Latent Growth Mixture Modeling Research Articles

LATER-LIFE TRAJECTORIES OF MARITAL QUALITY FOR WOMEN AND MEN

Abstract It is essential to better understand older adults’ marital dynamics, as marital quality is consequential for older adults’ physical and mental health, relationships with other social network members, and risk of divorce. Although numerous studies examine marital quality during the early life course, much less is known about later life trajectories. Earlier work suggested marital quality followed a U-shaped curve, characterized by a later-life upswing, but more recent research finds patterns of stability or decline over time. Gender differences in marital quality are well established, but it is less clear whether older men and women experience different marital quality trajectories during later life. We use nationally-representative data from a sample of continuously-married adults over age 50 in the Health and Retirement Study (n=2,175) with measures of both positive and negative marital quality at three time points (2006, 2010, and 2014). Latent growth mixture models in Mplus estimate trajectories of marital quality over the eight-year time period. Results show small declines in both positive (b = -0.016, p < 0.05) and negative (b = -0.028, p < 0.05) marital quality over the observation period, but the declines in positive marital quality are limited to those in remarriages. Women have lower initial positive marital quality and higher initial negative marital quality than men, but there are no significant gender differences in change over time. Results support the stability and continuous-decline patterns of marital quality over the life course rather than a U-shaped curve, and suggest persistence of gender differences over time.

FRAILTY TRAJECTORIES AMONG WORLD TRADE CENTER GENERAL RESPONDERS

Abstract As the WTC cohort ages, it is important to examine whether there are differences in frailty trajectories over time in the cohort and examine clinical risk profiles of subpopulations with different trajectories. We used longitudinal data collected annually from the WTC data center and included all individuals with 3+ Clinical Frailty Index (FI) measurements after 9/11 to examine frailty trajectories using latent class growth mixture models. These patterns of change of Clinical-FI all showed an increasing trend over time, but there were three distinct patterns with different rates of increase. These were associated with distinct profiles of characteristics including sociodemographic, occupational and exposure level. WTC responders with higher age, working in construction, and higher-intermediate WTC level of exposure had higher rate of increase of Clinical-FI over time. While WTC responders with younger age, working in protective environment, and with higher education had lower rate of increase of Clinical-FI over time.

Multiple pathways of integration: Acculturative change and associations with school adjustment in immigrant-origin adolescents.

Tracing developmental pathways of immigrant-origin adolescents, this 3-year longitudinal study (2012-2015) examined within-person changes in cultural orientations and their consequences for school adjustment. Multivariate latent growth mixture modeling confirmed multiple pathways of integration, revealing variable acculturative changes along dual trajectories of heritage and mainstream orientations among European-origin (N=592, Mage =14.45, 55.1% boys) and Turkish- and Moroccan-origin adolescents (N=1269, Mage =14.70, 53.1% boys). Two trajectories for European-origin adolescents differed in heritage orientations (high decreasing and low increasing); for Turkish- and Moroccan-origin adolescents, three trajectories differed in mainstream orientations (high stable, low increasing, and high decreasing). Acculturative change affected aspects of later school adjustment: European-origin adolescents in high heritage orientation trajectories reported more belonging and emotional engagement; Turkish- and Moroccan-origin adolescents in high mainstream orientation trajectories reported more behavioral engagement.

Modelling trajectories of change in psychopathology and well-being during eating disorder outpatient treatment

Objective: There are considerable differences in how eating disorder (ED) patients respond to treatment. This study aimed to identify change trajectories of mental health during treatment. Method: Longitudinal data of 442 patients was used with five time points during a year of outpatient treatment. ED psychopathology and well-being were used as primary measures. A series of latent growth mixture models were applied to model trajectories of change. Results: Three latent classes were found for ED psychopathology and well-being. For ED psychopathology, a high baseline severity and slow recovery class (55.9% of the patients), a high baseline severity followed by a substantial recovery class (19.9%) and a moderate baseline severity and no significant recovery class (24.2%) were found. For well-being, a low baseline followed by a slow growth class (44.6%), a low baseline and substantial growth class (9.5%) and a moderate and stable well-being class (45.9%) was found. General psychopathology, early symptom change, hope for recovery, intrinsic motivation and the ED type were predictive of class membership in either ED psychopathology or well-being. Conclusions: This study shows variability in ED psychopathology and well-being change trajectories, modelled in meaningful latent recovery classes. These results may have clinical implications, such as adjusting patients’ treatment based on change trajectories.

