AUTHOR=Zhang Kexin , Ju Yanmin , Yang Di , Cao Mengyu , Liang Hong , Leng Jiyan TITLE=Correlation analysis between body composition, serological indices and the risk of falls, and the receiver operating characteristic curve of different indexes for the risk of falls in older individuals JOURNAL=Frontiers in Medicine VOLUME=10 YEAR=2023 URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2023.1228821 DOI=10.3389/fmed.2023.1228821 ISSN=2296-858X ABSTRACT=Objective

This study assessed the risk factors for falls and evaluated the correlation between body composition, serological indices, and the risk of falls in older individuals.

Method

This cross-sectional study included 387 individuals ≥60 years of age in the cadre ward of the First Hospital of Jilin University. The information used in this study was obtained from the comprehensive geriatric assessment database of the cadre ward. The body composition of the individuals was measured by bioelectrical impedance analysis using an InBody S10 device. We assessed fall risk using the fall risk assessment tool. Individuals with ≤2 points were placed in the low-risk group, those with 3–9 points were placed in the medium-risk group, and those with ≥10 points were placed in the high-risk group.

Results

Differences in age, educational background, height, cognitive impairment, malnutrition, ability of daily living, depression, diastolic blood pressure, heart rate, intracellular water, total body moisture, water ratio, limb moisture (right and left, upper and lower), trunk moisture, fat-free weight, arm girth, body cell mass, skeletal muscle mass, limb muscle (right and left, upper and lower), appendicular skeletal muscle mass index (ASMI), sarcopenia, hemoglobin level, hematocrit level, aspartate aminotransferase level, albumin level, anemia, and hypoproteinemia were observed among the three groups (p < 0.001, p = 0.002, p = 0.006, p < 0.001, p < 0.001, p < 0.001, p < 0.001, p < 0.001, p = 0.008, p = 0.010). Ordinal logistic regression analysis showed that the probability of the fall risk increasing by one level was 1.902 times higher for each unit of decrease in educational background, respectively. In addition, the probability of the fall risk increasing by one level was 2.971, 3.732, 3.804, 1.690 and 2.155 times higher for each additional unit of age, cognitive impairment, lower limb edema, decreased skeletal muscle mass, and sarcopenia, respectively.

Conclusion

Our findings suggest that educational background, age, cognitive impairment, lower limb edema, decreased skeletal muscle mass, and sarcopenia were associated with falls in older individuals. Body composition and serological indices can assist in the early identification of falls in the older people.