scholarly journals Diagnostic measures for severe acute malnutrition in Indian infants under 6 months of age: a secondary data analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ranadip Chowdhury ◽  
Nitika ◽  
Tarun Shankar Choudhary ◽  
Sunita Taneja ◽  
Jose Martines ◽  
...  
Keyword(s):  
Severe Acute Malnutrition ◽  
Population Attributable Fraction ◽  
Acute Malnutrition ◽  
Adjusted Relative Risk ◽  
Z Score ◽  
Operating Characteristics ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
Growth Standards ◽  
Anthropometric Indicators

Abstract Background Weight for length z-score (WLZ) < − 3 is currently used to define severe acute malnutrition (SAM) among infants. However, this approach has important limitations for infants younger than 6 months of age as WLZ cannot be calculated using WHO growth standards if infant length is < 45 cm. Moreover, length for age z-score (LAZ) and weight for length z-score (WLZ) are least reliable measures, with high chances of variation, and less chances of detecting undernutrition in under 6 months infants. The objective of the current analysis was to compare WLZ with WAZ and LAZ in a cohort of Indian infants in predicting the deaths between 6 weeks and 6 months of age. Methods The data was from an individually randomized trial conducted in slums of Delhi, India in which infants’ weight and length were measured at 6 weeks of age (at the time of the first immunization visit). Vital status of the infants was documented from 6 weeks to 6 months of age. The sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios were calculated for WAZ < -3, WLZ < -3, and LAZ < -3 for deaths between 6 weeks and 6 months of age. The receiver operating characteristics curve was calculated for each of the above anthropometric indicators. Results For deaths occurring between 6 weeks to 6 months of age, the specificity ranged between 85.9–95.9% for all three anthropometric indicators. However, the sensitivity was considerably higher for WAZ; it was 64.6% for WAZ < -3, 39.1% for LAZ < -3, and 25.0% for WLZ < -3. WAZ < -3 had higher area under curve (0.75; 95% CI: 0.68, 0.82) and hence, better discriminated deaths between 6 weeks and 6 months of age than WLZ < -3. The adjusted relative risk (RR 10.6, 95% CI 5.9, 18.9) and the population attributable fraction (PAF 57.9, 95% CI 38.8, 71.0%) of mortality was highest for WAZ < -3. Conclusions We found WAZ < -3 at 6 weeks of age to be a better predictor of death in the 6 weeks to 6 months of life in comparison to WLZ < -3 and LAZ < -3 and propose that it should be considered to diagnose SAM in this age group.

scholarly journals Diagnostic measures for severe acute malnutrition in Indian infants under 6 months of age: a secondary data analysis

2021 ◽  
Author(s):  
Ranadip Chowdhury ◽  
Nitika Nitika ◽  
Tarun Shankar Choudhary ◽  
Sunita Taneja ◽  
Jose Carlos Martines ◽  
...  
Keyword(s):  
Severe Acute Malnutrition ◽  
Population Attributable Fraction ◽  
Secondary Data ◽  
Acute Malnutrition ◽  
Adjusted Relative Risk ◽  
Z Score ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
Growth Standards ◽  
Diagnostic Measures

Abstract Background Weight for length z-score (WLZ) <- 3 is currently used to define severe acute malnutrition (SAM) among infants. However, this approach has important limitations for infants younger than 6 months of age as WLZ cannot be calculated using WHO growth standards if infant length is <45 cm. Moreover, length for age z-score (LAZ) and weight for length z-score (WLZ) are least reliable measures, with high chances of variation, and less chances of detecting undernutrition in under 6 months infants. The objective of the current analysis was to compare WLZ with WAZ and LAZ in a cohort of Indian infants in predicting the deaths between 6 weeks and 6 months of age. Methods The data was from an individually randomized trial conducted in slums of Delhi, India in which infants’ weight and length were measured at 6 weeks of age (at the time of the first immunization visit). Vital status of the infants was documented from 6 weeks to 6 months of age. The sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios, and area under curve (AUC) were calculated for WAZ<-3, WLZ<-3, and LAZ<-3 for deaths between 6 weeks and 6 months of age. Results For deaths occurring between 6 weeks to 6 months of age, the specificity ranged between 85.9-95.9% for all three anthropometric indicators. However, the sensitivity was considerably higher for WAZ; it was 64.6 % for WAZ<-3, 39.1% for LAZ<-3, and 25.0% for WLZ<-3. WAZ <-3 had higher AUC (0.75; 95% CI: 0.68, 0.82) and hence, better discriminated deaths between 6 weeks and 6 months of age than WLZ<-3. The adjusted relative risk (RR 10.6, 95% CI 5.9, 18.9) and the population attributable fraction (PAF 57.9%, 95% CI 38.8, 71.0%) of mortality was highest for WAZ<-3. Conclusions We found WAZ<-3 at 6 weeks of age to be a better predictor of death in the 6 weeks to 6 months of life in comparison to WLZ<-3 and LAZ<-3 and propose that it should be considered to diagnose SAM in this age group.

