Behavioral Lifestyles Research Articles

Impact of Social Capital on Health Behaviors of Middle-Aged and Older Adults in China-An Analysis Based on CHARLS2020 Data.

To actively respond to the challenges posed by population aging, people are paying more and more attention to healthy behavioral lifestyles, and the impact of social capital as an informal system on health behaviors cannot be ignored. This paper explores the impact of social capital on health behaviors of middle-aged and older adults based on 2020 CHARLS data. Using binary logistic regression models, we discussed the association between social capital and five health behaviors. The results suggest that structural social capital significantly increases physical activity and physical examination behaviors among middle-aged and older adults but also decreases the probability of abstinence behaviors. Cognitive social capital increases the probability that middle-aged and older adults will have a reasonable amount of sleep and physical activity. However, it also decreases the probability that smoking cessation behaviors will occur. Further attention needs to be paid to the role of social capital, the creation of a harmonious social environment and the enhancement of social trust, the strengthening of communities and grass-roots social organizations, and the provision of more platforms for the participation of middle-aged and older adults in social activities, to improve the quality of the healthy lives of middle-aged and older adults and, in turn, to promote the establishment of healthy behaviors.

EFFECTS PROFESSIONAL ETHICS FOR FITNESS TRAINERS

This article is only the first step in exploring the professional ethics of fitness trainers in Latvia. Marking the discourse, looking at the theoretical frameworks and concepts, and identifying the situation are its basic elements. The next stage will be the analysis of information about the experience in other countries and primarily the Baltic countries, their comparison, discussion, conclusions, and suggestions for a more successful practice of professional ethics. Professional ethics for fitness trainers constitute a part of their professional competence, which shapes, determines and evaluates their professional activities from the perspective of ethical attitudes. The profession of a fitness trainer reflects health as a fundamental value, which sets the meaning of their professional activity as one that promotes and maintains health. This article examines the basic elements of professional ethics of fitness trainers. Their presentation in a single and logically structured form is an innovation in the literature on fitness trainers. Providing this type of information to future fitness trainers in Latvia is not only a necessary but also an urgent task. The article discusses in detail the concept of health lifestyle, the basic behavioral health lifestyles that are characteristic of the Latvian population. Fitness trainers need this background information to better fulfil their function as educators. The aim of the study is to examine the current situation with regard to codes of professional ethics and literature on professional ethics for fitness trainers and based on the literature analysis, to identify the main elements of professional ethics: levels of moral regulation, basic principles of ethics, codes, the issue of responsibility, tolerance and autonomy, trainer-client relationships, as well as the trainer’s relationship with other professionals. The article also examines the types of normative ethics (deontological, utilitarian, virtue ethics) required for ethical decision-making.

Identifying the most critical behavioral lifestyles associated with MAFLD: evidence from the NHANES 2017-2020.

Accumulating studies have demonstrated associations between single lifestyle exposures and metabolic dysfunction-associated fatty liver disease (MAFLD). However, the joint effects of lifestyle exposures remain unclear, hindering the development of targeted prevention and control strategies. We aimed to investigate the joint associations between lifestyle exposomes and MAFLD. This study included 5,002 participants from NHANES 2017-2020. Lifestyle exposomes, including sleep duration, metabolic equivalent of task (MET), Healthy Eating Index (HEI)-2015 score, alcohol consumption, and smoke exposure, were identified from questionnaire data. MAFLD was diagnosed by vibration-controlled transient elastography measurements and laboratory data. A logistic regression model and the weighted quantile sum method were used to evaluate the associations of single and joint lifestyle exposomes, respectively, with MAFLD. The population attributable fractions (PAFs) were calculated to assess the population benefits of different intervention strategies. Per-quartile range increases in sleep duration (OR=0.883, 95% CI: 0.826-0.944), MET (0.916, 0.871-0.963), and HEI-2015 score (0.827, 0.756-0.904) were significantly associated with MAFLD. The joint exposure of sleep duration, MET, and HEI-2015 score was associated with MAFLD (0.772, 0.688-0.865), with the highest weight (importance) for MET (0.526). PAFs revealed greater intervention benefits for sleep and the HEI-2015 when the majority of the population (>5%) had a low MAFLD risk (weak intervention targets), whereas MET was the most efficient intervention strategy when minority populations (≤5%) had a low MAFLD risk (strong intervention targets). This study demonstrated significant associations between MAFLD and single and joint exposures to sleep duration, MET, and HEI-2015 and identified physical activity as the most important lifestyle factor. Further population benefit analyses may provide evidence and suggestions for population-level interventions.

