Biomedical subjects

Andrew Roddam

Publications and source records attributed to Andrew Roddam.

11 recordsLinked to original sources

PubMed2006

Tobacco smoke and bladder cancer--in the European Prospective Investigation into Cancer and Nutrition.

The purpose of the present study was to investigate the association between smoking and the development of bladder cancer. The study population consisted of 429,906 persons participating in the European Prospective Investigation into Cancer and Nutrition (EPIC), 633 of whom developed bladder cancer during the follow-up period. An increased risk of bladder cancer was found for both current- (incidence rate ratio 3.96, 95% confidence interval: 3.07-5.09) and ex- (2.25, 1.74-2.91) smokers, compared to never-smokers. A positive association with intensity (per 5 cigarettes) was found among current-smokers (1.18, 1.09-1.28). Associations (per 5 years) were observed for duration (1.14, 1.08-1.21), later age at start (0.75, 0.66-0.85) and longer time since quitting (0.92, 0.86-0.98). Exposure to environmental tobacco smoke (ETS) during childhood increased the risk of bladder cancer (1.38, 1.00-1.90), whereas for ETS exposure as adult no effect was detected. The present study confirms the strong association between smoking and bladder cancer. The indication of a higher risk of bladder cancer for those who start smoking at a young age and for those exposed to ETS during childhood adds to the body of evidence suggesting that children are more sensitive to carcinogens than adults.

Adolescent↗

PubMed2006

Body size and risk of colon and rectal cancer in the European Prospective Investigation Into Cancer and Nutrition (EPIC).

BACKGROUND: Body weight and body mass index (BMI) are positively related to risk of colon cancer in men, whereas weak or no associations exist in women. This discrepancy may be related to differences in fat distribution between sexes or to the use of hormone replacement therapy (HRT) in women. METHODS: We used multivariable adjusted Cox proportional hazards models to examine the association between anthropometric measures and risks of colon and rectal cancer among 368 277 men and women who were free of cancer at baseline from nine countries of the European Prospective Investigation Into Cancer and Nutrition. All statistical tests were two-sided. RESULTS: During 6.1 years of follow-up, we identified 984 and 586 patients with colon and rectal cancer, respectively. Body weight and BMI were statistically significantly associated with colon cancer risk in men (highest versus lowest quintile of BMI, relative risk [RR] = 1.55, 95% confidence interval [CI] = 1.12 to 2.15; P(trend) = .006) but not in women. In contrast, comparisons of the highest to the lowest quintile showed that several anthropometric measures, including waist circumference (men, RR = 1.39, 95% CI = 1.01 to 1.93; P(trend) = .001; women, RR = 1.48, 95% CI = 1.08 to 2.03; P(trend) = .008), waist-to-hip ratio (WHR; men, RR = 1.51, 95% CI = 1.06 to 2.15; P(trend) = .006; women, RR = 1.52, 95% CI = 1.12 to 2.05; P(trend) = .002), and height (men, RR = 1.40, 95% CI = 0.99 to 1.98; P(trend) = .04; women, RR = 1.79, 95% CI = 1.30 to 2.46; P(trend)<.001) were related to colon cancer risk in both sexes. The estimated absolute risk of developing colon cancer within 5 years was 203 and 131 cases per 100,000 men and 129 and 86 cases per 100,000 women in the highest and lowest quintiles of WHR, respectively. Upon further stratification, no association of waist circumference and WHR with risk of colon cancer was observed among postmenopausal women who used HRT. None of the anthropometric measures was statistically significantly related to rectal cancer. CONCLUSIONS: Waist circumference and WHR, indicators of abdominal obesity, were strongly associated with colon cancer risk in men and women in this population. The association of abdominal obesity with colon cancer risk may vary depending on HRT use in postmenopausal women; however, these findings require confirmation in future studies.

Abdominal Fat↗

PubMed2006

Fruits and vegetables and renal cell carcinoma: findings from the European prospective investigation into cancer and nutrition (EPIC).

We examined the association between fruits and vegetables and risk of renal cell carcinoma (RCC) in the European Prospective Investigation into Cancer and Nutrition (EPIC). Dietary intake data and complete follow-up information on cancer incidence were available for 375,851 participants recruited in EPIC centers of 8 countries. During an average follow-up of 6.2 years, 306 incident cases of RCC were identified. The associations of consumption of total vegetables, total fruits, combined total fruits and vegetables and specific subtypes of vegetables with RCC risk were analyzed using Cox proportional hazards, stratified by centre and adjusted for potential confounders. No significant associations between fruit and vegetable consumption and RCC risk were observed despite a wide range of intake. The estimated relative risks (95% confidence intervals [CI]) in men and women combined were 0.97 (0.85-1.11) per 40 g increase in vegetable intake, 1.03 (0.97-1.08) per 40 g increase in fruit intake and 1.02 (0.93-1.11) per 80 g increase in fruit and vegetable intake combined. Among the vegetable subtypes, an inverse association was observed for root vegetables (RR per 8 g increase: 0.88; 95% CI: 0.78-0.99). These results suggest that total consumption of fruits and vegetables is not related to risk of RCC, although we cannot exclude the possibility that very low consumption is related to higher risk. The relationship of specific fruit and vegetable subgroups with RCC risk warrant further investigation.