scholarly journals Diagnostic Measures for Severe Acute Malnutrition in Indian Infants Under 6 Months of Age: a Secondary Data Analysis

2020 ◽  
Author(s):  
Ranadip Chowdhury ◽  
Nitika Nitika ◽  
Tarun Shankar Choudhary ◽  
Sunita Taneja ◽  
Jose Carlos Martines ◽  
...  
Keyword(s):  
Severe Acute Malnutrition ◽  
Population Attributable Fraction ◽  
Secondary Data ◽  
Acute Malnutrition ◽  
Adjusted Relative Risk ◽  
Z Score ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
Growth Standards ◽  
Diagnostic Measures

Abstract Background Weight for length z-score (WLZ) <- 3 is currently used to define severe acute malnutrition (SAM) among infants. However, this approach has important limitations for infants younger than 6 months of age as WLZ cannot be calculated using WHO growth standards if infant length is <45 cm. Moreover, length for age z-score (LAZ) and weight for length z-score (WLZ) are least reliable measures, with high chances of variation, and less chances of detecting undernutrition in under 6 months infants. The objective of the current analysis was to compare WLZ with WAZ and LAZ in a cohort of Indian infants in predicting the deaths between 6 weeks and 6 months of age. Methods The data was from an individually randomized trial conducted in slums of Delhi, India in which infants’ weight and length were measured at 6 weeks of age (at the time of the first immunization visit). Vital status of the infants was documented from 6 weeks to 6 months of age. The sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios, and area under curve (AUC) were calculated for WAZ<-3, WLZ<-3, and LAZ<-3 for deaths between 6 weeks and 6 months of age. Results For deaths occurring between 6 weeks to 6 months of age, the specificity ranged between 85.9-95.9% for all three anthropometric indicators. However, the sensitivity was considerably higher for WAZ; it was 64.6 % for WAZ<-3, 39.1% for LAZ<-3, and 25.0% for WLZ<-3. WAZ <-3 had higher AUC (0.75; 95% CI: 0.68, 0.82) and hence, better discriminated deaths between 6 weeks and 6 months of age than WLZ<-3. The adjusted relative risk (RR 10.6, 95% CI 5.9, 18.9) and the population attributable fraction (PAF 57.9%, 95% CI 38.8, 71.0%) of mortality was highest for WAZ<-3.Conclusions We found WAZ<-3 at 6 weeks of age to be a better predictor of death in the 6 weeks to 6 months of life in comparison to WLZ<-3 and LAZ<-3 and propose that it should be considered to diagnose SAM in this age group.

scholarly journals Examining Response to Treatment of Severe Acute Malnutrition in Children 6–59 Months Old in Afghanistan, Chad, Mali, and Niger (P12-002-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Erin Boyd
Keyword(s):  
Weight Gain ◽  
Health Center ◽  
Severe Acute Malnutrition ◽  
Acute Malnutrition ◽  
Daily Weight Gain ◽  
Z Score ◽  
Factors Affecting ◽  
Number Of Children ◽  
Status Number ◽  
Significant Factors

