Background
Physical inactivity, excessive sedentary time, and lack of sleep time have been independently associated with lower health‐related physical fitness. However, little is known about the ...combined association between 24‐h movement guidelines (i.e., physical activity, recreational screen time, and sleep duration) and components of physical fitness.
Objective
The main aim was to examine the likelihood of having high/very high levels on different components of physical fitness based on meeting with 24‐h movement guidelines.
Methods
In this cross‐sectional study, 1276 Spanish youths (13.07 ± 0.86; 55.88% boys), aged 11–16 years, completed self‐reported questionnaires on physical activity, recreational screen time, and sleep duration. Physical fitness components were assessed by 20‐m shuttle‐run test, standing long jump test, handgrip strength test, and 4 × 10‐m shuttle‐run test. Meeting 24‐h movement guidelines was defined as: 9–11 h/day (children aged 5–13) or 8–10 h/day (adolescents aged 14–17) of sleep, ≤2 h/day of recreational screen time and at least 60 min/day of moderate‐to‐vigorous physical activity. The probability of having a high/very high score for each physical fitness components (i.e., ≥60th centile according to the normative cut‐off points for European adolescents) in relation to adherence to 24‐h movement guidelines was analyzed using a series of binary logistic regressions.
Results
Participants who met the three 24‐h movement guidelines were more likely to have high/very high for cardiorespiratory fitness (OR = 3.31; 95% CI: 1.79, 6.14; p < 0.001), standing long jump (OR = 1.91; 95% CI: 1.06, 3.45; p = 0.031), muscular fitness (OR = 2.05; 95% CI: 1.09, 3.86; p = 0.048) and physical fitness (OR = 1.99; 95% CI: 1.08, 3.66; p = 0.012), but not for handgrip strength (OR = 1.15; 95% CI: 0.64, 2.01; p = 0.636) and speed/agility (OR = 1.65; 95% CI: 0.92, 2.96; p = 0.093), compared to those who did not meet all three recommendations.
Conclusion
Since meeting the three 24‐h movement guidelines increased the likelihood of having higher levels in most physical fitness components, it seems necessary to promote these movement behaviors early in life, as they could serve as a gateway for improving health‐related fitness in future generations.
In response to the coronavirus disease 2019 (Covid-19) world pandemic, affected countries such as Spain enacted measures comprising compulsory confinement as well as restrictions regarding free ...movement. Such measures likely influence children's and adolescents' lifestyles. Our study aimed to investigate the impact that the Covid-19 confinement has on health-related behaviors (HRBs) among Spanish children and adolescents. An online survey was administered to 516 parents to collect data about 860 children and adolescents (49.2% girls) aged between 3 and 16 years in relation to physical activity, screen exposure, sleep time, and fruit and vegetable consumption during the Covid-19 confinement. Respectively,
t
-paired test and
t
-test between groups served to check differences between HRBs levels before and during the confinement as well as between strict and relaxed confinement. Significant differences were found for a reduction of weekly minutes of physical activity during the confinement (−102.5,
SD
159.6) (
p
< 0.001), an increase of daily hours of screen exposure (2.9,
SD
2.1) (
p
< 0.001), and a reduction of daily fruit and vegetable consumption (−0.2,
SD
1.6) (
p
< 0.001). Sleep time showed a significant difference between strict and relaxed confinement (−0.3,
SD
0.1) (
p
< 0.05), whereas binomial logistic regression adjusted for covariates (age, sex, education of the parents, siblings, current condition, exposure to Covid-19, and previous health risk behavior) showed significantly lower odds for screen exposure risk behavior with relaxed confinement (OR 0.60, 95%CI 0.40–0.91). The present study suggests that Covid-19 confinement reduced physical activity levels, increased both screen exposure and sleep time, and reduced fruit and vegetable consumption. Therefore, most HRBs worsened among this sample of Spanish children and adolescents. Closure of schools, online education, and the lack of policies addressing the conciliation between labor and family life could have played an important role in HRBs worsening among pupils, which might be mitigated with adequate conciliation policies, parental guidance, and community support.
