Multivariate Longitudinal Models Research Articles

Trends in Gaps of Care for Patients With Congenital Heart Disease: Implications for Social Determinants of Health and Child Opportunity Index.

Lifelong continuity of care is essential for patients with congenital heart disease (CHD) to maximize health outcomes; unfortunately, gaps in care (GIC) are common. Trends in GIC and of social determinants of health factors contributing to GIC are poorly understood. This retrospective cohort study included patients with CHD, aged 0 to 34 years, who underwent surgery between January 2003 and May 2020, followed up at a pediatric subspeciality hospital. Patients were categorized as having simple, moderate, and complex CHD based on 2018 American Heart Association and American College of Cardiology guidelines. Social determinants of health, such as race, ethnicity, language, insurance status, and Child Opportunity Index, based on home address zip code, were analyzed. Of 2012 patients with CHD, a GIC of ≥3 years was identified in 56% (n=1119). The proportion of patients with GIC per year increased by 0.51% (P<0.001). Multivariable longitudinal models showed that the odds of GIC were higher for patients who were ≥10.5 years old, had simple CHD, lived out of state, lived farther from care site, received public insurance, had less protection with additional insurance plans, and with low Child Opportunity Index. A separate model for patients with only moderate/complex CHD showed similar findings. Race and ethnicity were not associated with the odds of experiencing GIC over time. GIC have increased over time for patients with CHD. Social determinants of health, like insurance, access, and neighborhood opportunity, are key risk factors for increasing GIC. Efforts to reduce GIC in patients with CHD should focus on addressing the impact of specific social determinants of health.

Simultaneous coefficient clustering and sparsity for multivariate mixed models

In many applications of multivariate longitudinal mixed models, it is reasonable to assume that each response is informed by only a subset of covariates. Moreover, one or more responses may exhibit the same relationship to a particular covariate e.g., if they are capturing the same underlying aspect of an individual physical, mental, and emotional health. To address the above challenges, we propose a method for simultaneous clustering and variable selection of fixed effect coefficients in multivariate mixed models. We achieve this in a computationally scalable manner via a composite likelihood approach: separate mixed models are first fitted to each response, after which the model estimates are combined into a single quadratic form resembling a multivariate Wald statistic. We then augment this with fusion- and sparsity-inducing penalties based on broken adaptive ridge regression. Simulation studies demonstrate that the proposed composite quadratic estimator is similar to or better than several existing techniques for fixed effects selection in (univariate) mixed models while being computationally much more efficient. We apply the proposed method to longitudinal panel data from Australia to quantify how an individual’s overall health, assessed via a set of eight composite scores, evolves as a function of various demographic and lifestyle variables.

Low CD4 counts predict excessive weight gains during first-line treatment for HIV.

Weight gain is common after antiretroviral initiation, especially among females, those of black race and lower baseline CD4, although this may potentially be due to lower baseline weight. Use of tenofovir disoproxil fumarate or efavirenz can suppress weight gain. Data were pooled from the ADVANCE (n = 1053), NAMSAL (n = 613) and WHRI001 (n = 536) trials investigating first-line regimen. Week 96 weight and body mass index (BMI) was stratified by baseline CD4. Multivariable models of weight change and incident obesity (BMI ≥30 kg/m2) were adjusted for baseline CD4, age, sex, tenofovir disoproxil fumarate, efavirenz, baseline BMI and trial. Participants across all treatment arms experienced weight gain from baseline to week 96, with baseline CD4 count, baseline HIV RNA, tenofovir alafenamide and dolutegravir use, and female sex significant predictors. Mean unadjusted weight change was highest with CD4 < 100 (+8.6 kg; SD = 8.2) and lowest with CD4 ≥ 350 (+3.0 kg; SD = 6.5). This weight gain in CD4 < 100 was highest for participants on tenofovir alafenamide-inclusive treatment, such that absolute weight at week 96 was highest in the CD4 < 100 group. Although not statistically significant, obesity rate (BMI ≥ 30 kg/m2) in those taking TAF/FTC + DTG with CD4 < 100 overtook that seen in CD4 ≥ 350, despite lower baseline obesity prevalence. The unadjusted findings were corroborated in multivariable longitudinal models. Participants with low CD4 may demonstrate significant 'overshoot' weight gain, in addition to 'return to health', with a trend towards increased risk of obesity when initiated on TAF/FTC + DTG. Use of tenofovir disoproxil fumarate and efavirenz were associated with smaller weight gains. Effective weight management strategies are needed, especially for individuals with low baseline CD4.

