Sex and Gender Determinants of Increased Blood Pressure Among Women With Previous Gestational Diabetes Mellitus in Rural China
Bibliographic record
Abstract
Abstract Background: Gestational diabetes mellitus (GDM) increases the long-term risk of hypertension and cardiovascular events for mothers later in life but has not been well recognized by nurses. The aims of the study were to describe the proportion of increased blood pressure in rural women with previous GDM and to explore the sex (biological) and gender (sociocultural) factors that contribute to the increased blood pressure.Methods: A cross-sectional descriptive survey including 397 women with previous GDM was conducted in rural areas of Central South of China between November 2017 and June 2018. The variables of sex (e.g., age, ethnicity, family history of hypertension, time since delivery, 75-g oral glucose tolerance test, body mass index, and waist circumference) and gender (education, occupation, income, physical activity, fruit and vegetable intake, sedentary time, perceived stress, and general self-efficacy) were collected on research site. Increased blood pressure referred to systolic blood pressure of ≥130 mm Hg and/or diastolic blood pressure of ≥85 mm Hg. Logistic regression was performed to recognize the sex and gender factors associated with increased blood pressure. Results: There were nearly 20% (78/397) of participants first found increased blood pressure. Among those participants who had increased blood pressure, advanced age, a family history of hypertension, and abnormal 2-h plasma glucose levels were sex-related factors associating with the increased blood pressure (P < 0.05), while obesity indicators (body mass index and waist circumference) were not associated (P > 0.05). General self-efficacy, a gender factor, had a protective relationship with increased blood pressure (P < 0.05). Conclusions: Increased blood pressure is prevalent in rural Chinese women with previous GDM. Both sex and gender are determinants. Interventions promoting glycemic status and general self-efficacy are promising to improve their cardiovascular health later in life.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".