Subgroup Of Individuals Research Articles

Meta-analysis of the association of prosaposin polymorphisms rs4747203 and rs885828 with risk of Parkinson's disease.

Previous research has established a connection between polymorphisms rs4747203 and rs885828 in the prosaposin (PSAP) gene and an increased risk of Parkinson's disease (PD). However, other studies have found no significant difference in risk compared to the general population. To evaluate the current evidence linking rs4747203 and rs885828 to PD risk, we conducted a comprehensive search of PubMed, the Web of Science, Embase, and the Cochrane Library for relevant studies up until May 2023. In addition, we analyzed data from the publicly available "PD Variant Browser". We performed a meta-analysis using Stata 17.0 to synthesize the findings from the selected studies. Our meta-analysis, which included data from six published studies and the public database, revealed no significant association between PD risk and either rs4747203 [OR (95% CI) = 0.99 (0.93-1.05), I2 = 90.3%, P = 0.635] or rs885828 [OR (95% CI) = 1.01 (0.95-1.07), I2 = 90.7%, P = 0.773]. These results remained consistent when examining subgroups of individuals within or outside of Asia. The available evidence does not support an association between the genotype at rs4747203 or rs885828 and the risk of PD.

Novel subgroups of obesity and their association with outcomes: a data-driven cluster analysis

BackgroundObesity is associated with various complications and decreased life expectancy, and substantial heterogeneity in complications and outcomes has been observed. However, the subgroups of obesity have not yet been clearly defined. This study aimed to identify the subgroups of obesity especially those for target of interventions by cluster analysis.MethodsIn this study, an unsupervised, data-driven cluster analysis of 9,494 individuals with obesity (body mass index ≥ 35 kg/m2) was performed using the data of ICD-10, drug, and medical procedure from the healthcare claims database. The prevalence and clinical characteristics of the complications such as diabetes in each cluster were evaluated using the prescription records. Additionally, renal and life prognoses were compared among the clusters.ResultsWe identified seven clusters characterised by different combinations of complications and several complications were observed exclusively in each cluster. Notably, the poorest prognosis was observed in individuals who rarely visited a hospital after being diagnosed with obesity, followed by those with cardiovascular complications and diabetes.ConclusionsIn this study, we identified seven subgroups of individuals with obesity using population-based data-driven cluster analysis. We clearly demonstrated important target subgroups for intervention as well as a metabolically healthy obesity group.

Characterizing the clinical subgroups of individuals who present to the emergency department for alcohol-related harms in Ontario, Canada: A latent class analysis

Alcohol-related emergency department (ED) visits are common and associated with adverse clinical outcomes, including premature mortality. This population-based retrospective cohort study identified clinically distinct subgroups of individuals who experience alcohol-related ED visits and characterized differences in the risk of adverse outcomes between them. 73,658 individuals who experienced an alcohol-related ED visit in Ontario, Canada between 2017 and 2018 were identified. Latent class analysis (LCA) revealed five clinically distinct subgroups within the overall cohort. These subgroups followed a severity gradient from low-frequency service use for acute intoxication to high-frequency service use for alcohol use disorder (AUD) and related comorbidities. Relative to those presenting for acute intoxication, those presenting for AUD and comorbidities had a much higher risk of hospital admission (adjusted odds ratio [aOR]: 8.26, 95 % confidence interval [CI]: 7.81–8.75) and post-discharge mortality (adjusted hazard ratio [aHR]: 3.07, 95 % CI: 2.81–3.37). There was a subgroup of individuals with a history of high frequency alcohol-related health service use who were at the highest risk of experiencing another alcohol-related ED visit after the index event (aHR: 4.76, 95 % CI: 4.55–4.99). Individuals who experience alcohol-related ED visits are not a homogenous population, but a constellation of subgroups with different clinical characteristics and risk of adverse outcomes.

