Int. J . Cancer: 45, 604-608 (1990) 0 1990 Wiley-Liss, Inc.
Publication of the International Union Against Cancer Publication de I'Union lnternationale Contre le Cancer
DIETARY FACTORS AND RISK OF PANCREATIC CANCER: RESULTS OF A CANADIAN POPULATION-BASED CASE-CONTROL STUDY M. JAI" and A.B. MILLER^ G.R. 'NCIC Epidemiology Unit, McMurrich Building, 3rd Floor, University of Toronto, 12 Queen's Park Crescent West, Toronto, Ontario M5S 1A8; and 2Department of Preventive Medicine and Biostatistics, University of Toronto, Toronto, Ontario M5S lA8, Canada. Dietary information from a case-control study of pancreatic cancer conducted in Metropolitan Toronto between I983 and 1986 is reported. A total of 249 cases and 505 populationbased controls completed quantitative diet histories from which total caloric intake and the intake of a number of nutrients were estimated. A positive association with total caloric intake was observed with a relative risk of 2.39, 95% confidence interval I. 18-4.83 (highest versus lowest quartile), due primarily to the intake of carbohydrates. Inverse associations were seen with fibre from fruit, vegetable and cereal sources, with a relative of risk of 0.42,0.22-0.78 (highest versus lowest quartile), for total fibre intake.
Cancer of the pancreas is the 4th leading cause of cancer mortality for both males and females in Canada, (National Cancer Institute of Canada, 1989) and is of similar importance in most Western countries. Rates in a number of countries have been increasing (Levin et al., 1981), and migrant studies (Wynder et al., 1973) have shown that risk increases when migrants move from low- to high-risk countries. These factors indicate the probable importance of lifestyle and/or environmental factors in the aetiology of this disease. International variations in the rate of pancreatic cancer have been shown by a number of authors to correlate positively with estimated per capita consumption of a number of food items and groups including fats and oils, sugar, animal protein and animal fat (Maruchi et al., 1977; Gordis, 1980; Yanai et al., 1979; Armstrong et al., 1975; Lea, 1967). Several analytical epidemiological studies (Durbec et a l . , 1983; Gold et al., 1985; Mack et al., 1986; Norell et al., 1986; Falk et al., 1988; Mills et al., 1988) have also found positive associations with foods such as butter, eggs, beef, and daily consumption of grilled and fried meats. In addition, several of these studies have found an inverse association with the consumption of various types of fruits and vegetables (Gold et al., 1985; Mack et al., 1986; Norell et al., 1986; Falk et al., 1988; Mills et al., 1988). This report describes results relating to dietary factors obtained in a population-based case-control study carried out in Toronto, Canada, between January 1983 and December 1986. A quantitative dietary history was used to estimate the daily intake of several nutrients and other dietary factors. Results relating to smoking, coffee and alcohol consumption, and a number of other non-dietary factors, will be reported separately. Several other case-control studies using the same protocol were simultaneously conducted in other cities in Canada and in other counties, under the auspices of the International Agency for Research on Cancer SEARCH programme. These studies were designed to be independent, and to be of adequate size to allow investigation of the major hypotheses of interest. It is planned to carry out a comparative analysis among the various studies in order to examine the consistency of results, and this combined analysis will also be reported subsequently. MATERIAL AND METHODS
Case ascertainment Potential cases consisted of all newly incident cases of can-
cer of the pancreas diagnosed in 20 Toronto hospitals between January 1983 and October 1986. These hospitals treat the great majority of pancreatic cancer patients diagnosed in Toronto. Cases were restricted to those aged 35-79 who were resident within the greater Metropolitan Toronto area. A total of 547 such cases were identified, interview data being obtained for 249 of these. Of the remaining 298, 20 were not interviewed because their physicians refused, 141 because the patient or a proxy relative refused, 67 could not be traced, 51 did not have a suitable proxy, 5 had language problems and 14 were too ill. Histological confirmation of diagnosis was obtained for 172 (69%) of the 249 cases, with diagnoses of the remainder being made clinically or radiologically. Control selection Controls, individually matched by sex and age (5 years), were chosen randomly from population lists of individuals resident in the same study area as the cases. Two non-proxy controls were interviewed for each case under 60 years of age and one non-proxy control for those over age 60. A total of 1,636 potential non-proxy and proxy controls were approached, of whom 505 were interviewed. Of the remainder, 564 were not interviewed due to subject refusal, while 567 could not be contacted. Proxy respondents Interviews were conducted with patients in their homes following discharge from hospital. To allow patients time to readjust after hospitalization and therapy, interviews were planned to take place approximately 3 months after diagnosis. However, because of the high mortality rate, a substantial proportion of patients died during this interval, and others were too sick to participate. Therefore, it became necessary to make use of proxy data for such cases, and the interview was conducted for these subjects with (in order of preference) spouses, daughters, sons, sisters, and brothers. Of the 249 cases, 194 were interviewed by proxy, and of these proxy interviews, 62% were with the spouse, 31% with daughters and sons, and 7% with others. In an attempt to compensate for any bias which use of proxy data might introduce, a proxy control was also obtained for each case interviewed by proxy. The letter, which was sent to such potential controls, requested that they allow their spouse, or other close relative, to answer the proxy questionnaire. A total of 194 such controls were used in the study, data for 72% being obtained from spouses, 19% from daughters and sons, and 9% from others. The decision to use proxy controls was not made until after the study had been started, when it became apparent that a large proportion of the cases would need proxy interviews. Therefore, there is some imbalance in the female/male ratio for proxy cases, as compared to proxy controls. As described below, stratification by proxy
3T0whom reprint requests should be sent. Received: October 16, 1989 and in revised form December 16, 1989.
