This observational study shows the feasibility of testing simpler metrics of cardiac autonomic regulation based on a multivariate unitary index in a preventive setting. This simple approach might foster a wider application of HRV in the clinical arena, and permit an easier appreciation of autonomic performance.

In spite of the large body of evidence suggesting Heart Rate Variability (HRV) alone or combined with blood pressure variability (providing an estimate of baroreflex gain) as a useful technique to assess the autonomic regulation of the cardiovascular system, there is still an ongoing debate about methodology, interpretation, and clinical applications. In the present investigation, we hypothesize that non-parametric and multivariate exploratory statistical manipulation of HRV data could provide a novel informational tool useful to differentiate normal controls from clinical groups, such as athletes, or subjects affected by obesity, hypertension, or stress. With a data-driven protocol in 1,352 ambulant subjects, we compute HRV and baroreflex indices from short-term data series as proxies of autonomic (ANS) regulation. We apply a three-step statistical procedure, by first removing age and gender effects. Subsequently, by factor analysis, we extract four ANS latent domains that detain the large majority of information (86.94%), subdivided in oscillatory (40.84%), amplitude (18.04%), pressure (16.48%), and pulse domains (11.58%). Finally, we test the overall capacity to differentiate clinical groups vs. control. To give more practical value and improve readability, statistical results concerning individual discriminant ANS proxies and ANS differentiation profiles are displayed through peculiar graphical tools, i.e., significance diagram and ANS differentiation map, respectively. This approach, which simultaneously uses all available information about the system, shows what domains make up the difference in ANS discrimination. e.g., athletes differ from controls in all domains, but with a graded strength: maximal in the (normalized) oscillatory and in the pulse domains, slightly less in the pressure domain and minimal in the amplitude domain. The application of multiple (non-parametric and exploratory) statistical and graphical tools to ANS proxies defines differentiation profiles that could provide a better understanding of autonomic differences between clinical groups and controls. ANS differentiation map permits to rapidly and simply synthesize the possible difference between clinical groups and controls, evidencing the ANS latent domains that have at least a medium strength of discrimination, while the significance diagram permits to identify the single ANS proxies inside each ANS latent domain that resulted in significant comparisons according to statistical tests.

Interests about the fine underpinnings of cardiovascular beat-by-beat variability have historical roots. Over the last decades, various aspects of the relationships between arterial pressure and heart period were taken as a proxy of the baroreflex in physiology and medicine, stimulating the interest of investigators in several interconnected scientific fields, in particular, bioengineering, neurophysiology, and clinical medicine. Studies of the overall system facilitated the emergence of a simplified negative (vagal) feedback model of the baroreflex and overshadowed the simultaneous interaction with excitatory, sympathetic positive-feedback mechanisms that would, however, better suit the model of a “paired antagonistic (parasympathetic/sympathetic) innervation of the internal organs.” From the bioengineering side, the simplicity of obtaining the series of subsequent RR intervals stimulated the analysis of beat-by-beat variations, providing a multitude of heart rate variability (HRV) indices considered as proxies of the underlying sympatho-vagal balance, and participating to the management of several important clinical conditions, such as hypertension. In this context, advanced statistical methods, used in an integrated manner and controlling for age and gender biases, might help shed new light on the relationship between cardiac baroreflex, assessed by the frequency domain index α, and the HRV indices with the varying of systolic arterial pressure (SAP) levels. The focus is also on a novel unitary Autonomic Nervous System Index (ANSI) built as a synthesis of HRV considering its three most informative proxies [RR, RR variance, and the rest-stand difference in the normalized power of low-frequency (LF) variability component]. Data from a relatively large set of healthy subjects ( n = 1154) with a broad range of SAP [from normal ( n Nt = 778) to elevated ( n Ht = 232)] show that, e.g., α and ANSI significantly correlate overall ( r = 0.523, p < 0.001), and that this correlation is lower in hypertensives ( r = 0.444, p < 0.001) and higher in pre-hypertensives ( r = 0.618, p < 0.001) than in normotensives ( r = 0.5, p < 0.001). That suggests the existence of curvilinear “umbrella” patterns that might better describe the effects of the SAP states on the relationships between baroreflex and HRV. By a mix of robust, non-parametric and resampling statistical techniques, we give empirical support to this study hypothesis and show that the pre-hypertensive group results at the apex/bottom in most of the studied trends.

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.

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.

BackgroundChronic 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.ObjectivesThe 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.MethodsWe 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.ResultsStatistical 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.ConclusionsThe 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.

In the context of functional determinants of cardiovascular risk, a simple excess in body weight, as indexed by a rise in body mass index (BMI), plays a significant, well-recognized causal role. Conversely, BMI reductions toward normal result in an improvement of risk. Obesity is associated with impaired cardiac autonomic regulation (CAR), through either vagal or sympathetic mechanisms, which could favor the tendency to foster hypertension. Here we study the changing properties of the relationship between increasing grades of BMI and CAR in a population of 756 healthy subjects (age 35.9 ± 12.41 years, 37.4% males, 21.6% overweight, and 16% obese). Evaluation of CAR is based on autoregressive spectral analysis of short-term RR interval and systolic arterial pressure variability, from which a multitude of indices, treated overall as autonomic nervous system (ANS) proxies, is derived. Inspection of the study hypothesis that elevated BMI conditions associate significantly with alterations of CAR, independently of age and gender, is carried out using a mix of statistical transformations, exploratory factor analysis, non-parametric testing procedures, and graphical tools particularly well suited to address alterations of CAR as a disturbed process. In particular, to remove the effects of the inter-individual variability, deriving from components like age, gender or ethnicity, and to reduce the number of ANS proxies, we set up six age-and-gender-adjusted CAR indicators, corresponding to four ANS latent domains (oscillatory, amplitude, pressure, and pulse), cardiac baroreflex regulation, and autonomic nervous system index (ANSI). An impairment of the CAR indicators is overall evident in the overweight group and more marked in the obesity group. Empirical evidence is strong (9/9 concordant non-parametric test results) for pressure domain, almost strong (8/9) for ANSI, medium-strong for baroreflex (6/9) and pulse (7/9), weak for oscillatory (2/9) and amplitude (1/9) domains. In addition, the distribution of the CAR indicators corresponding to pressure, pulse, baroreflex, and ANSI is skewed toward the unfavorable abscissa extremity, particularly in the obese group. The significant association of increased BMI with progressive impairments of CAR regarding specifically the pressure domain and the overall ANS performance might underscore the strong hypertensive tendency observed in obesity.

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