Long-term relatively high dietary manganese intake could decrease the risk of hyperuricemia: Twelve-year distinct dietary manganese consumption trajectories and the China Health and Nutrition Survey.

BACKGROUND AND AIM: Currently, the relationship between dynamic changes in dietary manganese (Mn) intake and risk of hyperuricemia (HU) is still unclear. This study aimed to identify dietary Mn consumption trajectories in the Chinese adults and assess their relation with the risk of HU. METHODS AND RESULTS: Cohort data from the China Health and Nutrition Survey (CHNS) 1997-2009 were employed in this study. Overall, 6886 adult participants were included. Participants were designated into subgroups based on the trajectories of dietary Mn consumption by sex. Cox proportional hazard models were used to explore the associations between different trajectories and the risk of HU. For men, compared with low stable trajectory group, moderate to high trajectory group was significantly related to reduced risk of HU (HR = 0.61, 95% CI: 0.38 to 0.98) with adjustment for covariates. TC, HDL-C, ApoB, and TG exerted partial regulation function between trajectories and HU. For women, compared with low stable trajectory group, high stable trajectory group was significantly related to reduced risk of HU (HR = 0.76, 95% CI: 0.60 to 0.95) with adjustment for covariates. Similarly, TC, HDL-C, ApoB, and ApoA exerted partial regulation function between trajectories and HU. CONCLUSIONS: Long-term relatively high dietary Mn consumption may have a protective effect against HU in Chinese adults. The differences in HU-related factors among different dietary Mn intake trajectories partially regulated the association between these trajectories and HU.

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.

Gestational weight trajectory and risk of adverse pregnancy outcomes among women with gestational diabetes mellitus: A retrospective cohort study.

The aim of this study was to explore gestational weight gain (GWG) trajectories and their associations with adverse pregnancy outcomes. A retrospective cohort study including 11,064 women with gestational diabetes mellitus (GDM) was conducted between 2015 and 2019 in China. The latent class trajectory model was used to identify GWG trajectories, and logistic regression was performed to examine odds ratio (OR) of pregnancy outcomes. Three trajectories of GWG were identified in these 11,604 women with GDM. Trajectory 1: 64.02% of women had sustained moderate GWG throughout pregnancy; Trajectory 2: 17.75% of women showed a high initial GWG but followed by a low GWG from the third trimester until delivery; Trajectory 3: 18.23% had low initial GWG but followed by drastic GWG from the second trimester until delivery. Compared with pregnant women with Trajectory 1, women with Trajectory 2 had a higher risk of large for gestational age (adjusted odds ratio [AOR]: 1.29, 95% confidence interval [CI]: 1.12-1.48) but at a lower risk of having hypertensive disorders of pregnancy (AOR: 0.76, 95% CI: 0.57-0.96). Women in Trajectory 3 were more likely to develop small for gestational age (AOR: 2.12, 95% CI: 1.62-2.78), low birthweight (AOR: 1.49, 95% CI: 1.07-2.08), preterm birth (AOR: 1.28, 95% CI: 1.05-1.63), caesarean section (AOR: 1.26, 95% CI: 1.112-1.42) and hypertensive disorders of pregnancy (AOR: 2.24, 95% CI: 1.82-2.76). The association of GWG trajectory with adverse pregnancy outcomes differs across prepregnancy body mass index and GWG categories. Women with a slow initial GWG but followed by drastic GWG had higher risks of adverse pregnancy outcomes. Early clinical recognition of poor GWG trajectory will contribute to early intervention in high-risk groups to minimise adverse outcomes.

Associations of early childhood body mass index trajectories with body composition and cardiometabolic markers at age 10 years: the Ethiopian infant anthropometry and body composition (iABC) birth cohort study.

