Is there a nonadherent subtype of hypertensive patient? A latent class analysis approach

Factors and at-risk group associated with hypertension self-management patterns among people with physical disabilities: a latent class analysis

Background

People with disabilities are vulnerable to chronic diseases such as hypertension. In South Korea, over half of the population living with a physical disability suffer from hypertension. Understanding the typology of hypertension self-management patterns will assist with behavioural interventions for people with physical disabilities. Thus, this study aims to identify the typology of hypertension self-management behavioural patterns, the factors associated with the latent classes, and to recognise potential at-risk populations by comparing potential health outcomes among hypertensive adults with physical disabilities.

Methods

Data of 1551 participants were extracted from the 2017 National Survey of Disabled Persons. Latent classes were analysed using five indicators of self-management: smoking, alcohol consumption, physical activity, diet, and weight control. Determinants of self-management patterns, such as general characteristics, health-related factors, and social relationships, were identified using multinomial logistic regression. Further, health measures, such as health profile, psychological health, and patient experience, were compared.

Results

The following three latent classes were identified: “high self-management” group (40.8%), “harmful habitual behaviour” group (20.6%), and “inactive behaviour” group (38.6%). Compared with the high self-management group, the predictors of belonging to the harmful habitual behaviour group were being male, young, and single. Being female, employed, severely disabled, dependent, and unsatisfied with friendships were predictors of the inactive behaviour group. Those in the inactive behaviour group had a poor health-related quality of life, poor subjective health, depression, and unmet medical needs.

Conclusions

This study provides evidence that there are mutually exclusive subgroups of patients with hypertension regarding self-management patterns, identifies an array of predictive factors in each latent class membership, and distinguishes a high-risk group by comparing the health measures among patients with hypertension with physical disabilities. Analysing subgroups may assist in identifying and meeting the diverse needs of self-management support in hypertensive patients with physical disabilities.

The patterns of lifestyle, metabolic status, and obesity among hypertensive Korean patients: a latent class analysis

OBJECTIVES

This study aimed to identify latent classes in hypertensive patients based on the clustering of factors including lifestyle risk factors, metabolic risk factors, and obesity in each sex.

METHODS

This cross-sectional study included 102,780 male and 103,710 female hypertensive patients who underwent health check-ups at 16 centers in Korea, in 2018. A latent class analysis approach was used to identify subgroups of hypertensive patients. Multinomial logistic regression was performed to examine the association between latent classes and comorbidities of hypertension.

RESULTS

A four-class model provided the best fit for each sex. The following latent classes were identified: Class I (male: 16.9%, female: 1.7%; high risk of lifestyle behaviors [HB] with metabolic disorders and obesity [MO]), Class II (male: 32.4%, female: 47.1%; low risk of lifestyle behaviors [LB] with MO), Class III (male: 15.3%, female: 1.8%; HB with metabolic disorders and normal weight [MNW]), Class IV (male: 35.5%, female: 49.4%; LB with MNW). Lifestyle patterns in the latent classes were classified as high-risk or low-risk according to smoking and high-risk drinking among male, and presented complex patterns including physical inactivity alone or in combination with other factors, among female. Stage 2 hypertensive or diabetic individuals were likely to belong to classes including obesity (HB-MO, LB-MO) in both sexes, and additionally belonged to the HB-MNW class in male.

CONCLUSIONS

Metabolic disorders were included in all latent classes, with or without lifestyle risk factors and obesity. Hypertensive females need to manage obesity, and hypertensive males need to manage lifestyle risk factors and obesity. Sex-specific lifestyle behaviors are important for controlling hypertension.

Distinct Profiles on Subjective and Objective Adherence Measures in Patients Prescribed Antidepressants

Objective

A recurrent observation is that associations between self-reported and objective medication adherence measures are often weak to moderate. Our aim was therefore to identify patients with different profiles on self-reported and objective adherence measures.

