Female sex and femininity independently associate with common somatic symptom trajectories.

BACKGROUND: Multiple predictors have been associated with persistent somatic symptoms. However, previous studies problematically defined the persistence of symptoms, conflated participants' sex and gender, and focused on patient populations. Therefore, we studied associations between predictors, especially sex and gender, and longitudinal patterns of somatic symptoms in the general adult population. We also assessed whether predictors for persisting symptoms differ between sexes. METHOD: To identify developmental trajectories of somatic symptoms, assessed by the SCL-90 SOM, we used latent class trajectory modeling in the Dutch Lifelines Cohort Study [N = 150 494; 58.6% female; median time to follow-up: 46.0 (min-max: 22.0-123.0) months]. To identify predictors of trajectories, we applied multiple logistic regression analyses. Predictors were measured by surveys at baseline and a composite gender index was previously developed. RESULTS: A five-class linear LCGA model fitted the data best: 93.7% of the population had a stable symptom trajectory, whereas 1.5% and 4.8% of the population had a consistently increasing or decreasing symptom trajectory, respectively. Female sex predicted severe, stable symptom severity (OR 1.74, 95% CI 1.36-2.22), but not increasing symptom severity (OR 1.15, 95% CI 0.99-1.40). Femininity was protective hereof (OR 0.60, 95% CI 0.44-0.82 and OR 0.66, 95% CI 0.51-0.85, respectively). Merely a few predictors of symptom severity, for instance hours of paid employment and physical functioning, differed in strength between sexes. Yet, effect sizes were small. CONCLUSION: Female sex and femininity predict symptom trajectories. No large sex differences in the strength of additional predictors were found, thus it may not be clinically useful to distinguish between predictors specific to male or female patients of persistent somatic symptoms.

A latent-class heteroskedastic hurdle trajectory model: patterns of adherence in obstructive sleep apnea patients on CPAP therapy.

BACKGROUND: Sleep apnea patients on CPAP therapy exhibit differences in how they adhere to the therapy. Previous studies have demonstrated the benefit of describing adherence in terms of discernible longitudinal patterns. However, these analyses have been done on a limited number of patients, and did not properly represent the temporal characteristics and heterogeneity of adherence. METHODS: We illustrate the potential of identifying patterns of adherence with a latent-class heteroskedastic hurdle trajectory approach using generalized additive modeling. The model represents the adherence trajectories on three aspects over time: the daily hurdle of using the therapy, the daily time spent on therapy, and the day-to-day variability. The combination of these three characteristics has not been studied before. RESULTS: Applying the proposed model to a dataset of 10,000 patients in their first three months of therapy resulted in nine adherence groups, among which 49% of patients exhibited a change in adherence over time. The identified group trajectories revealed a non-linear association between the change in the daily hurdle of using the therapy, and the average time on therapy. The largest difference between groups was observed in the patient motivation score. The adherence patterns were also associated with different levels of high residual AHI, and day-to-day variability in leakage. CONCLUSION: The inclusion of the hurdle model and the heteroskedastic model into the mixture model enabled the discovery of additional adherence patterns, and a more descriptive representation of patient behavior over time. Therapy adherence was mostly affected by a lack of attempts over time, suggesting that encouraging these patients to attempt therapy on a daily basis, irrespective of the number of hours used, could drive adherence. We believe the methodology is applicable to other domains of therapy or medication adherence.

Associations of Dietary Diversity Trajectories with Frailty among Chinese Older Adults: A Latent Class Trajectory Analysis Based on a CLHLS Cohort.

BACKGROUND: High dietary diversity has been found to be associated with frailty. However, the trajectory of dietary diversity intake in relation to frailty is unclear. METHODS: Using the latent class trajectory modeling approach, we identified distinctive dietary variety trajectory groups among 2017 participants based on the Chinese Longitudinal Healthy Longevity Survey acquired at four time points within a 10-year period. Frailty status was assessed using a frailty index comprising 37 health deficits. Dietary diversity was quantified using the dietary variety score (DVS), based on food category consumption frequency. Logistic regression analyses were employed to explore the association between DVS change trajectories and frailty. RESULTS: This study identified two distinct DVS trajectories: "Moderate-Slow decline-Slow growth", encompassing 810 (40.16%) individuals, and "Moderate-Slow growth-Accelerated decline", including 1207 (59.84%) individuals. After adjusting for covariates, the odds ratio for DVS in the "Moderate-Slow decline-Slow growth" group was 1.326 (95% confidence interval: 1.075-1.636) compared to the "Moderate-Slow growth-Accelerated decline" group. The "Moderate-Slow decline-Slow growth" trajectory continued to decrease and was maintained at a low level in the early stages of aging. CONCLUSION: Sustaining a high dietary diversity trajectory over time, particularly in the early stages of aging, could potentially decrease the risk of frailty among older Chinese adults.

