Prognostic value of illness perception on changes in knee pain among elderly individuals: Two-year results from the Frederiksberg Cohort study

Objective

To investigate the prognostic value of illness perception (IP) on knee pain, quality of life (QoL) and functional level in elderly individuals reporting knee pain.

Design

A prospective cohort study of 1552 elderly with knee pain comparing two previously established clusters based on the Brief Illness Perception questionnaire. Cluster 1 ("Concerned optimists" [hypothesized unfavorable profile]; n ​= ​642) perceived their knee pain as a greater threat to them than Cluster 2 ("Unconcerned confident" [hypothesized favorable profile]; n ​= ​910). Primary outcome was the change from baseline to year 2 in the KOOS Pain subscale. Secondary outcomes were changes from baseline in quality of life (EuroQol-5 Domain and EQ VAS) and in the KOOS subscales Symptom, Activities of Daily Living, Knee-related QoL and Sports and recreation. Analyses were done on the original Intention-To-Survey (ITS) population, using repeated measures mixed linear models.

Results

Among the ITS population, 841 (54%) responded to the 2-year survey. There was a statistically significant but clinically irrelevant cluster difference in the 2-year change from baseline in KOOS pain (mean difference: 6.0 KOOS points [95% CI: 7.3 to -4.7]) explained by a minor improvement in Cluster 1: (6.2 points) and no changes in Cluster 2: (0.2 points). Comparable results were found across the secondary outcomes. Clinically irrelevant cluster changes in IP were seen.

Conclusion

In a cohort of people with knee pain, IP phenotype (i.e., Clusters) were of no prognostic value for the 2-year changes in pain, function, and QoL. Targeting IP may not be relevant in this patient population.

Trial registration number and date of registration

The Frederiksberg Cohort study was pre-registered at clinicaltrials.gov (NCT03472300) on March 21, 2018.

Age at first calving and productive performance of primiparous Holsteins

This study investigated the age at first calving in Holstein heifers and its impact on various production parameters. A sample of 737 Holstein heifers born between 2015 and 2018 and finishing their first lactations between 2018 and 2020 was included. Cluster analysis revealed three groups based on age at first calving: high precocity, medium precocity and low precocity. Medium-precocity group exhibited the highest 305-day milk yield and peak milk production. Additionally, the same group demonstrated superior mean production per lactation, 305-day milk protein content, and 305-day milk yield. The lowest somatic cell count was found in the low-precocity group. In conclusion, medium-precocity cows showed better results such as higher 305-day milk yield and peak milk production.

A Fuzzy Clustering Approach to Identify Pedestrians' Traffic Behavior Patterns

BACKGROUND

Pattern recognition of pedestrians' traffic behavior can enhance the management efficiency of interested groups by targeting access to them and facilitating planning via more specific surveys. This study aimed to evaluate the pedestrians' traffic behavior pattern by fuzzy clustering algorithm and assess the factors related to higher-risk traffic behavior of pedestrians. Study Design: This study is a secondary methodological study based on the data from a cross-sectional study.

METHODS

The fuzzy c-means (FCM), as a machine learning clustering method, was conducted to identify the pattern of traffic behaviors by collecting data from 600 pedestrians in Urmia, Iran via "the Pedestrian Behavior Questionnaire" (PBQ) and using 5 domains of PBQ. Multiple logistic regression was fitted to identify risk factors of traffic behaviors.

RESULTS

Results revealed two clusters consisting of lower-risk and higher-risk behaviors. The majority of pedestrians (64.33%) were in the lower-risk cluster. Subjects≤33 years old (Odds ratio [OR]=1.92, P<0.001), subjects with≤6 years of education (OR=1.74, P=0.010), males (OR=1.90, P=0.001), unmarried pedestrians (OR=3.61, P=0.007), and users of public transportation (OR=2.01, P=0.002) were more likely to have higher-risk traffic behavior.

CONCLUSION

We identified traffic behavior patterns of Urmia pedestrians with lower-risk and higher-risk behaviors via FCM. The findings from this study would be helpful for policymakers to promote safety measures and train pedestrians.

