For categorical variables having k categories, k-1 odds ratio estimates were obtained when the variable was replaced by k-1 binary (0, 1) predictors that used the first category as a reference (odds ratio set to one). A test for trend was then undertaken by replacing the binary variables with the single predictor taking, for example, rank scores for the categories (1st
category=1, 2ndcategory=2, etc). The significance of the test for trend was evaluated by
examining the p-value of the Wald test.
Continuous variables can be analysed as continuous predictors provided they are
approximately“linearin the logit”.To assessthismodelling assumption,we categorised the
continuous variables into five levels and plotted the logit against the category number or its midpoint. Alternatively, these variables can be divided into categories and analysed as categorical variables.
5.8 S
UMMARYA population based case-control study was conducted in Tasmania, to investigate whether high past ultraviolet radiation exposure may reduce the risk of MS, and to examine whether other environmental factors might influence the development of MS. Interviews were conducted with 136 cases with MS and 272 community controls. Both cases and controls were drawn from the cohort of persons under the age of sixty years, resident on the mainland of Tasmanian, with at least one grandparent born in Tasmania. Cases were people with MS, defined by both clinical and magnetic resonance imaging criteria. Controls were randomly drawn from the community and matched on sex and birth year. Subjects were interviewed using an extensive questionnaire and were asked to complete a personal residence and work calendar. Phone interviews were held with proxies (someone who had close contact with the
subjectduring the subject’schildhood and adolescence)regarding exposuresthatoccurred
during childhood and adolescence. Repeat interviews were conducted with 52 cases and 52 controls, about 11 weeks after the main interview took place, to examine the reliability of measurements of the main study factors. Measurements were included on past sun exposure, vitamin D, skin type and sun avoidance behaviour, history of infections, immunisations, concussion, smoking and specific diseases, sibship structure, puberty development and female reproduction, exposure to chemicals, pets and farm animals, dietary intake (including alcohol), place of living, occupation and socio-economic status. Where possible objective measures included, such as the measurement of lifetime actinic damage using silicon casts of the hand, assessment of skin type by spectrophotometry and serum analysis of 25(OH)D and IgG levels of specific infections. Conditional logistic regression was used as the main type of analysis of the data.
5.9 P
OSTSCRIPTWe have now established the methodological aspects of the Tasmanian MS case-control study, the study that is central to this thesis. A number of chapters will refer back to this chapter, in order to limit duplication of information. Other aspects, however, will be discussed in more detail in other chapters when required. The next two chapters assess the reliability of measurements of the Tasmanian MS case-control study.
5.10 R
EFERENCES1. Hammond SR, McLeod JG, Millingen KS, et al. The epidemiology of multiple sclerosis in three Australian cities: Perth, Newcastle and Hobart. Brain 1988; 111:1-25.
2. Australian Bureau of Statistics. Demography Tasmania, 3311.6, 1999. 3. Dwyer T, Sale MM, Stankovich JM, Hazelwood KF, Mulcahy N. Using genetic
advances to investigate diabetes in Tasmania. Diabetes Technol Ther 2001; 3:641-6. 4. Cardon LR, Palmer LJ. Population stratification and spurious allelic association.
Lancet 2003; 361:598-604.
5. Rubio JP, Bahlo M, Butzkueven H, et al. Genetic dissection of the human leukocyte antigen region by use of haplotypes of Tasmanians with multiple sclerosis. Am J Hum Genet 2002; 70:1125-37.
6. Rose AS, Ellison GW, Myers LW, Tourtellotte WW. Criteria for the clinical diagnosis of multiple sclerosis. Neurology 1976; 26:20-2.
7. Poser CM, Paty DW, Scheinberg L, et al. New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol 1983; 13:227-31.
8. Paty DW, Oger JJ, Kastrukoff LF, et al. MRI in the diagnosis of MS: a prospective study with comparison of clinical evaluation, evoked potentials, oligoclonal banding, and CT. Neurology 1988; 38:180-5.
9. Means B, Swan GE, Jobe JB, Esposito JL. An alternative approach to obtaining personal history data. In: Biemer PP, Groves RM, Lyberg LE, Mathiowetz NA, Sudman S, eds. Measurement Errors in Surveys. New York: John Wiley & Sons, 1991:167-183.
