The Interactions of Media Use, Obesity, and Suboptimal Health Status: A Nationwide Time-Trend Study in China

Obesity and suboptimal health status (SHS) have been global public health concerns in recent decades. A growing number of works have explored the relationships between media use and obesity, as well as SHS. This study aimed to examine the time trend of the associations between media use (including traditional media and new media) and obesity, as well as SHS. The data were derived from three national random samples of the Chinese General Social Survey (CGSS), which was separately conducted in 2013, 2015, and 2017. In total, 34,468 respondents were included in this study, consisting of 16,624 males and 17,844 females, and the average age was 49.95 years old (SD = 16.72). It found that broadcast use and television use were positively associated with obesity and showed an increasing trend over time. Cellphone use emerged as a risk factor for obesity in 2017 and showed an increasing trend. By contrast, newspaper use, television use, and internet use were negatively associated with SHS, and television use showed a decreasing trend in the association with SHS, while internet and newspaper use showed an increasing trend. In conclusion, media use was positively associated with obesity while negatively associated with SHS. It showed a decreasing trend in the associations between traditional media use and obesity, while revealing an increasing trend in the associations between new media use and obesity, as well as SHS. The practical implications of the findings are discussed.

All around suboptimal health — a joint position paper of the Suboptimal Health Study Consortium and European Association for Predictive, Preventive and Personalised Medicine

First two decades of the twenty-first century are characterised by epidemics of non-communicable diseases such as many hundreds of millions of patients diagnosed with cardiovascular diseases and the type 2 diabetes mellitus, breast, lung, liver and prostate malignancies, neurological, sleep, mood and eye disorders, amongst others. Consequent socio-economic burden is tremendous. Unprecedented decrease in age of maladaptive individuals has been reported. The absolute majority of expanding non-communicable disorders carry a chronic character, over a couple of years progressing from reversible suboptimal health conditions to irreversible severe pathologies and cascading collateral complications. The time-frame between onset of SHS and clinical manifestation of associated disorders is the operational area for an application of reliable risk assessment tools and predictive diagnostics followed by the cost-effective targeted prevention and treatments tailored to the person.This article demonstrates advanced strategies in bio/medical sciences and healthcare focused on suboptimal health conditions in the frame-work of Predictive, Preventive and Personalised Medicine (3PM/PPPM). Potential benefits in healthcare systems and for society at large include but are not restricted to an improved life-quality of major populations and socio-economical groups, advanced professionalism of healthcare-givers and sustainable healthcare economy. Amongst others, following medical areas are proposed to strongly benefit from PPPM strategies applied to the identification and treatment of suboptimal health conditions: Stress overload associated pathologies Male and female health Planned pregnancies Periodontal health Eye disorders Inflammatory disorders, wound healing and pain management with associated complications Metabolic disorders and suboptimal body weight Cardiovascular pathologies Cancers Stroke, particularly of unknown aetiology and in young individuals Sleep medicine Sports medicine Improved individual outcomes under pandemic conditions such as COVID-19.

Endothelin-1 axes in the framework of predictive, preventive and personalised (3P) medicine

Endothelin-1 (ET-1) is involved in the regulation of a myriad of processes highly relevant for physical and mental well-being; female and male health; in the modulation of senses, pain, stress reactions and drug sensitivity as well as healing processes, amongst others. Shifted ET-1 homeostasis may influence and predict the development and progression of suboptimal health conditions, metabolic impairments with cascading complications, ageing and related pathologies, cardiovascular diseases, neurodegenerative pathologies, aggressive malignancies, modulating, therefore, individual outcomes of both non-communicable and infectious diseases such as COVID-19. This article provides an in-depth analysis of the involvement of ET-1 and related regulatory pathways in physiological and pathophysiological processes and estimates its capacity as a predictor of ageing and related pathologies, a sensor of lifestyle quality and progression of suboptimal health conditions to diseases for their targeted prevention and as a potent target for cost-effective treatments tailored to the person.

Associations of environment and lifestyle factors with suboptimal health status: a population-based cross-sectional study in urban China

Introduction Suboptimal health status (SHS), an intermediate state between chronic disease and health, is characterized by chronic fatigue, non-specific pain, headaches, dizziness, anxiety, depression, and functional system disorders with a high prevalence worldwide. Although some lifestyle factors (e.g. smoking, alcohol consumption, physical exercise) and environmental factors (e.g. air quality, noise, living conditions) have already been studied, few studies can comprehensively illustrate the associations of lifestyle and environment factors with general, physical, mental, and social SHS. Methods A cross-sectional study was conducted among 6750 urban residents aged 14 years or over in five random cities from September 2017 to September 2018 through face-to-face questionnaires. There were 5881 valid questionnaires with a response rate of 87%. A general linear model and structural equation model were developed to quantify the effects of lifestyle behaviors and environment factors on SHS. Results The detection rates of general, physical, mental, and social SHS were 66.7, 67.0, 65.5, and 70.0%, respectively. Good lifestyle behaviors and favorable environment factors positively affected SHS (P < 0.001). Lifestyle behaviors had the largest effect on physical SHS (β = − 0.418), but the least on social SHS (β = − 0.274). Environment factors had the largest effect on mental SHS (β = 0.286), but the least on physical SHS (β = 0.225). Conclusions Lifestyle behaviors and environment factors were important influencing factors of SHS. Physical SHS was more associated with lifestyle. Lifestyle and environment were similarly associated with mental and social SHS.