Association between living arrangements and health risk behaviors among the Hakka older adults in Fujian, China

BackgroundBehavioral lifestyles are important social determinants of health. The impact of changes in living arrangements on behavioral lifestyles is currently under-explored. This study aims to examine the association between living arrangements and health risk behaviors among the Hakka older adults.MethodsData were extracted from China’s Health-Related Quality of Life Survey for Older Adults 2018. Living arrangements were divided into five categories: living alone, living with spouse only, living with child, mixed habitation, and others. Five health risk behaviors, including unhealthy dietary patterns, drinking, smoking, irregular sleep practices, and physical inactivity were measured. Logistic regression analysis was used to assess the association between living arrangements and specific health risk behaviors, and generalized linear models were established to test the association between living arrangements and the number of health risk behaviors.ResultsA total of 1,262 Hakka older adults were included in this study. Compared to those living alone, those living with spouse only were less likely to have unhealthy dietary patterns (OR = 0.45, P < 0.05) and drinking (OR = 0.50, P < 0.05), those living with the child were less likely to experience unhealthy dietary patterns (OR = 0.35, P < 0.001), drinking (OR = 0.32, P < 0.001), smoking (OR = 0.49, P < 0.05), and physical inactivity (OR = 0.13, P < 0.01). Moreover, those who were living with child (β = -0.78, P < 0.001) or mixed habitation (β = -0.33, P < 0.05) tended to engage in fewer health risk behaviors than those living alone.ConclusionsThis study suggests significant differences in health risk behaviors among the Hakka older adults with different living arrangements. Living with the child could reduce the occurrence of health risk behaviors in the Hakka older adults and thus maintain their health status.

Association between daily use of social media and behavioral lifestyles in the Saudi community: a cross-sectional study.

This study aimed to investigate the association between nine social media platforms use and health-related behavior, including fruit and vegetable intake, physical activity, tobacco use, and risk factors including depression and obesity. A cross-sectional study was conducted using secondary data from the Sharik Health Indicators Surveillance System (SHISS). Participants 18 years and older were recruited via phone-interviews. The nine social media platform use [Twitter-(X), Facebook, Instagram, WhatsApp, LinkedIn, Snapchat, TikTok, Telegram, and YouTube] were assessed using self-reported use. Health-related variables include behavioral factors including diet, physical activity, and tobacco use including (cigarettes, waterpipes, and e-cigarettes), risk of depression and obesity. Logistic regression analysis was performed to explore the association between social media use and health-related variables. The study indicated that daily Snapchat users had a lower healthy diet (fruit and vegetable intake), whereas daily LinkedIn and WhatsApp users were positively associated with a healthier diet, relative to those with infrequent social media use. Furthermore, daily interaction with Instagram, TikTok, Telegram, and YouTube was significantly associated with increased depression risk. Conversely, Snapchat and WhatsApp usage was significantly linked to a decreased depression risk. Tobacco-smoking behaviors were associated with specific social media platforms: cigarette smoking was associated with Snapchat, TikTok, and YouTube; e-cigarette with Facebook, LinkedIn, Snapchat, and TikTok; and waterpipe smoking with Facebook and TikTok. Interestingly, some platforms, such as Instagram, were associated with reduced cigarette smoking. The relationship between social media activity and health-related outcomes remained significant after adjusting for age and gender. This study highlights the potential negative impact of particular daily social media use on health-related variables, including dietary habits, tobacco use, and depression. Nevertheless, particular daily social media use of some platforms was associated with a potential positive impact on the health-related variables. Social media platforms are tools that can be used to achieve both a positive and negative effect. By knowing which demographic segments have a greater presence on one platform, we are creating opportunities to understand the social phenomena and at the same time use it to reach those segments and communicate with them, because each social media platform has its unique way and framework of user communication.

Diabetes risk among US adults with different socioeconomic status and behavioral lifestyles: evidence from the National Health and Nutrition Examination Survey.

