BACKGROUND: Childhood overweight and obesity is a global concern and has increased in Spain over the last decades. Combinations of lifestyle behaviors (i.e., diet, sleep, and sedentarism) are highly related to weight status. Therefore, this study aimed to identify lifestyle patterns among children from Madrid City, and analyze associations with the prevalence of overweight, obesity, and abdominal obesity, considering socio-economic factors.
METHODS: A cross-sectional analysis was conducted on 4545 children from the ENPIMAD study with data on diet, sleep, anthropometric, and socio-economic variables. K-means cluster analysis was used to identify lifestyle clusters, and logistic regressions were used to examine the associations between socio-economic indicators and cluster membership, and between clusters and weight status.
RESULTS: Findings show three lifestyle clusters (healthy, mixed, and unhealthy), with boys and older children more represented in the unhealthy cluster. Food insecurity and low socio-economic status were associated with unhealthier clusters in boys and girls. Children in unhealthier clusters were more likely to have obesity and abdominal obesity. However, these associations disappeared in girls after controlling for food insecurity.
CONCLUSIONS: These results provide insight into the combination of behaviors and socio-economic factors associated with childhood obesity that may aid in the design of future interventions.

OBJECTIVE: To classify older adults into clusters based on accumulating long-term conditions (LTC) as trajectories, characterise clusters and quantify their associations with all-cause mortality.
METHODS: We conducted a longitudinal study using the English Longitudinal Study of Ageing over 9 years (n=15 091 aged 50 years and older). Group-based trajectory modelling was used to classify people into clusters based on accumulating LTC over time. Derived clusters were used to quantify the associations between trajectory memberships, sociodemographic characteristics and all-cause mortality by conducting regression models.
RESULTS: Five distinct clusters of accumulating LTC trajectories were identified and characterised as: \'no LTC\' (18.57%), \'single LTC\' (31.21%), \'evolving multimorbidity\' (25.82%), \'moderate multimorbidity\' (17.12%) and \'high multimorbidity\' (7.27%). Increasing age was consistently associated with a larger number of LTCs. Ethnic minorities (adjusted OR=2.04; 95% CI 1.40 to 3.00) were associated with the \'high multimorbidity\' cluster. Higher education and paid employment were associated with a lower likelihood of progression over time towards an increased number of LTCs. All the clusters had higher all-cause mortality than the \'no LTC\' cluster.
CONCLUSIONS: The development of multimorbidity in the number of conditions over time follows distinct trajectories. These are determined by non-modifiable (age, ethnicity) and modifiable factors (education and employment). Stratifying risk through clustering will enable practitioners to identify older adults with a higher likelihood of worsening LTC over time to tailor effective interventions to prevent mortality.

UNASSIGNED: Parental health literacy is important to children\'s health and development, especially in the first 3 years. However, few studies have explored effective intervention strategies to improve parental literacy.
UNASSIGNED: This study aimed to determine the effects of a WeChat official account (WOA)-based intervention on parental health literacy of primary caregivers of children aged 0-3 years.
UNASSIGNED: This cluster randomized controlled trial enrolled 1332 caregiver-child dyads from all 13 community health centers (CHCs) in Minhang District, Shanghai, China, between April 2020 and April 2021. Participants in intervention CHCs received purposefully designed videos via a WOA, which automatically recorded the times of watching for each participant, supplemented with reading materials from other trusted web-based sources. The contents of the videos were constructed in accordance with the comprehensive parental health literacy model of WHO (World Health Organization)/Europe (WHO/Europe). Participants in control CHCs received printed materials similar to the intervention group. All the participants were followed up for 9 months. Both groups could access routine child health services as usual during follow-up. The primary outcome was parental health literacy measured by a validated instrument, the Chinese Parental Health Literacy Questionnaire (CPHLQ) of children aged 0-3 years. Secondary outcomes included parenting behaviors and children\'s health outcomes. We used the generalized linear mixed model (GLMM) for data analyses and performed different subgroup analyses. The β coefficient, risk ratio (RR), and their 95% CI were used to assess the intervention\'s effect.
UNASSIGNED: After the 9-month intervention, 69.4% (518/746) of caregivers had watched at least 1 video. Participants in the intervention group had higher CPHLQ total scores (β=2.51, 95% CI 0.12-4.91) and higher psychological scores (β=1.63, 95% CI 0.16-3.10) than those in the control group. The intervention group also reported a higher rate of exclusive breastfeeding (EBF) at 6 months (38.9% vs 23.44%; RR 1.90, 95% CI 1.07-3.38) and a higher awareness rate of vitamin D supplementation for infants younger than 6 months (76.7% vs 70.5%; RR 1.39, 95% CI 1.06-1.82). No significant effects were detected for the physical score on the CPHLQ, breastfeeding rate, routine checkup rate, and children\'s health outcomes. Furthermore, despite slight subgroup differences in the intervention\'s effects on the total CPHLQ score and EBF rate, no interaction effect was observed between these subgroup factors and intervention factors.
UNASSIGNED: Using a WHO literacy model-based health intervention through a WOA has the potential of improving parental health literacy and EBF rates at 6 months. However, innovative strategies and evidence-based content are required to engage more participants and achieve better intervention outcomes.