Study Design and Setting

This was an observational study of 221 community pharmacy patients who were dispensed antidepressants. Adherence profiles were estimated with Latent Profile Analysis (LPA) using data on self-reported adherence (Medication Adherence Rating Scale) complemented with data on medication beliefs (perceived necessity and concerns measured with the Beliefs about Medicines Questionnaire) and data from objective adherence measures (electronic monitoring of medication taking and the Medication Possession Ratio calculated from pharmacy dispensing data).

Results

‘Goodness-of-fit’ statistics indicated the presence of three classes: “concordantly high adherent” (83%, high adherence on all measures), “concordantly suboptimal adherent” (11%, low adherence on all measures), and “discordant” (6%, high self-reported adherence but lower adherence on objective measures).

Conclusion

Most patients had concordant outcomes on self-reported and objective measures of adherence. A small discordant class had high self-reported but low objective adherence. LPA will enable sensitivity analyses in future studies, for example excluding patients from the discordant class.

Identifying targets for cardiovascular medication adherence interventions through latent class analysis

OBJECTIVE

Reasons for nonadherence to cardiovascular medications vary widely between individuals. Yet, adherence interventions are often uniformly applied, limiting their effectiveness. This study employed latent class analysis (LCA) to identify multidimensional profiles of reasons for nonadherence to cardiovascular medications.

METHOD

Participants (N = 137; MAge = 58.8, SDAge = 11.8) were drawn from an observational study of the impact of cardiac-induced posttraumatic stress disorder (PTSD) on cardiac medication adherence in patients presenting to the emergency department with a suspected acute coronary syndrome. Demographics and depressive symptoms were assessed at baseline. Extent of nonadherence to cardiovascular medications, reasons for nonadherence, and PTSD symptoms were assessed 1 month after discharge.

RESULTS

LCA identified 3 classes of reasons for medication nonadherence: capacity (related to routine or forgetting; approximately 45% of the sample), capacity + motivation (related to routine/forgetting plus informational or psychological barriers; approximately 14% of the sample), and no clear reasons (low probability of endorsing any items; approximately 41% of the sample). Participants reporting greater nonadherence were more likely to be in the capacity + motivation or no clear reasons classes compared with the capacity class. Participants endorsing higher PTSD severity were more likely to be in the capacity + motivation or capacity classes compared with the no clear reasons class.

CONCLUSIONS

Three distinct classes of reasons for nonadherence were identified, suggesting opportunities for tailored interventions: capacity, capacity + motivation, and no clear reasons. These preliminary findings, if replicated, could aid identification of patients at risk for greater extent of medication nonadherence and inform tailored interventions to improve adherence. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

VA and Medicare Utilization Among Dually Enrolled Veterans with Type 2 Diabetes: A Latent Class Analysis

BACKGROUND

Many Veterans treated within the VA Healthcare System (VA) are also enrolled in fee-for-service (FFS) Medicare and receive treatment outside the VA. Prior research has not accounted for the multiple ways that Veterans receive services across healthcare systems.

OBJECTIVE

We aimed to establish a typology of VA and Medicare utilization among dually enrolled Veterans with type 2 diabetes.

DESIGN

This was a retrospective cohort.

PARTICIPANTS

316,775 community-dwelling Veterans age ≥ 65 years with type 2 diabetes who were dually enrolled in the VA and FFS Medicare in 2008-2009.

METHODS

Using latent class analysis, we identified classes of Veterans based upon their probability of using VA and Medicare diabetes care services, including patient visits, laboratory tests, glucose test strips, and medications. We compared the amount of healthcare use between classes and identified factors associated with class membership using multinomial regression.

KEY RESULTS

We identified four distinct latent classes: class 1 (53.9%) had high probabilities of VA use and low probabilities of Medicare use; classes 2 (17.2%), 3 (21.8%), and 4 (7.0%) had high probabilities of VA and Medicare use, but differed in their Medicare services used. For example, Veterans in class 3 received test strips exclusively through Medicare, while Veterans in class 4 were reliant on Medicare for medications. Living ≥ 40 miles from a VA predicted membership in classes 3 (OR 1.1, CI 1.06-1.15) and 4 (OR 1.11, CI 1.04-1.18), while Medicaid eligibility predicted membership in class 4 (OR 4.30, CI 4.10-4.51).

