Nutritional assessment associated with length of inpatients' hospital stay

To evaluate the nutritional status of patients on hospital admission, identify the length of hospital stay and identify the parameters of nutritional assessment that are most closely related with the length of stay (LOS).

A cross-sectional study of 278 hospitalized patients evaluated patients' nutritional status in the 48 hours after admission and their LOS after discharge. Anthropometric and biochemical parameters, related to nutrition status were analyzed, such as: weight, height, arm circumference (AC), waist circumference (WC), triceps skinfold thickness (TST), mild arm muscle circumference (MAMC), albumin (Alb) and hemoglobin (HB). Body mass index (BMI) was used to classify the nutritional status. All the nutritional factors except type of disease, gender and age were associated with LOS. The chi-square, Student-t, Mann-Whitney, Kruskal-Wallis and binary logistic multivariate tests were used in the statistical analyses.

The majority of patients was male (53%), elderly (56%) and had neoplasm (19.4%). Undernutrition was higher in the elderly (p < 0.05) and neoplasm patients (p < 0.05), overweight or obese patients were more likely to suffer from cardiovascular diseases (p = 0.001). Average LOS was 14.7 days (± 12.5), longer in neoplasm patients (p < 0.05) and in elderly ones (p < 0.05), and also was 3 times longer in males (p < 0.0001). Among the nutritional parameters, patients with AC under 25 cm had higher LOS (p < 0.05), but only in women could it be considered a marker, increasing LOS 2.8 times. BMI less than 20 kg/m(2) increased LOS 2.1 times, and biochemical data (Alb and HB) do not contribute. In the multivariate analyses, male gender and TST depletion were the significant factors, which together best explained the lengths of hospital stay.

LOS was associated with disease, gender, age and nutritional status. We can highlight two anthropometric analyses: first, AC can be used in women as a marker of longer LOS and second TST is the best overall predictor of longer hospital stay.