Association between movement behavior patterns and cardiovascular risk among Chinese adults aged 40-75: a sex-specific latent class analysis.

BACKGROUND: Cardiovascular disease (CVD) is a major global health threat, particularly in China, contributing to over 40% of deaths. While sleep behaviors, sedentary behaviors, and physical activities are recognized as independent lifestyle risk factors for CVD, there remains limited understanding of specific movement behavior patterns and their CVD risks, especially considering sex-specific differences. This study examines movement behavior patterns among Chinese adults (40-75) and their associations with cardiovascular risk, with a focus on sleep, physical activity (PA), and sedentary behavior (SB). METHODS: Data pertaining to 13,465 male participants and 15,613 female participants, collected from the Chronic Disease and Risk Factor Surveillance Survey in Nanjing from February 2020 to December 2022. The latent class analysis method was employed to identify underlying movement patterns across sexes. Multinomial logistic regression models assessed CVD risk, and the China-PAR model calculated 10-year risk. RESULTS: Three male and four female movement patterns emerged. Active Movers (17.10% males, 5.93% females) adhered to PA recommendations but had poorer sleep quality. Moderate Achievers (61.42% males, 45.32% females) demonstrated moderate behavior. Sedentary Sleepers (21.48% males, 10.20% females) exhibited minimal PA but good sleep. Female Moderate Physical Activity (MPA) Dominant Movers demonstrated a prevalent adherence to recommended MPA levels. Active movers had the lowest CVD risk. After adjusting for potential confounders, moderate achievers (OR = 1.462, 95% CI 1.212, 1.764) and sedentary sleepers (OR = 1.504, 95% CI 1.211, 1.868) were both identified as being associated with a high-risk of cardiovascular diseases (CVDs) compared to active movers in males, demonstrating a similar trend for intermediate risk. Such associations were not statistically significant among females. CONCLUSIONS: Our study revealed sex-specific movement patterns associated with CVD risks among middle-aged Chinese adults. We suggest that adopting an active movement behavior pattern, characterized by meeting or exceeding recommended levels of vigorous physical activity (VPA) and reducing sedentary behavior, is beneficial for all middle-aged adults, particularly males. An active lifestyle could help counteract the adverse effects of relatively poor sleep quality on the risk of developing CVD in this population. Integrating sleep, PA, and SB information provides a holistic framework for understanding and mitigating CVD risks.

Using latent class analysis to operationalize a wholistic assessment of Inuit health and well-being.

Many indigenous cultures conceptualize health wholistically, whereby physical, mental, spiritual and relational dimensions of health are interconnected. Yet, quantitative approaches to studying Indigenous health remain anchored in western perspectives, that separate the dimensions of health. This paper aims to operationalize a wholistic indicator of health based on the IQI model of Inuit health. Variables from the 2017 Nunavik Health Survey (N = 1196) were selected based on their representativeness of IQI model. Exploratory Latent Class Analysis (LCA) was used to identify wholistic health profiles. Once participants assigned to their health profile, sociodemographic characteristics were compared across profiles, and multinomial regression models were used to examine the relationship between community-level social determinants of health and the profiles. The LCA revealed three health profiles, labelled as "excellent", "good" and "fair" based on the distribution of answers to the indicators. Nunavimmiut in "excellent" and "good" health were more likely to: rate their health positively; be over 30 years old; be in a relationship; and have participated or volunteered in community events. Nunavimmiut in "fair" health tended to report lower levels of community cohesion, family relationships, and emotional support. Intergrating culturally relevant models of health can support improved health status assessments and identify opportunities for health promotion.

Characterizing Socioecological Markers of Differentiated HIV Risk Among Men Who Have Sex with Men in Indonesia.