605
DIET A N D PANCREATIC CANCER RISK I N CANADA
status and sex was used in the analysis, so this difference does not bias the results. Interview
After identification of cases and controls, and after permission to approach the cases had been obtained from their physicians, letters were sent introducing the study as one of diet and health, requesting permission for an interviewer to carry out an in-person interview in the subject’s home. The letter was followed by telephone contact by the interviewer in order to make arrangements for the interview. Up to 6 telephone calls were carried out in the attempt to establish contact with the potential study subject. The interview was conducted by specially trained interviewers with considerable experience in such studies, with quality control being maintained by study supervisory staff. The questionnaire contained a number of questions relating to demographic characteristics, smoking, coffee, tea and alcohol consumption and a number of other postulated risk factors. In addition, a complete diet history was administered in which the usual frequency of intake of over 200 food items was ascertained. Quantification of the amount normally consumed was by use of physical food models. This diet history has been described in detail (Morgan et al., 1978; Jain, 1989) and has been subjected to both validity and reliability studies (Jain et al., 1980a,b).The food items in the questionnaire cover the great majority of foods found in the usual Canadian diet. Questions concerned the diet 1 to 2 years before interview, in order to overcome any changes in diet among the cases due to the onset of their disease. The dietary data were converted to the estimated daily intake of calories, and a number of other dietary factors using a database based on the US Department of Agriculture Handbook 8 (US Department of Agriculture, 1972), considerably expanded to take into account values for Canadian foods. Statistical analysis
Data were stratified into 28 sets consisting of the possible combinations of sex (2 categories), proxy status (2 categories), and age group (7 categories, 0-49, 50-54, . . . 70-74, 75 or more). Conditional logistic regression was then used to estimate relative risks and their confidence intervals, and to carry out tests of statistical significance. In order to reduce the problem of outliers, values of dietary variables more than 3 times the standard deviation from the mean on the log scale were eliminated from analysis. This procedure generally excluded less than 1% of study subjects. Relative risks are generally presented by quartile for each dietary factor, these quartiles being based on the distribution for all study subjects to ensure comparability, for example, between the sexes. Data are also presented in which the dietary factors are expressed as continuous variables in the logistic regression model. In this case, the unit chosen for presentation is the difference between the mean for the highest quartile and the mean for the lowest quartile for that factor. Thus, these estimates represent approximately the relative risk between highest and lowest quartiles. Tests of interaction of effects with both sex and proxy status were routinely computed, and these are reported where the effect is large or statistically significant. All logistic regression models include the variable pack-years of cigarette smoking, since smoking is a strong predictor of risk in the present data. Alternative methods for representing the smoking effect, e.g. inclusion of separate terms for average frequency and duration, led to virtually identical results to those presented in the present report for all dietary variables. Allp-values quoted are 2-sided. RESULTS
Table I shows the age, sex, and proxy distribution of cases and controls. Mean height, weight and body mass index
(weight/height*) for cases and controls are compared in Table 11. Data are shown separately for each of the 4 subgroups, namely male non-proxy and proxy, and female non-proxy and proxy respondents. Weight refers to the subject’s weight in kilograms 2 years prior to interview. Cases are slightly taller than controls, but none of these differences are large or statistically significant. The data for weight and body mass index show no consistent pattern among the subgroups, and again differences are small and none approach conventional levels of statistical significance. Analyses using the maximum lifetime weight reported by study subjects gave results very similar to those in Table 11, though case-control differences were even smaller. Logistic regression models using the height, weight and body-mass index parameters also led to small and nonstatistically significant relative risks (data not shown). Thus, the present data do not support any association between these factors and risk of pancreatic cancer. Table I11 presents mean estimated daily intake of kilocalories for cases and controls within the 4 subgroups defined by sex and proxy status. The mean intake among controls varies substantially within these 4 subgroups with females and