Diabetes disproportionately affects minorities and those with low socioeconomic status (SES) in the United States, and differences in behavioral lifestyles are largely responsible for the unequal distribution of diabetes among different groups. With data of 9,969 participants collected in the 2007-2008 and 2009-2010 cycles of the US National Health and Nutrition Examination Survey (NHANES), this study examined several mediators and their mediating effects in the connection between SES and the risk of diabetes. The SES is assessed by the income-to-poverty ratio (IPR), education level, and employment status. For the mediation analysis, we used health-related behaviors as mediators (smoking, alcohol use, consumption of green vegetables and fruits, physical activity and sedentary time, health insurance, and healthcare). In this study, the structural equation model was utilized to evaluate the mediating effects of behavioral lifestyle as a mediator in the relationship between SES and diabetes. A total of 9,969 participants were included in this study. We found a negative nonlinear association between IPR and diabetes risk (Poverall < 0.001; Pnon-linear = 0.46), which was independent of the majority of known or suspected risk factors and confounding variables (gender, age, race). Participants with lower SES had higher risk of diabetes compared with those with higher SES. In mediating analysis, we found alcohol intake (OR = 0.996), physical activity (OR = 0.993), health insurance (OR = 0.998), and healthcare (OR = 1.002) mediated the IPR-diabetes association. But in the relationship between education status and diabetes, the mediation effect of alcohol intake (OR = 0.995), physical activity (OR = 0.991), and health care (OR = 1.008) were obvious. Likewise, alcohol intake (OR = 0.996), fruit intake (OR = 0.998), and health care (OR = 0.975) were important mediators in the association between employment status and diabetes. This study provides critical insights on the link between SES and diabetes. Our results highlight that poor health-related behaviors and limited access to healthcare are important pathways for increased diabetes risk related to those with low SES, particularly among Mexican Americans and males. They should be top priorities for agencies and healthcare providers to develop behavior-related interventions to reduce inequalities in diabetes risk.

The relationship between unhealthy lifestyle patterns and depressive symptoms among residents in Beijing, China: A community-based cross-sectional study.

Depression is a prevalent mental disorder that has an irreversible impact on people's health status. Unhealthy lifestyles are modifiable and influence mental health significantly. The purpose of this study was to explore the impact of different unhealthy lifestyles and their patterns on depressive symptoms. The data for this study were obtained from the 2017 Community Diagnostic survey in Daxing District, Beijing. It was a cross-sectional study that included 6,252 samples. The Patient Health Questionnaire version 9 was used to measure depressive symptoms, and the self-administered questionaires were used to investigate five unhealthy lifestyles, including sleep deprivation, the inadequate intake of fruits and vegetables, physical inactivity, smoking, and excessive alcohol consumption. Respondents were assigned 1 point for each of their unhealthy lifestyles, and their overall unhealthy lifestyle scores were calculated. The total scores of unhealthy lifestyles ranged from 0 to 5. Descriptive analyses and Firth's logistic regression model were used to analyze the relationship between unhealthy lifestyle and depression symptoms. It was found that 12.1% of the participants had depressive symptoms. The respondents whose unhealthy lifestyle scores were 2 (OR1.45, 95%CI:1.01 to 2.12), 3 (OR2.29, 95%CI:1.57 to 3.42), 4 (OR 3.04, 95%CI:1.96 to 4.76), or 5 (OR4.08, 95%CI:2.09 to 7.78) were more likely to experience depressive symptoms in comparison with those whose unhealthy lifestyle scores were 0, and the OR increased with the unhealthy lifestyle scores. When the participants had 3 or more unhealthy lifestyles at the same time, different combination patterns of unhealthy lifestyles showed a different effect on depression. The OR was 3.01 (95%CI:1.45 to 5.95) for the combination of sleep deprivation-insufficient intake of fruit and vegetables-excessive alcohol consumption, and was 2.89 (95%CI:1.52 to 5.25) for the combination of sleep deprivation-insufficient intake of fruit and vegetables-physical inactivity-excessive alcohol consumption. The co-existence of multiple unhealthy behavioral lifestyles are associated with depressive symptoms. Among the five unhealthy lifestyles, sleep deprivation and the inadequate intake of fruits and vegetables may have a greater impact on depression.

Federated Meta-Learning with Attention for Diversity-Aware Human Activity Recognition.