Abstract Objectives Identify the most significant factors affecting the trajectory of recovery from severe acute malnutrition (SAM), as measured by average daily weight gain in each child 6–59 months of age who were diagnosed and treated for SAM and treated, adjusting for covariates including: breastfeeding status, number of children in household, illness, and distance to health center. Hypothesis 1a: Children 6–59 months enrolled in SAM treatment have slower times to recovery and slower weight gain if they are admitted for treatment at a lower anthropometric cut-off admission (weight for height z-score < −4) than children admitted for treatment at a higher anthropometric cut-off (weight for height z-score ≥ −4). Hypothesis 1b: Older children (24–59 months) recover more quickly than younger children (6–23 months) controlling for ration size. Methods A retrospective panel data analysis on children 6–59 months enrolled in standard outpatient treatment for severe acute malnutrition (SAM) between 2014 and 2016 was conducted. The study period was between September-December 2018. Children were exhaustively sampled. Children with edema, children with implausible z-scores for W/H (<−5 and >5) and H/A (<−6 and >6), children who were referred for inpatient therapeutic feeding to a stabilization center, and children from the same household, except in the case of twins, were eliminated from the analysis. There was one database per country. A total of 1384 children between 6–59 months were included in the analysis. Results The most significant factors affecting the proportional weight gain include age at enrollment (P = 0.001, 95%CI = −0.00—0.00) and Weight for height z-score (WHZ) (P = 0.00, 95%CI = 0.04—0.05) in each child 6–59 months of age who were diagnosed with SAM and treated, adjusting for covariates including: breastfeeding status, number of children in household, illness, and distance to health center. Sex of child did not significantly affect proportional weight gain (P = 0.404, 95%CI = −0.012–0.005). Conclusions The existing protocol to treat severe acute malnutrition should be modified to treat younger children and children who are admitted with a lower weight for height z-score due to different vulnerabilities. Funding Sources The research was conducted as part of a dissertation at The Friedman School of Nutrition Science and Policy at Tufts University. Data were obtained from World Vision.

scholarly journals Lay-screeners and Use of WHO Growth Standards Increase Case Finding of Hospitalized Malawian Children with Severe Acute Malnutrition

2014 ◽  
Vol 61 (1) ◽  
pp. 44-53 ◽  
Author(s):  
S. M. LaCourse ◽  
F. M. Chester ◽  
G. Preidis ◽  
L. M. McCrary ◽  
M. Maliwichi ◽  
...  
Keyword(s):  
Severe Acute Malnutrition ◽  
Case Finding ◽  
Acute Malnutrition ◽  
Growth Standards

scholarly journals Maternal perception of malnutrition among infants using verbal and pictorial methods in Kenya

2014 ◽  
Vol 18 (5) ◽  
pp. 869-876 ◽  
Author(s):  
Martha K Mwangome ◽  
Gregory Fegan ◽  
Andrew M Prentice ◽  
James A Berkley
Keyword(s):  
Qualitative Study ◽  
Rural Community ◽  
Severe Acute Malnutrition ◽  
Acute Malnutrition ◽  
Verbal Description ◽  
Likelihood Ratios ◽  
Anthropometric Measures ◽  
Cross Sectional ◽  
Quantitative Survey ◽  
Maternal Perception

AbstractObjectiveTo compare mothers’ perceptions of their own infants’ nutritional status with anthropometric indicators of undernutrition.DesignA qualitative study and cross-sectional quantitative survey. The qualitative study involved developing tools to assess mother’s perception. Two methods of verbal description and a pictorial scale were developed. The quantitative survey involved measuring maternal perception and comparing it with the anthropometric measures of weight-for-age Z-score (WAZ) and mid-upper arm circumference-for-age Z-score (MUACZ).SettingA rural community setting in Kenya.SubjectsSeventy-four infants aged between 4 and 6 months, and their mothers, living in rural Kenya were enrolled.ResultsUsing verbal description, the positive and negative likelihood ratios were 3·57 (95 % CI 1·44, 9·98) and 0·69 (95 % CI 0·50, 0·96) respectively for MUACZ<−2; and 4·60 (95 % CI 1·60, 13·3) and 0·67 (95 % CI 0·49, 0·92) respectively for WAZ<−2. Using the pictorial scale, the positive and negative likelihood ratios were 8·30 (95 % CI 1·91, 36·3) and 0·69 (95 % CI 0·52, 0·93) respectively for MUACZ<−2; and 4·31 (95 % CI 1·22, 15·0) and 0·78 (95 % CI 0·61, 1·00) respectively for WAZ<−2.ConclusionsIn a rural community, mothers better identify undernutrition in their infants using a pictorial scale than verbal description. However, neither can replace formal anthropometric assessment. Objective anthropometric tools should be validated for identification of severe acute malnutrition among infants aged less than 6 months.