Construct validity of the Suboptimal Health Status Questionnaire-25 in a Ghanaian population

Background The Suboptimal Health Status Questionnaire-25 (SHS-Q-25) developed to measure Suboptimal Health Status has been used worldwide, but its construct validity has only been tested in the Chinese population. Applying Structural Equation Modelling, we investigate aspects of the construct validity of the SHS-Q-25 to determine the interactions between SHS subscales in a Ghanaian population. Methods The study involved healthy Ghanaian participants (n = 263; aged 20–80 years; 63% female), who responded to the SHSQ-25. In an exploratory factor and parallel analysis, the study extracted a new domain structure and compared to the established five-domain structure of SHSQ-25. A confirmatory factor analysis (CFA) was conducted and the fit of the model further discussed. Invariance analysis was carried out to establish the consistency of the instrument across multi-groups. Results The extracted domains were reliable with Cronbach’s $$\alpha$$ α of 0.846, 0.820 and 0.864 respectively, for fatigue, immune-cardiovascular and cognitive. The CFA revealed that the model fit indices were excellent $$\left( {{\text{RMSEA}} = 0.049~ < ~0.08,\,{\text{CFI}} = 0.903 > 0.9,\,{\text{GFI}} = 0.880 < 0.9,\,{\text{TLI}} = 0.907 > 0.9} \right)$$ RMSEA = 0.049 < 0.08 , CFI = 0.903 > 0.9 , GFI = 0.880 < 0.9 , TLI = 0.907 > 0.9 . The fit indices for the three-domain model were statistically superior to the five-domain model. There were, however, issues of insufficient discriminant validity as some average variance extracts were smaller than the corresponding maximum shared variance. The three-domain model was invariant for all constrained aspects of the structural model across age, which is an important risk factor for most chronic diseases. Conclusion The validity tests suggest that the SHS-Q25 can measure SHS in a Ghanaian population. It can be recommended as a screening tool to early detect chronic diseases especially in developing countries where access to facilities is diminished.

Prevalence of Suboptimal Health Status and Its Influencing Fac-tors among Chinese Software Programmers

Background: There is a lack of specific study of the suboptimal health status (SHS) in software programmers. The aims of the present study were to investigate the prevalence of SHS and analyze the influencing factors among Chinese software programmers. Methods: A cross-sectional survey using a programmer SHS scale was conducted to evaluate the prevalence of SHS, as well chi-square test and multi-factor logistic regression were applied to analyze the relationship between suboptimal health and personal basic information, living and work habits in software programmers. Results: The prevalence of SHS was 18.67% in software programmers. Single factor analysis found that there were differences in suboptimal health prevalence among different work cities (P = 0.031), hours of sleep per day (P = 0.046), overtime days per month (P = 0.010) and exercise frequency per week (P = 0.015). The factors for suboptimal health such as hours of sleep per day (OR = 0.307, 95% CI = 0.096~0.984) and exercise frequency per week (OR = 0.190, 95% CI = 0.054~0.671) significantly affected subjects of SHS via multi-factor logistic regression analysis, indicating that adequate sleep and exercise decreased the chance of SHS up to 30.70% and 19.00%, respectively. Conclusion: Suboptimal health had become a serious public health challenge in Chinese software programmers. Whilst, the health status of the programmers could be effectively elevated by improving lifestyles.

Microbiological Characteristics of Intestinal Biocenosis of Ambulator Patients Having Behavioral Risk Factors for Chronic Non-Communicable Diseases

The earliest correction of behavioral risk factors for chronic non-communicable diseases will reduce the rates of premature mortality of the population. Currently, the relationship between the altered spectrum of intestinal microflora in various indicators of suboptimal health status and body mass index is not sufficiently studied. When they are in a state of suboptimal health status, patients consider themselves healthy and do not go to the doctor for a long time, which makes it difficult to implement early preventive measures in this group of patients. Goal. To determine the qualitative and quantitative composition of the intestinal microflora before and 1 month after taking a metaprebiotic complex containing dietary fiber (inulin) and oligosaccharides (oligofructose) in outpatient patients who consider themselves healthy, have behavioral risk factors for chronic non-communicable diseases or chronic non-communicable diseases in remission, and/or do not consult a doctor within the last 3 months. Materials and methods. Outpatient patients were examined (114 people: 36 men, 78 women aged 18 to 72 years). A survey was conducted, including a detailed active collection of complaints (including using the international SHSQ-25 questionnaire) and anamnesis, as well as a thorough physical examination with an anthropometric study. Using the MALDI-ToF mass spectrometry method, the degree of microbiotic disorders, the structure of the intestinal microflora were determined with the identification of microorganisms isolated from feces before and after taking the course of the metaprebiotic complex with various indicators of suboptimal status and body mass index. Results. New data were obtained on the intestinal biocenosis of patients who consider themselves healthy at different levels of suboptimal status. When using a metaprebiotic complex containing inulin and oligofructose, an improvement in the composition of the intestinal microflora was found due to a decrease in the frequency of release of conditionally pathogenic enterobacteria and other gram-negative microorganisms (median degree of contamination: from 0.45 (0.3-0.98) to 0.3(0.21-0.7) at low suboptimal status and from 0.5(0.7-1.7) to 0.31 (0.2-1.3) at high) and increase the frequency of enterococcal excretion (median degree of contamination: from 5,58 (4,16-7,0) tо 6,3 (4,8-7,8) at low suboptimal status and from от 4,5 (2,8-6,3) tо 5,1 (3,8-6,4) at high). Conclusion. The importance of studying the microbiotic complex of the intestine in increasing the indicators of suboptimal health status and body mass index in patients who consider themselves healthy is proved, which will allow for the earliest detection and rational individual prevention of chronic non-communicable diseases.