Patterns of Diet, Physical Activity, Sitting and Sleep Are Associated with Socio-Demographic, Behavioural, and Health-Risk Indicators in Adults

Our understanding of how multiple health-behaviours co-occur is in its infancy. This study aimed to: (1) identify patterns of physical activity, diet, sitting, and sleep; and (2) examine the association between sociodemographic and health-risk indicators. Pooled data from annual cross-sectional telephone surveys of Australian adults (2015–2017, n = 3374, 51.4% women) were used. Participants self-reported physical activity, diet, sitting-time, sleep/rest insufficiency, sociodemographic characteristics, smoking, alcohol use, height and weight to calculate body mass index (BMI), and mental distress frequency. Latent class analysis identified health-behaviour classes. Latent class regression determined the associations between health-behaviour patterns, sociodemographic, and health-risk indicators. Three latent classes were identified. Relative to a ‘moderate lifestyle’ pattern (men: 43.2%, women: 38.1%), a ‘poor lifestyle’ pattern (men: 19.9%, women: 30.5%) was associated with increased odds of a younger age, smoking, BMI ≥ 30.0 kg/m2, frequent mental distress (men and women), non-partnered status (men only), a lower Socioeconomic Index for Areas centile, primary/secondary education only, and BMI = 25.0–29.9 kg/m2 (women only). An ‘active poor sleeper’ pattern (men: 37.0%, women: 31.4%) was associated with increased odds of a younger age (men and women), working and frequent mental distress (women only), relative to a ‘moderate lifestyle’ pattern. Better understanding of how health-behaviour patterns influence future health status is needed. Targeted interventions jointly addressing these behaviours are a public health priority.

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Did self‐reported tobacco smoking, alcohol consumption, and physical activity change during the COVID-19 restrictions in Germany in spring 2020? Findings from a population survey (the DEBRA study)

10.21203/rs.3.rs-479652/v1 ◽

2021 ◽

Author(s):

Stephanie Klosterhalfen ◽

Sabrina Kastaun ◽

Daniel Kotz

Keyword(s):

Physical Activity ◽

Alcohol Consumption ◽

Health Behaviour ◽

Tobacco Smoking ◽

Social Life ◽

Multinomial Logistic Regression ◽

German Population ◽

Sociodemographic Characteristics ◽

Cross Sectional ◽

Younger Age

Abstract Background Broad nationwide restrictions of social life and contacts were implemented in Germany on March 22nd, 2020, to reduce the spread of the severe acute respiratory syndrome coronavirus type 2 (SARS‑CoV‑2). It is unclear how these restrictions affected peoples’ health behaviour. Objective To: i) examine changes in self-reported health behaviour of the German population regarding tobacco smoking, alcohol consumption, and physical activity during the restrictions compared with the time prior to these restrictions; ii) explore associations between potential changes and socioeconomic and sociodemographic characteristics. Methods We used data from two waves (June-August 2020) of the German Study on Tobacco Use (DEBRA): a cross-sectional, representative, face-to‐face household survey in people aged ≥ 14 years (N = 4078). Associations between socioeconomic and sociodemographic characteristics and changes in each health behaviour were analysed using multinomial logistic regression analyses (categories of the dependent variable: increase, no change, decrease). Results People reported changes in their health behaviour: smoking increase = 24.0% (95% confidence interval (CI) = 21.5–26.7), decrease = 12.2% (95%CI = 10.4–14.4); alcohol consumption increase = 12.9% (95%CI = 11.7–14.1), decrease = 19.9% (95%CI = 18.4–21.3); physical activity increase = 18.5% (95%CI = 17.3–19.7); decrease = 29.4% (95%CI = 28.0–31.0). People with a lower level of education and younger age were more likely to report a harmful change in health behaviour. Conclusion The majority of people in Germany did not change their health behaviour during the 2020 corona restrictions. Among those who changed, relatively more increased their smoking and decreased their alcohol consumption and physical activity. Public health interventions in this context should particularly target people with lower socioeconomic status and younger age e.g., by offering more online courses.

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Lifestyle Clusters and Cardiometabolic Risks in Adolescents: A Chinese School-Based Study Using a Latent Class Analysis Approach

Frontiers in Pediatrics ◽

10.3389/fped.2021.728841 ◽

2021 ◽

Vol 9 ◽

Author(s):

Weiying Zhao ◽

Danyan Su ◽

Luxia Mo ◽

Cheng Chen ◽

Bingbing Ye ◽

...

