Clustering of Health-Related Behavior Patterns and Demographics. Results From the Population-Based KORA S4/F4 Cohort Study

Associations between adrenal gland volume and adipose tissue compartments - a whole body MRI study

BACKGROUND

Obesity is associated with alterations in the hypothalamic-pituitary-adrenal (HPA) axis. Effects of glucocorticoids on adipose tissues appear to depend on the specific adipose depot, in which they take place. In this study, we aimed to investigate the role of MRI-based adrenal gland volume as an imaging marker in association with different adipose tissue compartments.

METHODS

The study cohort derives from the population-based research platform KORA (Cooperative Health Research in the Augsburg Region, Germany) MRI sub-study, a cross-sectional sub-study investigating the interactions between subclinical metabolic changes and cardiovascular disease in a study sample of 400 participants. Originally, eligible subjects underwent a whole-body MRI. MRI-based segmentations were performed manually and semi-automatically for adrenal gland volume, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), epi- and pericardial fat and renal sinus fat. Hepatic and pancreatic lipid content were measured as pancreatic proton density fraction (PDFF) and MR-spectroscopic hepatic fat fraction (HFF). Multivariable linear regression analyses were performed.

RESULTS

A number of 307 participants (56.2 ± 9.1 years, 60.3% male, 14.3% with type 2 diabetes (T2DM), 30.6% with obesity, 34.2% with hypertension) were included. In multivariable analyses, strong positive associations between adrenal gland volume and VAT, total adipose tissue (TAT) as well as HFF persisted after extensive step-wise adjustment for possible metabolic confounders (VAT: beta = 0.31, 95%-CI [0.71, 0.81], p < 0.001; TAT: beta = 0.14, 95%-CI [0.06, 0.23], p < 0.001; HFF: beta = 1.17, 95%-CI [1.04, 1.31], p = 0.009). In contrast, associations between adrenal gland volume and SAT were attenuated in multivariate analysis after adjusting for BMI. Associations between pancreatic PDFF, epi- and pericardial fat and renal sinus fat were mediated to a great extent by VAT (pancreatic PDFF: 72%, epicardial adipose tissue: 100%, pericardial adipose tissue: 100%, renal sinus fat: 81.5%).

CONCLUSION

Our results found MRI-based adrenal gland volume as a possible imaging biomarker of unfavorable adipose tissue distribution, irrespective of metabolic risk factors. Thus, adrenal gland volume may serve as a potential MRI-based biomarker of metabolic changes and contributes to an individual characterization of metabolic states and individual risk stratification. Future studies should elucidate in a longitudinal study design, if and how HPA axis activation may trigger unfavorable adipose tissue distribution and whether and to which extent this is involved in the pathogenesis of manifest metabolic syndrome.

Evaluating the impact of internet communication quality in human resource management on the productivity of construction projects

This research endeavors to examine the intricate relationship between human resource management and communication management in Iraqi construction projects, exploring their impact on project productivity. Beyond its primary objectives, the study aims to identify key challenges and limitations in implementing effective communication and human resource management practices in the Iraqi construction sector. Understanding these challenges provides valuable insights for practitioners and policymakers, informing strategies to overcome obstacles and enhance project productivity. The research methodology involves an initial survey using a main questionnaire, focusing on three key areas: internet communication in human resource management, the influence of internet quality on construction project management, and factors affecting work productivity. The sample size, determined using Morgan's Table, requires a minimum of 248 participants. The questionnaire is distributed to engineers, managers, and technicians, with the number of respondents meeting the required sample size. Data analysis utilizes the Statistical Package for Social Sciences (SPSS), conducting Exploratory Factor Analysis (EFA) for each variable to identify underlying factors. A first-order confirmatory factor analysis is performed using the Analysis of Moment Structures (AMOS) program, creating a structural model incorporating three variables and their associated factors. Out of the initial 64 factors, 21 are included in the final model, refined based on modification indices (M.I) output to improve fit. Results indicate a significant positive effect (0.92) of internet communication quality on labor productivity, while the impact of labor resource management is relatively negligible (-0.07). The size effect of variables on human resource management is 0.05, suggesting a small but non-zero effect. Overall, the findings underscore the importance of internet communication quality in enhancing labor productivity in construction projects and emphasize the need for effective human resource management practices in the industry. This study contributes valuable insights for project managers and practitioners in construction sector.

Breakfast quality and its sociodemographic and psychosocial correlates among Italian children, adolescents, and adults from the Italian Nutrition & HEalth Survey (INHES) study

BACKGROUND

Breakfast quality, together with regularity of breakfast, has been suggested to be associated with cardiometabolic health advantages. We aimed to evaluate the quality of breakfast and its socioeconomic and psychosocial correlates in a large sample of the Italian population.

METHODS

Cross-sectional analyses on 7,673 adult and 505 children/adolescent regular breakfast eaters from the Italian Nutrition & Health Survey (INHES; 2010-2013). Dietary data were collected through a single 24-h dietary recall. Breakfast quality was assessed through the Breakfast Quality Index (BQI) combining intake of ten food groups, energy, and nutrients of public health concern, and potentially ranging from 0 to 10. The association of sociodemographic and psychosocial factors with BQI were analyzed by multivariable-adjusted linear regression models.

RESULTS

The average BQI was 4.65 (SD ± 1.13) and 4.97 (SD ± 1.00) in adults and children/adolescents, respectively. Amongst adults, older age (β = 0.19; 95%CI 0.06 to 0.31 for > 65 vs. 20-40 years) and having a high educational level (β = 0.13; 0.03 to 0.23; for postsecondary vs. up to elementary) were independent predictors of better breakfast quality, while men reported lower BQI (β = -0.08; -0.14 to -0.02 vs. women). Perceived stress levels at home and work and financial stress were inversely associated with BQI. Children/adolescents living in Central and Southern Italian regions had lower BQI compared to residents in Northern Italy (β = -0.55; -0.91 to -0.19 and β = -0.24; -0.47 to -0.01, respectively).

CONCLUSIONS

In adults, breakfast quality was associated with age, sex, and educational level. Perceived stress levels were inversely associated with the quality of breakfast. In children/adolescents, a north-south gradient in breakfast quality was observed.

