Abstract
Relatively small lifestyle modifications related to weight reduction, physical activity and diet has been shown to decrease the risk of type 2 diabetes. Connected with diet, low consumption of meat has been suggested as a protective factor of diabetes. The aim was to examine the association between the consumption of total meat or the specific types of meat and risk of type 2 diabetes. The ATBC cohort included middle aged male smokers. During up to 12 years of follow-up, 1098 incident cases of diabetes were diagnosed from 24,845 participants through the nationwide register. Food consumption was assessed by a validated food frequency questionnaire. In the age and intervention group adjusted model, high total meat consumption was a risk factor of type 2 diabetes (relative risk (RR) 1.50, 95% confidence interval (CI): 1.23, 1.82, highest vs. lowest quintile). The result was similar after adjustment for environmental factors and foods related to diabetes and meat consumption. The RR of type 2 diabetes was 1.37 for processed meat (95% CI: 1.11, 1.71) in the multivariate model. The results were explained more by intakes of sodium than intakes of saturated fatty acids, protein, cholesterol, heme iron, magnesium and nitrate, and were not modified by obesity. No association was found between red meat, poultry and the risk of type 2 diabetes. In conclusion, it may help to prevent the global epidemic of type 2 diabetes by reducing the consumption of processed meat. It seems that sodium of processed meat may explain the association.
Keywords: cohort study, epidemiology, meat, processed meat, diabetes
INTRODUCTION
It has been predicted that the number of adults with diabetes will double during the next two decades, being worldwide 300 million in the year 2025(1). Because of long-term serious complications and indirectly mortality of diabetes, all established preventive factors against the disease are valuable. From lifestyle factors, obesity and physical inactivity have consistently been associated with an increased risk of type 2 diabetes(2, 3). The intervention studies have also shown the possibility to reduce the risk of type 2 diabetes by relatively small lifestyle modifications on weight control, physical activity and diet(4-5).
Three cohort studies from the United States have shown that high consumption of meat, particularly processed meat, may increase the risk of type 2 diabetes in men(7) and women(8,9). The only cohort study outside the United States found that especially high consumption of processed meat increased the risk of type 2 diabetes among overweight and obese Chinese women(10). The mechanisms behind the observed relationship are unclear.
The prospective data from the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (the ATBC Study) was used to examine the relations on the consumption of total meat and the types of meat (red meat, processed meat and poultry) to the risk of type 2 diabetes in Finnish middle-aged male smokers. Furthermore, the explanatory factors related to meat and whole diet (alcohol, fruits, vegetables, rye, milk, coffee, saturated fatty acids, protein, cholesterol, heme iron, magnesium, sodium, nitrate and energy) were examined.
METHODS
The Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study was a randomized, double-blinded, placebo-controlled clinical trial undertaken to determine effects of antioxidant supplements on cancer among male smokers aged 50-69 years and living in Southwestern Finland (n=29,133)(13-14). At baseline, men were excluded if they smoked fewer than five cigarettes a day, had a previous history of cancer, severe angina on exertion, chronic renal insufficiency, liver cirrhosis, alcoholism or other medical conditions limiting long-term participation. Furthermore, men who received anticoagulant therapy or used vitamin E, vitamin A or beta-carotene supplements in excess of predefined doses were excluded. The recruitment was carried out between 1985 and 1988, and the trial intervention continued until April 1993. The trial cohort has been followed up through national registers there after.
This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by the Institutional Review Boards of the National Public Health Institute (currently the National Institute for Health and Welfare), Finland, and the National Cancer Institute, USA. Written informed consent was obtained from all subjects.
Ascertainment of diabetes
In Finland, patients needing medical treatment for diabetes are entitled to reimbursement of their medication expenses according to the sickness insurance legislation. This requires a medical certificate from the attending physician. The certificate of every case is verified to fulfill the diagnostic criteria (blood glucose permanently 7.0 mmol/l or higher after dietary treatment) for diabetes at the Social Insurance Institution which maintains a central register of all persons receiving drug reimbursement. The participants of the ATBC Study were linked to the register through the unique personal identity number assigned to each Finnish citizen.
At baseline, 1,272 participants had a history of diabetes diagnosed by a physician. Furthermore, 1918 participants were excluded because of an incompletely filled in food frequency questionnaire. After the exclusions, the final cohort for this study comprised 25,943 men, among whom 1098 incident cases of diabetes were identified from the drug reimbursement register through December 1997 (followed up to 12 years).
