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

Identifying Clusters of Health Behaviors in a Japanese Working Population at Risk for Non-Communicable Diseases: A Latent Class Analysis of 12,168 Individuals

Introduction

Noncommunicable diseases (NCDs) have become a significant global problem. Health behaviors are associated with NCDs, and characterizing populations using a public health approach can help provide specific interventions according to their characteristics. This study aims to examine the formation of clusters of health behavior combinations in the Japanese working population at risk of NCDs, taking into account the influences of age and gender, using latent class analysis.

Methods

Participants were individuals at risk for NCDs but had not previously been diagnosed with any. Latent class analysis (LCA) was used to study clustering based on basic characteristics and health behaviors. All statistical analyses were conducted using R (Version 4.0.4) and the "poLCA" package (Version 1.6.0).

Results

This study included 12,168 participants. LCA compared models with one to six latent classes. The five-class model was determined to be the most appropriate based on Bayesian Information Criterion, Akaike Information Criterion, and G^2 values, as well as distinguishable cluster characteristics. Cluster 1: "having healthy lifestyles but disliking hospitals"; Cluster 2: "women with healthy lifestyle behaviors"; Cluster 3: "general population"; Cluster 4: "middle-aged group in need of lifestyle improvement"; Cluster 5: "a group receiving treatment for lifestyle-related diseases."

Conclusions

This study reveals discernible health behavior patterns in a sample of the Japanese population using large real-world data, suggesting the effectiveness of distinct approaches when considering a population approach to public health.

Novel Latent Profile Analysis of a Test of Concept, Stigma Intervention to Increase PrEP Uptake Among Black Sexual Minority Men

BACKGROUND

Pre-exposure prophylaxis (PrEP) has demonstrated efficacy for HIV prevention, yet uptake of PrEP among populations in urgent need of prevention tools (eg, Black sexual minority men) is limited, and stigma and medical mistrust remain strong barriers to accessing PrEP.

PURPOSE

To evaluate a test of concept brief intervention to address stigma and medical mistrust as barriers to PrEP uptake using novel latent profile analysis.

METHODS

Participants (N = 177) residing in the southeastern US were randomized to 1 of 4 arms to establish the potential impact of a brief, stigma focused counseling intervention (referred to as Jumpstart ) to increase PrEP uptake. We estimated intervention effect size (Cramer's V) for PrEP uptake and then explored differential intervention effects across latent profiles of psychosocial barriers to PrEP use.

RESULTS

The intervention resulted in small, but meaningful effect size, with self-reported PrEP uptake increasing across Jumpstart conditions with the control condition reporting 24% uptake and Jumpstart plus text/phone calls (the most intensive intervention arm) reporting 37% uptake, and a similar pattern emerging for biologically confirmed PrEP use. Among participants 30 and older, Jumpstart participants were more likely to move to a postintervention profile with fewer barriers than control participants and reported the highest uptake of PrEP.

CONCLUSIONS

Addressing social/emotional barriers to PrEP uptake is an essential component of bridging the gap between advances being made in biomedical forms of HIV prevention, and establishing and supporting access to those advances.

Trajectories of depression symptoms in a therapist-supported digital mental health intervention: a repeated measures latent profile analysis

PURPOSE

Major depression affects 10% of the US adult population annually, contributing to significant burden and impairment. Research indicates treatment response is a non-linear process characterized by combinations of gradual changes and abrupt shifts in depression symptoms, although less is known about differential trajectories of depression symptoms in therapist-supported digital mental health interventions (DMHI).

METHODS

Repeated measures latent profile analysis was used to empirically identify differential trajectories based upon biweekly depression scores on the Patient Health Questionnaire-9 (PHQ-9) among patients engaging in a therapist-supported DMHI from January 2020 to July 2021. Multivariate associations between symptom trajectories with sociodemographics and clinical characteristics were examined with multinomial logistic regression. Minimal clinically important differences (MCID) were defined as a five-point change on the PHQ-9 from baseline to week 12.

