Clustering of Modifiable Behavioral Risk Factors and Their Association with All-Cause Mortality in Taiwan's Adult Population: a Latent Class Analysis

Predicting future vaccination habits: The link between influenza vaccination patterns and future vaccination decisions among old aged adults in China

BACKGROUND

Annual influenza vaccination is crucially recommended for the elderly to maintain humoral immunity. Insufficient coverage requires us to understand the determinants of their influenza behaviors and how these patterns impact vaccination choices.

METHODS

Data from 540 Beijing residents aged over 65 were collected through interviews, capturing vaccination history and sociodemographic details. Individual influenza vaccination records from 2016 to 2020 were obtained from China's Immunization Information Systems. A latent class model identified three vaccination patterns. Multinomial logistic regression assessed relative risk ratios (RRRs) for vaccination based on sociodemographic factors. Vaccination patterns were used to predict future vaccination likelihood.

RESULTS

The analysis revealed three groups: sporadically vaccinated (63.33%), occasionally vaccinated (18.71%), and frequently vaccinated (17.96%). Factors associated with frequent vaccination included age over 70 (RRR = 2.81), lower income (RRR = 0.39), higher vaccine hesitancy (RRR = 3.10), multiple chronic conditions (RRR = 2.72), and rural residence (RRR = 2.48). The frequently vaccinated group was more likely to sustain regular vaccination habits in subsequent years compared to the occasionally vaccinated group.

CONCLUSIONS

Only 17.96% of Beijing's older population exhibited a consistent influenza vaccination pattern. Older age, rural residency, and chronic diseases correlated with repeated influenza vaccination. Segmenting the population based on past vaccination behavior can aid in designing targeted interventions to improve vaccination rates.

Co-occurrence of behavioural risk factors for non-communicable diseases among 40-year and above aged community members in three regions of Myanmar

Background

Risky behaviours such as smoking, alcohol consumption, physical inactivity and inadequate consumption of fruits and vegetables are known contributing factors for non-communicable diseases (NCDs) which account for 74% of global mortality. Such behavioural risk factors co-occur frequently resulting in synergistic action for developing NCD related morbidity and mortality. This study aims to assess the existence of multiple risk behaviours and determine the socio-economic and demographic factors associated with co-occurrence of behavioural risks among Myanmar adult population.

Method

Data were collected, in the context of the SUNI-SEA project (Scaling Up NCD interventions in Southeast Asia), from 660 community members aged 40 years and above of both sexes, residing in selected urban and rural areas from Ayeyawaddy, Yangon and Mandalay regions of Myanmar. The co-occurrence of behavioural risk factors was presented as percentage with 95% CI and its determinants were identified by multinomial logistic regression.

Results

The co-occurrence of two risk behaviours and three or four risk behaviours were found in 40% (95% CI: 36.2%, 43.9%) and 10.8% (95% CI: 8.5%, 13.4%) respectively. Urban residents, men, participants without formal schooling and unemployed persons were more likely to exhibit co-occurrence of two risk behaviors and three or four risk behaviours.

Conclusion

The current study shows high prevalence of co-occurrence of behavioural risk factors among Myanmar adults in the study area. NCD prevention and control programs emphasizing management of behavioural risks should be intensively promoted, particularly directed towards multiple behavioural risk factors, and not focused on individual factors only.

Clustering of health risk behaviors in pregnant individuals: Data from the Brazilian risk factor surveillance system for non-communicable chronic diseases

OBJECTIVE

To investigate the clustering of health risk behaviors (HRB) and its association with demographics, physical exercise, overweight, perception of health, and diseases in Brazilian pregnant people.

STUDY DESIGN

This is a cross-sectional study using data from the Risk Factor Surveillance System for Non-communicable Chronic Diseases by Telephone Survey (VIGITEL), the main health survey in Brazil.

METHODS

We used data on fruit and vegetable consumption, TV time, tobacco, and alcohol abuse in individuals who reported being pregnant (n = 4553). We used latent class analysis to identify optimal HRB clustering among participants. Multinomial regression (odds ratio [OR] and 95% confidence intervals [95%CI]) was applied to identify factors associated with HRB cluster.

RESULTS

Three clustering classes were identified: "without HRB cluster" (i.e., least unhealthy behaviors) (n = 2402, 52,8%), "moderate HRB cluster" (n = 1983, 43,5%), and "high HRB cluster" (i.e., most unhealthy behaviors) (n = 168, 3,7%). Pregnant people aged 35-50 years (OR = 1.89, 95%CI = 1.01; 3.52) who did not practice physical exercise (OR = 1.94, 95%CI 1.11; 3.39) were more likely to be classified as "high HRB cluster". Participants with 9-11 years (OR = 0.11, 95%CI = 0.07; 0.17) and ≥ 12 (OR = 0.05, 95%CI = 0.02; 0.11) years of education had a lower likelihood of being in the "high HRB cluster".

CONCLUSION

Three HRB clustering patterns were found in this study. Greater maternal age, low education, and absence of physical exercises increased the chances of being in the high HRB cluster group. Participants with higher educational levels were less likely to be in the High HRB cluster.