Long-Term Trajectories of High-Sensitivity C-Reactive Protein Level Among Patients with Acute Heart Failure.

Background: Inflammation contributes to the progression of heart failure (HF). However, long-term inflammatory trajectories and their associations with outcomes in patients with acute HF remain unclear. Methods: Data was obtained from the China Patient-Centered Evaluative Assessment of Cardiac Events Prospective Heart Failure Study, and high-sensitivity C-reactive protein (hsCRP) was used to reflect the inflammatory level. Only patients who survived over 12-month and had hsCRP data at admission, 1-, and 12-month after discharge were included. The latent class trajectory modeling was used to characterize hsCRP trajectories. Multivariable Cox regression models were used to explore the association between hsCRP trajectories and following mortality. Results: Totally, 1281 patients with a median 4.77 (interquartile range [IQR]: 4.24-5.07) years follow-up were included. The median age was 64 years (IQR: 54-73 years); 453 (35.4%) were female. Four distinct inflammatory trajectories were characterized: persistently low (n = 419, 32.7%), very high-marked decrease (n = 99, 7.7%), persistently high (n = 649, 50.7%), and persistently very high (n = 114, 8.9%). Compared with the persistently low trajectory, the all-cause mortality was increased in a graded pattern in the persistently high (hazard ratio [HR]: 1.59, 95% confidence interval [CI]: 1.23-2.07) and persistently very high (HR: 2.56, 95% CI: 1.83-3.70) trajectories; nevertheless, the mortality was not significantly increased in very high-marked decrease trajectory (HR: 0.94, 95% CI: 0.57-1.54). Conclusion: Four distinct inflammatory trajectories were identified among patients with acute HF who survived over 12-month. Patients with persistently high and very high trajectories had significantly higher mortality than those with the persistently low trajectory.

Estimated glomerular filtration rate trajectories in south Asians: Findings from the cardiometabolic risk reduction in south Asia study.

Background: Few longitudinal data characterize kidney function decline among South Asians, one of the world's largest population groups. We aimed to identify estimated glomerular filtration rate (eGFR) trajectories in a population-based cohort from India and assess predictors of rapid kidney function decline. Methods: We used 6-year longitudinal data from participants of a population-representative study from Delhi and Chennai, India who had at least two serum creatinine measures and baseline CKD-EPI eGFR> 60 ml/min/1.73m2 (n=7779). We used latent class trajectory modeling to identify patterns of kidney function trajectory (CKD-EPI eGFR) over time. In models accounting for age, sex, education, and city, we tested the association between 15 hypothesized risk factors and rapid kidney function decline. Findings: Baseline mean eGFR was 108 (SD 16); median eGFR was 110 [IQR: 99-119] ml/min/1.73m2. Latent class trajectory modeling and functional characterization identified three distinct patterns of eGFR: class-1 (no decline; 58%) annual eGFR change 0.2 [0.1, 0.3]; class-2 (slow decline; 40%) annual eGFR change -0.2 [-0.4, -0.1], and class-3 (rapid decline; 2%) annual eGFR change -2.7 [-3.4, -2.0] ml/min/1.73m2. Albuminuria (>30 mg/g) was associated with rapid eGFR decline (OR for class-3 vs class-1: 5.1 [95% CI: 3.2; 7.9]; class-3 vs. class-2: 4.3 [95% CI:2.7; 6.6]). Other risk factors including self-reported diabetes, cardiovascular disease, peripheral arterial disease, and metabolic biomarkers such as HbA1c and systolic blood pressure were associated with rapid eGFR decline phenotype but potential 'non-traditional' risk factors such as manual labor or household water sources were not. Interpretation: Although mean and median eGFRs in our population-based cohort were higher than those reported in European cohorts, we found that a sizeable number of adults residing in urban India are experiencing rapid kidney function decline. Early and aggressive risk modification among persons with albuminuria could improve kidney health among South Asians. Funding: The CARRS study has been funded with federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, under Contract No. HHSN2682009900026C and P01HL154996. Dr. Anand was supported by NIDDK K23DK101826 and R01DK127138.

