Rafael Flores-Ayala
Overview
Explore the profile of Rafael Flores-Ayala including associated specialties, affiliations and a list of published articles.
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39
Citations
1097
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Recent Articles
11.
Pickens C, Flores-Ayala R, Addo O, Whitehead Jr R, Palmieri M, Ramirez-Zea M, et al.
Prev Chronic Dis
. 2020 Jul;
17:E66.
PMID: 32701434
Introduction: Data on the prevalence and predictors of high blood pressure among children and non-pregnant women of reproductive age are sparse in Guatemala. Our objective was to identify the prevalence...
12.
Ford N, Bichha R, Parajuli K, Paudyal N, Joshi N, Whitehead Jr R, et al.
Matern Child Nutr
. 2020 Apr;
18 Suppl 1:e13013.
PMID: 32338438
We used data from the 2016 Nepal National Micronutrient Status Survey to evaluate factors associated with anaemia (World Health Organization cut-points using altitude- and smoking-adjusted haemoglobin [Hb]) among nationally representative...
13.
Ford N, Bichha R, Parajuli K, Paudyal N, Joshi N, Whitehead Jr R, et al.
Matern Child Nutr
. 2020 Mar;
18 Suppl 1:e12953.
PMID: 32153098
We used cross-sectional data from the 2016 Nepal National Micronutrient Status Survey to evaluate factors associated with anaemia among a nationally representative sample of nonpregnant women 15- 49 years (n...
14.
Ford N, Bichha R, Parajuli K, Paudyal N, Joshi N, Whitehead R, et al.
J Nutr
. 2019 Dec;
150(4):929-937.
PMID: 31883009
Background: Anemia is a major concern for children in Nepal; however, little is known about context-specific causes of anemia. Objective: We used cross-sectional data from the 2016 Nepal National Micronutrient...
15.
Conkle J, Suchdev P, Alexander E, Flores-Ayala R, Ramakrishnan U, Martorell R
PLoS One
. 2018 Oct;
13(10):e0205320.
PMID: 30356325
The usefulness of anthropometry to define childhood malnutrition is undermined by poor measurement quality, which led to calls for new measurement approaches. We evaluated the ability of a 3D imaging...
16.
de Onis M, Borghi E, Arimond M, Webb P, Croft T, Saha K, et al.
Public Health Nutr
. 2018 Oct;
22(1):175-179.
PMID: 30296964
Objective: Prevalence ranges to classify levels of wasting and stunting have been used since the 1990s for global monitoring of malnutrition. Recent developments prompted a re-examination of existing ranges and...
17.
Suchdev P, Young M, Williams A, Addo Y, Namaste S, Aaron G, et al.
Am J Clin Nutr
. 2018 Jul;
108(1):202-203.
PMID: 29982307
No abstract available.
18.
Conkle J, Ramakrishnan U, Flores-Ayala R, Suchdev P, Martorell R
PLoS One
. 2017 Dec;
12(12):e0189332.
PMID: 29240796
Anthropometric data collected in clinics and surveys are often inaccurate and unreliable due to measurement error. The Body Imaging for Nutritional Assessment Study (BINA) evaluated the ability of 3D imaging...
19.
Suchdev P, Williams A, Mei Z, Flores-Ayala R, Pasricha S, Rogers L, et al.
Am J Clin Nutr
. 2017 Oct;
106(Suppl 6):1626S-1633S.
PMID: 29070567
The determination of iron status is challenging when concomitant infection and inflammation are present because of confounding effects of the acute-phase response on the interpretation of most iron indicators. This...
20.
Gupta P, Hamner H, Suchdev P, Flores-Ayala R, Mei Z
Am J Clin Nutr
. 2017 Oct;
106(Suppl 6):1640S-1646S.
PMID: 29070559
Total-body iron stores (TBI), which are calculated from serum ferritin and soluble transferrin receptor concentrations, can be used to assess the iron status of populations in the United States. This...