This study was designed to determine whether participation in a single, one-hour focus group would spur a change in health-related behavior. All the respondents were teachers who had participated in ...a focus group designed to learn about teachers’ understanding that voice is a working tool. In the discussions, health-related behaviors were discussed as ways to deal with possible vocal strain or injury. Two months later, a follow-up survey was distributed to these participants asking them if they recalled the discussion and if they had sought out more information and/or had changed their vocal behavior due to their participation in the focus group. The qualitative data shows that the majority of these respondents both recalled the messages and had engaged in some type of health-related behavior change due to their participation in the focus group. Behavior change included such modifications as drinking more water and use of voice-amplification equipment in the classroom. Implications of this finding are discussed. (words = 157)
INTRODUCTION
Many lifestyle factors have been associated with dementia, but there is limited evidence of how these group together. The aim of this study was to examine the clustering of lifestyle ...behaviors and associations with dementia.
METHODS
This population‐based study included 9947 older Australian women. Latent class analysis was employed to identify distinct lifestyle classes, and Cox proportional hazard regression compared these with incident dementia over 17 years.
RESULTS
Three classes were identified: (1) “highly social and non‐smokers” (54.9%), (2) “highly social, smokers, and drinkers” (25.1%), and (3) “inactive and low socializers” (20.0%). Women in Class 3 exhibited a higher risk of dementia compared to both Class 1 (hazard ratio HR = 1.19, 95% confidence interval CI: 1.08 to 1.30) and Class 2 (HR = 1.12, 95% CI: 1.00 to 1.25).
DISCUSSION
A lifestyle pattern characterized by physical inactivity and low social engagement may be particularly detrimental for dementia risk in older women and should be prioritized in preventive strategies.
Highlights
Latent class analysis was employed to identify distinct lifestyle clusters.
Three lifestyle‐related clusters were differentially associated with dementia risk.
Inactive and low socializers exhibited the greatest risk of dementia.
Targeting physical inactivity and low social engagement in prevention is vital.
Abstract The World Health Organization has produced a multimedia, interactive online report entitled Health for the World's Adolescents: A Second Chance in the Second Decade . The report provides an ...overview of global and regional estimates of adolescent mortality and disability-adjusted life years, disaggregated by age, sex, and cause, and country-level data on health-related behaviors and conditions among adolescents. It outlines the reasons why adolescence is a unique period in the life course requiring special attention and synthesizes current thinking about the determinants that underlie the differences in health status between adolescents. For the first time, this new report pulls together recommendations and guidance from across the World Health Organization relating to interventions directed to a range of priority health problems, including use of alcohol and other psychoactive substances, AIDS, injuries, mental health, nutrition, sexual and reproductive health, tobacco use, and violence, focusing on four core functions of the health sector: supportive policies, service provision, strategic information, and working with other sectors. The report concludes with 10 key actions that would strengthen national responses to adolescent health, and outlines the approaches that are needed to overcome the obstacles to accelerating evidence-informed actions to improve the health of adolescents worldwide—with all the benefits that this will have for public health in the present and across the life course, for this generation and the next.
Mass lockdowns are a powerful infection‐reduction strategy but are a significant stressor. This study aimed to explore whether various factors known to predict distress in normal contexts (e.g. ...social connectedness, emotional‐regulation strategies, and health‐related behaviors) are associated with daily distress under lockdown conditions. A time‐based diary study evaluated how perceived social connectedness, health‐promoting, and risk behaviors predicted within‐person and between‐person psychological distress. One hundred and nine adults completed surveys on these variables daily for 15 days while under stringent COVID‐19 lockdown in Colombia. Emotional suppression and reappraisal were measured at the start of the study to explore whether they predicted distress. Distress was lower on the days that people experienced greater social connectedness (within‐person analyses) but was not significantly predicted by between‐participant differences in emotional regulation. Health‐promoting behaviors such as exercising and meaningful activity were associated with lower distress, while watching COVID‐19 news and eating high‐calorie food were associated with higher distress. Looking at individual dynamics provides meaningful insights on daily behaviors associated with distress that might improve people's wellbeing during lockdown, such as social connectedness, meaningful activity, nutrition, exercise, and minimizing news exposure. Future research with alternative designs will enable causal conclusions to be drawn.