RESULTS

The final sample included 2192 patients aged 18 to 82 (mean = 39.1). Four distinct trajectories emerged that differed by symptom severity and trajectory of depression symptoms over 12 weeks. All trajectories demonstrated reductions in symptoms. Despite meeting MCID criteria, evidence of treatment resistance was found among the trajectory with the highest symptom severity. Chronicity of major depressive episodes and lifetime trauma exposures were ubiquitous across the trajectories in a multinomial logistic regression model.

CONCLUSIONS

These data indicate that changes in depression symptoms during DMHI are heterogenous and non-linear, suggesting a need for precision care strategies to address treatment resistance and increase engagement. Future efforts should examine the effectiveness of trauma-informed treatment modules for DMHIs as well as protocols for continuation treatment and relapse prevention.

Maternal depressive symptoms, attendance of sessions and reduction of home safety problems in a randomized toddler safety promotion intervention trial: A latent class analysis

Objective

Little is known about the association between maternal depressive symptoms and attendance at safety promotion interventions. This study used latent class analysis (LCA) to identify the profile of attendance within a toddler safety intervention and assessed its relation with maternal depressive symptoms at baseline and reduction of home safety problems over time, separately.

Methods

The analytic sample included 91 mothers of toddlers (mean maternal age 28.16 years) who were assigned to the safety promotion intervention group as part of a randomized trial and assessed at baseline, 6-month and 12-month follow-ups. Using LCA, we classified mothers into low and high attendance classes based on their attendance at 8 intervention sessions. We assessed maternal depressive symptoms with the Beck Depression Inventory (BDI) and home safety problems with a 9-item home safety problem observation.

Results

The mothers were classified into low attendance (45%) and high attendance classes (55%). The posterior probability of attending each session ranged from 0–0.29 for the low attendance class and 0.68–0.92 for the high attendance class. Each one unit increase of BDI sum score at baseline was associated with an 8% reduced odds of being in the high attendance class (aOR = 0.92, 95% CI: 0.86, 1.00, p = 0.037). The home safety problem score reduction was greater among high attendance class participants than low attendance class participants at the 6-month follow-up (b = -1.15, 95% CI:-2.09, -0.20, p = 0.018).

Conclusion

Maternal depressive symptoms were associated with the reduced probability of maternal attendance at toddler safety promotion sessions; high session attendance was related to greater reduction of toddler home safety problems. Identifying risk factors for maternal low attendance to interventions and developing strategies to promote attendance should lead to reductions in home safety problems and reductions in unintentional injuries among young children.

Distinguishing early patterns of physical activity goal attainment and weight loss in online behavioral obesity treatment using latent class analysis

Physical activity (PA) goal adherence is consistently associated with greater weight loss during behavioral obesity treatment, and early weight loss response predicts future weight loss success. However, it remains unclear which behaviors during the initial weeks of treatment distinguish responders from nonresponders and might be effective targets for improving treatment outcomes. To characterize subgroups with distinct patterns of PA goal adherence during the initial 2 months of an online, group-based weight control program and determine associations between these patterns and 6-month weight loss. Participants received an online behavioral obesity intervention with PA goals and daily self-monitoring. Weekly adherence to step goals and moderate-to-vigorous PA (MVPA) minute goals based on self-monitoring records were examined using latent class analysis. Body weight was objectively measured at 0, 2, and 6 months. Participants (N = 212; 91.5% female, 31.6% race/ethnic minority, mean body mass index: 35.8 ± 5.9 kg/m2) clustered into three subgroups based on early goal attainment: "Both PA Goals," "MVPA Goals Only," and "Neither PA Goal." The "Both PA Goals" class had significantly greater 6-month weight loss (estimated mean weight loss [95% CI]: -9.4% [7.4 to 11.5]) compared to the "MVPA Goals Only" (-4.8% [3.4 to 6.1]) and "Neither PA Goal" classes (-2.5% [1.4 to 3.6]). Individuals meeting both PA goals early in treatment achieve greater weight losses than those meeting MVPA but not step goals, pointing to the need to explore factors associated with nonadherence to each of the PA goals to better understand these potential targets for treatment refinement and adaptive interventions.