Bayesian and deep-learning models applied to the early detection of ovarian cancer using multiple longitudinal biomarkers.

Ovarian cancer is the most lethal of all gynecological cancers. Cancer Antigen 125 (CA125) is the best-performing ovarian cancer biomarker which however is still not effective as a screening test in the general population. Recent literature reports additional biomarkers with the potential to improve on CA125 for early detection when using longitudinal multimarker models. Our data comprised 180 controls and 44 cases with serum samples sourced from the multimodal arm of UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). Our models were based on Bayesian change-point detection and recurrent neural networks. We obtained a significantly higher performance for CA125-HE4 model using both methodologies (AUC 0.971, sensitivity 96.7% and AUC 0.987, sensitivity 96.7%) with respect to CA125 (AUC 0.949, sensitivity 90.8% and AUC 0.953, sensitivity 92.1%) for Bayesian change-point model (BCP) and recurrent neural networks (RNN) approaches, respectively. One year before diagnosis, the CA125-HE4 model also ranked as the best, whereas at 2 years before diagnosis no multimarker model outperformed CA125. Our study identified and tested different combination of biomarkers using longitudinal multivariable models that outperformed CA125 alone. We showed the potential of multivariable models and candidate biomarkers to increase the detection rate of ovarian cancer.

Clinical outcomes in neovascular age-related macular degeneration: a cohort study of patients with care delay due to the COVID-19 pandemic

The COVID-19 pandemic has led to both intentional and unintentional care delay among age-related neovascular macular degeneration (nvAMD) patients. Prior studies have demonstrated that patients who discontinue nvAMD treatment for prolonged intervals are at high risk for vision loss, but less is known regarding shorter-term delay, such as during the height of the pandemic. Previous studies have looked at COVID-19 related delay in care and have shown a loss of visual acuity (VA) among these patients, but studies are limited by short follow-up or insufficient comparisons. This was an observational cohort study of nvAMD patients from March 1, 2019, through July 1, 2021, who experienced care delay. VA was modeled using a linear longitudinal mixed-effects model comparing historic data pre-lockdown to data post-lockdown. Covariates included baseline anatomic variables, demographic variables, and time intervals (treatment interval, delay interval). Secondary anatomic and treatment outcomes were modeled using a multilevel binary logistic regression model. 163 eyes among 116 patients were included. Initial longitudinal mixed-effects models found that although overall VA decreased at a yearly rate, when comparing pre-lockdown and post-lockdown time periods, VA slopes were not statistically different. Single-covariate longitudinal models showed that age, sex, and delay interval significantly affected VA slope. The multivariate longitudinal model found that a longer delay interval significantly decreased rate of VA loss. Multilevel binary logistic regression models showed a significant increase in odds of anti-VEGF treatment, presence of subretinal fluid, and macular hemorrhages in the post-lockdown period. Overall, when compared to historic data, rate of VA loss among our cohort did not vary significantly in pre-versus post-lockdown time periods, although treatment and anatomic variables did worsen post-lockdown suggesting that patients may be appropriately delayed but this comes at the risk of increased need for treatment.

Influence of mental health on information seeking, risk perception and mask wearing self-efficacy during the early months of the COVID-19 pandemic: a longitudinal panel study across 6 U.S. States

