Challenges Measuring All Forms of Malnutrition in Adolescence in Kenya: Varying Cut Offs for Obesity, Iron Deficiency, and Anemia Change the Prevalence of Malnutrition. (14th June 2022)

• Record Type: Journal Article
• Authors: Seiger, Emily; Owuor, Mercy; Nandoya, Erick; Omala, Hillary; Muasa, Mark; Ruto, Nathan; Meyer, Katie; Ammerman, Alice; Voruganti, Saroja; Pompano, Laura; Thompson, Amanda; Martin, Stephanie
• Is Part Of: Current developments in nutrition. Volume 6(2022)Supplement 1
• Page Start: 604
• Page End: 604
• Publication Date: 2022-06-14
• Subjects: Nutrition -- Periodicals; Nutritional Physiological Phenomena; Nutrition; Periodicals; Periodicals; Fulltext; Internet Resources; Periodicals; 612.3
• DOI: 10.1093/cdn/nzac060.062
• Languages: English
• ISSNs: 2475-2991

Abstract

Abstract: Objectives: Malnutrition is shifting in Kenya (increasing rates of obesity with high rates of undernutrition, micronutrient deficiency). There is little consensus on how to measure the coexistence of all forms of malnutrition among adolescents. This study aimed to compare how the prevalence of malnutrition changes depending on the cut-off values and measures of overweight, obesity, undernutrition, iron deficiency, and anemia used. Methods: Girls in late adolescence (15–19 years, n = 313) living in Kibera, an urban informal settlement, participated in a survey; height, weight, waist circumference assessment; and a blood draw. BMI z-scores (BMIz) were calculated from the WHO 2007 Child Growth Standards for overweight (>1SD) and obesity (>2SD). We defined central adiposity as waist circumference to height ratio (WHtR) > 0.5, underweight as BMIz< -2SD, stunting as height for age z-score (HAZ) <-2SD, iron deficiency (ID) as serum ferritin (Ft) < 25 µg/L (to account for functional iron deficiency masked by inflammation); and anemia (A) as Hb < 120 g/L adjusted for elevation. Results: Overweight, obesity, underweight, and stunting data were available from 313 participants, but hemoglobin and ferritin data were only available from 293 and 297 participants, respectively. The prevalence of central adiposity was 29.7%, overweight was 19.5%, and obesity was 2.2%. Using WHtR and BMIz led to an estimated prevalence of 13.1% for overweight and 2.2% for obesity. The prevalence of underweight was 1.0% and of stunting was 1.3%. The prevalence of iron deficiency was 19.2%, of anemia was 24.6%, and of iron deficiency anemia was 10.9%. We assessed the coexistence of all forms of malnutrition among 297 participants. The prevalence of the coexistence of overweight (BMIz or WHtR) and ID or A was 9.1%. The prevalence of the coexistence of obesity (BMIz or WHtR) and ID or A was 7.1%. When overweight is defined using BMIz AND WHtR, the prevalence of the coexistence of overweight and ID or A was only 2.4% and there was no coexistence of obesity and ID or A. When stunting was included, the prevalence of the coexistence all forms of malnutrition increased to 9.8%. Conclusions: Small changes in cut-offs led to notable changes in the prevalence of malnutrition. Further research is needed on which indicators provide the most precise estimates of malnutrition. Funding Sources: UNC Chapel Hill Nutrition Dept. Pilot Grant.