Abstract
Background
The influence of individual and home neighborhood socioeconomic status (SES) on health-related behaviors have been widely studied, but the majority of these studies have neglected ...the possible impact of the workplace neighborhood SES.
Objective
To examine within-individual associations between home and work place neighborhood SES and health-related behaviors in employed individuals.
Methods
We used participants from the Swedish Longitudinal Occupational Survey of Health who responded to a minimum of two surveys between 2012 and 2018. Data included 12,932 individuals with a total of 35,332 observations. We used fixed-effects analysis with conditional logistic regression to examine within-individual associations of home, workplace, as well as time-weighted home and workplace neighborhood SES index, with self-reported obesity, physical activity, smoking, excessive alcohol consumption, sedentary lifestyle, and disturbed sleep.
Results
After adjustment for covariates, participants were more likely to engage in risky alcohol consumption when they worked in a workplace that was located in the highest SES area compared to time when they worked in a workplace that was located in the lowest SES area (adjusted odds ratios 1.98; 95% confidence interval: 1.12 to 3.49). There was an indication of an increased risk of obesity when individuals worked in the highest compared to the time when they worked in the lowest neighborhood SES area (1.71; 1.02–2.87). No associations were observed for the other outcomes.
Conclusion
These within-individual comparisons suggest that workplace neighborhood SES might have a role in health-related behaviors, particularly alcohol consumption.
Comparing an individual to his/herself at two time points suggested that workplace neighborhood SES has a role in health-related behaviors, particularly in risky alcohol consumption
With widespread use of the internet and mobile devices, many people have gained improved access to health-related information online for health promotion and disease management. As the health ...information acquired online can affect health-related behaviors, health care providers need to take into account how each individual's online health literacy (eHealth literacy) can affect health-related behaviors.
To determine whether an individual's level of eHealth literacy affects actual health-related behaviors, the correlation between eHealth literacy and health-related behaviors was identified in an integrated manner through a systematic literature review and meta-analysis.
The MEDLINE, Embase, Cochrane, KoreaMed, and Research Information Sharing Service databases were systematically searched for studies published up to March 19, 2021, which suggested the relationship between eHealth literacy and health-related behaviors. Studies were eligible if they were conducted with the general population, presented eHealth literacy according to validated tools, used no specific control condition, and measured health-related behaviors as the outcomes. A meta-analysis was performed on the studies that could be quantitatively synthesized using a random effect model. A pooled correlation coefficient was generated by integrating the correlation coefficients, and the risk of bias was assessed using the modified Newcastle-Ottawa Scale.
Among 1922 eHealth literacy-related papers, 29 studies suggesting an association between eHealth literacy and health-related behaviors were included. All retrieved studies were cross-sectional studies, and most of them used the eHealth Literacy Scale (eHEALS) as a measurement tool for eHealth literacy. Of the 29 studies, 22 presented positive associations between eHealth literacy and health-related behaviors. The meta-analysis was performed on 14 studies that presented the correlation coefficient for the relationship between eHealth literacy and health-related behaviors. When the meta-analysis was conducted by age, morbidity status, and type of health-related behavior, the pooled correlation coefficients were 0.37 (95% CI 0.29-0.44) for older adults (aged ≥65 years), 0.28 (95% CI 0.17-0.39) for individuals with diseases, and 0.36 (95% CI 0.27-0.41) for health-promoting behavior. The overall estimate of the correlation between eHealth literacy and health-related behaviors was 0.31 (95% CI 0.25-0.34), which indicated a moderate correlation between eHealth literacy and health-related behaviors.