Latent class growth modelling for the evaluation of intervention outcomes: example from a physical activity intervention

Intervention studies often assume that changes in an outcome are homogenous across the population, however this assumption might not always hold. This article describes how latent class growth modelling (LCGM) can be performed in intervention studies, using an empirical example, and discusses the challenges and potential implications of this method. The analysis included 110 young adults with mobility disability that had participated in a parallel randomized controlled trial and received either a mobile app program (n = 55) or a supervised health program (n = 55) for 12 weeks. The primary outcome was accelerometer measured moderate to vigorous physical activity (MVPA) levels in min/day assessed at baseline, 6 weeks, 12 weeks, and 1-year post intervention. The mean change of MVPA from baseline to 1-year was estimated using paired t-test. LCGM was performed to determine the trajectories of MVPA. Logistic regression models were used to identify potential predictors of trajectories. There was no significant difference between baseline and 1-year MVPA levels (4.8 min/day, 95% CI: -1.4, 10.9). Four MVPA trajectories, 'Normal/Decrease', 'Normal/Increase', 'Normal/Rapid increase', and 'High/Increase', were identified through LCGM. Individuals with younger age and higher baseline MVPA were more likely to have increasing trajectories of MVPA. LCGM uncovered hidden trajectories of physical activity that were not represented by the average pattern. This approach could provide significant insights when included in intervention studies. For higher accuracy it is recommended to include larger sample sizes.

Use of latent class analysis as a method of assessing the physical activity level, sedentary behavior and nutritional habit in the adolescents' lifestyle: A scoping review

BACKGROUND

Currently, adolescents' lifestyle is commonly characterized by physical inactivity, sedentary behavior, and inappropriate eating habits in general. A person-oriented approach as Latent Class Analysis (LCA) can offer more insight than a variable-centered approach when investigating lifestyle practices, habits, and behaviors of adolescent population.

OBJECTIVE

The aim of the present study was to assess which variables are mostly used to represent the physical activity level, sedentary behavior SB) and nutritional habit in the adolescents' lifestyle in studies that used the LCA.

DESIGN

Scoping review.

METHODS

The study was a performed in accordance with the proposed criteria for systematic reviews and meta-analyses-Preferred Reporting Items for Systematic Reviews and Meta-Analyses and registered in PROSPERO (CRD42018108444). The original articles were searched in MEDLINE/PubMed, Scopus, ScienceDirect, Web of Science, PsycINFO, and SPORTdiscus. The Quality Assessment Tool analyzed the risk of bias of the included studies.

RESULTS

30 original articles were selected. The physical activity level (28 studies), SB and nutritional habits (18 studies) were the most common variable used to evaluate the adolescent's lifestyle by LCA model. Specifically, physical inactivity and high SB were the manifest variables with higher frequency in the negative latent classes (LCs) in adolescent girls. On the other hand, physical exercises and sports were activities more commonly labeled as positive LCs.

CONCLUSIONS

The LCA models of the most of selected studies showed that physical inactivity, high SB were the most common in the LCs with negative characteristics of the adolescents' lifestyle. Better understanding the results of analyzes of clusters of multivariate behaviors such as the LCA can help to create more effective strategies that can make the lifestyle of adolescents healthier.

Patterns of self-monitoring technology use and weight loss in people with overweight or obesity

Mobile applications and paired devices allow individuals to self-monitor physical activity, dietary intake, and weight fluctuation concurrently. However, little is known regarding patterns of use of these self-monitoring technologies over time and their implications for weight loss. The objectives of this study were to identify distinct patterns of self-monitoring technology use and to investigate the associations between these patterns and weight change. We analyzed data from a 6-month weight loss intervention for school district employees with overweight or obesity (N = 225). We performed repeated measures latent profile analysis (RMLPA) to identify common patterns of self-monitoring technology use and used multiple linear regression to evaluate the relationship between self-monitoring technology use and weight change. RMLPA revealed four distinct profiles: minimal users (n = 65, 29% of sample), activity trackers (n = 124, 55%), dedicated all-around users (n = 25, 11%), and dedicated all-around users with exceptional food logging (n = 11, 5%). The dedicated all-around users with exceptional food logging lost the most weight (X2[1,225] = 5.27, p = .0217). Multiple linear regression revealed that, adjusting for covariates, only percentage of days of wireless weight scale use (B = -0.05, t(212) = -3.79, p < .001) was independently associated with weight loss. We identified distinct patterns in mHealth self-monitoring technology use for tracking weight loss behaviors. Self-monitoring of weight was most consistently linked to weight loss, while exceptional food logging characterized the group with the greatest weight loss. Weight loss interventions should promote self-monitoring of weight and consider encouraging food logging to individuals who have demonstrated consistent use of self-monitoring technologies.

