We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
In the present study, we aimed to compare anthropometric indicators as predictors of mortality in a community-based setting.
Design:
We conducted a population-based longitudinal study nested in a cluster-randomized trial. We assessed weight, height and mid-upper arm circumference (MUAC) on children 12 months after the trial began and used the trial’s annual census and monitoring visits to assess mortality over 2 years.
Setting:
Niger.
Participants:
Children aged 6–60 months during the study.
Results:
Of 1023 children included in the study at baseline, height-for-age Z-score, weight-for-age Z-score, weight-for-height Z-score and MUAC classified 777 (76·0 %), 630 (61·6 %), 131 (12·9 %) and eighty (7·8 %) children as moderately to severely malnourished, respectively. Over the 2-year study period, fifty-eight children (5·7 %) died. MUAC had the greatest AUC (0·68, 95 % CI 0·61, 0·75) and had the strongest association with mortality in this sample (hazard ratio = 2·21, 95 % CI 1·26, 3·89, P = 0·006).
Conclusions:
MUAC appears to be a better predictor of mortality than other anthropometric indicators in this community-based, high-malnutrition setting in Niger.
Recommend this
Email your librarian or administrator to recommend adding this to your organisation's collection.