Nadia Solaro

Complementary medicine for the management of chronic stress: Superiority of active versus passive techniques

Background Recent epidemiological data indicate that chronic stress is an important component of cardiovascular risk, implicitly suggesting that stress management might offer a useful complement to orthodox medical treatment and prevention of hypertension. In this context, information on mechanisms, such as subclinical increases in arterial pressure and sympathetic drive, is well documented. Conversely, evidence on methodologies and comparative efficacy needs to be improved. Accordingly, this study was planned to test the autonomic and subjective effects of two popular modalities of stress management. Methods We studied 70 patients complaining of stress-related symptoms, avoiding any potential autonomic confounder, such as established hypertension or drug treatment. Patients were divided in three groups: group I (n = 30) followed a breathing-guided relaxation training (active); group II (n = 15) an oriental massage, shiatsu (passive); and group III (n = 25) followed a sham intervention. Subjective effects of stress were assessed by validated questionnaires and autonomic nervous system regulation by spectral analysis of RR interval variability. Factor analysis was used to extract information simultaneously embedded in subjective and functional data. Results Although the problem of a greater quantity of treatment procedure in the active group than in the passive group existed, results showed that active relaxation, further to slightly reducing arterial pressure, might be more effective in relieving symptoms of stress and inducing an improved profile of autonomic cardiovascular regulation, as compared with passive massage or sham intervention. Conclusion This active technique seems capable of beneficially addressing simultaneously the individual psychological and physiopathological dimensions of stress in clinical settings, with potentially beneficial effects on cardiovascular risk profile.

Health Promotion in the Workplace: Assessing Stress and Lifestyle With an Intranet Tool

Background Chronic noncommunicable conditions, particularly cardiovascular and metabolic diseases, are the major causes of death and morbidity in both industrialized and low- to middle-income countries. Recent epidemiological investigations suggest that management of lifestyle factors, such as stress and lack of physical activity, could have an important value in cardiometabolic conditions, while information technology tools could play a significant facilitatory role. Objectives The objective of our study was to verify the feasibility of using a private website, directed to the workers of a major Italian company, to describe their health profile and lifestyle and work habits using an ad hoc self-administered questionnaire. Methods We administered anonymous multiple choice Web-based questionnaires to 945 participants (683 completed the task) as part of an ongoing health promotion program in a multinational company. Qualitative and quantitative data were synthesized with nonlinear principal component analysis to construct indicators (ie, variables) for stress, control, and lifestyle domains. Considering in addition absenteeism, the Calinski-Harabasz statistic and cluster analysis jointly differentiated seven clusters, which displayed different distributions of standardized classification variables. The final step consisted in assessing the relationship of the resulting seven subject typologies with personal data, illnesses, and metabolic syndrome status, carried out for the most part with descriptive methods. Results Statistical analyses singled out two not-overlapping domains of stress and control, as well as three not-overlapping domains of physical activity, smoking, and alcohol habits. The centroids of the seven clusters generated by the procedure were significantly (P < .001) different considering all possible 21 comparisons between couples of groups. Percentage distributions of variables describing personal information (gender, age group, work category, illness status, or metabolic syndrome) within participant typologies show some noteworthy findings: females, workers aged 35–44 years, junior white collar workers, and respondents reporting illness were more prevalent in the stress group than in the overall studied population; preclinical metabolic syndrome status was more prevalent in the group with higher alcohol consumption. Absentees reported more illness. Conclusions The present Intranet-based study shows the potential of applying diverse statistical techniques to deal jointly with qualitative and quantitative self-reported data. The resulting formal description of subject typologies and their relationship with personal characteristics might provide a convenient tool for supporting health promotion in the work environment.

Thyroid dysfunction in women with systemic sclerosis

Abstract:  Hypothyroidism has been frequently reported in systemic sclerosis (SSc), but whether SSc itself increases the risk of thyroid dysfunction is still controversial. The aim of the present study was to determine whether routine thyroid function screening in SSc should be warranted. Serum levels of free triiodothyronine, free thyroxine, and thyroid‐stimulating hormone, and the presence of thyroid‐specific autoantibodies (antithyroid peroxidase and antithyreoglobulin) were measured in 79 women with SSc and 81 age‐matched women with osteoarthritis (OA) serving as controls. Hyperthyroidism was found in 2 of 79 (2.5%) SSc and in 4 of 81 (5%) OA cases. Hypothyroidism was found in 16 of 79 (20%) patients with SSc (subclinical in 14/16 cases) and in 9 of 81 (11%) patients with OA (subclinical in all cases; P= 0.131). Antithyreoglobulin antibodies were present in 14% versus 13% patients (SSc versus OA, P= NS), whereas antithyroid peroxidase antibodies were present in 23% versus 11% patients (SSc versus OA, P= 0.057). The risk of hypothyroidism was significantly higher in antithyroid peroxidase‐positive patients (P < 0.0001), irrespective of the primary diagnosis, and greater in women with OA (OR = 24.6, 95% CI 4.3–141.9, P < 0.0001) than SSc (OR = 4.2, 95% CI 1.2–14.3, P= 0.035). SSc is not independently associated with an increased risk of thyroid dysfunction, but antithyroid peroxidase antibodies may identify a subset of patients at risk of developing thyroid dysfunction.

