Food groups and risk of non-Hodgkin lymphoma: A multicenter, case-control study in Italy

Authors


Abstract

Incidence of non-Hodgkin lymphoma (NHL) has been rising worldwide, but the reasons are undefined. Dietary habits may play a role in the etiology of NHL by influencing the metabolic pathways of several cells of the immune system. This case-control study investigated the relation between food consumption and NHL risk. Between 1999 and 2002, we conducted a hospital-based case-control study on NHL in 2 areas of Italy. Cases were 190 patients (median age 58 years) with incident NHL admitted to specialized and general hospitals. Controls were 484 patients (median age 63 years) with acute non-neoplastic conditions admitted to the same hospitals network of cases. A validated food-frequency questionnaire was used to assess habitual diet 2 years before interview. Unconditional multiple logistic regression was used to estimate the odds ratios (OR) and the corresponding 95% confidence intervals (CI), with allowance for energy intake, according to the residual model. Consumption of highest versus lowest quartile of pasta/rice (OR = 1.87, 95% CI: 1.04–3.36) and cheese (OR = 1.66, 95% CI: 0.98–2.83) were associated with a significantly increased NHL risk. Inverse association was found for vegetables (OR = 0.49, 95% CI: 0.28–0.87), fruits (OR = 0.51, 95% CI: 0.30–0.85), and egg consumption (OR = 0.59, 95% CI: 0.36–0.97). The association of pasta/rice was also supported by an increased risk of high glycemic load levels (OR = 1.86, 95% CI: 1.04–3.32). In conclusion, our results suggested that diet could affect NHL risk. © 2005 Wiley-Liss, Inc.

Unlike most cancers whose mortality rates have been decreasing over the last 2 decades, non-Hodgkin lymphoma (NHL) incidence and mortality rates have been steadily increasing. Since the 1970s and the 1980s, an increasing NHL incidence rate of 3–4% per year has been observed worldwide, and these rises are greater in developed than in developing countries.1, 2 The reasons of such an increase are largely unknown, and include diagnostic improvements, changes in NHL classification, HIV/AIDS and other immunosuppressive conditions,3 and other infectious agents.4, 5, 6, 7 Various occupational, environmental and chemical agents have also been analyzed as risk factors for NHL,8, 9 but none of these factors explain the recent rise in NHL rates.

Functions and metabolic pathways of several cells of the immune system are known to depend on certain nutrients,10 pointing to a possible role of diet in the etiology of NHL.11

Since the late 1980s, at least 15 epidemiological studies have examined the role of diet and NHL. Five were hospital-based case-control studies12, 13, 14, 15, 16; 6 were population-based case-control studies17, 18, 19, 20, 21, 22; 4 were cohort studies.23, 24, 25, 26 Among these, 1 epidemiological study found an increased risk of NHL associated with breads and cereals17; 3 studies observed inverse associations, in particular for intake of whole-grain foods12, 14, 21; 3 studies did not find any association.19, 22, 25 Meat or animal proteins were associated with increased risk of NHL in some studies16, 18, 19, 21, 22, 24, 25 but not in others.12, 17, 24 Increased risk of NHL was associated with milk or dairy intake in some studies,12, 14, 17, 21, 22, 23 but others did not confirm this association.16, 18, 19, 24, 25 Likewise, a high consumption of butter, oil12, 14 and eggs19 was associated with an increased risk of NHL.

In contrast, increased intakes of vegetables,12, 13, 14, 17, 19, 24, 26 fruit or citrus fruits17, 24, 26 and fish16, 20 were associated to reduced NHL risk.

The present paper, based on a multi-center Italian study, provides further insights on the relation between food consumption and NHL.

Material and methods

Between January 1999 and July 2002, we conducted a hospital-based, case-control study on NHL, in the province of Pordenone, North-Eastern Italy, and in Naples, Southern Italy.7 Cases were patients between 18 and 84 years with incident, histologically confirmed NHL, admitted to major reference hospitals of the areas under surveillance. Cases were classified according to the International Classification of Disease for Oncology.27 Out of 240 identified NHL cases, 2 refused participation, 7 were excluded because of previous or concomitant cancer and 6 patients did not provide a blood sample. Additional 35 cases, which did not have comprehensive information on dietary habits, were excluded, thus leaving 190 eligible cases (median age: 58 years), HIV-negative, for whom questionnaires and blood samples were available.