Statistical matching using kernel canonical correlation analysis and super-organizing map

The potential to study and improve different aspects of our lives is ever growing thanks to the abundance of data available in today’s modern society. Scientists and researchers often need to analyze data from different sources; the observations, which only share a subset of the variables, cannot always be paired to detect common individuals. This is the case, for example, when the information required to study a certain phenomenon is coming from different sample surveys. Statistical matching is a common practice to combine these data sets. In this paper, we investigate and extend to statistical matching two methods based on Kernel Canonical Correlation Analysis (KCCA) and Super-Organizing Map (Super-OM). These methods are designed to deal with various variable types, sample weights and incompatibilities among categorical variables. In the first case, we use KCCA, a non-linear extension of CCA, to create canonical variables that we can compare in the two data sets. In the second case, Super-OM uses organizing maps to create subgroups of individuals who share the same characteristics. We use the 2017 Belgian Statistics on Income and Living Conditions (SILC) and we compare the performance of the proposed statistical matching methods by means of a cross-validation technique, as if the data were available from two separate sources. The results indicate that our proposed methods are superior to existing methods because they preserve the distribution of generated variables while also providing good predictions. Existing methods typically only achieve one or the other. These new techniques open the door to improving statistical matching in other applications such as medicine, economics, …

A Different Perspective of COVID-19 Pandemic: Efficacy and Safety of mRNA Vaccines in Immunocompetent and Immunocompromised Individuals (Part 3).

Shortly after the declaration of the pandemic, several anti-SARS-CoV-2 vaccines entered phase 3 clinical trials. One year later, Pfizer-BioNTech and Moderna published their initial trial results, encompassing a 2-month follow-up. The studies were only designed to test whether the vaccines were effective and safe on the short-term.The vaccine's efficacy in the 2 trials was defined as relative risk reduction instead of absolute risk reduction, a more accurate determinant of vaccine effectiveness in the real world. These studies were not designed to assess viraltransmission, disease severity, and death as primary outcomes.Vulnerable subgroups of individuals were excluded from the studies. No correlate of immunity against the SARS-CoV2 was identified.Vaccine-induced immunity declined shortly after vaccination and was not protective against new variants. Vaccination and boosting effectiveness were suboptimal in immunocompromised patients. In contrast, in recovered COVID-19 patients, natural immunity was shown to be protective, lasting longer and being more effective against new variants. Findings from subsequent scientific reports questioned the effectiveness of these vaccines in providing protective immunity despite boosting in infection-naïve and infection-experienced individuals. Reports also raised concerns on their safety in relation to cardiovascular pathology, sudden death, and acquired autoimmunity mainly in the low-risk young population. With the doubtful accuracy of the polymerase chain reaction testing in relation to case definition and diagnosis, the inability of the vaccines to stop viral transmission, the uncertain effectiveness of these vaccines, and serious adverse events of these vaccines lead us to question the validity ofthe vaccine mandate in public and private domains.

Revealing subgroup-specific mechanisms of change via moderated mediation: A meditation intervention example.

Effective psychosocial interventions exist for numerous mental health conditions. However, despite decades of research, limited progress has been made in clarifying the mechanisms that account for their beneficial effects. We know that many treatments work, but we know relatively little about why they work. Mechanisms of change may be obscured due to prior research collapsing across heterogeneous subgroups of patients with differing underlying mechanisms of response. Studies identifying baseline individual characteristics that predict differential response (i.e., moderation) may inform research on why (i.e., mediation) a particular subgroup has better outcomes to an intervention via tests of moderated mediation. In a recent randomized controlled trial comparing a 4-week meditation app with a control condition in school system employees (N = 662), we previously developed a "Personalized Advantage Index" (PAI) using baseline characteristics, which identified a subgroup of individuals who derived relatively greater benefit from meditation training. Here, we tested whether the effect of mindfulness acquisition in mediating group differences in outcome was moderated by PAI scores. A significant index of moderated mediation (IMM = 1.22, 95% CI [0.30, 2.33]) revealed that the effect of mindfulness acquisition in mediating group differences in outcome was only significant among those individuals with PAI scores predicting relatively greater benefit from the meditation app. Subgroups of individuals may differ meaningfully in the mechanisms that mediate their response to an intervention. Considering subgroup-specific mediators may accelerate progress on clarifying mechanisms of change underlying psychosocial interventions and may help inform which specific interventions are most beneficial for whom. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Proprotein convertase subtilisin/kexin type 9 inhibitors protect against contrast-associated acute kidney injury in patients with atherosclerotic cardiovascular disease.