May autonomic indices from cardiovascular variability help identify hypertension

Introduction: Altered profile of RR variability and reduced baroreflex gain, as autonomic proxies, are observed in hypertensive individuals. Aim: To assess whether using logistic models and cross-validation techniques autonomic proxies can be used to identify clinical hypertensive and normotensive groups. Methods: An observational study on 405 individuals (155 mild hypertensive and 250 controls). We used four steps for statistical analysis: preliminary descriptive statistics; logistic regression modelling; detection of best parsimonious set of variables; and concordance analysis between clinical and autonomic hypertension profile. Results: Accuracy index (rate of correct identifications of normotensive and hypertensive states), computed on each of the four gradually more complex logistic models (from A to D), reached its highest value (82.7%), in the most complete model D, including autonomic nervous system indices (RR variability and baroreflex gain), age and sex. Measures of predictive performance increased from the simplest model to the most complex one [model D, positive predictive value (PPV) = 0.767, negative predictive value (NPV) = 0.866], with higher specificity than sensitivity. A parsimonious set of autonomic proxies (Mean RR, &Dgr;RRLFnu – i.e. change from rest to standing up – baroreflex gain combined with age and sex) led to an accuracy index of 80.5%, thus proving to have discriminant and predictive powers in detecting hypertension very similar to the whole set of the explicative variables comprised in the complete model D. Conclusion: The clinical value of the observation that the information collectively carried by a small subset of indirect autonomic proxies may identify either hypertensive or normotensive groups needs to be further investigated.

Sensitivity Analysis and Robust Approach in Multidimensional Scaling: An Evaluation of Customer Satisfaction

Abstract Multidimensional scaling (MDS) methods are devoted par excellence to representing a set of objects in a low-dimensional Euclidean space by preserving, as far as possible, the proximities between the objects themselves. Like other data analysis techniques, MDS methods treat a set of data as the entire population of interest. It is therefore important to determine the stability and robustness of the results against possible perturbations or errors present in the data. This issue is particularly important in customer satisfaction analysis, where satisfaction indicators and customer ranking can be heavily influenced by such anomalies. These kinds of problems are specifically addressed in this work. Starting from commonly applied methods, a combination of sensitivity and robust analysis will be proposed. A case study will then be considered.

A Composite Autonomic Index as Unitary Metric for Heart Rate Variability: A Proof of Concept.

This study addresses whether a unitary cardiac autonomic nervous system index (ANSI), obtained combining multiple metrics from heart rate variability (HRV) into a radar plot could provide an easy appreciation of autonomic performance in a clinical setting.

A sequential distance-based approach for imputing missing data: Forward Imputation

Missing data recurrently affect datasets in almost every field of quantitative research. The subject is vast and complex and has originated a literature rich in very different approaches to the problem. Within an exploratory framework, distance-based methods such as nearest-neighbour imputation (NNI), or procedures involving multivariate data analysis (MVDA) techniques seem to treat the problem properly. In NNI, the metric and the number of donors can be chosen at will. MVDA-based procedures expressly account for variable associations. The new approach proposed here, called Forward Imputation, ideally meets these features. It is designed as a sequential procedure that imputes missing data in a step-by-step process involving subsets of units according to their “completeness rate”. Two methods within this context are developed for the imputation of quantitative data. One applies NNI with the Mahalanobis distance, the other combines NNI and principal component analysis. Statistical properties of the two methods are discussed, and their performance is assessed, also in comparison with alternative imputation methods. To this purpose, a simulation study in the presence of different data patterns along with an application to real data are carried out, and practical hints for users are also provided.

Reducing the risk of metabolic syndrome at the worksite: preliminary experience with an ecological approach

AimGiven the time spent at work, the workplace represents an ideal setting to implement preventive programs for non-communicable diseases, the major cause of mortality and morbidity in Western and developing countries. We sought to verify if an ecological approach based on corporate culture, employees’ education and concrete modifications of workplace environment, offering easy opportunity to assume healthy lifestyle, could be associated with reduced cardiometabolic risk.MethodsThe study involved 1089 workers in two multinational companies following different workplace health promotion policies. Company A offered to all employees the opportunity to access a web platform dedicated to general information on health and diseases. Company B implemented an ecological model encompassing company culture, employees’ education and concrete modifications of workplace environment, giving to all employees the opportunity to adopt healthy solutions throughout daily living at workplace. Participants volunteered self-reported clinical information using an IT tool. Numbers of Metabolic Syndrome components (MetS) were taken as proxy of cardiometabolic risk.ResultsMetS probability obtained via statistical modeling was lower in company B as compared to company A, and absenteeism was also lower in company B. Our study shows that a work environment favoring assumption of healthy lifestyle, as in company B, is associated with a lower percentage of employees with MetS components and lower absenteeism. Moreover, statistical modeling shows that individual probabilities of being without MetS elements, controlling for age and gender, is remarkably higher in company B.ConclusionsOur data suggest that ecological approaches might be useful in worksite prevention policies.

The Forward Search for Classical Multidimensional Scaling When the Starting Data Matrix Is Known

This work provides an extension of the Forward Search to classical multidimensional scaling according to a double perspective: first, as a diagnostic tool in order to detect outlying units and monitor their influences on the main analysis results. Second, as a comparative tool when two or more solutions need to be compared. A case study from a clinical setting is then considered.

On Parameters Estimation Procedures in Multilevel Models

We examine maximum likelihood estimation procedures in multilevel models re-latedto two-level hierarchically structured data. Usually, for fixed effects and variance com-ponentsestimation, multivariate normal distribution is assumed. Here we consider for randomeffects multivariate exponential power distribution (MEP), which represents one of the possiblegeneralizations of multivariate normal distribution. We examine robustness of maximum like-lihoodestimators under normal assumption when, indeed, random effects are MEP distributed. The study is conducted through MC simulation procedures