Controls were patients between 18 and 84 years, admitted for a wide spectrum of acute conditions to the same network of hospitals where NHL cases had been interviewed. Specifically excluded from the control group were patients admitted for malignant diseases, conditions related to alcohol and tobacco consumption (i.e., cirrhosis, gastric ulcer, ulcerative colitis, cardiovascular and respiratory tract diseases, chronic bronchitis), hepatitis, any chronic diseases that might have changed substantially lifestyle habits, hematological, allergic and autoimmune diseases. A total of 554 controls were contacted, of whom 550 accepted participation. Blood samples were available for 504 controls. Twenty controls were further excluded because of incomplete dietary questionnaire, thus leaving 484 available controls (median age: 63 years). Of these, 27% were admitted to the hospital for trauma, 24% for non-traumatic orthopedic diseases, 22% for acute surgical conditions, 15% for eye diseases and 12% for a variety of other illnesses. Controls were slightly older than cases (Table I) as age matching was conducted according to the age distribution of the whole group of cases in the entire study (which included lymphohematopoietic neoplasm other than NHL and hepatocarcinoma).

Table I. Distribution of 190 Cases of Non-Hodgkin Lymphoma and 484 Controls and Corresponding Odds Ratio (OR) and 95% Confidence Intervals (CI)1 for Selected Socio–Demographic Factors, Hepatitis C Virus (HCV) Test, and Total Energy Intake. Italy, 1999-2002
 Cases N (%)Controls N (%)OR(95% CI)
  • 1

    Estimated from unconditional logistic regression adjusted for gender, age, center, education, and place of birth when appropriate.

  • 2

    Reference category.

  • 3

    The test for trend was based on the likelihood-ratio test between the models with and without the linear term.

Gender
Males101 (53.2)330 (68.2)  
Females89 (46.8)154 (31.8)  
Age (years)
<4543 (22.6)102 (21.1)  
45–5434 (17.9)55 (11.4)  
55–6457 (30.0)116 (24.0)  
≥6556 (29.5)211 (43.6)  
Center
Aviano/Pordenone95 (50.0)260 (53.7)  
Naples95 (50.0)224 (46.3)  
Place of birth
North–Center72 (37.9)228 (47.1)12 
South118 (62.1)256 (52.9)2.12(1.19–3.80)
Education (years)
<777 (40.5)238 (49.2)12 
7–1160 (31.6)124 (25.6)1.47(0.93–2.31)
≥1253 (27.9)122 (25.2)1.31(0.82–2.08)
χmath image trend3   1.43; p = 0.23
HCV test
Negative152 (80.0)440 (90.9)12 
Positive38 (20.0)44 (9.1)2.72(1.63–4.52)
Total energy intake (Kcal)
<197164 (33.7)159 (32.9)12 
1971–<244262 (32.6)160 (33.1)1.12(0.72–1.73)
≥244264 (33.7)165 (34.1)1.28(0.81–2.05)
χmath image trend3   1.10; p = 0.29

All study participants signed an informed consent, following the recommendations of the Ethical Committee of the Aviano National Cancer Institute. The same interview-based, structured questionnaire and coding manual were used in each study center. Centrally trained and supervised interviewers identified and questioned cases and controls during their hospital stay. Cases were interviewed not longer than 12 months after the diagnosis (median time span: 4 months). On average, less than 1% of both cases and controls refused the interview. The data were checked centrally for consistency. Each case and each control provided a 15 ml sample of blood on the day the interview took place. Sera were screened for antibodies against HCV, using a third-generation MEIA (AxSYM HCV, version 3.0; Abbott, Wiesbaden, Germany).7