BackgroundUnderstanding factors that influence information seeking, assessment of risk and mitigation behaviors is critical during a public health crises. This longitudinal study examined the influence of self-reported mental health during the early months of the COVID-19 pandemic on information seeking, risk perception and perceived mask wearing ability. Mental health screener items included fear, anger, and hopelessness in addition to avoidance, diminished functional ability and global distress. Theoretical models inform hypotheses linking mental health items and outcomes.MethodsThe research employed a longitudinal 6-state 3-wave online panel survey, with an initial sample of 3,059 participants (2,232 included in longitudinal analyses). Participants roughly represented the states’ age, race, ethnicity, and income demographics.ResultsWomen, those who identified as Hispanic/Latinx, Black Americans and lower income participants reported higher overall rates of distress than others. Information seeking was more common among older persons, Democrats, retirees, those with higher education, and those who knew people who had died of COVID-19. Controlling for such demographic variables, in multivariable longitudinal models that included baseline mental health measures, distress and fear were associated with increased information seeking. Distress and fear were also associated with increased risk perception, and feelings of hopelessness were associated with lower reported mask-wearing ability.ConclusionsResults advance understanding of the role mental health can play in information seeking, risk perception and mask wearing with implications for clinicians, public health practitioners and policy makers.

Bayesian multivariate longitudinal model for immune responses to Leishmania: A tick-borne co-infection study.

While many Bayesian state-space models for infectious disease processes focus on population infection dynamics (eg, compartmental models), in this work we examine the evolution of infection processes and the complexities of the immune responses within the host using these techniques. We present a joint Bayesian state-space model to better understand how the immune system contributes to the control of Leishmania infantum infections over the disease course. We use longitudinal molecular diagnostic and clinical data of a cohort of dogs to describe population progression rates and present evidence for important drivers of clinical disease. Among these results, we find evidence for the importance of co-infection in disease progression. We also show that as dogs progress through the infection, parasite load is influenced by their age, ectoparasiticide treatment status, and serology. Furthermore, we present evidence that pathogen load information from an earlier point in time influences its future value and that the size of this effect varies depending on the clinical stage of the dog. In addition to characterizing the processes driving disease progression, we predict individual and aggregate patterns of Canine Leishmaniasis progression. Both our findings and the application to individual-level predictions are of direct clinical relevance, presenting possible opportunities for application in veterinary practice and motivating lines of additional investigation to better understand and predict disease progression. Finally, as an important zoonotic human pathogen, these results may support future efforts to prevent and treat human Leishmaniosis.

Multivariate disease progression modeling with longitudinal ordinal data.

Disease modeling is an essential tool to describe disease progression and its heterogeneity across patients. Usual approaches use continuous data such as biomarkers to assess progression. Nevertheless, categorical or ordinal data such as item responses in questionnaires also provide insightful information about disease progression. In this work, we propose a disease progression model for ordinal and categorical data. We built it on the principles of disease course mapping, a technique that uniquely describes the variability in both the dynamics of progression and disease heterogeneity from multivariate longitudinal data. This extension can also be seen as an attempt to bridge the gap between longitudinal multivariate models and the field of item response theory. Application to the Parkinson's progression markers initiative cohort illustrates the benefits of our approach: a fine-grained description of disease progression at the item level, as compared to the aggregated total score, together with improved predictions of the patient's future visits. The analysis of the heterogeneity across individual trajectories highlights known disease trends such as tremor dominant or postural instability and gait difficulties subtypes of Parkinson's disease.

GAMLSS for Longitudinal Multivariate Claim Count Models

By generalizing traditional regression frameworks, generalized additive models for location, scale, and shape (GAMLSSs) allow parametric or semiparametric modeling of one or more parameters of distributions that are not members of the linear exponential family. Consequently, these GAMLSS approaches offer an interesting theoretical framework to allow the use of several potentially helpful distributions in actuarial science. GAMLSS theory is coupled with longitudinal approaches for counting data because these approaches are essential to predictive pricing models. Indeed, they are mainly known for modeling the dependence between the number of claims from the contracts of the same insured over time. Considering that the models’ cross-sectional counterparts have been successfully applied in actuarial work and the importance of longitudinal models, we show that the proposed approach allows one to quickly implement multivariate longitudinal models with nonparametric terms for ratemaking. This semiparametric modeling is illustrated using a dataset from a major insurance company in Canada. An analysis is then conducted on the improvement of predictive power that the use of historical data and nonparametric terms in the modeling allows. In addition, we found that the weight of past experience in bonus–malus predictive premiums analysis is reduced in comparison with a parametric model and that this method could help for continuous covariate segmentation. Our approach differs from previous studies because it does not use any simplifying assumptions as to the value of the a priori explanatory variables and because we have carried out a predictive pricing integrating nonparametric terms within the framework of the GAMLSS in an explicit way, which makes it possible to reproduce the same type of study using other distributions.