Associations between household solid fuel use and activities of daily living trajectories: A nationwide longitudinal study of middle and older adults in China

BackgroundMore studies focus on reporting the effects of ambient air pollution on physical activity while ignoring the hazards of indoor air pollution caused by household solid fuel use. Moreover, the impact of individual cognitive and depressive status on the health effects of air pollution is often overlooked. ObjectiveWe examined the association between household solid fuel and activities of daily living (ADL) trajectories, and further examined this association in homogeneous subgroups of cognitive or depressive trajectories. MethodsParticipants were from the China Health and Retirement Longitudinal Study, which conducted four waves of surveys from 2011 to 2018. We collected information on participants' household fuel use, then the ADL, cognitive and depressive performances were assessed in each wave. The latent growth mixture model (LGMM) was used to identify the optimal trajectory class for ADL, cognition, and depression. Then, the multinomial logistic regression was used to assess the association between solid fuel use and ADL trajectories in total population, as well as subgroups with different cognitive or depression trajectories. Furthermore, we examined the association between switching household fuel types and ADL trajectories across the four-wave survey. ResultsThe study sample included 7052 participants. We identified three ADL trajectory classes in total population: “Low-stable”, “Moderate-anterior rise”, and “Moderate-posterior rise”. The multinomial logistic regression results showed that solid fuel use was associated with elevated odds for the adverse ADL trajectories, and this association was still shown in homogeneous subgroups of cognitive or depressive trajectories, while some effects were less significant. In addition, the risk of adverse ADL trajectories generally increases with the times of solid fuel use across the four-wave survey. ConclusionsFor middle and older adults in China, household solid fuel use was not conducive to physical activity development, which inspires that a further transformation to cleaner fuels is an important intervention.

Head and Neck Symptom Severity (HNSS) and Health-Related Quality of Life (HRQL) Trajectories during and after Chemoradiotherapy (CRT) for HPV-Associated Oropharyngeal Cancer (HPVOPC): A TROG 12.01 Secondary Analysis