BACKGROUND: Variability in body mass index (BMI) (kg/m2) trajectories is associated with body composition and cardiometabolic markers in early childhood, but it is unknown how these associations track to later childhood. OBJECTIVES: We aimed to assess associations of BMI trajectories from 0 to 5 y with body composition and cardiometabolic markers at 10 y. METHODS: In the Ethiopian infant anthropometry and body composition (iABC) birth cohort, we previously identified 4 distinct BMI trajectories from 0 to 5 y: stable low BMI (19.2%), normal BMI (48.8%), rapid growth to high BMI (17.9%), and slow growth to high BMI (14.1%). At 10 y, we obtained data from 320 children on anthropometry, body composition, abdominal subcutaneous and visceral fat, and cardiometabolic markers. Associations of BMI trajectories and 10-y outcomes were analyzed using multiple linear regression. RESULTS: Compared with children with the normal BMI trajectory, those with rapid growth to high BMI had 1.7 cm (95% CI: 0.1, 3.3) larger waist circumference and those with slow growth to high had 0.63 kg/m2 (95% CI: 0.09, 1.17) greater fat mass index and 0.19 cm (95% CI: 0.02, 0.37) greater abdominal subcutaneous fat, whereas those with stable low BMI had -0.28 kg/m2 (95% CI: -0.59, 0.03) lower fat-free mass at 10 y. Although the confidence bands were wide and included the null value, children with rapid growth to high BMI trajectory had 48.6% (95% CI: -1.4, 123.8) higher C-peptide concentration and those with slow growth to high BMI had 29.8% (95% CI: -0.8, 69.8) higher insulin and 30.3% (95% CI: -1.1, 71.6) higher homeostasis model assessment of insulin resistance, whereas those with rapid growth to high BMI had -0.23 mmol/L (95% CI: -0.47, 0.02) lower total cholesterol concentration. The trajectories were not associated with abdominal visceral fat, blood pressure, glucose, and other lipids at 10 y. CONCLUSIONS: Children with rapid and slow growth to high BMI trajectories before 5 y tend to show higher measures of adiposity and higher concentrations of markers related to glucose metabolism at 10 y. CLINICAL TRIAL REGISTRY: ISRCTN46718296 (https://www.isrctn.com/ISRCTN46718296).

Trajectories and comorbid symptom networks of posttraumatic stress symptoms in frontline rescuers: A longitudinal study.

BACKGROUND: Previous research has largely lacked studies that explore the trajectories of Posttraumatic stress symptoms (PTSS) and the structure of comorbid psychiatric symptom networks following traumatic event, while controlling for the severity of traumatic exposure. The present study aims to explore the characteristic trajectories of PTSS, in the context of ensuring controlled levels of traumatic exposure. Furthermore, the PTSS, depressive, and anxiety comorbid symptom networks of different PTSS trajectory subgroups are also investigated. METHODS: A total of 296 frontline rescue personnel were enrolled into our study. In an effort to control for variations in traumatic exposure severity, this study ensured that all participants had same responsibilities and cumulative operational duration at the post-disaster rescue circumstance. Growth mixture models (GMMs) were employed to scrutinize the trajectories of PTSS. Additionally, network analysis was used to examine the comorbid symptom network of PTSS, depression, and anxiety. RESULTS: Four distinct PTSS trajectories were identified, namely Persisting Symptom, Gradual Recovery, Gradual Aggravation, and Asymptomatic. Although both the Persisting Symptom and Gradual Aggravation groups belong to the high-risk subgroups for persistent PTSS, they exhibit differences in core symptoms within their respective networks. The core symptom for the Persisting Symptom Network is flashbacks, while for the Gradual Aggravation Network, it is sleep disturbances. CONCLUSION: To the best of our knowledge, the present study represents the first research endeavor to integrate longitudinal trajectory analysis of PTSS with longitudinal symptom network analysis, clarifying the evolving features of PTSS but also offering valuable insights for early screening and intervention strategies.

Heterogeneity in glycaemic control in children and adolescents with type 1 diabetes: A latent class trajectory analysis of Danish nationwide data.