HIV prevention programs typically focus on changing individuals' risk behaviors, often without considering the socioecological factors that can moderate this risk. We characterized HIV risk among men who have sex with men (MSM) in Indonesia (n = 1314) using latent class analysis and used multinomial logistic regression to identify latent class relationships with demographics, social/sexual networks, and community-level socioecological indicators of HIV risk. Three HIV risk latent classes were identified-"Sexually Moderate" (n = 333), "Sexual Explorative" (n = 575), and "Navigating Complexities" (n = 406). Using "Sexually Moderate" (lowest risk) as the reference group, MSM in the "Sexual Explorative" class had additional social/sexual network-level risks (meeting partner(s) using both online and offline methods [RR = 3.8; 95%CI 1.7-8.6] or general social media and gay-specific online platforms [RR = 2.6; 95%CI 1.9-3.6] to meet partners, group sex [RR = 10.9; 95%CI 4.5-25.4], transactional sex [RR = 1.6; 95%CI 1.2-2.2]), and community-level risks (experiencing homosexual-related assaults [RR = 1.4; 95%CI 1.1-1.9]). MSM in the "Navigating Complexities" class had additional social/sexual network-level risks (low social support [RR = 1.6; 95%CI 1.1-2.5], less disclosure of their sexuality [RR = 1.4; 95%CI 1.0-1.9]) and community-level risks (higher internalized homonegativity scores [RR = 1.2; 95%CI 1.1-1.4], ever experiencing homosexual-related assaults [RR = 1.4:95%CI 1.1-1.9], less exposure to HIV/STI health promotion [RR = 0.7; 95%CI 0.5-0.9], attending STI-related services in the past 6 months [RR = 0.6; 95%CI 0.4-0.8]). Co-occurring individual and socioecological risk recommend holistic HIV prevention strategies tailored to consider the social and structural conditions of MSM in Indonesia are needed.

Association between adjuvant radiation treatment and breast cancer-specific mortality among older women with comorbidity burden: A comparative effectiveness analysis of SEER-MHOS.

BACKGROUND: The National Comprehensive Cancer Network suggested that older women with low-risk breast cancer (LRBC; i.e., early-stage, node-negative, and estrogen receptor-positive) could omit adjuvant radiation treatment (RT) after breast-conserving surgery (BCS) if they were treated with hormone therapy. However, the association between RT omission and breast cancer-specific mortality among older women with comorbidity is not fully known. METHODS: 1105 older women (≥65 years) with LRBC in 1998-2012 were queried from the Surveillance, Epidemiology, and End Results-Medicare Health Outcomes Survey data resource and were followed up through July 2018. Latent class analysis was performed to identify comorbidity burden classes. A propensity score-based inverse probability of treatment weighting (IPTW) was applied to Cox regression models to obtain subdistribution hazard ratios (HRs) and 95% CI for cancer-specific mortality considering other causes of death as competing risks, overall and separately by comorbidity burden class. RESULTS: Three comorbidity burden (low, moderate, and high) groups were identified. A total of 318 deaths (47 cancer-related) occurred. The IPTW-adjusted Cox regression analysis showed that RT omission was not associated with short-term, 5- and 10-year cancer-specific death (p = 0.202 and p = 0.536, respectively), regardless of comorbidity burden. However, RT omission could increase the risk of long-term cancer-specific death in women with low comorbidity burden (HR = 1.98, 95% CI = 1.17, 3.33), which warrants further study. CONCLUSIONS: Omission of RT after BCS is not associated with an increased risk of cancer-specific death and is deemed a reasonable treatment option for older women with moderate to high comorbidity burden.

Type of deliveries supported by Dutch clinical midwives.