<h3>Purpose/Objective(s)</h3> This secondary analysis aimed to identify HNSS and HRQL trajectories during and following CRT for HPVOPC. <h3>Materials/Methods</h3> All 182 evaluable TROG 12.01 patients were included. HNSS was assessed with the MDASI-HN (range 0-10) at baseline (BL), weekly during CRT (weeks (w) 1-7) and then 1, 3, 5, 9 and 13w and 6, 12 and 24 months (m) post CRT. HRQL was assessed using the FACT-G (range 0-108) at BL, and 7w, 6m, 12m and 24m post CRT. Latent class growth mixture modelling (LCMM) was performed to identify trajectories. Mean estimates and 95% confidence intervals (CI) were calculated at each time point. <h3>Results</h3> The HNSS model identified 4 trajectory classes (HNSS1-4) distinguished by differences in HNSS at BL, during the peak of treatment symptoms (w7 CRT/1w post CRT) and during early (1w to 9w post CRT) and intermediate recovery (9w to 12m post CRT). The trajectories of all 4 classes were stable beyond 12m. The reference trajectory (HNSS4, n=74) score was 0.1 (CI 0.1-0.2) at BL, peaking at 4.6 (CI 4.2-5.0), with rapid early recovery (1.1, CI 0.8-2.2) and gradual improvement to 12m (0.6, CI 0.5-0.8). HNSS2 ("high BL", n=30) reported higher BL scores (1.4, CI 0.8-2.0) but was otherwise similar, HNSS3 ("low acute", n=53) reported reduced acute symptoms (2.5, CI 2.2-2.9) with stable scores beyond 9w post CRT (1.1, CI 0.9-1.4). HNSS1 ("slow recovery", n=25) had slower recovery from an acute peak of 4.9 (CI 4.3-5.6) to 0.9 (CI 0.6-1.3) at 12m. Compared to HNSS4, the high BL group were younger (mean 53.6 vs 57.4), with fewer ECOG0 (87 vs 99%) or with higher degree (38 vs 69%), and higher baseline anxiety (HADS, mean 6.8 vs 4.4). The low acute group were older (mean 60.1), had fewer ECOG0 patients (87%) and were more likely to have received cetuximab (68% vs 43%). The slow recovery group had fewer with a higher degree (52%). The HRQL model included 2 trajectory classes. The reference trajectory (HRQL2, n=156) scores were 90 (CI 88-92) at BL, similar 7w post CRT (88, CI 85-90) with slow but clinically meaningful improvement to 12m (98, CI 96-100). HRQL1 (n=26) had lower BL mean scores (80, CI 74-86), with a significant decline at 7w post CRT (57, CI 50-63) and a slower recovery to BL scores over 12m (83, CI 72-94). Both trajectories were flat beyond 12m. The slow recovery group were older (mean 61.1 vs 56.8), with worse BL anxiety (mean 6.5 vs 4.4) and depression (mean 4.5 vs 2.1). In addition, LCMM identified 4 trajectories for head and neck symptom interference, 3 for anxiety and 4 for depression, which will be presented. <h3>Conclusion</h3> LCMM identified distinct trajectories of HNSS and HRQL during and after CRT. These and their associations with variations in HPVOPC patients' characteristics and treatment factors provide clinically relevant insights into identifying patients who may require increased support during and after CRT.

BMI Trends for Veterans Up to 10 Years After VA Enrollment Following Military Discharge.

BackgroundObesity (body mass index [BMI]≥30kg/m2) among US adults has tripled over the past 45 years, but it is unclear how this population-level weight change has occurred.ObjectiveWe sought to identify distinct long-term BMI trajectories and examined associations with demographic and clinical characteristics.DesignThe design was latent trajectory modeling over 10 years of a retrospective cohort. Subgroups were identified via latent class growth mixture models, separately by sex. Weighted multinomial logistic regressions identified factors associated with subgroup membership.ParticipantsParticipants were a retrospective cohort of 292,331 males and 62,898 females enrolled in VA.Main MeasuresThe main outcome measure was 6-month average VA-measured BMI over the course of 10 years. Additional electronic health record measures on demographic, clinical, and services utilization characteristics were also used to characterize latent trajectories.Key ResultsFour trajectories were identified for men and for women, corresponding to standard BMI categories “normal weight” (BMI <25), “overweight” (BMI 25-29.99), and “with obesity” (BMI ≥30): “normal weight” and increasing (males: 28.4%; females: 22.8%), “overweight” and increasing (36.4%; 35.6%), “with obesity” and increasing (33.6%; 40.0%), and “with obesity” and stable (males: 1.6%) or decreasing (females: 1.6%). Race, ethnicity, comorbidities, mental health diagnoses, and mental health service utilization discriminated among classes.ConclusionsBMI in the 10 years following VA enrollment increased modestly. VA should continue prioritizing weight management interventions to the large number of veterans with obesity upon VA enrollment, because the majority remain with obesity.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11606-022-07818-5.

