A parsimonious and comprehensive screening tool for adult health behaviors

Kuo, Ya-Wen; Chang, Shu‐Ting; Huang, Cheng-Hsien; Chen, Mei‐Yen

doi:10.1111/phn.13085

Cited by 1 publication

(1 citation statement)

References 21 publications

(38 reference statements)

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“…Modifiable risk factors were assessed with a cluster of four health-promoting habits and three health-related behaviors that were based on the American Heart Association recommendations of LE-8 (2, 10) and previous studies (22)(23)(24).…”

Section: Measurementmentioning

confidence: 99%

A novel nomogram for predicting cardiometabolic diseases from modifiable risks in middle-aged adults-implication for health education

Chang,

Lin,

Lin

et al. 2024

Front. Endocrinol.

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BackgroundMiddle-aged adults often overlook critical modifiable risk factors that contribute to the emergence of cardiometabolic diseases (CMDs), including hypertension and diabetes. Many CMDs can be alleviated by addressing these modifiable risks. However, there has been insufficient research focused on rural adults with lower levels of health literacy in this regard. The aim of this study was to explore and develop an intuitive assessment tool for predicting cardiometabolic diseases (CMDs), which can be used for health education with adults of low health literacy.MethodsThis was a community-based, cross-sectional study. A structured questionnaire on health-promoting habits, smoking, sleep, and physiological biomarkers was obtained via community health screening in the coastal region of Yunlin County, Taiwan. Multivariate logistic regression was used to screen for significant variables in the nomogram construction. Analysis with nonlinear restricted cubic spline was performed.ResultsA total of 712 participants (60.9% females) aged 40–64 years, with middle school level or lower education, were included. The average age was 55.6 years (SD=7.3), and 220 individuals (31%) had CMDs. Multivariate logistic regression analysis revealed that age, lower scores of vegetables, fruit, water, and exercise (VFWE), smoking history, sleep deprivation, and being overweight were significantly associated with CMDs. The model incorporating these modifiable risk factors demonstrated good discriminatory ability, as indicated by an area under the receiver operating characteristic curve of 0.75 (0.73–0.76). A predictive nomogram was developed that presented modifiable risk factors in a simple graphical format to facilitate the prediction of CMDs.ConclusionsThis study highlights a high prevalence of CMDs among middle-aged adults, along with the disregard for important risk factors that could be modified. The developed nomogram could be a practical and effective tool for community health education to enhance health literacy and prevent the progression of CMDs.

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Section: Measurementmentioning

confidence: 99%