Cumulative Stress Exposure and Cognitive Function Among Older Adults: The Moderating Role of a Healthy Lifestyle

OBJECTIVES

Although chronic stress is a risk factor for poor age-related cognitive health, there is limited research that has examined how cumulative stress across the lifespan affects cognitive aging. There may also be resilience factors that minimize the effects of cumulative stress on cognitive health. Engaging in a healthy lifestyle is protective against cognitive decline and may therefore interact with cumulative stress to buffer the stress-cognition relationship. The objective of the current study was to examine the moderating role of a healthy lifestyle, comprised of physical activity, social engagement, and sleep quality, in the relationship between cumulative stress exposure (CSE) and baseline and change in cognitive performance (global cognition, episodic memory, executive function) over 9 years among 1,297 older adults in the Midlife in the United States cohort (Mage = 69.0 ± 6.4, 57.8% female).

METHODS

CSE and healthy lifestyle behaviors were indexed using self-reported questionnaires at baseline, and cognitive function was assessed using a battery of standardized neuropsychological tests at baseline and follow-up.

RESULTS

Controlling for age, sex, education, race, marital status, employment status, hypertension, diabetes, and depression, higher CSE was associated with poorer baseline performance and slower decline over time in global cognition and executive function, but not episodic memory. A healthy lifestyle did not significantly moderate the relationship between cumulative stress and cognitive function. Exploratory analyses showed a significant cumulative stress-cognition relationship among females only.

DISCUSSION

This study lends support for a lifespan model of cognitive aging and suggests that the cognitive health consequences of stress extend beyond immediate timescales.

Identifying Clusters of Health Behaviors in a Japanese Working Population at Risk for Non-Communicable Diseases: A Latent Class Analysis of 12,168 Individuals

Introduction

Noncommunicable diseases (NCDs) have become a significant global problem. Health behaviors are associated with NCDs, and characterizing populations using a public health approach can help provide specific interventions according to their characteristics. This study aims to examine the formation of clusters of health behavior combinations in the Japanese working population at risk of NCDs, taking into account the influences of age and gender, using latent class analysis.

Methods

Participants were individuals at risk for NCDs but had not previously been diagnosed with any. Latent class analysis (LCA) was used to study clustering based on basic characteristics and health behaviors. All statistical analyses were conducted using R (Version 4.0.4) and the "poLCA" package (Version 1.6.0).

Results

This study included 12,168 participants. LCA compared models with one to six latent classes. The five-class model was determined to be the most appropriate based on Bayesian Information Criterion, Akaike Information Criterion, and G^2 values, as well as distinguishable cluster characteristics. Cluster 1: "having healthy lifestyles but disliking hospitals"; Cluster 2: "women with healthy lifestyle behaviors"; Cluster 3: "general population"; Cluster 4: "middle-aged group in need of lifestyle improvement"; Cluster 5: "a group receiving treatment for lifestyle-related diseases."

Conclusions

This study reveals discernible health behavior patterns in a sample of the Japanese population using large real-world data, suggesting the effectiveness of distinct approaches when considering a population approach to public health.

Comparison of Seven Healthy Lifestyle Scores Cardiometabolic Health: Age, Sex, and Lifestyle Interactions in the NutrIMDEA Web-Based Study

BACKGROUND

Global health status concerns both the assessment of wellbeing as well as the associated individualized determinants including quality of life and lifestyle factors. This study aimed to evaluate seven cardiometabolic health related scores and the influence, as well as interactions of lifestyle, heart-related and health-related quality of life (HRQoL) factors in order to inform the future implementation of precision public health (PPH).

METHODS

Data collected from 17,333 participants who were enrolled of the NutrIMDEA study. The data collection period was between May 2020 and November 2020 through an online survey. The baseline questionnaire collected information on socio-demographic data, cardiometabolic history, anthropometric variables and lifestyle aspects. Also, physical and mental component scores of SF12 Health Survey (PCS12/MCS12) were assessed as HRQoL features, which were applied to estimated seven scores (LS7, HLS, 20-years DRS %, FBS, CLI, WAI derived, LWB-I).

RESULTS

Most indices (except FBS, CLI, 20-years DRS % and WAI derived) showed that cardiometabolic outcomes and HRQoL measures were dependent on interactions by age and sex. The largest ponderal effect was found in PA total and Mediterranean Diet Score (MEDAS-14) interaction using LS7 as reference. However, using LWB-I as standard, the greatest effect was found in the quality-of-life feature MCS12. Noteworthy, LS7 showed good discrimination against PCS12, while LWB-I demonstrated excellent discrimination to MCS12.

CONCLUSIONS

A major finding was the interplay between MEDAS-14 and PA on the LS7 scale as well as major effects of lifestyle factors and MCS12/PCS12 among scores, which need to be accounted with precision when implementing cardiometabolic screenings with PPH purposes.

Longitudinal associations between metabolites and immediate, short- and medium-term exposure to ambient air pollution: Results from the KORA cohort study

BACKGROUND

Short-term exposure to air pollution has been reported to be associated with cardiopulmonary diseases, but the underlying mechanisms remain unclear. This study aimed to investigate changes in serum metabolites associated with immediate, short- and medium-term exposures to ambient air pollution.

METHODS

We used data from the German population-based Cooperative Health Research in the Region of Augsburg (KORA) S4 survey (1999-2001) and two follow-up examinations (F4: 2006-08 and FF4: 2013-14). Mass-spectrometry-based targeted metabolomics was used to quantify metabolites among serum samples. Only participants with repeated metabolites measurements were included in this analysis. We collected daily averages of fine particles (PM2.5), coarse particles (PMcoarse), nitrogen dioxide (NO2), and ozone (O3) at urban background monitors located in Augsburg, Germany. Covariate-adjusted generalized additive mixed-effects models were used to examine the associations between immediate (2-day average of same day and previous day as individual's blood withdrawal), short- (2-week moving average), and medium-term exposures (8-week moving average) to air pollution and metabolites. We further performed pathway analysis for the metabolites significantly associated with air pollutants in each exposure window.