CONCLUSIONS

Veterans with diabetes can be grouped into four distinct classes of dual health system use, representing a novel way to characterize how patients use multiple services across healthcare systems. This classification has applications for identifying patients facing differential risk from care fragmentation.

Application of Latent Class Analysis to Identify Behavioral Patterns of Response to Behavioral Lifestyle Interventions in Overweight and Obese Adults

BACKGROUND

Examining responders and non-responders to behavioral lifestyle interventions among overweight/obese adults with additional comorbidities may aid in refining and tailoring obesity treatment.

PURPOSE

The purpose of this study is to demonstrate the use of latent class analysis to identify patterns of response to behavioral lifestyle interventions based on adherence to diet and exercise recommendations.

METHOD

Repeated measures latent class analysis was applied to two clinical trial datasets, combination of two active interventions in the PREMIER Trial (n = 501) and phase 1 of the Weight Loss Maintenance Trial (WLM; n = 1685), to identify patterns of response to behavioral lifestyle interventions. Treatment response was based on adherence to daily recommendations for fruit/vegetable, fat, saturated fat, sodium, and exercise at baseline and 6 months.

RESULTS

In PREMIER, three distinct latent classes emerged: responders (45.9%), non-responders (23.6%), and early adherers (30.5%). Responders and Early Adherers had greater weight loss at 6 and 18 months and were more likely to meet behavioral recommendations at 18 months than Non-responders. For WLM, there were four latent classes: partial responders (16%), non-responders (40%), early adherers (2%), and fruit/veggie only responders (41%). Non-responders in WLM had significantly less weight loss at 6 months compared to that of the other three latent classes.

CONCLUSION

Latent class analysis is a useful method to apply to clinical trial data to identify distinct patterns of response to behavioral interventions. Overweight/ obese participants who respond to behavioral lifestyle treatment (i.e., meet behavioral recommendations) have significantly greater weight loss than that of participants who do not make behavioral changes.

Heterogeneous demographic and cultural profiles of Chinese American patients nonadherent to colorectal cancer screening: a latent class analysis

BACKGROUND

Colorectal cancer (CRC) is one of the leading causes of cancer death in Chinese Americans, but their CRC screening rates remain low.

OBJECTIVE

We examined subgroups of Chinese American patients nonadherent to CRC screening guidelines to better inform clinical practices to effectively promote screening.

METHODS

Using latent class analysis of data from 327 participants recruited from 18 primary care clinics, we classified nonadherent patients based on sociodemographics, screening barriers, and attitudinal and clinical factors for CRC screening.

RESULTS

The best-fitting latent class analysis model described 3 distinctive classes: Western healthcare class (36%), Eastern healthcare class (18%), and mixed healthcare class (46%). Western healthcare class patients were highly educated, with average US residency of 20 years, a high level of English proficiency, the least Eastern cultural views of care, and the greatest exposure to physician recommendations, but reported having no time for screenings. Eastern healthcare class patients were highly educated seniors and recent immigrants with the least CRC knowledge and the most Eastern cultural views. Mixed healthcare class patients had low level of education, resided in the United States for 20 years, and half had sought services of their physicians for at least 3 years, but their knowledge and cultural views were similar to those of Eastern healthcare class patients.

CONCLUSIONS

Nonadherent Chinese American patients are heterogeneous. It is essential to have future intervention programs tailored to address specific screening beliefs and barriers for subtypes of nonadherent patients.

IMPLICATIONS FOR PRACTICE

Training primary care physicians to recognize patients' different demographic characteristics and healthcare beliefs may facilitate physicians' communication with patients to overcome their barriers and improve screening behaviors.