The ubiquity of smartphones equipped with multiple sensors has provided the possibility of automatically recognizing of human activity, which can benefit intelligent applications such as smart homes, health monitoring, and aging care. However, there are two major barriers to deploying an activity recognition model in real-world scenarios. Firstly, deep learning models for activity recognition use a large amount of sensor data, which are privacy-sensitive and hence cannot be shared or uploaded to a centralized server. Secondly, divergence in the distribution of sensory data exists among multiple individuals due to their diverse behavioral patterns and lifestyles, which contributes to difficulty in recognizing activity for large-scale users or 'cold-starts' for new users. To address these problems, we propose DivAR, a diversity-aware activity recognition framework based on a federated Meta-Learning architecture, which can extract general sensory features shared among individuals by a centralized embedding network and individual-specific features by attention module in each decentralized network. Specifically, we first classify individuals into multiple clusters according to their behavioral patterns and social factors. We then apply meta-learning in the architecture of federated learning, where a centralized meta-model learns common feature representations that can be transferred across all clusters of individuals, and multiple decentralized cluster-specific models are utilized to learn cluster-specific features. For each cluster-specific model, a CNN-based attention module learns cluster-specific features from the global model. In this way, by training with sensory data locally, privacy-sensitive information existing in sensory data can be preserved. To evaluate the model, we conduct two data collection experiments by collecting sensor readings from naturally used smartphones annotated with activity information in the real-life environment and constructing two multi-individual heterogeneous datasets. In addition, social characteristics including personality, mental health state, and behavior patterns are surveyed using questionnaires. Finally, extensive empirical results demonstrate that the proposed diversity-aware activity recognition model has a relatively better generalization ability and achieves competitive performance on multi-individual activity recognition tasks.

Estilos de vida comportamentais e motivações para adoção do estilo vegetariano entre universitários do Estado de São Paulo, Brasil.

OBJECTIVE: Young adults have gained recognition as a period marked by changes in dietary and other lifestyle behaviors. The aim was to characterized young adults as meat and non-meat consumers and examine non-meat consumers associations between lifestyle behaviors, reasons, and motivations for adhering to vegetarian styles. METHODS: cross-sectional analysis with 692 college students from 18 to 25 years old. Participants reported socio-demographic and lifestyle characteristics. Non-meat consumers questionnaire was related to aspects of adhering a vegetarian style, and they were classified as difficulties, positive and negative aspects of adhering it. Questions related to overall health were asked. Descriptive analysis and logistic regressions were used for analyses. RESULTS: The majority of the study participants were female (79.2%) with mean age of 21.2±0.07 years. Almost 18% of the participants were non-meat consumers, from those, 78.9% reported themselves as ovo-lacto-vegetarian. Meat consumers had a higher probability for practicing less physical activity (PA) (OR 1.51; 95%CI 1.01, 2.27) and being less underweight (OR 0.22; 95%CI 0.10, 0.49) or normal weight (OR 0.48; 95%CI 0.28, 0.84) as compared to non-meat consumers. Ovo-lacto-vegetarian was more likely to reduce industrialized items (OR 3.69; 95%CI 1.18, 11.56) and less willing to do things (OR 0.10; 95%CI 0.01, 0.52) than vegan adults. Conclusion: Most participants were meat-consumers and had higher chances of not practicing PA and being more overweight. Vegans might be consuming more industrialized foods and were more willing to do things. Future studies should be considered to increase data generalizability in Brazil and other countries.

Levels, distribution, sources and children health risk of PAHs in residential dust: A multi-city study in China