RESULTS

Of 9,620 observations from 4,261 study participants, we included 5,772 (60.0%) observations from 2,583 (60.6%) participants in this analysis. Out of 108 metabolites that passed quality control, multiple significant associations between metabolites and air pollutants with several exposure windows were identified at a Bonferroni corrected p-value threshold (p < 3.9 × 10-5). We found the highest number of associations for NO2, particularly at the medium-term exposure windows. Among the identified metabolic pathways based on the metabolites significantly associated with air pollutants, the glycerophospholipid metabolism was the most robust pathway in different air pollutants exposures.

CONCLUSIONS

Our study suggested that short- and medium-term exposure to air pollution might induce alterations of serum metabolites, particularly in metabolites involved in metabolic pathways related to inflammatory response and oxidative stress.

Evaluation of lifestyle behaviors, anxiety and depression in patients with hematologic disorders

Patients with hematologic disorders may experience anxiety and depression due to their immunocompromised status and potential side effects of therapies. Healthy lifestyle behaviors might enhance the mental health. To evaluate the association of both separate and clustering pattern lifestyle behaviors with anxiety and depression in hematological patients, healthcare providers can develop future initiatives that respond to the specific needs of this population. A total of 185 patients with hematologic disorders were enrolled in this cross-sectional study. Linear regression analysis was performed to measure the association of separate lifestyles with anxiety and depression. Latent class analysis was further conducted to identify homogeneous and mutually exclusive lifestyle classes, and the logistic regression was then used to assess the relationship between class memberships and symptoms of anxiety and depression. The study found sleep quality was correlated with anxiety and depression. Nevertheless, no association of anxious and depressive symptoms with sitting and exercise, dietary habits, toxicant exposure, drinking, and smoking, in either the overall patient population or patients classified by hematologic neoplasms. Two latent classes of lifestyle behaviors were further identified, but the class memberships were independent of anxiety and depression. The study suggested that promoting sleep quality was a viable intervention for patients with hematologic disorders. However, the clustering pattern of lifestyles may not be a reliable indicator of psychological issues.

A health data led approach for assessing potential health benefits of green and blue spaces: Lessons from an Irish case study

Research producing evidence-based information on the health benefits of green and blue spaces often has within its design, the potential for inherent or implicit bias which can unconsciously orient the outcomes of such studies towards preconceived hypothesis. Many studies are situated in proximity to specific or generic green and blue spaces (hence, constituting a green or blue space led approach), others are conducted due to availability of green and blue space data (hence, applying a green or blue space data led approach), while other studies are shaped by particular interests in the association of particular health conditions with presence of, or engagements with green or blue spaces (hence, adopting a health or health status led approach). In order to tackle this bias and develop a more objective research design for studying associations between human health outcomes and green and blue spaces, this paper discussed the features of a methodological framework suitable for that purpose after an initial, year-long, exploratory Irish study. The innovative approach explored by this study (i.e., the health-data led approach) first identifies sample sites with good and poor health outcomes from available health data (using data clustering techniques) before examining the potential role of the presence of, or engagement with green and blue spaces in creating such health outcomes. By doing so, we argue that some of the bias associated with the other three listed methods can be reduced and even eliminated. Finally, we infer that the principles and paradigm adopted by the health data led approach can be applicable and effective in analyzing other sustainability problems beyond associations between human health outcomes and green and blue spaces (e.g., health, energy, food, income, environment and climate inequality and justice etc.). The possibility of this is also discussed within this paper.

Occupational resource profiles for an addressee orientation in occupational health management: a segmentation analysis

Introduction

In order to make sustainable decisions in precision prevention and health promotion, it is important to adequately assess people's demands and resources at work. To reach them in an addressee-oriented way, a segmentation of employers and employees based on occupational resources is a promising option. We identified profiles based on personal and perceived organizational resources. Furthermore, we used job demands for profile descriptions to obtain a deeper understanding of the profiles, characterizing people with similar occupational resources.

Methods

Personal occupational resources (occupational health literacy and self-efficacy) and perceived organizational resources (job decision latitude and participation in health at work) were assessed among employers and employees (n = 828) in small- and medium-sized enterprises in Germany. Job demands, socioeconomic status, and hierarchy levels in the company were used for further profile descriptions.

Results

A six-profile solution fitted best to the data based on cluster and profile analyses. One profile was characterized by above-average occupational resources, and another profile was characterized by below-average resources. The other four profiles showed that the individual and perceived organizational resources contrasted. Either organizational resources such as job decision latitude existed and personal resources were not highly developed or people had high individual motivation but few possibilities to participate in health at work. People with medium or high job demands as well as people with low socioeconomic status were most frequently in below-average resource profiles. Employers with high hierarchy levels were overrepresented in the above-average profiles with high organizational resources.

Discussion

Following the segmentation of the addressees, organizations might be supported in identifying needs and areas for prevention and health promotion. Interventions can be optimally developed, tailored, and coordinated through a deeper understanding of job demands and resources. Especially employees with low socioeconomic status and high job demands might profit from an addressee-orientated approach based on resource profiles. For example, employees obtain an overview of their occupational resource profile to recognize the development potential for safe and healthy behavior at work. Follow-up research should be used to examine how this feedback to employers and employees is implemented and how it affects the sustainability of tailored interventions.

Lifestyle behaviors and associated factors among individuals with diabetes in Brazil: a latent class analysis approach

The purpose of the cross-sectional study was to identify patterns of modifiable lifestyle behaviors and examine the relationship between sociodemographic characteristics and distinct lifestyle behaviors. The data were gathered from the National Health Survey 2019, a study that included adults with diabetes. Four domains of lifestyle behaviors were used to define these behaviors: smoking, alcohol consumption, physical activity, and diet. The association between patterns of lifestyle behaviors and variables of interest was assessed using multinomial regression analysis. The three lifestyle patterns identified were: Class 1, referred to as "unhealthy diet," comprised 17.0% of the sample and was characterized by unhealthy eating habits; Class 2 (less active and insufficient fruit and vegetable intake) represented 71.2% of the sample; Class 3 referred to as "low risk" (11.8%) is characterized by a lower probability of engaging in most risky behaviors. A person over 45 years of age with little or no education and no health care coverage was less likely to be a member of Class 1. Male individuals who do not attend a doctor regularly exhibited more chances of belonging to Class 2. Mixed-race individuals aged 45 years or more with a low level of education have a lower chance of belonging to this class.

