Overweight and obesity among women in a predominantly rural district of Ghana
Bibliographic record
Abstract
The double burden of malnutrition is evident among women of reproductive age (WRA) in Ghana where micronutrient deficiencies commonly occur concurrent with an increasing prevalence of overweight and obesity (OW/OB). However, overnutrition among Ghanaian women has been rarely characterized. We assessed sociodemographic determinants of OW/OB among women in a predominantly rural district of Ghana. Cross‐sectional data were collected from WRA (n=1095) who lived in the Upper Manya Krobo District of the Eastern Region and who participated in the Nutrition Links Infant Household baseline survey between November 2013 and May 2014. The women were interviewed about their personal and household characteristics and weight and height measurements were taken. Body mass index (BMI) was calculated and a dichotomous variable was used to represent non‐OW/OB (BMI<25 kg/m 2 ) and OW/OB (BMI ≥ 25 kg/m 2 ). The mean age of the women was 27.4 ± 7.6 y. Over one‐quarter of them were either overweight (21%) or obese (6.4%); the prevalence of underweight (7.2%) was similar to that of obesity. OW/OB was significantly associated with being 30 y or older, married, and having more household assets (at least 4 out of 12 items) ( p <0.05). However, those women who owned their home were less likely to be OW/OB ( p <0.05). Combined, the prevalence of overweight and obesity was almost four‐fold higher than that of underweight among these predominantly rural women. Concurrent efforts to address both over‐ and undernutrition are needed to enhance women's health and well‐being in this population. Support or Funding Information Funded by the Department of Foreign Affairs, Trade, and Development (DFATD) of the Government of Canada
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".