Prevalence of lifestyle risk factors in a family practice

Which modifiable health risk behaviours are related? A systematic review of the clustering of Smoking, Nutrition, Alcohol and Physical activity ('SNAP') health risk factors

OBJECTIVE

There is a growing body of literature examining the clustering of health risk behaviours, but little consensus about which risk factors can be expected to cluster for which sub groups of people. This systematic review aimed to examine the international literature on the clustering of smoking, poor nutrition, excess alcohol and physical inactivity (SNAP) health behaviours among adults, including associated socio-demographic variables.

METHOD

A literature search was conducted in May 2014. Studies examining at least two SNAP risk factors, and using a cluster or factor analysis technique, or comparing observed to expected prevalence of risk factor combinations, were included.

RESULTS

Fifty-six relevant studies were identified. A majority of studies (81%) reported a 'healthy' cluster characterised by the absence of any SNAP risk factors. More than half of the studies reported a clustering of alcohol with smoking, and half reported clustering of all four SNAP risk factors. The methodological quality of included studies was generally weak to moderate. Males and those with greater social disadvantage showed riskier patterns of behaviours; younger age was less clearly associated with riskier behaviours.

CONCLUSION

Clustering patterns reported here reinforce the need for health promotion interventions to target multiple behaviours, and for such efforts to be specifically designed and accessible for males and those who are socially disadvantaged.

Randomized controlled trial of a computer strategy to increase general practitioner preventive care

BACKGROUND

Previous interventions targeting primary care practitioners with the aim of increasing preventive care delivery have demonstrated limited effectiveness. The primary aim of this study was to assess the effectiveness of a computerized continuing medical education program to increase rates of three screening behaviors (cholesterol, blood pressure, and cervical screening) and to identify three risk behaviors (smoking, alcohol consumption, benzodiazepine use) in general practice.

METHODS

Nineteen general practitioners were randomly allocated to intervention or control conditions. Those given the intervention received a computerized feedback system. The intervention was delivered using a touch-screen computer located in the surgery waiting area. The preventive behaviors of interest were patient smoking, alcohol use, benzodiazepine use, and blood pressure, cholesterol and cervical screening using the Papanicolou test. Differences in performance by group in each of the outcomes was measured at baseline and 3-month follow-up. Logistic regression analyses with generalized estimating equations were conducted as the main analyses.

RESULT

At 3-month follow-up, statistically significant differences were evident in the following outcome measures: accurate classification of benzodiazepine users (z = 2.8540, P < 0.05); accurate classification of non-benzodiazepine users (z = 2.7339, P < 0.05); accurate classification of hazardous or harmful alcohol drinkers (z = 2.3079, P < 0.02); blood pressure screening (z = 3.4136, P < 0.001); and cholesterol screening (z = 6.6313, P < 0.001).

CONCLUSION

A computerized system of performance-specific feedback was effective at increasing some preventive care services in general practice.

A practical approach to lifestyle change counselling in primary care

Many contemporary medical conditions have been found to be the consequence of lifestyle choices. These adverse habit patterns have their origin in the individuals family and/or natural social network. Primary care practitioners frequently interact with their patients for the purpose of helping them resolve medical problems by clarifying issues or presenting different options. In lifestyle related conditions, the initiation and maintenance of possible behaviour changes is usually the optimal resolution. How people intentionally change well-established behaviour patterns is still not well understood, and most clinicians are not confident in their ability to help patients alter adverse behaviours. Several studies provide support for a 'stage-matched framework' of behaviour change that integrates readiness for change with intervention processes from various theoretical models. This article provides a brief overview of the current thinking with respect to self-initiated and professionally facilitated behaviour change, and then describes a generic five-step approach to individualized lifestyle counselling for use in primary care clinical settings.

Consistency and variation in unhealthy behaviour among Finnish men, 1982-1990

The aim of the study was to describe four health related lifestyle characteristics--smoking, exercise, alcohol and food consumption--among Finnish men in 1982-1990. How do unhealthy patterns of behaviour vary according to socio-demographic factors, and do they aggregate or accumulate? The data was compiled in connection with a larger programme entitled 'Monitoring Health Behaviour among the Finnish Adult Population' and conducted by the National Public Health Institute. In the programme a postal questionnaire has been sent annually to a random sample of Finns (N = 5000, resp. rate 70-85%). In this paper, food consumption patterns are described by the use of butter, high-fat milk, coffee sugar and vegetables. The other patterns of behaviour are each measured by one variable. The degree of accumulation is analyzed by comparing the observed and expected (assuming independent occurrence) proportions for simultaneous occurrence of 3-4 unhealthy behaviour patterns. The proportion of men displaying 3-4 unhealthy behaviour patterns has decreased, mostly because of dietary changes. The majority of the men belonged to the intermediate group of 1-2 unhealthy behaviour patterns, and their proportion remained practically unchanged throughout the study period. Unhealthy behaviour was more common in lower educational groups, especially among middle-aged (30-49) and divorced men with a low educational level. Despite the decreasing prevalence of unhealthy behaviour, the degree of accumulation did not change. Accumulation of unhealthy behaviour was much less pronounced among non-smokers than among smokers. This implies that smokers are consistent in their unhealthy behaviour. Smoking might be the gateway to an unhealthy lifestyle in general.

Bad faith and victim-blaming: the limits of health promotion

Two models of the relationship between individual behaviour and health status are examined. On the Freedom Model, the individual is presumed to be capable of free choices including many that have important health consequences. Freedom entails accountability. Thus individuals can be held responsible for health conditions that result from choices they have made. To hold otherwise--to refuse to acknowledge the freedom and responsibilities of individuals--is bad faith. On the Facticity Model, behaviour is a result of facts--genetic and environmental--beyond an individual's control. There is little or no freedom; people are the bodies and roles they inherit. Important among these facts is socio-economic position since it determines much of behaviour and resulting health status. Many people who are poor and lack education also suffer from poor health. To blame their poor health on their behaviour is to blame people already victimized by their circumstances. The relationships of these two models to health promotion are explored. Though conflicting in theory, some justice can be done to each model in the practical world of health promotion by appealing to the freedom in individuals in health education and to the facts that shape individuals in other health promotion and health care contexts.