Lifestyle Assessment: Part 4 - Europe PMC

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Hamilton, ON., District Health Councils. Research Program, Hamilton-Wentworth ... Nie NH, Hull CH, Jenkins JG, et al: Statistical Package for the SocialĀ ...
R. Simpson W. Albert D. M. C. Wilson D. Ciliska C. E. Evans

Lifestyle Assessment: Part 4 The Halton Health Promotion Survey SUMMARY

SOMMAIRE

In the Region of Halton, a health promotion data base was developed to assist with planning for local services and programs. Three data sources were used: preventable mortality, preventable morbidity, and the prevalence of modifiable risk among community members. Existing information was used for the first two sources, and the community was surveyed for the last. A survey version of the FANTASTIC Lifestyle Checklist was mailed to a random sample of 1,200 households. FANTASTIC showed itself to be a reliable lifestyle construct with two major factors: a group of psychosocial behaviors, and a set of "'bad habits". (Can Fam Physician 1984; 30:2147-2155).

Dans la region de Halton, on a developpe des donnees de base dans le domaine de la promotion de la sante, lesquelles pourraient contribuer a planifier les programmes et les services locaux. On a utilise 3 sources de donnees: mortalite evitable, morbidite evitable et prevalence de risques modifiables parmi les membres de la communaute. Pour les deux premieres sources, on a utilise l'information existante et on a fait une enquete dans la communaute pour la derniere. Une version d'enquete du FANTASTIC Lifestyle Checklist fut postee a un echantillon de 1200 foyers. FANTASTIC s'est revele un outil valide concernant le style de vie dans deux facteurs majeurs: un groupe de comportements psychosociaux et une se'rie de "mauvaises habitudes".

Mr. Simpson is a program TIC lifestyle checklist as an instrument consultant in health promotion at for family physicians and other health the Addiction Research care providers to assess their patients' Foundation, and chairman of the physical, mental, and social wellHealth Promotion Committee, being. 1 2 This article extends these Halton District Health Council. Dr. clinical applications and discusses the use of FANTASTIC as a survey instruAlbert is a scientist with the ment in planning community health Community Programs Evaluation promotion services. Centre at the Addiction Research Foundation. The opinions expressed In Ontario, locally-based District in this article are those of the Health Councils are devoting an inauthors and not of the Addicition creasing proportion of their energies to Research Foundation. Drs. Wilson health promotion.3 In 1981, a consorand Evans, certificants of the tium of health councils established a College, are associate professors in Task Force on Health Promotion to dethe Department of Family velop a relevant model for planning at Medicine, and Ms. Ciliska is an the local level. The final report of the assistant professor in the School of Task Force, published in 1983, deNursing, all at McMaster University. Reprint requests to: Dr. Douglas M. C. Wilson, Department Fig. 1. The Well-lIl Continuum.8 of Family Medicine, McMaster Well University Faculty of Health Optimal At low At Sciences, Hamilton, ON. L8N 3Z5.

PREVIOUS ARTICLES in this series have introduced the FANTASCAN. FAM. PHYSICIAN Vol. 30: OCTOBER 1984

health

scribes a theoretical model for helping communities plan the evolution of their health promotion services.4 Concurrent with the release of this report, the Halton District Health Council, in collaboration with the Halton Regional Department of Health, launched the initial implementation of the planning model and its attendant processes.5 Many communities already have an assortment of services which fall under the health promotion umbrella. Typically, these include services to help with weight loss, smoking cessation, stress management, moderating alcohol consumption, improving nutritional habits, and so on. In addition, a variety of programs often provide in-

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formation and apply persuasion in such areas as drinking and driving, the use of seatbelts, smoking, and exercise. In most cases, these services and programs will have evolved independently, without reference to documented community need. Steps should be taken to match the network of health promotion services and programs as closely as possible with community needs. In this way, the health promotion network can be refined to better address the demand. Although it is easy to articulate this 'planning perspective' as an abstract principle, it is considerably more difficult to determine the relative need for health promotion services within a community. A systematic way to approach this problem is to develop a data base which yields a statistical profile of community need. This article describes the experience of Halton in the design and development of a health promotion data base. Particular attention is given to the role played by the FANTASTIC lifestyle checklist as a principal input.

