Research Snapshots

Characteristics of global data onadolescents’ dietary intake
This is a summary of the following paper: Demmler K, Beal T, Ghadirian M et al (2024)
Characteristics of global data on adolescent's dietary intake: A systematic scoping review.
Current Developments in Nutrition, 8, 1, 102054. https://doi.org/10.1016/j.cdnut.2023.102054

Despite data on adolescents’ dietaryintake being essential to improve
nutrition status, the availability ofhigh-quality disaggregated data remains limited and with large global differences. These knowledge gaps hinder the assessmentof adolescent diets and the development of evidence-based interventions to improve adolescent health and that of future generations.
A systematic scoping review was conducted
to investigate the availability, characteristics, andgaps in global adolescent dietary data. This included peer-reviewed and grey literature articles (from2010 onwards) on the dietary intake of male andfemale adolescents aged 10–24 years. Studies fromall countries and languages were included, incorporating any information related to types of foodconsumed, diet composition, dietary diversity, ormeal patterns. Studies with insufficient methodological information, sample sizes less than 25,school-based data sets containing less than six
schools, and studies that focused on pregnant or
unhealthy study populations were excluded. Data,including year(s) of data collection, age, gender,sample size, dietary assessment methods, numberof food items/groups, study design, location, andrepresentativeness, were extracted. Of the 722 articles that were included, 677 (94%) were peer reviewed, representing 1,223 data sets, and 45 (6%)
were grey literature, representing 98 data sets. Halfof all data sets were from high-income countries.
Most of the data was collected in cross-sectional
surveys and over half of the data sets (57%) werefrom national representative surveys.
The literature search revealed that there wasno dietary data for adolescents in over one-third

Finding the most vulnerable: How to

identify malnourished infantsThis is a summary of the following paper: Mahmud I, Guesdon B, Kerac M et al (2024) Mortality
risk in infants receiving therapeutic care for malnutrition: A secondary analysis. Maternal &Child Nutrition, e13635. https://pubmed.ncbi.nlm.nih.gov/38433606/

T

his secondary analysis investigated inpatient therapeutic care data for 3,692 infants (aged under six months) across 34
field sites, between 2002 and 2008, from12 countries: Afghanistan, Burundi, the Democratic Republic of Congo, Ethiopia, Kenya, Liberia, Myanmar, Niger, Somalia, Sudan, Tajikistan,and Uganda. Admittance criteria was comprisedof 1) infant too weak to suckle effectively, 2) notgaining weight at home, 3) weight-for-lengthz-score <-3, and/or 4) presence of bilateral pitting
oedema. Multiple variables were collected at admission and discharge, with death at discharge being the outcome of interest in this analysis. Logistic regression was used to examine the associationof various anthropometric deficits and mortality.
In this admitted population, 95.8% were underweight, 82.8% wasted, and 77.8% stunted(figure 1). When applying the Composite Index of Anthropometric Failure (CIAF) – which
combines underweight, wasted, and stunted intoa single indicator of anthropometric deficits –96.8% of children fell under this classification.
Infants with multiple anthropometric deficits
were often more severely wasted, stunted, andunderweight than those with a single anthropometric deficit. This underscores the urgent needfor targeted interventions to address the specificneeds of these vulnerable infants.

compared to anthropometrically normal infants. Severely underweight infants had over triple the odds of mortality (OR 3.3, 95% CI 0.813.6, p=0.09), although this was not a significant
finding due to the broad confidence interval observed. Notably, weight had fewer missing values
and flagged data, making this assessment morepractical. Sex differences were observed, whereboys had greater odds of inpatient mortality
than girls (OR 1.40, 95% CI 1.02-1.92, p=0.03).
In this analysis, the only infants to die were thosewith multiple anthropometric deficits, although
their odds of mortality were not significant due
to the broad confidence intervals observed.
The study excluded participants with missing data and/or outlier data based on predetermined guidelines, which may increase our confidence in the statistical analysis, but may also
introduce selection bias into the sample. As thisFigure 1of countries globally. Most of these countries
were in Sub-Saharan Africa. Furthermore, 14%of all countries (n=22) – primarily in Sub-Saharan Africa, and Europe and Central Asia –lacked nationally representative dietary data.
The review identified a limited amount of detailed dietary information. In many countries,
data on adolescent diets was available for fewer than seven food items/groups, which did notallow for quantification of intake. In the absenceof a validated dietary diversity score for adolescents, assumptions were based on the Minimum Dietary Diversity score for children aged
6–23 months. Despite the existence of the validated Minimum Dietary Diversity for Women(ages 15–49 years, assessing 10 food groups), a
seven-food group count was chosen as a threshold. This was assumed to provide a meaningfulcharacterisation of adolescent dietary intake. A
significant limitation of this review was that only
peer-reviewed journals from one database (PubMed) were included.
The study highlights the critical significance ofaddressing adolescent nutrition, emphasising thepressing need for enhanced, accessible, and comprehensive data on adolescents' dietary intake tosupport effective nutritional interventions.

study took place across multiple sites, variation
in measurements taken by different staff may
have introduced measurement bias. However,
the inclusion of multiple sites increases both thesample size and the generalisability of the findings. Seasonality may also affect our interpretation, as measurements were taken at different
time points in different locations. This analysis
lacked data on participants' co-morbidities, congenital anomalies, prenatal and birth history, orbreastfeeding practices. These factors could potentially influence the observed associations between anthropometric deficits and mortality.
These results are not generalisable beyond thisinpatient setting – which is a subgroup of alreadymalnourished children – so the findings should
be interpreted with caution. This analysis does reinforce existing knowledge that there are sex differences in malnutrition-related mortality andthat children with concurrent forms of malnutrition face the greatest mortality risk. Using morecomprehensive indicators, such as CIAF, offers amore holistic understanding of undernutrition
and risk of infant mortality. Yet, more research isneeded to determine the added benefit of CIAF
whilst balancing its additional burden/complexity for programme staff. Wasting and underweightappear to correlate more strongly with mortality
compared to stunting in this setting.

Prevalence and overlap of different anthropometric deficits andmortality

A total of 141 infants died during inpatienttherapeutic care, of which 116 were severely wasted and 138 were severely underweight.
Severely wasted infants had double the odds
of mortality (OR 2.1, 95% CI 1.2-2.7, p=0.009)
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