The questionnaire included information on age, education and other socio-demographic characteristics, anthropometrics measures, tobacco smoking, history of selected diseases, lifestyle behaviors and exposures that entailed risk of Hepatitis C Virus (HCV) transmission. A validated food frequency questionnaire (FFQ) was employed to assess subjects' habitual diet and to estimate their total energy intake,28, 29 2 years before cancer diagnosis or hospital admission for the controls. The FFQ included 63 foods, food groups or recipes divided into 7 sections: (i) milk, yogurt, coffee, tea, sugar and artificial sweeteners; (ii) bread and cereals (first courses); (iii) meat and foods used as meat substitutes in meals in Italy (second courses); (iv) vegetables (side dishes); (v) fruits; (vi) sweets, desserts and soft drinks; (vii) alcoholic beverages. For vegetables and fruit subject to seasonal variation, consumption in season and the corresponding duration were elicited. For food items, serving size was defined either in “natural” units (e.g., 1 teaspoon of sugar, 1 egg) or as an average serving in the Italian diet (e.g., 80 g serving of pasta or rice with tomato or meat sauce; 250 g pizza; 120–150 g serving of red meat).28, 29

Intake lower than once a week but at least once a month was coded as 0.5 per week. The list of food groups, constituents and weekly serving size, listed in the FFQ, were reported in Appendix I. Some questionnaire items and recipes were allocated to 2 food groups, according to their contents (e.g.: pizza was apportioned into both bread and cheese for one half each). The FFQ allowed estimation of intake of total energy using Italian food-composition database.30 Use of supplements and multivitamins, in our study, was less than 3% (8 cases and 9 controls), and therefore was not considered.

For each carbohydrate content food, we expressed glycemic index (GI) as a percentage of the glycemic response elicited using ‘white bread’ as a standard food, using international tables.31 The average daily GI of a subjects' diet was computed by summing the products of the GI value of 1 serving of each food times the average number of servings of that food consumed by the subject per week divided by the weekly available carbohydrate intake. A score for the daily average glycemic load (GL) was computed as the GI, but without dividing by the total amount of carbohydrates. To take into account Italian cooking habits (e.g. pasta ‘al dente’), Italian sources were adopted for a few local recipes.32 Food items for which a GI had not been determined were assigned the GI of the closest commensurable food (e.g. tangerines were assigned the same GI as oranges).

Odds ratios (OR) and the corresponding 95% confidence intervals (CI) were computed by unconditional multiple logistic regression, including: age (in quinquennia), sex, center, years of education (<7, 7–11, ≥12 years), place of birth (North-Center and South), seropositivity for HCV and total energy intake (in continuous).33 Adjustment for energy was made using a residual model.34 Food groups were entered in the model as quartiles of intake based on the distribution of cases and controls combined.

Results

Table I shows the distribution of NHL cases and controls by gender, age group, study center and selected variables. An increased risk of NHL in association with place of birth (North/Center versus South of Italy, OR = 2.12, 95% CI: 1.19–3.80) and HCV test (positive versus negative, OR = 2.72, 95% CI: 1.63–4.52) was found, though not with education and total energy intake.

Table II shows the upper limit of intake quartiles of food groups and the corresponding multivariate ORs and relative 95% CI values. A significant increased risk was found for the highest versus lowest quartile of intake of pasta/rice (OR = 1.87, 95% CI: 1.04–3.36) and cheese (OR = 1.66, 95% CI: 0.98–2.83). A decreasing risk was found for vegetables (OR = 0.49, 95% CI: 0.28–0.87), fruits (OR = 0.51, 95% CI: 0.30–0.85) and eggs (OR = 0.59, 95% CI: 0.36–0.97, ≥2 versus <1 egg per week). Intakes of meat (white, red and pork), fish, dessert and sugars were not significantly related to NHL risk.

Table II. Odds Ratio (OR) and Corresponding 95% Confidence Interval (CI)1 of Non-Hodgkin Lymphoma by Quartileof Intake of Food Groups. 190 Cases and 484 Controls. Italy, 1999–2002
Food groupsEnergy-adjusted quartile of intakep value χmath image trend3
12234
Upper limits (servings/week)
  • 1

    Estimated from unconditional logistic regression adjusted for gender, age, center, education, place of birth, HCV (hepatitis C virus) test, and total energy intake (Kcal).

  • 2

    Reference category.

  • 3

    The test for trend was based on the likelihood-ratio test between the models with and without the linear term.

