Assessment of nutritional status using anthropometric variables by multivariate analysis
| Autor: | Subrata K. Roy, Baidyanath Pal, Ankita Bhattacharya, Shankarashis Mukherjee |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Adult
Male Multivariate analysis Population India 030209 endocrinology & metabolism Confirmatory factor analysis Body Mass Index 03 medical and health sciences 0302 clinical medicine Discriminant function analysis Humans Medicine 030212 general & internal medicine education Nutritional status assessment education.field_of_study Anthropometry business.industry lcsh:Public aspects of medicine Malnutrition Public Health Environmental and Occupational Health Reproducibility of Results lcsh:RA1-1270 Middle Aged Test (assessment) Nutrition Assessment Multivariate Analysis Arm Female Biostatistics Anthropometric measurements business Body mass index Research Article Demography |
| Zdroj: | BMC Public Health, Vol 19, Iss 1, Pp 1-9 (2019) BMC Public Health |
| ISSN: | 1471-2458 |
| DOI: | 10.1186/s12889-019-7372-2 |
| Popis: | Background Undernutrition is a serious health problem and highly prevalent in developing countries. There is no as such confirmatory test to measure undernutrition. The objective of the present study is to determine a new Composite Score using anthropometric measurements. Composite Score was then compared with other methods like body mass index (BMI) and mid-upper arm circumference (MUAC) classification, to test the significance of the method. Methods Anthropometric data were collected from 780 adult Oraon (Male = 387, Female = 393) labourers of Alipurduar district of West Bengal, India, following standard instruments, and protocols. Nutritional status of the study participants were assessed by conventional methods, BMI and MUAC. Confirmatory factor analysis was carried out to reduce 12 anthropometric variables into a single Composite Score (C) and classification of nutritional status was done on the basis of the score. Furthermore, all the methods (BMI, MUAC and C) were compared and discriminant function analysis was adopted to find out the percentage of correctly classified individuals by each of the three methods. Result The frequency of undernutrition was 45.9% according to BMI category, 56.7% according to MUAC category and 51.8% according to newly computed Composite Score. Further analysis showed that Composite Score has a higher strength of correct classification (98.7%), compared to BMI (95.9%) and MUAC (96.2%). Conclusion Therefore, anthropometric measurements can be used to identify nutritional status in the population more correctly by calculating Composite Score of the measurements and it is a non-invasive and relatively correct way of identification. |
| Databáze: | OpenAIRE |
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