This suggests that the main effects of self-esteem on risk of coronary heart disease cannot solely be explained by an indirect pathway via health risk behaviors, but rather direct via effects on psychoneuroimmunological mechanisms [ 23 ]. One of the few studies investigating the relationship between self-esteem and health behaviors examined the number of cigarettes among smokers.
Self-esteem showed a negative correlation with the number of cigarettes. In particular, an interaction effect was found where males with lower self-esteem exhibited more positive beliefs about smoking compared to women [ 32 ]. In future studies, possible interaction effects of psychosocial factors and behavior-specific factors would be interesting to explore, as well as gender aspects. After controlling for the effects of all other psychosocial factors, trust was the only factor remaining statistically significant in the model.
As trust was the instrument showing the smallest correlations to other factors, this could indicate an independent role of trust; however, this needs to be further investigated. Evidence supporting the effect of trust was found in a recent analysis of this data on year coronary heart disease incidence where trust showed an independent effect data to be published. A strength of the study is the unique design of the LSH research program, which allowed for comprehensive analyses of multiple health risk behaviors and psychosocial factors due to the broad range of variables.
The well-characterized population-based sample also made it possible to adjust for known confounders. Although the statistical power of the study is a potential limitation, our findings consistently showed associations in the expected directions between health behaviors and psychosocial factors, with little indication that our conclusions or their generalizability would be affected by low power.
After multiple-comparison correction carried out according to the false discovery rate FDR , significance remained for eight out of nine factors. In these analyses, the risk of a type I error, associated with multiple testing, must be balanced toward the risk of a type II error, due to a too rigid analysis.
We do suggest that, after the abovementioned control, our main message remains. Our correlation analysis showed, as expected, that all the psychosocial factors do correlate. These correlation coefficients are, in general, low to moderate, with the largest r being 0. The theoretical base for these instruments differs and, in earlier studies, we demonstrated that the choice of measures matters [ 60 ].
However, our aim was not to assess the different measures in relation to one another examining, e. Moreover, most often one or two psychosocial factors are and can be included in different studies, whether population-based or clinical. We, therefore, find it important to demonstrate the results for each of these. Finally, an important limitation is the cross-sectional design. We cannot draw conclusions on the directions of these relationships; we, therefore, do not know whether health risk behaviors are a result of or contribute to the psychosocial situation.
Prospective studies are needed to assess the direction of associations. However, based on previous research, showing independent associations of psychosocial factors on the risk of disease [ 42 ], we do suggest that the main direction is the former, i. There is often a debate whether to focus on individual responsibility for behavior change or create structural conditions that promote and enable healthy lifestyles.
It is obvious that structural factors are important and must be targeted, for example, increasing the capacity for support from the social environment to enhance positive outcome expectancies and health. However, concurrently, empowerment strategies building on the ambition to enhance individual chances of developing positive expectancies, hopes, and trust are needed [ 63 ]. Our findings illustrate the importance of identifying vulnerable individuals with loss of coping in terms of vital exhaustion and depressiveness, especially in the case of multiple health risk behaviors.
Examining associations between a broad range of psychosocial factors and multiple health risk behaviors revealed consistent and significant associations for almost all psychosocial factors. These associations were more prominent compared to analyzing associations to single health risk behaviors.
Conceptualization, M. All authors have read and agreed to the published version of the manuscript. Author Margareta Kristenson is the principal investigator and recipient of these grants.
National Center for Biotechnology Information , U. Published online Feb Find articles by Kristin Thomas. Find articles by Evalill Nilsson. Find articles by Karin Festin. Find articles by Margareta Kristenson. Author information Article notes Copyright and License information Disclaimer. Received Dec 30; Accepted Feb This article has been cited by other articles in PMC.
Abstract Background : The health behaviors smoking, risky alcohol consumption, insufficient physical activity, and poor diet constitute the main contributors to non-communicable diseases.
