A cross-sectional survey and latent class analysis of the prevalence and clustering of health risk factors among people attending an Aboriginal Community Controlled Health Service

Lifestyle patterns, nutritional, and metabolic syndrome determinants in a sample of the older Iranian population

BACKGROUND

Chronic diseases and metabolic disorders are prevalent health concerns that often escalate with increasing age and thus affect older individuals. The proportion of the elderly population in Iran increased from 7.22% in 2006 to 12.0% in 2023. The current study aimed to evaluate lifestyle patterns and lifestyle risk factors among patients with metabolic syndrome (MetS) based on dietary, physical activity, and smoking, as well as MetS components.

METHODS

This cross-sectional study included 582 older people with MetS living in Yazd, Iran. Latent class analysis (LCA) was used to determine the lifestyle behaviors of diet patterns, smoking, and physical activity. Dietary intake was measured using a validated food frequency questionnaire, and dietary patterns were identified using principal component analysis (PCA). Clinical measurements of MetS components were examined using relevant guidelines.

RESULTS

The mean age of the participants was 72.71 years (SD = 5.57). Using PCA, two dietary patterns were identified: traditional patterns (e.g., fruits, fish, poultry, vegetables, meats, salt, and sugar sweetened beverages) and high-fat patterns (e.g., high-fat dairy). Applying LCA identified two classes of lifestyle patterns. About 35% (n = 204) of the participants were categorized in a low-risk class (I) and characterized by physical activity (0.93%, n = 190), a traditional pattern for diet (61%, n = 122), and zero probability of smoking. About 65% (n = 378) of the patients were categorized in high-risk class (II) and characterized by low physical activity levels (69%, n = 261), cigarette smoking (71.6%, n = 271), and a high-fat dietary pattern (56.9%, n = 215).

CONCLUSION

The results of our study indicated two distinct classes within the patients. In class I, aging patients with MetS exhibited characteristics such as engagement in physical activity and having a traditional pattern for diet. Class II, with a higher prevalence of lifestyle risk factors, included individuals who engaged in cigarette smoking, displayed low physical activity (69%), and having a high-fat diet. The combination of these lifestyle factors exposed them to a heightened risk of developing MetS. The findings could guide healthcare professionals to be aware of the associations between different lifestyle risk factors and to focus on multiple behaviors at the same time.

Health risk factors in Australian Stroke Survivors: A latent class analysis

ISSUES ADDRESSED

To (i) determine the prevalence of health risk factors (physical activity, diet, alcohol, smoking, blood pressure medication use and mental health) in community-dwelling stroke survivors; and (ii) examine how these health risk factors cluster, and identify associations with physical functioning, independent living, or sociodemographic factors.

METHODS

A secondary analysis of data obtained during a national randomised controlled trial. Participants had experienced stroke and completed a baseline telephone survey on demographic and stroke characteristics, health risk factors, physical functioning and independence in activities of daily living. A latent class analysis was performed to determine health risk profiles. Univariate logistic regressions were performed to identify if participant characteristics were associated with resulting classes.

RESULTS

Data analysed from 399 participants. Two classes of health risk factors were identified: Low Mood, Food & Moves Risk (16% of participants) and Alcohol Use Risk (84% of participants). The Low Mood, Food & Moves Risk group had poorer diet quality, lower physical activity levels and higher levels of depression and anxiety. Lower levels of independence and physical functioning were predictor variables for this group. In contrast, the Alcohol Use Risk group had better physical activity and diet scores, significantly lower probability of depression and anxiety, but a higher probability of risky drinking.

CONCLUSIONS

We identified two distinct health risk factor groups in our population. SO WHAT?: Future interventions may benefit from targeting the specific needs and requirements of people who have experienced stroke based on their distinct risk group. Alcohol consumption in poststroke populations requires further attention.

Patterns of Risky Health Behaviors and Associations With Chronic Diseases Among Young Adult Nursing Students: A Latent Class Analysis

BACKGROUND

Little is known about how health behaviors cluster to form meaningful patterns that influence health outcomes in young adult nursing students.

PURPOSE

The purpose of this study was to identify the unique health behavior patterns among young adult nursing students in China and examine the associations between health behaviors and chronic diseases.

METHODS

Using an electronic app, the achievements of an exercise target, sedentary behavior, smoking and drinking, and dietary patterns were assessed in 1,480 nursing student participants aged 18-24 years from two medical universities in Eastern China.