OBJECTIVE: The number of clinical midwives in the Netherlands has substantially increased over the last twenty years, but their role in obstetric care is not clearly defined. Our aim was to identify the type of deliveries that are usually supported by clinical midwives and whether these changed over time. DESIGN, SETTING, AND PARTICIPANTS: National data from the Netherlands Perinatal Registry from the years 2000 to 2016 (n = 2.999.411 deliveries) were used to divide all deliveries into classes using latent class analyses based on delivery characteristics. In the primary analyses, the identified classes, type of hospital, and year of cohort were used to predict deliveries supported by a clinical midwife. In secondary analyses, the same analyses were repeated where the classes were replaced by individual level characteristics of deliveries and stratified by referral during birth. MEASUREMENTS AND FINDINGS: The latent class analyses identified three classes: I. referral during birth; II. Induction of labour; and III. Planned caesarian section. The primary analyses indicated that women in both class I and II were frequently supported by clinical midwives and those in the third class almost never. Therefore, only data from deliveries assigned to class I and II were used in the secondary analyses. The secondary analyses showed that clinical midwives supported deliveries with a great variety in characteristics, such as pain relief and preterm birth. Although the frequency of clinical midwives being involved in the second stage of labour increased over the years, we did not find noticeable changes in their involvement. KEY CONCLUSION AND IMPLICATIONS FOR PRACTICE: Clinical midwives care for women with various types of deliveries with varying degrees of pathology and complexity during second stage of labour. Additional training, taking previously acquired skills and competences into account, is necessary to deal with this complexity for which clinical midwives are not always trained.

Sociodemographic and Health Correlates of Multiple Health Behavior Adherence among Cancer Survivors: A Latent Class Analysis.

The study aimed to (a) assess current levels of adherence to the National Comprehensive Cancer Network's multiple health behavior guidelines and (b) identify characteristics of cancer survivors associated with different adherence levels. Cancer survivors (N = 661) were identified through the state registry and completed questionnaires. Latent class analysis (LCA) was used to identify patterns of adherence. Associations between predictors with the latent classes were reported as risk ratios. LCA identified three classes: lower- (39.6%), moderate- (52.0%), and high-risk lifestyle (8.3%). Participants in the lower-risk lifestyle class had the highest probability of meeting most of the multiple health behavior guidelines compared to participants in the high-risk lifestyle class. Characteristics associated with membership in the moderate-risk lifestyle class included self-identifying as a race other than Asian/Asian American, being never married, having some college education, and having been diagnosed with later stage colorectal or lung cancer. Those in the high-risk lifestyle class were more likely to be male, never married, have a high school diploma or less, diagnosed with colorectal or lung cancer, and diagnosed with pulmonary comorbidities. Study findings can be used to inform development of future interventions to promote multiple health behavior adherence among higher risk cancer survivors.

Patterns of polysubstance use and clinical comorbidity among persons seeking substance use treatment: An observational study.

INTRODUCTION: Polysubstance use is common among individuals seeking treatment for substance use disorders (SUD). However, we know less about patterns and correlates of polysubstance use among treatment-seeking populations. The current study aimed to identify latent patterns of polysubstance use and associated risk factors in persons entering SUD treatment. METHODS: Patients (N = 28,526) being admitted for substance use treatment reported on their use of thirteen substances (e.g., alcohol, cannabis, cocaine, amphetamines, methamphetamines, other stimulants, heroin, other opioids, benzodiazepines, inhalants, synthetics, hallucinogens, and club drugs) in the month before treatment and prior to the month before treatment. Latent class analysis (LCA) determined the relationship between class membership and gender, age, employment status, unstable housing, self-harm, overdose, past treatment, depression, generalized anxiety disorder, and/or post-traumatic stress disorder (PTSD). RESULTS: Identified classes included: 1) Alcohol primary, 2) Moderate probability of past-month alcohol, cannabis, and/or opioid use; 3) Alcohol primary, Lifetime cannabis and cocaine use; 4) Opioid primary, Lifetime use of alcohol, cannabis, hallucinogens, club drugs, amphetamines, and cocaine; 5) Moderate probability of past-month alcohol, cannabis, and/or opioid use, Lifetime use of various substances; 6) Alcohol and cannabis primary, Lifetime use of various substances; and 7) High past-month polysubstance use. Individuals who engaged in past-month polysubstance use attended to face elevated risk of screening positive for recent unstable housing, unemployment, depression, anxiety, PTSD, self-harm, and overdose. CONCLUSIONS: Current polysubstance use is associated with significant clinical complexity. Tailored treatments that reduce harms resulting from polysubstance use and related psychiatric comorbidity may improve treatment outcomes in this population.