Mental resources, mental health and sociodemography: a cluster analysis based on a representative population survey in a large German city

BACKGROUND

Mental resources such as optimism and social support are important to face different stressors. The aim of this study is to identify groups in the population that are similar in terms of their mental resources.

METHODS

For this purpose, a randomly selected general population community sample was used, representative for the city of Leipzig, Germany. In a two-stage process, three clusters were identified using hierarchical cluster analysis and the K-means method and then tested with a multinomial logistic regression analysis for differences in sociodemographic characteristics.

RESULTS

Three clusters were identified which vary in their extent of social support and optimism. In distinguishing between those with higher and lower (medium or poor) mental resources, male gender, unemployment, being born abroad and low household income are risk factors for having fewer mental resources. Internal migrants from West Germany and persons with children at home have a higher chance of being in the type with good mental resources. The groups with medium and lower mental resources differ significantly only by variables living with a partner and employment.

CONCLUSION

Our results indicate that good mental resources are associated with good mental health. Special mental health care programs, focusing in particular on the needs of vulnerable groups with poor mental resources within a society, should be implemented.

Phenotyping for percutaneous coronary intervention and long-term recurrent weighted outcomes

INTRODUCTION

Percutaneous coronary interventions (PCI) are often performed in multimorbid patients with heterogeneous characteristics and variable clinical outcomes. We aimed to identify distinct clinical phenotypes utilizing machine learning and explore their relationship with long-term recurrent and weighted outcomes.

METHODS

This prospective observational cohort study enrolled all-comer PCI patients in 2020-2021. Multiple imputation k-means clustering was utilized to detect specific phenotypes. The study endpoints were patient-oriented and device oriented composite endpoints (POCE, DOCE), its individual components, and major bleeding. We applied semiparametric regression models for recurrent and weighted endpoints.

RESULTS

The study included a total of 643 patients. We unveiled three phenotype clusters: 1) inflammatory (n = 44, with high white blood cell counts, high values of C-reactive protein (CRP) and neutrophil-to-lymphocyte ratio), 2) high erythrocyte sedimentation rate (ESR) (n = 204), and 3) non-inflammatory (n = 395). For ACS-only population, we four distinct phenotypes (high-CRP, high-ESR, high aspartate-aminotransferase, and normal). For all-comer PCI patients, identified phenotypes had a higher risk of POCE (mean ratio (MR) 1.42 (95% confidence interval (CI) 1.11-1.81) and MR 2.01 (95% CI 1.58-2.56), respectively), DOCE (MR 1.61 (95% CI 1.20-2.16), MR 2.60 (95%CI 1.94-3.48), respectively), and stroke (hazard ratio (HR) 2.86 (95% CI 1.10-7.4), 6.83 (95% CI 2.01-23.2)). Similarly, high-ESR and high-CRP phenotypes of ACS patients were significantly associated with the development of clinical composite outcomes.

CONCLUSION

Machine learning unveiled three distinct phenotype clusters in patients after PCI that were linked with the risk of recurrent and weighted clinical endpoints. German Clinical Trial Registry number: DRKS00020892.

A multilevel approach for screening natural compounds as an antiviral agent for COVID-19

The COVID-19 has a worldwide spread, which has prompted concerted efforts to find successful drug treatments. Drug design focused on finding antiviral therapeutic agents from plant-derived compounds which may disrupt the attachment of SARS-CoV-2 to host cells is with a pivotal need and role in the last year. Herein, we provide an approach based on drug design methods combined with machine learning approaches to classify and discover inhibitors for COVID-19 from natural products. The spike receptor-binding domain (RBD) was docked with database of 125 ligands. The docking protocol based on several steps was performed within Autodock Vina to identify the high-affinity binding mode and to reveal more insights into interaction between the phytochemicals and the RBD domain. A protein-ligand interaction analyzer has been developed. The drug-likeness properties of explored inhibitors are analyzed in the frame of exploratory data analyses. The developed computational protocol yielded a comprehensive pipeline for predicting the inhibitors to prevent the entry RBD region.