Karst groundwater, which is one of most important drinking water sources, is vulnerable to be polluted as its closed hydraulic relation with surface water. Thus, it is very important to identify the groundwater source to control groundwater pollution. The Pearson correlation coefficient among major ions (Na + K+, Ca2+, Mg2+, HCO3 -, SO4 2-, and Cl-) was employed to deduce the groundwater types in Zhong Liang Mountain, Southwest China. Then, the combined method of principal component analysis and cluster analysis were employed to identify the groundwater sources in a typical karst region of southwest China. The results shown that (1) the high positive correlation between cations and anions indicated the water-rock reaction of Ca-HCO3, Ca-SO4, (Na + K)-Cl, and Mg-SO4. (2) The major two principal components that would represent water-rock reaction of CaSO4 and Ca-HCO3 would, respectively, explain 60.41% and 31.80% of groundwater information. (3) Based on the two principal components, 33 groundwater samples were clustered into eight groups through hierarchical clustering, each group has similar water-rock reaction. The findings would be employed to forecast the surge water, that was an important work for tunnel construction and operation. PRACTITIONER POINTS: The components of groundwater was highly correlated with water-rock reaction. The principal component analysis screens the types of groundwater. The cluster analysis identifies the groundwater sources.

OBJECTIVE: Systemic lupus erythematous (SLE) is a heterogenous disease characterised by a large panel of autoantibodies and a wide spectrum of clinical signs and symptoms that engender different outcomes. We aimed to identify distinct, homogeneous SLE patients\' phenotypes.
METHODS: This retrospective study enrolled SLE patients meeting the Systemic Lupus International Collaborating Clinics (SLICC) classification criteria, enrolled in the French multicentre \"APS (antiphospholipid syndrome) and SLE‿ Registry. Based on 29 variables selected to cover a broad range of clinical and laboratory (excluding autoantibodies) SLE manifestations, unsupervised multiple correspondence analysis followed by hierarchical ascendent-clustering analysis assigned different phenotypes.
RESULTS: We included 440 patients, mostly women (94.3%). Median age at SLE diagnosis was 24 (IQR 19-32) years. Cluster analysis yielded three distinct subgroups based on cumulative clinical manifestations, not autoantibody pattern. Cluster 1 (n=91) comprised mostly Caucasian patients, with APS-associated clinical and biological manifestations, e.g., livedo, seizure, thrombocytopaenia and haemolytic anaemia. Cluster 2 (n=221), the largest, included patients with mild clinical manifestations, mainly articular, more frequently associated with Sjögren\'s syndrome and with less frequent autoantibody-positivity. Cluster 3 (n=128) consisted of patients with the largest panel of SLE-specific clinical manifestations (cutaneous, articular, proliferative nephritis, pleural, cardiac and haematological), the most frequent autoantibody-positivity, low complement levels, and more often of Asian and sub-Saharan African origin.
CONCLUSIONS: This unsupervised clustering method distinguished three distinct SLE patient subgroups, highlighting SLE heterogeneity.