Differences in treatment response to a total diet replacement intervention versus a food-based intervention: A secondary analysis of the OPTIWIN trial

OBJECTIVE

For every weight loss treatment, there are usually groups of people who lose less than expected. This study sought to determine if response rates to a total diet replacement (TDR) differed from those of a calorie-restricted, food-based (FB) diet.

METHODS

Data from OPTIWIN, a 12-month multicenter trial in adults with a BMI of 30-55 kg/m2, with 26-week weight-loss and weight-maintenance phases, were utilized. Participants (n = 330) were randomized to the OPTIFAST programme (OP) or to a reduced-energy FB diet. Treatment non-responders were defined as those who lost <3% of initial weight at months 6 or 12.

RESULTS

There were 103 (76%) responders in the OP compared with 78 (57%) in the FB group at 12 months. The odds of treatment response at 12 months among participants who were non-responders at 3 months was not significantly different between the OP and FB groups (p = 0.64). Race, type 2 diabetes status and previous weight loss attempts were significantly associated with responder status. OP responders had higher meal plan adherence and non-caloric fluid intake compared with FB responders.

CONCLUSION

Early treatment response is more likely and better sustained with TDR compared with an FB diet. Individual and treatment level factors appear to influence early treatment response to behavioural interventions for weight reduction.

Differential Health Care Use, Diabetes-Related Complications, and Mortality Among Five Unique Classes of Patients With Type 2 Diabetes in Singapore: A Latent Class Analysis of 71,125 Patients

OBJECTIVE

With rising health care costs and finite health care resources, understanding the population needs of different type 2 diabetes mellitus (T2DM) patient subgroups is important. Sparse data exist for the application of population segmentation on health care needs among Asian T2DM patients. We aimed to segment T2DM patients into distinct classes and evaluate their differential health care use, diabetes-related complications, and mortality patterns.

RESEARCH DESIGN AND METHODS

Latent class analysis was conducted on a retrospective cohort of 71,125 T2DM patients. Latent class indicators included patient's age, ethnicity, comorbidities, and duration of T2DM. Outcomes evaluated included health care use, diabetes-related complications, and 4-year all-cause mortality. The relationship between class membership and outcomes was evaluated with the appropriate regression models.

RESULTS

Five classes of T2DM patients were identified. The prevalence of depression was high among patients in class 3 (younger females with short-to-moderate T2DM duration and high psychiatric and neurological disease burden) and class 5 (older patients with moderate-to-long T2DM duration and high disease burden with end-organ complications). They were the highest tertiary health care users. Class 5 patients had the highest risk of myocardial infarction (hazard ratio [HR] 12.05, 95% CI 10.82-13.42]), end-stage renal disease requiring dialysis initiation (HR 25.81, 95% CI 21.75-30.63), stroke (HR 19.37, 95% CI 16.92-22.17), lower-extremity amputation (HR 12.94, 95% CI 10.90-15.36), and mortality (HR 3.47, 95% CI 3.17-3.80).

CONCLUSIONS

T2DM patients can be segmented into classes with differential health care use and outcomes. Depression screening should be considered for the two identified classes of patients.

Approach bias modification training to increase physical activity: A pilot randomized controlled trial in healthy volunteers

Regular physical activity is associated with better physical and mental health outcomes as well as higher quality of life. This pilot randomized controlled trial examined whether approach bias modification, an economical and easily accessible computerized cognitive training, could increase objectively and subjectively measured physical activity in individuals aiming for more physical activity. Forty healthy volunteers of normal weight were randomly allocated to six sessions of approach bias modification or no treatment. The approach bias modification adopted an implicit learning paradigm that trained participants to show approach behavior in response to visual cues of physical activity. Approach bias modification did not increase objectively and subjectively measured physical activity.