Baseline data collection
At baseline, each man completed questionnaires on general characteristics as well as medical history, smoking and physical activity. Height and weight were measured, and body mass index (kg/m2) was calculated. Blood pressure was measured by mercury sphygmomanometer from the right arm while the subject remained seated. Serum samples were collected and stored at -70°C. Serum glucose was determined by the enzymatic hexokinase method using an Optima analyzer (ThermoFischer, Vantaa, Finland). Serum total cholesterol concentrations were determined enzymatically (CHOD-PAP - cholesterol oxidase-p-aminophenazone method; Boehringer Mannheim, Mannheim, Germany). HDL-cholesterol was measured after precipitation with dextran sulphate and magnesium chloride.
Dietary assessment
Food consumption over the previous 12 months was assessed at baseline with a validated self-administered food frequency questionnaire (FFQ) developed for the ATBC Study(15). The consumption of 276 food items and mixed dishes (about 50 food items or dishes included meat, sausage or poultry) was recorded by asking the number of times an item was usually consumed per day, week or month. Participants were also allowed to report additional foods consumed frequently but not listed in the FFQ. The portion size was assessed by a picture booklet including 122 color photographs of food items or dishes. The participants completed the FFQ at home and returned it during the second baseline visit, where a trained study nurse checked the FFQ through and modified possible discrepancies during a 30-minute-interview. Thereafter, a senior nutritionist reviewed all the FFQs for final approval. In all, 93 percent of the FFQs were approved. The food data were converted into daily meat consumption (total meat, red meat: beef and pork, processed meat and poultry) and nutrient intakes according to the software and food composition database at the National Public Health Institute in Finland. We did not assess the fish consumption in this study.
The reproducibility and validity of the dietary questionnaire were tested in a pilot study with 189 men using a 24-day food record (2*12 days) as a reference method(15). For the meat variables, the extended analyses of crude intraclass correlations between the first and second FFQ ranged from 0.56 (pork) to 0.74 (poultry), and the correlation coefficient between the first FFQ and the food records from 0.31 (pork) to 0.50 (processed meat).
Statistical analyses
The associations between quintiles of meat consumption and the incidence of diabetes were calculated by Cox proportional hazards regression and expressed as relative risks (RR) and 95% confidence intervals (95 % CI). The proportional hazards assumption was tested with no evidence of non-proportional hazards. Person-years of follow-up were calculated from the date of randomization to the date of diabetes occurrence, death, or the end of follow-up (December 1997), whichever came first.
The first model (Model 1) was adjusted for age and intervention groups (alpha-tocopherol, beta-carotene, both or placebo). The Model 2 was further adjusted for body mass index, number of cigarettes smoked daily, smoking years, systolic blood pressure, diastolic blood pressure, serum total cholesterol and serum high-density lipoprotein cholesterol, leisure-time physical activity, and intakes of alcohol and energy. Furthermore, the multivariate Model 3 was adjusted for all the variables included in the Model 2 plus consumption of foods related to type 2 diabetes (fruit, vegetables, rye, milk and coffee). We also added (Model 4) intakes of saturated fatty acids, protein, cholesterol, heme iron, magnesium, sodium and nitrate to examine mechanisms/explanatory factors behind the results (data not shown). Nutrient intakes were energy-adjusted according to the residual method(16).
Tests for linearity of the trend across the categories were performed using the Wald test by modeling the median value of each quintile as a continuous variable.
The likelihood ratio test was used to study whether body mass index modified the effect of meat consumption on diabetes incidence.
All analyses were carried out with the R statistical programme version 2.7.2 (R Foundation for Statistical Computing, Vienna, Austria)(17). All P-values were two-sided, and P <0.05 was considered statistically significant.
RESULTS
On average, men with high consumption of total meat were younger, more obese, physically less active and had more energy in their diet compared with the others (Table 1). The consumption of total meat was 3-fold higher in the highest quintile compared with the lowest quintile. Especially, the consumption of processed meat and poultry was relatively high among those in the highest quintile of total meat consumption. Furthermore, men whose diet was rich in meat tended to have a higher intake of other foods and nutrients as well.
Table 1.