Contrast-associated acute kidney injury (CA-AKI) may occur in patients undergoing medical procedures involving x-rays and radiocontrast media, potentially resulting in prolonged renal impairment. However, no effective treatments are available. Therefore, this study aimed to investigate the efficacy of evolocumab, a proprotein convertase subtilisin/kexin type 9 inhibitor, in reducing CA-AKI incidence among patients with atherosclerotic cardiovascular disease (ASCVD) undergoing percutaneous coronary intervention. This retrospective cohort study included patients who underwent percutaneous coronary intervention between January 2020 and December 2021 at Tianjin Chest Hospital. The study endpoint was CA-AKI incidence, and the impact of selection bias and other potential confounding factors was mitigated using bias matching. Overall, 1,642 patients were included in this study: 821 patients received evolocumab treatment before contrast agent application, and 821 did not receive such treatment. CA-AKI incidence was 6.21% and 8.04% in the evolocumab and control groups, respectively. After propensity-score matching, the incidence rate was 5.09% and 14.16% in the evolocumab and control groups, respectively. Evolocumab treatment significantly reduced CA-AKI incidence (p < 0.001). Consistent findings were obtained in the subgroups of individuals with type II diabetes mellitus, chronic heart failure, and hypertension. Evolocumab exhibited a significantly greater protective effect in the high- and extremely high-risk populations than in the low- and middle-risk populations (p < 0.001). Evolocumab administration significantly reduced CA-AKI incidence among patients with ASCVD. Notably, this effect was more prominent within the subset of high- and extremely high-risk individuals who were already experiencing CA-AKI.

Gut microbiome and intestinal inflammation in preclinical stages of rheumatoid arthritis

BackgroundFaecal Prevotellaceae, and other microbes, have been associated with rheumatoid arthritis (RA) and preclinical RA. We have performed a quantitative microbiome profiling study in preclinical stages of RA.MethodsFirst-degree relatives of...

Prescription Opioid Use before and after Diagnosis of Cancer Among Older Cancer Survivors With Non-Cancer Chronic Pain Conditions (NCPCs): An Application of Group-Based Trajectory Modeling (GBTM).

Prescription opioids are essential in managing pain among adults with chronic pain conditions. However, persistent use over time can lead to negative health consequences. Identifying individuals with persistent use over time and their characteristics can inform clinical decision-making and aid in reducing the risk of abuse and overdose deaths. This study aims to examine trajectories of prescription opioid use over time and factors associated with these trajectories among older cancer survivors with any non-cancer pain conditions (NCPC). We conducted a retrospective cohort study design with longitudinal data of older (age at cancer diagnosis ≥67years) cancer (incident breast, colorectal, and prostate cancers, or non-Hodgkin lymphoma) survivors with any NCPC. Data were derived from the 2007-2015 linked Surveillance, Epidemiology, and End Results (SEER)-Medicare dataset (N = 35,071). Group-Based Trajectory Modeling (GBTM) was used to identify homogeneous subgroups (distinct trajectories) of individuals based on every 90-day prescription opioid use during pre-cancer diagnosis (t1-t4), acute cancer treatment (t5-t8), and post-cancer treatment (t9-t12) periods. Biological factors, social determinants of health (SDoH), physical and mental health, medication use, health care use, and external factors associated with a trajectory membership were analyzed with multivariable multinomial logistic regressions. Four distinct trajectories of opioid use were identified: (1) increase-decrease use (6.1%); (2) short-term use after cancer diagnosis (40.6%); (3) low-use (41.0%); and (4) persistent use (12.3%). In the fully-adjusted multinomial logistic regression, the SDoH such as Non-Hispanic Black [adjusted odds ratios (AOR) = 1.69; 95%CI = 1.48, 1.93)] and rural residence (AOR = 1.49; 95%CI = 1.15, 1.94)], comorbid anxiety (AOR = 1.33; 95%CI = 1.18, 1.51), and medication use (NSAIDs - AOR = 1.20; 95%CI = 1.10, 1.30) were associated with membership in the persistent use group. Persistent use was less likely among those with higher fragmented care index (AOR = 0.95, 95%CI = 0.93, 0.97) and those living in counties with higher Medicare advantage penetration (AOR = 0.96; 95%CI = 0.95, 0.97). One in eight older adults had persistent opioid use over time. The profile characteristics of this group were different from the other trajectory groups. Policies and programs to reduce chronic opioid use need to consider the intra- and inter-individual variability to reduce opioid-related morbidity and mortality.

