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ABSTRACT: To examine the influence of intense sweetener consumption on nutrient intakes in insulin dependent diabetics compared to controls.
Case-control food consumption survey.
Dietary data were collected from individuals in Ireland between 1998 and 1999.
Diabetics were recruited through diabetic outpatient departments of St. James's Hospital Dublin. Controls were friends of the patients or staff/students of Trinity College and University College Dublin. Of the 171 diabetics contacted, 122 agreed to participate (70% response rate) and 119 completed the study.
In all, 3-day food diaries were used to collect the food consumption data.
Fat--sugar seesaw, intense sweetness.
Patients had significantly higher % energy from starch, lower % energy from sugars and a high intake of fibre compared to controls. In both groups, there was an inverse relationship between % energy from fat and % en from sugar, with the diabetics at the lower level of sugar intake. A score of intense sweetness intakes was computed and across tertiles of this score, there were no significant effects on macronutrient intakes.
The fat-sugar seesaw present in the diabetic group was at a lower level compared to the control group. A high intake of intense sweeteners does not have a detrimental effect on macronutrient and micronutrient intakes.
European Journal of Clinical Nutrition 11/2004; 58(10):1336-41. · 2.46 Impact Factor
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ABSTRACT: A key component of a food chemical exposure assessment using probabilistic analysis is the selection of the most appropriate input distribution to represent exposure variables. The study explored the type of parametric distribution that could be used to model variability in food consumption data likely to be included in a probabilistic exposure assessment of food additives. The goodness-of-fit of a range of continuous distributions to observed data of 22 food categories expressed as average daily intakes among consumers from the North-South Ireland Food Consumption Survey was assessed using the BestFit distribution fitting program. The lognormal distribution was most commonly accepted as a plausible parametric distribution to represent food consumption data when food intakes were expressed as absolute intakes (16/22 foods) and as intakes per kg body weight (18/22 foods). Results from goodness-of-fit tests were accompanied by lognormal probability plots for a number of food categories. The influence on food additive intake of using a lognormal distribution to model food consumption input data was assessed by comparing modelled intake estimates with observed intakes. Results from the present study advise some level of caution about the use of a lognormal distribution as a mode of input for food consumption data in probabilistic food additive exposure assessments and the results highlight the need for further research in this area.
Food Additives and Contaminants 12/2003; 20(11):1023-33. · 2.13 Impact Factor
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ABSTRACT: The validity of a range of simple conceptual models designed specifically for the estimation of food additive intakes using probabilistic analysis was assessed. Modelled intake estimates that fell below traditional conservative point estimates of intake and above 'true' additive intakes (calculated from a reference database at brand level) were considered to be in a valid region. Models were developed for 10 food additives by combining food intake data, the probability of an additive being present in a food group and additive concentration data. Food intake and additive concentration data were entered as raw data or as a lognormal distribution, and the probability of an additive being present was entered based on the per cent brands or the per cent eating occasions within a food group that contained an additive. Since the three model components assumed two possible modes of input, the validity of eight (2(3)) model combinations was assessed. All model inputs were derived from the reference database. An iterative approach was employed in which the validity of individual model components was assessed first, followed by validation of full conceptual models. While the distribution of intake estimates from models fell below conservative intakes, which assume that the additive is present at maximum permitted levels (MPLs) in all foods in which it is permitted, intake estimates were not consistently above 'true' intakes. These analyses indicate the need for more complex models for the estimation of food additive intakes using probabilistic analysis. Such models should incorporate information on market share and/or brand loyalty.
Food Additives and Contaminants 11/2003; 20 Suppl 1:S61-72. · 2.13 Impact Factor
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ABSTRACT: Patterns of food additive usage in the Irish food supply and changes in patterns of usage between 1995-97 and 1998-99 were assessed by means of an Irish National Food Ingredient Database (INFID). Of the 300 additives permitted for use according to the European Union food additives Directives, some 54% were recorded in foods in INFID. Colours, emulsifiers and acids were the most frequently used additive categories, representing 18, 13 and 12% of the total additives used, respectively. Colours were most commonly recorded in sauces (n = 182 brands, 26% of sauces), emulsifiers were most commonly recorded in biscuits (n = 181 brands, 47% of biscuits) and acids were most commonly recorded in sauces (304 brands, 43% of sauces). Carotenes (E160a), Annatto (E160b), mono- and diglycerides of fatty acids (E471) and citric acid (E330) were the most commonly used colour, emulsifier and acid, respectively. All diet soft drinks (n = 37), low-fat spreads (n = 25) and liver pâtés (n = 10) recorded the use of at least one additive. When expressed in terms of the number of brands that contain additives, sauces (n = 522, 73% of sauces), biscuits (n = 323, 84% of biscuits) and preserves (n = 321, 85% of preserves) were ranked highest. For most categories of additive (n = 24), there appeared to be a minimal change in qualitative additive usage between 1995-97 and 1998-99. However, there was a significant increase in the frequency of use of emulsifiers (p < 0.001), acids (p < 0.01), sweeteners (p < 0.05) and acidity regulators (p < 0.05), and a significant decrease in the frequency of use of antioxidants (p < 0.05) during the period 1998-99 compared with 1995-97. Despite changes in additive usage patterns, it appeared that changes in the types of brands on sale between both periods were more apparent than actual changes in qualitative ingredient formulations across brands, as some 17% of brands that were on sale in 1995-97 were no longer on sale in 1998-99.
