Clustering of Lifestyle Risk Factors in a General Adult Population

Schuit, Albertine J.; Loon, A.J.M. van; Tijhuis, Marja; Ocké, Marga C.

doi:10.1006/pmed.2002.1064

Cited by 460 publications

(523 citation statements)

References 18 publications

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“…This is particularly important given that lifestyle factors tend to cluster in individuals (8)(9)(10)(11) . Hence, the study of the clustering of risk factors has important implications on both disease risk and the development of preventive interventions targeting the combination of risk factors rather than individual risk factors.…”

mentioning

confidence: 99%

Clustering of lifestyle factors in Spanish university students: the relationship between smoking, alcohol consumption, physical activity and diet quality

Moreno-Gómez

Romaguera

Tauler

et al. 2012

Public Health Nutr.

121

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Objective: To ascertain the prevalence of and association between main lifestyle factors (diet, physical activity, alcohol consumption and smoking) in students from the Balearic Islands University. Design: A cross-sectional, descriptive study. A questionnaire including questions on lifestyle, dietary habits and physical activity habits was administered to the students. Four different diet quality scores were calculated (Diet Diversity Score, Mediterranean Diet Score, Dietary Guidelines Score and Global Dietary Guidelines Score). Setting: A sample of students from the Balearic Islands University. Subjects: Nine hundred and eighty-seven students (45?5 % males; mean age 21?5 (SD 3?3) years). Results: The dietary pattern of the student population was characterized by a low consumption of cereals and tubers, fruits, vegetables, olive oil, legumes and nuts, and a high consumption of processed meat, sweets, snacks, soft drinks and pastries. Linear, positive and statistically significant correlations were found between the number of meals consumed daily and all of the diet quality scores determined. Determinants of diet quality, both in the univariate and multivariate analyses, were physical activity practice, sex, age and number of meals consumed daily. Conclusions: Risk factors such as smoking, diet and physical inactivity had a tendency of clustering among Spanish university students. Overall diet quality was low, due to important departures from dietary recommendations and loss of the traditional Mediterranean dietary pattern. Nutritional education campaigns that include promotion of physical activity practice are needed to improve the overall health status of this population. Keywords Diet Physical activity Smoking Alcohol drinking University studentsCurrently, there is extensive evidence that lifestyle factors, such as unhealthy diet, excessive alcohol consumption, smoking and sedentary lifestyle, contribute to an increase in morbidity and mortality due to the development of chronic diseases such as CVD, type 2 diabetes and cancer, among others (1,2) .Despite the fact that most studies have focused on the independent effect of each lifestyle factor on disease risk, recent publications have studied the synergistic effect of several combined lifestyle factors on health risk (3)(4)(5)(6)(7) . This is particularly important given that lifestyle factors tend to cluster in individuals (8)(9)(10)(11) . Hence, the study of the clustering of risk factors has important implications on both disease risk and the development of preventive interventions targeting the combination of risk factors rather than individual risk factors.As recent studies suggest, physical activity and diet are key factors for health maintenance, sharing -even synergistically -physiological mechanisms affecting the global metabolism (12,13) .It is well known that the prevalence of smoking, alcohol consumption and physical inactivity is increasing in Spanish adolescents and young adults, but information on the clustering of these behaviours is s...

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mentioning

confidence: 99%

Clustering of lifestyle factors in Spanish university students: the relationship between smoking, alcohol consumption, physical activity and diet quality

Moreno-Gómez

Romaguera

Tauler

et al. 2012

Public Health Nutr.

121

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“…Investigating the negative health-related physical fitness indicators with sociodemographic and lifestyle factors in adolescents is justified, since in addition to verifying to what extent this particular group of schoolchildren can be screened, information in literature regarding these constructs is presented in their majority, bidirectionally 3,5,11 . Likewise, the verification of negative physical fitness indicators simultaneously is important because it is possible that the potential negative health effect caused by the combination of these indicators may be greater than the sum of each independent factor 13 . In addition, health problems associated with negative physical fitness indicators usually manifest throughout adult life; however, their development seems to begin in childhood and adolescence 14 .…”

Section: Introductionmentioning

confidence: 99%

“…The prevalence observed for the sample of this study was identified, and the expected prevalence was calculated by multiplying the individual probability of each risk factor based on its occurrence in the study population. Through this process, it is possible to identify combinations that are above or below expectations 13 .…”

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confidence: 99%

Combinação de indicadores negativos da aptidão física e fatores associados em adolescentes

Lima

Silva

2017

Rev. Bras. Cineantropom. Desempenho Hum.