Hypocapnia in women with fibromyalgia.

The purpose of this study was to investigate whether people with fibromyalgia (FM) have dysfunctional breathing by examining acid-base balance and comparing it with healthy controls. Thirty-six women diagnosed with FM and 36 healthy controls matched for age and gender participated in this cross-sectional study. To evaluate acid-base balance, arterial blood was sampled from the radial artery. Carbon dioxide, oxygen, bicarbonate, base excess, pH and lactate were analysed for between-group differences. Blood gas analyses were performed stepwise on each individual to detect acid-base disturbance, which was categorized as primary respiratory and possible compensation indicating chronicity. A three-step approach was employed to evaluate pH, carbon dioxide and bicarbonate in this order. Women with FM had significantly lower carbon dioxide pressure (p = 0.013) and higher lactate (p = 0.038) compared to healthy controls at the group level. There were no significant differences in oxygen pressure, bicarbonate, pH and base excess. Employing a three-step acid-base analysis, 11 individuals in the FM group had a possible renally compensated mild chronic hyperventilation, compared to only 4 among the healthy controls (p = 0.042). In this study, we could identify a subgroup of individuals with FM who may be characterized as mild chronic hyperventilators. The results might point to a plausible dysfunctional breathing in some women with FM.

Identification of multimorbidity patterns in older adults receiving long-term care in Canada, Italy, Finland and New Zealand: results from the ICARE4OLD project

Background: Older adults receiving home care (HC) services and living in long-term care homes (LTC) experience high levels of multimorbidity. In this project - called iCARE4OLD, we aimed first to identify and compare subgroups of care dependent individuals sharing the same patterns of chronic diseases. For these subgroups, we will identify care paths and try to make integration of services and continuity of care possible. &#x0D; Settings and participants: We studied 102,000 individuals 60+ years receiving HC services or living in LTC homes in Canada, Italy, Finland and New Zealand.&#x0D; Methods: This is a cross-sectional study including the baseline interRAI HC and LTCF assessments of older people in the period of 2014 until 2018. The project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement number 965341 and from the New Frontiers Research Fund, grant number NFRFG-2020-00500.&#x0D; Latent Class Analysis (LCA) was used to classify individuals according to their underlying diseases patterns starting from a list of 19 conditions. &#x0D; Results: Mean age of the sample was 80 years (65% females). After assessing several fit parameters, a 5-class solution was chosen as the best model for both HC and LTC. The following 5 disease patterns were identified in all countries: (1) Alzheimer/dementia; (2) psychiatric diseases; (3) cardio-pulmonary diseases; (4) stroke/hemiplegia; (5) other dementias. The distribution of sociodemographic, clinical and functional characteristics varied across the different multimorbidity patterns, with the cardio-pulmonary disease and the stroke/hemiplegia patterns showing the highest complexity and impairment.&#x0D; Results: Our results show that, by using a common assessment tool, it is possible to identify homogeneous morbidity patterns in older patients receiving long-term care. These may be useful to compare health status in care-dependent individuals across different settings and countries, as well as to predict health trajectories and care needs. &#x0D; Discussion: By applying this methodology to whole populations, care paths can be drawn for home care and residential care clients in a more evidence-based way. The goals would be to use these algorithms to design more integrated care plans for older persons, so that clients and their families are better served, and policy makers can finance the right services and offer targeted care.&#x0D;