Adherence to behavioral recommendations for weight loss and associated psychosocial factors among African American adults

PURPOSE

To identify patterns of behavioral adherence among 388 African Americans who participated in the Weight Loss Maintenance trial and examine associated psychosocial factors.

METHODS

Using repeated measures latent class analysis, we modeled patterns of adherence to recommendations regarding fruit and vegetable, total fat, and saturated fat intake and physical activity at baseline, 6, and 18 months. Latent classes were compared on the SF-36 (mental health composite and vitality subscale), Perceived Stress Scale, and PHQ-8 at each time point.

RESULTS

Three distinct latent classes emerged: Nutrition Adherers (n = 96); Physical Activity Adherers (n = 61); and Non-Adherers (n = 231). All groups showed initial improvement in psychosocial measures followed by relapse. Non-Adherers had significantly lower mean mental health and vitality scores and higher depression scores than adherers at 6 and 18 months.

CONCLUSION

Psychological well-being should be addressed with African Americans in weight loss treatment to enhance behavior change and improve weight loss outcomes.

Is There a Spillover Effect of Targeted Dietary Change on Untargeted Health Behaviors? Evidence From a Dietary Modification Trial

Background. The gateway behavior hypothesis posits that change in a health behavior targeted for modification may promote positive changes in other untargeted health behaviors; however, previous studies have shown inconsistent results. Aims. To examine the patterns and predictors of change in untargeted health behaviors in a large health behavior change trial. Method. Using repeated-measures latent class analysis, this study explored patterns of change in untargeted physical activity, alcohol consumption, and smoking behavior during the first year of the Women's Health Initiative dietary modification trial that targeted total fat reduction to 20% kcal and targeted increased fruit and vegetable intake. Participants were healthy postmenopausal women who were randomly assigned to either the low-fat dietary change intervention (n = 8,193) or a control (n = 12,187) arm. Results. Although there were increases in untargeted physical activity and decreases in alcohol consumption and smoking in the first year, these changes were not consistently associated with study arm. Moreover, although the results of the repeated-measures latent class analysis identified three unique subgroups of participants with similar patterns of untargeted health behaviors, none of the subgroups showed substantial change in the probability of engagement in any of the behaviors over 1 year, and the study arms had nearly identical latent class solutions. Discussion and Conclusion. These findings suggest that the dietary intervention did not act as a gateway behavior for change in the untargeted behaviors and that researchers interested in changing multiple health behaviors may need to deliberately target additional behaviors.

Evaluation of lifestyle of female adolescents through latent class analysis approach

BACKGROUND

Lack of regular physical activity, high sedentary behavior and presence of unbalanced alimentary practices are attitudes associated with an inadequate lifestyle among female adolescents.

OBJECTIVE

to assess the lifestyle of female adolescents based on measurements of behavioral variables.

METHODS

Cross-sectional study with 405 female adolescents between 14 and 19 years old, resident and attending public schools in Viçosa (state of Minas Gerais). Their lifestyle was analyzed by the Physical Activity Recall, number of steps, screen time (ST), cellphone time (CT), sitting time, food frequency questionnaire (FFQ), and alcohol and tobacco consumption. With multiple correspondence analysis it was possible to observe dispersion and approximation of the variables' categories. Latent class analysis (LCA) was used for modeling the "lifestyle" variable, having been conducted in the poLCA (Polychromous Variable Latent Class Analysis) package of the R statistical software.

