Objectives This study aims to describe the mortality risk of children in the community who had severe acute malnutrition (SAM) defined by either a mid-upper arm circumference (MUAC) <115mm, a low weight-for-height Z-score (WHZ) <-3 or both criteria. Methods We pooled individual-level data from children aged 6–59 months enrolled in 3 community-based studies in the Democratic Republic of the Congo (DRC), Senegal and Nepal. We estimate the mortality hazard using Cox proportional hazard models in groups defined by either anthropometric indicator. Results In total, we had 49,001 time points provided by 15,060 children available for analysis, summing to a total of 143,512 person-months. We found an increasing death rate with a deteriorating nutritional status for all anthropometrical indicators. Children identified as SAM only by a low MUAC (<115mm) and those identified only by a low WHZ (Z-score <-3) had a similar mortality hazard which was about 4 times higher than those without an anthropometric deficit. Having both a low MUAC and a low WHZ was associated with an 8 times higher hazard of dying compared to children within the normal range. The 2 indicators identified a different set of children; the proportion of children identified by both indicators independently ranged from 7% in the DRC cohort, to 35% and 37% in the Senegal and the Nepal cohort respectively. Conclusion In the light of an increasing popularity of using MUAC as the sole indicator to identify SAM children, we show that children who have a low WHZ, but a MUAC above the cut-off would be omitted from diagnosis and treatment despite having a similar risk of death.
Background: Growth assessment based on the WHO child growth velocity standards can potentially be used to predict adverse health outcomes. Nevertheless, there are very few studies on growth velocity to predict mortality.Objectives: We aimed to determine the ability of various growth velocity measures to predict child death within 3 mo and to compare it with those of attained growth measures.Design: Data from 5657 children <5 y old who were enrolled in a cohort study in the Democratic Republic of Congo were used. Children were measured up to 6 times in 3-mo intervals, and 246 (4.3%) children died during the study period. Generalized estimating equation (GEE) models informed the mortality risk within 3 mo for weight and length velocity z scores and 3-mo changes in midupper arm circumference (MUAC). We used receiver operating characteristic (ROC) curves to present balance in sensitivity and specificity to predict child death.Results: GEE models showed that children had an exponential increase in the risk of dying with decreasing growth velocity in all 4 indexes (1.2- to 2.4-fold for every unit decrease). A length and weight velocity z score of <−3 was associated with an 11.8- and a 7.9-fold increase, respectively, in the RR of death in the subsequent 3-mo period (95% CIs: 3.9, 35.5, and 3.9, 16.2, respectively). Weight and length velocity z scores had better predictive abilities [area under the ROC curves (AUCs) of 0.67 and 0.69] than did weight-for-age (AUC: 0.57) and length-for-age (AUC: 0.52) z scores. Among wasted children (weight-for-height z score <−2), the AUC of weight velocity z scores was 0.87. Absolute MUAC performed best among the attained indexes (AUC: 0.63), but longitudinal assessment of MUAC-based indexes did not increase the predictive value.Conclusion: Although repeated growth measures are slightly more complex to implement, their superiority in mortality-predictive abilities suggests that these could be used more for identifying children at increased risk of death.
ObjectiveTo estimate the abilities of weight and length velocities vs attained growth measures to predict stunting, wasting, and underweight at age 2 years.Study designWe analyzed data from a community-based cohort study (The Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development study [MAL-ED] study) in Bhaktapur, Nepal. A total of 240 randomly selected children were enrolled at birth and followed up monthly up to age 24 months. Linear and logistic regression models were used to predict malnutrition at 2 years of age with growth velocity z scores at 0-3, 0-6, 3-6, 6-9, 6-12, and 9-12 months (using the World Health Organization Growth Standards) or attained growth at 0, 3, 6, and 12 months as predictors.ResultsAt age 2 years, 4% of the children were wasted, 13% underweight, and 21% stunted. Children who were malnourished at age 2 years had lower mean growth z scores already at birth and throughout the study period. Anthropometric indicators in infancy were significant predictors for growth at the age of 2 years during most periods and at most ages in infancy. Weight-for-age z score, length-for-age z score, and weight-for-length z score at age 12 months had excellent areas under the curve (91-95) to predict the value of the same indicator at age 24 months. Maximum area under the curve values for weight and length velocity were somewhat lower (70-84).ConclusionsGrowth measured at one time point in infancy was better correlated with undernutrition at age 2 years than growth velocity.
Introduction: There is an increase in the double burden of malnutrition globally, with a particular rise documented in Asia. In Nepal, undernutrition has been prevalent for decades. Today, however, the incidence of overweight and obesity (OWOB) in the country has increased substantially. There is a need to conduct local studies reporting on the concurrent burden of both underweight and OWOB across adult populations. This study addresses this need by describing the distribution of body mass index (BMI) in a defined population of adults living in the peri-urban community of Bhaktapur, Nepal. Material and methods: For this cross-sectional analysis, we used data that were available from 600 women and 445 men whose children were enrolled in an individually randomized, double-blind, placebo-controlled trial assessing the effect of daily vitamin B12 supplementation. Upon enrolment of their 6-11-month old children, mothers and fathers were interviewed about their socio-demographic details. In addition, their weight and height were measured by trained field workers. Each parent's BMI was calculated as the ratio of body weight (in kg) and height squared (in m), expressed as kg/m 2 , and categorized according to the WHO recommendation. We used linear and multinomial logistic regression models to assess associations between the BMI of the mothers and fathers, and their baseline characteristics. Results: The mean BMI was 23.7 kg/m 2 for both the mothers and fathers with a standard deviation (SD) of 3.6 and 3.7, respectively. The proportion categorized as underweight, overweight, and obese was also similar in the two groups with around 5% being underweight, 30% being overweight and 5% being obese. Age was positively associated with BMI in both groups. Those categorized as daily wage earner had a lower mean BMI than those in other occupational groups. Conclusion: Our results contribute to documenting the burden of both under-and overnutrition in a selected group of young adults living in a peri-urban community in Nepal. As Nepal is undergoing an improvement in its economic situation, as well as a nutrition transition, it is important to provide sufficient information to enable timely action, and evidence-based decision-making to prevent a further increase in Nepal's growing double burden of malnutrition.
