Rationale & Model for the Present Research

This section presents the rationale and context of the present study, elaborating the choice of study design, the components and make u p of the research model, as well as considering the influence of confounding variables. The present study was based on secondary data analysis of the W hitehall II Study, a cohort m ade u p of London-based civil servants. As the cohort includes both m en and women, w ith age limits of 35 to 55 years, it provides an opportunity to examine w hether psychological distress is

associated w ith increased risk of cancer incidence, thereby complementing the existing cohort literature (see section 1.2.3). Moreover, there is the opportunity to investigate the possibility of an indirect association and assess the function of health behaviours as explanatory variables in any relationship between psychological distress and cancer incidence.

2.3.1 M odel Com ponents

The components of the model for the present study include the independent variable (psychological distress), the explanatory variables (health behaviours), key

confounders (age, sex and socioeconomic status), other risk factors for cancer (family history and for women, reproductive factors) and the dependent variable, cancer. The health behaviours of interest include smoking, alcohol use, diet and exercise. Each of these have, in some measure, recognised associations w ith cancer risk (Schottenfeld & Fraum eni 1996). Key confounders include age, sex and socioeconomic status, as each of these m ight be expected to have an effect on both the independent and dependent variables (as well as on the explanatory variables) and this issue deserves particular com m ent (see 2.3.3 below).

2.3.1.1 D epression & psychological distress

The m ain m easure of psychiatric morbidity used in the W hitehall 11 Study was the 30- item General Health Questionnaire (GHQ; Goldberg 1972). The GHQ has been

adm inistered at regular intervals since baseline. As a screening questionnaire, the 30- item GHQ does not provide a clinical diagnosis but gives a score which serves as 'a rough proxy m easure of the position of that individual on the hypothetical underlying dimension of psychiatric illness' (Goldberg & W illiams 1988, p.8).The GHQ was designed to detect inability to carry out norm al functions and the appearance of new

and distressing phenomena. However, it is a 'p u re state m easure' (Goldberg & W illiams 1988, p. 9) and could miss less transient psychological disorder. It w ould be difficult to argue for a short-lived exposure to have any reasonable effect on

carcinogenesis. One strategy for detecting longstanding disorders is to use the CGHQ scoring convention developed by Goodchild and Duncan-Jones (1985) in place of the conventional GHQ scoring. This scoring m ethod is sensitive to m ore chronic disorder or distress and has several advantages including producing a more norm al distribution of scores and the scores obtained correlate better w ith other m easures of psychiatric illness, such as the Present State Examination (Goodchild & Duncan-Jones 1985).

Thus psychological distress rather than depression is the focus for the present study, implying a dimensional rather than categorical approach. A nd while earlier studies have presented findings in the Whitehall II Study using the GHQ (Stansfeld & M arm ot 1992), the prevalence of psychological distress assessed using the CGHQ m ethod has not been reported to date. A sub-scale assessing depressive sym ptom s deriving from the GHQ (Ferrie 1999; Stansfeld et al. 1995; Stansfeld, Head, & M arm ot 1998) was also available, which allowed for some comparison w ith the psychological distress

measure.

2.3.1.2 N um bers of cancer events over follow up

Particular characteristics of the Whitehall II cohort m ight serve to limit the num ber of cancer cases to be expected during the follow-up period. Some reasons w hy one m ight expect fewer cancer cases include the healthy w orker effect, length of follow-up and the completeness of registration data, as well as the specific age characteristics of the cohort.

As previously discussed, it is not sound practice to lum p all cancers together into one dichotom ous outcome variable irrespective of site, such as 'cancer'/'no cancer' (Fox 1978; Perrin & Pierce 1959) and ideally analysis should be of risk in relation to single sites. In addition to the features of Whitehall II m entioned above, m ost cancers are relatively rare (Breslow & Day 1987) and so there were legitimate grounds to be

concerned as to w hether there w ould be sufficient num bers of any one site for analysis. It seemed expedient therefore to group cancers of different sites together according to

common aetiological features, relating those groupings in tu rn to the explanatory variables of the p resent investigation. This method has been used in other cohort studies to investigate cancer risk associated w ith childhood energy intake (Davey Smith, Shipley, & Leon 1998) and height (Gunnell et al. 1998) and w ith respect to depression in the W ashington County Study (Linkins & Comstock 1990).

The fundam ental logic to grouping cancers of different sites depends upo n evidence of the commonality of an aetiological factor and its relationship to the explanatory

variables m the present research (principally health behaviours such as smoking, alcohol use, diet, as well as reproductive factors am ongst women). The full rationale and literature review for the grouping of cancer sites used in the present study is available in A ppendix I. It was not supposed that the groups themselves should have achieved H ill's criteria of causation (Hill 1965), but that the rationale for placing an individual cancer site w ithin a group was based on robust evidence.