Longitudinal exposure to neighborhood poverty and obesity risk in emerging adulthood

This study uses data from the longitudinal Panel Study of Income Dynamics data and its Transition to Adulthood (TA) Study (2005–2017), in conjunction with decades of neighborhood-level data from the U.S. decennial census and American Community Survey, to examine the relationship between individuals’ neighborhood poverty exposure trajectories in childhood and the likelihood of obesity in emerging adulthood. Latent growth mixture models reveal that exposure to neighborhood poverty differs considerably for white and nonwhite individuals over their childhood life course. Durable exposure to neighborhood poverty confers greater subsequent obesity risks in emerging adulthood than transitory experiences of neighborhood poverty. Racial differences in the changing and persistent trajectories of neighborhood poverty help explain part of the racial differences in obesity risks. Among nonwhites, and compared to consistent nonpoor neighborhood conditions, both durable and transitory neighborhood poverty exposures are significantly associated with higher obesity risks. This study suggests that a theoretical framework that integrates key elements of the life-course perspective is helpful to uncover the individual and structural pathways through which neighborhood histories in poverty shape population health in general.

Patient reported outcomes measures (PROMs) trajectories after elective hip arthroplasty: a latent class and growth mixture analysis

BackgroundPatient-reported outcome measures (PROMs) are an extensively used tool to assess and improve the quality of healthcare services. PROMs can be related to individual demographic and clinical characteristics in patients undergoing hip arthroplasty (HA). The aim of this study is to identify distinct subgroups of patients with unique trajectories of PROMS scores and to determine patients’ features associated with these subgroups.MethodsWe conducted a prospective, cohort study in which PROMs questionnaires (Euro Quality 5 Dimensions 3L, EQ-5D-3L, Euro-Quality-Visual-Analytic-Score, EQ-VAS, Hip disability and Osteoarthritis Outcome Score, HOOS-PS) were administered to patients undergoing elective HA pre-operatively, and at 6 and 12 months after surgery. For each measure, latent class growth analysis and growth mixture models were used to identify subgroups of patients with distinct trajectories of scores. Demografic and clinical predictors of the latent classes in growth mixture model were identified using a 3-step approach.ResultsWe found three distinct trajectories for each PROM score. These trajectories indicated a response heterogeneity to the HA among the patients (n = 991). Patient’s gender, ASA score, and obesity were significantly associated with different PROMs trajectories.ConclusionsWe identified three distinct trajectories for each of the three PROMs indicators. Several demographic and clinical characteristics are associated with the different trajectories of PROMs at 6 and 12 months after HA and could be used to identify groups of patients with different outcomes following HA surgery. These findings underline the importance of patient-centered care, supporting the usefulness of integrating PROMs data alongside routinely collected healthcare records for guiding clinical care and maximizing patients’ positive outcomes.Trial registration: Protocol version (1.0) and trial registration data are available on the platform www.clinicaltrial.gov with the identifier NCT03790267, posted on December 31, 2018.

Trajectories of Depressive Symptoms Among Older Adults and in Adults With Hip Fracture: Analysis From the English Longitudinal Study of Ageing.

This study aimed to determine trajectories of depressive symptoms among older adults in England, overall and for those with hip fracture. The study aimed to explore the differential characteristics of each trajectory identified. Analysis of adults aged 60 years or more (n = 7 050), including a hip fracture subgroup (n = 384), from the English Longitudinal Study of Ageing. Latent class growth mixture modeling was completed. Depressive symptom prevalence was estimated at baseline. Chi-square tests were completed to compare baseline characteristics across trajectories. Three trajectories of depressive symptoms (no, mild, and moderate-severe) were identified overall and for those with hip fracture. The moderate-severe trajectory comprised 13.7% and 7% of participants for overall and hip fracture populations, respectively. The proportion of participants with depressive symptoms in the moderate-severe trajectory was 65.4% and 85.2% for overall and hip fracture populations, respectively. Depressive symptoms were stable over time, with a weak trend toward increasing severity for the moderate-severe symptom trajectory. Participants in the moderate-severe symptom trajectory were older, more likely to be female, live alone, and had worse health measures than other trajectories (p < .001). Older adults, and those with hip fracture, follow one of the 3 trajectories of depressive symptoms that are broadly stable over time. Depressive symptoms' prevalence was higher for those with hip fracture and, when present, the symptoms were more severe than the overall population. Results suggest a role of factors including age, gender, and marital status in depressive symptom trajectories.

