Nutritional Status of Fishermen Communities: Validation of Conventional Methods with Discriminant Function Analysis

Abstract

Anthropological methods of assessing nutritional status of adults have been reinvestigated. Objective of the study is to detect the predictor variables that discriminate for under nutrition or Chronic Energy Deficiency (CED) by two conventional methods e.g. Body Mass Index (BMI) and Mid Upper Arm Circumference (MUAC). Discriminant function analysis was used to build valid and accurate predictive model for evaluating nutritional status. Anthropometric measurements were collected using standard techniques and used as independent variables. Recommended cut-off values of BMI and MUAC was used for evaluating nutritional status. The extent of CED (BMI < 18.5) was found 43.50% and prevalence of under-nutrition in terms of MUAC (MUAC < 23.0 cm for Male and < 22.0 cm for Female) was 21.7%. Discriminant function analysis reveals that 85.7% and 72.0% individuals were classified correctly in terms of nutritional status. Therefore, BMI is the good indicator for detecting malnutrition. Fat mass discriminates between groups.