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      A systematic review on the clustering and co-occurrence of multiple risk behaviours

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          Risk behaviours, such as smoking and physical inactivity account for up to two-thirds of all cardiovascular deaths, and are associated with substantial increased mortality in many conditions including cancer and diabetes. As risk behaviours are thought to co-occur in individuals we conducted a systematic review of studies addressing clustering or co-occurrence of risk behaviours and their predictors. As the main aim of the review was to inform public health policy in England we limited inclusion to studies conducted in the UK.


          Key databases were searched from 1990 to 2016. We included UK based cross-sectional and longitudinal studies that investigated risk behaviours such as smoking, physical inactivity, unhealthy diet. High heterogeneity precluded meta-analyses.


          Thirty-seven studies were included in the review (32 cross-sectional and five longitudinal). Most studies investigated unhealthy diet, physical inactivity, alcohol misuse, and smoking. In general adult populations, there was relatively strong evidence of clustering between alcohol misuse and smoking; and unhealthy diet and smoking. For young adults, there was evidence of clustering between sexual risk behaviour and smoking, sexual risk behaviour and illicit drug use, and sexual risk behaviour and alcohol misuse.

          The strongest associations with co-occurrence and clustering of multiple risk behaviours were occupation (up to 4-fold increased odds in lower SES groups) and education (up to 5-fold increased odds in those with no qualifications).


          Among general adult populations, alcohol misuse and smoking was the most commonly identified risk behaviour cluster. Among young adults, there was consistent evidence of clustering found between sexual risk behaviour and substance misuse. Socio-economic status was the strongest predictor of engaging in multiple risk behaviours.

          This suggests the potential for interventions targeting multiple risk behaviours either sequentially or concurrently particularly where there is evidence of clustering. In addition, there is potential for intervening at the social or environmental level due to the strong association with socio-economic status.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12889-016-3373-6) contains supplementary material, which is available to authorized users.

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          Most cited references 52

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          The prevalence and clustering of four major lifestyle risk factors in an English adult population.

          The aim of this study was to examine the clustering of four major lifestyle risk factors (smoking, heavy drinking, lack of fruit and vegetables consumption, and lack of physical activity), and to examine the variation across different socio-demographic groups in the English adult population. The study population was derived from the 2003 Health Survey for England (n=11,492). Clustering was examined by comparing the observed and expected prevalence of the different possible combinations. A multinomial multilevel regression model was conducted to examine the socio-demographic variation in the clustering of the four risk factors. The study found that, when using British health recommendations, a majority of the English population have multiple lifestyle risk factors at the same time. Clustering was found at both ends of the lifestyle spectrum and was more pronounced for women than for men. Overall, multiple risk factors were more prevalent among men, lower social class households, singles, and people who are economically inactive, but less prevalent among home owners and older age groups. The clustering of multiple risk factors provides support for multiple-behavior interventions as opposed to single-behavior interventions.
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            Prevalence of multiple chronic disease risk factors. 2001 National Health Interview Survey.

            Four common factors--cigarette smoking, risky drinking of alcoholic beverages, physical inactivity, and overweight--contribute substantially to chronic disease prevalence. We used data from the 2001 National Health Interview Survey to provide an up-to-date picture of multiple risk factor prevalence and clustering in the U.S. population. We conducted a multinomial logit analysis to examine the independent association between each covariate and the dependent ordinal risk factor variable with three levels (none or one risk factor, two risk factors, and three or four risk factors). Seventeen percent of the sample of 29,183 subjects had three or more risk factors. For the entire sample, the mean number of risk factors was 1.68 (95% confidence interval [CI]=1.66-1.70). Many demographic and health factors were significantly associated with the mean number of risk factors including gender, age, ethnic/racial categories, education, martial status, presence of chronic diseases, level of mental distress, country of birth, and presence and type of health insurance. Using the risk factor score as the ordinal dependent variable, adjusted odds for having a risk score of three or four versus zero or one were as follows: men aged <65, 2.49 (95% CI=2.29-2.72); education attainment of high school graduate or less, 3.24 (95% CI=2.86-3.67); and individuals with high levels of mental distress, 2.06 (95% CI=1.65-2.58). Our analyses confirm earlier reports of the high prevalence of multiple, clustered behavioral risk factors and underline the challenge this presents for primary care and public health systems.
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              Health behaviors from early to late midlife as predictors of cognitive function: The Whitehall II study.

              The authors examined associations of health behaviors over a 17-year period, separately and in combination, with cognition in late midlife in 5,123 men and women from the Whitehall II study (United Kingdom). Health behaviors were assessed in early midlife (mean age = 44 years; phase 1, 1985-1988), in midlife (mean age = 56 years; phase 5, 1997-1999), and in late midlife (mean age = 61 years; phase 7, 2002-2004). A score of the number of unhealthy behaviors (smoking, alcohol abstinence, low physical activity, and low fruit and vegetable consumption) was defined as ranging from 0 to 4. Poor (defined as scores in the worst sex-specific quintile) executive function and memory in late midlife (phase 7) were analyzed as outcomes. Compared with those with no unhealthy behaviors, those with 3-4 unhealthy behaviors at phase 1 (odds ratio (OR) = 1.84, 95% confidence interval (CI): 1.27, 2.65), phase 5 (OR = 2.38, 95% CI: 1.76, 3.22), and phase 7 (OR = 2.76, 95% CI: 2.04, 3.73) were more likely to have poor executive function. A similar association was observed for memory. The odds of poor executive function and memory were the greater the more times the participant reported unhealthy behaviors over the 3 phases. This study suggests that both the number of unhealthy behaviors and their duration are associated with subsequent cognitive function in later life.

                Author and article information

                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                29 July 2016
                29 July 2016
                : 16
                [1 ]Centre for Reviews and Dissemination, University of York, York, YO10 5DD UK
                [2 ]Department of Health Sciences, University of York, York, UK
                [3 ]Department of Social and Environmental Health Research, London School of Hygiene and Tropical Medicine, London, UK
                [4 ]Population, Policy and Practice, UCL Institute of Child Health, London, UK
                [5 ]UKCRC Centre for Diet and Activity Research (CEDAR), MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
                © The Author(s). 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

                Funded by: Department of Health, UK
                Research Article
                Custom metadata
                © The Author(s) 2016

                Public health

                co-occurrence, clustering, systematic review, multiple risk behaviours


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