RESULTS

The mean age was 15.92 ± 1.27 years. Most of the adolescents were considered physically inactive (78%) and with low number of steps (82.57%); 41.45% reported not performing Moderate to Vigorous Physical Activities (MVPA) adequately. Sedentary behavior was found high when assessing ST (72.90%) and CT (65.31%). It was found the best fitted latent class model for the lifestyle (p-G2 = 0.055, p-χ2 = 0.066) featured three latent classes and one covariate (alcohol): Class 1, 'Inactive and Sedentary' (γ = 77.5%); Class 2, 'Inactive and Non-sedentary lifestyle (γ=16.31%); and Class 3, 'Active and sedentary' (γ=6.19%). Female adolescents that had 'never consumed alcohol' were 2.26 times as likely (log OR = 0.8174; p = 0.033) to belong to class 3 (Active & Sedentary lifestyle) than to class 1 (Inactive & Sedentary lifestyle).

CONCLUSION

Latent class analysis model with five manifest variable (MVPA, number of steps, ST, sitting time and number of meals) and alcohol consumption like covariate showed itself to be an accurate and objective method in the assessment of female adolescents' lifestyle. Female adolescents that had 'never consumed alcohol' were more as likely to belong to class 'Active & Sedentary lifestyle' than to class Inactive & Sedentary lifestyle. An inactive and sedentary lifestyle is coupled to other unhealthy behaviors during adolescence, possibly carrying over into adult life.

Validation of the Diet Satisfaction Questionnaire: a new measure of satisfaction with diets for weight management

Objective

The Diet Satisfaction Questionnaire was developed to fill the need for a validated measure to evaluate satisfaction with weight‐management diets. This paper further develops the questionnaire, examining the factor structure of the original questionnaire, cross‐validating a revised version in a second sample and relating diet satisfaction to weight loss during a 1‐year trial.

Methods

The 45‐item Diet Satisfaction Questionnaire (DSat‐45) uses seven scales to assess characteristics that influence diet satisfaction: Healthy Lifestyle, Convenience, Cost, Family Dynamics, Preoccupation with Food, Negative Aspects, and Planning and Preparation. It was administered five times during a 1‐year weight‐loss trial (n = 186 women) and once as an online survey in a separate sample (n = 510 adults). Confirmatory factor analysis was used to assess and refine the DSat‐45 structure, and reliability and validity data were examined in both samples for the revised questionnaire, the DSat‐28. Associations were examined between both DSat questionnaires and weight loss in the trial.

Results

Internal consistency (reliability) was moderate for the DSat‐45. Confirmatory factor analysis showed improved fit for a five‐factor structure, resulting in the DSat‐28 that retained four of the original scales and a shortened fifth scale. This revised questionnaire was reliable in both samples. Weight loss across the year‐long trial was positively related to satisfaction with Healthy Lifestyle, Preoccupation with Food, and Planning and Preparation in both versions of the questionnaire.

Conclusions

Measures of reliability and validity were improved in the more concise DSat‐28 compared to the DSat‐45. This shorter measure should be used in future work to evaluate satisfaction with weight‐management diets.

CKD Self-management: Phenotypes and Associations With Clinical Outcomes

BACKGROUND

To slow chronic kidney disease (CKD) progression and its complications, patients need to engage in self-management behaviors. The objective of this study was to classify CKD self-management behaviors into phenotypes and assess the association of these phenotypes with clinical outcomes.

STUDY DESIGN

Prospective cohort study.

SETTING & PARTICIPANTS

Adults with mild to moderate CKD enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study. 3,939 participants in the CRIC Study recruited between 2003 and 2008 served as the derivation cohort and 1,560 participants recruited between 2013 and 2015 served as the validation cohort.

PREDICTORS

CKD self-management behavior phenotypes.

OUTCOMES

CKD progression, atherosclerotic events, heart failure events, death from any cause.

MEASUREMENTS

Latent class analysis stratified by diabetes was used to identify CKD self-management phenotypes based on measures of body mass index, diet, physical activity, blood pressure, smoking status, and hemoglobin A1c concentration (if diabetic); Cox proportional hazards models.

RESULTS

3 identified phenotypes varied according to the extent of implementation of recommended CKD self-management behaviors: phenotype I characterized study participants with the most recommended behaviors; phenotype II, participants with a mixture of recommended and not recommended behaviors; and phenotype III, participants with minimal recommended behaviors. In multivariable-adjusted models for those with and without diabetes, phenotype III was strongly associated with CKD progression (HRs of 1.82 and 1.49), death (HRs of 1.95 and 4.14), and atherosclerotic events (HRs of 2.54 and 1.90; each P < 0.05). Phenotype II was associated with atherosclerotic events and death among those with and without diabetes.