Career Outcome Expectations of Chinese Medical Students: A Short‐Term Longitudinal Study1

AbstractThis study examined the longitudinal association between career outcome expectations and positive psychological capital, using data from four investigations of 885 Chinese medical students over a 9‐month period. Latent growth curve modeling (LGCM) and latent growth mixture modeling (LGMM) were used to examine the overall trajectory of career outcome expectations and to group them. Career outcome expectations showed a linear growth trend on the whole. The modeling distinguished three growth trajectories of career outcome expectations. There is an association between positive psychological capital and career outcome expectations, that is, positive psychological capital positively affects career outcome expectations and not the other way around. The results speak to the noteworthy individual differences in the development of career outcome expectations among Chinese medical students.

Effects of growth trajectory of shock index within 24 h on the prognosis of patients with sepsis.

BackgroundSepsis is a serious disease with high clinical morbidity and mortality. Despite the tremendous advances in medicine and nursing, treatment of sepsis remains a huge challenge. Our purpose was to explore the effects of shock index (SI) trajectory changes on the prognosis of patients within 24 h after the diagnosis of sepsis.MethodsThis study was based on Medical Information Mart for Intensive Care IV (MIMIC- IV). The effects of SI on the prognosis of patients with sepsis were investigated using C-index and restricted cubic spline (RCS). The trajectory of SI in 24 h after sepsis diagnosis was classified by latent growth mixture modeling (LGMM). Cox proportional hazard model, double robust analysis, and subgroup analysis were conducted to investigate the influence of SI trajectory on in-hospital death and secondary outcomes.ResultsA total of 19,869 patients were eventually enrolled in this study. C-index showed that SI had a prognostic value independent of Sequential Organ Failure Assessment for patients with sepsis. Moreover, the results of RCS showed that SI was a prognostic risk factor. LGMM divided SI trajectory into seven classes, and patients with sepsis in different classes had notable differences in prognosis. Compared with the SI continuously at a low level of 0.6, the SI continued to be at a level higher than 1.0, and the patients in the class whose initial SI was at a high level of 1.2 and then declined had a worse prognosis. Furthermore, the trajectory of SI had a higher prognostic value than the initial SI.ConclusionBoth initial SI and trajectory of SI were found to be independent factors that affect the prognosis of patients with sepsis. Therefore, in clinical treatment, we should closely monitor the basic vital signs of patients and arrive at appropriate clinical decisions on basis of their change trajectory.

Predictors of psychological resilience trajectories in patients with knee arthroplasty: A longitudinal study.

To identify the different classes of total knee arthroplasty patients according to the heterogenous trajectories of psychological resilience and investigate the predictors for different patterns of resilience. A prospective cohort study. A total of 210 patients with total knee arthroplasty from March to December 2021 were included. Baseline assessment (T0) data were collected before surgery and included demographic, biological (clinical characteristics), psychological (psychological resilience, self-efficacy, psychological distress, hope, medical coping mode) and social (social support) factors. Resilience measurements were repeated at 3 days after surgery (T1), the date of discharge (T2), and 1 month (T3) and 3 months (T4) after discharge. Latent growth mixture modelling was employed to define different resilience trajectories. Predictors of class membership were identified using multinomial logistic regression. Data from 198 patients were analysed. Three latent classes were identified with similar patterns in different intercepts, showing a significant decrease in resilience from admission (T0) to 3 days after surgery (T1) followed by an increase from T1 to T4. The three trajectories of psychological resilience were named the stable-resilience class (65.66%), high-resilience class (17.68%), and low-resilience class (16.66%). Multinomial logistic regression showed that compared with the stable-resilience class, the high-resilience class was predicted by having a higher level of hope, having higher education, living in urban areas and having more children, while the low-resilience class was predicted by having lower levels of self-efficacy and hope, living in semirural areas, and having more children. The three trajectories indicated that surgery was the major stressor influencing patients' psychological resilience and that patients in the low-resilience class needed to be intervened. Predictors of patients in different classes provide evidence for the identification of vulnerable populations and lay a foundation for future research contributing to the development of targeted interventions for improving patients' psychological resilience. No patient or public contribution but the time points of investigation were decided based on our interviews with 12 total knee arthroplasty patients.

