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Record W2131061036 · doi:10.4269/ajtmh.13-0422

Relative Undernourishment and Food Insecurity Associations with Plasmodium falciparum Among Batwa Pygmies in Uganda: Evidence from a Cross-Sectional Survey

2014· article· en· W2131061036 on OpenAlexfundno aff
Joseph A. Lewnard, James D. Ford, Shuaib Lwasa, Didacus B. Namanya, Kaitlin Patterson, Blánaid Donnelly, Manisha A. Kulkarni, Sherilee L. Harper, Nicholas H. Ogden, César Cárcamo

Bibliographic record

VenueAmerican Journal of Tropical Medicine and Hygiene · 2014
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsCross-sectional studyPlasmodium falciparumFood insecurityEnvironmental healthMalariaGeographyBiologyMedicineDemographySocioeconomicsFood securityImmunologyEcologyPathology

Abstract

fetched live from OpenAlex

Although malnutrition and malaria co-occur among individuals and populations globally, effects of nutritional status on risk for parasitemia and clinical illness remain poorly understood. We investigated associations between Plasmodium falciparum infection, nutrition, and food security in a cross-sectional survey of 365 Batwa pygmies in Kanungu District, Uganda in January of 2013. We identified 4.1% parasite prevalence among individuals over 5 years old. Severe food insecurity was associated with increased risk for positive rapid immunochromatographic test outcome (adjusted relative risk [ARR] = 13.09; 95% confidence interval [95% CI] = 2.23-76.79). High age/sex-adjusted mid-upper arm circumference was associated with decreased risk for positive test among individuals who were not severely food-insecure (ARR = 0.37; 95% CI = 0.19-0.69). Within Batwa pygmy communities, where malnutrition and food insecurity are common, individuals who are particularly undernourished or severely food-insecure may have elevated risk for P. falciparum parasitemia. This finding may motivate integrated control of malaria and malnutrition in low-transmission settings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.308
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations21
Published2014
Admission routes1
Has abstractyes

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