Milk5.259.013.0  
OR (95% CI)11.27 (0.76–2.12)1.31 (0.78–2.19)0.91 (0.54–1.54)0.75
Coffee and tea17.532.042.25  
OR (95% CI)11.10 (0.65–1.85)1.31 (0.79–2.17)1.09 (0.65–1.84)0.61
Bread13.021.029.0  
OR (95% CI)10.79 (0.47–1.34)1.26 (0.74–2.14)0.84 (0.48–1.47)0.94
Pasta/Rice3.04.05.75  
OR (95% CI)11.76 (1.03–3.01)2.32 (1.35–3.97)1.87 (1.04–3.36)0.02
Soup1.02.03.0  
OR (95% CI)11.11 (0.67–1.85)0.88 (0.51–1.52)1.05 (0.62–1.78)0.92
White meats1.02.03.0  
OR (95% CI)10.99 (0.61–1.62)0.68 (0.41–1.14)0.80 (0.48–1.33)0.21
Red meats1.62.43.25  
OR (95% CI)10.98 (0.59–1.63)0.84 (0.50–1.40)0.93 (0.56–1.55)0.65
Pork and processed meat1.52.03.5  
OR (95% CI)10.76 (0.45–1.28)1.04 (0.63–1.72)1.10 (0.67–1.81)0.47
Fish4.05.57.5  
OR (95% CI)10.70 (0.42–1.19)0.92 (0.55–1.54)1.26 (0.76–2.08)0.27
Cheese2.253.55.5  
OR (95% CI)10.74 (0.44–1.26)0.93 (0.54–1.58)1.66 (0.98–2.83)0.04
Eggs0.51.02.0  
OR (95% CI)10.56 (0.33–0.93)0.53 (0.32–0.88)0.59 (0.36–0.97)0.04
Vegetables10.013.519.0  
OR (95% CI)10.44 (0.26–0.74)0.56 (0.33–0.94)0.49 (0.28–0.87)0.03
Potatoes0.51.52.0  
OR (95% CI)11.02 (0.61–1.72)1.42 (0.86–2.35)1.20 (0.72–2.01)0.29
Fruits16.525.534.5  
OR (95% CI)10.54 (0.33–0.90)0.65 (0.40–1.07)0.51 (0.30–0.85)0.02
Dessert2.254.58.25  
OR (95% CI)11.02 (0.59–1.76)1.32 (0.76–2.29)1.37 (0.80–2.29)0.17
Sugar14.530.049.5  
OR (95% CI)10.59 (0.35–0.99)0.58 (0.34–0.98)0.73 (0.44–1.21)0.22

Only those food groups which emerged in relation to NHL risk were further investigated in separate strata of gender and age (Table III). The estimates were similar across strata of gender. However, women seemed to be at higher risk of NHL for elevated intakes of pasta/rice (ORs: 2.36 and 1.66 for women and men, respectively) and cheese (ORs: 2.63 and 1.43). Likewise, men seemed to be at a decreased risk of NHL for elevated consumption of vegetables (ORs: 0.52 and 0.84 for men and women, respectively). When analysis was conducted across strata of age (≥60 versus <60 years), no apparent differences emerged, even if a slight modifying effect was found for cheese (OR: 2.32 and 1.33, respectively), vegetables (ORs: 0.43 and 0.85, respectively), and fruits (ORs: 0.21 and 1.01, respectively).

Table III. Odds Ratio (OR) and Corresponding 95% Confidence Interval (CI)1 of Non-Hodgkin Lymphoma by Quartile of Intake of Selected Food Groups and by Strata of Gender and Age. 190 Cases and 484 Controls. Italy, 1999–2002
 Energy-adjusted quartile of intakep value χmath image trend3
12234
Upper limits
  • 1

    Estimated from unconditional logistic regression adjusted for gender, age, center, education, place of birth, HCV (hepatitis C virus) test, and total energy intake (Kcal), when appropriate.

  • 2

    Reference category.

  • 3

    The test for trend was based on the likelihood-ratio test between the models with and without the linear term.