Clustering of Health and Oral Health-Compromising Behaviours in Army Personnel in Central Peninsular Malaysia

Health- and oral health-compromising behaviours (HOHCBs) impact the health readiness of military personnel, resulting in decreased fitness performance, thus affecting combat readiness. This study aimed to identify the clustering patterns and number of HOHCBs in army personnel in Central Peninsular Malaysia. Thus, a cross-sectional study using a multistage sampling technique and a validated 42-item online questionnaire was conducted to assess ten health (medical screening, physical activity, sedentary lifestyle, smoking status, alcohol consumption, substance abuse, aggressive behaviours, sleep, and road safety habits) and five oral health behaviour domains (tooth brushing, fluoridated toothpaste use, flossing, dental visits, and bruxism). Each HOHCB was dichotomised into healthy and health-compromising behaviour and analysed using hierarchical agglomerative cluster analysis (HACA). With the majority being males (92.5%), of other ranks (96.8%), and healthy (83.9%), 2435 army members of a mean age of 30.3 years (SD = 5.9) participated, with a response rate of 100%. HACA identified two clustering patterns: (i) 'high-risk behaviours' (30 HOHCBs) and (ii) 'most common risk behaviours' (12 HOHCBs) with a mean clustering number of 14.1 (SD = 4.1). In conclusion, army personnel in Central Peninsular Malaysia displayed 2 broad HOHCB clustering patterns, 'high-risk' and 'most common risk', with an average of 14 HOHCB clusters per person.

Longitudinal patterns and sociodemographic profiles of health-related behaviour clustering among middle-aged and older adults in China and Japan

Given inevitable age-related decreases in physical or mental capacity, studies on health-related behaviour (HRB) clustering in older people provide an opportunity to reduce health-care costs and promote healthy ageing. This study explores the clustering of HRBs and transition probabilities of cluster memberships over time, and compares sociodemographic characteristics of these clusters among Chinese and Japanese middle-aged and older adults. Using the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2015 (N = 19614) and the Japanese Study of Ageing and Retirement (JSTAR) from 2007 to 2011 (N = 7,080), Latent Transition Analysis was applied to investigate the clustering and change in clustering memberships of smoking, alcohol consumption, physical activity and body mass index. Multivariate logistic regression was used to explore the sociodemographic characteristics of these longitudinal HRB cluster members. We identified four common clusters in CHARLS and JSTAR: ‘smoking’, ‘overweight or obese’, ‘healthy lifestyle’ and ‘current smoking with drinking’, and an additional cluster named ‘ex-smoking with drinking’ in JSTAR. Although HRB cluster members were largely stable in both cohorts, participants in China tended to move towards an unhealthy lifestyle, while participants in Japan did the opposite. We also found that participants who smoked and drank were more likely to be male, younger, less educated and unmarried in both cohorts, but the overweight or obese participants were female, urban and higher income in CHARLS but not JSTAR. Our study not only contributes to the knowledge of longitudinal changes in health-related behavioural clustering patterns in an Asian elderly population, but may also facilitate the design of targeted multi-behavioural interventions to promote healthy lifestyles among older people in both countries.

A Cross-Sectional Investigation of Preadolescent Cardiometabolic Health: Associations with Fitness, Physical Activity, Sedentary Behavior, Nutrition, and Sleep

BACKGROUND

Cardiometabolic disease (CMD) risk often begins early in life. Healthy lifestyle behaviors can mitigate risk, but the optimal combination of behaviors has not been determined. This cross-sectional study simultaneously examined the associations between lifestyle factors (fitness, activity behaviors, and dietary patterns) and CMD risk in preadolescent children.

METHODS

1480 New Zealand children aged 8-10 years were recruited. Participants included 316 preadolescents (50% female, age: 9.5 ± 1.1 years, BMI: 17.9 ± 3.3 kg/m²). Fitness (cardiorespiratory fitness [CRF], muscular fitness), activity behaviors (physical activity, sedentary, sleep), and dietary patterns were measured. Factor analysis was used to derive a CMD risk score from 13 variables (adiposity, peripheral and central hemodynamics, glycemic control, and blood lipids).

RESULTS

Only CRF (β = -0.45, p < 0.001) and sedentary time (β = 0.12, p = 0.019) were associated with the CMD risk score in the adjusted multivariable analysis. CRF was found to be nonlinear (VO₂ max ≤ ≈42 mL/kg/min associated with higher CMD risk score), and thus a CRF polynomial term was added, which was also associated (β = 0.19, p < 0.001) with the CMD risk score. Significant associations were not found with sleep or dietary variables.

CONCLUSION

The findings indicate that increasing CRF and decreasing sedentary behavior may be important public health targets in preadolescent children.

Association of lifestyle behaviors with health-related quality of life among patients with hematologic diseases

PURPOSE

Health-related quality of life (HRQoL) is a multi-dimensional construct used to assess the impact of health status on quality of life, and it is known to be affected by lifestyle behaviors. This study focused on multiple lifestyle behaviors among patients with hematologic diseases, including physical activity, dietary intake, sleep quality, occupational exposure, alcohol consumption and smoking. The main objective was to investigate the association of both individual and clustering of health behaviors with HRQoL among the population with hematologic diseases based on a comprehensive lifestyle survey.

METHODS

A total of 539 patients with hematologic diseases aged over 18 years were enrolled in this cross-sectional study. Latent class analysis was used to identify homogeneous, mutually exclusive lifestyle classes, and multinomial logistic regression was then performed to explore the association of lifestyle classes membership with HRQoL. Meanwhile, multiple linear regression and quantile regression were used to identify the relationship between individual lifestyle behaviors and HRQoL.