BackgroundPolycyclic aromatic hydrocarbons (PAHs) are typical residential pollutants mainly from biofuel combustion that impose inevitable risk to children. The PAHs in residential dust is universal in most Chinese households with an obvious public health concern. MethodsIn this observational study, a total of 235 residential dust samples from 8 Chinese cities (Panjin, Shijiazhuang, Lanzhou, Luoyang, Xi'an, Wuxi, Mianyang, and Shenzhen) were collected from April 2018 to March 2019, which were extracted and analyzed for 16 priority PAHs by HPLC/FD-UV. Diagnostic ratios, hierarchical clustering analysis and principal component analysis were applied simultaneously for source apportionments. Incremental lifetime cancer risk was employed to estimate children's health risks based on the assumed exposure scenarios. Spearman correlation, Mann-Whitney U test, Kruskal-Wallis H test and Partial Least Squares were used to screen the factors affecting the concentration of PAHs in residential dust. ResultsThe median concentration of ∑16PAHs in residential dust from 8 cities was 44.11 μg/g (0.04 - 355.79 μg/g). ∑16PAHs were found both higher in dust samples in heating season and from downwind households only in Mianyang (p < 0.05). The leading two sources of PAHs were combustion processes and automobile exhaust emissions based on four principal components that accounted for 74.29 % of the total variance. Indoor air environmental factors, household characteristics, and residents' behavioral lifestyles may be the influencing factors of residential dust PAHs. The carcinogenic risk of children aged 0 - 5 years, under the moderate exposure level of PAHs in residential dust, exceeded the acceptable level (10−5 - 10−4 for dermal contact and 10−6 - 10−5 for ingestion). ConclusionsThere was serious PAHs pollution in residential dust under actual living conditions in eight cities across China. More evidence-based measures were needed to control PAHs pollution to safeguard children's health according to appointed sources and influencing factors in residential dust.

Uncontrolled Hypertension and Behavioral Risk Factors among Adult Hypertensive Patients at Saint Paul’s Hospital, Millennium Medical College, Addis Ababa, Ethiopia

Introduction. Uncontrolled hypertension is a state of systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg even though the patients are on antihypertension. The WHO states that it is the most prevalent risk factor for death and disability worldwide, particularly in developing nations. The goal of the current study was to investigate behavioral risk factors for uncontrolled hypertension among adult hypertensive patients in Ethiopia. Methods. From October to November 2020, a cross-sectional study design was carried out in the hypertension follow-up clinic at Saint Paul’s Hospital, Millennium Medical College. The choice of 474 study participants was made using a straightforward random sampling method. A semistructured questionnaire was used to obtain data through a chart review as well as an interview. The data were coded before being imported into Epi-data version 7.0 and exported to SPSS version 25 for analysis. To determine the factors associated with uncontrolled hypertension, a multivariate logistic regression model (AOR, 95% CI, and p value 0.05) was used. Result. This study found that 52.1% of hypertensive patients had uncontrolled hypertension. Among hypertensive patients who are alcoholics, smokers, or salt consumers, the odds of having uncontrolled hypertension are AOR = 16.7, 95% CI = (8.13–34.346); AOR = 7.4, 95% CI = (1.211–45.29); and AOR = 13.4, 95% CI = (7.355–25.098), respectively. Uncontrolled hypertension is 3 (AOR and 95% CI) and 1.5 (AOR and 95% CI) times more prevalent in illiterates and obese people, correspondingly. Hypertensive patients from urban areas, those who did not engage in physical activity, and those who were overweight had uncontrolled hypertension odds that were 0.55, 0.43, and 0.25 (AOR and 95% CI) times lower, respectively. Conclusion. Uncontrolled hypertension is very common among adult hypertensive patients at the hospital. Behavioral practices and lifestyles factors have a strong association with uncontrolled hypertension. Health education and awareness are on the effect of poor behavior practices and lifestyles to increase adherence to hypertension-controlling medical advice.

Planetary sleep medicine: Studying sleep at the individual, population, and planetary level.

Circadian rhythms are a series of endogenous autonomous oscillators that are generated by the molecular circadian clock which coordinates and synchronizes internal time with the external environment in a 24-h daily cycle (that can also be shorter or longer than 24 h). Besides daily rhythms, there exist as well other biological rhythms that have different time scales, including seasonal and annual rhythms. Circadian and other biological rhythms deeply permeate human life, at any level, spanning from the molecular, subcellular, cellular, tissue, and organismal level to environmental exposures, and behavioral lifestyles. Humans are immersed in what has been called the "circadian landscape," with circadian rhythms being highly pervasive and ubiquitous, and affecting every ecosystem on the planet, from plants to insects, fishes, birds, mammals, and other animals. Anthropogenic behaviors have been producing a cascading and compounding series of effects, including detrimental impacts on human health. However, the effects of climate change on sleep have been relatively overlooked. In the present narrative review paper, we wanted to offer a way to re-read/re-think sleep medicine from a planetary health perspective. Climate change, through a complex series of either direct or indirect mechanisms, including (i) pollution- and poor air quality-induced oxygen saturation variability/hypoxia, (ii) changes in light conditions and increases in the nighttime, (iii) fluctuating temperatures, warmer values, and heat due to extreme weather, and (iv) psychological distress imposed by disasters (like floods, wildfires, droughts, hurricanes, and infectious outbreaks by emerging and reemerging pathogens) may contribute to inducing mismatches between internal time and external environment, and disrupting sleep, causing poor sleep quantity and quality and sleep disorders, such as insomnia, and sleep-related breathing issues, among others. Climate change will generate relevant costs and impact more vulnerable populations in underserved areas, thus widening already existing global geographic, age-, sex-, and gender-related inequalities.

