PREDICTIVE VARIABLES FOR WEIGHT CHANGE 2 YEARS FOLLOWING PARTICIPATION IN A WEIGHT LOSS INTERVENTION PROGRAM

A historical prospective study was designed to assess the man weight status of subjects who participated in a behavioral weight reduction program in 1983 and to determine whether there was an association between the dependent variable weight change and any of 31 independent variables after a 2 year follow-up period. Data was obtained by abstracting the subjects records and from a follow-up questionnaire administered 2 years following program participation. Five hundred nine subjects (386 females and 123 males) of 1460 subjects who participated in the program, completed and returned the questionnaire. Results showed that mean weight was significantly different (p < 0.001) between the measurement at baseline and after a 2 year follow-up period. The mean weight loss of the group was 5.8 pounds, 10.7 pounds for males and 4.2 pounds for females after a 2 year follow-up period. A total of 63.9% of the group, 69.9% of males and 61.9% of females were still below their initial weight after the 2 year follow-up period. Sixteen of the 31 variables assessed utilizing bivariate analyses were found to be significantly (p (LESSTHEQ) 0.05) associated with weight change after a 2 year follow-up period. These variables were then entered into a multivariate linear regression model. A total of 37.9% of the variance of the dependent variable, weight change, was accounted for by all 16 variables. Eight of these variables were found to be significantly (p (LESSTHEQ) 0.05) predictive of weight change in the stepwise multivariate process accounting for 37.1% of the variance. These variables included: Two baseline variables (percent over ideal body weight at enrollment and occupation) and six follow-up variables (feeling in control of eating habits, percent of body weight lost during treatment, frequency of weight measurement, physical activity, eating in response to emotions, and number of pounds of weight gain needed to resume a diet). It was concluded that a greater amount of emphasis should be placed on the six follow-up variables by clinicians involved in the treatment of obesity, and by the subjects themselves to enhance their chances of success at long-term weight loss. ^

Examining Gender Differences in Received, Provided and Invisible Social Control: An Application of the Dual-Effects-Model

The dual-effects model of social control not only assumes that social control leads to better health practices but also arouses psychological distress. However, findings are inconsistent. The present study advances the current literature by examining social control from a dyadic perspective in the context of smoking. In addition, the study examines whether control, continuous smoking abstinence, and affect are differentially related for men and women. Before and three weeks after a self-set quit attempt, we examined 106 smokers (77 men, mean age: 40.67, average number of cigarettes smoked per day: 16.59 [SD=8.52, range=1-40] at baseline and 5.27 [SD=6.97, range=0-40] at follow-up) and their nonsmoking heterosexual partners, assessing received and provided control, continuous abstinence, and affect. With regard to smoker's affective reactions, partner's provided control was related to an increase in positive and to a decrease in negative affect, but only for female smokers. Moreover, the greater the discrepancy between smoker received and partner's provided control was the more positive affect increased and the more negative affect decreased, but again only for female smokers. These findings demonstrate that female smokers' well-being was raised over time if they were not aware of the control attempts of their nonsmoking partners, indicating positive effects of invisible social control. This study's results emphasize the importance of applying a dyadic perspective and taking gender differences in the dual-effects model of social control into account.

General distress, hopelessness—suicidal ideation and worrying in adolescence: Concurrent and predictive validity of a symptom-level bifactor model for clinical diagnoses

BACKGROUND: Clinical disorders often share common symptoms and aetiological factors. Bifactor models acknowledge the role of an underlying general distress component and more specific sub-domains of psychopathology which specify the unique components of disorders over and above a general factor. METHODS: A bifactor model jointly calibrated data on subjective distress from The Mood and Feelings Questionnaire and the Revised Children's Manifest Anxiety Scale. The bifactor model encompassed a general distress factor, and specific factors for (a) hopelessness-suicidal ideation, (b) generalised worrying and (c) restlessness-fatigue at age 14 which were related to lifetime clinical diagnoses established by interviews at ages 14 (concurrent validity) and current diagnoses at 17 years (predictive validity) in a British population sample of 1159 adolescents. RESULTS: Diagnostic interviews confirmed the validity of a symptom-level bifactor model. The underlying general distress factor was a powerful but non-specific predictor of affective, anxiety and behaviour disorders. The specific factors for hopelessness-suicidal ideation and generalised worrying contributed to predictive specificity. Hopelessness-suicidal ideation predicted concurrent and future affective disorder; generalised worrying predicted concurrent and future anxiety, specifically concurrent generalised anxiety disorders. Generalised worrying was negatively associated with behaviour disorders. LIMITATIONS: The analyses of gender differences and the prediction of specific disorders was limited due to a low frequency of disorders other than depression. CONCLUSIONS: The bifactor model was able to differentiate concurrent and predict future clinical diagnoses. This can inform the development of targeted as well as non-specific interventions for prevention and treatment of different disorders.