The role of socioeconomic status in different trajectories of depressive symptoms in Chinese college freshmen.

The associations between socioeconomic status (SES) and depressive symptoms have been found in previous studies. However, the role of SES in different trajectories of depressive symptoms in Chinese college freshmen has not been discovered. The present study aims to identify how depressive symptom trajectories are related to SES during the first semester of freshman. Six hundred fifty-two Chinese college freshmen (64.9% female) were followed 4 times across 4 months. The Latent Growth Mixture Model (LGMM) was used to identify trajectories of depressive symptoms. Multinomial Logical Regression was used to identify the influence of family socioeconomic status (FSES), subjective socioeconomic status (SSS), and demographic variables on trajectories of depressive symptoms for freshmen. Results found that college freshmen’s depressive symptoms gradually decreased during the four tests, F(2.758, 1795.383) = 52.642, p < 0.001, and there are three trajectories of depressive symptoms: normal group (Class 1, 73.1%), depression risk group (Class 2, 20.7%), and depression deterioration group (Class 3, 6.1%). The decline of SSS predicted increasing depressive symptoms. Age and left-behind experience have significant effects on trajectories of depressive symptoms. FSES, birthplace, and gender had no significant impact on trajectories of depressive symptoms. These results demonstrated that low SSS, age, and left-behind might be risk factors for the development of depressive symptoms.

High triglyceride-glucose index in young adulthood is associated with incident cardiovascular disease and mortality in later life: insight from the CARDIA study

BackgroundThis study aimed to investigate the associations between the triglyceride-glucose (TyG) index in young adulthood with incident cardiovascular disease (CVD) and mortality.MethodsWe included 4,754 participants from the Coronary Artery Risk Development in Young Adults study at baseline. The TyG index was calculated as ln (fasting TG [mg/dl] × fasting glucose [mg/dl]/2), and the TyG index trajectories were identified by using the latent class growth mixture model. We evaluated the association between the baseline and trajectories of the TyG index with incident CVD events and all-cause mortality using Cox proportional hazards regression analysis. The added value of the TyG index included in pooled cohort equations for CVD prediction was also analyzed.ResultsAmong 4754 participants (mean age 24.72 years, 45.8% male, 51.2% black), there were 158 incident CVD events and 246 all-cause mortality during a median 25 years follow-up. After adjusting for multiple confounding variables, each one-unit increase in the TyG index was associated with a 96% higher CVD risk (hazard ratio [HR] 1.96, 95% confidence interval [CI] 1.44–2.66) and a 85% higher all-cause mortality risk (HR 1.85, 95% CI 1.45–2.36). Three distinct trajectories of the TyG index along the follow-up duration were identified: low (44.0%), moderate (45.5%), and high (10.5%). Compared with those participants in the low TyG index trajectory group, those in the high TyG index trajectory group had a greater risk of CVD events (HR 2.35, 95% CI 1.34–4.12) and all-cause mortality (HR 3.04, 95% CI 1.83–5.07). The addition of baseline TyG index to pooled cohort equations for CVD improved the C-statistics (P < 0.001), integrated discrimination improvement value (P < 0.001), and category-free net reclassification improvement value (P = 0.003).ConclusionsHigher baseline TyG index levels and higher long-term trajectory of TyG index during young adulthood were significantly associated with an increased risk of incident CVD events and all-cause mortality in later life.

Post-traumatic growth trajectories among frontline healthcare workers during the COVID-19 pandemic: A three-wave follow-up study in mainland China.