Comorbidities in unclassifiable interstitial lung disease

BACKGROUND

Comorbidities are common in interstitial lung diseases (ILD) and have an important association with survival, but the frequency and prognostic impact of comorbidities in unclassifiable interstitial lung disease (uILD) remains elusive. We aimed to describe the prevalence of comorbidities and assess the impact on survival in patients with uILD. Furthermore, we aimed to identify and characterize potential phenotypes based on clusters of comorbidities and examine their association with disease progression and survival.

METHODS

Incident patients diagnosed with uILD were identified at two ILD referral centers in Denmark and Germany from 2003 to 2018. The diagnosis uILD was based on multidisciplinary team meetings. Clinical characteristics and comorbidities were extracted from ILD registries and patient case files. Survival analyses were performed using Cox regression analyses, disease progression was analyzed by linear mixed effects models, and clusters of comorbidities were analyzed using self-organizing maps.

RESULTS

A total of 249 patients with uILD were identified. The cohort was dominated by males (60%), former (49%) or current (15%) smokers, median age was 70 years, mean FVC was 75.9% predicted, and mean DLCO was 49.9% predicted. One-year survival was 89% and three-year survival was 73%. Eighty-five percent of the patients had ≥ 1 comorbidities, 33% had ≥ 3 comorbidities and 9% had ≥ 5 comorbidities. The only comorbidity associated with excess mortality was dyslipidemia. No association between survival and number of comorbidities or the Charlson comorbidity index was observed. Three clusters with different comorbidities profiles and clinical characteristics were identified. A significant annual decline in FVC and DLCO % predicted was observed in cluster 1 and 2, but not in cluster 3. No difference in mortality was observed between the clusters.

CONCLUSIONS

The comorbidity burden in uILD is lower than reported in other types of ILD and the impact of comorbidities on mortality needs further clarification. Three clusters with distinct comorbidity profiles were identified and could represent specific phenotypes. No difference in mortality was observed between clusters, but slower disease progression was observed in cluster 3. Better understanding of disease behavior and mortality will require further studies of subgroups of uILD with longer observation time.

Clusters of comorbidities in fibrotic hypersensitivity pneumonitis

BACKGROUND

Hypersensitivity pneumonitis (HP) is a type of interstitial lung disease (ILD) with a variable disease course and prognosis ranging from inflammatory and self-limiting to irreversible and progressive pulmonary fibrosis. Comorbidities are common in HP and may have an impact on prognosis. Due to the heterogeneity of HP presentation and progression, the identification of specific phenotypes in relationship to disease course and outcome is essential. The aim of this study was to identify clusters of comorbidities which could represent phenotypes in fibrotic HP and examine their impact on prognosis.

METHODS

Patients diagnosed with fibrotic HP at a tertiary referral center for ILD were included. Comorbidities were systematically registered and clusters of comorbidities were identified using cluster analyses. Disease progression and survival was estimated for each cluster.

RESULTS

The cohort comprised 211 patients with 53.6% males, mean age 63.0, baseline FVC 72.7%, DLCO 44.1%. Median follow-up time was 1.8 years (IQR 0.7-3.9). Three clusters with distinct comorbidity profiles and clinical characteristics were identified. One cluster dominated by elder male patients with predominantly cardiovascular diseases was associated with more respiratory hospitalizations and a worse prognosis. Differences in pulmonary function or exercise capacity trajectories between clusters were not observed.

CONCLUSIONS

Three clusters with distinct comorbidities were identified and could represent phenotypes in fibrotic HP not previously recognized. The worst prognosis was observed in a cluster dominated by elder males with cardiovascular diseases. Increased focus on prevention and treatment of comorbidities could potentially improve the prognosis of patients with fibrotic HP.