Age-standardized baseline characteristics (medians) by quintiles of total meat consumption* among 25943 men in the ATBC Study, Finland, 1985-1997.
| Quintiles of total meat intake |
|||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| Background characteristics | |||||
| N | 5189 | 5188 | 5189 | 5188 | 5189 |
| Age, y | 59 | 58 | 57 | 56 | 56 |
| Body mass index, kg/m2 | 25.7 | 25.7 | 25.9 | 26.0 | 26.2 |
| Cigarettes smoked daily, # | 20 | 20 | 20 | 20 | 20 |
| Smoking years | 37 | 36 | 36 | 36 | 37 |
| Systolic blood pressure, mm Hg | 140 | 140 | 140 | 140 | 140 |
| Diastolic blood pressure, mm Hg | 88 | 88 | 88 | 88 | 88 |
| Serum total cholesterol, mmol/L | 6.12 | 6.16 | 6.18 | 6.23 | 6.19 |
| Serum HDL cholesterol, mmol/L | 1.14 | 1.15 | 1.15 | 1.16 | 1.15 |
| Leisure-time physical activity, % | 59 | 60 | 60 | 58 | 56 |
| Energy, kJ/day | 8985 | 10003 | 10836 | 11749 | 13453 |
| Alcohol, g/day | 8 | 10 | 11 | 12 | 14 |
| Fruits, g/day | 138 | 160 | 176 | 184 | 199 |
| Vegetables, g/day | 219 | 255 | 282 | 311 | 338 |
| Rye, g/day | 77 | 80 | 83 | 83 | 87 |
| Milk, g/day | 466 | 499 | 528 | 543 | 595 |
| Coffee, g/day | 550 | 550 | 550 | 600 | 600 |
| Meat related characteristics (/day) | |||||
| Total meat, g | 79 | 111 | 139 | 174 | 244 |
| Red meat, g | 40 | 54 | 63 | 74 | 88 |
| Beef, g | 12 | 18 | 22 | 26 | 30 |
| Pork, g | 25 | 33 | 38 | 44 | 52 |
| Processed meat, g | 28 | 46 | 62 | 84 | 139 |
| Poultry, g | 2 | 8 | 10 | 14 | 14 |
| Saturated fatty acids, g | 40 | 45 | 49 | 53 | 63 |
| Protein, g | 74 | 83 | 91 | 100 | 116 |
| Cholesterol, mg | 413 | 478 | 533 | 594 | 719 |
| Heme iron, mg | 1.9 | 2.6 | 3.1 | 3.7 | 4.8 |
| Magnesium, mg | 411 | 443 | 465 | 493 | 542 |
| Sodium, mg | 3745 | 4272 | 4723 | 5282 | 6285 |
| Nitrate, mg | 40 | 48 | 54 | 60 | 66 |
All differences were statistically significant, except for diastolic blood pressure and leisure time physical activity
† Moderate or heavy activity at leisure time
The Pearson coefficients of correlation (adjusted for energy) between the consumption of total meat and specific types of meat (read meat, processed meat and poultry) were 0.48, 0.82 and 0.27, respectively. Instead, correlations between the consumption of processed meat and the other types of meat (red meat, beef, pork and poultry) ranged from -0.04 to -0.02. Total meat, especially pork and processed meat, correlated positively with energy intake (r>0.35).
In the model adjusted for age and intervention groups, the RR of type 2 diabetes was significantly higher by 50 percent for the highest versus the lowest quintile of total meat consumption (Table 2). The association did not change after adjustment for confounding factors related to diabetes (RR 1.45, 95 % CI: 1.16, 1.81; P-value, test for trend <0.001), and for foods (RR 1.50, 95 % CI: 1.19, 1.89; P-value, test for trend <0.001). Among nutrients, the association between total meat consumption and the risk of diabetes was slightly attenuated by an additional adjustment for sodium (RR 1.28, 95 % CI: 1.00 1.64; P-value, test for trend 0.04).
Table 2.