BACKGROUND: Laboratory test overuse in hospitals is a form of healthcare waste that also harms patients. Developing and evaluating interventions to reduce this form of healthcare waste is critical. We detail the protocol for our study which aims to implement and evaluate the impact of an evidence-based, multicomponent intervention bundle on repetitive use of routine laboratory testing in hospitalized medical patients across adult hospitals in the province of British Columbia, Canada.
METHODS: We have designed a stepped-wedge cluster randomized trial to assess the impact of a multicomponent intervention bundle across 16 hospitals in the province of British Columbia in Canada. We will use the Knowledge to Action cycle to guide implementation and the RE-AIM framework to guide evaluation of the intervention bundle. The primary outcome will be the number of routine laboratory tests ordered per patient-day in the intervention versus control periods. Secondary outcome measures will assess implementation fidelity, number of all common laboratory tests used, impact on healthcare costs, and safety outcomes. The study will include patients admitted to adult medical wards (internal medicine or family medicine) and healthcare providers working in these wards within the participating hospitals. After a baseline period of 24 weeks, we will conduct a 16-week pilot at one hospital site. A new cluster (containing approximately 2-3 hospitals) will receive the intervention every 12 weeks. We will evaluate the sustainability of implementation at 24 weeks post implementation of the final cluster. Using intention to treat, we will use generalized linear mixed models for analysis to evaluate the impact of the intervention on outcomes.
CONCLUSIONS: The study builds upon a multicomponent intervention bundle that has previously demonstrated effectiveness. The elements of the intervention bundle are easily adaptable to other settings, facilitating future adoption in wider contexts. The study outputs are expected to have a positive impact as they will reduce usage of repetitive laboratory tests and provide empirically supported measures and tools for accomplishing this work.
BACKGROUND: This study was prospectively registered on April 8, 2024, via ClinicalTrials.gov Protocols Registration and Results System (NCT06359587). https://classic.
RESULTS: gov/ct2/show/NCT06359587?term=NCT06359587&recrs=ab&draw=2&rank=1.

UNASSIGNED: Serious illness conversations (SICs) that elicit patients\' values, goals, and care preferences reduce anxiety and depression and improve quality of life, but occur infrequently for patients with cancer. Behavioral economic implementation strategies (nudges) directed at clinicians and/or patients may increase SIC completion.
UNASSIGNED: To test the independent and combined effects of clinician and patient nudges on SIC completion.
UNASSIGNED: A 2 × 2 factorial, cluster randomized trial was conducted from September 7, 2021, to March 11, 2022, at oncology clinics across 4 hospitals and 6 community sites within a large academic health system in Pennsylvania and New Jersey among 163 medical and gynecologic oncology clinicians and 4450 patients with cancer at high risk of mortality (≥10% risk of 180-day mortality).
UNASSIGNED: Clinician clusters and patients were independently randomized to receive usual care vs nudges, resulting in 4 arms: (1) active control, operating for 2 years prior to trial start, consisting of clinician text message reminders to complete SICs for patients at high mortality risk; (2) clinician nudge only, consisting of active control plus weekly peer comparisons of clinician-level SIC completion rates; (3) patient nudge only, consisting of active control plus a preclinic electronic communication designed to prime patients for SICs; and (4) combined clinician and patient nudges.
UNASSIGNED: The primary outcome was a documented SIC in the electronic health record within 6 months of a participant\'s first clinic visit after randomization. Analysis was performed on an intent-to-treat basis at the patient level.
UNASSIGNED: The study accrued 4450 patients (median age, 67 years [IQR, 59-75 years]; 2352 women [52.9%]) seen by 163 clinicians, randomized to active control (n = 1004), clinician nudge (n = 1179), patient nudge (n = 997), or combined nudges (n = 1270). Overall patient-level rates of 6-month SIC completion were 11.2% for the active control arm (112 of 1004), 11.5% for the clinician nudge arm (136 of 1179), 11.5% for the patient nudge arm (115 of 997), and 14.1% for the combined nudge arm (179 of 1270). Compared with active control, the combined nudges were associated with an increase in SIC rates (ratio of hazard ratios [rHR], 1.55 [95% CI, 1.00-2.40]; P = .049), whereas the clinician nudge (HR, 0.95 [95% CI, 0.64-1.41; P = .79) and patient nudge (HR, 0.99 [95% CI, 0.73-1.33]; P = .93) were not.
UNASSIGNED: In this cluster randomized trial, nudges combining clinician peer comparisons with patient priming questionnaires were associated with a marginal increase in documented SICs compared with an active control. Combining clinician- and patient-directed nudges may help to promote SICs in routine cancer care.
UNASSIGNED: ClinicalTrials.gov Identifier: NCT04867850.

In a phase 3 trial (PANAMO, NCT04333420), vilobelimab, a complement 5a (C5a) inhibitor, reduced 28-day mortality in mechanically ventilated COVID-19 patients. This post hoc analysis of 368 patients aimed to explore treatment heterogeneity through unsupervised learning. All available clinical variables at baseline were used as input. Treatment heterogeneity was assessed using latent class analysis (LCA), Ward\'s hierarchical clustering (HC) and the adjudication to previously described clinical sepsis phenotypes. The primary outcome was 28-day mortality. For LCA, a 2-class latent model was deemed most suitable. In the LCA model, 82 (22%) patients were assigned to class 1 and 286 (78%) to class 2. Class 1 was defined by more severely ill patients with significantly higher mortality. In an adjusted logistic regression, no heterogeneity of treatment effect (HTE) between classes was observed (p = 0.998). For HC, no significant classes were found (p = 0.669). Using the previously described clinical sepsis subtypes, 41 patients (11%) were adjudicated subtype alpha (α), 17 (5%) beta (β), 112 (30%) delta (δ) and 198 (54%) gamma (γ). HTE was observed between clinical subtypes (p = 0.001) with improved 28-day mortality after treatment with vilobelimab for the δ subtype (OR = 0.17, 95% CI 0.07-0.40, p < 0.001). No signal for harm of treatment with vilobelimab was observed in any class or clinical subtype. Overall, treatment effect with vilobelimab was consistent across different classes and subtypes, except for the δ subtype, suggesting potential additional benefit for the most severely ill patients.