Integrating attentional control theory and the strength model of self-control

In the present article, we argue that it may be fruitful to incorporate the ideas of the strength model of self-control into the core assumptions of the well-established attentional control theory (ACT). In ACT, it is assumed that anxiety automatically leads to attention disruption and increased distractibility, which may impair subsequent cognitive or perceptual-motor performance, but only if individuals do not have the ability to counteract this attention disruption. However, ACT does not clarify which process determines whether one can volitionally regulate attention despite experiencing high levels of anxiety. In terms of the strength model of self-control, attention regulation can be viewed as a self-control act depending on the momentary availability of self-control strength. We review literature that has revealed that self-control strength moderates the anxiety-performance relationship, discuss how to integrate these two theoretical models, and offer practical recommendations of how to counteract negative anxiety effects.

Neuroenhancement and the strength model of self-control

Neuroenhancement (NE), the use of substances as a means to enhance performance, has garnered considerable scientific attention of late. While ethical and epidemiological publications on the topic accumulate, there is a lack of theory-driven psychological research that aims at understanding psychological drivers of NE. In this perspective article we argue that self-control strength offers a promising theory-based approach to further understand and investigate NE behavior. Using the strength model of self-control, we derive two theory-driven perspectives on NE-self-control research. First, we propose that individual differences in state/trait self-control strength differentially affect NE behavior based on one’s individual experience of NE use. Building upon this, we outline promising research questions that (will) further elucidate our understanding of NE based on the strength model’s propositions. Second, we discuss evidence indicating that popular NE substances (like Methylphenidate) may counteract imminent losses of self-control strength. We outline how further research on NE’s effects on the ego-depletion effect may further broaden our understanding of the strength model of self-control.

Are functional and genetic components of platelets linked to coronary artery disease: A case-control study

Coronary artery disease (CAD) is a multifactorial disease process involving behavioral, inflammatory, clinical, thrombotic, and genetic components. Previous epidemiologic studies focused on identifying behavioral and demographic risk factors of CAD, but none focused on platelets. Current platelet literature lacks the known effects of platelet function and platelet receptor polymorphisms on CAD. This case-control analysis addressed these issues by analyzing data collected for a previous study. Cases were individuals who had undergone CABG and thus had been diagnosed with CAD, while the controls were volunteers presumed to be CAD free. The platelet function variables analyzed included fibrinogen Von Willebrand Factor activity (VWF), shear-induced platelet aggregation (SIPA), sCD40L, and mean platelet volume; and the platelet polymorphisms studied included PIA, α2 807, Ko, Kozak, and VNTR. Univariate analysis found fibrinogen, VWF, SIPA, and PIA to be independent risk factors of CAD. Logistic regression was used to build a predictive model for CAD using the platelet function and platelet polymorphism data adjusted for age, sex, race, and current smoking status. A model containing only platelet polymorphisms and their respective receptor densities, found polymorphisms within GPIbα to be associated with CAD, yielding an 86% (95% C.I. 0.97–3.55) increased risk with the presence of at least 1 polymorphism in Ko, Kozak, or VNTR. Another model included both platelet function and platelet polymorphism data. Fibrinogen, the receptor density of GPIbα, and the polymorphism in GPIa-IIa (α2 807) were all associated with CAD with odds ratios of 1.10, 1.04, and 2.30 for fibrinogen (10mg/dl increase), GPIbα receptors (1 MFI increase), and GPIa-IIa, respectively. In addition, risk estimates and 99% confidence intervals adjusted for race were calculated to determine if the presence of a platelet receptor polymorphism was associated with CAD. The results were as follows: PIA (1.64, 0.74–3.65); α2 807 (1.35, 0.77–2.37); Ko (1.71, 0.70–4.16); Kozak (1.17, 0.54–2.52); and VNTR (1.24, 0.52–2.91). Although not statistically significant, all platelet polymorphisms were associated with an increased risk for CAD. These exploratory findings indicate that platelets do appear to have a role in atherosclerosis and that anti-platelet drugs targeting GPI-IIa and GPIbα may be better treatment candidates for individuals with CAD. ^

