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Evaluation of Risk Factors of Diabetes Mellitus among Out-patients in two Nigerian Secondary Health Facilities

2020· dataset· en· W4230071830 on OpenAlexaboutno aff
Chinonyerem O. Iheanacho, Doyin O Osoba, Uchenna I. H. Eze

Bibliographic record

VenueAuthorea · 2020
Typedataset
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOverweightWaistDiabetes mellitusType 2 diabetesEnvironmental healthBlood sugarObesityGerontologyInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Aim: Prevention of type 2 diabetes is enabled by identification and effective management of risk factors. The study was conducted to evaluate the risk factors associated with the development of type 2 diabetes. Methods: A cross-sectional survey was conducted on persons without diabetes in two secondary hospitals using Canadian diabetes risk assessment questionnaire. Data analysis was done using SPSS version 18. Result: A total of 300 respondents participated in the study and 160 (53.3%) were at high risk of developing type 2 diabetes. From the risk evaluation, males (62.5%), overweight (65.1%) and obese (82.6%) participants; were at high risk for type 2 diabetes. Others found to be at high risk were; respondents with high waist circumference (55.6%), respondents who did not exercise (77.0%), those who did not eat fruits and vegetable daily (54.4% ), those with high blood pressure (67.5% ) and those who have had raised blood sugar in the past (71.0% ). Conclusion: Majority of the study participants was at high risk for type 2 diabetes and male participants had higher risks than their female counterparts. Other socio-demographic factors also presented major risks for type 2 diabetes.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.656
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.301
Teacher spread0.271 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2020
Admission routes1
Has abstractyes

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