OBJECTIVE: Identifying whether experienced symptom burden in individuals with medical predisposition indicates somatic symptom disorder (SSD) is challenging, given the high overlap in the phenomenology of symptoms within this group. This study aimed to enhance understanding SSD in individuals at risk for heart failure.
METHODS: Cross-sectional data from the Hamburg City Health Study was analyzed including randomly selected individuals from the general population of Hamburg, Germany recruited from February 2016 to November 2018. SSD symptoms assessed with the Somatic Symptom Scale-8 and the Somatic Symptom Disorder-12 scale were categorized by applying cluster analysis including 412 individuals having at least 5% risk for heart failure-related hospitalization within the next ten years. Clusters were compared for biomedical and psychological factors using ANOVA and chi-square tests. Linear regressions, adjusting for sociodemographic, biomedical, and psychological factors, explored associations between clusters with general practitioner visits and quality of life.
RESULTS: Three clusters emerged: none (n = 215; 43% female), moderate (n = 151; 48% female), and severe (n = 46; 54% female) SSD symptom burden. The SSS-8 mean sum scores were 3.4 (SD = 2.7) for no, 6.4 (SD = 3.4) for moderate, and 12.4 (SD = 3.7) for severe SSD symptom burden. The SSD-12 mean sum scores were 3.1 (SD = 2.6) for no, 12.2 (SD = 4.2) for moderate, and 23.5 (SD = 6.7) for severe SSD symptom burden. Higher SSD symptom burden correlated with biomedical factors (having diabetes: p = .005 and dyspnea: p ≤ .001) and increased psychological burden (depression severity: p ≤ .001; anxiety severity: p ≤ .001), irrespective of heart failure risk (p = .202). Increased SSD symptoms were associated with more general practitioner visits (β = 0.172; p = .002) and decreased physical quality of life (β = -0.417; p ≤ .001).
CONCLUSIONS: Biomedical factors appear relevant in characterizing individuals at risk for heart failure, while psychological factors affect SSD symptom experience. Understanding SSD symptom diversity and addressing subgroup needs could prove beneficial.

UNASSIGNED: Understanding chronic disease prevalence, patterns, and co-occurrence is pivotal for effective health care planning and disease prevention strategies. In this paper, we aimed to identify the clustering of major non-communicable diseases among Indian adults aged ≥50 years based on their self-reported diagnosed non-communicable disease status and to find the risk factors that heighten the risk of developing the identified disease clusters.
UNASSIGNED: We utilised data from the nationally representative survey Study on Global AGEing and Adult Health (SAGE Wave-2). The eligible sample size was 6298 adults aged ≥50 years. We conducted the latent class analysis to uncover latent subgroups of multimorbidity and the multinomial logistic regression to identify the factors linked to observed latent class membership.
UNASSIGNED: The latent class analysis grouped our sample of men and women >49 years old into three groups - mild multimorbidity risk (41%), moderate multimorbidity risk (30%), and severe multimorbidity risk (29%). In the mild multimorbidity risk group, the most prevalent diseases were asthma and arthritis, and the major prevalent disease in the moderate multimorbidity risk group was low near/distance vision, followed by depression, asthma, and lung disease. Angina, diabetes, hypertension, and stroke were the major diseases in the severe multimorbidity risk category. Individuals with higher ages had an 18% and 15% higher risk of having moderate multimorbidity and severe multimorbidity compared to those in the mild multimorbidity category. Females were more likely to have a moderate risk (3.36 times) and 2.82 times more likely to have severe multimorbidity risk.
UNASSIGNED: The clustering of diseases highlights the importance of integrated disease management in primary care settings and improving the health care system to accommodate the individual\'s needs. Implementing preventive measures and tailored interventions, strengthening the health and wellness centres, and delivering comprehensive primary health care services for secondary and tertiary level hospitalisation may cater to the needs of multimorbid patients.