Intersection of Perceived COVID-19 Risk, Preparedness, and Preventive Health Behaviors: Latent Class Segmentation Analysis

Background

COVID-19 risk perception is a factor that influences the pandemic spread. Understanding the potential behavioral responses to COVID-19, including preparedness and adoption of preventive measures, can inform interventions to curtail its spread.

Objective

We assessed self-perceived and latent class analysis (LCA)-based risks of COVID-19 and their associations with preparedness, misconception, information gap, and preventive practices among residents of a densely populated city in Nigeria.

Methods

We used data from a cross-sectional survey conducted among residents (N=140) of Onitsha, Nigeria, in March 2020, before the government-mandated lockdown. Using an iterative expectation-maximization algorithm, we applied LCA to systematically segment participants into the most likely distinct risk clusters. Furthermore, we used bivariate and multivariable logistic regression models to determine the associations among knowledge, attitude, preventive practice, perceived preparedness, misconception, COVID-19 information gap, and self-perceived and LCA-based COVID-19 risks.

Results

Most participants (85/140, 60.7%) had good knowledge and did not perceive themselves as at risk of contracting COVID-19. Three-quarters of the participants (102/137, 74.6%; P<.001) experienced COVID-19-related information gaps, while 62.9% (88/140; P=.04) of the participants had some misconceptions about the disease. Conversely, most participants (93/140, 66.4%; P<.001) indicated that they were prepared for the COVID-19 pandemic. The majority of the participants (94/138, 68.1%; P<.001) self-perceived that they were not at risk of contracting COVID-19 compared to 31.9% (44/138) who professed to be at risk of contracting COVID-19. Using the LCA, we identified 3 distinct risk clusters (P<.001), namely, prudent or low-risk takers, skeptics or high-risk takers, and carefree or very high-risk takers with prevalence rates (probabilities of cluster membership that represent the prevalence rate [γc]) of 47.5% (95% CI 40%-55%), 16.2% (95% CI 11.4%-20.9%), and 36.4% (95% CI 28.8%-43.9%), respectively. We recorded a significantly negative agreement between self-perceived risk and LCA-based segmentation of COVID-19 risk (κ=-0.218, SD 0.067; P=.01). Knowledge, attitude, and perceived need for COVID-19 information were significant predictors of COVID-19 preventive practices among the Onitsha city residents.

Conclusions

The clustering patterns highlight the impact of modifiable risk behaviors on COVID-19 preventive practices, which can provide strong empirical support for health prevention policies. Consequently, clusters with individuals at high risk of contracting COVID-19 would benefit from multicomponent interventions delivered in diverse settings to improve the population-based response to the pandemic.

Association between clustering of unhealthy behaviors and depressive symptom among adolescents in Taiwan: A nationwide cross-sectional survey

Background

Among Taiwanese adolescents, how the clustering of unhealthy behaviors, including insufficient physical activity, screen-based sedentary behavior and frequent sugar-sweetened beverage consumption affecting depressive symptom remains unclear. This study aims to examine the cross-sectional association between clustering of unhealthy behaviors and depressive symptom.

Methods

We analyzed 18,509 participants from the baseline survey of the Taiwan Adolescent to Adult Longitudinal Survey in 2015. The outcome was depressive symptoms, and the main exposures were insufficient physical activity, screen-based sedentary behaviors and frequent sugar-sweetened beverage consumption. Generalized linear mixed models were performed to find key factor associated with depressive symptom.

Results

Depressive symptoms were common among participants (31.4%), particularly in female and older adolescents. After adjustments for covariates including sex, school type, other lifestyle factors and social determinants, individuals exhibiting clustering of unhealthy behaviors were more likely (aOR = 1.53, 95% CI: 1.48–1.58) to exhibit depressive symptoms than those who have no or only one unhealthy behavior.

Conclusions

Clustering of unhealthy behaviors is positively associated with depressive symptom among Taiwanese adolescents. The findings highlight the importance of strengthening public health interventions to improve physical activity and decrease sedentary behaviors.

Health behavior interventions for university students measuring mental health outcomes: A scoping review

Introduction

Many university students have poor mental health, and co-occurring health risk behaviors. Targeting health behavior change in this population may improve mental health outcomes. This scoping review describes the extent and range of randomized controlled trials (RCT) evaluating interventions targeting health risk behaviors and measuring a mental health outcome, among university students.

Methods

Six electronic databases were searched for RCTs published until the 18^th May 2021. Eligible RCTs included university students, evaluated interventions that promoted health behavior change (i.e., dietary intake, physical activity, sedentary behavior, alcohol and drug use, smoking, and sleep), and measured a mental health-related outcome.

Results

Fifty-nine RCTs met the inclusion criteria that were published from 2000 to 2021, and over half (n = 33) were conducted in the United States. Interventions evaluated within the RCTs (n = 92) predominantly targeted changes to dietary intake (n = 41 interventions), physical activity (n = 39), or alcohol intake (n = 35). Most interventions targeted one (n = 51) or two (n = 27) health behaviors only. Included RCTs considered mental ill health outcomes (n = 24), psychological wellbeing outcomes (n = 20), or both (n = 15).

Discussion

This scoping review identified a moderate volume of experimental research investigating the impact of health behavior interventions on university students' mental health. There is scope for further research examining health behavior interventions targeting university students, particularly interventions taking a multi-behavioral approach.