Household Wealth Inequalities in High Body Mass Index among Women of Childbearing Age: Evidence from the Ghana Demographic and Health Survey
Bibliographic record
Abstract
Abstract Background Ghana is currently experiencing higher body mass index (BMI), that is overweight and obesity, among reproductive-aged women. However, understanding the role of socioeconomic status in the high BMI among this cohort has not been studied extensively in Ghana and the few existing studies in the country have generated mixed results. This study aims to examine household wealth inequalities in high BMI among Ghanaian women of childbearing age. Methods The 2014 Ghana Demography and Health Survey (GDHS) dataset was analyzed. A univariable and multivariable regression model with a logit link function was specified to ascertain the effect of household wealth inequalities in high BMI among Ghanaian women. Furthermore, concentration index and curve were used to measure the degree of household wealth inequalities in high BMI among reproductive aged women. Results This study found high BMI prevalence of 35.9 percent with significant household wealth-related inequalities (Concentration index = 0.24, 95%CI (confidence interval): 0.22–0.26). The analysis revealed that high BMI is concentrated among wealthier women. Compared to poorest women, poorer (AOR (Adjusted odds ratio) = 2.18, 95%CI: 1.66–2.85), middle-class (AOR = 4.44, 95%CI: 3.24–6.09), richer (AOR = 7.75, 95%CI: 5.53–10.86) and richest (AOR = 11.03, 95%CI: 8.07–15.06) women were more likely to have high BMI. On top of that, socioeconomic characteristics including age, marital status, and education of reproductive-aged women were significantly associated with high BMI. Conclusions The research revealed that a woman from a wealthier household had higher likelihood of having high BMI relative to those from a less wealthy household. Also, women who were educated and cohabiting, formerly or currently married had an increased risk of having high BMI. This observation suggests targeted policy interventions and programs that promote healthy body weight to reduce the high BMI prevalence among women of childbearing age in Ghana.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.043 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.015 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".