A cluster analytic approach to examining the role of cortisol in the development of post-traumatic stress and dysphoria in adult traumatic injury survivors

Identification of specific risk factors for posttraumatic stress disorder (PTSD) versus depression after trauma has been challenging, in part due to the high comorbidity of these disorders. As exposure to trauma triggers activation of the hypothalamic-pituitary-adrenal (HPA)-axis, examining atypical stress responses via HPA-axis hormones, namely cortisol, may help in the delineation of these disorders. Indeed, extant research demonstrates that, following stress, individuals with chronic PTSD exhibit hypocortisolism (e.g., lower cortisol response than controls), while those with chronic depression exhibit hypercortisolism (e.g., higher response than controls). Less is known about the role of cortisol and these seemingly disparate profiles immediately following traumatic injury as well as whether cortisol can be used as a predictor of future development of PTSD versus depression symptoms. In this study cortisol was measured blood from 172 traumatic injury survivors during hospitalization (on average 2.5 days post-injury). PTSD and depression severity were assessed from Clinician Assessed PTSD Scale (CAPS-5) six-eight months later using a two-factor dimensional approach that measures trauma-specific symptoms of PTSD versus dysphoria (akin to depression). Cluster analysis was used to group individuals based on post-injury cortisol, PTSD, and dysphoria. Results demonstrated that trauma survivors who only developed symptoms of dysphoria at six months (with minimal symptoms of PTSD) were differentiated by high post-injury cortisol compared to other groups. By contrast, individuals who developed symptoms of both PTSD and dysphoria were differentiated by low post-injury cortisol and most severe symptoms of PTSD. Findings provide support for the presence of subgroups of trauma survivors defined, in part, by post-trauma cortisol.

Urban environment and obesity and weight-related behaviours in primary school children

BACKGROUND

Urban environments are characterised by many factors that may influence children's lifestyle and increase the risk of childhood obesity, but multiple urban exposures have scarcely been studied.

OBJECTIVE

We evaluated the association between multiple urban exposures and childhood obesity outcomes and weight-related behaviours.

METHODS

We conducted a cross-sectional study including 2213 children aged 9-12 years in Sabadell, Spain. We estimated ambient air pollution, green spaces, built and food environment, road traffic and road traffic noise at residential addresses through a total of 28 exposure variables in various buffers. Childhood obesity outcomes included body mass index (BMI), waist circumference and body fat. Weight-related behaviours included diet (fast food and sugar-sweetened beverage consumption), physical activity, sedentary behaviour, sleep duration and well-being. Associations between exposures (urban environment) and outcomes (obesity and behaviours) were estimated in single and multiple-exposure regression models and in a hierarchical clustering on principal components (HCPC) analysis.

RESULTS

Forty percent of children were overweight or obese. In single exposure models, very few associations were observed between the urban exposures and obesity outcomes or weight-related behaviours after correction for multiple testing. In multiple exposure models, PM_coarse, denser unhealthy food environment and land use mix were statistically significant associated with childhood obesity outcomes (e.g 17.7 facilities/km² increase of unhealthy food environment (OR overweight/obesity status) = 1.20 [95% CI: 1.01; 1.44]). Cluster analysis identified 5 clusters of urban exposures. Compared to the most neutral cluster, the cluster with high air pollution, road traffic, and road noise levels was associated with a higher BMI and higher odds of overweight and obesity (β (zBMI) = 0.17, [95% CI: 0.01, 0.17]; OR (overweight/obesity) = 1.36, [95% CI: 0.99, 1.85]); the clusters were not associated with the weight-related behaviours.

CONCLUSIONS

This systematic study of many exposures in the urban environment suggests that an exposure pattern characterised by higher levels of ambient air pollution, road traffic and road traffic noise is associated with increased childhood obesity risk and that PM_coarse, land use mix and food environment are separately associated with obesity risk. These findings require follow-up in longitudinal studies and different settings.

Outbreak of Central American born Shigella sonnei in two youth camps in Belgium in the summer of 2019

In 2019, an outbreak of Shigella sonnei occurred during two youth camps in Belgium. The clustering of isolates from both camps was confirmed by next-generation sequencing, as well as a secondary infection of a technician. The outbreak strain clustered with internationally isolated strains from patients with recent travel history to Central America. This report exemplifies enhanced surveillance and international collaboration between public health institutes by enabling to link local outbreaks to region-specific sublineages circulating abroad.