Data-driven classification of health status of older adults with diabetes: The diabetes and aging study.

BACKGROUND: We set out to identify empirically-derived health status classes of older adults with diabetes based on clusters of comorbid conditions which are associated with future complications. METHODS: We conducted a cohort study among 105,786 older (≥65 years of age) adults with type 2 diabetes enrolled in an integrated healthcare delivery system. We used latent class analysis of 19 baseline comorbidities to derive health status classes and then compared incident complication rates (events per 100 person-years) by health status class during 5 years of follow-up. Complications included infections, hyperglycemic events, hypoglycemic events, microvascular events, cardiovascular events, and all-cause mortality. RESULTS: Three health status classes were identified: Class 1 (58% of the cohort) had the lowest prevalence of most baseline comorbidities, Class 2 (22%) had the highest prevalence of obesity, arthritis, and depression, and Class 3 (20%) had the highest prevalence of cardiovascular conditions. The risk for incident complications was highest for Class 3, intermediate for Class 2 and lowest for Class 1. For example, the age, sex and race-adjusted rates for cardiovascular events (per 100 person-years) for Class 3, Class 2 and Class 1 were 6.5, 2.3, and 1.6, respectively; 2.1, 1.2, 0.7 for hypoglycemia; and 8.0, 3.8, and 2.3 for mortality. CONCLUSIONS: Three health status classes of older adults with diabetes were identified based on prevalent comorbidities and were associated with marked differences in risk of complications. These health status classes can inform population health management and guide the individualization of diabetes care.

Geographical pattern of minerals and its association with health disparities in the USA.

This study aimed to determine the common latent patterns of geographical distribution of health-related minerals across the USA and to evaluate the real-world cumulative effects of these patterns on overall population health. It was an ecological study using county-level data (3080 contiguous counties) on the concentrations of 14 minerals (i.e., aluminum, arsenic, calcium, copper, iron, lead, magnesium, manganese, mercury, phosphorus, selenium, sodium, titanium, zinc) in stream sediments (or surface soils), and the measurements of overall health including life expectancy at birth, age-specific mortality risks and cause-specific (summarized by 21 mutually exclusive groups) mortality rates. Latent class analysis (LCA) was employed to identify the common clusters of life expectancy-related minerals based on their concentration characteristics. Multivariate linear regression analyses were then conducted to examine the relationship between the LCA-derived clusters and the health measurements, with adjustment for potential confounding factors. Five minerals (i.e., arsenic, calcium, selenium, sodium and zinc) were associated with life expectancy and were analyzed in LCA. Three clusters were determined across the USA, the 'common' (n = 2056, 66.8%), 'infertile' (n = 739, 24.0%) and 'plentiful' (n = 285, 9.3%) clusters. Residents in counties with the 'infertile' profile were associated with the shortest life expectancy, highest mortality risks at all ages, and highest mortality rates for many reasons including the top five leading causes of death: cardiovascular diseases, neoplasms, neurological disorders, chronic respiratory conditions, and diabetes, urogenital, blood and endocrine diseases. Results remained statistically significant after confounding adjustment. Our study brings novel perspectives regarding environmental geochemistry to explain health disparities in the USA.

Somatic symptom profiles are associated with pre-treatment depression and anxiety symptom severity but not inpatient therapy outcomes.

OBJECTIVE: Although somatic symptoms are common among mental health patients, their association with symptom severity and inpatient treatment outcomes is not yet well understood. METHODS: Using a pre-post design and latent class analysis (LCA), 641 inpatients (63.4% female) were classified based on their self-reported somatic symptoms. We examined how the resulting somatic symptom classes related to depression and anxiety symptom severity pre-treatment (T1) and to symptom reduction post-treatment (T2). RESULTS: Our results suggest four somatic symptom classes, namely (1) unspecific/low somatic symptom burden, (2) sexual problems, (3) gastrointestinal symptoms with pain syndrome, and (4) cardiopulmonary symptoms. While class 1 indicated the lowest pre-treatment depression and anxiety symptom severity, class 2 reported high depressive symptoms coupled with low anxiety, class 3 reported moderate depressive and anxiety symptom severity, and class 4 reported the highest depressive and anxiety symptom burden. Somatic symptom classes, however, did not predict the degree of reduction in either depression or anxiety symptoms post-treatment. CONCLUSIONS: These findings demonstrate somatic heterogeneity in mental health patients and reveal the relationship of somatic symptom patterns to affective symptom severity. Clinical implications are discussed.