RESULTS

A four-class model was developed using latent class analysis that included the "failure to achieve exercise target, alcohol-drinking, and insufficient fruit and vegetable group" (Group 1, n = 187, 12.6%), the "alcohol-drinking and sedentary behavior group" (Group 2, n = 290, 19.6%), the "sedentary behavior only group" (Group 3, n = 721, 48.7%), and the "failure to achieve exercise target only group" (Group 4, n = 282, 19.1%). Logistic regressions indicated that nursing students in Group 2 (odds ratio [ OR ] = 0.42), Group 3 ( OR = 0.51), and Group 4 ( OR = 0.30) were less likely to have chronic diseases than those in Group 1 after adjusting for sociodemographic variables.

CONCLUSIONS

The health behaviors were clustered in different patterns among young adult nursing students. Tailoring interventions to specific groups is suggested to improve health outcomes.

Clustering of multiple health-risk factors among vocational education students: a latent class analysis

Physical and mental health risks often commence during young adulthood. Vocational education institutions are an ideal setting for understanding how health-risks cluster together in students to develop holistic multiple health-risk interventions. This is the first study to examine clustering of tobacco smoking, fruit intake, vegetable intake, alcohol consumption, physical inactivity, overweight/obesity, depression, and anxiety in vocational education students and the socio-demographic characteristics associated with cluster membership. A cross-sectional survey with vocational education students (n = 1134, mean age = 24.3 years) in New South Wales, Australia. Latent class analysis identified clusters and latent class regression examined characteristics associated with clusters. Four clusters were identified. All clusters had moderate inadequate fruit intake and moderate overweight/obesity. Cluster 1 (13% of sample) had "high anxiety, high inadequate vegetable intake, low tobacco, and low alcohol use." Cluster 2 (16% of sample) had "high tobacco smoking, high alcohol use, high anxiety, high depression, and high inadequate vegetable intake." Cluster 3 (52% of sample) had "high risky alcohol use, high inadequate vegetable intake, low depression, low anxiety, low tobacco smoking, and low physical inactivity." Cluster 4 (19% of sample) was a "lower risk cluster with high inadequate vegetable intake." Compared to cluster 4, 16-25-year-olds and those experiencing financial stress were more likely to belong to clusters 1, 2, and 3. Interventions for vocational education students should address fruit and vegetable intake and overweight/obesity and recognize that tobacco use and risky alcohol use sometimes occurs in the context of mental health issues.

Clustering of multiple health risk behaviours and association with socio-demographic characteristics and psychological distress among adolescents in Ghana: A latent class analysis

This study examined the prevalence of multiple health risk behaviours, the clustering patterns of health risk behaviours, the association between socio-demographic characteristics, psychological distress and clusters and the relationship between number of health risk behaviours and psychological distress among adolescents in Ghana. Participants were senior high school (SHS) students aged 11-19 years who participated in the 2012 Global School-based Students Health Survey (n = 1763). Five health risk behaviours (smoking tobacco, inadequate fruit intake, inadequate vegetable intake, alcohol intake and physical inactivity) were measured. Participants were classified to be at risk if they indicated they smoked tobacco, did not eat fruit ≥ 2 times a day and vegetables ≥ 5 a day, drank alcohol during the past 30 days and did not engage in physical activity for ≥ 60 min per day during the past 7 days. Latent class analysis and latent regression were used to identify the clusters and factors associated with the clusters respectively. Multiple logistic regression was used to determine the relationship between number of health risk behaviours and psychological distress. The prevalence of multiple health risk behaviours (2 or more) was 94.8%. Two clusters emerged: Cluster 1 ("Poor nutrition, inactive, low substance use cluster"; 91%); Cluster 2 ("High Risk Cluster"; 9%). Using cluster 1 as a reference group, adolescents in the 11-15 years category had lower odds of belonging to cluster 2 (OR = 0.21 CI 0.05-0.91, ρ = 0.036) while those experiencing symptoms of depression had higher odds of belonging to cluster 2 (OR = 2.45 CI 1.45-4.14, ρ = 0.001). No significant relationship was found between number of health risk behaviour and psychological distress. Health risk behaviours cluster among adolescents with age and depression associated with the identified clusters. Early interventions that target these clusters are needed at the individual, school and community level to mitigate the burden of non-communicable diseases.