Vitamin D and Probability of Developmental Disorders among Perinatally HIV-Affected and Unaffected Ugandan Children.

We tested the hypothesis that vitamin D deficiency (VDD) is associated with higher developmental disorder probability in 604 children with perinatal HIV infection (CPHIV, n = 199), HIV exposed and uninfected (CHEU, n = 196), and HIV unexposed uninfected (CHUU, n = 201). Children at 6-18 years old and their adult caregivers were assessed at enrollment, 6, and 12-month follow-ups. Serum 25-hydroxyvitamin-D (25OHD) levels in children quantified per the NHANES protocol were used to define VD categories as VDD (25OHD < 20 ng/mL), VD insufficient (VDI, 20 ≤ 25OHD ≤ 25 ng/mL), and VD sufficient (VDS = reference group if 25OHD > 25 ng/mL). Perinatal HIV status per DNA polymerase chain reaction/HIV rapid diagnostic tests included: CPHIV, CHEU, and CHUU. Developmental stage was defined as pre-adolescent (age < 11) vs. adolescent (age ≥ 11) years. Caregiver responses to standardized questions from Behavioral Assessment System for Children, Third Edition (BASC-3), were used to calculate probability scores for four disorders, namely: autism (ASD), attention deficit & hyperactivity (ADHD), emotional behavioral disorder (EBD), functional impairment (FI), and resiliency at 0, 6 and 12 months. Multivariable longitudinal models estimated VD-associated standardized mean difference (SMD) and corresponding 95% confidence intervals (95% CI) in respective probability scores in Statistical Analysis Software (v.9.4). Baseline VDD vs. VDS predicted higher probability scores of moderate clinical importance for ASD, ADHD, EBD, and higher FI among pre-adolescents (SMD = 0.32 to 0.40, 95% CI: 0.00 to 0.74). VDD was not associated with resiliency or any developmental disorders among adolescents. VDD predicted higher developmental disorder and FI scores over 12 months in a developmental stage-dependent manner. This relationship requires further understanding to appropriately target future interventions.

Association of Rates of Ganglion Cell and Inner Plexiform Thinning With Development of Glaucoma in Eyes With Suspected Glaucoma

In eyes with suspected glaucoma, it is clinically relevant to find diagnostic tests for the risk of development of perimetric glaucoma. To investigate the association between rates of ganglion cell/inner plexiform layer (GCIPL) and circumpapillary retinal nerve fiber layer (cpRNFL) thinning and the development of perimetric glaucoma in eyes with suspected glaucoma. This observational cohort study used data collected in December 2021 from a tertiary center study and a multicenter study. Participants with suspected glaucoma were followed up for 3.1 years. The study was designed in December 2021 and finalized in August 2022. Development of perimetric glaucoma was defined as having 3 consecutive results showing abnormal visual fields. Using linear mixed-effect models, rates of GCIPL were compared between eyes with suspected glaucoma that did and did not develop perimetric glaucoma. A joint longitudinal multivariable survival model was used to investigate the performance of rates of GCIPL and cpRNFL thinning in predicting the risk of developing perimetric glaucoma. Rates of GCIPL thinning and hazard ratio (HR) of developing perimetric glaucoma. Among a total of 462 participants, the mean (SD) age was 63.3 (11.1) years, and 275 patients (60%) were female. Of 658 eyes, 153 eyes (23%) developed perimetric glaucoma. The mean rates of GCIPL thinning were faster in eyes that developed perimetric glaucoma (-1.28 vs -0.66 μm/y for minimum GCIPL thinning; difference, -0.62; 95% CI, -1.07 to -0.16; P = .02). Based on the joint longitudinal survival model, every 1-μm/y faster rate of minimum GCIPL and rate of global cpRNFL thinning were associated with a 2.4 and 1.9 higher risk of developing perimetric glaucoma, respectively (HR, 2.4; 95% CI, 1.8 to 3.2, and HR, 1.99; 95% CI, 1.76 to 2.22, respectively; P < .001). Among the predictive factors, African American race (HR, 1.56; 95% CI, 1.05 to 2.34; P = .02), male sex (HR, 1.47; 95% CI, 1.02 to 2.15; P = .03), 1-dB higher baseline visual field pattern standard deviation (HR, 1.73; 95% CI, 1.56 to 1.91; P < .001), and 1-mm Hg higher mean intraocular pressure during follow-up (HR, 1.11; 95% CI, 1.05 to 1.17; P < .001) were associated with higher risk of developing perimetric glaucoma. This study found that faster rates of GCIPL and cpRNFL thinning were associated with higher risks of developing perimetric glaucoma. Rates of cpRNFL thinning and specifically GCIPL thinning may be useful measures for monitoring eyes with suspected glaucoma.