Polysubstance Use Patterns among Outpatients Undergoing Substance Use Disorder Treatment: A Latent Class Analysis.

Substance Use Disorders (SUDs) pose significant challenges to both individuals and society at large. The primary focus of existing research with clinical SUD populations has been on individual substances, but research is required to better understand the profiles of individuals who use different substances simultaneously. The purpose of the current study was, therefore, to identify patterns of use among subjects (n = 1025) who reported using multiple substances by adopting a Latent Class Analysis (LCA) methodology. The Addiction Severity Index (ASI-lite) was included as a measure of substance misuse, we performed LCA to identify patterns of substance use through the administration of the ASI-Lite. Responses were collected from the following substances: alcohol, cannabis/cannabinoids, opioids and heroin, and cocaine. Results identified two latent classes: (1) alcohol use dominant, and (2) poly-abuser use dominants. Class 1 represented 60.0% of the sample and refers to individuals with the dominant use of alcohol, of those a higher proportion (47%) reported low-frequency use (1 to 7 days per month) and 26% reported a frequency of use of 24 to 30 days per month. Furthermore, 18% used alcohol in combination with cocaine. Class 2 represents 40.0% of the sample. This class is characterized by low-frequency and high-frequency users of several substances. The results obtained highlight the importance of deepening the study of the concomitant use of substances in individuals with SUDs to better understand the health risk of the combined use of two or more substances.

Awareness and use of home remedies in Italy's alps: a population-based cross-sectional telephone survey.

BACKGROUND: Belief in complementary and alternative medicine practices is related to reduced preparedness for vaccination. This study aimed to assess home remedy awareness and use in South Tyrol, where vaccination rates in the coronavirus pandemic were lowest in Italy and differed between German- and Italian-speaking inhabitants. METHODS: A population-based survey was conducted in 2014 and analyzed using descriptive statistics, multiple logistic regression, and latent class analysis. RESULTS: Of the representative sample of 504 survey respondents, 357 (70.8%) participants (43.0% male; primary language German, 76.5%) reported to use home remedies. Most commonly reported home remedies were teas (48.2%), plants (21.0%), and compresses (19.5%). Participants from rural regions were less likely (odds ratio 0.35, 95% confidence interval 0.19-0.67), while female (2.62, 1.69-4.10) and German-speaking participants (5.52, 2.91-9.88) were more likely to use home remedies. Latent classes of home remedies were "alcoholic home remedies" (21.4%) and "non-alcohol-containing home remedies" (78.6%). Compared to the "non-alcohol-containing home remedies" class, members of the "alcoholic home remedies" class were more likely to live in an urban region, to be male and German speakers. CONCLUSION: In addition to residence and sex, language group membership associates with awareness and use of home remedies. Home remedies likely contribute to socio-cultural differences between the language groups in the Italian Alps. If the observed associations explain the lower vaccination rates in South Tyrol among German speakers requires further study.

[Relationship between Yingyangbao consumption and anemia status among infants and young children in impoverish areas of Henan Province:a cross-sectional study based on latent class analysis].

