Inadequate Utilization of Prenatal Care Services, Socioeconomic Status, and Educational Attainment Are Associated with Low Birth Weight in Zimbabwe
Bibliographic record
Abstract
BACKGROUND: Globally, low birth weight (LBW) remains a leading cause of neonatal and infant mortality and poses significant challenges toward the progress of achieving infant mortality-related goals. Experience from developed countries shows that two major causes of LBW (premature delivery and intrauterine growth restriction) can be averted to a great extent by adequate utilization of maternal health-care services, during pregnancy. In this study, we attempt to measure the prevalence of LBW in Zimbabwe and explore the association between adequate utilization of prenatal care (PNC) services and LBW in Zimbabwe. We also explore other possible associations with LBW. METHODOLOGY: This study was based on nationally representative, cross-sectional data from Multiple Indicator Cluster Survey round 5, conducted in 2014. Participants included 3,221 mothers from both rural and urban areas. The participants were selected regardless of their current pregnancy status. Sample characteristics were presented using descriptive statistics. Association between utilization status of ANC and LBW was measured by chi-square (bivariate) test and logistic regression methods. RESULTS: Prevalence of LBW was 12.8%. There was 11% reduction in the odds of having LBW babies for participants from urban area when compared with rural area (AOR = 0.897; 95% CI = 0.707-1.138). When compared to women with higher education, those having primary/below primary and secondary level qualification had higher odds of experiencing LBW babies by 73 and 56%, respectively. Participants who had less than four PNC/ANC visits had 34% higher odds (AOR = 1.340; 95% CI = 1.065-1.685) than those with at least four visits, and those who had given birth more than once, had 38% lower odds (AOR = 0.620; 95% CI = 0.493-0.780) of giving birth to LBW babies when compared to those who had given birth only once. CONCLUSION: and not only in terms of hospitalization but also in terms of outpatient and physician visits during the first year of their life.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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; a candidate call from one teacher head, 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".