proxy respondents reporting substantially lower intakes. For all 4 subgroups, cases reported a higher mean intake than did the corresponding controls, with the excess ranging from 408 kCal for male non-proxy respondents, to 103 kCal for female proxy respondents. None of these differences achieve a formal level of statistical significance of 0.05, though the value for male proxy respondents approaches this level (p = 0.06).Estimates of relative risk for all study subjects combined, for the 2nd, 3rd, and 4th quartiles of daily caloric intake compared to the lowest quartile are 1.24, 1.33 and 1.56 respectively, and this trend is statistically significant (p = 0.024). However, when this association with caloric intake was examined using models which included other dietary components and other non-dietary factors as possible confounders, the positive association with caloric intake was strengthened by the inclusion of terms corresponding to estimated daily dietary fibre intake. Fibre itself showed a weak inverse association with risk, with the upper 3 quartiles of intake having relative risks of 0.75, 0.83 and 0.64 respectively, this trend also being statistically significant (p = 0.023). Inclusion of both caloric intake and fibre intake simultaneously in a logistic regression model led to a substantial strengthening both of the positive association with caloric intake and the inverse association with fibre intake (Table IV). Both caloric and fibre intake have highly statistically significant trends (p < 0.001). It was necessary to adjust for cigarette smoking in this model, since such adjustment reduces the associations with both caloric and fibre intakes. As shown in Table V, the associations with both caloric and fibre intakes were stronger among proxy than among nonproxy subjects. Estimates for the highest vs. lowest quartile of intake are shown, based on modelling intakes using continuous variables in a logistic regression model. A formal test of interaction of proxy status with caloric intake and fibre intake using this model gavep values of 0.09 and 0.05, respectively. TABLE I - DISTRIBUTION AND MEAN AGE OF CASES AND CONTROLS BY SEX AND PROXY STATIJS
Males Non-proxy
Number of cases Number of controls Mean age of cases Mean age of controls
27 153
Females Roxy
114 117
Non-proxy
28 158
Proxy
80 77
Total
249 505
60.7
64.4
63.1
66.6
64.6
62.7
65.8
64.4
68.1
64.8
606
H O W E ET AL.
TABLE I1 - MEAN HEIGHT, WEIGHT, WEIGHT/HEIGHTZ FOR CASES AND CONTROLS BY SEX AND PROXY STATUS Males
Height (metre), cases Height (metre), controls Difference Standard error of difference p value Weight (kg), cases Weight (kg), controls Difference Standard error of difference p value Weighvheightl (kg/m2), cases Weight/heightz(kg/m2), controls Difference Standard error of difference D value
Females
Non-proxy
Proxy
Non-proxy
Proxy
1.766 1.742 0.024 0.015 0.12 82.58 78.47 4.11 2.55 0.11 26.58 25.81 0.76 0.72 0.29
1.741 1.736 0.005 0.010 0.58 76.65 77.22 -0.58 1.66 0.73 25.24 25.55 -0.31 0.49 0.53
1.616 1.614 0.002 0.001 0.88 61.63 63.28 - 1.65 2.27 0.47 23.48 24.32 -0.84 0.86 0.33
1.622 1.617 0.005 0.01 1 0.66 62.47 64.18 - 1.71 2.03 0.40 23.77 24.69 -0.92 0.80 0.25
leads to a x24of 0.94, p (2-sided) = 0.92. However, a formal test of the difference in effect between carbohydrates and other Males Females sources of calories results in a p-value of 0.18, so it is not possible to reject the null hypothesis that carbohydrates and Non-nroxv Proxv NOn-DrOxv Proxv other sources of calories have an equal effect on risk. KCaUday, cases 3,495 2,893 2,155 1,922 A number of logistic regression models were constructed to KCaUday, controls 3,087 2,653 2,031 1,819 examine the possible confounding effect of other factors on the 103 240 123 Difference 408 associations with caloric and fibre intakes shown in Tables IV 119 129 175 Standard error of 276 and V. The point estimates are essentially unaffected by includifference sion of other nutrients, alternative measures of smoking, coffee 0.06 0.48 0.39 p value 0.14 and alcohol consumption, height, weight, body-mass index, and a number of socio-demographic factors, including educaWhen examining the contribution to the total caloric asso- tion. In particular, when the analysis was restricted to the 597 ciation by those individual nutrients which contribute to caloric subjects who reported no or little dietary change in the 10 years intake, it is essential to consider the potential confounding prior to interview, the relative risks for highest vs. lowest effect of the remaining sources of calories (Willett and quartile (based on the continuous model) for caloric and fibre Stampfer, 1986; Howe et al., 1986). The nutrients in question intake are 2.73 @ trend = 0.003) and 0.29 (p trend = in the present context are total fat and its components, protein, 0.0004), respectively. The independent effects of vegetable, fruit and fibre intakes and carbohydrate. The strategy followed in the present analysis is that proposed by Howe (1989). The data are first examined were also examined. Inclusion of vegetable intake in a model for