The 'Well-I11' Continuum There is no universally-accepted definition of the term "health promotion" 6 Accordingly, our first task in Halton was to develop a practical definition based on a consensus of community perspectives, and considering the major theoretical controversies .' The definition we ultimately adopted can best be described through the 'Well-Ill Continuum' ,8 which describes six categories of health status, three of which can be ascribed to the 'well' population, and three to the 'ill' population. The population can move from one status to another in response to a variety of influences, some of which are within their control and others beyond it. We defined health promotion services and programs as measures directed towards the population of 'well' people, and intended either to inhibit their transition to 'ill' status, or to enhance existing levels of health. Within this general definition, we identified three specific types of intervention: 1. Identification and modification of risk behaviors and conditions among the population at risk, moving them towards low risk status. (This is sometimes referred to as risk reduction, or secondary prevention). 2148

2. Implementation of measures directed at members of the low risk category, to reduce the likelihood of movement towards risk status. (This is sometimes referred to as risk avoidance, or primary prevention). 3. Implementation of measures that will increase levels of health as measured by indicators of physical, mental, and social wellbeing. This is sometimes referred to as health enhancement. We then needed to establish a data base that could suggest to us which health promotion services and programs were required and in what priority. Turning again to the Well-Ill Continuum, we concluded that it was important to obtain measurements from three categories: "premature death", "disease and disability", and "at risk".

We reasoned that information about premature death would tell us what people were dying from and what could have been prevented. By examining the causes, we anticipated being able to identify a number of associated risk factors which lend themselves to modification, such as smoking, seatbelt use, obesity, anxiety, air quality, road design, etc. Mortality data would be valid only if current rates were stable and predictive of future ones, all else being equal. For this reason, we concluded that corroborative data were required, and turned to measurements from two other categories. The "disease and disability" category is, in effect, a measurement of morbidity. Here again we reasoned that if we would list all causes, and separate out those which were prevent-

Fig. 2.

Frequency histogram for FANTASTIC scale score ranges (N=779). 40 38 36 34 32 30 28 26 24 22 20 18 16 14 12 10 8 6 4 2

+1 SD

-1 SD

+2 SD

-2 SD

-3 SD

34-54 very high risk

65-73 55-64 high risk moderate risk

74-83 low risk

84-93 very low risk

94-98 optimal

-lifestyle

mean 73.9 "FANTASTIC" Scale Score Ranges CAN. FAM. PHYSICIAN Vol. 30: OCTOBER 1984

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References: 1. Hirshleifer, I., Curr. Ther. Res., 15, 4, 158 (1973) 2. Blinder, S., Curr. Ther. Res., 7, 12 (1965) 3. Klein, H.O., and Berger, H.J., Cardiology, 58, 313 (1973) 4. Data on file, Rhone-Poulenc Pharma Inc. 5. Winsor, T. and Berger, H.J., Am. Heart J., vol. 90, 61 1-612 (1975)

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able, we would have a basis from which to define associated risk factors. These, in turn, would become the focus of health promotion initiatives. As with mortality data, morbidity statistics are only of value if they tend to remain stable over time. To help offset this limitation, we decided to examine both sets of data over a three-year period in order to identify any obvious anomalies. The first two data sources would provide us with retrospective indicators; the third was intended to be prospective, or predictive, in nature. We reasoned that by measuring the frequency of common risk factors in the community, we could adjust our health

promotion activities according to the most significant threats to community health. We further refined this idea to focus on risks which were, to some extent, within the power of the individual to change. Accordingly, this measure became an indicator of modifiable risk. We envisioned the definition of community need for health promotion services as a derivation of all three data sets. In addition, we decided that the information should be organized by sex and by age. Six age groupings were selected (0-4, 5-14, 15-19, 2034, 35-64, and over 65) to correspond with the typical age-related segmentation of health promotion initiatives. Thus, for example, for males aged 20-

TABLE 1 Results of One Way Analyses of Variance (N=779) Mean FANTASTIC Independent Scale Scores Variable n Sex male 73.08 377 female 74.70 399 Employment status full-time 71.55 401 part-time 74.88 139 not employed 77.18 235 Marital status single 75.11 188 married 73.63 534 widowed 78.68 19 17 separated 69.53 divorced 71.38 13 cohabiting 7 67.86

Significance Level .02