H owever, while one factor m ight be established as having the effect of increasing cancer risk, other aetiological factors m ight interact, or act independently either to reduce risk or increase it further. For example, the synergistic effect of smoking and alcohol use observed for risk for cancer of the oesophagus is well recognised (Baron & Rohan 1996). Similarly, if an individual's occupation presents an increased risk for carcinogenic exposures, the addition of smoking will elevate the risk of cancer. But consider diet: the consum ption of fruit and vegetables and vitam in A is protective, and reduces cancer risk in smokers as opposed to those w ith a lower intake of these

nutrients. Therefore factors associated w ith a reduction in risk for particular sites are also explored in A ppendix I, and where possible, these effects are taken into account in the analyses. As well as identifying key groupings of cancers, the overall grouping scheme perm its useful conceptualisation of risk and protective factors.

2.3.2 Choice of Study D esign

The W hitehall II Study is a longitudinal cohort that has been followed prospectively since 1985—88, bearing all the advantages of such a design, including estimates of absolute risk, as well as possessing a wealth of covariate and exposure information relevant for studying the relationship between exposure to psychological distress and

subsequent developm ent of disease. Since there were data on person-time and cancer events w ithin the sample, the m ost appropriate technique for addressing this research question w ould be a survival regression technique (e.g. Cox's regression). But the num ber of cancer cases accrued by the end of follow up m ay prove too few for the analysis to be viable: relative risk may be high for a given exposure (i.e. psychological distress), b u t the incidence of cancer too low to be informative (Breslow & Day 1987). N or can follow up time be extended for this thesis.

Alternative design strategies include the nested case-control design (Liddell,

McDonald, & Thomas 1977; M antel 1973), Prentice's case-cohort design (Prentice 1986) and the two-phase design (Cain & Breslow 1988). Indeed, there is evidence which indicates that these alternative approaches to full cohort analysis drastically reduce sample size requirements bu t w ith little cost to statistical efficiency (Wacholder, Gail, & Pee 1991). However, the m ain strategy for the present study was secondary data

analysis and it was not possible to elicit more information from participants than was already available. Therefore, of these approaches, the tw o-phase design, which depends on further data collection, was ruled inappropriate.

The case-cohort design (Prentice 1986), entails selection of a single unm atched control sample at random from the entire cohort at entry and uses Cox's regression to compare each case w ith a subset of controls still at risk at the tim e each case occurred (Thomas 1998). But overall cancer incidence may be overlooked using this approach and analysis complicated by the dependency between contributions from each case- subcohort comparison (Thomas 1998; W acholder et al. 1992).

The m ost prom ising alternative m ethod is the nested case-control design. For each case, controls are chosen from 'those members of the cohort who are at risk at that moment, in other w ords from the risk set defined by the case' (Clayton & Hills 1993, p. 329). This m ethod avoids m any of the problems of the case-control design whilst retaining the advantages of the cohort method (Austin et al. 1994). The labour and cost of data collection is reduced because the focus is on a sub-sample of the whole sample, although this is a slim advantage in the present study. However, A ustin et al. (1994) cautioned that this method may be unsuitable if the disease is very rare, or if one is

attem pting to evaluate recent exposures or exposures that change over time. Moreover, the precision of the case-control study does not seem greatly enhanced compared w ith the cohort study (Clayton & Hills 1993).

Choosing betw een the alternatives and cohort analysis depends on num erous factors, not least considering the substantive question to be answered, the nature and m easure of the outcome un d er study, and the nature of exposures and covariates and their relation to outcome (Samet & M unoz 1998). The loss of time of event m easurem ent disadvantages m any alternative methods of analysis, even allowing that the dating of cancer incidence can only be an estimate, given that we are unable to determ ine the exact date of disease onset. The choice then betw een cohort and nested case-control analysis is particularly keen. Reasonable objectives for the present research are to make the m ost of the data available, obtain incidence data and enable comparison w ith previous research, i.e. cohort studies. Therefore the cohort design was preferred for the present study.

2.3.3 A Sum m ary of the Influence of Key C onfounders

Depression, like mental disorders in general, is commonly associated w ith low

socioeconomic status (Kessler & Zhao 1999; Levi 1998), although w hether that is due to drift (those w ith mental disorders tending to slip dow n the social classes as they w ould have m ore difficulty w ith employment) or selection (those predisposed to mental disorder have lower than expected educational and occupational attainment) is unclear (Eaton & M untaner 1999). It is also associated w ith being young or very old;

consequently, M irowsky and Ross argue that m iddle age is 'th e best time of life in terms of depression' (Mirowsky & Ross 1999). Finally, although overall rates of

psychopathology do not differ as a function of gender, studies have shown that women tend to have higher rates of depression and anxiety than m en (American Psychiatric Association 1994; Wittchen, Knauper, & Kessler 1994), although depression in wom en is not necessarily more chronic than in men (Kessler & Zhao 1999).