OBJECTIVE: To explore latent classes of Yingyangbao(YYB) consumption among infants and young children in impoverished areas of Henan Province, and to analyze the relationship between these classes and anemia status. METHODS: We recruited 4433 children aged 6 to 24 months by multi-stage random sampling in 14 poverty-stricken counties of Henan Province between June and September 2018. We conducted hemoglobin concentration measurement among children and questionnaire survey among their caregivers. Then we used latent class analysis to classify the characteristics of YYB consumption among the children and two-level Logistic regression was used to explore relationship between YYB consumption and anemia status. RESULTS: The prevalence of anemia was 15.1% in poor areas of Henan Province in 2018. There were two latent classes of YYB consumption among children: the one was "effective consumption", latent class probability was 0.889; the other called "ineffective consumption", latent class probability was 0.111. Compared with effective consumption, children who never have consumed YYB(odds ratio(OR)=1.365, P<0.001) or were in "ineffective consumption" class(OR=1.265, P=0.034) were both positive related to anemia. CONCLUSION: Prevalence of anemia among children in impoverished areas has been significantly reduced since the launch of Program of Children's Nutrition Improvement in Impoverished Areas. Effective consumption is a key to ensuring YYB's anemia intervention effect.

Heterogeneity of quality of life in young people attending primary mental health services.

AIMS: The utility of quality of life (QoL) as an outcome measure in youth-specific primary mental health care settings has yet to be determined. We aimed to determine: (i) whether heterogeneity on individual items of a QoL measure could be used to identify distinct groups of help-seeking young people; and (ii) the validity of these groups based on having clinically meaningful differences in demographic and clinical characteristics. METHODS: Young people, at their first presentation to one of five primary mental health services, completed a range of questionnaires, including the Assessment of Quality of Life-6 dimensions adolescent version (AQoL-6D). Latent class analysis (LCA) and multivariate multinomial logistic regression were used to define classes based on AQoL-6D and determine demographic and clinical characteristics associated with class membership. RESULTS: 1107 young people (12-25 years) participated. Four groups were identified: (i) no-to-mild impairment in QoL; (ii) moderate impairment across dimensions but especially mental health and coping; (iii) moderate impairment across dimensions but especially on the pain dimension; and (iv) poor QoL across all dimensions along with a greater likelihood of complex and severe clinical presentations. Differences between groups were observed with respect to demographic and clinical features. CONCLUSIONS: Adding multi-attribute utility instruments such as the AQoL-6D to routine data collection in mental health services might generate insights into the care needs of young people beyond reducing psychological distress and promoting symptom recovery. In young people with impairments across all QoL dimensions, the need for a holistic and personalised approach to treatment and recovery is heightened.

A latent class analysis of health risk behaviours in the UK Police Service and their associations with mental health and job strain.

BACKGROUND: Health risk behaviours (e.g., harmful drinking and smoking) often cluster together and can be associated with poor mental health and stress. This study examined how health risk behaviours cluster together in individuals in a high stress occupation (UK Police Service), and the associations with mental health and job strain. METHODS: Data was obtained from the Airwave Health Monitoring Study (25,234 male and 14,989 female police employees), which included measures of health risk behaviours (alcohol use, diet, smoking status, physical activity), poor mental health (depression, anxiety, post-traumatic stress disorder [PTSD]), and job strain (low, high, active, passive). Classes of health risk behaviours were identified using Latent Class Analysis (LCA) and the associations with mental health and job strain were analysed through multinomial logistic regressions. RESULTS: For men and women, a 5-class solution was the best fit. Men and women with depression, anxiety, and/or PTSD (analysed as separate variables) had at least double the odds of being assigned to the "high health risk behaviours" class, compared to those with no mental health problem. Compared to those reporting low strain, men and women reporting high strain had increased odds of being assigned to the "low risk drinkers with other health risk behaviours" classes. CONCLUSIONS: These finding highlight the importance of holistic interventions which target co-occurring health risk behaviours, to prevent more adverse physical health consequences. Police employees with poor mental health are more likely to engage in multiple health risk behaviours, which suggests they may need additional support. However, as the data was cross-sectional, the temporal associations between the classes and mental health or job strain could not be determined.

Multimorbidity classes indicate differential patterns of health care engagement among people who inject drugs.