Pasta/Rice
 Men11.89 (0.94–3.79)1.99 (0.98–4.04)1.66 (0.77–3.59)0.15
 Women11.67 (0.67–4.11)3.45 (1.39–8.56)2.36 (0.90–6.22)0.04
 Age <60 years11.37 (0.66–2.84)2.48 (1.18–5.20)1.82 (0.82–4.05)0.06
 Age ≥60 years12.28 (1.00–5.21)2.08 (0.91–4.76)1.92 (0.78–4.69)0.17
Cheese
 Men10.59 (0.30–1.16)0.57 (0.27–1.22)1.43 (0.72–2.85)0.47
 Women11.13 (0.44–2.92)1.86 (0.75–4.64)2.63 (1.00–6.89)0.02
 Age <60 years10.79 (0.39–1.61)0.90 (0.43–1.87)1.33 (0.65–2.71)0.42
 Age ≥60 years10.67 (0.29–1.55)1.09 (0.48–2.45)2.32 (1.01–5.36)0.03
Eggs
 Men10.81 (0.42–1.54)0.69 (0.35–1.36)0.74 (0.37–1.45)0.30
 Women10.21 (0.08–0.54)0.24 (0.10–0.60)0.34 (0.14–0.82)0.09
 Age <60 years10.70 (0.36–1.39)0.53 (0.26–1.08)0.49 (0.24–1.00)0.03
 Age ≥60 years10.44 (0.19–1.00)0.58 (0.27–1.24)0.84 (0.40–1.77)0.88
Vegetables
 Men10.37 (0.19–0.72)0.40 (0.20–0.84)0.52 (0.25–1.08)0.04
 Women11.26 (0.51–3.16)1.06 (0.45–2.53)0.84 (0.33–2.11)0.60
 Age <60 years10.67 (0.33–1.36)0.82 (0.38–1.77)0.85 (0.40–1.82)0.72
 Age ≥60 years10.52 (0.24–1.13)0.48 (0.23–1.01)0.43 (0.19–0.98)0.04
Fruits
 Men10.62 (0.34–1.16)0.39 (0.19–0.81)0.59 (0.30–1.15)0.04
 Women10.41 (0.16–1.06)1.12 (0.48–2.60)0.51 (0.21–1.22)0.49
 Age <60 years10.66 (0.33–1.32)0.83 (0.41–1.67)1.01 (0.50–2.02)0.88
 Age ≥60 years10.78 (0.17–0.81)0.38 (0.18–0.81)0.21 (0.09–0.47)<0.01

The effect of a high GI diet and NHL risk was investigated in Table IV. Results were suggestive of a direct relation between GL and NHL risk (OR = 1.86, 95% CI: 1.04–3.32), in particular, for people below 60 years (OR = 2.36, 95% CI: 1.02–5.46).

Table IV. Odds Ratio (OR) and Corresponding 95% Confidence Interval (CI)1 of Non-Hodgkin Lymphoma by Quartile of Glycemic Index and Glycemic Load, Overall and by Strata of Gender and Age. 190 Cases and 484 Controls. Italy, 1999–2002
 Energy-adjusted quartilep value χmath imagetrend3
12234
  • 1

    Estimated from unconditional logistic regression adjusted for gender, age, center, education, place of birth, HCV (hepatitis C virus) test, and total energy intake (Kcal), when appropriate.

  • 2

    Reference category.

  • 3

    The test for trend was based on the likelihood-ratio test between the models with and without the linear term.

Glycemic index
 Overall11.71 (1.02–2.88)1.39 (0.81–237)1.70 (0.99–2.94)0.11
 Men11.54 (0.72–3.28)1.36 (0.63–2.94)1.55 (0.75–3.23)0.33
 Women12.07 (0.97–4.41)1.32 (0.60–2.91)1.52 (0.59–3.89)0.51
 Age <60 years12.37 (1.07–5.26)1.18 (0.54–2.59)1.74 (0.81–3.72)0.45
 Age ≥60 years11.33 (0.64–2.77)1.65 (0.77–3.54)1.47 (0.64–3.40)0.27
Glycemic load
 Overall11.58 (0.92–2.71)1.52 (0.86–2.66)1.86 (1.04–3.32)0.06
 Men11.19 (0.58–2.46)0.89 (0.40–1.97)1.47 (0.68–3.16)0.42
 Women12.42 (1.00–5.85)2.96 (1.20–7.29)2.12 (0.78–5.71)0.12
 Age <60 years11.81 (0.79–4.15)1.76 (0.77–4.01)2.36 (1.02–5.46)0.07
 Age ≥60 years11.26 (0.59–2.66)0.95 (0.41–2.17)1.25 (0.52–3.01)0.82