RESULTS

A three-class model was selected based on conceptual interpretation and model fit. We found no association between multiple lifestyle behaviors and HRQoL in the 3-class model, either in the whole patients or in subgroups stratified by hematological malignancies. Further research on each lifestyle found that physical activity, dietary intake, occupational exposure, alcohol consumption or smoking were independent of HRQoL. Sleep quality was positively associated with HRQoL.

CONCLUSION

Our findings suggested that clustering of lifestyle behaviors may not be an indicator to reflect the health quality of patients with hematologic diseases. Sleep represents a viable intervention target that can confer health benefits on the hematologic patients.

Lifestyle Profiles and Their Sociodemographic Correlate in an Academic Community Sample

Promoting healthy behaviors throughout life is an essential prevention tool. Prior research showed that unhealthy behaviors tend to co-occur and interplay. However, which behaviors co-occur most frequently and which sociodemographic variables are associated with specific clusters of unhealthy behavior are still being determined. This study aimed to identify different lifestyle profiles and analyze their associations with sociodemographic factors in an Italian academic community to plan targeted initiatives to promote healthy lifestyles. A sample of 8715 adults from an Italian university (mean age = 26 years; range = 18-76; 30% male) participated in an online survey in 2019. Four health-related behaviors were evaluated: diet, physical activity, smoking, and alcohol consumption. Lifestyle profiles were identified through cluster analysis. Then, a multinomial logistic regression was performed to explore the association among lifestyle profiles, sociodemographic variables (age, gender, and academic role), and body mass index (BMI). Results showed that older age was associated with the probability of belonging to the profile characterized by smoke addiction and regular alcohol consumption but also with the healthiest diet. The younger the age, the greater the probability of belonging to the most physically active profile. Men were more likely than women to belong to the lifestyle profile with the most regular alcohol consumption and the highest physical activity. Lower BMI was associated with the most physically active profile. This study shed light on factors associated with different co-occurring health-related behaviors that should be considered in planning effective communication strategies and preventive health interventions within the academic community.

Patterns of health lifestyle behaviours: findings from a representative sample of Israel

Background

Researchers are increasingly acknowledging the importance of understanding patterns of engagement in multiple, as opposed to isolated, health behaviours. Accordingly, several studies, targeting various geographical regions, have begun to identify and characterize unique classes of individuals in terms of their engagement in health behaviours, towards gaining insights that might guide tailored health interventions. Our study extends this stream of research to the Israeli context, as well as examines whether certain sociodemographic characteristics tend to be associated with affiliation to a specific group of individuals, i.e., class membership.

Methods

Two large representative samples were obtained from the 2010 and 2017 National Social Surveys of the Israel Central Bureau of Statistics. Latent Class Analysis was used to identify different classes, based on levels of engagement in five health behaviours: fruit-and-vegetable consumption, physical activity, smoking avoidance, sleep, and influenza vaccination. Multinomial logistic regression was applied to test the associations between sociodemographic characteristics (age, gender, religion, education level) and class membership.

Results

We identified three distinct classes (denoted “healthy”, “unhealthy”, and “mixed”). Overall, the “healthy” class was characterized by healthy levels of fruit-and-vegetable consumption and physical activity, a low rate of currently-smoking individuals, and a high proportion of influenza vaccination. The “mixed” class was characterized by healthy levels of fruit-and-vegetable consumption and sleep duration, moderate levels of physical exercise, a high proportion of currently light smokers, and a low rate of vaccination. The “unhealthy” class was marked by relatively low levels of engagement in health behaviours. Generally, older, Jewish, and more-educated individuals were more likely to belong to the “healthy” class, while young, non-Jewish, and less-educated individuals were more likely to belong to the “unhealthy” class. We further identified differences between the 2010 and 2017 samples (e.g., differences in men’s likelihood of being in the “unhealthy” class), suggesting that some behavioural patterns might have changed over time.

Conclusion

This research identified three classes of engagement in health behaviours across two large and representative samples. Moreover, the classes were associated with unique sociodemographic characteristics. Consequently, our findings can highlight health-behavioural patterns relevant to different sub-populations that should be considered in public health interventions.

Association between Sleep Disturbances During Childhood and Smoking Trajectories During Adulthood: The Longitudinal TEMPO Cohort Study

OBJECTIVE

This study examined the longitudinal association between child sleep disturbances from ages 3 to 16 and smoking in adulthood among subjects from a French cohort study.

METHODS

Data from 2,134 subjects who participated in the French TEMPO cohort from 1991 to 2018 were used. Sleep disturbances observed from ages 3 to 16 years defined our exposure. Tobacco consumption trajectories constitute our outcomes and were ascertained by using Group-Based Trajectory Modeling, a semiparametric probabilistic method that hypothesizes the existence of distinct developmental trajectories over time within one population. The impact of SDs in childhood on adulthood's Tobacco consumption were studied using multinomial logistic regression.

RESULTS

Sleep disturbances at 16 years or under were observed in 26.5% of participants. Five smoking trajectories were defined: "non-smokers", "decrease in consumption at age 20 years", "low-level tobacco use", "smoking followed by cessation at age 30 years" and "high-level tobacco use". No statistically significant association between sleep disturbances and smoking trajectories was found. Compared with nonsmokers, adjusted odds-ratios and 95% Confidence Intervals for each trajectory were respectively: 0.81 [0.52-1.26], 1.28 [0.74-2.22], 1.37 [0.88-2.15] and 1.01 [0.60-1.69].

CONCLUSION

These results suggest that smoking in adulthood may not be related to sleep disturbances in childhood.