Machine learning: A non-invasive prediction method for gastric cancer based on a survey of lifestyle behaviors.

Gastric cancer remains an enormous threat to human health. It is extremely significant to make a clear diagnosis and timely treatment of gastrointestinal tumors. The traditional diagnosis method (endoscope, surgery, and pathological tissue extraction) of gastric cancer is usually invasive, expensive, and time-consuming. The machine learning method is fast and low-cost, which breaks through the limitations of the traditional methods as we can apply the machine learning method to diagnose gastric cancer. This work aims to construct a cheap, non-invasive, rapid, and high-precision gastric cancer diagnostic model using personal behavioral lifestyles and non-invasive characteristics. A retrospective study was implemented on 3,630 participants. The developed models (extreme gradient boosting, decision tree, random forest, and logistic regression) were evaluated by cross-validation and the generalization ability in our test set. We found that the model developed using fingerprints based on the extreme gradient boosting (XGBoost) algorithm produced better results compared with the other models. The overall accuracy of which test set was 85.7%, AUC was 89.6%, sensitivity 78.7%, specificity 76.9%, and positive predictive values 73.8%, verifying that the proposed model has significant medical value and good application prospects.

Consumption of fruits, vegetables, and legumes are associated with overweight/obesity in the middle- and old-aged Chongqing residents: A case-control study.

This study aimed to investigate the association of dietary habits with the risk of overweight/obesity among middle-and-old-aged Chongqing residents and also to examine the joint effects of behavioral lifestyles, dietary habits, and overweight/obesity.In this case-control study, age (±3 years), sex, and time of physical exercise matched 979 overweight/obesity residents, and 979 normal weight residents were recruited.A validated questionnaire was used to collect participants’ information. Conditional logistic regression analysis was performed to determine the adjusted odds ratios (ORs) and 95% CIs of dietary habits and lifestyles associated with overweight/obesity risk.Overweight/obesity was defined as body mass index (BMI) ≥ 24 kg·m−2, and normal weight was defined as 18.5 ≤ BMI < 24 kg·m−2.The multivariate-adjusted models showed the weekly intake frequency of fruits 0–1 (day/week) (OR = 1.79, 95% CI = 1.04–3.10), and legumes 0–1 (day/week) (OR = 2.45, 95% CI = 1.28–4.67), as well as the weekly intake percentage of vegetables ≥ 15% (OR = 2.44, 95% CI = 1.04–5.71) were associated with a higher risk of overweight/obesity. Besides, there were joint effects of lifestyles (smoking or drinking) and dietary habits on overweight/obesity risk (P for interaction < 0.05).The consumption of vegetables, fruits, legumes, and the joint effects of behavioral habits (smoking or drinking) may modify the risk of being overweight/obese. It is essential to consume fruits and legumes at least 2 days/week, quit smoking, and stop consuming alcohol to avoid overweight/obesity among middle-aged and elderly people in Chongqing, China.

Multimorbidity patterns in old adults and their associated multi-layered factors: a cross-sectional study

BackgroundInfluenced by various factors such as socio-demographic characteristics, behavioral lifestyles and socio-cultural environment, the multimorbidity patterns in old adults remain complex. This study aims to identify their characteristics and associated multi-layered factors based on health ecological model.MethodsIn 2019, we surveyed a total of 7480 participants aged 60+ by using a multi-stage random cluster sampling method in Shanxi province, China. Latent class analysis was used to discriminate the multimorbidity patterns in old adults, and hierarchical regression was performed to determine the multi-layered factors associated with their various multimorbidity patterns.ResultsThe prevalence of multimorbidity was 34.70% among the old patients with chronic disease. Over half (60.59%) of the patients with multimorbidity had two co-existing chronic diseases. “Degenerative/digestive diseases”, “metabolic diseases” and “cardiovascular diseases” were three specific multimorbidity patterns. Behavioral lifestyles-layered factors had the most explanatory power for the three patterns, whose proportions of explanatory power were 54.00, 43.90 and 48.15% individually. But the contributions of other multi-layered factors were different in different patterns; balanced diet, medication adherence, the size of family and friendship network, and different types of basic medical insurance might have the opposite effect on the three multimorbidity patterns (p < 0.05).ConclusionsIn management of old patients with multimorbidity, we should prioritize both the “lifestyle change”-centered systematic management strategy and group-customized intervention programs.

