Predicting Lifestyle Patterns among Hypertension Patients: A Latent-Class Analysis
Abstract
Background: Hypertension remains one of the most important preventable risk
factors for diseases and death. Identifying clustered patterns of modifiable
lifestyle risk factors for hypertension and demographics factors related to these
clustered patterns allows for targeting health prevention interventions. Therefore,
this study aims to identify latent classes of hypertensive patients’ lifestyle risk
factors based on the clustering of four modifiable lifestyle risk factors: eating,
physical activity patterns, smoking habits, and blood pressure control.
Methods: this study is a cross-sectional study. a total of 750 patients with
diagnosed hypertension in Takab’s urban and rural primary health care centers
were recruited randomly from August 2016 to February 2017. The standardized
questionares including frequency food questionnaire ans international physical
activity questionnaire were used in this study. In order to explain the clusters
demographic information (age, gemder, body mass index, systolic blood pressure,
diastolic blood pressure and taking the blood pressure medicines) were
ghathererd. The simple random sampling proceed. Latent class analysis was
performed by using proc LCA in SAS 9.2.Background: Hypertension remains one of the most important preventable risk
factors for diseases and death. Identifying clustered patterns of modifiable
lifestyle risk factors for hypertension and demographics factors related to these
clustered patterns allows for targeting health prevention interventions. Therefore,
this study aims to identify latent classes of hypertensive patients’ lifestyle risk
factors based on the clustering of four modifiable lifestyle risk factors: eating,
physical activity patterns, smoking habits, and blood pressure control.
Methods: this study is a cross-sectional study. a total of 750 patients with
diagnosed hypertension in Takab’s urban and rural primary health care centers
were recruited randomly from August 2016 to February 2017. The standardized
questionares including frequency food questionnaire ans international physical
activity questionnaire were used in this study. In order to explain the clusters
demographic information (age, gemder, body mass index, systolic blood pressure,
diastolic blood pressure and taking the blood pressure medicines) were
ghathererd. The simple random sampling proceed. Latent class analysis was
performed by using proc LCA in SAS 9.2.Results: Three classes of lifestyle patterns were identified. About 14.4% of
hypertensive patients were categorized in a low-risk class (I), 54.6% in an
intermediate-risk class (II), and 31% in a high-risk class (III) of lifestyle. A one- ع
year increase in age significantly increases the risk of membership in classes II
and III. Similarly, being widowed or divorced increases the risk of membership in
classes II and III. Also, having a higher education level decreases the risk of
membership in classes II and III.
Conclusion: This study contributes to the literature on lifestyle behaviors among
older adults and provides evidence that there are considerable differences in
lifestyle behaviors between subgroups of older adult patients. The three profiles of
hypertensive patients’ conditions suggest that because behaviors often occur
simultaneously within an individual level, a latent-class approach helps cluster cooccurrence risk behaviors and focuses on interventions targeted to several healthy
behaviors among high-risk patients.