Clustering of Health Risk Behaviors in Mexican and Puerto Rican Men: Results from the Latino Men's Health Initiative

Engaging in multiple health risk behaviors simultaneously may increase the risk for cardiometabolic diseases. This study examined the prevalence and clustering of three health behaviors (physical activity, fruit and vegetable consumption, and smoking) among Latino men. The participants were 99 Mexican and 104 Puerto Rican men who participated in a study addressing culture- and obesity-related factors. The health behaviors were obtained from self-reported and anthropometric assessments through objective measurements. Among all participants, 5% had no health risk behaviors, 30% had one, 47% had two, and 18% had all three; their most common health risk behavior cluster was low physical activity and low fruit and vegetable consumption (28%). Among Puerto Rican men, 7% had no health risk behaviors, 24% had one, 51% had two, and 18% had all three; their most common health risk behavior cluster was current smoker and low fruit and vegetable consumption (28%). Among Mexican men, 3% had no health risk behaviors, 36% had one, 43% had two and 19% had all three; their most common health risk behavior cluster was low physical activity and low fruit and vegetable consumption (33%). The findings highlight the need for lifestyle interventions that target multiple health risk behaviors related to cardiometabolic diseases in Latinos.

Clustering of health behaviors among Japanese adults and their association with socio-demographics and happiness

Background

Scholars have associated happiness with health behaviors, which co-occur and exert synergistic effects. Therefore, identifying clusters of health behaviors and their effect on happiness can contribute to the development of strategies for promoting happiness and improving health behaviors.

Aim

This study aimed to examine clusters of health behaviors and their associations with socio-demographics and with happiness among Japanese adults.

Methods

This study used data from the Japanese Household Panel Survey and the Keio Household Panel Survey. Questionnaires were distributed to 4,993 households out of which 1,554 responses were analyzed (participants aged 27−65 years). The survey included health behaviors (alcohol consumption, smoking, vegetable and fruit consumption, breakfast-eating habits, and physical activities), happiness, and socio-demographics. Latent class analysis was conducted to identify the clusters, whereas latent regression was employed to investigate socio-demographics related to the clusters. Logistic regression analysis was conducted to examine the relation between happiness and the clusters.

Results

Two health behavior clusters were identified: Cluster 1 (low substance use and good dietary habit; n = 817; 52.3%) and Cluster 2 (high alcohol, poor nutrition, and inactive; n = 737; 47.7%). Latent regression analysis indicated that all socio-demographics, barring socioeconomic status, were significantly associated with the clusters. The “low substance use and good dietary habit” cluster was significantly related with higher odds of happiness (odds ratio = 1.425, 95% confidence interval = 1.146−1.772, p = 0.001).

Conclusions

This study identified health behavior clusters among Japanese adults and established the association between the “low substance use and good dietary habit” cluster and high levels of happiness. However, the causality of the relationship between health behavior and happiness remains unclear, which highlights the need for further research to elucidate the underlying mechanisms.

Sleep Characteristics According to Gender and Age Measured by Wrist Actigraphy

The sleep/wake rhythm is one of the most important biological rhythms. Quality and duration of sleep change during lifetime. The aim of our study was to determine differences in sleep efficiency, movement, and fragmentation during sleep period between genders and according to age. Sleep period was monitored by wrist actigraphy under home-based conditions. Seventy-four healthy participants-47 women and 27 men participated in the study. The participants were divided by age into groups younger than 40 years and 40 years and older. Women showed lower sleep fragmentation and mobility during sleep compared to men. Younger women showed a higher actual sleep and sleep efficiency compared to older women and younger men. Younger men compared to older men had a significantly lower actual sleep, lower sleep efficiency and significantly more sleep and wake bouts. Our results confirmed differences in sleep parameters between genders and according to age. The best sleep quality was detected in young women, but gender differences were not apparent in elderly participants, suggesting the impact of sex hormones on sleep.

Attribute-centred theorizing to address behavioural changes

Despite the importance of behaviours in promoting health and wellness, persuading people to adopt and sustain healthy behaviours remains a significant public health challenge. Considerable progress has been made in developing and testing theories about the personal, social, environmental and structural drivers of behaviours. However, theorizing about behaviours themselves has remained elusive, as evidenced by the absence of a widely accepted taxonomy of behaviours. By carefully examining the nature of behaviours, practitioners and researchers can identify the most effective ways to promote behavioural change. We propose attribute-centred theorizing as an approach for defining behaviours based on their relevant properties, which can then assist in developing a taxonomy of behaviours and theorizing about them. Behaviours differ because of their underlying properties; for example, some behaviours are addictive, others are publicly observable and others are expensive. Addictiveness, privacy and cost are therefore three (of the many) attributes relevant for theorizing about behaviours. We describe a framework for operationalizing attribute-centred theorizing, which includes generating behavioural attributes, verifying and testing those attributes, and constructing a behavioural matrix to inform campaigns or interventions. We illustrate this framework using the examples of Guinea-worm disease and cardiovascular diseases. The benefits of our approach include the ability to inform intervention development and the ability to generalize across different behaviours; however, more research on converting the behavioural matrix into actual policy is needed.

Health-Related Lifestyle Profiles in Healthy Adults: Associations with Sociodemographic Indicators, Dispositional Optimism, and Sense of Coherence

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally. Promoting healthy behaviors throughout life is an essential prevention tool. This study investigated the associations among lifestyle profiles (including diet, alcohol consumption, physical activity, cigarette smoking, and cardiovascular screening), sociodemographic factors (gender, age, education, and family history of CVDs), and psychological factors (sense of coherence and dispositional optimism). In total, 676 healthy adults (mean age = 35 years; range = 19-57; 46% male) participated in an online survey. Lifestyle profiles were identified through cluster analysis, and a multinomial logistic regression was then performed to explore their association with sociodemographic and psychological variables. Results show that men were more likely than women to belong to the lifestyle profile with the highest amount of physical activity (OR = 2.40; p < 0.001) and the greatest attention to cardiovascular screening (OR = 2.09; p < 0.01). Lower dispositional optimism was associated with the profile paying the greatest attention to cardiovascular screening (OR = 0.67; p < 0.05). Sense of coherence, in terms of lower comprehensibility (OR = 0.67; p < 0.05) and higher manageability (OR = 1.43; p < 0.05), was associated with the lifestyle profile characterized by an unhealthy diet, sedentary lifestyle, and nonsmoking. This study shed light on factors associated with different co-occurring health-related behaviors that should be considered in planning effective communication strategies promoting adherence to health claims.