Keyword(s):

Physical Activity ◽

Latent Class Analysis ◽

Latent Class ◽

Healthy Lifestyle ◽

Class Analysis ◽

Lifestyle Behaviors ◽

School Based ◽

Significant Difference ◽

Cardiometabolic Risks ◽

Lifestyle Pattern

Background: Unhealthy dietary and lifestyle behaviors are associated with a higher prevalence of non-communicable chronic diseases and higher mortality in adults. However, there remains some uncertainty about the magnitude of the associations between lifestyle behaviors and cardiovascular factors in adolescents.Methods: We conducted a school-based cross-sectional study of 895 Chinese adolescents aged 15–19 years. They participated in a questionnaire survey, physical examination, and blood sample collection. Latent class analysis (LCA) was used to identify heterogeneous subgroups of lifestyle behaviors. A set of 12 latent class indicators, which reflected lifestyle behaviors including dietary habits, physical activity, sleep duration, screen time, and pressure perception, were included in the analysis. Logistic regression analysis was performed to determine whether the derived classes were related to a cardiometabolic risk.Results: In total, 13.7 and 5.6% of the participants were overweight and obese, respectively, and 8.4 and 14.1% reported having pre-hypertension and hypertension, respectively. A two-class model provided the best fit with a healthy lifestyle pattern (65.8%) and a sub-healthy lifestyle pattern (34.2%). There were more female participants with a healthy lifestyle (56.2 vs. 43.8%), whereas there were more males with a sub-healthy lifestyle (45.4 vs. 54.6%), (all P = 0.002). Increased risk of cardiometabolic abnormality (BMI categories, blood pressure and lipids) was not significant across lifestyle patterns, except for waist circumference (70.5 vs 69.1 cm, P = 0.044). There was no significant difference in physical activity and intake of fruit and vegetable between the two patterns.Conclusion: Primary prevention based on lifestyle modification should target patterns of behaviors at high risk in adolescents. Due to the complex effect of lifestyle clusters on cardiometabolic risks, well-designed and prospective studies in adolescents are needed in the future.

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Association between allostatic load and health behaviours: a latent class approach

Journal of Epidemiology & Community Health ◽

10.1136/jech-2018-211289 ◽

2019 ◽

Vol 73 (4) ◽

pp. 340-345 ◽

Cited By ~ 5

Author(s):

Sarah N Forrester ◽

Jeannie-Marie Leoutsakos ◽

Joseph J Gallo ◽

Roland J Thorpe ◽

Teresa E Seeman

Keyword(s):

Physical Activity ◽

Blood Pressure ◽

Alcohol Use ◽

Health Behaviour ◽

Allostatic Load ◽

Latent Class ◽

Health Behaviours ◽

Biological Indicators ◽

Latent Class Regression ◽

Multiethnic Population

BackgroundAllostatic load (AL) has been characterised in many ways throughout the literature; however, its relationship to health behaviours has only been studied in limited populations. We aimed to uncover qualitative patterns of biological indicators in AL and determine if those patterns were associated with certain health behaviours.MethodsWe conducted latent class analysis using biological indicators from a multiethnic population. We fit latent class regression of class on health behaviours (smoking, poor diet, physical activity and alcohol use) to measure the association between each latent class of AL and each health behaviour.ResultsFour classes, ‘Metabolic+Cholesterol, ‘Blood Pressure’, ‘Metabolic+Blood Pressure’ and ‘Low’, were found in the sample. Latent class regression showed that physical activity and alcohol use were significantly associated with the ‘Metabolic+Blood Pressure’ class.ConclusionLess physical activity was required to improve AL than was previously found. Low to moderate alcohol use was beneficial for lower AL. Implications of the amount of physical activity necessary to lower AL is discussed.

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Lipid profile in men and women with different levels of sports participation and physical activity

Public Health Nutrition ◽

10.1017/s1368980007001425 ◽

2008 ◽

Vol 11 (11) ◽

pp. 1098-1106 ◽

Cited By ~ 3

Author(s):

Tineke Scheers ◽

Renaat Philippaerts ◽

Leen Van Langendonck ◽

William Duquet ◽

Nathalie Duvigneaud ◽

...

Keyword(s):

Physical Activity ◽

Energy Expenditure ◽

Lipid Profile ◽

Leisure Time ◽

Hdl Cholesterol ◽

Sports Participation ◽

Group Differences ◽

Men And Women ◽

Younger Age ◽

Active Leisure

AbstractObjectiveThe purpose of the present study was to analyse the lipid profile in men and women differentiated according to energy expenditure during sports participation (EESPORT), energy expenditure during active leisure time (EEALT) and overall energy expenditure (EETOTAL).DesignThe subjects were grouped by sex, age, EESPORT, EEALT and EETOTAL. Group differences were analysed using analyses of covariance with BMI and alcohol consumption as covariates.SettingPhysical activity was assessed using the Flemish Physical Activity Computerised Questionnaire. Fasting blood samples were taken to measure total cholesterol (TC), TAG, HDL-cholesterol (HDL-C), LDL-cholesterol (LDL-C) and the ratio TC:HDL-C.SubjectsThe study sample consisted of 1170 Flemish men and women between 18 and 75 years of age.ResultsDifferences in lipid profile were observed in the younger age group (<45 years), all in favour of the most active group. More specifically, when differentiating by EEALT and EETOTAL, men had a healthier lipid profile for TAG, HDL-C and TC:HDL-C. Differentiation according to EESPORT revealed the same significant results except for TAG. In women significant results for HDL-C, LDL-C and TC:HDL-C were found when differentiated by EESPORT.ConclusionsMen and women <45 years of age with higher levels of energy expenditure due to sport show a better lipid profile than their sedentary counterparts. When differentiating subjects according to energy expenditure during active leisure time or overall energy expenditure, only in men was a healthier lipid profile observed in favour of the most active subjects.