scholarly journals Evaluation of anthropometric indicators in malnourished children at Nutritional Rehabilitation Center, Gujarat, India

2019 ◽  
Vol 6 (4) ◽  
pp. 1410
Author(s):  
Dhara Patel ◽  
Nisha Upadhyay
Keyword(s):  
Severe Acute Malnutrition ◽  
Nutritional Intervention ◽  
Cross Sectional Study ◽  
Acute Malnutrition ◽  
Daily Weight Gain ◽  
Cross Sectional ◽  
Clinical Criteria ◽  
Anthropometric Indicators ◽  
Malnourished Children ◽  
Intervention Measures

Background: It is very difficult to recognize the cases with mild-to-moderate malnutrition because clinical criteria for their diagnosis are imprecise and are difficult to interpret accurately. The objective of the study was daily weight gain in gram/kg/day in severely malnourished children.Methods: This was a hospital based cross sectional study in which total of 114 consecutive patients of SAM less than 5 years treated for complications of severe acute malnutrition using WHO protocol. The study design included 114 children from the NRC and then followed up the period of 6 months to assess the nutritional status during the period of initial stage and the entire follow up period using available record of anthropometry indicators of the admitted children recruited in the study at the NRC.Results: Mean weight at admission was 6.4 Kg, 6.5 Kg and 6.2 Kg of overall, boys and girls respectively. Mean weight at discharge was 6.8 Kg, 6.7 Kg and 6.6 Kg of overall, boys and girls respectively. Mean MUAC at admission was 10.7 cm, 10.9 cm and 10.6 cm of overall, boys and girls respectively. Mean MUAC at discharge was 10.9 cm, 10.9 cm and 10.8 cm of overall, boys and girls respectively.Conclusions: For treatment of severe acute malnutrition, systematic guidelines required, thus this study indicates that following WHO guidelines, it has become easier to manage SAM in hospital settings, with least possible stay at hospital. The objective of the study was to know the effect of nutritional intervention measures on selected anthropometric indicators of severe acute malnourished children.

scholarly journals Risk assessment of preterm birth through identification and stratification of pregnancies using a real-time scoring algorithm

2021 ◽  
Vol 9 ◽  
pp. 205031212098672
Author(s):  
Lisa BE Shields ◽  
Clayton Weymouth ◽  
Kevin L Bramer ◽  
Scott Robinson ◽  
Donna McGee ◽  
...  
Keyword(s):  
Preterm Birth ◽  
Pregnant Women ◽  
Real Time ◽  
First Trimester ◽  
Operating Characteristics ◽  
Early Care ◽  
Likelihood Ratios ◽  
Third Trimester ◽  
Predictive Values ◽  
Scoring Algorithm

Introduction: Preterm birth poses a significant challenge. This study evaluated a real-time scoring algorithm to identify and stratify pregnancies to indicate preterm birth. Methods: All claims data of pregnant women were reviewed between 1 January 2014 and 31 October 2018 in Kentucky. Results: A total of 29,166 unique women who were matched to a live newborn were documented, with the pregnancy identified during the first trimester in 54.1% of women. Negative predictive values, sensitivity, and positive likelihood ratios increased from the first to third trimesters as pregnant women who were matched to a live newborn had more visits with their physicians. The area under the receiving-operating characteristics curve on test data classifying preterm birth was 0.59 for pregnancies identified during the first trimester, 0.62 for pregnancies identified in the second trimester, and 0.73 for pregnancies identified in the third trimester. Conclusions: This study presents a real-time scoring algorithm of indicating preterm birth in the first trimester of gestation which permits stratification of pregnancies to provide more efficient early care management.

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