Discussion

Our study found an association between consumptions of pasta/rice and NHL risk. Consumption of bread and cereal products was positively associated with NHL risk also in a population-based case-control study conducted in Nebraska.17 In 2 Italian case-control studies,12, 14 a protective effect of whole-grain bread and pasta consumption combined was reported. Pasta, in particular refined wheat one, and rice are high in simple sugars and refined carbohydrates, and their consumption triggers insulin secretion. High insulin and insulin-related growth factor (IGF) levels have been linked to an increased risk of several cancers (e.g., breast, colon, prostate, ovary).35, 36, 37 Along the same line, an increased NHL risk in individuals diagnosed with diabetes was reported.38, 39, 40

Epidemiological evidence suggests a direct association of GI (expressed as GL, a measure of quality as well as quantity of total carbohydrate intake and, thus, an indirect measure of dietary insulin demand) to risk of diabetes, heart disease, obesity and some cancers.41 Our study suggests an approximate 2-fold increase in risk of NHL for high GL levels, confirming the link between NHL risk and pasta/rice consumption. Previous studies investigated the effects of insulin and insulin-like growth factor (IGF) on the growth of human cells in vitro (e.g., erythropoiesis, granulopoiesis and lymphopoiesis). IGFs, especially IGF-1, are mitogenic for cell lines of myeloid and lymphoid leukemia, Burkitt's lymphoma, and it may stimulate proliferation of B-cell and T-cell acute lymphocytic leukemia.42

In our study, a direct association was also found with cheese. Previous results on cheese and NHL risk were controversial. A positive association was reported in 2 population-based case-control studies,19, 22 but not in other investigations.12, 14, 17, 24 The results of studies investigating the importance of animal fats consumption have been suggestive of an association. Furthermore, experimental evidence from animal studies suggested that high intakes of fats and proteins could induce chronic hyperstimulation of the immune system.43, 44, 45, 46, 47

Inverse associations of NHL risk with vegetables and fruits were found in our study. Intakes of vegetables and fruits have been investigated in some previous studies.12, 13, 14, 16, 17, 18, 19, 21, 22, 24, 26 Ward et al.,17 Chiu et al.,24 Matsuo et al.16 and Chang et al.22 found that a high fruit intake was associated to a low risk of NHL, whereas the other 7 studies found no relationship. However, evidence suggesting a protective effect of high consumptions of at least some types of vegetables emerged from 6 studies: Ward et al.17 (e.g., carrots and dark green vegetables); Tavani et al.14 (e.g., carrots); Zhang et al.26 (e.g., vegetables); Matsuo et al.16 (e.g., carrots); Zheng et al.21 (e.g., dietary fiber; cruciferous) and Chang et al.22 (e.g., cruciferous, green leafy vegetables, orange vegetables, only in women). In contrast, 1 study did not report such an association,24 and 3 studies reported a weak positive association with NHL risk.13, 18, 19 Concerning fruit consumption, there was no consistent findings across the 8 case-control or population case-control studies12, 13, 14, 16–, [17], [18], 19, 22 and 2 cohort ones.24, 26

It has been hypothesized that the antioxidant properties of vegetables and fruits or their contents of flavonoids or other micronutrients may have a protective effect against NHL, but any interpretation remains speculative.

An unexpected result of the present study is the protective effect of eggs. Two previous studies19, 21 found an increased risk of NHL associated to eggs. Our association may be due to chance; however, different dietary habits between Italian and North-American populations, including fat for cooking, may partly account for those differences.

Our study did not find any association of NHL risk with high consumptions of meats, including liver and lean processed meats. Association with NHL risk were observed across different types of meat or animal proteins in 3 hospital-based case-control studies,12, 14, 16 and in 4 population-based, case-control studies.18, 19, 21, 22Vice versa, a population-based case-control study17 found no association neither with consumption of animal products nor with intakes of animal proteins. Among cohort studies, Chiu et al.24 showed an increased risk for high consumption of animal fat or red meat (particularly hamburgers), animal protein, and saturated and monounsaturated fats. Similarly, Zhang et al.25 reported an increased risk with high intakes of beef, pork or lamb and saturated and trans-unsaturated fats, but not with protein intakes.