Relative risks (RR) and 95% confidence intervals (95 % CI) of diabetes by quintiles of meat consumption among 25 943 men in the ATBC Study, Finland, 1985-1997.
| Quintiles of meat consumption |
||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | P for Trend | |||||
| Total meat | ||||||||||
| Median, g/d | 79 | 111 | 139 | 174 | 244 | |||||
| Cases, n | 181 | 192 | 225 | 220 | 280 | |||||
| Age-adjusted RR (95 % CI)* | 1.00 | 1.03 | 0.83, 1.26 | 1.19 | 0.97, 1.46 | 1.15 | 0.94, 1.41 | 1.50 | 1.23, 1.82 | <0.001 |
| Multivariate RR (95 % CI)† | 1.00 | 1.05 | 0.85, 1.29 | 1.22 | 1.00, 1.50 | 1.19 | 0.96, 1.47 | 1.45 | 1.16, 1.81 | <0.001 |
| Multivariate RR (95 % CI)‡ | 1.00 | 1.06 | 0.85, 1.31 | 1.24 | 1.00, 1.53 | 1.22 | 0.98, 1.52 | 1.50 | 1.19, 1.89 | <0.001 |
| Red meat | ||||||||||
| Median, g/d | 33 | 47 | 60 | 76 | 106 | |||||
| Cases, n | 189 | 217 | 241 | 219 | 232 | |||||
| Age-adjusted RR (95 % CI)* | 1.00 | 1.12 | 0.92, 1.37 | 1.22 | 1.00, 1.48 | 1.08 | 0.89, 1.32 | 1.14 | 0.93, 1.39 | 0.33 |
| Multivariate RR (95 % CI)† | 1.00 | 1.23 | 1.00, 1.50 | 1.31 | 1.07, 1.59 | 1.16 | 0.94, 1.42 | 1.19 | 0.97, 1.47 | 0.23 |
| Multivariate RR (95 % CI)‡ | 1.00 | 1.24 | 1.01, 1.52 | 1.33 | 1.08, 1.63 | 1.18 | 0.95, 1.46 | 1.22 | 0.97, 1.53 | 0.21 |
| Beef | ||||||||||
| Median, g/d | 6 | 14 | 20 | 29 | 47 | |||||
| Cases, n | 189 | 221 | 222 | 217 | 249 | |||||
| Age-adjusted RR (95 % CI)* | 1.00 | 1.14 | 0.94, 1.39 | 1.12 | 0.92, 1.37 | 1.09 | 0.89, 1.33 | 1.23 | 1.01, 1.50 | 0.09 |
| Multivariate RR (95 % CI)† | 1.00 | 1.13 | 0.93, 1.38 | 1.19 | 0.97, 1.45 | 1.12 | 0.91, 1.36 | 1.23 | 1.01, 1.50 | 0.08 |
| Multivariate RR (95 % CI)‡ | 1.00 | 1.13 | 0.92, 1.37 | 1.19 | 0.98, 1.46 | 1.11 | 0.91, 1.37 | 1.22 | 0.99, 1.50 | 0.10 |
| Pork | ||||||||||
| Median, g/d | 19 | 29 | 37 | 47 | 66 | |||||
| Cases, n | 216 | 200 | 224 | 250 | 208 | |||||
| Age-adjusted RR (95 % CI)* | 1.00 | 0.89 | 0.74, 1.09 | 0.99 | 0.82, 1.20 | 1.10 | 0.91, 1.33 | 0.90 | 0.74, 1.09 | 0.99 |
| Multivariate RR (95 % CI)† | 1.00 | 0.94 | 0.77, 1.14 | 1.04 | 0.85, 1.26 | 1.14 | 0.94, 1.38 | 0.96 | 0.78, 1.18 | 0.57 |
| Multivariate RR (95 % CI)‡ | 1.00 | 0.94 | 0.77, 1.15 | 1.04 | 0.85, 1.27 | 1.15 | 0.95, 1.41 | 0.97 | 0.78, 1.20 | 0.50 |
| Processed meat | ||||||||||
| Median, g/d | 22 | 42 | 60 | 86 | 142 | |||||
| Cases, n | 176 | 186 | 236 | 243 | 257 | |||||
| Age-adjusted RR (95 % CI)* | 1.00 | 1.04 | 0.84, 1.28 | 1.32 | 1.08, 1.61 | 1.35 | 1.10, 1.64 | 1.46 | 1.20, 1.77 | <0.001 |
| Multivariate RR (95 % CI)† | 1.00 | 1.04 | 0.84, 1.29 | 1.26 | 1.03, 1.55 | 1.19 | 0.97, 1.46 | 1.35 | 1.09, 1.68 | <0.001 |
| Multivariate RR (95 % CI)‡ | 1.00 | 1.04 | 0.84, 1.29 | 1.26 | 1.03, 1.54 | 1.19 | 0.96, 1.46 | 1.37 | 1.11, 1.71 | <0.001 |
| Poultry | ||||||||||
| Median, g/d | 0 | 8 | 14 | 17 | 32 | |||||
| Cases, n | 366 | 174 | 179 | 165 | 214 | |||||