AIMS: Suboptimal glycaemic control in children and adolescents with type 1 diabetes is prevalent and associated with increased risk of diabetes-related complications and mortality later in life. First, we aimed to identify distinct glycated haemoglobin (HbA1c) trajectories in children and adolescents (2-19 years) with type 1 diabetes. Second, we examined their associations with clinical and socio-demographic factors. METHODS: Data were obtained from the Danish Registry of Childhood and Adolescent Diabetes (DanDiabKids) comprising all Danish children and adolescents diagnosed with type 1 diabetes from 1996 to 2019. Subgroups of distinct mean trajectories of HbA1c were identified using data-driven latent class trajectory modelling. RESULTS: A total of 5889 children (47% female) had HbA1c measured a median of 6 times (interquartile range 3-8) and contributing to 36,504 measurements. We identified four mean HbA1c trajectories, referred to as 'Stable but elevated HbA1c' (83%), 'Increasing HbA1c' (5%), 'Late HbA1c peak' (7%), and 'Early HbA1c peak' (5%). Compared to the 'Stable but elevated HbA1c' group, the three other groups presented rapidly deteriorating glycaemic control during late childhood or adolescence, had higher HbA1c at study entry, and included fewer pump users, higher frequency of inadequate blood glucose monitoring, more severe hypoglycaemic events, lower proportions with Danish origin, and worse educational status of parents. The groups also represented significant differences by healthcare region. CONCLUSIONS: Children and adolescents with type 1 diabetes experience heterogenous trajectories with different timings and magnitudes of the deterioration of HbA1c levels, although the majority follow on average a stable, yet elevated HbA1c trajectory. The causes and long-term health implications of these heterogenous trajectories need to be addressed.

Association between Sarcopenia and Cognitive Trajectories among Middle-Aged and Older Adults in China: A Nationally Representative Cohort Study.

OBJECTIVES: The relationship between sarcopenia and cognitive function has been extensively studied, but is usually explored at a single time point. We used repeatedly measured cognitive data to examine the relationship between sarcopenia and cognitive trajectories over time among middle-aged and older Chinese adults. DESIGN: A nationally representative cohort study. SETTING AND PARTICIPANTS: Data were from three waves (2011, 2013 and 2015) of the China Health and Retirement Longitudinal Study (CHARLS). A total of 8963 participants with complete baseline data (wave 1) and at least two cognitive function tests (waves 1-3) were enrolled in this study. MEASUREMENTS: Sarcopenia was diagnosed at baseline (wave 1). The wave 1-3 data were used to analyze cognitive trajectories over time by constructing a latent class trajectory model (LCTM). Logistic regression model was used to analyze the association between sarcopenia and cognitive trajectories. RESULTS: Among 8693 participants, we identified two trajectories of cognitive function development, including a persistent low trajectory (n= 4856, 55.86%) and a persistent high trajectory (n= 3837, 44.14%). Sarcopenia was associated with persistently low cognitive trajectory of global cognitive (OR: 1.248, 95%CI: 1.046-1.490) after adjustment for other covariates. This association was still observed when stratified by age, gender, educational level, marital status, social activity, smoking status and drinking status. Mediation analysis showed that body mass index (BMI) mediated efficacy accounting for 42.32% of the relationship. CONCLUSIONS: Our study showed two trajectory groups of global cognitive function. Sarcopenia was associated with a persistent low trajectory over time and BMI mediated the relationship between sarcopenia and cognitive trajectories among middle-aged and older Chinese adults.

Exploration of model misspecification in latent class methods for longitudinal data: Correlation structure matters.

Modeling longitudinal trajectories and identifying latent classes of trajectories is of great interest in biomedical research, and software to identify latent classes of such is readily available for latent class trajectory analysis (LCTA), growth mixture modeling (GMM) and covariance pattern mixture models (CPMM). In biomedical applications, the level of within-person correlation is often non-negligible, which can impact the model choice and interpretation. LCTA does not incorporate this correlation. GMM does so through random effects, while CPMM specifies a model for within-class marginal covariance matrix. Previous work has investigated the impact of constraining covariance structures, both within and across classes, in GMMs-an approach often used to solve convergence problems. Using simulation, we focused specifically on how misspecification of the temporal correlation structure and strength, but correct variances, impacts class enumeration and parameter estimation under LCTA and CPMM. We found (1) even in the presence of weak correlation, LCTA often does not reproduce original classes, (2) CPMM performs well in class enumeration when the correct correlation structure is selected, and (3) regardless of misspecification of the correlation structure, both LCTA and CPMM give unbiased estimates of the class trajectory parameters when the within-individual correlation is weak and the number of classes is correctly specified. However, the bias increases markedly when the correlation is moderate for LCTA and when the incorrect correlation structure is used for CPMM. This work highlights the importance of correlation alone in obtaining appropriate model interpretations and provides insight into model choice.