Adult↗

PubMed2006

Anthropometric measures, endogenous sex steroids and breast cancer risk in postmenopausal women: a study within the EPIC cohort.

In a large case-control study on breast cancer risk and serum hormone concentrations, nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we examined to what extent the relationship of excess body weight with breast cancer risk may be explained by changes in sex steroids. Height, weight, waist and hip circumferences, and serum measurements of testosterone [T], androstenedione [Delta4], dehydroepiandrosterone sulphate [DHEAS], estradiol [E2], estrone [E1] and sex-hormone binding globulin [SHBG] were available for 613 breast cancer cases, and 1,139 matched controls, who were all menopausal at the time of blood donation. Free T [fT] and free E2 [fE2] were calculated using mass action equations. Breast cancer risk was related to body mass index (BMI) (RR = 1.11 [0.99-1.25], per 5 kg/m2 increase in BMI), and waist (RR = 1.12 [1.02-1.24], per 10 cm increase) and hip circumferences (RR = 1.14 [1.02-1.27], per 10 cm increase). The increase in breast cancer risk associated with adiposity was substantially reduced after adjustment for any estrogens, especially for fE2 (from 1.11 [0.99-1.25] to 0.99 [0.87-1.12], from 1.12 [1.02-1.24] to 1.02 [0.92-1.14] and from 1.14 [1.02-1.27] to 1.05 [0.93-1.18] for BMI, waist and hip circumferences, respectively). A modest attenuation in excess risk was observed after adjustment for fT, but the remaining androgens had little effect on the association of body adiposity with breast cancer. Our data indicate that the relationship of adiposity with breast cancer in postmenopausal women could be partially explained by the increases in endogenous estrogens, and by a decrease in levels of SHBG.

Adiposity↗

PubMed2006

Body size and risk of renal cell carcinoma in the European Prospective Investigation into Cancer and Nutrition (EPIC).

Previous studies suggest that obesity is related to increased risk of renal cell carcinoma (RCC); however, only a few studies report on measures of central vs. peripheral adiposity. We examined the association between anthropometric measures, including waist and hip circumference and RCC risk among 348,550 men and women free of cancer at baseline from 8 countries of the European Prospective Investigation into Cancer and Nutrition (EPIC). During 6.0 years of follow-up we identified 287 incident cases of RCC. Relative risks were calculated using Cox regression, stratified by age and study center and adjusted for smoking status, education, alcohol consumption, physical activity, menopausal status, and hormone replacement therapy use. Among women, an increased risk of RCC was conferred by body weight (relative risk [RR] in highest vs. lowest quintile = 2.13; 95% confidence interval [CI] = 1.16-3.90; p-trend = 0.003), body mass index (BMI) (RR = 2.25; 95% CI = 1.14-4.44; p-trend = 0.009), and waist (RR = 1.67; 95% CI = 0.94-2.98; p-trend = 0.003) and hip circumference (RR = 2.30; 95% CI = 1.22-4.34; p-trend = 0.01); however, waist and hip circumference were no longer significant after controlling for body weight. Among men, hip circumference (RR = 0.44; 95% CI = 0.20-0.98; p-trend = 0.03) was related significantly to decreased RCC risk only after accounting for body weight. Height was not related significantly to RCC risk. Our findings suggest that obesity is related to increased risk of RCC irrespective of fat distribution among women, whereas low hip circumference is related to increased RCC risk among men. Our data give further credence to public health efforts aiming to reduce the prevalence of obesity to prevent RCC, in addition to other chronic diseases.

Body Composition↗

PubMed2006

Anthropometry, physical activity, and the risk of pancreatic cancer in the European prospective investigation into cancer and nutrition.

