Differentials in prevalence and correlates of metabolic risk factors of non-communicable diseases among women in sub-Saharan Africa: evidence from 33 countries
Bibliographic record
Abstract
BACKGROUND: Even with the widespread recognition of non- communicable diseases (NCDs) in sub-Saharan Africa region, yet, sufficient evidence-based surveillance systems to confirm the prevalence and correlates of these diseases is lacking. In an attempt to understand the problem of NCDs in resource-constrained settings, this study was conducted to establish the pattern of the risk factors of NCDs in sub-Sahara Africa region. METHODS: ). Hemoglobin level: anemic < 12.0 g/dL (< 120 g/L) for women. Hypertension was defined as systolic blood pressure (SBP) ≥140 mmHg and/or diastolic blood pressure (DBP) ≥90 mmHg. Binary and multinomial logistic regression models were used to investigate the correlates of the variables. RESULTS: The percentage of hypertension was highest among women in Lesotho with about 17.3% and lowest among women in Burundi (1.0%). Anemia was prevalent among sub-Saharan Africa women; where more than half of the women from several countries were anemic with Gabon (60.6%) reporting the highest prevalence. The percentage of obesity in sub-Saharan Africa showed that Lesotho (19.9%), Gabon (18.9%) and Ghana (15.6%) were the prominent countries with obese women, while Madagascar (1.1%) had the minimum obese women. Body mass index was significantly associated with hypertension and anemia. The behavioural or modifiable factors of hypertension and body mass index were; smoking, fruits, vegetables and alcohol consumption. While the non-modifiable significant factors include; age, residence, religion, education, wealth index, marital status, employment and number of children ever born. However, anemia shared similar factors except that smoking and vegetable consumption were not statistically significant. In addition, involvement in exercise was associated with anemia and hypertension. CONCLUSION: The problem of NCDs and associated factors remains high among women of reproductive age in sub-Sahara region. The findings of this study suggest that promotion of regular positive health care-seeking behaviour, screening and early treatment are essential to mitigate the burden of NCDs. Furthermore, preventive interventions of NCDs risk factors should be strengthened among key population through behavior change communication with support from government and stakeholders in health care.
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".