Keywords: multiple health behaviors, psychosocial factors, lifestyle factors, health behavior change. Introduction The role of health behaviors in the development of the major non-communicable diseases, i.
Methods 2. Study Design, Population, and Procedure The present study is a part of the Life Conditions, Stress, and Health LSH research program, which aims to, prospectively, investigate the causes of socioeconomic status differences in the incidence of coronary heart disease CHD. Table 1 Demographic characteristics, health behaviors, and socioeconomic status of the study population. Open in a separate window. Table 2 Prevalence of health behaviors and their combinations.
Data 2. Health Behaviors Four health behaviors were investigated in the present study. Psychosocial Factors A broad range of validated psychosocial scales were used to measure psychosocial resources and psychological risk factors.
Table 3 Characteristics of psychosocial factors in the study population. Table 4 Correlation matrix for psychosocial factors. Demographic Data and Socioeconomic Status Age, sex, and socioeconomic status in terms of education, employment, and immigrant status were reported via the questionnaire. Statistical Data Analysis Health behaviors, psychosocial factors, and demographic data were described as numbers and percentages, means standard deviation, SD , or medians interquartile range.
Statement of Human Rights All procedures performed in the study were in accordance with the ethical standards of the regional research committee and with the Declaration of Helsinki and its subsequent amendments or comparable ethical standards. Informed Consent Written informed consent was obtained from all individual participants included in the study. Results Table 1 presents demographic characteristics, health behaviors, and socioeconomic status in the study population.
Table 5 Associations between health risk behaviors and psychosocial factors. Table 6 Relationships between psychosocial factors and number of health risk behaviors 0—1, 2, or 3—4. Discussion This study investigated the association between a broad range of psychosocial factors and multiple health behaviors in a population-based sample of Swedish middle-aged men and women. Methodological Considerations A strength of the study is the unique design of the LSH research program, which allowed for comprehensive analyses of multiple health risk behaviors and psychosocial factors due to the broad range of variables.
Implications for Practice There is often a debate whether to focus on individual responsibility for behavior change or create structural conditions that promote and enable healthy lifestyles. Conclusions Examining associations between a broad range of psychosocial factors and multiple health risk behaviors revealed consistent and significant associations for almost all psychosocial factors. Author Contributions Conceptualization, M.
Conflicts of Interest The authors declare no conflict of interest. References 1. Lim S. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, a systematic analysis for the Global Burden of Disease Study Lozano R.
Global and regional mortality from causes of death for 20 age groups in and a systematic analysis for the Global Burden of Disease Study Babor T. World Health Organization; Geneva, Switzerland: Poortinga W. The prevalence and clustering of four major lifestyle risk factors in an English adult population. Coups E. Physician screening for multiple behavioral health risk factors. Silva D. Clustering of risk behaviors for chronic noncommunicable diseases: A population-based study in southern Brazil.
Chiolero A. Clustering of risk behaviors with cigarette consumption: A population-based survey. Noble N. Which modi fi able health risk behaviours are related? Falkstedt D. Prevalence, co-occurrence, and clustering of health-risk behaviors among people with different socio-economic trajectories: A population-based study.
Laaksonen M. Read more. Movement policy on addressing mental health and psychosocial need Mental Health Matters: Addressing mental health and psychosocial Mental Health and Psychosocial Support. What we do. Visit the website. Watch: mental health videos. The importance of mental health and psychosocial support during C Psychological demands include requirements imposed on workers in the course of their activities.
These include variables that measure pace, volume, time to perform tasks, and the existence of conflicting requests 8. The combination of experiences in the higher and lower levels of these two dimensions results in different work characteristics represented by four categories as follows: low work demand low psychological demand, high control over the work itself , active work high demand and high control , passive work low demand and low control and high demand high demand and low control.
However, there are few studies on the psychosocial aspects of work, with respect to elementary school teachers. The different forms of work, reflected in their organizational aspects, may cause various health consequences and compromise the quality of life of teachers 4. According to the World Health Organization 10 , quality of life QOL is the perception of individuals of their position in life, in the context of culture and the system of values in which they live in as well as their goals, expectations, standards, and concerns.