Chimpanzee: A predictive model for the human cytochrome P450 3A subfamily

The human cytochrome P450 3A (CYP3A) subfamily is responsible for most of the metabolism of therapeutic drugs; however, an adequate in vivo model has yet to be discovered. This study begins with an investigation of a controversial topic surrounding the human CYP3As--estrogen regulation. A novel approach to this topic was used by defining expression in the estrogen-responsive endometrium. This study shows that estrogen down-regulates CYP3A4 expression in the endometrium. On the other hand, analogous studies showed an increase in CYP3A expression as age increases in liver tissue. Following the discussion of estrogen regulation, is an investigation of the cross-species relationships among all of the CYP3As was completed. The study compares isoforms from piscines, avians, rodents, canines, ovines, bovines, and primates. Using the traditional phylogenetic analyses and employing a novel approach using exon and intron lengths, the results show that only another primate could be the best animal model for analysis of the regulation of the expression of the human CYP3As. This analysis also demonstrated that the chimpanzee seems to be the best available human model. Moreover, the study showed the presence and similarities of one additional isoform in the chimpanzee genome that is absent in humans. Based on these results, initial characterization of the chimpanzee CYP3A subfamily was begun. While the human genome contains four isoforms--CYP3A4, CYP3A5, CYP3A7, and CYP3A43--the chimpanzee genome has five, the four previously mentioned and CYP3A67. Both species express CYP3A4, CYP3A5, and CYP3A43, but humans express CYP3A7 while chimpanzees express CYP3A67. In humans, CYP3A4 is expressed at higher levels than the other isoforms, but some chimpanzee individuals express CYP3A67 at higher levels than CYP3A4. Such a difference is expected to alter significantly the total CYP3A metabolism. On the other hand, any study considering individual isoforms would still constitute a valid method of study for the human CYP3A4, CYP3A5, and CYP3A43 isoforms. ^

Frequencies and risk factors for bisphosphonate-related osteonecrosis of the jaw in cancer patients: A matched case-control study

Bisphosphonates represent a unique class of drugs that effectively treat and prevent a variety of bone-related disorders including metastatic bone disease and osteoporosis. High tolerance and high efficacy rates quickly ranked bisphosphonates as the standard of care for bone-related diseases. However, in the early 2000s, case reports began to surface that linked bisphosphonates with osteonecrosis of the jaw (ONJ). Since that time, studies conducted have corroborated the linkage. However, as with most disease states, many factors can contribute to the onset of disease. The aim of this study was to determine which comorbid factors presented an increased risk for developing ONJ in cancer patients.^ Using a case-control study design, investigators used a combination of ICD-9 codes and chart review to identify confirmed cases of ONJ at The University of Texas M. D. Anderson Cancer Center (MDACC). Each case was then matched to five controls based on age, gender, race/ethnicity, and primary cancer diagnosis. Data querying and chart review provided information on variables of interest. These variables included bisphosphonate exposure, glucocorticoids exposure, smoking history, obesity, and diabetes. Statistical analysis was conducted using PASW (Predictive Analytics Software) Statistics, Version 18 (SPSS Inc., Chicago, Illinois).^ One hundred twelve (112) cases were identified as confirmed cases of ONJ. Variables were run using univariate logistic regression to determine significance (p < .05); significant variables were included in the final conditional logistic regression model. Concurrent use of bisphosphonates and glucocorticoids (OR, 18.60; CI, 8.85 to 39.12; p < .001), current smokers (OR, 2.52; CI, 1.21 to 5.25; p = .014), and presence of diabetes (OR, 1.84; CI, 1.06 to 3.20; p = .030) were found to increase the risk for developing ONJ. Obesity was not associated significantly with ONJ development.^ In this study, cancer patients that received bisphosphonates as part of their therapeutic regimen were found to have an 18-fold increase in their risk of developing ONJ. Other factors included smoking and diabetes. More studies examining the concurrent use of glucocorticoids and bisphosphonates may be able to strengthen any correlations.^