| Age-adjusted RR (95 % CI)* | 1.00 | 0.86 | 0.72, 1.04 | 1.05 | 0.88, 1.27 | 0.89 | 0.74, 1.07 | 1.15 | 0.96, 1.36 | 0.25 |
| Multivariate RR (95 % CI)† | 1.00 | 0.92 | 0.77, 1.11 | 1.00 | 0.83, 1.20 | 0.92 | 0.76, 1.11 | 1.04 | 0.87, 1.23 | 0.88 |
| Multivariate RR (95 % CI)‡ | 1.00 | 0.90 | 0.75, 1.09 | 0.98 | 0.82, 1.18 | 0.89 | 0.74, 1.08 | 1.01 | 0.85, 1.21 | 0.88 |
Adjusted for age and intervention group.
Adjusted further for body mass index, number of cigarettes smoked daily, smoking years, systolic blood pressure, diastolic blood pressure, serum total cholesterol, serum high-density lipoprotein cholesterol, leisure-time physical activity, and intakes of alcohol and energy.
Adjusted further for consumption of fruit, vegetables, rye, milk and coffee
The RR of type 2 diabetes was 1.46 (95 % CI: 1.20, 1.77; P-value, test for trend <0.001) for the highest compared with the lowest quintile of processed meat consumption. The association was attenuated slightly after adjustment for confounding factors related to type 2 diabetes (RR 1.35, 95 % CI: 1.09, 1.68; P-value, test for trend <0.001) and foods (RR 1.37, 95 % CI: 1.11, 1.71; p-value, test for trend =0.001), but remained statistically significant. The attenuation of RR was more explained by the intakes of sodium than other nutrients (RR 1.19, 95 % CI: 0.95, 1.49; p-value, test for trend =0.10). No associations were found between the consumption of red meat (beef and pork), poultry and the risk of type 2 diabetes.
When the diabetes cases diagnosed during the first five years of follow-up were excluded (n=417) from the analyses, the results between the consumption of total meat as well as specific types of meat and the risk of type 2 diabetes did not change. For example, the risk of type 2 diabetes (adjusted for risk factors related to diabetes) was 1.52 (95 % CI: 1.14, 2.01; P-value, test for trend <0.001) for the highest quintile of total meat consumption, and 1.46 (95 % CI: 1.11, 1.92; P-value, test for trend = 0.01) for processed meat.
The associations between the consumption of total meat, processed meat and the risk of type 2 diabetes were not modified by body mass index (P-value, test for interaction ≥0.30).
DISCUSSION
In this cohort study of Finnish male smokers followed up to 12 years, the multivariate relative risk (included, e.g., body mass index and energy) of type 2 diabetes was 50 percent higher for the highest quintile of total meat consumption compared with the lowest quintile. Especially, high consumption of processed meat was associated with a 35% percent increased risk of type 2 diabetes compared with diet low in processed meat (median consumption on average 22g vs. 142g), also after adjustments for environmental and dietary factors. The consumption of red meat (beef and pork) and poultry was not associated with the risk of type 2 diabetes.
