EPIC is among the largest cohort studies, with approximately 475,000 study participants, on the etiological influence of diet and chronic diseases. During a 4-year recruitment period, two German EPIC centers, located in Heidelberg and Potsdam, aimed to recruit a total of 60,000 study participants from the local populations. The recruitment process was based on addresses from general population registries and started 4–5 weeks in advance with an initial invitation by mail to the basic examination for this study. Subjects not responding within 2 weeks were reminded. In Potsdam, this was done by mail and telephone, and in Heidelberg by telephone. During the recruitment phase, from 1994 to 1998, 53,162 subjects in total were examined for the cohort studies in Heidelberg (n = 25,546) and Potsdam (n = 27,616). The participation rate, compared to the invited number of subjects, was 22.7% in Potsdam and 38.3% in Heidelberg, with a considerable variation by municipality and gender. A comparison with data from the National Health Survey 1991/1992 revealed that the cohort populations were of higher socio-economic status and were healthier than the source population. We concluded that the selective participation would help to ensure high maintenance of the cohort during active follow-up. Selective participation does not harm etiological conclusions because disease associations are derived internally as relative risk. The relative risk estimates can be used to calculate population-attributable risk and preventable proportion, based on exposure prevalence derived by surveys and other studies.
Objective: To evaluate the influence of recent weight changes (weight gain, loss and cycling) on subsequent weight changes. Design: Prospective cohort study with 2 y of follow-up. Data analysis with a polytomous logistic regression model. Subjects: A total of 18 001 non-smoking subjects, 6689 men and 11 312 women, from the general population. Measurements: Body height and weight measurements and interview data on lifestyle habits and medical history at baseline. For follow-up, self-administered questionnaires for assessment of body weight and incident diseases. Results: Recent changes in body weight, that is weight gain, weight loss and weight cycling, were significant predictors of subsequent weight changes in both men and women after controlling for age, baseline BMI and several lifestyle and behavioural characteristics as potential confounding factors. Weight cycling before baseline was the strongest predictor of subsequent large weight gain ( ! 2 kg) with an odds ratio (OR) of 4.84 (95% confidence interval (CI) 3.34 -7.02) in men. In women, prior weight loss was the strongest predictor of subsequent large weight gain (OR 4.77; 95% CI 3.63 -6.03), followed by weight cycling (OR 3.02; 95% CI 2.15 -4.25). Conclusion: These data indicate the need for thorough weight history assessment to identify those who are most likely to gain weight. Effective weight control before the development of obesity or after intentional weight loss due to obesity should be a primary goal in the management of obesity.
OBJECTIVE: To investigate whether body mass index (BMI) is related to energy intake during pregnancy, and whether BMI, energy intake and other factors are related to net weight gain. DESIGN: Longitudinal, duration of pregnancy. SUBJECTS: 156 healthy pregnant women residing in Quedlinburg county, Germany. METHODS: Weighed 7 d food records and standardized anthropometric measures in the ®rst, second and third trimester. The analysis of variance (ANOVA) statistical technique was used to analyze differences in energy intake, net weight gain and birthweight across BMI groups, and the Cochran-Mantel Haenszel test was used to analyze food group intake by BMI group. RESULTS: Women at the highest level of BMI were signi®cantly less often in the high energy intake category than women at the medium or low level of BMI (15% vs 36% and 48%). Net weight gain during pregnancy was independently in¯uenced by BMI status and energy intake. Women at the highest level of BMI gained signi®cantly less weight (4.2 kg) from ®rst to third trimester than women at the medium or low levels of BMI (weight gains of 6.2 kg and 5.9 kg, respectively). Women with a low daily energy intake gained 4.6 kg during pregnancy, while women with medium and high energy intakes gained 6.0 kg and 6.1 kg, respectively. Examination of net weight gain simultaneously across BMI and parity groups revealed a much lower net weight gain among multigravid women at the highest BMI level (3.3 kg). Primigravid high BMI women, in contrast, gained 6.9 kg, whereas multigravid and primigravid women at medium and low BMI levels gained average of 4.8 kg and 6.5 kg, respectively. The mean birth weight in the three BMI groups did not differ and was not in¯uenced by age, marital status, education, parity or smoking. CONCLUSION: Because other studies have shown that weight gain during pregnancy increases the risk of subsequent overweight, multigravid high BMI women may prevent an increased weight retention after pregnancy due to lower weight gain in the current gestation. A lower caloric diet may help to accomplish a lower weight gain during pregnancy in overweight women without increased risk of low birth weight infants. These ®ndings indicate further investigation of the associations between BMI, parity and caloric intake during pregnancy are needed to increase understanding of factors affecting subsequent weight gain.
Quality control is an indispensable part of quality assurance in any study, intending to ensure high standards during data acquisition. The aim of this paper is to describe the measures of quality control undertaken in the German EPIC study centers and to present selected results of these procedures (EPIC = European Prospective Investigation into Cancer and Nutrition). For all data assessment tools applied in the German EPIC study, procedures were developed to monitor both the personnel as well as the technical instruments. These procedures combined quantitative and qualitative measurements of quality control. Interviewer performance was evaluated through direct observation and rated according to an evaluation score. Blood pressure and anthropometric measurements were both controlled through direct observation of measurement procedures as well as through periodical technical control of measurement devices. Blood sampling procedures were directly monitored and subsequent handling of the probes tightly recorded, including information on time sequence of work-up and room temperature. With these diverse control measurements and the obtained rating of assessment procedures a broad pool of information has been made available to support a critical evaluation of the data obtained in the EPIC study centers in Heidelberg and Potsdam.
OBJECTIVE: To determine the relation of skeletal body build and obesity to blood pressure and the prevalence of hypertension. DESIGN: Cross-sectional data obtained from the baseline recruitment of the EPIC-Potsdam Study, which is part of the European Prospective Investigation into Cancer and Nutrition (EPIC). SUBJECTS: A total of 10 303 subjects (4387 men, aged 40 ± 65 y and 5916 women, aged 35 ± 65 y) were recruited between January 1995 and July 1996. MEASUREMENTS: Anthropometric measures included body mass index (BMI), waist-hip ratio (WHR) and metrik index (MIX) as a measure of body build that is derived from the relation of chest depth and breadth to body height. Systolic and diastolic blood pressure was obtained using automatic oscillometric devices. Hypertension was de®ned as blood pressure !160a95 mmHg or current use of antihypertensive medication. Information on lifestyle factors were obtained by personal interview. STATISTICAL ANALYSIS: Logistic regression was used to de®ne the association of categories of BMI, WHR, and MIX and the prevalence of hypertension. Odds ratios (ORs) of being hypertensive were estimated comparing the highest to the lowest quintile, adjusting for age, smoking status, alcohol intake level, educational attainment, physical activity categories, and each of the anthropometric variables. RESULTS: The simultaneously adjusted OR of being hypertensive, comparing the highest vs the lowest category, was for BMI 2.3 (95% con®dence interval (CI) 1.6 ± 3.2) in men and 1.8 (95% CI 1.4 ± 2.5) in women, for WHR 1.8 (95% CI 1.4 ± 2.4) in men and 1.5 (95% CI 1.2 ± 2.0) in women, and for MIX (largest chest size vs lowest chest size relative to body height) 2.0 (95% CI 1.4 ± 2.8) in men and 2.2 (95% CI 1.6 ± 3.1) in women. CONCLUSION: In addition to measures of overall obesity (BMI) as well as central obesity (WHR), skeletal body build (MIX) was independently associated with the prevalence of hypertension. The biological mechanism relating MIX to hypertension, however, is still unclear and needs further exploration.
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