PUBLIC HEALTH CURRICULUM: DEMENTIA CAREGIVING AS A PUBLIC HEALTH CHALLENGE AND OPPORTUNITY

Abstract A new, free, one-hour, interactive, online module, Dementia Caregiving as a Public Health Challenge and Opportunity, is designed for public health students, educators and professionals. This course approaches caregiving for people with Alzheimer’s disease and other dementias from a population-based perspective , while remembering that these are the individual stories and lives of millions of people today. Dementia caregiving is a public health priority because of its prevalence; its profound influence on individuals, families, communities, and healthcare systems; and its disproportionate effects on subgroups of individuals. A number of public health actions can help to address the population effects of dementia caregiving. There remains a gap in public health curricula that features dementia and dementia caregiving, and this module represents an educational innovation to introduce key concepts in dementia caregiving for students and others. This module defines dementia caregiving, specifies why dementia caregiving is a public health issue, and reviews evidence-based programs for assisting dementia caregivers. Public health examples and case studies are used to support and assess learner understanding. This module was developed for the Alzheimer’s Association by the Emory Centers for Public Health Training and Technical Assistance with support from the Building our Largest Dementia Infrastructure (BOLD) Public Health Center of Excellence on Dementia Caregiving, and represents a novel strategy to elevate dementia caregiving as a matter of public health concern.

PERSONALIZED AND TYPICAL CONCURRENT RISK: JOINT MODELS OF RECURRENT OUTCOMES AND MORTALITY BY RACE/ETHNICITY

Abstract The growing burden of multiple chronic conditions documented by a U.S. Department of Health and Human Services initiative noted the importance of studies that 1) “Develop tools to identify and target population subgroups of individuals with multiple chronic conditions who are at high risk for poor health outcomes”, and 2) “Improve knowledge about patient trajectories temporally in relation to changes in health status, functional status, and health services use”. Expanding upon our methods for jointly modeling multiple outcomes, where each person’s shared influence on concurrent outcomes can be captured by using a random intercept term, we demonstrate how to model additional heterogeneity. Based on the estimates from the joint model, the typical concurrent risk (TCR) of each outcome (i.e., probability) can be estimated at the cohort level, providing a method for identifying average longitudinal effects of risk factors useful for healthcare system policies. In contrast, a person-specific effect reflects the probability of each outcome within a defined interval of time, while currently at risk for another non-mutually exclusive outcome (i.e., personalized concurrent risk [PCR]). Chronic conditions and sociodemographic risk factors may partially account for the heterogeneity of a cohort. However, differences in the occurrences and associations among these may differ for minoritized groups. These methods identify persons above (or below) average risk. We expanded these joint models to address truncation of measurement due to death and the interdependence of outcomes at the person-level, while maintaining the Type I error rate. We have made the code publicly available.

SEX AND ETHNICITY-RELATED DISPARITIES IN ALZHEIMER’S DISEASE AMONG RESIDENTS OF SKILLED NURSING FACILITIES

Abstract Residents of nursing homes represent a special subset of the population characterized by increased vulnerability and higher rates of Alzheimer’s Disease (AD). Nursing home ethnic composition does not reflect that of the general population with minorities more likely to be concentrated in facilities with serious deficiencies, and to have lower health status at time of admission. Significant ethnic disparities in quality-of-care aspects such as hospitalizations, preventive care, and the management of chronic conditions exist and these patterns extend to sex and ethnicity-specific subgroups of individuals with AD. However, there is a paucity of knowledge on the actual size of sex and ethnicity-related disparities in AD within this high-risk population. In this study we used 100% of all nursing home resident evaluations (N=23,080,518; Male:40.66%; Female:59.34%; White: 77.29%; Black:11.62%; Other:3.80%; Hispanic:4.97%; Asian:1.81%; Pacific Islander:0.15%; Native American Native:0.39%), 1999-2012, from the Minimum Dataset to assess sex and ethnicity-specific differences in age-specific prevalence of AD. Total AD prevalence increases sharply (numbers are prevalence proportions with 95% confidence intervals in parentheses) from 1.79 (1.75-1.84) at age 60 to 13.45 (13.39-13.51) at 85. Notable statistically significant sex and ethnicity-related disparities were present at all ages. For example, at age 85 the prevalence of AD was for: i)Males: 11.34 (11.24-11.44); ii)Females: 14.53 (14.45-14.62); iii)Whites: 13.21 (13.14-13.28); iv)Blacks: 15.32 (15.09-15.55); v)Other/Unknown: 9.75 (9.42-10.07); vi)Hispanics: 18.17 (17.82-18.52); vii)Asians: 11.30 (10.87-11.72); viii)Pacific Islanders: 10.33 (8.65-12.01); ix)North American Natives: 11.78 (10.62-12.94). In depth analysis of the causes, time-trends, and geographic distribution of these disparities is needed.