Elena+ Care for COVID-19, a Pandemic Lifestyle Care Intervention: Intervention Design and Study Protocol

Background: The current COVID-19 coronavirus pandemic is an emergency on a global scale, with huge swathes of the population required to remain indoors for prolonged periods to tackle the virus. In this new context, individuals' health-promoting routines are under greater strain, contributing to poorer mental and physical health. Additionally, individuals are required to keep up to date with latest health guidelines about the virus, which may be confusing in an age of social-media disinformation and shifting guidelines. To tackle these factors, we developed Elena+, a smartphone-based and conversational agent (CA) delivered pandemic lifestyle care intervention. Methods: Elena+ utilizes varied intervention components to deliver a psychoeducation-focused coaching program on the topics of: COVID-19 information, physical activity, mental health (anxiety, loneliness, mental resources), sleep and diet and nutrition. Over 43 subtopics, a CA guides individuals through content and tracks progress over time, such as changes in health outcome assessments per topic, alongside user-set behavioral intentions and user-reported actual behaviors. Ratings of the usage experience, social demographics and the user profile are also captured. Elena+ is available for public download on iOS and Android devices in English, European Spanish and Latin American Spanish with future languages and launch countries planned, and no limits on planned recruitment. Panel data methods will be used to track user progress over time in subsequent analyses. The Elena+ intervention is open-source under the Apache 2 license (MobileCoach software) and the Creative Commons 4.0 license CC BY-NC-SA (intervention logic and content), allowing future collaborations; such as cultural adaptions, integration of new sensor-related features or the development of new topics. Discussion: Digital health applications offer a low-cost and scalable route to meet challenges to public health. As Elena+ was developed by an international and interdisciplinary team in a short time frame to meet the COVID-19 pandemic, empirical data are required to discern how effective such solutions can be in meeting real world, emergent health crises. Additionally, clustering Elena+ users based on characteristics and usage behaviors could help public health practitioners understand how population-level digital health interventions can reach at-risk and sub-populations.

Daily Physical Activity, Sedentary Behavior and Alcohol Use in At-Risk College Students

BACKGROUND

The college years present an opportunity to establish health behavior patterns that can track across adulthood. Health behaviors tend to cluster synergistically however, physical activity and alcohol have shown a positive association.

PURPOSE

This study applied a multi-method approach to estimate between- and within-person associations between daily physical activity, sedentary behavior and alcohol use among polysubstance-using college students.

METHODS

Participants were screened for recent binge drinking and either tobacco or cannabis use. They wore an activPAL4 activity monitor and a Secure Continuous Remote Alcohol Monitor continuously in the field for 11 days, and completed daily online questionnaires at the beginning of each day to report previous day physical activity, sedentary behavior, and alcohol consumption.

RESULTS

Participants (N = 58, Mage = 20.5 years, 59% women, 69% White) reported meeting national aerobic physical activity guidelines (75%) and drinking 2-4 times in the past month (72%). On days when participants reported an hour more than usual of daily sedentary behavior, they reported drinking for less time than usual (γ = -.06). On days when participants took 1,000 more steps than usual, the longest episode of continuous transdermal alcohol detection was shorter (γ = -.03).

CONCLUSIONS

Daily physical activity and sedentary behavior were negatively associated with time-based measures of alcohol use with the lowest risk on days characterized by both activity and sedentary behavior. Intensive longitudinal monitoring of time-based processes can provide new insights into risk in multiple behavior change and should be prioritized for future work.

Dietary habits and the presence and degree of asymptomatic diverticular disease by magnetic resonance imaging in a Western population: a population-based cohort study

BACKGROUND

Despite the worldwide burden of diverticular disease, the connections between diverticular disease and dietary habits remain poorly understood, particularly in an asymptomatic representative sample. We investigated the association between asymptomatic diverticular disease as assessed by magnetic resonance imaging (MRI) and dietary habits in a Western study cohort.

METHODS

Participants from a cross-sectional sample of a population-based cohort study underwent whole-body 3T-MRI including an isotropic VIBE-Dixon sequence. The presence and extent of diverticular disease was assessed in blinded fashion. Habitual dietary intake was recorded using a blended approach, applying 24-h food lists and a food-frequency questionnaire. Traditional cardiometabolic risk factors were obtained by interviews and medical examination. Univariate and multivariate associations were calculated.

RESULTS

A total of 308 subjects were included in this analysis (56% male, 56.4 ± 9.1 years). 39.9% had any form of diverticular disease and 15.3% had advanced asymptomatic diverticular disease. After adjustment for age, sex and total energy intake a higher intake of fiber and vegetables was associated with a lower odds for asymptomatic diverticular disease (fiber: OR 0.68 95% CI [0.48, 0.95]; vegetables: OR 0.72 95% CI [0.53, 0.97]) and an increased intake of meat was associated with an approximately two-fold higher odds for advanced asymptomatic diverticular disease (OR 1.84 95% CI [1.13, 2.99]). However, after additional adjustment for body-mass-index (BMI), alcohol consumption, smoking behavior and physical activity only a high fiber and vegetables intake remained significantly associated with lower odds of asymptomatic diverticular disease.

CONCLUSION

Our results indicate that a high-fiber diet and increased intake of vegetables is associated with lower odds of having asymptomatic diverticular disease, independent of age, sex, total energy intake, BMI and other life-style factors.

Health Behaviors and Health-Related Quality of Life Among U.S. Adults Aged 18-64 Years

INTRODUCTION

This study aims to (1) describe the prevalence and clustering of 3 health behaviors, (2) examine the association between individual health behaviors and health-related quality of life, and (3) explore the association between the clustering of the health behaviors and health-related quality of life.

METHODS

Investigators analyzed a sample of U.S. adults aged 18-64 years using data from the 2016-2018 Behavioral Risk Factor Surveillance System survey in March 2020. Logistic regression models examined the associations among 3 healthy behaviors (currently not smoking, physical activity, and nonheavy alcohol consumption) and 4 indicators of health-related quality of life (general health, physical health, mental health, and activity limitation). Alpha was set at 0.01.