Longitudinal Study of Left Ventricular Mass Index Trajectories and Risk of Mortality in Hypertension: A Cohort Study.

Background Left ventricular mass index (LVMI) has been extensively studied for its relationship with mortality but has been typically assessed at a single time point. We, therefore, describe the trajectory of LVMI in a population with hypertension over 6 years to study the subsequent risk of mortality. Methods and Results We assessed LVMI that was collected during annual health examinations in round 1 (2010-2012), round 2 (2013-2014), and round 3 (2015-2016) with 2 allometric scalings, height2.7, and body surface area, in a cohort of participants with hypertension to identify 6-year trajectories of LVMI by latent class trajectory modeling. We followed up with participants for mortality by latent trajectory from the last echocardiographic examination (September 17, 2014-December 8, 2016) to December 31, 2018. We calculated mortality hazard ratios by assigned trajectory using Cox proportional hazards models. We obtained data for LVMI from 2453 participants (mean age, 61.80 [SD, 12.14] years, 1428 [58.2%] female). We identified 3 trajectories of LVM/H2.7, characterized by maintained low stable (1298 [52.9%]); moderate stable (935 [38.1%]); high stable (220 [9.0%]), as well as 3 trajectories by LVM/body surface area. During a median follow-up of 2.15 years, 167 participants developed all-cause mortality, and 71 were cardiovascular mortality. Only the high stable trajectory was associated with a higher risk of all-cause mortality compared with the low stable trajectory by LVM/H2.7 or LVM/body surface area (all P<0.05). In Kaplan-Meier survival analysis, the trajectory with high stable LVM/body surface area had significantly lower survival probability. Conclusions In community hypertension, the individuals with high stable LVMI trajectory had the highest risk of all-cause mortality. The individuals in the moderate stable trajectory had a similar risk for mortality as those in the low stable trajectory.

Association between use of psychotropic medications prior to SARS-COV-2 infection and trajectories of COVID-19 recovery: Findings from the prospective Predi-COVID cohort study.

Psychological disturbances are frequent following COVID-19. However, there is not much information about whether pre-existing psychological disorders are associated with the severity and evolution of COVID-19. We aimed to explore the associations between regular psychotropic medication use (PM) before infection as a proxy for mood or anxiety disorders with COVID-19 recovery trajectories. We used data from the Predi-COVID study. We followed adults, tested positive for SARS-CoV-2 and collected demographics, clinical characteristics, comorbidities and daily symptoms 14 days after inclusion. We calculated a score based on 16 symptoms and modeled latent class trajectories. We performed polynomial logistic regression with PM as primary exposure and the different trajectories as outcome. We included 791 participants, 51% were men, and 5.3% reported regular PM before infection. We identified four trajectories characterizing recovery dynamics: "Almost asymptomatic," "Quick recovery," "Slow recovery," and "Persisting symptoms". With a fully adjusted model for age, sex, socioeconomic, lifestyle and comorbidity, we observed associations between PM with the risks of being in more severe trajectories than "Almost Asymptomatic": "Quick recovery" (relative risk (95% confidence intervals) 3.1 (2.7, 3.4), "Slow recovery" 5.2 (3.0, 9.2), and "Persisting symptoms"11.7 (6.9, 19.6) trajectories. We observed a gradient of risk between PM before the infection and the risk of slow or no recovery in the first 14 days. These results suggest that a pre-existing psychological condition increases the risk of a poorer evolution of COVID-19 and may increase the risk of Long COVID. Our findings can help to personalize the care of people with COVID-19.