Instrumental variables for implementation science: exploring context-dependent causal pathways between implementation strategies and evidence-based interventions

BackgroundThe impact of both implementation strategies (IS) and evidence-based interventions (EBI) can vary across contexts, and a better understanding of how and why this occurs presents fundamental but challenging questions that implementation science as a field will need to grapple with. We use causal epidemiologic methods to explore the mechanisms of why sharp distinctions between implementation strategies (IS) and efficacy of an evidence-based intervention (EBI) may fail to recognize that the effect of an EBI can be deeply intertwined and dependent on the context of the IS leading to its uptake.MethodsWe explore the use of instrumental variable (IV) analyses as a critical tool for implementation science methods to isolate three relevant quantities within the same intervention context when exposure to an implementation strategy is random: (1) the effect of an IS on implementation outcomes (e.g., uptake), (2) effect of EBI uptake on patient outcomes, and (3) overall effectiveness of the IS (i.e., ~ implementation*efficacy). We discuss the mechanisms by which an implementation strategy can alter the context, and therefore effect, of an EBI using the underlying IV assumptions. We illustrate these concepts using examples of the implementation of new ART initiation guidelines in Zambia and community-based masking programs in Bangladesh.ResultsCausal questions relevant to implementation science are answered at each stage of an IV analysis. The first stage assesses the effect of the IS (e.g., new guidelines) on EBI uptake (e.g., same-day treatment initiation). The second stage leverages the IS as an IV to estimate the complier average causal effect (CACE) of the EBI on patient outcomes (e.g., effect of same-day treatment initiation on viral suppression). The underlying assumptions of CACE formalize that the causal effect of EBI may differ in the context of a different IS because (1) the mechanisms by which individuals uptake an intervention may differ and (2) the subgroup of individuals who take up an EBI may differ. IV methods thus provide a conceptual framework for how IS and EBIs are linked and that the IS itself needs to be considered a critical contextual determinant. Moreover, it also provides rigorous methodologic tools to isolate the effect of an IS, EBI, and combined effect of the IS and EBI.DiscussionLeveraging IV methods when exposure to an implementation strategy is random helps to conceptualize the context-dependent nature of implementation strategies, EBIs, and patient outcomes. IV methods formalize that the causal effect of an EBI may be specific to the context of the implementation strategy used to promote uptake. This integration of implementation science concepts and theory with rigorous causal epidemiologic methods yields novel insights and provides important tools for exploring the next generation of questions related to mechanisms and context in implementation science.

Relation between orthorexia nervosa and healthy orthorexia: A latent profile analysis

Orthorexic eating behaviors can be conceptualized as a bidimensional construct encompassing an orthorexia nervosa dimension (ON) and a healthy orthorexia dimension (HO). Although variable-centered studies showed that ON and HO are distinguishable orthorexic eating behaviors, the evidence of whether they can co-occur or be distinct in subgroups of individuals is still limited. The present study aimed to address previous person-centered studies' limitations by examining profiles of ON and HO among a convenience sample of 251 French-speaking Canadian adults (85.7% women; Mage = 33.56). Profile membership was examined as function of participants characteristics such as age, gender, body mass index, frequency of physical activity and sports and vegetarianism. The relation between profile membership, intuitive eating and disordered eating attitudes and behaviors was also assessed. Latent profile analysis (LPA) were used to estimate profiles of ON and HO. Results from LPA did not provide support for the distinguishability of ON and HO. Indeed, they revealed the presence of two profiles showing co-occurring levels of ON and HO that only differed quantitatively: low (68.9% of the sample; low levels of ON and HO) or moderate orthorexic eating behaviors (31.1%; moderate levels of ON and HO). Participants who declared being vegetarian and being more frequently involved in physical activities and sports were more likely to belong to the moderate orthorexic eating behaviors' profile. Finally, participants from the moderate orthorexic eating behaviors' profile showed higher levels of disordered eating attitudes and behaviors, whereas those from the low orthorexic eating behaviors’ profile showed higher levels of intuitive eating. Findings from the present study question the distinguishability of ON and HO dimensions. They also suggest that, similarly to ON, HO is also related to higher eating and lifestyle preoccupations.

