A Prospective Study of Growth and Biomarkers of Exposure to Aflatoxin and Fumonisin during Early Childhood in Tanzania
Candida P. Shirima; Martin Kimanya; Michael N. Routledge; Chou Srey; Joyce Kinabo; Hans‐Ulrich Humpf; Christopher P. Wild; Yu‐Kang Tu · 2014 · Environmental Health Perspectives
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
BACKGROUND: Aflatoxin and fumonisin are toxic food contaminants. Knowledge about effects of their exposure and coexposure on child growth is inadequate. OBJECTIVE: We investigated the association between child growth and aflatoxin and fumonisin exposure in Tanzania. METHODS: A total of 166 children were recruited at 6-14 months of age and studied at recruitment, and at the 6th and 12th month following recruitment. Blood and urine samples were collected and analyzed for plasma aflatoxin-albumin adducts (AF-alb) using ELISA, and urinary fumonisin B1 (UFB1) using liquid chromatography-mass spectr
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
Catastrophic Natural Disasters and Economic Growth
Negative / Null Result ReportBrain anomalies in children exposed prenatally to a common organophosphate pesticide
Negative / Null Result ReportPhylogenomic Insights into the Evolution of Stinging Wasps and the Origins of Ants and Bees
Negative / Null Result ReportSpecies Richness and the Temporal Stability of Biomass Production: A New Analysis of Recent Biodiversity Experiments
Negative / Null Result ReportNew Insight into the History of Domesticated Apple: Secondary Contribution of the European Wild Apple to the Genome of Cultivated Varieties
Negative / Null Result ReportIncreasing Crop Diversity Mitigates Weather Variations and Improves Yield Stability
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: OpenAlex · DOI 10.1289/ehp.1408097