Spatio-temporal mapping of breast and prostate cancers in South Iran from 2014 to 2017

Background

The most common gender-specific malignancies are cancers of the breast and the prostate. In developing countries, cancer screening of all at risk is impractical because of healthcare resource limitations. Thus, determining high-risk areas might be an important first screening step. This study explores incidence patterns of potential high-risk clusters of breast and prostate cancers in southern Iran.

Methods

This cross-sectional study was conducted in the province of Kerman, South Iran. Patient data were aggregated at the county and district levels calculating the incidence rate per 100,000 people both for cancers of the breast and the prostate. We used the natural-break classification with five classes to produce descriptive maps. A spatial clustering analysis (Anselin Local Moran’s I) was used to identify potential clusters and outliers in the pattern of these cancers from 2014 to 2017.

Results

There were 1350 breast cancer patients (including, 42 male cases) and 478 prostate cancer patients in the province of Kerman, Iran during the study period. After 45 years of age, the number of men with diagnosed prostate cancer increased similarly to that of breast cancer for women after 25 years of age. The age-standardised incidence rate of breast cancer for women showed an increase from 29.93 to 32.27 cases per 100,000 people and that of prostate cancer from 13.93 to 15.47 cases per 100,000 during 2014–2017. Cluster analysis at the county level identified high-high clusters of breast cancer in the north-western part of the province for all years studied, but the analysis at the district level showed high-high clusters for only two of the years. With regard to prostate cancer, cluster analysis at the county and district levels identified high-high clusters in this area of the province for two of the study years.

Conclusions

North-western Kerman had a significantly higher incidence rate of both breast and prostate cancer than the average, which should help in designing tailored screening and surveillance systems. Furthermore, this study generates new hypotheses regarding the potential relationship between increased incidence of cancers in certain geographical areas and environmental risk factors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-020-07674-8.

Provenance and fate of trace and rare earth elements in the sediment-aquifers systems of Majuli River Island, India

In this work we present a completely new dataset of Rare Earth Element (REE) distribution and fractionation in the groundwater and sediments of the world's largest populated river island-Majuli, located in the Brahmaputra River, India. Groundwater (n = 9) and borehole sediments (n = 23) of different depths were collected randomly and analyzed for REEs using inductively coupled plasma mass spectrometry (ICP-MS). Multivariate statistical techniques were applied to determine interrelationships among different REEs. Both water and sediments exhibit a higher content of light rare earth elements (LREEs) than heavy rare earth elements (HREEs), implying that source rock composition primarily controls the REE signatures of these river sediments, largely owing to variations in levels of chlorite and monazite, which are more abundant in bottom river sediments of the Brahmaputra. However, lower LREE/HREE ratios in groundwater samples (8.42-14.48) compared to sediments (8.9-52.6) suggest less dissolved phase mobilization of LREE during weathering and transport. Hierarchical cluster analysis showed more consistent clustering in sediment compared to water and clear demarcations of MREE, HREE and LREE were observed in the sediments. The primitive mantle-normalized REE patterns of borehole sediments were similar to the upper continental crust (UCC) and the compositions of average Himalayan rocks. LREE enrichment compared to HREE suggest dominance of a felsic source. However, a La/V versus Th/Yb plot suggests a small contribution from the mafic source component. The sediments show high Th/Sc (>1 of UCC) and high Zr/Sc. A Eu/Eu* verses Gd_N/Yb_N plot suggests that the dominant source with Upper crustal composition has undergone multiple recycling.