Our results of a positive correlation between eHealth literacy and health-related behaviors indicate that eHealth literacy can be a mediator in the process by which health-related information leads to changes in health-related behaviors. Larger-scale studies with stronger validity are needed to evaluate the detailed relationship between the proficiency level of eHealth literacy and health-related behaviors for health promotion in the future.
Despite the large volume of research dedicated to health-related behavior change, chronic disease costs continue to rise, thus creating a major public health burden. Health literacy, the ability to ...seek, understand, and utilize health information, has been identified as an important factor in the course of chronic conditions. Little research has been conducted on the relationship between health literacy and health-related behaviors and health status in elderly Chinese. The aim of this study was to elucidate the relationship between health literacy and health-related behaviors and health status in China.
The subjects enrolled in this study were selected based on a stratified cluster random sampling design. Information involving >4500 older adults in 44 pension institutions in Urumqi, Changji, Karamay, and Shihezi of Xinjiang between September 2011 and June 2012 was collected. The Chinese Citizen Health Literacy Questionnaire (China Health Education Centre, 2008) and a Scale of the General Status were administered and the information was obtained through face-to-face inquiries by investigators. A total of 1452 respondents met the inclusion criteria. A total of 1452 questionnaires were issued and the valid response rate was 96.14% (1396 of 1452). Factors affecting health literacy and the relationship to health literacy were identified by one-way ANOVA and a multiple linear regression model.
The average health literacy level of the elderly in nursing homes was relatively low (71.74 ± 28.35 points). There were significant differences in the health literacy score among the factors of age, gender, race, education level, household income, marital conditions, and former occupation (p < 0.001). The health literacy score was significantly associated with smoking, drinking, physical exercise, and health examination (p < 0.001). The elderly with higher health literacy scores were significantly less likely to have risky behaviors (smoking, regular drinking, and lack of physical exercise), and in turn significantly more likely to undergo health examinations regularly, report good self-rated health, and significantly more likely to access sufficient health information from multiple sources (p < 0.001). No differences were noted between the health literacy score and BMI (p > 0.05). Multiple linear regression analysis showed that the independent influencing factors of health literacy included education level, race, former occupation, household income, age, physical exercise, health examination, smoking, and health information access (p < 0.001).
Health literacy was significantly associated with health-related behaviors in elderly Chinese. Further longitudinal studies are needed to help confirm that improving health literacy in the elderly may be effective in changing health-related behaviors. To reduce risky habits, educational interventions to improve health literacy should be simultaneously conducted in health promotion work.
Continued smoking following myocardial infarction (MI) is strongly associated with increased morbidity and mortality. Patients who continue to smoke may also engage in other behaviors that exacerbate ...risk. This study sought to characterize the risk profile of a national sample of individuals with previous MI who currently smoke. Data were taken from the 2017 Behavioral Risk Factor Surveillance Survey (United States), with 4.2% of the sample reporting a past MI (N = 26,004). Participants were classified by smoking status (current/former/never) and compared on medical comorbidities and the clustering of modifiable behaviors relevant for secondary prevention (smoking, poor nutrition, problematic alcohol use, physical inactivity, medication adherence). Current smokers were more likely to report other comorbidities including stroke, chronic obstructive pulmonary disease, physical limitations, and poor mental health. Smokers were also less likely to report taking blood pressure and cholesterol medications, and less likely to attend cardiac rehabilitation (examined in a subset of the sample, N = 2181). Current smoking remained an independent predictor of other health-related behaviors even when controlling for age, sex, race, educational attainment, and other comorbidities. In the modifiable risk-factor behavior cluster analysis, the most common pattern among current smokers was having two risk factors, smoking plus one additional risk factor, whereas the most common pattern was zero risk factors among never or former-smokers. Physical inactivity was the most common additional risk factor across smoking statuses. Current smoking is associated with multiple comorbidities and should be considered a marker for a high-risk behavioral profile among patients with a history of MI.
•Many patients continue to smoke after having a myocardial infarction (MI).•People who smoke after an MI also have other adverse cardiac risk factors•People who smoke after MI likely need to change multiple unhealthy behaviors.
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