evidence of a total caloric association and, if this is found, containing fibre, calories and lifetime cigarette consumption 2 logistic regression models are constructed for each nutrient. gave a relative risk of 1.03 comparing the highest to lowest The first model includes the nutrient itself, together with a term quartile of vegetable consumption (274 g/day), with 95% concorresponding to other sources of calories (Howe et al., 1986). fidence interval 0.79-1.34. The same approach for fruit intake The coefficient of the nutrient represents the effect of that yielded a relative risk of 0.92 per 273 g/day of fruit, with 95% nutrient independent of other sources of calories, i.e., uncon- confidence interval 0.74-1.14. For both these last two models, founded by those other sources. The second model (Willett and the relative risks for calories and fibre were essentially unafStampfer, 1986; Pike et al., 1989) includes both the nutrient fected by inclusion of the term for vegetable and fruit intake. itself and total calories from all sources, and the coefficient of Estimates of fibre intake from fruits, vegetables and cereals the nutrient in this model tests the dizerence in effect between were computed separately for all study subjects. When included simultaneously in a logistic regression model the relathe nutrient and other sources of calories. A number of logistic regression models were constructed tive risk estimates per 28 g of fibre per day are 0.38 for fibre according to these principles. The results are best summarized from fruit, 0.56 for fibre from vegetables, and 0.22 for fibre by the model shown in Table VI, in which the 5 major dietary from cereals. Table VII shows estimated relative risks for the highest vs. components contributing to caloric intake (protein, carbohydrate, saturated, mono-unsaturated, and poly-unsaturated fat) lowest quartile of consumption of a number of other dietary were included simultaneously in a single regression model. factors. All these analyses are controlled for caloric and fibre Although such a model may be subject to instability, because intake, and lifetime cigarette consumption. There is no eviof the simultaneous inclusion of a number of highly correlated dence of any substantial association of risk with any of these variables, the results shown in Table VI are consistent with dietary factors, the smallest p-value being 0.17 for the weak those obtained using other models with fewer variables in- inverse association with nitrite intake. Examination of the data cluded simultaneously. It is clear that the primary contribution relating to supplementary vitamin intake, particularly for vitato the positive association observed with total caloric intake mins A and C, also showed no association with risk of pancomes from a positive association with carbohydrate intake. creatic cancer (data not shown). The questionnaire also contained a number of qualitative There is little evidence for a positive association with other sources of calories. In fact, a model which includes only car- questions relating to changes in consumption of a number of bohydrates and no other sources of calories fits the data almost food products during the 10 years prior to interview. These as well as the full model shown in Table VI, with 4 fewer food products included meat, poultry, fish, eggs, butter, raw degrees of freedom. Inclusion of the 4 extra terms in the model and cooked vegetables, and fruit. The response to each quesTABLE 111- MEAN DAILY CALORIC INTAKE OF CASES AND CONTROLS BY SEX AND PROXY STATUS
607
DIET A N D PANCREATIC CANCER RISK I N C A N A D A
TABLE IV - RELATIVE RISKS OF PANCREATIC CANCER BY QUARTILES OF DAILY CALORIC AND FIBRE INTAKE' Quartiles Variable
KCaVday
2
1
Range 3,009 2.39 1.184.83
0.00044
21.7-29.3 0.65 0.38-1.13
>29.3 0.42 0.22-0.78
0.00039
interval
Fibre glday Range Relative risk 95% confidence interval
Publication of the International Union Against Cancer Publication de I'Union lnternationale Contre le Cancer
DIETARY FACTORS AND RISK OF PANCREATIC CANCER: RESULTS OF A CANADIAN POPULATION-BASED CASE-CONTROL STUDY M. JAI" and A.B. MILLER^ G.R. 'NCIC Epidemiology Unit, McMurrich Building, 3rd Floor, University of Toronto, 12 Queen's Park Crescent West, Toronto, Ontario M5S 1A8; and 2Department of Preventive Medicine and Biostatistics, University of Toronto, Toronto, Ontario M5S lA8, Canada. Dietary information from a case-control study of pancreatic cancer conducted in Metropolitan Toronto between I983 and 1986 is reported. A total of 249 cases and 505 populationbased controls completed quantitative diet histories from which total caloric intake and the intake of a number of nutrients were estimated. A positive association with total caloric intake was observed with a relative risk of 2.39, 95% confidence interval I. 18-4.83 (highest versus lowest quartile), due primarily to the intake of carbohydrates. Inverse associations were seen with fibre from fruit, vegetable and cereal sources, with a relative of risk of 0.42,0.22-0.78 (highest versus lowest quartile), for total fibre intake.