A number of important characteristics about the quality of life construct are built into the WHOQOL group concept, such as subjectivity, multidimensionality, and the presence of positive and negative dimensions In a cross-sectional study carried out with workers, aged between 18 and 64 years, negative associations were reported between the psychosocial aspects of work and quality of life.
The results showed a significant statistical association between the high work demand variable high demand and low control and low scores in the following quality of life domains: functional capability, physical limitations, vitality, social aspects and mental health In this context, according to the Demand-Control model, we consider the hypothesis that the teaching profession, which is characterized as active and very demanding, compromises the quality of life of elementary school teachers.
It is believed that the results of this investigation can help direct public policies aimed at promoting the health of this group of workers. The aim of the present study was to investigate the quality of life of public school teachers in Natal, Brazil, and to describe the psychosocial characteristics of control and the psychological demands of work in addition to investigate the existence of a difference between the means of quality of life domains and the categories of the demand-control model.
This is a descriptive cross-sectional study with a population of 2, public elementary teachers in Natal, Brazil, in data provided by the Municipal Health Secretariat. The sample teachers was calculated from this population, using a mean reference value for the quality of life domain of First, we determined the number of individuals to be selected from each of the four city districts, using the proportionality between the total number of teachers as the sample number. The teachers were randomly selected after those occupying administrative positions were excluded.
Once they were informed about the aims of the study, the teachers were given a 3-part self-report questionnaire. The first block of questions were related to demographics and socioeconomic data sex, age, marital status, income and schooling level and occupational data number of years in the teaching profession, weekly work load, number of students in the classroom and whether or not the school was located in the same district of the teacher's residence.
The second part corresponded to the assessment of quality of life using the Quality of Life-Bref WHOQOL-bref instrument of the World Health Organization, validated for the Brazilian population, and which showed satisfactory internal consistency Cronbach's coefficient ranging between 0.
The WHOQOL-bref consists of 26 questions pertaining to four domains that express the quality of life of the subjects investigated: physical, psychological, environment and social relations. Each question was assigned a score between one and five, and the results of each domain were then transformed into a scale graduated from 0 to , zero corresponding to the worst quality of life status and one hundred to the best status, enabling the individual analysis of each dimension.
The third part contained questions from the Job Content Questionnaire JCQ 15 about the degree of control and the psychological demand of work. The questionnaire was translated and validated in Brazil, resulting in a Cronbach coefficient between 0.
From the Demand-Control model proposed by Karasek, the teachers' responses were assigned to four categories: non-demanding work little psychological demand, high control over the work itself , active work high demand and control passive work little demand and control and demanding work high demand and little control.
The control and demand variables were summed, considering the aspects foreseen in the operationalization process of the model.
This paper is part of the research project entitled "Quality of life and conception of health: what elementary school teachers think and do when the topic is health". Data distribution, using the Kolmogorov-Smirnov test, showed non-normal distribution. Descriptive statistics, determining means x and standard deviation SD were used for the quantitative variables, and simple and relative frequencies for the categorical variables.
Of the teachers studied, In regard to schooling, Mean number of years of teaching experience was Weekly work load showed a mean of A total of Regional Office for Europe Accessed 15 July Mittal S Air pollution and its impact on mental health. Accessed 29 May Google Scholar. Int Rev Psychiatry 22 3 — In: Walter L et al eds Climate literacy and innovations in climate change education: distance learning for sustainable development.
Springer, Cham Google Scholar. Parr J. In: Leal Filho W. Accessed 14 Aug Salami SO Psychopathology and academic performance among Nigerian high school adolescents: the moderator effects of study behavior, self-efficacy and motivation. J Soc Sci 16 2 — Salami OS Emotional intelligence, self-efficacy, psychological well-being and students attitudes: implications for quality education.
Eur J Educ Stud —
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