It has been observed a 20-30 percent higher risk of type 2 diabetes for the highest category of frequent red meat consumption compared with the lowest category in the Nurses’ Health Study and in the Women's Health Study(8, 9), and a 40-90 percent higher risk for the consumption of processed meat at least 5 times a week compared with consumption less than once a week in the Nurses’ Health Study and in the Health Professionals Follow-Up Study(7, 18). Long-term adherence to a diet that included at least weekly meat consumption was associated with a 74% increase risk of diabetes compared with a vegetarian diet(19). In a large Chinese female cohort with a very low intake of meat, the consumption of processed meat (>once a month vs. never) was also slightly associated with the risk of type 2 diabetes(10), especially among the obese women (BMI≥30 kg/m2) whose risk of type 2 diabetes was 3.5-fold higher compared to the women with normal weight. A relatively small cohort study among Japanese-Brazilians found that high meat consumption was related to the risk of metabolic syndrome(28). The result, however, attenuated when the model was adjusted for the intake of saturated fatty acid. Furthermore, two cross-sectional studies have found contradictory results(29, 30). Our study is the first European cohort on this issue. Furthermore, our male population was totally different than the previous male cohorts, the well-educated health professionals(18) and the participants in the Adventist Health Study. Our population, in general, included low-educated smokers (about 10% smokers in the Health Professionals Follow-Up Study) whose coffee and alcohol consumption was high (on average 18 g and 610g per day, respectively). In our study, the range of meat consumption was especially high, between 79 and 244 g/day (median in the lowest and highest quintile) including mainly red meat and sausages. The results of this study, however, confirmed the previous findings that the high consumption of processed meat seemed to be a risk factor against type 2 diabetes more than the high total meat consumption. The results were not modified by body mass index.
The mechanisms related to the positive associations between red meat or processed meat consumption and type 2 diabetes are unclear. It has been suggested that the associations observed are mediated through high intake of fat, saturated fatty acids(2), protein(9), heme iron(12, 20), preservatives used in processed meat (such as nitrates and nitrite)(11), heterocyclic amines and polycyclic aromatic hydrocarbons formed in meat through high heating practicing(21-22), or glycation end products formed in meat and high fat products through heating and processing(23). These dietary factors have been found to affect insulin resistance(24), oxidative stress(25), inflammation(26) and toxically pancreatic cells(21). In our data, the attenuation of RR was more explained by the intakes of sodium than saturated fatty acids, protein, cholesterol, heme iron, magnesium, nitrate, energy, alcohol, fruits, vegetables, rye, milk or coffee. The other factors related to preservation or cooking meat at high temperature could not be included in our analyses. The effect of nitrite was difficult to assess because of the very high correlation between nitrite and total meat intakes (r=0.82). On the other hand, high meat consumption may be a biomarker for a general lifestyle related to high risk of type 2 diabetes.
A strength of our study was the prospective cohort design, which minimize recall and selection biases. We also had large amounts and range of the consumption of total meat and the specific types of meat. Although we were able to adjust for main non-dietary risk factors of type 2 diabetes, we cannot entirely rule out the possibility of residual or unmeasured confounding.
The ATBC Study included only male smokers, which should be noted when the results are extrapolated to women or non-smokers. Furthermore, the drug reimbursement register was not able to separate the types of diabetes (type 1 and type 2 diabetes). We assumed, however, that the new diabetes cases in this study had type 2 diabetes based on the age (50-69 years) of the participants at baseline. We were able to identify only patients receiving medication for treatment of diabetes, not individuals treating their disease with dietary changes. This will attenuate our estimates between meat consumption and diabetes incidence towards unity. Furthermore, we had a single assessment of diet by a food frequency questionnaire at baseline, and were not able to investigate changes in meat consumption during the follow-up. This may have contributed to misclassification of exposure that also will attenuate the observed associations.
Maintenance of normal weight, avoidance of sedentary behavior and smoking, moderate alcohol consumption and healthy diet are the most potential preventive factors against the type 2 diabetes(27). Our findings confirmed that diet poor in meat, especially processed meat, may also help to prevent type 2 diabetes.
Acknowledgments
The ATBC study was supported by U.S. Public Health Service contracts N01-CN-45165, N01-RC-45035, and N01-RC-37004 from the National Cancer Institute, National Institutes of Health, and the Department of Health and Human Services.
Footnotes
SM: prepared the first draft of the manuscript; JK: analyzed the data; all authors designed the study, interpreted analyses, refined the subsequent drafts and provided consultation on the final draft. None of the authors had any conflicts of interest.
Contributor Information
Satu Männistö, National Institute for Health and Welfare, Helsinki, Finland.
Jukka Kontto, National Institute for Health and Welfare, Helsinki, Finland.
Merja Kataja-Tuomola, National Institute for Health and Welfare, Helsinki, Finland.
Demetrius Albanes, National Cancer Institute, National Institute of Health, Bethesda, MD, USA.
Jarmo Virtamo, National Institute for Health and Welfare, Helsinki, Finland.
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