Cancer of the pancreas is the 4th leading cause of cancer mortality for both males and females in Canada, (National Cancer Institute of Canada, 1989) and is of similar importance in most Western countries. Rates in a number of countries have been increasing (Levin et al., 1981), and migrant studies (Wynder et al., 1973) have shown that risk increases when migrants move from low- to high-risk countries. These factors indicate the probable importance of lifestyle and/or environmental factors in the aetiology of this disease. International variations in the rate of pancreatic cancer have been shown by a number of authors to correlate positively with estimated per capita consumption of a number of food items and groups including fats and oils, sugar, animal protein and animal fat (Maruchi et al., 1977; Gordis, 1980; Yanai et al., 1979; Armstrong et al., 1975; Lea, 1967). Several analytical epidemiological studies (Durbec et a l . , 1983; Gold et al., 1985; Mack et al., 1986; Norell et al., 1986; Falk et al., 1988; Mills et al., 1988) have also found positive associations with foods such as butter, eggs, beef, and daily consumption of grilled and fried meats. In addition, several of these studies have found an inverse association with the consumption of various types of fruits and vegetables (Gold et al., 1985; Mack et al., 1986; Norell et al., 1986; Falk et al., 1988; Mills et al., 1988). This report describes results relating to dietary factors obtained in a population-based case-control study carried out in Toronto, Canada, between January 1983 and December 1986. A quantitative dietary history was used to estimate the daily intake of several nutrients and other dietary factors. Results relating to smoking, coffee and alcohol consumption, and a number of other non-dietary factors, will be reported separately. Several other case-control studies using the same protocol were simultaneously conducted in other cities in Canada and in other counties, under the auspices of the International Agency for Research on Cancer SEARCH programme. These studies were designed to be independent, and to be of adequate size to allow investigation of the major hypotheses of interest. It is planned to carry out a comparative analysis among the various studies in order to examine the consistency of results, and this combined analysis will also be reported subsequently. MATERIAL AND METHODS
Case ascertainment Potential cases consisted of all newly incident cases of can-
cer of the pancreas diagnosed in 20 Toronto hospitals between January 1983 and October 1986. These hospitals treat the great majority of pancreatic cancer patients diagnosed in Toronto. Cases were restricted to those aged 35-79 who were resident within the greater Metropolitan Toronto area. A total of 547 such cases were identified, interview data being obtained for 249 of these. Of the remaining 298, 20 were not interviewed because their physicians refused, 141 because the patient or a proxy relative refused, 67 could not be traced, 51 did not have a suitable proxy, 5 had language problems and 14 were too ill. Histological confirmation of diagnosis was obtained for 172 (69%) of the 249 cases, with diagnoses of the remainder being made clinically or radiologically. Control selection Controls, individually matched by sex and age (5 years), were chosen randomly from population lists of individuals resident in the same study area as the cases. Two non-proxy controls were interviewed for each case under 60 years of age and one non-proxy control for those over age 60. A total of 1,636 potential non-proxy and proxy controls were approached, of whom 505 were interviewed. Of the remainder, 564 were not interviewed due to subject refusal, while 567 could not be contacted. Proxy respondents Interviews were conducted with patients in their homes following discharge from hospital. To allow patients time to readjust after hospitalization and therapy, interviews were planned to take place approximately 3 months after diagnosis. However, because of the high mortality rate, a substantial proportion of patients died during this interval, and others were too sick to participate. Therefore, it became necessary to make use of proxy data for such cases, and the interview was conducted for these subjects with (in order of preference) spouses, daughters, sons, sisters, and brothers. Of the 249 cases, 194 were interviewed by proxy, and of these proxy interviews, 62% were with the spouse, 31% with daughters and sons, and 7% with others. In an attempt to compensate for any bias which use of proxy data might introduce, a proxy control was also obtained for each case interviewed by proxy. The letter, which was sent to such potential controls, requested that they allow their spouse, or other close relative, to answer the proxy questionnaire. A total of 194 such controls were used in the study, data for 72% being obtained from spouses, 19% from daughters and sons, and 9% from others. The decision to use proxy controls was not made until after the study had been started, when it became apparent that a large proportion of the cases would need proxy interviews. Therefore, there is some imbalance in the female/male ratio for proxy cases, as compared to proxy controls. As described below, stratification by proxy
3T0whom reprint requests should be sent. Received: October 16, 1989 and in revised form December 16, 1989.