Gender differences and multiple determinants of perceived physical and mental health in Italy.

Perceived health is largely dependent on multiple socio-demographic and behavioral lifestyles and healthcare related factors. This could be accentuated when gender is taken into account. The aim of this study is to explore gender-related differences in multiple socio-demographic and behavioral lifestyles and healthcare related factors associated with individual health status and to identify those responsible for changes in perceived physical and mental health among men and women in Italy. We conducted a cross-sectional retrospective study to investigate the association between multiple socio-demographic and behavioral lifestyles and healthcare related factors and individual health status of 99,479 adults in Italy, using data and information obtained from a nationwide survey. To identify the factors that correlate with the perceived physical and mental health status between males and females, we employed a censored regression analysis, a Tobit model, stratifying the analysis by gender. Socio-demographic and behavioral lifestyles factors differently impact on males and females and this impact is stronger on perceived physical than mental health. The perceived physical and mental health status resulted better for men than for women. The integrated analysis of gender differences in socio-demographic and behavioral lifestyles and determinants of health revealed important inequalities, mainly related to citizenship and educational level, among the socio-demographic factors, and smoking habit and obesity, among the behavioral lifestyle factors. Gender imbalances mainly fall into inequality in social inclusion, educational level, and healthy lifestyle. This demonstrates how gender differences are still abundantly present in the modern Italian society. Such information should be taken into consideration by policy makers when interventions to improve the health and quality of life of the population are planned or evaluated.

Anything New about Paternal Contribution to Reproductive Outcomes? A Review of the Evidence.

Paternal health and behavioral lifestyles affect reproductive and neonatal outcomes and yet the magnitude of these effects remain underestimated. Even though these impacts have been formally recognized as a central aspect of reproductive health, health care services in Europe often neglect the involvement of fathers in their reproductive programs. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for systematic reviews, a literature search was carried out to assess the possible impact of paternal health on reproductive outcomes. The comprehensive strategy included cohort studies and meta-analysis available on PubMed, Web of Science, CINAHL, and Google scholar. Cross-referencing of bibliographies of the selected papers ensured wider study capture. Paternal factors were grouped into two categories respectively identified with the terms “Biological Paternal Factors” and “Lifestyle Paternal Factors”. Advanced age may impair male fertility and affect early pregnancy stages. Increased body mass index, smoking, alcohol and recreational drugs, all alter seminal fluid parameters. Hazardous alcohol use correlates with low birthweight in pregnancy and harmful behavioral lifestyles have been linked to congenital heart defects, metabolic and neurodevelopmental disorders in the offspring. Measures targeting paternal health and lifestyle within the first 1,000 days' timeframe need to be implemented in couples undergoing reproductive decisions. Health professionals, as well as future fathers, must be aware of the benefits for the offspring associated with correct paternal behaviors. More research is needed to build guidelines and to implement specific programs aiming at reproductive health promotion.

Association between dietary patterns and depressive symptom based on reduced rank regression in people aged 55 and above in 4 provinces of China