Characterization of trajectories of physical activity and cigarette smoking from early adolescence to adulthood

BackgroundCigarette smoking and physical inactivity are two critical risk factors for noncommunicable diseases and all-cause mortality. However, few studies have compared the long-term trajectories of both behaviors, as well as multilevel factors associated with trajectory patterns. Using the National Longitudinal Study of Adolescent to Adult Health (Add Health) Wave I through V survey data, this study characterized distinct subgroups of the population sharing similar behavioral patterns from adolescence to adulthood, as well as predictors of subgroup membership for physical activity (PA) and cigarette smoking behavior respectively.MethodsUsing the Add Health Wave I through V survey data, we identified the optimal number of latent classes and class-specific trajectories of PA and cigarette smoking from early adolescence to adulthood, fitting latent growth mixture models with standardized PA score and past 30-day cigarette smoking intensity as outcome measures and age as a continuous time variable. Associations of baseline sociodemographic factors, neighborhood characteristics, and sociopsychological factors with trajectory class membership were assessed using multinomial logistic regression.ResultsWe identified three distinct subgroups of non-linear PA trajectories in the study population: moderately active group (N = 1067, 5%), persistently inactive group (N = 14,257, 69%) and worsening activity group (N = 5410, 26%). Foror cigarette smoking, we identified three distinct non-linear trajectory subgroups: persistent non-smoker (N = 14,939, 72%), gradual quitter (N = 2357, 11%), and progressing smoker (N = 3393, 16%). Sex, race/ethnicity, neighborhood environment and perceived peer support during adolescence were significant predictors of both physical activity and cigarette smoking trajectory subgroup membership from early adolescence to adulthood.ConclusionsThere are three distinct subgroups of individuals sharing similar PA and cigarette smoking behavioral profile respectively from adolescence to adulthood in the Add Health study population. Behavioral interventions that focus on neighborhood environment (e.g. establish community-based activity center) and relationship to peers during adolescence (e.g. peer counseling) could be key to long-term PA promotion and cigarette smoking cessation.

NetMUG: a novel network-guided multi-view clustering workflow for dissecting genetic and facial heterogeneity.

Introduction: Multi-view data offer advantages over single-view data for characterizing individuals, which is crucial in precision medicine toward personalized prevention, diagnosis, or treatment follow-up. Methods: Here, we develop a network-guided multi-view clustering framework named netMUG to identify actionable subgroups of individuals. This pipeline first adopts sparse multiple canonical correlation analysis to select multi-view features possibly informed by extraneous data, which are then used to construct individual-specific networks (ISNs). Finally, the individual subtypes are automatically derived by hierarchical clustering on these network representations. Results: We applied netMUG to a dataset containing genomic data and facial images to obtain BMI-informed multi-view strata and showed how it could be used for a refined obesity characterization. Benchmark analysis of netMUG on synthetic data with known strata of individuals indicated its superior performance compared with both baseline and benchmark methods for multi-view clustering. The clustering derived from netMUG achieved an adjusted Rand index of 1 with respect to the synthesized true labels. In addition, the real-data analysis revealed subgroups strongly linked to BMI and genetic and facial determinants of these subgroups. Discussion: netMUG provides a powerful strategy, exploiting individual-specific networks to identify meaningful and actionable strata. Moreover, the implementation is easy to generalize to accommodate heterogeneous data sources or highlight data structures.