Identification of Distinct Subgroups in Moderately Severe Rheumatic Mitral Stenosis Using Data-Driven Phenotyping of Longitudinal Hemodynamic Progression.

Background Rheumatic mitral stenosis is a significant cause of valvular heart disease. Pulmonary arterial systolic pressure (PASP) reflects the hemodynamic consequences of mitral stenosis and is used to determine treatment strategies. However, PASP progression and expected outcomes based on PASP changes in patients with moderately severe mitral stenosis remain unclear. Methods and Results A total of 436 patients with moderately severe rheumatic mitral stenosis (valve area 1.0-1.5 cm2) were enrolled. Composite outcomes included all-cause mortality and hospitalization for heart failure. Data-driven phenotyping identified 2 distinct trajectory groups based on PASP progression: rapid (8.7%) and slow (91.3%). Patients in the rapid progression group were older and had more diabetes and atrial fibrillation than those in the slow progression group (all P<0.05). The initial mean diastolic pressure gradient and PASP were higher in the rapid progression group than in the slow progression group (6.2±2.4 mm Hg versus 5.1±2.0 mm Hg [P=0.001] and 42.3±13.3 mm Hg versus 33.0±9.2 mm Hg [P<0.001], respectively). The rapid progression group had a poorer event-free survival rate than the slow progression group (log-rank P<0.001). Rapid PASP progression was a significant risk factor for composite outcomes even after adjusting for comorbidities (hazard ratio, 3.08 [95% CI, 1.68-5.64]; P<0.001). Multivariate regression analysis revealed that PASP >40 mm Hg was independently associated with allocation to the rapid progression group (odds ratio, 4.95 [95% CI, 2.08-11.99]; P<0.001). Conclusions Rapid PASP progression was associated with a higher risk of the composite outcomes. The main independent predictor for rapid progression group allocation was initial PASP >40 mm Hg.

Body mass index trajectories in early childhood in relation to cardiometabolic risk profile and body composition at 5 years of age.

BACKGROUND: Both impaired and accelerated postnatal growth have been associated with adult risks of obesity and cardiometabolic diseases, like type 2 diabetes and cardiovascular disease. However, the timing of the onset of cardiometabolic changes and the specific growth trajectories linking early growth with later disease risks are not well understood. OBJECTIVES: The aim of this study was to identify distinct trajectories of BMI growth from 0 to 5 y and examine their associations with body composition and markers of cardiometabolic risk at age 5 y. METHODS: In a prospective birth cohort study of 453 healthy and term Ethiopian children with BMIs assessed a median of 9 times during follow-up, we identified subgroups of distinct BMI trajectories in early childhood using latent class trajectory modeling. Associations of the identified growth trajectories with cardiometabolic markers and body composition at 5 y were analyzed using multiple linear regression analyses in 4 adjustment models for each outcome. RESULTS: We identified 4 heterogeneous BMI growth trajectories: stable low BMI (19.2%), normal BMI (48.8%), rapid catch-up to high BMI (17.9%), and slow catch-up to high BMI (14.1%). Compared with the normal BMI trajectory, children in the rapid catch-up to high BMI trajectory had higher triglycerides (TGs) (range of ß-coefficients in Models 1-4: 19-21%), C-peptides (23-25%), fat masses (0.48-0.60 kg), and fat-free masses (0.50-0.77 kg) across the 4 adjustment models. Children in the stable low BMI trajectory had lower LDL cholesterol concentrations (0.14-0.17 mmol/L), HDL cholesterol concentrations (0.05-0.09 mmol/L), fat masses (0.60-0.64 kg), and fat-free masses (0.35-0.49 kg), but higher TGs (11-13%). CONCLUSIONS: The development of obesity and cardiometabolic risks may be established already in early childhood; thus, our data provide a further basis for timely interventions targeted at young children from low-income countries with unfavorable growth patterns. The birth cohort was registered at ISRCTN as ISRCTN46718296.