Robust effect sizes and their confidence intervals for group difference between trajectories in hierarchical linear growth model

Hierarchical linear growth model (HLGM), as a flexible and powerful analytic method, has played an increased important role in psychology, public health and medical sciences in recent decades. Mostly, researchers who conduct HLGM are interested in the treatment effect on individual trajectories, which can be indicated by the cross-level interaction effects. However, the statistical hypothesis test for the effect of cross-level interaction in HLGM only show us whether there is a significant group difference in the average rate of change, rate of acceleration or higher polynomial effect; it fails to convey information about the magnitude of the difference between the group trajectories at specific time point. Thus, reporting and interpreting effect sizes have been increased emphases in HLGM in recent years, due to the limitations and increased criticisms for statistical hypothesis testing. However, most researchers fail to report these model-implied effect sizes for group trajectories comparison and their corresponding confidence intervals in HLGM analysis, since lack of appropriate and standard functions to estimate effect sizes associated with the model-implied difference between grouping trajectories in HLGM, and also lack of computing packages in the popular statistical software to automatically calculate them. ^ The present project is the first to establish the appropriate computing functions to assess the standard difference between grouping trajectories in HLGM. We proposed the two functions to estimate effect sizes on model-based grouping trajectories difference at specific time, we also suggested the robust effect sizes to reduce the bias of estimated effect sizes. Then, we applied the proposed functions to estimate the population effect sizes (d ) and robust effect sizes (du) on the cross-level interaction in HLGM by using the three simulated datasets, and also we compared the three methods of constructing confidence intervals around d and du recommended the best one for application. At the end, we constructed 95% confidence intervals with the suitable method for the effect sizes what we obtained with the three simulated datasets. ^ The effect sizes between grouping trajectories for the three simulated longitudinal datasets indicated that even though the statistical hypothesis test shows no significant difference between grouping trajectories, effect sizes between these grouping trajectories can still be large at some time points. Therefore, effect sizes between grouping trajectories in HLGM analysis provide us additional and meaningful information to assess group effect on individual trajectories. In addition, we also compared the three methods to construct 95% confident intervals around corresponding effect sizes in this project, which handled with the uncertainty of effect sizes to population parameter. We suggested the noncentral t-distribution based method when the assumptions held, and the bootstrap bias-corrected and accelerated method when the assumptions are not met.^

Calcareous nannofossil datums and control points for the TCMS age model of ODP Site 175-1085

An astronomically calibrated age model for the Pliocene section of Ocean Drilling Program Leg 175 Cape Basin Site 1085 based on magnetic susceptibility data was developed using shipboard biostratigraphic datums. The composite core magnetic susceptibility record was compiled using shipboard correlations between Holes 1085A and 1085B and then tuned to the record of orbital variations in eccentricity to generate an orbitally tuned age model. Magnetic susceptibility apparently records climate variations in the Cape Basin. Strong power spectra values at the 100- and 400-k.y. frequency suggest an orbital control on the beat of Pliocene climate change in the Cape Basin.

Three time-slice simulations of the Eemian (eem), the mid-Holocene (hol), and a pre-industrial (pri) control run with the coupled atmosphere-ocean-model ECHAM5/MPI-OM

Orbital forcing does not only exert direct insolation effects, but also alters climate indirectly through feedback mechanisms that modify atmosphere and ocean dynamics and meridional heat and moisture transfers. We investigate the regional effects of these changes by detailed analysis of atmosphere and ocean circulation and heat transports in a coupled atmosphere-ocean-sea ice-biosphere general circulation model (ECHAM5/JSBACH/MPI-OM). We perform long term quasi equilibrium simulations under pre-industrial, mid-Holocene (6000 years before present - yBP), and Eemian (125 000 yBP) orbital boundary conditions. Compared to pre-industrial climate, Eemian and Holocene temperatures show generally warmer conditions at higher and cooler conditions at lower latitudes. Changes in sea-ice cover, ocean heat transports, and atmospheric circulation patterns lead to pronounced regional heterogeneity. Over Europe, the warming is most pronounced over the north-eastern part in accordance with recent reconstructions for the Holocene. We attribute this warming to enhanced ocean circulation in the Nordic Seas and enhanced ocean-atmosphere heat flux over the Barents Shelf in conduction with retreat of sea ice and intensified winter storm tracks over northern Europe.