10. Boiko A. Data collection guidelines for questionnaires to be used in case- control studies of multiple sclerosis. Neurology 1997; 49:S75-80.
11. Dwyer T, Blizzard L, Gies PH, Ashbolt R, Roy C. Assessment of habitual sun
exposure in adolescents via questionnaire-a comparison with objective measurement using polysulphone badges. Melanoma Res 1996; 6:231-9.
12. Freyer J, Blizzard L, Dickenson J. Sun exposure, vitamin D and prostate cancer. Manuscript in preparation.
13. Blizzard L, Dwyer T. Sun exposure and risk of malignant melanoma, basal cell
carcinoma, and squamous cell carcinoma of the skin: a population based case-control study. Manuscript in preparation.
14. Beagley J, Bibson IM. Changes in skin condition in relation to degree of exposure to ultraviolet light. Perth: Western Australia Institute of Technology, School of Biology, 1980.
15. Green AC. Premature ageing of the skin in a Queensland population. Med J Aust 1991; 155:473-4, 477-8.
16. Holman CD, Evans PR, Lumsden GJ, Armstrong BK. The determinants of actinic skin damage: problems of confounding among environmental and constitutional variables. Am J Epidemiol 1984; 120:414-22.
17. English DR, Armstrong BK, Kricker A. Reproducibility of reported measurements of sun exposure in a case-control study. Cancer Epidemiol Biomarkers Prev 1998; 7:857-63.
18. Dwyer T, Muller HK, Blizzard L, Ashbolt R, Phillips G. The use of spectrophotometry to estimate melanin density in Caucasians. Cancer Epidemiol Biomarkers Prev 1998; 7:203-6.
19. Weatherall IL, Coombs BD. Skin color measurements in terms of CIELAB color space values. J Invest Dermatol 1992; 99:468-73.
20. Strachan DP. Family size, infection and atopy: the first decade of the "hygiene hypothesis". Thorax 2000; 55 (Suppl. 1):S2-S10.
21. Landtblom AM. Epidemiological and radiological aspects of multiple sclerosis.
Departments of Clinical Neuroscience and Occupational and Environmental Medicine. Linkoping: University Hospital, 1996.
22. Hodge A, Patterson AJ, Brown WJ, Ireland P, Giles G. The Anti Cancer Council of Victoria FFQ: relative validity of nutrient intakes compared with weighed food records in young to middle-aged women in a study of iron supplementation. Aust N Z J Public Health 2000; 24:576-83.
23. Kelly JP, Nichols JS, Filley CM, Lillehei KO, Rubinstein D, Kleinschmidt-DeMasters BK. Concussion in sports. Guidelines for the prevention of catastrophic outcome. JAMA 1991; 266:2867-9.
24. Blizzard L, Dwyer T. Case-control study of lung cancer during 1994-1997 in the birth cohort in Tasmania, Australia, with an excess of female cases during 1983-1992. Cancer Causes Control 2003; 14:123-9.
25. Brooks DR, Palmer JR, Strom BL, Rosenberg L. Menthol cigarettes and risk of lung cancer. Am J Epidemiol 2003; 158:609-16; discussion 617-20.
26. Vartiainen E, Seppala T, Lillsunde P, Puska P. Validation of self reported smoking by serum cotinine measurement in a community-based study. J Epidemiol Community Health 2002; 56:167-70.
27. Standen A, Fletcher N, Meischke M. Smarter Hearts - A community' Response to Cardiovascular Health: Burnie Take Heart Project. Hobart: Menzies Centre for Population Health Research. National Library of Australia Cataloguing in Publication data, 1992.
28. Hosmer DW, Lemeshow S. Applied logistic regression. New York: John Wiley & sons inc., 2000.
29. Rothman K, Greenland S. Matching. In: Rothman K, Greenland S, eds. Modern Epidemiology. Philadelphia: Lippincott-Raven Publishers, 1998:147-162.
30. Cox DR. Two further applications of a model for binary regression. Biometrika 1958; 45:562-565.
31. Miettinen OS. Estimation of relative risk from individually matched series. Biometrics 1970; 26:75-86.
32. Rothman KJ, Greenland S. Modern epidemiology. Philadelphia: Lippincott-Raven Publishers, 1998.