68-1.13) 0.311 -0.18 0.84 (0.63-1.12) 0.236 Hb 0.01 1.01 (0.99-1.03) 0.116 0.01 1.01 (0.99-1.03) 0.314 CRP 0.01 1.01 (1.00-1.01) 0.190 0.01 1.01 (1.00-1.03) 0.140 Women Optimal HGS -0.07 0.93 (0.89-0.98) 0.003 -0.07 0.93 (0.88-0.98) 0.003 Age 0.07 0.93 (0.89-0.98) 0.002 0.03 0.93 (0.88-0.98) 0.157 BMI -0.23 0.80 (0.72-0.88) < 0.001 -0.17 0.84 (0.76-0.94) 0.001 WC 0.01 1.01 (0.98-1.04) 0.452 0.01 1.01 (0.98-1.05) 0.415 CC 0.03 0.97 (0.89-1.06) 0.505 -0.10 0.90 (0.82-0.99) 0.031 ALB -0.05 0.96 (0.89-1.03) 0.221 0.05 0.96 (0.89-1.04) 0.286 TP -0.01 0.99 (0.95-1.04) 0.743 -0.02 0.98 (0.94-1.03) 0.393 TC 0.02 1.03 (0.86-1.23) 0.792 0.05 1.07 (0.89-1.30) 0.476 Hb 0.01 1.01 (0.99-1.02) 0.238 0.00 1.00 (0.99-1.01) 0.902 CRP 0.00 1.00 (0.99-1.01) 0.451 0.00 1.00 (0.99-1.01) 0.771 Note. β: regression coefficient; OR: odds ratios; CI: confidence interval Table 4. Gender-and Age-Specific ROC Curve of the Optimal HGS to Screen Malnutrition or Nutritional Risk on the Basis of SGA and NRS 2002 in Elderly Inpatients
Variable Age (year) AUC SE P 95% CI Cut-point (kg) Sensitivity (%) Specificity (%) Nutritional Risk/Malnutrition, n (%) Men NRS 65-74 0.734 0.027 < 0.001 0.678-0.786 27.5 69.1 63.6 155 (41.11) 2002 75-90 0.670 0.030 < 0.001 0.611-0.729 21.0 83.3 44.8 97 (30.89) SGA 65-74 0.761 0.029 < 0.001 0.703-0.819 24.9 78.0 58.5 113 (29.97) 75-90 0.715 0.032 < 0.001 0.653-0.777 20.8 81.8 54.3 91 (28.98) Women NRS 65-74 0.688 0.029 < 0.001 0.630-0.746 17.0 70.5 58.6 145 (38.46) 2002 75-90 0.687 0.032 < 0.001 0.624-0.750 14.6 69.3 62.8 132 (48.00) SGA 65-74 0.672 0.033 < 0.001 0.608-0.736 15.2 77.4 53.2 114 (30.24) 75-90 0.720 0.031 < 0.001 0.660-0.781 13.5 71.7 65.1 140 (50.91) Note. AUC: area under the curve; SE: standard error; CI: confidence interval. -
[1] Araujo Dos Santos C, De Oliveira Barbosa Rosa C, Queiroz Ribeiro A, et al. Patient-Generated Subjective Global Assessment and Classic Anthropometry:Comparison between the Methods in Detection of Malnutrition among Elderly with Cancer. Nutr Hosp, 2015; 31, 384-92. https://www.researchgate.net/publication/270654011_Patient... [2] Sanz Paris A, Garcia JM, Gomez-Candela C, et al. Malnutrition prevalence in hospitalized elderly diabetic patients. Nutr Hosp, 2013; 28, 592-9. https://www.researchgate.net/publication/249316875_Malnutrition... [3] Klek S. Malnutrition and its impact on cost of hospitalization, length of stay, readmission and 3-year mortality——letter to the editor. Clin Nutr, 2013; 32, 488. doi: 10.1016/j.clnu.2012.12.013 [4] Sorensen J, Kondrup J, Prokopowicz J, et al. EuroOOPS:an international, multicentre study to implement nutritional risk screening and evaluate clinical outcome. Clin Nutr, 2008; 27, 340-9. doi: 10.1016/j.clnu.2008.03.012 [5] Wells JL, Dumbrell AC. Nutrition and aging:assessment and treatment of compromised nutritional status in frail elderly patients. Clin Interv Aging, 2006; 1, 67-79. doi: 10.2147/ciia.2006.1.issue-1 [6] Keevil V, Mazzuin Razali R, Chin AV, et al. Grip strength in a cohort of older medical inpatients in Malaysia:a pilot study to describe the range, determinants and association with length of hospital stay. Arch Gerontol Geriatr, 2013; 56, 155-9. doi: 10.1016/j.archger.2012.10.005 [7] J K, HH R, O H, et al. Nutritional risk screening (NRS 2002):a new method based on an analysis of controlled clinical trials. Clin Nutr, 2003; 22, 321-36. doi: 10.1016/S0261-5614(02)00214-5 [8] Detsky AS, McLaughlin JR, Baker