The risk, perceived and actual, of developing type 2 diabetes mellitus for mothers of preschool children in urban China
Bibliographic record
Abstract
BACKGROUND: The perceived risk of developing type 2 diabetes mellitus (T2DM) can motivate individuals to adopt preventive health behaviors. Compared with fathers, mothers of young children often experience unique risk factors for developing T2DM: pregnancy-related weight gain, lifestyle changes related to child care, and the increased incidence of gestational diabetes mellitus. Understanding how actual risk factors affect the perceived risk of developing T2DM can foster effective diabetes prevention interventions for this population. The aims of this study were to describe the risk, perceived and actual, of developing T2DM and to explore the influencing factors of perceived risk for Chinese mothers of preschool children in China. METHODS: A multisite, cross-sectional survey was conducted and included 176 mothers (mean age of 31.19 years old) of preschool children (aged 3-7 years old) from four preschools in Changsha, the capital city of Hunan Province, China. The overall perceived risk of developing T2DM was measured by one item "Your own personal health risk is at almost no risk, slight risk, moderate risk or high risk from diabetes" from the Risk Perception Survey for Developing Diabetes (RPS-DD). PRS-DD and the Chinese version of the Canadian Diabetes Risk Assessment Questionnaire (CHINARISK) were used to assess perceived risk related worry, personal control, optimistic bias, and diabetes risk knowledge and actual risk of T2DM. Mothers also reported their height, weight, and waist circumference followed by the NIH protocol. Pearson correlation and stepwise multivariate linear regression were used to explore how the actual risk factors affected the perceived risk of developing diabetes (RPS-DD)). RESULTS: Nearly 90% of mothers perceived almost no/slight risk for developing diabetes. Nearly half of the mothers had parents or siblings with diabetes. Roughly 70% of the mothers did not eat five servings of fruits and vegetables per day, and more than 50% did not exercise at least 30 minutes a day. In the five stepwise multivariate linear regression models, young mothers (95% CI .400-1.311) and those with a family history of diabetes (95% CI -0.74- .000) were founded a higher overall perceived risk. Mothers who reported more sedentary time (95% CI -0.029- -0.008) and less physical activity had less personal control (95% CI -0.354- -0.046). Mothers with more sedentary time had more worries about developing T2DM(95% CI 0.008-0.035) . Mothers who were older (95% CI -0.440-0.055) or had more physical activities (95% CI 0.003-0.048) had more optimistic bias of not developing T2DM. Mothers who had a higher education level (95% CI .354-1.422) and a family history of diabetes (95% CI .029-2.231) had more diabetes risk knowledge of developing T2DM. CONCLUSION: This study found that Chinese mothers of preschool children in urban areas reported low perceived risk of developing T2DM, although they have actual risk factors. These women did not associate anthropometric, health history, or health behavior factors with the risk of developing T2DM. Anthropometrics and risk factors associated with behavioral risk factors may be the focus of diabetes prevention programs.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".