Variations in patterns of social class and cancer m orbidity and m ortality have been observed, w ith an overall negative social gradient apparent for cancer mortality in the UK (Faggiano et al. 1997). Principal sites where this effect has been found am ongst men

include cancers of the mouth, larynx, lung and stomach. A similar pattern has been found in w om en in all cancer sites combined and in cervical cancer; no clear gradient is apparent for colon and other cancers, although a positive relationship has been found w ith melanoma. Cancers of the breast, endom etrium and ovaries tend to be more common in w om en of higher socioeconomic status (Henderson, Pike, & et al. 1984; Silva & Beral 1997), typically reflecting later age at first birth and lower achieved parity w ith consequent variation in horm one exposure in these women. In contrast, cervical cancer is consistently associated w ith lower socioeconomic status, presum ably reflecting differences in sexual behaviour and exposure to varieties of the hum an papillom a virus (Silva & Beral 1997).

While the pattern of tobacco smoking by class has changed over the past 40 years in the UK, being predom inantly a habit of the upper classes in the 1940's, it was common to all classes by the 1950's. Since then there has been a steady decline in smoking in the higher classes, w ith the General Household Survey (1972-88) revealing an inverse gradient w ith social class. The interactive effects of smoking and alcohol intake are well established (Baron & Rohan 1996) and while a strong social gradient for smoking has been observed, the evidence is less strong for alcohol intake. A lthough Koveginas has shown that 25% of m anual versus 10% of non-m anual w orkers are heavy drinkers (Kogevinas 1990), this finding has not been consistently supported by other research in the UK. Others concluded that differences in mortality due to social class gradient in alcohol intake were more likely due to differences in smoking (Moller & Tonnessen 1997).

Finally, there is an unequal distribution of dietary and related risk behaviour across social class, especially w ith respect to fat, meat and alcohol intake and the consum ption of fresh fruit and vegetables, favouring the higher social classes (Potter 1997). Similarly, higher socioeconomic status groups tend to report m ore vigorous activity (Wardie & Griffith 2001). But only 14% of m en and 4% of w om en in the general population take enough exercise to gain m aximum cardiac benefit and a substantial proportion of the population, some 60% of m en and 70% of women, m ay be considered sedentary (DOH 1999).

2.3.4 O th er Key C ovariates

Two further groups of variables deserve comment. In the process of determ ining the association of psychological distress w ith health behaviours, it w ould also be useful to assess how psychological distress was associated w ith other personal health indicators such as longstanding illness or disability, use of medications and self-assessed health^ some of w hich m ay have a bearing on cancer risk. In addition, given the prom inent role of sleep in definitions of depression and psychological distress (APA 1994; Goldberg & Williams 1988), some account of the relationship of sleep w ith psychological distress in the sample w ould be appropriate.

Another group of variables that pertain to cancer risk include family history of cancer; reproductive variables; and to a lesser extent, obesity. Family history of cancer is salient and no t sim ply for those cancers for which genes have been identified (e.g. FAP, some forms of breast cancer) bu t as a general risk factor. Epidemiological studies have shown that close relatives of a cancer patient may be considered to have some elevated risk of developing neoplastic disease at that site, b u t not for all forms of cancer (Li 1996). To a lesser degree, family history m ight indicate the effect of nurture, health behaviours passed from parent to child. A different set of risk factors concern w om en only. Those reproductive risk factors which contribute to horm onal exposure over the lifespan should be assessed in relation to cancer risk of relevant sites, both in term s of endogenous and exogenous hormones. Finally the potential of obesity to be a general risk factor for cancer is gaining credence in the literature (Peto 2001).

2.3.5 Research M odel

The hypothesised model which forms the core of the present study is illustrated in a simplified form in Figure 2.3. A direct relationship betw een psychological distress and cancer is represented by arrow A. Lack of evidence for such an association w ould support the null association, but not exclude the possibility of an indirect association. It is proposed that an indirect relationship exists betw een psychological distress and cancer incidence, m ediated by health behaviours (arrows Bi and B2). The effect of key confounders such as age, gender and socioeconomic status (SES) on the independent and dependent variables as well as the explanatory variables is also indicated and it may be assumed that these confounders will also have an im pact on the other risk factors for cancer. The particulars of this m odel will alter as a function of the exact cancer outcome: for example, reproductive factors should have no bearing on risk of lung cancer in men.

Figure2.3 Core research model: Psychological Distress & Cancer Incidence

Arrow A rep resents a direct association betw een psychological distress & cancer; arrow s Bi and

02 indicate an indirect association b etw een psychological distress & c a n c e r m ediated by health

behaviours. Arrow D indicates the role o f other risk factors, and the line arrow s indicate the influence o f key confounders.