An ecological model of drug and alcohol use and related harms among Aboriginal and Torres Strait Islander Australians: A systematic review of the literature

Globally, Indigenous populations experience a disproportionately higher burden of disease related to substance use. Effective prevention of harm related to substance use is a key strategy for improving the health and wellbeing of Aboriginal and Torres Strait Islander peoples in Australia. To inform preventative approaches, this review synthesised the evidence of risk and protective factors of substance use and related harms among Aboriginal and Torres Strait Islander peoples. Eight peer-reviewed and two grey literature databases were systematically searched for quantitative or qualitative studies assessing factors associated with substance use and related harms among Aboriginal and Torres Strait Islander peoples, published between 1 January 1990 and 30 April 2018. Study quality was assessed using validated instruments. Risk or odds ratios were extracted or calculated and factors were summarised in an ecological model into individual, relationship, community, societal or culturally-distinct levels. Thirty-eight relevant studies were identified and reviewed. Individual-level risk factors for substance use were identified including low socio-economic status, high psychological distress, poly drug use and being male. Relationship-level factors were peer pressure and partner/family substance use; protective factors were supportive environments and positive role models. Community-level risk factors included availability of substances. Culturally-distinct factors included cultural connection as a protective factor, but cultural obligations around sharing was a risk factor. Societal risk factors included intergenerational trauma caused by government policies. These findings highlight the importance of tailored preventative approaches for Aboriginal and Torres Strait Islander communities that address identified risk factors and promote protective factors across all ecological levels.

Characterizing Dietary Intakes in Rural Australian Adults: A Systematic Literature Review

Rural Australians experience a higher burden of diet-related chronic disease than their metropolitan counterparts. Dietary intake data is needed to understand priorities for nutrition initiatives that reduce disparities in the health of rural Australians. A systematic literature review aimed to synthesize the evidence on dietary intakes in adult populations residing in rural and remote Australia, to identify areas for intervention, and make recommendations for future research. A comprehensive search of five electronic databases was conducted and 22 articles were identified for inclusion. Half of the included studies (50%) collected dietary data using non-validated questionnaires and nearly half (41%) did not benchmark dietary intakes against public health guidelines. Most studies (95%) showed that rural populations have suboptimal dietary intakes. Despite the high level of preventable diet-related disease in rural and remote Australia, this review identified that there is insufficient high-quality dietary data available and a lack of consistency between dietary outcomes collected in research to inform priority areas for intervention. Further cross-sectional or longitudinal data should be collected across all remoteness areas, using robust, validated dietary assessment tools to adequately inform nutrition priorities and policies that reduce rural health disparities.

The relationship between lifestyle components and dietary patterns

We conducted a narrative review on the interaction between dietary patterns with demographic and lifestyle variables in relation to health status assessment. The food pattern has the advantage of taking into account the correlations that may exist between foods or groups of foods, but also between nutrients. It is an alternative and complementary approach in analysing the relationship between nutrition and the risk of chronic diseases. For the determination of dietary patterns one can use indices/scores that evaluate the conformity of the diet with the nutrition guidelines or the established patterns (a priori approach). The methods more commonly used are based on exploratory data (a posteriori): cluster analysis and factor analysis. Dietary patterns may vary according to sex, socio-economic status, ethnicity, culture and other factors, but more, they may vary depending on different associations between these factors. The dietary pattern exerts its effects on health in a synergistic way or even in conjunction with other lifestyle factors, and we can therefore refer to a 'pattern of lifestyle'.

Lifestyle patterns and their nutritional, socio-demographic and psychological determinants in a community-based study: A mixed approach of latent class and factor analyses

Background

Lifestyle risk factors, such as unhealthy diet, physical inactivity or tobacco smoking can have detrimental effects on health and well-being. Therefore, it is important to examine multiple lifestyle risk factors instead of single ones. Cluster analysis allows the combination of single health behaviors in order to recognize distinguished behavior patterns. This study aimed to evaluate lifestyle patterns of general adult population in northwest of Iran with particular focus on dietary patterns, physical activity, and smoking status.

Methods

The current cross-sectional study consists of 525 adults aged 18–64 years from East-Azarbaijan Iran. Latent class analysis (LCA) was applied to recognize patterns of lifestyle behaviors with ingredients of diet, physical activity, and smoking status. Dietary intake was assessed using a validated food frequency questionnaire and dietary patterns were derived using factor analysis. Biochemical parameters including fasting blood sugar (FBS), serum lipids, liver enzyme and serum 25(OH)-D3 were measured with commercial ELIZA kits.