Previous Syphilis Not Associated With Neurocognitive Outcomes in People Living With Human Immunodeficiency Virus in Ontario, Canada.

Background About 40% to 60% of people living with human immunodeficiency virus (HIV) experience neurocognitive impairments, irrespective of antiretroviral status. We hypothesized that a history of syphilis or neurosyphilis would be associated with worse neurocognitive outcomes in this population. Methods Among health care–engaged people living with HIV in Ontario older than 16 years enrolled in the OHTN Cohort Study, neurocognitive outcomes were as follows: (1) self-reported Medical Outcome Study–HIV Health Survey 4-item cognitive scale; (2) average T score summary scores based on objective neuropsychological testing of complex attention, speed of processing, and learning/memory; and (3) global deficit score dichotomized into impaired/unimpaired neurocognitive status. Syphilis history was determined by laboratory data or chart review. Univariable and multivariable generalized linear mixed models assessed the association between each of: syphilis, number of episodes of syphilis, and years since syphilis diagnosis with these neurocognitive outcomes controlling for age, sex, race, education, income, years of HIV, nadir and most recent CD4 count, most recent HIV viral load, substance use, depression, and number of prior neurocognitive tests. Results Of 1288 eligible participants, 218 (16.9%) had a history of syphilis at baseline and an additional 53 were diagnosed during follow up for a total of 271 (21.0%) at the most recent visit. Of those with past infection at baseline, 179 (82.1%) had 1 and 39 (17.9%) had 2 or more episodes of syphilis. In longitudinal multivariable models, we observed no relationship between syphilis diagnosis or years since syphilis diagnosis and any of the neurocognitive outcomes. Conclusions In this sample, prior syphilis was not associated with worse neurocognitive outcomes over time according to self-reported scales or objective neuropsychological testing.

Assessing the temporal stability of psychological constructs: An illustration of Type D personality, anxiety and depression

Various methods exist to assess the temporal stability of psychological constructs. In this paper we discuss common methods based on a review of the personality traits negative affectivity and social inhibition. Most methods ignore the non-normal distributions and measurement error in the questionnaire item scores. We illustrate how to handle these issues using three longitudinal latent variable models. We further highlight the importance of testing the often overlooked assumption of longitudinal measurement invariance. Lastly, we apply several longitudinal measurement invariance models, univariate and multivariate latent growth curves models, and latent trait-state occasions models to data from 2625 cancer survivors, to assess the temporal stability of negative affectivity, social inhibition, depression, anxiety, across a period of four years.

Assessing related factors to fasting blood sugar and glycosylated hemoglobin in patients with type 2 diabetes simultaneously by a multivariate longitudinal marginal model

The multivariate marginal model can be used to simultaneously examine the factors affecting both FBS and HbA1c using longitudinal data. The model fitted to multivariate longitudinal data should prevent redundant parameter estimation in order to have greater efficiency. In this study, a multivariate marginal model is used to simultaneously investigate the factors affecting both FBS and HbA1c with longitudinal data for patients with type 2 diabetes in Northern Iran. The present research is a retrospective cohort study. Overall, 500 medical records with complete information were reviewed. The multivariate marginal model is used to determine the factors associated with FBS and HbA1c using longitudinal data. Data have been analyzed in R-3.4.0 using ‘mmm2’ package. Given that the coefficients for the interactions of rtype with the intercept, time, family history of diabetes, history of hypertension, history of smoking, insulin therapy, systolic/diastolic blood pressure and duration of disease at first visit are significantly different from zero (P < 0.05), the effect of the independent variables on the two response variables is different and different coefficients should be used for each. Therefore, the interactions of these variables with rtype are kept in the final model. The coefficients for the interactions of rtype with sex, age at first visit, history of high cholesterol, and weight are not significantly different from zero (P > 0.05), indicating that their effect on the two response variables is similar and only one coefficient should be used for each. We examined the similarity of coefficients when fitting the longitudinal multivariate model for the relationship between FBS/HbA1c and sex, age, history of high blood cholesterol, and body weight. If an independent variable has similar effects on both responses, only one coefficient should be estimated, which will increase the efficiency of the model and the reliability of the results.