BackgroundLongitudinal studies describing incidence and natural course of malnutrition are scarce. Studies defining malnutrition clinically [moderate clinical malnutrition (McM) marasmus, kwashiorkor] rather than anthropometrically are rare. Our aim was to address incidence and course of malnutrition among pre-schoolers and to compare patterns and course of clinically and anthropometrically defined malnutrition.MethodsUsing a historical, longitudinal study from Bwamanda, DR Congo, we studied incidence of clinical versus anthropometrical malnutrition in 5 657 preschool children followed 3-monthly during 15 months.ResultsIncidence rates were highest in the rainy season for all indices except McM. Incidence rates of McM and marasmus tended to be higher for boys than for girls in the dry season. Malnutrition rates increased from the 0–5 to the 6 – 11 months age category. McM and marasmus had in general a higher incidence at all ages than their anthropometrical counterparts, moderate and severe wasting. Shifts back to normal nutritional status within 3 months were more frequent for clinical than for anthropometrical malnutrition (62.2-80.3% compared to 3.4-66.4.5%). Only a minority of moderately stunted (30.9%) and severely stunted children (3.4%) shifted back to normal status. Alteration from severe to mild malnutrition was more characteristic for anthropometrically than for clinically defined malnutrition.ConclusionsOur data on age distribution of incidence and course of malnutrition underline the importance of early life intervention to ward off malnutrition. In principle, looking at incidence may yield different findings from those obtained by looking at prevalence, since incidence and prevalence differ approximately differ by a factor “duration”. Our findings show the occurrence dynamics of general malnutrition, demonstrating that patterns can differ according to nutritional assessment method. They suggest the importance of applying a mix of clinical and anthropometric methods for assessing malnutrition instead of just one method. Functional validity of characterization of aspects of individual nutritional status by single anthropometric scores or by simple clinical classification remain issues for further investigation.
Background: Studying the influence of geographical factors on child growth is important, especially given the increasing interest in climate change and health in resource-poor settings and the recognized importance of growth faltering as a general marker of population health. We describe patterns in children's weight and length velocity and relate them to seasonal and spatial factors in rural DR Congo. The study setting is a food-insecure area with a majority dependent on rain-fed subsistence farming and expected to be one of the regions most affected by climate change. Methods:We studied the effect of selected geographical factors, i.e. season, village size and distances to hospital, health center, forest, fishing grounds and market on growth of children under two years old. We calculated individual growth velocity Z-scores according to the WHO-2009 growth velocity standards for up to five successive 3-month growth periods. Associations with geographical factors were examined in multivariate mixed effects regression models.Results: For the study population of 2223 children is characterized by low nutritional status. Age and season were the only independent predictors of growth velocity in the multivariate regression analysis. Mean velocity Z-scores were already low in children aged 0-6 months for weight [-1.34 (95% CI: -1.45, -1.22)] and for length [-0.99 (95% CI: -1.13, -0.84)]. They increased with age, while Z-scores of attained growth gradually decreased. Mean growth velocities were lowest before the main harvest season with a mean improvement of 1.2 and 2.3 Z-scores for weight and length velocity thereafter. A seasonal pattern was not seen in attained growth. No relation to spatial factors was found. Conclusions: In this rural subsistence economy area, geographical factors relating to distances to food sources and health services are less important determinants than harvest season, which is the major underlying determinant of child growth in these settings.
The aim of this study was to explore the association between adolescent subjective social status (SSS) and body mass index (BMI) at two different time points and to determine whether this association was mediated by health-related behaviors. In 2002 (n = 1596) and 2017 (n = 1534), tenth-grade students (15–16 years old) in schools in the District of Oppland, Norway, completed a survey. Four categories of perceived family economy were measured as SSS, and structural equation modeling was performed, including a latent variable for unhealthy behavior derived from cigarette smoking, snuff-use, and alcohol-drinking as well as dietary and exercise as mediators. No linear association was found between SSS and BMI in 2002 (standardized ß −0.02, (95% confidence interval (CI) −0.07, 0.03)). However, an association was present in 2017 (standardized ß −0.05 (95% CI −0.10, −0.001)), indicating that BMI decreased by 0.05 standard deviations (0.05 × 3.1 = 0.16 BMI unit) for every one-category increase in SSS. This association was mediated by exercise (standardized ß −0.013 (95% CI −0.02, −0.004) and unhealthy behavior (standardized ß −0.009 (95% CI −0.002, −0.04)). In conclusion, a direct association between SSS and BMI was found in 2017 in this repeated cross-sectional survey of 15–16-year-old Norwegian adolescents. This association was mediated through health-related behavior.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.