Results

Mean ages of participants were 42.90 ± 11.89 years. Using principal component analysis (PCA) three major dietary patterns were extracted including traditional dietary pattern (e.g. nuts and dry fruits), unhealthy dietary pattern (e.g. fast foods, refined grains) and the healthy dietary patterns (e.g. fruits, vegetables). Using LCA, three classes of lifestyles pattern were identified: 1^st class was characterized by a healthy dietary pattern, moderate physical activity, and low probability of smoking. 2^nd class was characterized by a traditional dietary pattern, low level of physical activity and low probability of smoking and 3^rd class was characterized by a unhealthy dietary pattern, low level of physical activity and low probability of smoking and further analysis found that there were significant differences in body mass index (BMI), Waist-to-hip ratio (WHR), FBS, Hemoglobin (Hb), education levels and anxiety status between classes (P <0.05).

Conclusion

This study attempts to classify Iranian adults by their own health behavior. Healthcare professionals should be aware of associations between different lifestyle risk factors and health promotion strategies should further focus on multiple behaviors at the same time. In our country, more studies about the adult population are needed to support the observed findings of our study and therefore allow for a certain generalization of the observations.

Clustering of cardiovascular disease biological risk factors among older adults in Shenzhen City, China: a cross-sectional study

OBJECTIVES

Few studies reported the clustering of cardiovascular disease (CVD) biological risk factors among older adults. The objective of this study was to characterise the clustering of CVD biological risk factors among adults aged 65 or older in Shenzhen city, China.

DESIGN

Cross-sectional study.

SETTING

General communities in Shenzhen, Guangdong, China.

PARTICIPANTS

A representative sample of 5635 participants aged 65 or older participated in the survey with a response rate of 93.6%.

MAIN OUTCOME MEASURES

Individual CVD biological risk factors (overweight/obesity, central obesity, hypertension, dyslipidaemia and diabetes) and their clustering.

RESULTS

The prevalence of overweight, obesity, central obesity, hypertension, dyslipidaemia and diabetes in this study was 37.4%, 10.8%, 37.0%, 51.9%, 40.2% and 18.0%, respectively. The mean count of CVD biological risk factors per participant was 1.95. The 86.0% of the participants presented at least one CVD biological risk factor and 33.8% of the participants presented clustering of CVD biological risk factors, that is, presenting three or more CVD biological risk factors, as defined in this study. Multivariable logistic regression analysis showed that gender, age, and drinking and smoking status were significantly associated with clustering of CVD biological risk factors (P<0.05). Women, the older and alcohol drinkers were more likely to have clustering of CVD biological risk factors.

CONCLUSIONS

The prevalence of CVD biological risk factors is fairly high in the older adults with a tendency of clustering in Shenzhen. The findings highlight the need for integrated management of CVD biological risk factors among older adults.

Multiple health behaviours among mothers and partners in England: Clustering, social patterning and intra-couple concordance

Research on multiple health behaviours is increasing but little is known about parental behaviours and how they covary. Our study investigates cigarette smoking, alcohol intake, fruit and vegetable (F&V) consumption and physical activity among mothers and co-resident partners in England. Using the UK Household Longitudinal Study, we examined (i) clustering of health behaviours using observed-expected ratios and latent class analysis (ii) socio-demographic correlates of the derived latent classes and (iii) intra-couple concordance of individual health behaviours and their latent classes. We identified five latent classes for mothers and partners: Never smoked drinkers (28% of mothers; 29% of partners), Abstainers (25%; 17%), Drinkers and ex-smokers (19%; 26%), Unhealthy low frequency drinkers (18%; 16%) and Unhealthiest behaviour group (11%; 12%). These had distinctive social profiles. Never smoked drinkers were more likely than those in other groups to be white and socially advantaged: married, older, and with higher educational qualifications and incomes. Abstainers were non-smokers who never or occasionally drank, and were disproportionately drawn from ethnic minority groups and middle/lower income families. Drinkers and ex-smokers were the most physically active group and were more likely to be socially advantaged. Unhealthy low frequency drinkers were more likely to be disadvantaged and have a limiting long-standing illness. The Unhealthiest behaviour group had the highest proportion of smokers, heavy smokers and binge drinkers and the lowest F&V intake and physical activity levels. They were largely white and socially disadvantaged: younger, non-married and with lower educational levels. Mothers and their partners typically shared the same risk behaviours, and 44 per cent of partners and mothers belonged to the same latent class. Our findings point to the potential for a broadening of research and policy perspectives, from separate behaviours to combinations of behaviours, and from individuals to the domestic units and communities of which they are part.