Perceptions of societal ageism and declines in subjective memory during the COVID-19 pandemic: Longitudinal evidence from US adults aged ≥55 years.

The cognitive health of older adults since the COVID‐19 pandemic onset is unclear, as is the potential impact of pandemic‐associated societal ageism on perceived cognition. We investigated associations between perceptions of societal ageism and changes in subjective memory over a 10‐month period during the COVID‐19 pandemic. We collected longitudinal data from monthly online questionnaires in the nationwide COVID‐19 Coping Study of US adults aged ≥55 from April 2020 to January 2021 (N = 4444). We analyzed the data using multivariable longitudinal multilevel models. We identified an overall decline in subjective memory, especially in the initial months of the pandemic. Adults who perceived that societal respect for older adults decreased during the pandemic experienced more rapid declines in their subjective memory. These findings suggest that aging adults perceived a decline in their memory, especially during the initial months of the COVID‐19 pandemic. Societal interventions to combat ageism may help improve subjective memory and could decrease risk for cognitive decline among middle‐aged and older adults.

Anti-Citrullinated Protein Antibody Titers Are Independently Modulated by Both Disease Activity and Conventional or Biologic Anti-Rheumatic Drugs.

This study aimed to analyze the factors that influence anti-citrullinated protein antibody (ACPA) titers in a seropositive early arthritis (EA) population under non-protocolized treatment with disease-modifying anti-rheumatic drugs (DMARDs). A total of 130 ACPA-positive patients from the PEARL (Princesa Early Arthritis Longitudinal) study were studied along a 5-year follow-up. Sociodemographic, clinical, and therapeutic variables, along with serum samples, were collected at five visits by protocol. Anti-cyclic citrullinated peptide 2 (CCP2) ACPA titers were measured by ELISA. The effect of different variables on anti-CCP2 titers was estimated using longitudinal multivariate analysis models, nested by visit and patient. Data from 471 visits in 130 patients were analyzed. A significant decrease in anti-CCP2 titers was observed at all time-points, compared to baseline, following the decline of disease activity. In the multivariate analysis, active or ever smoking was significantly associated with the highest anti-CCP2 titers while reduction in disease activity was associated with titer decline. After adjusting for these variables, both conventional synthetic (cs) and biologic (b) DMARDs accounted for the decline in anti-CCP2 titers as independent factors. Conclusion: In patients with EA, an early and sustained reduction in ACPA titers can be detected associated with the decline in disease activity, irrespective of the treatment used.

Trauma, Mental Health Distress, and Infectious Disease Prevention Among Women Recently Released From Incarceration.