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-Inadequate levels in health-related physical fitness components are associated with early cardiovascular mortality in adult life. The aim of this study was to analyze the association between clusters of negative physical fitness indicators with sociodemographic and lifestyle variables in adolescents. The survey was conducted with 866 students (14-19 years) from public schools of São José, Santa Catarina, Brazil. Aerobic fitness was assessed by the modified Canadian aerobic fitness test; muscle strength was measured by handgrip dynamometer; flexibility was assessed by the sit-and-reach test; body fat was measured by the sum of triceps and subscapular skinfolds. Sociodemographic and lifestyle variables were verified by questionnaire. The simultaneity of behaviors was evaluated by the ratio between observed and expected prevalence of inadequate physical fitness levels. The combination of negative physical fitness indicators was analyzed through multinomial logistic regression. The prevalence observed for the simultaneity of four negative physical fitness indicators was 30% higher than expected. Female adolescents were more susceptible to the presence of two, three and four negative physical fitness indicators. Adolescents who presented risk behavior in relation to screen time were more likely to present one, three and four negative physical fitness indicators. Female gender and risk behavior in relation to screen time were factors associated with the simultaneity of negative physical fitness indicators.Key words: Adolescent health; Cross-sectional studies; Epidemiology; Prevention and control. (14-19 anos) Resumo -Níveis inadequados nos componentes da aptidão física relacionada à saúde estão associados à mortalidade cardiovascular precoce na vida adulta. Objetivou-se analisar a associação entre a combinação de indicadores negativos da aptidão física com variáveis sociodemográficas e do estilo de vida em adolescentes. Pesquisa realizada com 866 estudantes

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“…Disparities exist across US occupational classes and socioeconomic levels for meeting recommended goals for diet and physical activity; for example, blue-collar workers and people with lower socioeconomic position exhibit higher risk [2, [4][5][6][7][8]. While disparities in health behaviors across occupational class are well documented for discrete health behaviors [8], a few studies have also suggested that there may be disparities in clustering of health behaviors among people of different occupational classes and socioeconomic and education levels [9,10]. Since both chronic disease burden and clusters of unhealthy behaviors have been shown to be disproportionately high among blue-collar workers; examining contextually relevant programs that address multiple health behaviors is an important public health endeavor.…”

Section: Introductionmentioning

confidence: 99%

Sociodemographic and social contextual predictors of multiple health behavior change: data from the Healthy Directions–Small Business study

Harley

Sapp

et al. 2013

Behav. Med. Pract. Policy Res.

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Multiple modifiable health behaviors contribute to the chronic diseases that are the leading causes of death in the USA. Disparities for meeting recommended health behavior guidelines exist across occupational classes and socioeconomic levels. The purpose of this paper was to investigate sociodemographic and social contextual predictors of multiple health behavior change in a worksite intervention. We analyzed data on four diet and exercise variables from an intervention trial with worksite-level randomization. Eight hundred forty-one employees had complete data from baseline (response rate084 %) and follow-up surveys (response rate077 %). Multilevel logistic regression estimated associations between least absolute shrinkage and selection operator-selected sociodemographic and social contextual predictor variables and the multiple health behavior change outcome (changing 2+ versus 0 behaviors). Gender, being married/partnered, and perceived discrimination were significantly associated with multiple health behavior change. Sociodemographic and social contextual factors predict multiple health behavior change and could inform the design and delivery of worksite interventions targeting multiple health behaviors.

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Clustering of Lifestyle Risk Factors in a General Adult Population

Cited by 460 publications

References 18 publications

Clustering of lifestyle factors in Spanish university students: the relationship between smoking, alcohol consumption, physical activity and diet quality

Clustering of lifestyle factors in Spanish university students: the relationship between smoking, alcohol consumption, physical activity and diet quality

Combinação de indicadores negativos da aptidão física e fatores associados em adolescentes

Sociodemographic and social contextual predictors of multiple health behavior change: data from the Healthy Directions–Small Business study

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