PaCO2 trajectories in mechanically ventilated patients with COVID-19: A population-based cohort study.

OBJECTIVE: To identify PaCO2 trajectories and assess their associations with mortality in critically ill patients with coronavirus disease 2019 (COVID-19) during the first and second waves of the pandemic in Denmark. DESIGN: A population-based cohort study with retrospective data collection. PATIENTS: All COVID-19 patients were treated in eight intensive care units (ICUs) in the Capital Region of Copenhagen, Denmark, between March 1, 2020 and March 31, 2021. MEASUREMENTS: Data from the electronic health records were extracted, and latent class analyses were computed based on up to the first 3 weeks of mechanical ventilation to depict trajectories of PaCO2 levels. Multivariable Cox regression analyses were used to calculate adjusted hazard ratios (aHRs) for Simplified Acute Physiology Score 3, sex and age with 95% confidence intervals (CIs) for death according to PaCO2 trajectories. MAIN RESULTS: In latent class trajectory models, including 25,318 PaCO2 measurements from 244 patients, three PaCO2 latent class trajectories were identified: a low isocapnic (Class I; n = 130), a high isocapnic (Class II; n = 80), as well as a progressively hypercapnic (Class III; n = 34) trajectory. Mortality was higher in Class II [aHR: 2.16 {1.26-3.68}] and Class III [aHR: 2.97 {1.63-5.40}]) compared to Class I (reference). CONCLUSION: Latent class analysis of arterial blood gases in mechanically ventilated COVID-19 patients identified distinct PaCO2 trajectories, which were independently associated with mortality.

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.

Fetal growth trajectories of babies born large-for-gestational age in the LIFECODES Fetal Growth Study.

BACKGROUND: Babies born large-for-gestational age have an increased risk of adverse health outcomes, including birth injuries, childhood obesity, and cardiometabolic disorders. However, little work has been done to characterize patterns of fetal growth among large-for-gestational age births, which may further elucidate high- and low-risk subgroups. OBJECTIVE: This study aimed to identify subgroups of large-for-gestational age births based on trajectories of fetal growth derived from prenatal ultrasound measurements and explore differences in sociodemographic, pregnancy, and birth outcome characteristics across subgroups. STUDY DESIGN: This study identified and described trajectories of fetal growth among large-for-gestational age births (n=235) in the LIFECODES Fetal Growth Study. Ultrasound measurements of fetal growth in middle to late pregnancy were abstracted from health records. Group-based multi-trajectory modeling was applied to measurements of head circumference, abdominal circumference, and femur length z-scores to identify multivariate trajectories of fetal growth. Moreover, sociodemographic variables, pregnancy characteristics, and birth outcomes based on trajectory membership were summarized. RESULTS: This study identified 4 multivariate trajectories of fetal growth among large-for-gestational age births: catch-up growth (n=28), proportional abdominal circumference-to-femur length growth (n=67), disproportional abdominal circumference-to-femur length growth (n=96), and consistently large (n=44). Fetuses in the "catch-up growth" group exhibited small relative sizes in midpregnancy (ie, below average head circumference, abdominal circumference, and femur length z-scores) and large relative sizes in late pregnancy. Growth among these births was driven by increases in relative abdominal circumference and head circumference sizes. Participants who delivered births assigned to this group were less likely to have normal glucose control (40% vs 65%-75%) and more likely to have pregestational diabetes mellitus (36% vs 10%-17%) than other large-for-gestational age subgroups. In addition, the babies in this trajectory group were more likely to have macrosomia (86% vs 67%-73%) and to be admitted to the neonatal intensive care unit (32% vs 14%-21%) than other large-for-gestational age subgroups. In contrast, babies in the "consistently large" group had the largest relative size for all growth parameters throughout gestation and experienced a lower risk of adverse birth outcomes than other large-for-gestational age subgroups. CONCLUSION: This study characterized several trajectories of fetal growth among large-for-gestational age births, which were related to different pregnancy characteristics and the distribution of adverse birth outcomes. Although the number of individuals within some trajectories was small, a subgroup that exhibited a catch-up growth phenotype during gestation was identified, which may be uniquely associated with exposure to pregestational diabetes mellitus and a higher risk of admission to the neonatal intensive care unit. These results have highlighted that the risk of adverse outcomes may not be evenly distributed across all large-for-gestational age births.