Abstract A108: Perceived negative effects of COVID-19 on mental health based on a history of cancer

Abstract Background: The COVID-19 pandemic had profound effects on cancer care and healthcare in general, including access and delays in receiving care. However, while the perceived negative effects of COVID-19 on mental health have been widely acknowledged, it remains unclear whether individuals with a history of cancer are at a higher risk of experiencing mental health issues as a result of the pandemic. Methods: We used the 2021 cross-sectional epidemiological data from the National Survey on Drug Use and Health (NSDUH) in the United States. Our outcome of interest was based on a single-item question in the 2021 data that elicited perception of the COVID-19 pandemic's negative effect on emotional or mental health. We examined the association between a history of cancer and our outcome of interest, using a multivariable logistic regression to estimate the odds of perceiving negative mental health effect due to COVID-19 based on a history of cancer. A secondary analysis examined demographic factors associated with perceived negative mental health effect of COVID-19 among individuals with a history of cancer. Results: Our analysis included a total of 15,959 individuals aged ≥18 years, 12.7% of which had a history of cancer (n = 2,030). After adjusting for age, race/ethnicity, and sex, compared to individuals without a history of cancer, those with a history of cancer had higher odds of perceived negative mental health due to the pandemic (aOR = 1.23; 95% CI 1.01, 1.49). Within the subgroup of individuals with a history of cancer, compared to individuals who were ≥65 years, individuals aged 35 – 49 had higher odds of perceived negative mental health due to COVID-19 (aOR = 1.73; 95% CI = 1.04, 2.88). Additionally, individuals who were non-Hispanic Others (Asians, Native American Indian/Alaskan Natives, Native Hawaiian/other Pacific Islanders, and mixed races) had higher odds of perceived negative mental health due to COVID-19, when compared to non-Hispanic white individuals (aOR = 2.75; 95% CI = 1.29 - 5.87). Conclusion: Individuals with a history of cancer may have perceived being more negatively impacted mentally by the COVID-19 pandemic compared to those without a history of cancer, especially certain age groups and minoritized populations. As cancer care emerges into a post-COVID era, it is imperative to prioritize mental health to ensure a better quality of life during cancer survivorship. Citation Format: Meng Chen, Dina K. Abouelella, Melissa C. White, Rong Jiang, Oluwole A. Babtunde, Eric Adjei Boakye, Tammara L. Watts, Nosayaba Osazuwa-Peters. Perceived negative effects of COVID-19 on mental health based on a history of cancer [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr A108.

Preterm Birth and Metal Mixture Exposure among Pregnant Women from the Navajo Birth Cohort Study.

Preterm birth (PTB), defined as birth before 37 wk gestation, is associated with hypertension, diabetes, inadequate prenatal care, unemployment or poverty, and metal exposure. Indigenous individuals are more likely to have maternal risk factors associated with PTB compared with other populations in the United States; however, the role of environmental metals on PTB among pregnant Indigenous women remains uncertain. Previous research identified associations between PTB and individual metals, but there is limited investigation on metal mixtures and this birth outcome. We used a mixtures analysis framework to investigate the association between metal mixtures and PTB among pregnant Indigenous women from the Navajo Birth Cohort Study (NBCS). Maternal urine and blood samples were collected at the time of study enrollment and analyzed for metals by inductively coupled plasma dynamic reaction cell mass spectrometry. Bayesian Profile Regression was used to identify subgroups (clusters) of individuals with similar patterns of coexposure and to model association with PTB. Results indicated six subgroups of maternal participants with distinct exposure profiles, including one group with low exposure to all metals and one group with total arsenic, cadmium, lead, and uranium concentrations exceeding representative concentrations calculated from the National Health and Nutrition Examination Survey (NHANES). Compared with the reference group (i.e., the lowest exposure subgroup), the subgroup with the highest overall exposure had a relative risk of PTB of 2.9 times (95% credible interval: 1.1, 6.1). Exposures in this subgroup were also higher overall than NHANES median values for women 14-45 years of age. Given the wide range of exposures and elevated PTB risk for the most exposed subgroups in a relatively small study, follow-up investigation is recommended to evaluate associations between metal mixture profiles and other birth outcomes and to test hypothesized mechanisms of action for PTB and oxidative stress caused by environmental metals. https://doi.org/10.1289/EHP10361.