Tobacco smoking is the only established risk factor for pancreatic cancer. Results from several epidemiologic studies have suggested that increased body mass index and/or lack of physical activity may be associated with an increased risk of this disease. We examined the relationship between anthropometry and physical activity recorded at baseline and the risk of pancreatic cancer in the European Prospective Investigation into Cancer and Nutrition (n = 438,405 males and females age 19-84 years and followed for a total of 2,826,070 person-years). Relative risks (RR) were calculated using Cox proportional hazards models stratified by age, sex, and country and adjusted for smoking and self-reported diabetes and, where appropriate, height. In total, there were 324 incident cases of pancreatic cancer diagnosed in the cohort over an average of 6 years of follow-up. There was evidence that the RR of pancreatic cancer was associated with increased height [RR, 1.74; 95% confidence interval (95% CI), 1.20-2.52] for highest quartile compared with lowest quartile (P(trend) = 0.001). However, this trend was primarily due to a low risk in the lowest quartile, as when this group was excluded, the trend was no longer statistically significant (P = 0.27). A larger waist-to-hip ratio and waist circumference were both associated with an increased risk of developing the disease (RR per 0.1, 1.24; 95% CI, 1.04-1.48; P(trend) = 0.02 and RR per 10 cm, 1.13; 95% CI, 1.01-1.26; P(trend) = 0.03, respectively). There was a nonsignificant increased risk of pancreatic cancer with increasing body mass index (RR, 1.09; 95% CI, 0.95-1.24 per 5 kg/m(2)), and a nonsignificant decreased risk with total physical activity (RR, 0.82; 95% CI, 0.50-1.35 for most active versus inactive). Future studies should consider including measurements of waist and hip circumference, to further investigate the relationship between central adiposity and the risk of pancreatic cancer.

Adult↗

PubMed2005

An approach to estimate between- and within-group correlation coefficients in multicenter studies: plasma carotenoids as biomarkers of intake of fruits and vegetables.

In a multicenter study, the overall correlation between two variables can be broken down into a within- and a between-group correlation reflecting associations at the individual and aggregate levels, respectively. A random-effects model is used to estimate variance components of nutrition-related variables and the within- and between-group correlation coefficients. Using data from the European Prospective Investigation into Cancer and Nutrition (EPIC), the authors analyzed the association between levels of three plasma carotenoids (alpha-carotene, beta-cryptoxanthin, and lycopene) and dietary intake of three items (total fruits, carrots, and tomatoes), assessed through dietary questionnaire and single 24-hour dietary recall measurements, in a cross-sectional study involving 3,089 subjects from nine European countries. Intraclass correlation coefficients were 0.178 for alpha-carotene, 0.216 for beta-cryptoxanthin, and 0.299 for lycopene. The between-group correlation coefficients were higher than the within-group coefficients for all three carotenoids. For beta-cryptoxanthin and fruit intake, the between-group versus the within-group correlations were 0.78 and 0.26 for the dietary questionnaire and 0.85 and 0.19 for the 24-hour dietary recall. Results indicate that variability of exposure is driven mainly by the individual compared with the aggregate variation and that biomarker levels perform fairly accurately in discriminating population-level consumption of fruits and vegetables.

Adult↗

PubMed2005

Serum sex steroids in premenopausal women and breast cancer risk within the European Prospective Investigation into Cancer and Nutrition (EPIC).

BACKGROUND: Contrasting etiologic hypotheses about the role of endogenous sex steroids in breast cancer development among premenopausal women implicate ovarian androgen excess and progesterone deficiency, estrogen excess, estrogen and progesterone excess, and both an excess or lack of adrenal androgens (dehydroepiandrosterone [DHEA] or its sulfate [DHEAS]) as risk factors. We conducted a case-control study nested within the European Prospective Investigation into Cancer and Nutrition cohort to examine associations among premenopausal serum concentrations of sex steroids and subsequent breast cancer risk. METHODS: Levels of DHEAS, (Delta4-)androstenedione, testosterone, and sex hormone binding globulin (SHBG) were measured in single prediagnostic serum samples from 370 premenopausal women who subsequently developed breast cancer (case patients) and from 726 matched cancer-free control subjects. Levels of progesterone, estrone, and estradiol were also measured for the 285 case patients and 555 matched control subjects who had provided information about the day of menstrual cycle at blood donation. Conditional logistic regression models were used to estimate relative risks of breast cancer by quartiles of hormone concentrations. All statistical tests were two-sided. RESULTS: Increased risks of breast cancer were associated with elevated serum concentrations of testosterone (odds ratio [OR] for highest versus lowest quartile = 1.73, 95% confidence interval [CI] = 1.16 to 2.57; P(trend) = .01), androstenedione (OR for highest versus lowest quartile = 1.56, 95% CI = 1.05 to 2.32; P(trend) = .01), and DHEAS (OR for highest versus lowest quartile = 1.48, 95% CI = 1.02 to 2.14; P(trend) = .10) but not SHBG. Elevated serum progesterone concentrations were associated with a statistically significant reduction in breast cancer risk (OR for highest versus lowest quartile = 0.61, 95% CI = 0.38 to 0.98; P(trend) = .06). The absolute risk of breast cancer for women younger than 40 followed up for 10 years was estimated at 2.6% for those in the highest quartile of serum testosterone versus 1.5% for those in the lowest quartile; for the highest and lowest quartiles of progesterone, these estimates were 1.7% and 2.6%, respectively. Breast cancer risk was not statistically significantly associated with serum levels of the other hormones. CONCLUSIONS: Our results support the hypothesis that elevated blood concentrations of androgens are associated with an increased risk of breast cancer in premenopausal women.