An application of group-based trajectory modeling to define fetal growth phenotypes among small-for-gestational-age births in the LIFECODES Fetal Growth Study.

BACKGROUND: Reductions in fetal growth are associated with adverse outcomes at birth and later in life. However, identifying fetuses with pathologically small growth remains challenging. Definitions of small-for-gestational age are often used as a proxy to identify those experiencing pathologic growth (ie, fetal growth restriction). However, this approach is subject to limitation as most newborns labeled small-for-gestational age are constitutionally, not pathologically, small. Incorporating repeated ultrasound measures to examine fetal growth trajectories may help distinguish pathologic deviations in growth from normal variability, beyond a simple definition of small-for-gestational age. OBJECTIVE: This study aimed to characterize phenotypes of growth using ultrasound trajectories of fetal growth among small-for-gestational-age births. STUDY DESIGN: This study identified and described trajectories of fetal growth among small-for-gestational-age births (<10th percentile weight for gestational age; n=245) in the LIFECODES Fetal Growth Study using univariate and multivariate trajectory modeling approaches. Available ultrasound measures of fetal growth (estimated fetal weight, head circumference, abdominal circumference, and femur length) from health records were abstracted. First, univariate group-based trajectory modeling was used to define trajectories of estimated fetal weight z scores during gestation. Second, group-based multi-trajectory modeling was used to identify trajectories based on concurrent measures of head circumference, abdominal circumference, and femur length z scores. Last, how these trajectories were related to patient demographics, pregnancy characteristics, and birth outcomes compared with those observed among appropriate-for-gestational-age controls was described. RESULTS: Of note, 3 univariate trajectories of estimated fetal weight and 4 multivariate trajectories of fetal growth among small-for-gestational-age births were identified. In our univariate approach, infants with the smallest estimated fetal weight trajectory throughout pregnancy had poorer outcomes, including the highest risk of neonatal intensive care unit admission. The remaining univariate trajectory groups did not have an elevated risk of adverse birth outcomes relative to appropriate-for-gestational-age controls. In our multivariate approach, 2 groups at increased or moderately increased risk of neonatal intensive care unit admission were identified, including infants that remained extremely small for all parameters throughout pregnancy and those who had disproportionately smaller femur length and abdominal circumference compared with head circumference. The remaining multivariate trajectory groups did not have an elevated risk of adverse birth outcome relative to appropriate-for-gestational-age controls. CONCLUSION: Latent class group-based trajectory modeling applied to ultrasound measures of fetal growth may help distinguish pathologic vs constitutional growth profiles among newborns born small-for-gestational age. Although trajectories cannot be fully characterized until delivery, limiting the direct clinical application of these methods, they may still contribute to the development of approaches for separating growth restriction from constitutional smallness.

Early developmental profiles of sensory features and links to school-age adaptive and maladaptive outcomes: A birth cohort investigation.

Sensory-based subtypes among autistic children have been well documented, but little is known about longitudinal sensory subtypes beyond autistic populations. This prospective study aimed to identify subtypes based on trajectories of parent-reported sensory features measured at 6-19 months, 3-4, and 6-7 years of age among a community-based birth cohort (N = 1,517), and to examine their associations with school-age clinical and adaptive/maladaptive outcomes on a subset sample (N = 389). Latent class growth analysis revealed five trajectory subtypes varying in intensity and change rates across three sensory domains. In contrast to an Adaptive-All Improving subtype (35%) with very low sensory features and overall better school-age outcomes, an Elevated-All Worsening subtype (3%), comprised of more boys and children of parents with less education, was associated with most elevated autistic traits and poorest adaptive/maladaptive outcomes. Three other subtypes (62% in total) were generally characterized by stable or improving patterns of sensory features at mild to moderate levels, and challenges in certain outcome domains. Our findings indicate that characterizing children based on early sensory trajectories may contribute to earlier detection of subgroups of children with sensory challenges who are more likely to experience developmental challenges by school age, followed by early targeted interventions for improved long-term outcomes.