ObjectivesThe COVID-19 pandemic has taken a significant toll on people worldwide for more than 2 years. Previous studies have highlighted the negative effects of COVID-19 on the mental health of healthcare workers (HCWs) more than the positive changes, such as post-traumatic growth (PTG). Furthermore, most previous studies were cross-sectional surveys without follow-ups. This study draws on PTG follow-up during the COVID-19 outbreak at 12-month intervals for 2 years since 2020. The trajectories and baseline predictors were described.MethodsA convenience sampling method was used to recruit frontline nurses or doctors at the COVID-19-designated hospital who were eligible for this study. A total of 565 HCWs completed the 2 years follow-up and were used for final data analysis. The latent growth mixture models (GMM) was used to identify subgroups of participants with different PTG trajectories. Multinomial logistic regression model was used to find predictors among sociodemographic characteristics and resilience at baseline.ResultsFour trajectory PTG types among HCWs were identified: ‘Persistent, “Steady increase”, “High with drop”, and “Fluctuated rise.” Comparing the “Persistent low” type, the other three categories were all associated with older age, higher education. Furthermore, “Persistent low” was also negatively associated with resilience at baseline.ConclusionThe PTG of HCWs with different characteristics showed different trends over time. It is necessary to increase the measure frequency to understand the PTG status in different times. Improving HCW’s resilience could help improve staff PTG.

Study on adherence to positive airway pressure treatment for patients with obstructive sleep apnea using real-world big data in a telemedicine management system.

Obstructive Sleep Apnea (OSA) is a disorder that is characterized by obstructive apneas and hypopneas/respiratory effort-related arousals caused by upper airway collapse during sleep. Positive Airway Pressure (PAP) is the first-line treatment for moderate to severe OSA. However, the effectiveness of PAP therapies is contingent on treatment adherence. With the implementation of the wireless transmission for PAP treatment, it is possible to evaluate the objective adherence to PAP use. The purpose of this study is to assess the adherence to PAP therapy of Chinese OSA patients in a telemedicine management system which could fulfill automatic transmission of PAP treatment data. First, we use the telemedicine management system to extract PAP adherence information of OSA adult patients in one week, one month, three months, six months and 12months. Second, we describe the general profile of PAP therapy adherence. Third, the latent class growth modeling and growth mixture modeling was conducted using Mplus 8.0 to identify the trajectories of adherence over time. Of all the 662 patients involved in our study, PAP adherence declined over time. After one year, the proportion of days compliant was 53.7%, the proportion of good compliance was 45.2%, the daily usage (all days) was 3.9h/night, slightly lower than subjective adherence reported in the previous literatures. In addition, we identified three patterns of adherence over time: great users (39.9%; high mean value and level, negative slope, slow decline), good users (34.8%; moderate mean value and level, negative slope, rapid decline) and low users (25.3%; low mean value and level, negative slope, rapid decline). In brief, telemedicine management system provides a convenient platform for monitoring the treatment compliance of OSA patients powerfully and accurately. To improve the low PAP adherence in China, we should make good use of the PAP therapy telemedicine management platform to detect patients with poor adherence and provide timely intervention. Besides, our research provides a foundation for future studies to explore the determinants of observed trajectories of PAP adherence based on the telemedicine platforms.

Latent growth trajectories of county-level diabetes prevalence in the United States, 2004–2017, and associations with overall environmental quality

Background:The prevalence of type 2 diabetes (T2D) has increased in the United States, and recent studies suggest that environmental factors contribute to T2D risk. We sought to understand if environmental factors were associated with the rate and magnitude of increase in diabetes prevalence at the county level.Methods:We obtained age-adjusted diabetes prevalence estimates from the CDC for 3,137 US counties from 2004 to 2017. We applied latent growth mixture models to these data to identify classes of counties with similar trends in diabetes prevalence over time, stratified by Rural Urban Continuum Codes (RUCC). We then compared mean values of the US EPA Environmental Quality Index (EQI) 2006–2010, overall and for each of the five domain indices (air, water, land, sociodemographic, and built), with RUCC-specific latent class to examine associations of environmental factors and class of diabetes prevalence trajectory.Results:Overall diabetes prevalence trends between 2004 and 2017 were similar across all RUCC strata. We identified two classes among metropolitan urbanized (RUCC 1) counties; four classes among non-metro urbanized (RUCC 2) counties; and three classes among less urbanized (RUCC 3) and thinly populated (RUCC 4) counties. Associations with overall EQI values and class of diabetes prevalence trends differed by RUCC strata, with the clearest association between poor air EQI and steeper increases in diabetes prevalence among rural counties (RUCC 3 and 4).Conclusions:Similarities in county-level diabetes prevalence trends between 2004 and 2017 were identified for each RUCC strata, although associations with environmental factors varied by rurality.

