Abstract Background The associations of vegetarian diets with risks for site-specific cancers have not been estimated reliably due to the low number of vegetarians in previous studies. Therefore, the Cancer Risk in Vegetarians Consortium was established. The aim is to describe and compare the baseline characteristics between non-vegetarian and vegetarian diet groups and between the collaborating studies. Methods We harmonised individual-level data from 11 prospective cohort studies from Western Europe, North America, South Asia and East Asia. Comparisons of food intakes, sociodemographic and lifestyle factors were made between diet groups and between cohorts using descriptive statistics. Results 2.3 million participants were included; 66% women and 34% men, with mean ages at recruitment of 57 (SD: 7.8) and 57 (8.6) years, respectively. There were 2.1 million meat eaters, 60,903 poultry eaters, 44,780 pescatarians, 81,165 vegetarians, and 14,167 vegans. Food intake differences between the diet groups varied across the cohorts; for example, fruit and vegetable intakes were generally higher in vegetarians than in meat eaters in all the cohorts except in China. BMI was generally lower in vegetarians, particularly vegans, except for the cohorts in India and China. In general, but with some exceptions, vegetarians were also more likely to be highly educated and physically active and less likely to smoke. In the available resurveys, stability of diet groups was high in all the cohorts except in China. Conclusions Food intakes and lifestyle factors of both non-vegetarians and vegetarians varied markedly across the individual cohorts, which may be due to differences in both culture and socioeconomic status, as well as differences in questionnaire design. Therefore, care is needed in the interpretation of the impacts of vegetarian diets on cancer risk.
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A review of the literature concerning the design, utilisation and validation of food-frequency questionnaires (FFQ) has been carried out using a semi-systematic approach to obtaining, reviewing and extracting data from articles. Databases were searched from 1980 to 1999. The present review identified 227 validation (from 1980 to September 1999) and 164 utilisation (for 1998 only) studies. A number of design issues have been evaluated through the present review. These include: the need to consider how portion sizes have been described, self-defined giving higher mean correlations; how an FFQ was administered, interviewer-administered giving higher mean correlations for some nutrients; how many items to include on an FFQ, those with the largest number of items having higher correlations. Validation techniques were described. Most validation studies involved comparing an FFQ against another dietary assessment method; only 19 % compared an FFQ to a biomarker. Measurement differences were most commonly assessed by correlation coefficients as opposed to other more appropriate methods. Mean correlation coefficients were highest for Ca and fat, and lowest for vitamin A and vegetables. The utilisation studies showed that FFQ were most commonly used in cross-sectional surveys, with ninety-three of the FFQ being designed to be disease-specific. The present review results were presented to a group of experts and a consensus arrived at concerning the development, validation and use of FFQ. Recommendations derived from the consensus arising from the literature review are presented as an appendix to the present paper.
Dietary assessment is complex, and strategies to select the most appropriate dietary assessment tool (DAT) in epidemiological research are needed. The DIETary Assessment Tool NETwork (DIET@NET) aimed to establish expert consensus on Best Practice Guidelines (BPGs) for dietary assessment using self-report. The BPGs were developed using the Delphi technique. Two Delphi rounds were conducted. A total of 131 experts were invited, and of these 65 accepted, with 48 completing Delphi round I and 51 completing Delphi round II. In all, a total of 57 experts from North America, Europe, Asia and Australia commented on the 47 suggested guidelines. Forty-three guidelines were generated, grouped into the following four stages: Stage I. Define what is to be measured in terms of dietary intake (what? who? and when?); Stage II. Investigate different types of DATs; Stage III. Evaluate existing tools to select the most appropriate DAT by evaluating published validation studies; Stage IV. Think through the implementation of the chosen DAT and consider sources of potential biases. The Delphi technique consolidated expert views on best practice in assessing dietary intake. The BPGs provide a valuable guide for health researchers to choose the most appropriate dietary assessment method for their studies. These guidelines will be accessible through the Nutritools website, www.nutritools.org .
Childhood obesity has increased dramatically over the past few decades, even more so in the last few years. This increase has finally reached pandemic levels in the developed world and is ever increasing in the developing world with no sign of it decreasing in the foreseeable future (Connelly et al., 2007; Wang & Lobstein, 2006). Current records show that overweight and obesity and its related co morbidities are the fifth leading risk for mortality, globally. Obesity substantially increases the risk of Type II diabetes, heart disease and certain cancers (WHO, 2009). As a result obesity has become a main concern for public health officials at a global scale (Herrick, 2007). Whilst it is known that obesity in its simplest form is due to increased consumption of food and decreased amounts of physical activity, it has been proposed that it is further increased by environmental rather than genetic factors (Hill & Peters, 1998). The overall aim of this paper is to analyse cross sectional data obtained from the National Child Measurement Programme. This gives data for 4-5 year olds and 10-11 year olds at school since 2006. Obesity will be defined using both the British Reference dataset and the International Obesity Task Force (IOTF) to allow for international comparison. The case study area is Wigan, Lancashire in the UK. This will allow for small scale analysis of environmental factors in relation to other indicators that determine obesity levels. Firstly it will enable us to map changing obesity levels at the small area level and then identify any areas that seem to be conforming to or resisting the obesogenic environment they are in. Further analysis will allow identification of areas which are showing obesity rates that contradict the results the environment suggests they should have, low obesity rates in low income areas (or indeed high obesity in areas of affluence). KEYWORDS Childhood Obesity, Obesogenic Environments, NCMP
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