To investigate the dietary patterns related to depressive symptoms based on reduced rank regression in people aged 55 and above in 4 provinces of China and the degree of association between this dietary pattern and depressive symptoms. Stratified, multi-stage, cluster and random sampling method was used to collect personal information such as demographic characteristics, behavioral lifestyles, disease history and medicine use in Chinese aged 55 and above who participated in the baseline survey of &quot;Community-based Cohort Study on Nervous System Diseases&quot; project conducted in 2018 and 2019 in Hebei, Zhejiang, Shaanxi and Hunan Provinces. Food frequency questionnaire was used to obtain dietary data. Depressive symptom was assessed by geriatric depression scale with a cut-off of 11. Participants who have incomplete demographic information, dietary data or scores of geriatric depression scale, and those whose intake frequency of each food-group &gt;99. 5% were excluded. A total of 11 497 participants, 43. 1% of whom were male, were involved in this study with average age of(67. 3±7. 6) years. The reduced rank regression method was used to extract depressive symptoms-related dietary patterns by gender, and the degree of association between dietary patterns and depressive symptom was analyzed by logistic regression. Among males, the depressive symptoms-related dietary pattern was characterized by the higher intake frequency of fried flour-made food, meat, processed meat, animal offal, and preserved eggs, and the lower intake frequency of liquid milk/milk power/cheese, fresh eggs(except preserved eggs) and nut. Among females, the depressive symptoms-related dietary pattern was characterized by the higher intake frequency of fried flour-made food, meat, processed meat, animal offal and preserved eggs, and the lower intake frequency of coarse cereals, fruits, liquid milk/milk power/cheese and fresh eggs(except preserved eggs). The highest quartile group of the dietary pattern score had a significantly higher risk of depressive symptom than the lowest quartile group(OR=3. 498, 95% CI 2. 624-4. 663, P&lt;0. 001 for males; OR=3. 853, 95% CI 3. 002-4. 944, P&lt;0. 001 for females). The depressive symptoms-related dietary pattern is characterized by the higher intake frequency of fried flour-made food, meat, processed meat, animal offal and preserved eggs, and the lower intake frequency of liquid milk/milk power/cheese and fresh eggs(except preserved eggs) in the Chinese aged 55 and above. The score of this dietary pattern is significantly positively correlated with depressive symptom.

Prevalence and Associated Factors of Hypertension among Adults living in the City of Bandundu, Republic Democratic Republic of the Congo: A Population-Based Cross-Sectional Study

Background and Aim: In limited resource settings, reliable epidemiological data generated from hypertension high risk geographical areas or people is a prerequisite for the planning of proven and effective interventions. The aim of the present survey was to assess the prevalence, awareness, control and factors associated with hypertension in adults living in the port City of Bandundu, located in the southwestern part of DRC. Methods: a cross-sectional survey using a modified WHO STEPwise questionnaire for data collection during face-to-face interviews were conducted from 1st May to 30th October 2018. A multistage cluster sampling method was used and inclusion criteria were age ≥18 years and informed consent. Information on demographic parameters, behavioral lifestyles, anthropometric and blood pressure (BP) measurements were obtained. Hypertension was defined as an average of two BP ≥140/90 mmHg or self-reported history of antihypertensive medication use. Independent factors associated with hypertension were identified using logistic regression analysis. Results: The prevalence of hypertension was 34.5% (Women 36.6%). Older age (p

Blood Pressure and Control Factor in Hypertensives Monitored at the Referral Hopsital in Boma. Democratic Repubic of the Congo

Uncontrolled hypertension remains a significant problem in daily clinical practice worldwide. Few data are available on blood pressure control in hospitals. The aim of this study was the frequency of uncontrolled hypertension and associated risk factors in hypertensive patients followed at the general referral hospital of Boma in the province of Kongo Central in the Democratic Republic of Congo From January 1 to May 31, 2019; we conducted a cross-sectional and descriptive study at the Boma reference hospital located in the southeast and 440 Km from Kinshasa, the capital of DR Congo. Included was any hypertensive patient aver 18 years and informed consent. Information on demographic parameters, behavioral lifestyles, anthropometric and biological (blood sugar, creatinine, urine strip and lipid profile ) and blood pressure (BP) measurements was obtained. Hypertension was defined as an average of two BP ≥ 140/90 mmHg. Independent factors associated with control hypertension were identified using logistic regression analysis. P&lt;0.05 defined the level of statistical significance. The prevalence of uncontrolled hypertension was 62 % BP control was observed in 150 (38.0%) of 395 treated hypertensive participants mainly in men than women (68.3 vs 53.3 %; p=0.001). Age &lt;60 years (p=0.005), no smoking ( p=0.047), no Central obesity (p=0.008), CKD ( stade 1 vs 2 ) (p=0.065) , and no hypercholesterolemia ( p= 0.014) emerged as associated with control hypertension. Uncontrolled hypertension was common in our hospitals.Therapeutic lifestyle changes and pharmacological treatment are necessary for hypertensive participants.