Association Between the Risk of Hyperuricemia and Changes in Branched-Chain Amino Acids Intake Over Twelve Years: A Latent Class Trajectory Analysis From the China Health and Nutrition Survey, 1997-2009.

Objective: This study aims to identify dietary branched-chain amino acids (BCAA) consumption trajectories in Chinese adults and to evaluate their association with the risk of hyperuricemia (HU). Methods: Cohort data from the China Health and Nutrition Survey 1997-2009 were adopted in this research. A total of 6,810 participants aged ≥18 years were included in this study. Participants were designated into four subgroups on basis of the trajectories of dietary BCAA consumption. Cox proportional hazards models were performed to discuss the relationships between varied trajectories and the risk of HU after adjusting potential confounders. The intermediary effect of differential blood indexes between the trajectories and the risk of HU was explored with mediation analysis. Results: Four distinct trajectory groups of dietary BCAA consumption were identified. Compared with the low stable trajectory group, high to low trajectory group was greatly related to an increased risk of HU (HR 1.35 (95% CI 1.03 to 1.79)) with modification for covariates. Total cholesterol (TC), hemoglobin A1c (HbA1c), fasting blood glucose (FBG), and triglyceride (TG) partially regulated trajectories and HU. Conclusion: Gradually decreasing dietary BCAA intake increased the risk of HU, which is, at least, partially mediated by TC, HbA1c, FBG, and TG levels.

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.

Mental and physical health among the French population before and during the first and second COVID-19 lockdowns: Latent class trajectory analyses using longitudinal data.

BACKGROUND: The French government issued national COVID-19-related confinement and stay-at-home orders depending on different epidemic levels in a bid to stem the coronavirus pandemic and its resurgence. The long-term impact of lockdown measures on the general population may vary. We aimed to identify and characterize self-reported mental and physical health trajectories in the French population from pre-lockdown to the first and second COVID-19 lockdowns and to identify factors associated with health status variation patterns. METHODS: We did a secondary analysis of the MAVIE cohort in France. Volunteers of this national cohort were recruited between November 2014 and December 2019, and information was collected at recruitment (pre-lockdown), April-May 2020 (the first lockdown), and October-December 2020 (the second lockdown). Latent class mixed models were built to identify distinct anxiety (as measured by GAD-7) and depressive (as measured by PHQ-9) symptoms, and self-perceived mental and physical health trajectories. Factors associated with status variation were identified by logistic or multinomial regression. RESULTS: A total of 613 participants with data in all three data collection waves were included. Respondents spent almost half as much time on traditional media, websites and social media during the second lockdown as during the first. Mean anxiety scores were 1.96, 2.37 and 2.82 at pre-lockdown, and the first and second lockdowns, respectively. Mean depressive scores were 3.12, 3.36 and 3.95, respectively. Latent class mixed models fitted two and three distinct trajectory classes respectively for anxiety symptoms ('no pre-pandemic anxiety, slightly increase', 58.9%; 'consistently fair', 41.1%) and depressive symptoms ('consistently very low', 34.6%; 'consistently low', 56.1%; 'increasing and clinically significant at the second lockdown', 9.3%), and four classes for self-perceived mental and physical health. Females were more likely to belong to trajectories of the most vulnerable one as regard to the symptoms of anxiety and depression, and self-perceived mental and physical health. The younger participants were also more vulnerable to anxiety symptoms and those with a clinical diagnosis or a positive COVID-19 test for the participant or relatives were more likely to belong to vulnerable trajectories for depressive symptoms and self-perceived mental health. CONCLUSION: A continuing increase in the mean scores of anxiety and depression symptoms was observed throughout the two lockdown periods in France. Further analyses revealed distinct patterns with a small fraction of volunteers experiencing worsening mental and physical health symptoms. This vulnerable small part of the population requires targeted support.

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.

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.