RESULTS

A total of 450,870 individuals were included in the analysis (weighted n=100,102,329). Of these, 82.0% were current nonsmokers, 92.8% were nonheavy drinkers, and 77.6% reported physical activity. The prevalence of having none, 1, 2, and 3 of the health behaviors was 0.7%, 7.7%, 30.1%, and 61.5%, respectively. Smoking status and physical activity status were significantly associated with all the 4 health-related quality of life indicators. Alcohol status was significantly associated with mental health and activity limitation. The associations demonstrated a higher health-related quality of life among individuals who reported healthy behaviors than among those who did not engage in healthy behaviors. Compared with respondents who reported none of the health behaviors, people with all 3 health behaviors were more likely to report higher health-related quality of life.

CONCLUSIONS

Health behaviors were significantly associated with health-related quality of life among U.S. adults. Healthy behaviors should be encouraged because adopting these behaviors may contribute to a higher health-related quality of life.

High educational attainment redresses the effect of occupational social class on health-related lifestyle: findings from four Spanish national health surveys

PURPOSE

Social determinants as occupational social class or educational attainment might influence health outcomes. This phenomenon is known as the social gradient of health and is related to a skewed distribution of health behaviours that might explain differences in morbidity and mortality between social groups. But social class and educational attainment differ in their nature and might have distinct effects on health. Here we study the combined effect of educational attainment and occupational social class on health-related lifestyle.

METHODS

We retrieved data from four large-scale, national representative Spanish surveys (n = 67,171). A latent class regression analysis was run to identify clusters of health-related lifestyle behaviours. Clusters were made according to sociodemographic factors, including a combined analysis of education and occupational social class.

RESULTS

Higher educational attainment and occupational social class were associated with a healthier lifestyle for both sexes. The combined analysis of education and social class indicated that women with secondary education showed a high risk combination of unhealthy behaviours, as men with middle, primary or no education.

CONCLUSIONS

Regardless of social class, a higher educational attainment redresses the effect of occupational social class on health-related behaviours. Our results suggest that education likely plays a crucial role in population health outcomes through its effects on lifestyle.

Clustering of lifestyle risk factors among adult population in India: A cross-sectional analysis from 2005 to 2016

Introduction

Individual’s early life style and health behaviors are directly linked to chronic non-communicable diseases. Considering the increased burden of NCDs during the last two decades, the aim of this study is to assess co-occurrence/clustering of lifestyle risk factors and its association with different socio-demographic and economic characteristics among adult men and women in India from 2005–2016.

Methods

This study utilized the data from the National Family Health Survey 2005–06 and 2015–16 survey rounds. Multinomial logistic regression is employed to evaluate co-occurrence of multiple risk factors among adult men and women of different socio-economic and demographic characteristics to identify the subgroups with elevated risk of clustering of multiple unhealthy lifestyle risk factors.

Results

More adult men in India tend to exhibit clustering of multiple non-communicable disease risk factors than females. Individuals between 30–49 years of age, residing in urban areas, the population with no education, separated couples and those from poor economic strata are the specific population subgroups show higher prevalence of co-occurrence of multiple risk factors. The regional pattern of clustering of risk factors shows that the prevalence of co-occurrence of multiple risk factors is higher among men and women from the North-Eastern part of India compared to the other regions of the country.

Conclusion

The prevalence of clustering of multiple risk factors associated with chronic NCDs is substantially high and has increased between 2005–06 to 2015–16. India may therefore experience a significant increase in the burden of chronic non-communicable diseases in the coming years. We therefore conclude that appropriate strategies should be implemented by policy makers and the government to reduce the overall health burden of NCDs due to lifestyle habits.

Cluster of factors associated with physical frailty in community-dwelling elderly people

Abstract Frailty is characterized as a set of factors related to the body structure that lead the subject to a process of physical vulnerability, increasing their dependence. The study aims to investigate the aggregation of factors related to physical frailty (PF) in elderly residents of a city with a low Human Development Index (HDI). This is a cross-sectional study carried out in the city of Ibicuí, state of Bahia, Brazil, and including a random 270 elderly people aged ≥ 60 years. The physical frailty condition was identified according to the criteria proposed by Fried and collaborators. In the data analysis, descriptive statistics, cluster analysis, and multinominal logistic regression procedures were used. The highest prevalence of aggregation was identified when the four risk factors were combined: weight loss, strength, walking speed and physical activity levels (O/E = 4.36; CI = 4.04 - 4.68). It was identified that older people (80 years old or more) with a lower level of education (unlettered) were more likely to have three or more risk factors for physical frailty (p <0.05). As for sociodemographic variables, those who were older and had lower levels of education were more likely to have three or more risk factors. The development of actions that encourage a healthier lifestyle to favor the prevention and treatment of physical frailty, as well as to increase health literacy and knowledge, may reduce the problems related to this condition in older adults, mainly thinking about the next generations.

Empirically derived dietary-lifestyle patterns and cardiometabolic health in young men: a review

Sex and gender are important factors that impact cardiometabolic traits. Men have lower life expectancy and higher prevalence of fatal chronic conditions at younger age. Lifestyle risk profiles in young men have been rarely studied in the context of cardiometabolic health. This review aimed to summarise the evidence regarding the patterns of dietary-lifestyle behaviours in a population of young men (age <40years) and their associations with cardiometabolic health. Overall, unfavourable clusters of health behaviours are more prominent in men, when compared to women and more prevalent in younger adults, when compared to older age groups. Early signs of cardiometabolic health abnormalities have been reported among men with higher adherence to patterns which consistently shared poor dietary habits as a common denominator, combined with stimulant use, inadequate sleep or insufficient physical activity. In the majority of studies, dietary assessment was limited to the investigation of one or two behaviours, most frequently fruit and vegetable intake. Since young men may engage in a mixture of explicit behaviours, the examination of a singular dietary habit may not represent the overall diet quality. To conclude, the data regarding the synergistic effects of a broad spectrum of dietary and lifestyle behaviours in the context of cardiometabolic health remain scarce in this population. The inclusion of a broader range of dietary and lifestyle variables into the multicomponent pattern analysis might have a greater potential in explaining the association with cardiometabolic health. Defining behavioural clusters can help to develop interventions, tailored to the specific needs of the targeted group.