Further Development of P4 Approach to Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is a heterogeneous disorder. Cluster analysis has identified different physiologic subtypes with respect to symptoms. A difference exists in cardiovascular risk from OSA between the 7 subtypes identified. There are 3 basic subtypes replicated in multiple studies: (a) a group where insomnia is the main symptom; (b) an asymptomatic group; (c) a group with marked excessive sleepiness. The symptomatic benefit from treatment with nasal CPAP varies between these 3 subtypes. Data from the Sleep Heart Health Study reveal that the increased risk of cardiovascular disease from OSA occurs only in the excessively sleepy group.

Heavy metal distribution, contamination and analysis of sources - Intertidal zones of Sandu Bay, Ningde, China

Concentrations of heavy metals in sediments and seawaters from the intertidal zone are analyzed along with cage-bred fish in the Sandu Bay of Fujian Province in China. Elements measured are As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn. The concentrations of Cu and Ni found in the sediments do not meet the first standard of the Chinese National Criteria for Marine Sediment Quality. The results of I_geo, EF, and CF index calculations for the sediment samples clearly prove anthropogenic causes of contamination. The water quality standard for fisheries was exceeded by As, Hg, and Cu. Cage-bred fish show increased levels of As, Cr, and Zn. Significant associations are found for AsCu and NiZn. These findings can be related to coal and crude oil combustion and processes associated with the production of batteries, steel, and alloys. The results point to industrial source locations along discharging rivers north and northwest of the Sandu Bay.

Metabotyping for the development of tailored dietary advice solutions in a European population: the Food4Me study

Traditionally, personalised nutrition was delivered at an individual level. However, the concept of delivering tailored dietary advice at a group level through the identification of metabotypes or groups of metabolically similar individuals has emerged. Although this approach to personalised nutrition looks promising, further work is needed to examine this concept across a wider population group. Therefore, the objectives of this study are to: (1) identify metabotypes in a European population and (2) develop targeted dietary advice solutions for these metabotypes. Using data from the Food4Me study (n 1607), k-means cluster analysis revealed the presence of three metabolically distinct clusters based on twenty-seven metabolic markers including cholesterol, individual fatty acids and carotenoids. Cluster 2 was identified as a metabolically healthy metabotype as these individuals had the highest Omega-3 Index (6·56 (sd 1·29) %), carotenoids (2·15 (sd 0·71) µm) and lowest total saturated fat levels. On the basis of its fatty acid profile, cluster 1 was characterised as a metabolically unhealthy cluster. Targeted dietary advice solutions were developed per cluster using a decision tree approach. Testing of the approach was performed by comparison with the personalised dietary advice, delivered by nutritionists to Food4Me study participants (n 180). Excellent agreement was observed between the targeted and individualised approaches with an average match of 82 % at the level of delivery of the same dietary message. Future work should ascertain whether this proposed method could be utilised in a healthcare setting, for the rapid and efficient delivery of tailored dietary advice solutions.

Identification of long-range transport pathways and potential sources of PM2.5 and PM10 in Beijing from 2014 to 2015

Trajectory clustering, potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) methods were applied to investigate the transport pathways and identify potential sources of PM_2.5 and PM₁₀ in different seasons from June 2014 to May 2015 in Beijing. The cluster analyses showed that Beijing was affected by trajectories from the south and southeast in summer and autumn. In winter and spring, Beijing was not only affected by the trajectories from the south and southeast, but was also affected by trajectories from the north and northwest. In addition, the analyses of the pressure profile of backward trajectories showed that backward trajectories, which have important influence on Beijing, were mainly distributed above 970hPa in summer and autumn and below 950hPa in spring and winter. This indicates that PM_2.5 and PM₁₀ were strongly affected by the near surface air masses in summer and autumn and by high altitude air masses in winter and spring. Results of PSCF and CWT analyses showed that the largest potential source areas were identified in spring, followed by winter and autumn, then summer. In addition, potential source regions of PM₁₀ were similar to those of PM_2.5. There were a clear seasonal and spatial variation of the potential source areas of Beijing and the airflow in the horizontal and vertical directions. Therefore, more effective regional emission reduction measures in Beijing's surrounding provinces should be implemented to reduce emissions of regional sources in different seasons.