605
DIET A N D PANCREATIC CANCER RISK I N CANADA
status and sex was used in the analysis, so this difference does not bias the results. Interview
After identification of cases and controls, and after permission to approach the cases had been obtained from their physicians, letters were sent introducing the study as one of diet and health, requesting permission for an interviewer to carry out an in-person interview in the subject’s home. The letter was followed by telephone contact by the interviewer in order to make arrangements for the interview. Up to 6 telephone calls were carried out in the attempt to establish contact with the potential study subject. The interview was conducted by specially trained interviewers with considerable experience in such studies, with quality control being maintained by study supervisory staff. The questionnaire contained a number of questions relating to demographic characteristics, smoking, coffee, tea and alcohol consumption and a number of other postulated risk factors. In addition, a complete diet history was administered in which the usual frequency of intake of over 200 food items was ascertained. Quantification of the amount normally consumed was by use of physical food models. This diet history has been described in detail (Morgan et al., 1978; Jain, 1989) and has been subjected to both validity and reliability studies (Jain et al., 1980a,b).The food items in the questionnaire cover the great majority of foods found in the usual Canadian diet. Questions concerned the diet 1 to 2 years before interview, in order to overcome any changes in diet among the cases due to the onset of their disease. The dietary data were converted to the estimated daily intake of calories, and a number of other dietary factors using a database based on the US Department of Agriculture Handbook 8 (US Department of Agriculture, 1972), considerably expanded to take into account values for Canadian foods. Statistical analysis
Data were stratified into 28 sets consisting of the possible combinations of sex (2 categories), proxy status (2 categories), and age group (7 categories, 0-49, 50-54, . . . 70-74, 75 or more). Conditional logistic regression was then used to estimate relative risks and their confidence intervals, and to carry out tests of statistical significance. In order to reduce the problem of outliers, values of dietary variables more than 3 times the standard deviation from the mean on the log scale were eliminated from analysis. This procedure generally excluded less than 1% of study subjects. Relative risks are generally presented by quartile for each dietary factor, these quartiles being based on the distribution for all study subjects to ensure comparability, for example, between the sexes. Data are also presented in which the dietary factors are expressed as continuous variables in the logistic regression model. In this case, the unit chosen for presentation is the difference between the mean for the highest quartile and the mean for the lowest quartile for that factor. Thus, these estimates represent approximately the relative risk between highest and lowest quartiles. Tests of interaction of effects with both sex and proxy status were routinely computed, and these are reported where the effect is large or statistically significant. All logistic regression models include the variable pack-years of cigarette smoking, since smoking is a strong predictor of risk in the present data. Alternative methods for representing the smoking effect, e.g. inclusion of separate terms for average frequency and duration, led to virtually identical results to those presented in the present report for all dietary variables. Allp-values quoted are 2-sided. RESULTS
Table I shows the age, sex, and proxy distribution of cases and controls. Mean height, weight and body mass index
(weight/height*) for cases and controls are compared in Table 11. Data are shown separately for each of the 4 subgroups, namely male non-proxy and proxy, and female non-proxy and proxy respondents. Weight refers to the subject’s weight in kilograms 2 years prior to interview. Cases are slightly taller than controls, but none of these differences are large or statistically significant. The data for weight and body mass index show no consistent pattern among the subgroups, and again differences are small and none approach conventional levels of statistical significance. Analyses using the maximum lifetime weight reported by study subjects gave results very similar to those in Table 11, though case-control differences were even smaller. Logistic regression models using the height, weight and body-mass index parameters also led to small and