JP, et al. What is subjective global assessment of nutritional status? JPEN-Parenter Enteral, 1987; 11, 8-13. doi: 10.1177/014860718701100108 [9] Salva A, Corman B, Andrieu S, et al. Minimum data set for nutritional intervention studies in elderly people. J Gerontol A-Biol, 2004; 59, 724-9. doi: 10.1093/gerona/59.7.M724 [10] Fontes D, Generoso SD, Toulson Davisson Correia MI. Subjective global assessment:A reliable nutritional assessment tool to predict outcomes in critically ill patients. Clin Nutr, 2014; 33, 291-5. doi: 10.1016/j.clnu.2013.05.004 [11] Van Nes MC, Herrmann FR, Gold G, et al. Does the mini nutritional assessment predict hospitalization outcomes in older people? Age Ageing, 2001; 30, 221-6. doi: 10.1093/ageing/30.3.221 [12] Kondrup J, Allison SP, Elia M, et al. Educational and Clinical Practice Committee, European Society for Clinical Nutrition and Metabolism (ESPEN). ESPEN guidelines for nutrition screening 2002. Clin Nutr, 2003; 22, 415e21. [13] Raslan M1, Gonzalez MC, Torrinhas RS, et al. Complementarity of Subjective Global Assessment (SGA) and Nutritional Risk Screening 2002 (NRS 2002) for predicting poor clinical outcomes in hospitalized patients. Clin Nutr, 2011; 30, 49-53. doi: 10.1016/j.clnu.2010.07.002 [14] Russell DM, Walker PM, Leiter LA, et al. Metabolic and structural changes in skeletal muscle during hypocaloric dieting. Am J Clin Nutr, 1984; 39, 503-13. https://www.ncbi.nlm.nih.gov/pubmed/6201062 [15] Ardawi MS, Majzoub MF, Masoud IM, et al. Enzymic and metabolic adaptations in the gastrocnemius, plantaris and soleus muscles of hypocaloric rats. Biochem J, 1989; 261, 219-25. doi: 10.1042/bj2610219 [16] Thompson A, Damyanovich A, Madapallimattam A, et al. 31P-nuclear magnetic resonance studies of bioenergetic changes in skeletal muscle in malnourished human adults. Am J Clin Nutr, 1998; 67, 39-43. http://intl-ajcn.nutrition.org/content/67/1/39.abstract [17] Madapallimattam AG, Law L, Jeejeebhoy KN. Effect of hypoenergetic feeding on muscle oxidative phosphorylation and mitochondrial complex Ⅰ-Ⅳ activities in rats. Am J Clin Nutr, 2002; 76, 1031-9. http://www.academia.edu/12202680/Antioxidant_effects_of_statins_in_the... [18] Norman K, Stobaus N, Gonzalez MC, et al. Hand grip strength:outcome predictor and marker of nutritional status. Clin Nutr, 2011; 30, 135-42. doi: 10.1016/j.clnu.2010.09.010 [19] Flood A, Chung A, Parker H, et al. The use of hand grip strength as a predictor of nutrition status in hospital patients. Clin Nutr, 2014; 33, 106-14. doi: 10.1016/j.clnu.2013.03.003 [20] Izawa KP, Watanabe S, Osada N, et al. Handgrip strength as a predictor of prognosis in Japanese patients with congestive heart failure. Eur J Cardiovasc Prev Rehabil, 2009; 16, 21-7. doi: 10.1097/HJR.0b013e32831269a3 [21] AS D, JR M, JP B, et al. What is subjective global assessment of nutritional status? JPEN-Parenter Enteral, 1987; 11, 8-13. doi: 10.1177/014860718701100108 [22] Leong DP, Teo KK, Rangarajan S, et al. Reference ranges of handgrip strength from 125, 462 healthy adults in 21 countries:a prospective urban rural epidemiologic (PURE) study. J Cachexia Sarcopenia Muscle, 2016; 7, 535-46. doi: 10.1002/jcsm.12112 [23] Guerra RS, Fonseca I, Pichel F, et al. Handgrip strength cutoff values for undernutrition screening at hospital admission. Eur J Clin Nutr, 2014; 68, 1315-21. doi: 10.1038/ejcn.2014.226 [24] Silva C, Amaral TF, Silva D, et al. Handgrip strength and