Sex-specific metabolic risk factors and their trajectories towards the non-alcoholic fatty liver disease incidence.

Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disease. This study examined sex-specific associations between NAFLD and metabolic factors and investigated the trajectory of risk factors. We retrospectively investigated 16,140 individuals from Beijing Health Management Cohort. Univariate and multivariate time-dependent Cox regression analyses were performed to identify independent risk factors for new-onset NAFLD. The trajectory of risk factors was investigated using the latent growth curve model and growth mixture model. Over a median follow-up of 3.15years, 2,450 (15.18%) participants developed NAFLD. The risk factors for NAFLD in men were increased body mass index (BMI); waist circumference (WC); triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), haemoglobin (Hb), and serum uric acid (SUA) levels; and platelet (PLT) count and decreased serum creatinine-to-body weight (sCr/bw) and high-density lipoprotein cholesterol (HDL-C) levels. In women, the risk factors were increased BMI, WC, and fasting plasma glucose (FPG), TG, LDL-C, SUA, white blood cell (WBC), and PLT and decreased sCr/bw and HDL-C levels. In addition, BMI, LDL-C, sCr/bw and PLT changing trajectories were associated with NAFLD in men; BMI, WC, TG, LDL-C, SUA and sCr/bw trends was associated with NAFLD risk in women. Development of NAFLD is associated with BMI, LDL-C, sCr/bw and PLT changing trajectories in men; BMI, WC, TG, LDL-C, SUA and sCr/bw trends are associated an increased risk of NAFLD in women. Deterioration of metabolic risk factors status can be a predictor of NAFLD many years before its occurrence.

Urban-rural disparities in the healthy ageing trajectory in China: a population-based study

PurposeThe aim of this study is to measure the trajectory of healthy ageing among Chinese middle-aged and older population, and explore the disparity of the trajectory, as well as contributing factors, between urban and rural areas in China.MethodsA total of 9402 respondents aged 45 years and older interviewed in four waves (2011, 2013, 2015 and 2018) were selected from the China Health and Retirement Longitudinal Study. Healthy ageing score was calculated through item response theory. A latent growth mixture model (LGMM) was applied to distinguish the trajectory of healthy aging. A multinomial logistics regression model (MLRM) was used to explore the relationship between urban-rural areas and healthy aging trajectories, and further to explore associated factors in rural and urban areas separately.ResultsThe healthy ageing score was lower in rural areas than urban areas in each survey wave. Five classes (“continuing-low”, “continuing-middle”, “continuing-middle-to-high”, “significantly-declining”, “continuing-high”) were grouped through LGMM. The MLRM results showed that urban living was significantly associated with a higher likelihood of being healthy (for [continuing-low/continuing-high]: β = − 1.17, RRR = 0.31, P < 0.001, 95% CI = 0.18–0.53; and for [continuing-middle/continuing-high]: β = − 0.53, RRR = 0.59, P < 0.001, 95% CI = 0.49–0.71).ConclusionHealthy ageing is a prominent objective in the development of a country, and rural-urban disparities are an essential obstacle to overcome, with the rural population more likely to develop a low level of healthy ageing trajectory. Prevention and standardized management of chronic diseases should be enhanced, and social participation should be encouraged to promote healthy ageing. The policy inclination and resource investment should be enhanced to reduce disparity in healthy ageing between urban and rural areas in China.