Prevalence of hyperglycemia in pregnancy and influence of body fat on development of hyperglycemia in pregnancy among pregnant women in urban areas of Arusha region, Tanzania
Bibliographic record
Abstract
BACKGROUND: Hyperglycemia in pregnancy is a medical condition resulting from either pre-existing diabetes or insulin resistance developed during pregnancy. This study aimed to determine the prevalence of hyperglycemia in pregnancy and influence of body fat percentage and other determinants on developing hyperglycemia in pregnancy among women in Arusha District, Tanzania. METHODS: A cross-sectional study was conducted between March and December 2018 at selected health facilities in Arusha District involving 468 pregnant women who were not known to have diabetes before pregnancy. Blood glucose was tested by Gluco-Plus™ using the World Health Organization criteria at fasting and 2 h after consuming 75 g of glucose dissolved in 300 ml of water. Body fat was measured using a bioelectric impedance analyzer, mid-upper arm circumference using a regulated tape, weight using SECA™, blood pressure using a GT-868UF Geratherm™ machine, and height using a stadiometer. Demographic and maternal characteristics were collected through face to face interviews using a structured questionnaire. RESULTS: (SD ± 5.5). One-third of participants had mid-upper arm circumferences ≥28 cm with 25% being overweight and 22.7% obese before pregnancy. Prevalence of hyperglycemia in pregnancy was 16.2% (n = 76) of which 13% had gestational diabetes and 3.2% diabetes in pregnancy. Hyperglycemia in pregnancy was significantly associated with body fat percentage (AOR 1.33; 95% CI: 1.22-1.44), family history of Type 2 diabetes mellitus (AOR 6.95, 95% CI: 3.11-15.55), previous delivery of babies ≥4 kg (AOR 2.3, 95% CI: 1.00-5.28), mid-upper arm circumference ≥ 28 cm (AOR 1.2, 95% CI: 1.09-1.32), and Type 2 diabetes mellitus symptoms (AOR 2.83, 95% CI: 1.53-6.92). CONCLUSION: The prevalence of hyperglycemia in pregnancy was high, particularly among women with history of delivering ≥4-kg babies, increased body fat, mid-upper arm circumference, symptoms and/or family history of Type 2 diabetes mellitus. These findings identify opportunities to further explore the utility of body fat percentage and other determinants for rapid screening and management of hyperglycemia in pregnancy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".