nutrition status in hospitalized pediatric patients. Nutr Clin Pract, 2014; 29, 380-5. doi: 10.1177/0884533614528985 [25] Flood A, Chung A, Parker H, et al. The use of hand grip strength as a predictor of nutrition status in hospital patients. Clin Nutr, 2014; 33, 106-14. doi: 10.1016/j.clnu.2013.03.003 [26] Pieterse S, Manandhar M, Ismail S. The association between nutritional status and handgrip strength in older Rwandan refugees. Eur J Clin Nutr, 2002; 56, 933-9. doi: 10.1038/sj.ejcn.1601443 [27] de Luis DA, Lopez Mongil R, Gonzalez Sagrado M, et al. Evaluation of the mini-nutritional assessment short-form (MNA-SF) among institutionalized older patients in Spain. Nutr Hosp, 2011; 26, 1350-4. http://www.oalib.com/paper/975842 [28] Puh U. Age-related and sex-related differences in hand and pinch grip strength in adults. Int J Rehabil Res, 2010; 33, 4-11. doi: 10.1097/MRR.0b013e328325a8ba [29] van Lier AM, Payette H. Determinants of handgrip strength in free-living elderly at risk of malnutrition. Disabil Rehabil, 2003; 25, 1181-6. doi: 10.1080/09638280310001599943 [30] Ranganathan VK, Siemionow V, Sahgal V, et al. Effects of aging on hand function. J Am Geriatr Soc, 2001; 49, 1478-84. doi: 10.1046/j.1532-5415.2001.4911240.x [31] Chilima DM, Ismail SJ. Nutrition and handgrip strength of older adults in rural Malawi. Public Health Nutr, 2001; 4, 11-7. https://www.cambridge.org/core/journals/public-health-nutrition/... [32] Bassey EJ. Longitudinal changes in selected physical capabilities:muscle strength, flexibility and body size. Age Ageing, 1998; 27 Suppl 3, 12-6. doi: 10.1093/ageing/27.suppl_3.12 [33] Sharma P, Rauf A, Matin A, et al. Handgrip Strength as an Important Bed Side Tool to Assess Malnutrition in Patient with Liver Disease. J Clin Exp Hepatol, 2017; 7, 16-22. doi: 10.1016/j.jceh.2016.10.005 [34] Rantanen T, Volpato S, Ferrucci L, et al. Handgrip strength and cause-specific and total mortality in older disabled women:exploring the mechanism. J Am Geriatr Soc, 2003; 51, 636-41. doi: 10.1034/j.1600-0579.2003.00207.x [35] Matos LC, Tavares MM, Amaral TF. Handgrip strength as a hospital admission nutritional risk screening method. Eur J Clin Nutr, 2007; 61, 1128-35. doi: 10.1038/sj.ejcn.1602627 [36] Sallinen J, Stenholm S, Rantanen T, et al. Hand-grip strength cut points to screen older persons at risk for mobility limitation. J Am Geriatr Soc, 2010; 58, 1721-6. doi: 10.1111/j.1532-5415.2010.03035.x [37] Garcia-Pena C, Garcia-Fabela LC, Gutierrez-Robledo LM, et al. Handgrip strength predicts functional decline at discharge in hospitalized male elderly:a hospital cohort study. PloS One, 2013; 8, e69849. doi: 10.1371/journal.pone.0069849 [38] Izawa KP, Watanabe S, Oka K, et al. Differences in physical performance based on the Geriatric Nutritional Risk Index in elderly female cardiac patients. Aging Clin Exp Res, 2015; 27, 195-200. doi: 10.1007/s40520-014-0264-5 [39] Izawa KP, Watanabe S. Relation of nutritional status to physiological outcomes after cardiac surgery in elderly patients with diabetes mellitus:a preliminary study. Aging Clin Exp Res, 2016; 28, 1267-71. doi: 10.1007/s40520-015-0520-3 [40] Alvares-da-Silva MR, Reverbel da Silveira T. Comparison between handgrip strength, subjective global assessment, and prognostic nutritional index in assessing malnutrition and predicting clinical outcome in cirrhotic outpatients. Nutrition, 2005; 21, 113-7. doi: 10.1016/j.nut.2004.02.002