Multivariate Analyses of Heavy Metals in Surface Soil Around an Organized Industrial Area in Eskisehir, Turkey

A total of 50 surface industrial area soil in Eskisehir, Turkey were collected and the concentrations of As, Cr, Cd, Co, Cu, Ni, Pb, Zn, Fe and Mg, at 11.34, 95.8, 1.37, 15.28, 33.06, 143.65, 14.34, 78.79 mg/kg, 188.80% and 78.70%, respectively. The EF values for As, Cu, Pb and Zn at a number of sampling sites were found to be the highest among metals. Igeo-index results show that the study area is moderately polluted with respect to As, Cd, Ni. According to guideline values of Turkey Environmental Quality Standard for Soils, there is no problem for Pb, but the Cd values are fairly high. However, Cr, Cu, Ni and Zn values mostly exceed the limits. Cluster analyses suggested that soil the contaminator values are homogenous in those sub classes. The prevention and remediation of the heavy metal soil pollution should focus on these high-risk areas in the future.

Influence of ligands on metal speciation, transport and toxicity in a tropical river during wet (monsoon) period

Metal speciation and transport are seldom assessed in densely populated Tropical River. An evaluation of the phase distribution for Copper (Cu), Lead (Pb) and Zinc (Zn) along with chemical speciation, variance with different water quality parameters and toxicity were conducted in the Brahmaputra River of India from upstream to downstream during wet (monsoon) periods in July 2014. Results indicated that metal free ions and carbonates were dominant in the inorganic fractions whereas metal concentrations were negligible in the anionic inorganic fractions. Due to high sediment load in the river during monsoon, metals were substantially higher in the particulate fractions than in the aqueous phase. Partition coefficient for Cu (3.1-6.1), Pb (3.4-6.5) and Zn (3.5-6.9), demonstrated strong adsorption of the metals on suspended matter. Q-mode hierarchical cluster analysis (HCA) illustrated groupings mainly governed by quality parameters rather than by the river course. R-mode results imply selectivity of the affinities of metals for different ligands. Health risk index (HRI) values were less than 1 for dissolved metal for Cu, Pb and Zn while it was greater than 1 for total metal for Pb and Cu indicating potential human health risk. The study demonstrated that binding of metals with naturally occurring dissolved organic matter or suspended particulate matter affects metal bioavailability in river during wet periods when sediment load is particularly high. A combination of empirical, computational and statistical relationships between ionic species and fractions of metals provided greater certitude in identifying the resemblance among the different locations of the river.

A cluster analytic approach to identifying predictors and moderators of psychosocial treatment for bipolar depression: Results from STEP-BD

BACKGROUND

We sought to address how predictors and moderators of psychotherapy for bipolar depression - identified individually in prior analyses - can inform the development of a metric for prospectively classifying treatment outcome in intensive psychotherapy (IP) versus collaborative care (CC) adjunctive to pharmacotherapy in the Systematic Treatment Enhancement Program (STEP-BD) study.

METHODS

We conducted post-hoc analyses on 135 STEP-BD participants using cluster analysis to identify subsets of participants with similar clinical profiles and investigated this combined metric as a moderator and predictor of response to IP. We used agglomerative hierarchical cluster analyses and k-means clustering to determine the content of the clinical profiles. Logistic regression and Cox proportional hazard models were used to evaluate whether the resulting clusters predicted or moderated likelihood of recovery or time until recovery.

RESULTS

The cluster analysis yielded a two-cluster solution: 1) "less-recurrent/severe" and 2) "chronic/recurrent." Rates of recovery in IP were similar for less-recurrent/severe and chronic/recurrent participants. Less-recurrent/severe patients were more likely than chronic/recurrent patients to achieve recovery in CC (p=.040, OR=4.56). IP yielded a faster recovery for chronic/recurrent participants, whereas CC led to recovery sooner in the less-recurrent/severe cluster (p=.034, OR=2.62).

LIMITATIONS

Cluster analyses require list-wise deletion of cases with missing data so we were unable to conduct analyses on all STEP-BD participants.