nonstatistically significant relative risks (data not shown). Thus, the present data do not support any association between these factors and risk of pancreatic cancer. Table I11 presents mean estimated daily intake of kilocalories for cases and controls within the 4 subgroups defined by sex and proxy status. The mean intake among controls varies substantially within these 4 subgroups with females and proxy respondents reporting substantially lower intakes. For all 4 subgroups, cases reported a higher mean intake than did the corresponding controls, with the excess ranging from 408 kCal for male non-proxy respondents, to 103 kCal for female proxy respondents. None of these differences achieve a formal level of statistical significance of 0.05, though the value for male proxy respondents approaches this level (p = 0.06).Estimates of relative risk for all study subjects combined, for the 2nd, 3rd, and 4th quartiles of daily caloric intake compared to the lowest quartile are 1.24, 1.33 and 1.56 respectively, and this trend is statistically significant (p = 0.024). However, when this association with caloric intake was examined using models which included other dietary components and other non-dietary factors as possible confounders, the positive association with caloric intake was strengthened by the inclusion of terms corresponding to estimated daily dietary fibre intake. Fibre itself showed a weak inverse association with risk, with the upper 3 quartiles of intake having relative risks of 0.75, 0.83 and 0.64 respectively, this trend also being statistically significant (p = 0.023). Inclusion of both caloric intake and fibre intake simultaneously in a logistic regression model led to a substantial strengthening both of the positive association with caloric intake and the inverse association with fibre intake (Table IV). Both caloric and fibre intake have highly statistically significant trends (p < 0.001). It was necessary to adjust for cigarette smoking in this model, since such adjustment reduces the associations with both caloric and fibre intakes. As shown in Table V, the associations with both caloric and fibre intakes were stronger among proxy than among nonproxy subjects. Estimates for the highest vs. lowest quartile of intake are shown, based on modelling intakes using continuous variables in a logistic regression model. A formal test of interaction of proxy status with caloric intake and fibre intake using this model gavep values of 0.09 and 0.05, respectively. TABLE I - DISTRIBUTION AND MEAN AGE OF CASES AND CONTROLS BY SEX AND PROXY STATIJS
Males Non-proxy
Number of cases Number of controls Mean age of cases Mean age of controls
27 153
Females Roxy
114 117
Non-proxy
28 158
Proxy
80 77
Total
249 505
60.7
64.4
63.1
66.6
64.6
62.7
65.8
64.4
68.1
64.8
606
H O W E ET AL.
TABLE I1 - MEAN HEIGHT, WEIGHT, WEIGHT/HEIGHTZ FOR CASES AND CONTROLS BY SEX AND PROXY STATUS Males
Height (metre), cases Height (metre), controls Difference Standard error of difference p value Weight (kg), cases Weight (kg), controls Difference Standard error of difference p value Weighvheightl (kg/m2), cases Weight/heightz(kg/m2), controls Difference Standard error of difference D value
Females
Non-proxy
Proxy
Non-proxy
Proxy
1.766 1.742 0.024 0.015 0.12 82.58 78.47 4.11 2.55 0.11 26.58 25.81 0.76 0.72 0.29
1.741 1.736 0.005 0.010 0.58 76.65 77.22 -0.58 1.66 0.73 25.24 25.55 -0.31 0.49 0.53
1.616 1.614 0.002 0.001 0.88 61.63 63.28 - 1.65 2.27 0.47 23.48 24.32 -0.84 0.86 0.33
1.622 1.617 0.005 0.01 1 0.66 62.47 64.18 - 1.71 2.03 0.40 23.77 24.69 -0.92 0.80 0.25
leads to a x24of 0.94, p (2-sided) = 0.92. However, a formal test of the difference in effect between carbohydrates and other Males Females sources of calories results in a p-value of 0.18, so it is not possible to reject the null hypothesis that carbohydrates and Non-nroxv Proxv NOn-DrOxv Proxv other sources of calories have an equal effect on risk. KCaUday, cases 3,495 2,893 2,155 1,922 A number of logistic regression models were constructed to KCaUday, controls 3,087 2,653 2,031 1,819 examine the possible confounding effect of other factors on the 103 240 123 Difference 408 associations with caloric and fibre intakes shown in Tables IV 119 129 175 Standard error of 276 and V. The point estimates are essentially unaffected by includifference sion of other nutrients, alternative measures of smoking, coffee 0.06 0.48 0.39 p value 0.14 and alcohol consumption, height, weight, body-mass index, and a number of socio-demographic factors, including educaWhen examining the contribution to the total caloric asso- tion. In particular, when the analysis was restricted to the 597 ciation by those individual