Recall and selection biases are possible in this as in most case-control studies. Awareness of any particular dietary hypothesis in NHL cancer etiology, however, was limited in the Italian public at the time of the study, as the issue had not received media attention. Although our study was not population-based, the catchment areas were comparable for cases and controls. It is possible that dietary habits of hospital controls may have differed from those of the general population; however, by study design, great attention was paid in excluding all diagnoses that might have been associated to or had determined special dietary habits in control subjects. Moreover, to reduce the possibility of recall bias due to changes in diet related to disease onset, we elicited information on food intake during the 2 years before the interview. The questionnaire was administered to cases and controls by the same interviewers under similar conditions in a hospital setting, thus minimizing information bias. In addition, our findings are strengthened by the nearly complete participation of identified cases and controls and by the reliance on a validated food-frequency questionnaire.28, 29 Adjustments for sex, age, center, education, place of birth and total energy intake were made to address potential confounding.

In conclusion, our study reports a positive association of NHL risk to high consumptions of pasta/rice and cheese. Moreover, high consumptions of eggs, raw vegetables and fruits showed an inverse association. The increase in risk for high levels of GL supports a possible mechanism in terms of insulin and IGF-related factors in the etiology of NHL.

Acknowledgements

The authors thank Drs A. Pinto and A. Carbone for the collaboration to the study, Mrs O. Volpato for study coordination, Drs G. Laconca, M. Grimaldi and O. Manganelli for their help in data collection and Mrs L. Mei for editorial assistance. We are deeply thankful to Drs. R. Mele, A. Grandi and L. Forner for providing hospital control patients.

APPENDIX I

I

Table I. Food Groups, Food Item Constituents, and Weekly Serving Size as Listed in the Food-Frequency Questionnaire
Food groupsFood item (weekly serving size)1
  • 1

    ½, ⅓, ⅔, ¼, ¾ indicates recipes or questionnaire items allocated to 2 different food groups.

MilkWhole and skim milk and yoghurt (1 cup/125 ml); ¼ coffee and cappuccino (1 coffee-cup)
Coffee and tea¾ coffee and cappuccino (1 coffee-cup); Decaffeinated coffee (1 coffee-cup); Tea (1 teacup)
BreadWhite bread (1 slice/50 g); Crackers, bread stick, melba toast (30 g); Whole wheat bread (1 slice/50 g); Whole wheat crackers, bread stick, melba toast (30 g); Other whole wheat products (medium serving size); ½ pizza (250 g)
Pasta/RicePasta/Rice with butter/oil/tomato (80 g); ½ pasta/rice with meat sauce (80 g); ½ lasagne/cannelloni (250 g)
SoupLight soup (200 g); ½ vegetable soup (250 g)
White meatChicken, turkey or rabbit (200 g)
Red meat⅔ beef, veal, or pork (150 g); Liver (150 g); ½ pasta/rice with meat sauce (80 g); ½ lasagne/cannelloni (250 g)
Pork and processed meat⅓ beef, veal, or pork (150 g); Prosciutto, ham, salami, and sausages (50 g)
FishBoiled or broiled fish or shellfish (150/80 g); Fried fish (150 g); Tuna or sardines packed in oil (80 g)
CheeseCheese (80 g); ½ pizza (250 g)
EggsEggs (1 egg)
VegetablesGreen and red salad (50 g); Mixed salad (tomatoes, carrots, cucumbers, bell peppers) (100 g); Tomatoes (150 g); Raw carrots (100 g); Pulses (100 g fresh/40 g dried); Cruciferae (125 g); Spinach and green leaf vegetables (200 g); Cooked carrots (100 g); Zucchini, eggplants, and bell peppers (150 g)
PotatoesPotatoes (200 g)
FruitsApples and pears (150 g); Citrus fruits (150 g); Kiwi fruits (100 g); Peaches, apricots, and prunes (100 g); Bananas (200 g); Grapes (200 g); Strawberries and cherries (150 g); ½ unsweetened fruit juices (1 glass); ½ cooked fruits (1 fruit bowl);
DessertsCookies (7 pieces/50 g); Pastries with or without cream (1 piece/slice); Ice-creams (200 g); ½ cooked fruits (1 fruit bowl)
SugarSugar (1 tablespoon); Honey and jams (1 tablespoon); Chocolate and candy bars (30 g); Candies (2 candies); soft drinks (1 glass/150 ml); sweetened fruit juices (200 ml)

Ancillary