CONCLUSIONS

A well-powered, parametric approach can distinguish patients based on illness history and provide clinicians with symptom profiles of patients that confer differential prognosis in CC vs. IP.

Co-occurrence perspective of arsenic and fluoride in the groundwater of Diphu, Assam, Northeastern India

Considerable lacunae exists in As and F(-) co-contamination investigation in the Brahmaputra and Gangetic floodplains. Therefore we selected Diphu a township in the Karbi Plateau rising from the Brahmaputra floodplains for evaluation of As and F co-occurrence, correlation with coexisting ions of the aquifer system and elucidation of potential processes for releasing As and F(-) in the groundwater. Our initial appraisal used generic plots for identification of hydro geochemical processes and major water types. Subsequently, As and F(-) co-occurrence with pH, depth, HCO3(-), SO4(2-), Ca(2+) and Fe were probed for possible correlation followed by hierarchical cluster analyses to identify key processes for co-occurrence. Finally, saturation indices of groundwater minerals were calculated using MINTEQA2 to elucidate prospective As and F(-) release into groundwater. Results indicate F(-) and As presence in Ca-HCO3 rich water along with positive correlation between Ca(2+) and F(-) possibly due to limestone reserves in adjoining areas. Multivariate analyses suggest the presence of high concentrations of PO4(3-), and H4SiO4 either individually or in combination can enhance the mobility of both As and F(-) and possibly abet conditions conducive for co-contamination of aquifers. Initial release of As and F(-) from the parent rock seems driven by the anthropogenic activities while mobilization depends on chemical interactions and individual affinities of the elements. The results of speciation highlight further mobilization of As and F(-) into the groundwater which in turn require regular attention for sustainable management of scarce water resource present in the area.

Multiproblem Families Referred to Youth Mental Health: What's in a Name?

The purpose of this study was threefold, namely (1) to differentiate between multiproblem families and control families on characteristics and processes within the family based on a theoretical framework, (2) to identify multiproblem families by establishing cut-off scores on various questionnaires, and (3) to categorize multiproblem families into subtypes by cluster analyses. Various questionnaires were administered to multiproblem families (n = 85) and control families (n = 150). Results showed that what we propose to refer to as multiproblem families present a broad range of problems on seven domains: (1) child factors, (2) parental factors, (3) childrearing problems (inadequate or inconsistent parenting), (4) family functioning problems, (5) contextual problems, (6) social network problems, and (7) mental health care problems. Further, reliable cut-off scores were established for various questionnaires. Finally, three types of families were found: (1) community-problem families, (2) multiproblem families, and (3) child-focused mild-problem families. This paper looks to advance an evidence-based definition and assessment of "multiproblem families" suggesting the possible value of defining and assessing multiproblem families in relation to these seven dimensions. Moreover, the classification of multiproblem families stresses the importance of providing tailored treatments.

Patterns of individual change in a parenting program for child maltreatment and their relation to family and professional environments

In the area of child maltreatment prevention, little is known about the typology of changes that individuals undergo in response to parent-training interventions. In this study, we examined the patterns of change observed in parents immediately after their completion of the Apoyo Personal y Familiar (APF, Personal and Family Support) parenting program. We identified five clusters and classified 496 parents according to two criteria: (a) the amount of pre-post changes (total or partial) as reflected in their self-reports on implicit theories, parental agency and childrearing practices, and (b) the positive, negative or mixed character of these changes. The study also included a follow-up of a subset of 95 participants intended to examine the extent to which the patterns of change identified in the first part of the study might predict the quality of the childrearing environment at home and the successful integration of the APF program into social services structures one year on. In this follow-up study, external evaluators observed families' home environments and collected the parenting program facilitators' self-reports on changes to their work environment. The evaluators found higher-quality childrearing environments and more positive appraisals of the changes to the teams' work with families in those cases where participants had experienced partial or total positive changes as a result of the APF. This approach offers insights into processes of individual change that have practical implications for the successful implementation of parenting programs in child maltreatment prevention services.