nutrients which contribute to caloric subjects who reported no or little dietary change in the 10 years intake, it is essential to consider the potential confounding prior to interview, the relative risks for highest vs. lowest effect of the remaining sources of calories (Willett and quartile (based on the continuous model) for caloric and fibre Stampfer, 1986; Howe et al., 1986). The nutrients in question intake are 2.73 @ trend = 0.003) and 0.29 (p trend = in the present context are total fat and its components, protein, 0.0004), respectively. The independent effects of vegetable, fruit and fibre intakes and carbohydrate. The strategy followed in the present analysis is that proposed by Howe (1989). The data are first examined were also examined. Inclusion of vegetable intake in a model for evidence of a total caloric association and, if this is found, containing fibre, calories and lifetime cigarette consumption 2 logistic regression models are constructed for each nutrient. gave a relative risk of 1.03 comparing the highest to lowest The first model includes the nutrient itself, together with a term quartile of vegetable consumption (274 g/day), with 95% concorresponding to other sources of calories (Howe et al., 1986). fidence interval 0.79-1.34. The same approach for fruit intake The coefficient of the nutrient represents the effect of that yielded a relative risk of 0.92 per 273 g/day of fruit, with 95% nutrient independent of other sources of calories, i.e., uncon- confidence interval 0.74-1.14. For both these last two models, founded by those other sources. The second model (Willett and the relative risks for calories and fibre were essentially unafStampfer, 1986; Pike et al., 1989) includes both the nutrient fected by inclusion of the term for vegetable and fruit intake. itself and total calories from all sources, and the coefficient of Estimates of fibre intake from fruits, vegetables and cereals the nutrient in this model tests the dizerence in effect between were computed separately for all study subjects. When included simultaneously in a logistic regression model the relathe nutrient and other sources of calories. A number of logistic regression models were constructed tive risk estimates per 28 g of fibre per day are 0.38 for fibre according to these principles. The results are best summarized from fruit, 0.56 for fibre from vegetables, and 0.22 for fibre by the model shown in Table VI, in which the 5 major dietary from cereals. Table VII shows estimated relative risks for the highest vs. components contributing to caloric intake (protein, carbohydrate, saturated, mono-unsaturated, and poly-unsaturated fat) lowest quartile of consumption of a number of other dietary were included simultaneously in a single regression model. factors. All these analyses are controlled for caloric and fibre Although such a model may be subject to instability, because intake, and lifetime cigarette consumption. There is no eviof the simultaneous inclusion of a number of highly correlated dence of any substantial association of risk with any of these variables, the results shown in Table VI are consistent with dietary factors, the smallest p-value being 0.17 for the weak those obtained using other models with fewer variables in- inverse association with nitrite intake. Examination of the data cluded simultaneously. It is clear that the primary contribution relating to supplementary vitamin intake, particularly for vitato the positive association observed with total caloric intake mins A and C, also showed no association with risk of pancomes from a positive association with carbohydrate intake. creatic cancer (data not shown). The questionnaire also contained a number of qualitative There is little evidence for a positive association with other sources of calories. In fact, a model which includes only car- questions relating to changes in consumption of a number of bohydrates and no other sources of calories fits the data almost food products during the 10 years prior to interview. These as well as the full model shown in Table VI, with 4 fewer food products included meat, poultry, fish, eggs, butter, raw degrees of freedom. Inclusion of the 4 extra terms in the model and cooked vegetables, and fruit. The response to each quesTABLE 111- MEAN DAILY CALORIC INTAKE OF CASES AND CONTROLS BY SEX AND PROXY STATUS
607
DIET A N D PANCREATIC CANCER RISK I N C A N A D A
TABLE IV - RELATIVE RISKS OF PANCREATIC CANCER BY QUARTILES OF DAILY CALORIC AND FIBRE INTAKE' Quartiles Variable
KCaVday
2
1
Range 3,009 2.39 1.184.83
0.00044
21.7-29.3 0.65 0.38-1.13
>29.3 0.42 0.22-0.78
0.00039
interval
Fibre glday Range Relative risk 95% confidence interval