BackgroundU.S. women recently released from incarceration experience significantly higher rates of trauma and exacerbation of mental health conditions, and the period following release has been identified as a window of heightened risk for mental health distress and human immunodeficiency virus (HIV), sexually transmitted infections (STI) and hepatitis C (HCV) transmissions. Despite these vulnerabilities, and an urgent need for supports, optimal engagement strategies remain unclear. WORTH Transitions is a program made up of two evidence-based interventions focused on improving the health of women returning to the community from incarceration with substance use disorders. Combining the two was designed to reduce HIV/STIs/HCV risks and increase overall health treatment engagement using a community health worker led intervention.MethodsWe examined associations between trauma, mental health symptomology, and HIV/STI/HCV outcomes among women who engaged in the WORTH Transitions intervention (N = 206) Specifically, bivariate and longitudinal multivariate models were created to examine associations between trauma and mental health distress (defined as depressive and PTSD symptoms), on (1) types of engagement in HIV/STIs/HCV prevention and behavioral health services; and (2) HIV/STIs/HCV risk outcomes. The women who engaged in the intervention were 18 years and older and some were White, Black and other racial or ethnic minority.ResultsPTSD symptomology and being a Black or indigenous woman of color was significantly (p = 0.014) associated with individual or group session engagement. Neither trauma nor PTSD symptoms were associated with higher HIV/STIs/HCV risks. Instead, relative to those who did not engage in HIV/STI/HCV risky behaviors, PTSD symptomology (p = 0.040) was associated with more than 3-fold increase in the probability of being lost to follow up (relative risk ratio = 3.722).ConclusionGiven the impact of PTSD-related symptoms on driving both engagement in HIV/STIs/HCV prevention services and intervention attrition among women leaving incarceration, physical and behavioral health interventions must be both overtly trauma- and mental health-informed. As was the case with WORTH Transitions, physical and behavioral health services for this population must include intentional and active support of the forms of treatment participants endorse to ensure maximal engagement.

Adverse childhood experiences, sexual victimization, and suicide ideation and attempts: A longitudinal path analysis spanning 22 years.

Suicide is an urgent public health problem. The purpose of this study was to determine if adverse childhood experiences (ACEs) increased the risk for suicide ideations and attempts approximately 22 years later, and if sexual victimization (SV) in adulthood mediated these associations. Prospective data from a nationally representative sample of 10,914 participants in the National Longitudinal Study of Adolescent to Adult Health were used to test direct associations of ACEs (physical, sexual, and emotional abuse, neglect, family history of suicide attempts, and parental death, alcoholism, and incarceration) with suicide ideation and attempts and their indirect effects through sexual victimization in adulthood. All but one ACE significantly predicted increased odds of making a suicide attempt. Physical, sexual, and emotional abuse as well as family history of suicide attempts and parental incarceration predicted seriously considering suicide. All forms of childhood abuse and family history of suicide attempts predicted increased odds of sexual victimization. In multivariate longitudinal models controlling for age, race, and gender, the odds of seriously considering suicide and making a suicide attempt increased as the number of ACEs increased. Experiencing two or more ACEs also was associated with an increased likelihood of experiencing sexual victimization in adulthood, which in turn mediated the effects of ACEs on suicide ideation but not suicide attempts. Findings indicate that reducing ACEs is an important strategy for suicide prevention not only due to ACEs' direct association with suicide ideation and attempts, but also due to their indirect association via subsequent sexual victimization. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Serum lipid trajectories in the years before a lymphoma diagnosis

We conducted a case-control study of patients from the Clinical Practice Research Datalink in the United Kingdom to describe the trajectories of serum lipid in the years before a diagnosis of lymphoma. Study participants had at least one cholesterol measurement. Multilevel, multivariable linear longitudinal models were fit to examine the adjusted trajectories of serum lipid levels in the years before lymphoma diagnosis. Overall, 11,969 cases of non-Hodgkin lymphoma, 473 of Hodgkin lymphoma, and 61,894 controls were selected. Mean cholesterol levels in the years before the index date showed a more pronounced decrease in the 4 years before lymphoma diagnosis than in controls. Triglycerides levels were unrelated to case status. This research is the first to replicate the results of a similar study conducted in the United States while adjusting for more potential confounders. The newly described different behavior of cholesterol and triglycerides suggests a potential role of cholesterol in lymphomagenesis.

Dynamic modelling of corporate credit ratings and defaults

In this article, we propose a longitudinal multivariate model for binary and ordinal outcomes to describe the dynamic relationship among firm defaults and credit ratings from various raters. The latent probability of default is modelled as a dynamic process which contains additive firm-specific effects, a latent systematic factor representing the business cycle and idiosyncratic observed and unobserved factors. The joint set-up also facilitates the estimation of a bias for each rater which captures changes in the rating standards of the rating agencies. Bayesian estimation techniques are employed to estimate the parameters of interest. Several models are compared based on their out-of-sample prediction ability and we find that the proposed model outperforms simpler specifications. The joint framework is illustrated on a sample of publicly traded US corporates which are rated by at least one of the credit rating agencies S&amp;P, Moody's and Fitch during the period 1995–2014.