LIMITATIONS

No consensus definition of CKD self-management; limited to baseline behavior data.

CONCLUSIONS

There are potentially 3 CKD self-management behavior phenotypes that distinguish risk for clinical outcomes. These phenotypes may inform the development of studies and guidelines regarding optimal self-management.

Clinical Trajectories, Healthcare Resource Use, and Costs of Diabetic Nephropathy Among Patients with Type 2 Diabetes: A Latent Class Analysis

INTRODUCTION

Patients with type 2 diabetes mellitus (T2DM) are clinically heterogeneous in terms of disease severity, treatment, and comorbidities, potentially resulting in differential diabetic nephropathy (DN) progression courses. In this exploratory study we used latent class analysis (LCA) to identify patient groups with distinct clinical profiles of T2DM severity and explored the association between disease severity, DN progression or reversal, and healthcare resource use (HRU) and costs.

METHODS

Latent class analysis was used to group adults with ≥  2 medical claims with a diagnosis of T2DM and ≥ 2 urine albumin tests within the Truven MarketScan database (2004-2014), based on T2DM-related complications, comorbidities, and therapies. DN severity categories (normoalbuminuria, moderately increased albuminuria, and severely increased albuminuria) were determined based on urine albumin measure. The risks of DN progression and reversal (change to a more/less severe DN category) were compared among all identified latent classes using Kaplan-Meier analyses and log-rank tests. All-cause and DN-related costs and HRU were assessed and compared during the study period among the identified latent classes.

RESULTS

Four clinically distinct profiles were identified among the 23,235 eligible patients: low comorbidity/low treatment (46.5%), low comorbidity/high treatment (29.0%), moderate comorbidity/high insulin use (9.7%), and high comorbidity/moderate treatment (14.8%). The 5-year DN progression rates for these clinically distinct profiles were 11.8, 18, 16.5, and 27.7%, respectively. Compared with the low comorbidity/low treatment group, all other groups were associated with an increased risk of DN progression (all p < 0.001). Increasing comorbidity was significantly associated with higher all-cause and DN-related HRU and costs, primarily driven by higher pharmacy and inpatient costs.

CONCLUSION

Patients with T2DM who have more comorbidities experienced higher rates of DN progression and HRU and incurred higher healthcare costs compared with patients with low comorbidity profiles. Future prospective studies are needed to confirm the significance of these groups on DN progression, HRU, and costs.

FUNDING

Takeda Development Center Americas, Inc.

Predictors of Long-Term Adherence to Multiple Health Behavior Recommendations for Weight Management

BACKGROUND

We have demonstrated previously that patterns of behavioral adherence in the first 6 months of behavioral lifestyle interventions were associated with significant weight loss at 18 months. In this article, we extend this work to examine patterns of behavioral adherence over 18 months and to explore baseline demographic and psychosocial predictors.

METHOD

Latent class analysis was applied separately to the Weight Loss Maintenance and PREMIER trials data to examine patterns of adherence to the following recommendations: (1) consuming ≥9 servings of fruits and vegetables per day, (2) ≤25% of energy from total fat, (3) ≤7% energy from saturated fat, and (4) ≥180 minutes of moderate-to-vigorous physical activity per week. Multinomial logistic regression was used to test demographic and psychosocial predictors of latent class membership.

RESULTS

Four distinct subgroups with common patterns of behavioral adherence were identified in each trial including, Behavioral Maintainers, who maintained adherence to all behavioral recommendations for 1 year, Nonresponders, who did not adhere to the recommendations at any time point, and latent classes that reflected patterns of adherence to one or two behaviors or behavioral relapse. A significantly higher proportion of Behavioral Maintainers sustained ≥5% weight loss for 1 year compared with Nonresponders. Participants with higher vitality scores at baseline were more likely to belong to a latent class with long-term adherence to one or more recommendations than the Nonresponders class.