Adult↗

PubMed2005

C-peptide, IGF-I, sex-steroid hormones and adiposity: a cross-sectional study in healthy women within the European Prospective Investigation into Cancer and Nutrition (EPIC).

OBJECTIVES: The risk of some cancers is positively associated with body weight, which may influence circulating levels of sex-steroid hormones, insulin and IGF-I. Interrelationships between these hormones and the associations with adiposity were evaluated in healthy women participating in the European Prospective Investigation into Cancer and Nutrition (EPIC). METHODS: A cross-sectional analysis was performed on anthropometric and hormonal data from 743 pre- and 1217 postmenopausal women. Body mass index (BMI) and waist circumference were used as indicators of adiposity. C-peptide, Insulin Growth Factor (IGF)-I, Insulin Growth Factor binding protein (IGFBP)-3, androgens, estrogens and sex hormone binding globulin (SHBG) were measured by immunoassays; free sex steroid concentrations were calculated. RESULTS: BMI and waist circumference were positively correlated with estrogens in postmenopausal women and with C-peptide, free testosterone and inversely with SHBG in all women. C-peptide and IGF-I were inversely correlated with SHBG, and positively with free sex steroids in postmenopausal women. IGF-I was positively associated with postmenopausal estrogens and androgen concentrations in all women. CONCLUSIONS: Sex-steroid concentrations appear to be regulated along several axes. Adiposity correlated directly with estrogens in postmenopausal women and with insulin, resulting in lower SHBG and increased levels of free sex steroids. Independent of adiposity and insulin, IGF-I was associated with decreased SHBG levels, and increased concentrations of androgens and postmenopausal estrogens.

Androgens↗

PubMed2004

Within- and between-cohort variation in measured macronutrient intakes, taking account of measurement errors, in the European Prospective Investigation into Cancer and Nutrition study.

Multicenter epidemiologic studies provide a unique opportunity to evaluate the association between exposure and disease at the individual and the aggregate levels. The two components can eventually be pooled to corroborate each other, using weights proportional to the intraclass correlation coefficient (ICC), which expresses the amount of between-cohort variability in the exposure variable compared with the total. The greater the ICC, the more the overall estimate will reflect the between-cohort component. Dietary measurements are affected by measurement errors, particularly within a cohort. In 1992-2000, the variability of macronutrient intake distribution before and after calibration for measurement error in the European Prospective Investigation into Cancer and Nutrition was evaluated. A two-level, random-effects model was used. Evaluation of macronutrient densities revealed that energy has a considerable effect on the calibration model, leading to ICC values larger than those for the absolute intakes. Given the shrinkage of the within-center variability, a sizable increase in the ICC was observed for protein in men and women (0.48 and 0.54, respectively) and carbohydrates in men (0.41). Results suggest that the effect of calibration on macronutrient intake variability is greater for the within-cohort component, thus increasing the relative importance of the between-cohort component. After calibration, the two components had a similar weight. This observation has important implications for the analysis of multicenter studies because the between-cohort component provides a large part of the overall heterogeneity.

Analysis of Variance↗

PubMed2002

p values for pathogens: statistical inference from infectious-disease data.

Certain features of infectious-disease data-including the aggregated nature of the data, confounding variables, correlated variables, and non-linear relations-complicate the use of standard statistical procedures. Using data on a helminth infection, we review the use of three parametric tests (analysis of variance, linear regression, and logistic regression), address the complications arising from violation of the assumptions for these tests, and suggest methods of correction. We also compare the relative merits of parametric methods with equivalent non-parametric approaches, and illustrate the differences produced with results from a Kruskal-Wallis test and a t test. The value of using a resampling method-bootstrapping-is also shown. Finally, we discuss problems arising from use of a study design that requires data on the same attribute to be collected from the same individual over a period of time, and present three methods for overcoming this complication, showing that, in the example used, the mixed effect model and generalised estimating equation give similar results.

Analysis of Variance↗