BACKGROUND: Aging people who inject drugs (PWID) have complex health needs. Health care management could be complicated by persistent substance use, multiple health challenges, and inconsistent access to care. However, we know little about the relationship between chronic multimorbidity and health care engagement in this population. The purpose of this study is to characterize patterns and correlates of chronic disease multimorbidity among PWID. METHODS: We conducted a latent class analysis (LCA) using data from the AIDS Linked to the IntraVenous Experience (ALIVE) Study, a community-based observational cohort, to determine classes of multimorbid chronic diseases. We then conducted regressions to determine factors associated with class membership and the impact of each multimorbid class on health events and utilization. RESULTS: Of 1387 individuals included, the majority were male (67%) and Black (81%), with a mean age of 53 years. We identified four classes of multimorbidity: Low Multimorbidity (54%), and Low Multimorbidity Including Psychiatric Comorbidity (26%), Multimorbidity (12%), and Multimorbidity Including Psychiatric Comorbidity (7%). Female sex, baseline age, and receipt of disability were factors significantly associated with membership in all three classes compared to the Low Multimorbidity class. Additionally, PWID in these three classes were significantly more likely to utilize emergency room and outpatient health care. Membership in both classes with psychiatric comorbidity was associated with significantly higher adjusted odds of receiving medication for opioid use disorder. DISCUSSION: Holistic health care systems can best address the needs of aging PWID with integrated care that provides harm reduction, substance use and mental health treatment together, and wrap around services.

A population-health approach to characterizing migraine by comorbidity: Results from the Mindfulness and Migraine Cohort Study.

BACKGROUND: The heterogeneity of migraine has been reported extensively, with identified subgroups usually based on symptoms. Grouping individuals with migraine and similar comorbidity profiles has been suggested, however such segmentation methods have not been tested using real-world clinical data. OBJECTIVE: To gain insights into natural groupings of patients with migraine using latent class analysis based on electronic health record-determined comorbidities. METHODS: Retrospective electronic health record data analysis of primary-care patients at Sutter Health, a large open healthcare system in Northern California, USA. We identified migraine patients over a five-year time period (2015-2019) and extracted 29 comorbidities. We then applied latent class analysis to identify comorbidity-based natural subgroups. RESULTS: We identified 95,563 patients with migraine and found seven latent classes, summarized by their predominant comorbidities and population share: fewest comorbidities (61.8%), psychiatric (18.3%), some comorbidities (10.0%), most comorbidities - no cardiovascular (3.6%), vascular (3.1%), autoimmune/joint/pain (2.2%), and most comorbidities (1.0%). We found minimal demographic differences across classes. CONCLUSION: Our study found groupings of migraine patients based on comorbidity that have the potential to be used to guide targeted treatment strategies and the development of new therapies.

Heterogeneity in preferences for outcomes of integrated care for persons with multiple chronic diseases: a latent class analysis of a discrete choice experiment.

PURPOSE: For an integrated care programme to be successful, preferences of the stakeholders involved should be aligned. The aim of this study is to investigate to which extent outcomes beyond health are valued and to study the heterogeneity of preferences of those involved in integrated care. METHODS: A discrete choice experiment (DCE) was conducted to elicit preferences for eight Triple Aim outcomes, i.e., physical functioning, psychological well-being, social relationships & participation, enjoyment of life, resilience, person-centeredness, continuity of care and total health and social care costs. Stakeholders were recruited among Dutch persons with multi-morbidity, informal caregivers, professionals, payers, and policymakers. A Bayesian mixed-logit model was used to analyse the data. Subsequently, a latent class analysis was performed to identify stakeholders with similar preferences. RESULTS: 739 stakeholders completed the DCE. Enjoyment of life was perceived as the most important outcome (relative importance: 0.221) across stakeholders, while total health and social care costs were perceived as least important (0.063). The latent class analysis identified four classes. The first class (19.9%) put most weight on experience with care outcomes. The second class (39%) favoured enjoyment of life. The third class (18%) focused relatively more on physical health. The fourth class (24%) had the least consistent preferences. CONCLUSION: This study has highlighted the heterogeneity in views of stakeholders in integrated care on what is important in health(care) for persons with multi-morbidity. To accurately value integrated care a variety of outcomes beyond health-e.g., enjoyment of life and experience with care-should be taken into account.