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Racial Disparities in Health Risk Indicators Reported by Alabamians Diagnosed with COPD

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18189662 ◽

2021 ◽

Vol 18 (18) ◽

pp. 9662

Author(s):

Michael Stellefson ◽

Min-Qi Wang ◽

Caitlin Kinder

Keyword(s):

Substance Use ◽

Health Insurance ◽

High Risk ◽

Health Risk ◽

Racial Disparities ◽

Latent Class ◽

Healthcare Access ◽

Public Health Problem ◽

Risk Indicators ◽

Risk Class

Chronic Obstructive Pulmonary Disease (COPD) is a growing public health problem in the southern United States, particularly in Alabama. However, very little is known about specific health risk factors disproportionately impacting Alabamians with COPD. We conducted a latent class analysis of 2015–2019 Behavioral Risk Factor Surveillance System data from 4057 Alabamians with COPD (White = 2947, Black = 873, Other = 237). Eighteen risk indicators were examined across three health-related domains: (1) comorbidities, (2) limited healthcare access, and (3) substance use/abuse. Racial disparities between Black and white Alabamians with COPD were assessed using configural similarity analysis. Findings showed that almost one-third (31%) of Alabamians with COPD were in the high-risk class for eight comorbidities, and nearly one-half (48.88%) belonged to the high-risk class for limited healthcare access. Black Alabamians with COPD who did not have health insurance were much more likely to be at high risk for limited healthcare access (94.44%) when compared to their counterparts with insurance (5.56%), χ2(df = 2) = 1389.94, p < 0.0001. Furthermore, the proportion of high-risk, uninsured Black Alabamians with COPD (94.44%) substantially exceeded the percentage of high-risk, uninsured white Alabamians with COPD (59.70%). Most Alabamians with COPD (82.97%) were at low risk for substance use/abuse. Future research should explore new mechanisms for facilitating better healthcare access among high-risk Alabamians living with COPD and other prevalent comorbidities. Greater attention should be focused on Black Alabamians with COPD who cannot afford adequate health insurance.

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Associations Between Short- and Long-Term Unemployment and Frequent Mental Distress Among a National Sample of Men and Women

Journal of Occupational and Environmental Medicine ◽

10.1097/01.jom.0000094994.09655.0f ◽

2003 ◽

Vol 45 (11) ◽

pp. 1159-1166 ◽

Cited By ~ 50

Author(s):

David W. Brown ◽

Lina S. Balluz ◽

Earl S. Ford ◽

Wayne H. Giles ◽

Tara W. Strine ◽

...

Keyword(s):

Mental Distress ◽

National Sample ◽

Men And Women ◽

Frequent Mental Distress ◽

Short And Long Term

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Clustering of health-related behaviours within children aged 11–16: a systematic review

BMC Public Health ◽

10.1186/s12889-020-10140-6 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Victoria Whitaker ◽

Melissa Oldham ◽

Jennifer Boyd ◽

Hannah Fairbrother ◽

Penny Curtis ◽

...

Keyword(s):

Physical Activity ◽

Substance Use ◽

Literature Search ◽

Latent Class ◽

Principal Component ◽

Risk Indicators ◽

Youth Health ◽

Substance Users ◽

Single Substance ◽

Health Related

Abstract Objective We aimed to systematically review and synthesise evidence on the clustering of a broad range of health-related behaviours amongst 11–16 year olds. Method A literature search was conducted in September 2019. Studies were included if they used cluster analysis, latent class analysis, prevalence odds ratios, principal component analysis or factor analysis, and considered at least three health-related behaviours of interest among 11–16 year olds in high-income countries. Health-related behaviours of interest were substance use (alcohol, cigarettes and other drug use) and other behavioural risk indicators (diet, physical activity, gambling and sexual activity). Results The review identified 41 studies, which reported 198 clusters of health-related behaviours of interest. The behaviours of interest reported within clusters were used to define eight behavioural archetypes. Some included studies only explored substance use, while others considered substance use and/or other health-related behaviours. Consequently, three archetypes were comprised by clusters reporting substance use behaviours alone. The archetypes were: (1) Poly-Substance Users, (2) Single Substance Users, (3) Substance Abstainers, (4) Substance Users with No/Low Behavioural Risk Indicators, (5) Substance Abstainers with Behavioural Risk Indicators, (6) Complex Configurations, (7) Overall Unhealthy and (8) Overall Healthy. Conclusion Studies of youth health behavioural clustering typically find both a ‘healthy’ cluster and an ‘unhealthy’ cluster. Unhealthy clusters are often characterised by poly-substance use. Our approach to synthesising cluster analyses may offer a means of navigating the heterogeneity of method, measures and behaviours of interest in this literature.

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