Praveen Kumar1, Rajesh Sinha2, Narendra Patil2, Virendra Kumar1. 1. Lady Hardinge Medical College and associated Kalawati Saran Children's Hospital, C-604 Connaught Circus, DIZ Area, Connaught Place, New Delhi - 110001, India. 2. National Nutritional Rehabilitation Resource and Training Centre, Kalawati Saran Children's Hospital, New Delhi, India.
Abstract
OBJECTIVE: To assess the strength of correlation and agreement between mid-upper arm circumference (MUAC) and BMI, and determine suitable MUAC cut-offs, to detect wasting and severe wasting among non-pregnant adult women in India. DESIGN: Cross-sectional studies were conducted in five high-burden pockets of four Indian states. SETTING: Prevalence of malnutrition among women and children is very high in these pockets and the government plans to implement community-based pilot projects to address malnutrition in these areas. PARTICIPANTS: Anthropometric measurements were carried out on 1716 women with children <5 years of age. However, analyses were conducted on 1538 non-pregnant adult women. RESULTS: The results showed a strong correlation between MUAC and BMI in the non-pregnant women, with correlation coefficient of 0·860 (95 % CI 0·831, 0·883; P < 0·001). Cohen's κ of 0·812 and 0·884 also showed good agreement between MUAC and BMI in identifying maternal wasting and severe wasting, respectively. The univariate regression model between MUAC and BMI explained 0·734 or 73 % of the variation in BMI. The MUAC cut-offs for wasting (BMI < 18·5 kg/m2) and severe wasting (BMI < 16·0 kg/m2) were calculated as 232 and 214·5 mm, respectively. CONCLUSIONS: MUAC is a strong predictor of maternal BMI among non-pregnant women with children <5 years in high-burden pockets of four Indian states. In a resource-constrained setting where BMI may not be feasible, the MUAC cut-offs could reliably be used to screen wasting and severe wasting in non-pregnant women for providing appropriate care.
OBJECTIVE: To assess the strength of correlation and agreement between mid-upper arm circumference (MUAC) and BMI, and determine suitable MUAC cut-offs, to detect wasting and severe wasting among non-pregnant adult women in India. DESIGN: Cross-sectional studies were conducted in five high-burden pockets of four Indian states. SETTING: Prevalence of malnutrition among women and children is very high in these pockets and the government plans to implement community-based pilot projects to address malnutrition in these areas. PARTICIPANTS: Anthropometric measurements were carried out on 1716 women with children <5 years of age. However, analyses were conducted on 1538 non-pregnant adult women. RESULTS: The results showed a strong correlation between MUAC and BMI in the non-pregnant women, with correlation coefficient of 0·860 (95 % CI 0·831, 0·883; P < 0·001). Cohen's κ of 0·812 and 0·884 also showed good agreement between MUAC and BMI in identifying maternal wasting and severe wasting, respectively. The univariate regression model between MUAC and BMI explained 0·734 or 73 % of the variation in BMI. The MUAC cut-offs for wasting (BMI < 18·5 kg/m2) and severe wasting (BMI < 16·0 kg/m2) were calculated as 232 and 214·5 mm, respectively. CONCLUSIONS: MUAC is a strong predictor of maternal BMI among non-pregnant women with children <5 years in high-burden pockets of four Indian states. In a resource-constrained setting where BMI may not be feasible, the MUAC cut-offs could reliably be used to screen wasting and severe wasting in non-pregnant women for providing appropriate care.
Entities:
Keywords:
BMI; Correlation; Malnutrition; Maternal wasting; Mid-upper arm circumference
Authors: Carin A Northuis; Thomas A Murray; Pamela L Lutsey; Kenneth R Butler; Steve Nguyen; Priya Palta; Kamakshi Lakshminarayan Journal: Blood Press Monit Date: 2022-02-01 Impact factor: 1.430
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