CONCLUSIONS

Regular assessment of health behaviors and psychosocial measures such as vitality may help identify nonresponders and inform treatment tailoring to improve long-term behavioral and weight outcomes.

Identifying Patterns of Lifestyle Behaviors among People with Type 2 Diabetes in Tianjin, China: A Latent Class Analysis

INTRODUCTION

Lifestyle behaviors are essential elements of diabetes care. The aims of this study were to identify distinct subgroups of people with type 2 diabetes based on personal levels of lifestyle behaviors and explore the different characteristics across these subgroups.

METHODS

In 2015 and 2016, 1504 outpatients with a diagnosis of type 2 diabetes were selected via two-stage simple random sampling from 10 municipal district hospitals in Tianjin. Participants accepted an invitation by experienced physicians to complete a questionnaire containing demographic and lifestyle content. Clinical data were collected by reviewing medical records. Latent class analysis was applied to identify patterns of lifestyle behaviors. Multinomial logistic regression was used to investigate the characteristics of the subgroups.

RESULTS

The final model yielded a four-class solution: the healthy behavioral group, unhealthy diet and less activity group, smoking and drinking group, and sedentary and extremely inactive group. Further analysis found that variables, including age, sex, general/central obesity, treatment modalities, glycemic control, diabetes duration, and diabetes-related complications and comorbidities, were disproportionately distributed across the four latent classes (P < 0.05). Participants in the unhealthy diet and less activity group were more likely to have a longer duration of diabetes, poor glycemic control and more diabetes-related diseases relative to the other three latent classes.

CONCLUSIONS

Identification and characterization of subgroups based on lifestyle behaviors in individuals with type 2 diabetes can help health care providers to shift to targeted intervention strategies.

Adaptive Interventions in Child and Adolescent Mental Health

The treatment or prevention of child and adolescent mental health (CAMH) disorders often requires an individualized, sequential approach to intervention, whereby treatments (or prevention efforts) are adapted over time based on the youth's evolving status (e.g., early response, adherence). Adaptive interventions are intended to provide a replicable guide for the provision of individualized sequences of interventions in actual clinical practice. Recently, there has been great interest in the development of adaptive intervenions by investigators working in CAMH. The development of such replicable, real-world, individualized sequences of decision rules to guide the treatment or prevention of CAMH disorders represents an important "next step" in interventions research. The primary purpose of this special issue is to showcase some recent work on the science of adaptive interventions in CAMH. In this overview article, we review why individualized sequences of interventions are needed in CAMH, provide an introduction to adaptive interventions, briefly describe each of the articles included in this special issue, and describe some exciting areas of ongoing and future research. A hopeful outcome of this special issue is that it encourages other researchers in CAMH to pursue creative and significant research on adaptive interventions.

Managing temptation in obesity treatment: A neurobehavioral model of intervention strategies

Weight loss outcomes in lifestyle interventions for obesity are primarily a function of sustained adherence to a reduced-energy diet, and most lapses in diet adherence are precipitated by temptation from palatable food. The high nonresponse and relapse rates of lifestyle interventions suggest that current temptation management approaches may be insufficient for most participants. In this conceptual review, we discuss three neurobehavioral processes (attentional bias, temporal discounting, and the cold-hot empathy gap) that emerge during temptation and contribute to lapses in diet adherence. Characterizing the neurobehavioral profile of temptation highlights an important distinction between temptation resistance strategies aimed at overcoming temptation while it is experienced, and temptation prevention strategies that seek to avoid or minimize exposure to tempting stimuli. Many temptation resistance and temptation prevention strategies heavily rely on executive functions mediated by prefrontal systems that are prone to disruption by common occurrences such as stress, insufficient sleep, and even exposure to tempting stimuli. In contrast, commitment strategies are a set of devices that enable individuals to manage temptation by constraining their future choices, without placing heavy demands on executive functions. These concepts are synthesized in a conceptual model that categorizes temptation management approaches based on their intended effects on reward processing and degree of reliance on executive functions. We conclude by discussing the implications of our model for strengthening temptation management approaches in future lifestyle interventions, tailoring these approaches based on key individual difference variables, and suggesting high-priority topics for future research.