What Brings Young Adults to the Yoga Mat? Cross-Sectional Associations Between Motivational Profiles and Physical and Psychological Health Among Participants in the Project EAT-IV Survey.

Objectives: This study examines motivations for yoga and identifies unique motivational profiles among a sample of young adult yoga practitioners. This study further determines how young adult yoga practitioners' motivational profiles associate with physical health behaviors and psychological factors. Subjects/Setting: Survey data were drawn from the fourth wave of a large, population-based study (Project EAT-IV; Eating and Activity in Teens and Young Adults). Design: Latent class analysis (LCA) was used to identify motivational profiles among Project EAT-IV participants practicing yoga (n = 297; mean age: 30.8-1.7 years; 79.7 % female). Cross-sectional associations between latent motivational profiles, physical health behaviors, and psychological factors were determined with unadjusted and adjusted (gender, race/ethnicity, and body mass index) general linear models. Results: Across motivational profiles, most young adult yoga practitioners were motivated by enhanced fitness and stress reduction/relaxation. Additional motivations for yoga clustered by appearance (desire to change body appearance or weight) or mindfulness (desire to increase present moment awareness) underpinnings. The LCA characterized motivational profiles as "Low Appearance, Low Mindfulness" (Class 1; n = 77), "Low Appearance, High Mindfulness" (Class 2; n = 48), "High Appearance, Low Mindfulness" (Class 3; n = 79), and "High Appearance, High Mindfulness" (Class 4; n = 93). Having a profile with high mindfulness and low appearance motivations (Class 2) was associated with higher body satisfaction in comparison to the other classes (p < 0.001). Relative to Class 2, those with low mindfulness motivations (Class 1; Class 3) reported less total physical activity (p = 0.002) and those with high appearance motivations (Class 3; Class 4) reported higher compulsive exercise scores (p = 0.002). Conclusions: In this sample, high mindfulness and low appearance motivations for yoga appeared optimal for physical and psychological health. Cross-sectional findings suggest that young adult yoga practitioners' mind-body health may be supported by motivational underpinnings that emphasize yoga's internal (mindfulness) rather than external (appearance) benefits.

Three patterns of sensitization to mugwort, timothy, birch and their major allergen components revealed by Latent class analysis.

BACKGROUND: Mugwort, timothy, and birch are commonly spread pollen allergens across China. Although several studies have described the rates of sensitization to mugwort, timothy, and birch in China, most of them just on specific whole-allergen extracts but little was known about the co-sensitization characteristics of its allergen components. This study aimed to explore the patterns of sensitization to mugwort, timothy, birch, and their major allergen components. METHOD: Serum specific IgE (sIgE) levels of allergen components of mugwort, timothy, birch, and cross-reactive carbohydrate determinants (CCD) were detected in 160 patients whose serum showed positive results to at least one of mugwort, timothy, and birch allergens via EUROBlotMaster system. Skin prick testing was utilized to assess the allergic reaction of grass, weed, and tree allergens. Latent class analysis was used to identify underlying patterns of sensitization to a series of allergen components and their corresponding extracts. RESULTS: 88.8% of patients with allergic rhinitis and/or asthma were positive for mugwort-sIgE, 30% for timothy-sIgE, and 32.5% for birch-sIgE. By using the LCA model, three sensitization patterns as "Mugwort, Art v 4, Bet v 2 and Phl p 12 co-sensitized", "Timothy, mugwort, and CCD co-sensitized", "Mugwort and Art v 1 co-sensitized" were revealed based on optimal statistical fit in this study. Compared with other clusters, participants in "Mugwort, Art v 4, Bet v 2 and Phl p 12 co-sensitized" pattern were associated with higher sensitization rates of common grass and tree pollens allergen. The spearman's coefficient between CCD and timothy was larger than the corresponding values of CCD with mugwort or birch. CONCLUSION: CCD and profilin, as minor allergens in pollens, were associated with other pollen sIgE false positives presumably due to cross-reactivity. Patients sensitized with profilin had a significantly higher risk of sensitization to other pollens.