Food Additives and Contaminants 12/2002; 19(12):1105-15. · 2.13 Impact Factor
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ABSTRACT: Estimates of exposure to intentionally added flavouring substances based on two indirect methods, namely the theoretical added maximum daily intake (TAMDI) and maximized survey-derived daily intake (MSDI), were compared with exposure estimates based on a flavourings stochastic model (FSM). Twelve flavouring substances were chosen to reflect broadly the large number of flavouring substances currently used in Europe. Over 40,000 flavour formulae used at known levels of incorporation in 31 different categories of food and beverages were examined to provide maximum concentrations, distributions of concentrations and an indication of the probability of encountering each substance in a flavoured food or beverage in any category. Food consumption data were based on the intakes of males, aged 16-24 years, according to the Dietary and Nutritional Survey of British Adults (1988). The percentage of flavoured brands within food groups was estimated using the Irish National Food Ingredient Database. For all 12 flavouring substances, the estimates of TAMDI were > 97.5th percentile of the FSM, sometimes by > 3 orders of magnitude. With the exception of 2,6-dimethyl pyrazine, the 97.5th percentile of the FSM was less than the MSDI estimate. The probability of the FSM estimates exceeding the TAMDI ranged from < 0.0001 to 0.0037 for the 12 substances, while the probability of exceeding the MSDI estimates ranged from 0.0004 to 0.0753. The study supports the findings of a recent publication using detailed dietary analysis of US data that also indicated that the MSDI appeared, within the limits of the studies, to be a practical and conservative method for assessing exposure to intentionally added flavouring substances.
Food Additives and Contaminants 02/2002; 19(1):2-14. · 2.13 Impact Factor
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ABSTRACT: The purpose of this survey was to establish a database of habitual food and drink consumption in a representative sample of Irish adults aged 18-64 years.
A cross-sectional food consumption survey was carried out. Food intake data were collected using a 7-day estimated food diary. Anthropometric data included measurements of weight, height, waist and hip circumferences and body composition using bioelectrical impedance analysis. Questionnaire data included assessments of health, lifestyle and socio-demographic status, levels of physical activity, attitudes to diet and health and restrained eating.
Northern Ireland and Republic of Ireland between 1997 and 1999.
In total, 1379 adults aged 18-64 years participated in the survey and completed the 7-day food diary. This paper gives details of the methods used to carry out the survey. Sampling, respondent recruitment, dietary assessment, collection of anthropometric and questionnaire data and data management and analysis are described.
The North/South Ireland Food Consumption Survey is unique in being the first food consumption survey ever to be carried out in the Republic of Ireland and Northern Ireland concurrently using the same methodology.
Public Health Nutrition 11/2001; 4(5A):1037-42. · 2.17 Impact Factor
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J Lambe,
J Kearney,
C Leclercrq,
D Berardi,
H F Zunft,
S Sulzer,
S De Henauw,
M De Volder,
C J Lamberg-Allardt,
M U Karkkainen,
A Dunne,
M J Gibney
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ABSTRACT: In principle, a proper risk assessment for a food chemical requires that the time-frame for food chemical intake estimates matches the time-frame for the toxicological assessments upon which the safety statements (ADI, PTWI, etc.) are based. For food additives, the toxicological assessments are based on exposure over a lifetime. While food consumption data cannot be collected over the lifetimes of individuals, the information should reflect habitual intakes as closely as possible. This study investigated the possibility of combining a 3-day food diary with a food frequency questionnaire to estimate mean consumer-only food intakes comparable to estimates based on a 14-day diary. The study population consisted of 948 teenagers and analysis was based on 32 clearly defined foods. For 47% of the foods, the difference was < or = 1 g/day. When expressed as portion sizes, 56% of the foods showed differences representing < 5% of an average portion and no food showed a difference > 14% of an average portion. When between-method differences (portions/day) were plotted against the mean of the methods, the mean between-method difference was 0.02(+/- 0.06) portions/day with limits of agreement of -0.10 to 0.14. This preliminary investigation suggests that the combined 3-day diary and FFQ method provides comparable estimates of mean consumer only intakes to a 14-day diary. Therefore, a qualitative FFQ may be a useful adjunct to a food consumption survey of short duration if estimates of longer term food intakes are required.
Food Additives and Contaminants 03/2000; 17(3):177-87. · 2.13 Impact Factor
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ABSTRACT: To examine the influence of food consumption survey duration on estimates of percentage consumers, mean total population intakes and intakes among consumers only and to consider its relevance for public health nutrition and food safety issues.
Prospective food consumption survey.
A multicentre study in five centres in the European Union-Dublin, Ghent, Helsinki, Potsdam and Rome.
Teenage subjects were recruited through schools; 948 (80%) out of 1180 subjects completed the survey.
14-day food diaries were used to collect the food consumption data.
For mean total population intakes, 53% of the foods had slopes significantly different to 0 (P<0.05). In practical terms (g/day), these differences were small, with 41% of foods having differences of </=1 g/day and a further 35% having differences of 1-5 g/day. Estimates of percentage consumers based on 3 days and 14 days were 1.9 and 3.6 times the 1-day estimate, respectively. For 72% of foods, at least 50% of non-consumers on day 1 became consumers over the subsequent 13 days. Estimates of mean consumer only intakes based on 3 days and 14 days were 53% and 32% of the 1 day value.
In practical terms, survey duration influences estimates of percentage consumers and intakes among consumers only but not mean total population intakes. Awareness of this influence is important for improved interpretation of dietary data for epidemiological studies, development of food-based dietary guidelines and food chemical intakes.
The Institute of European Food Studies, a non-profit research organization based in Trinity College Dublin. European Journal of Clinical Nutrition (2000) 54, 166-173
European Journal of Clinical Nutrition 02/2000; 54(2):166-73. · 2.46 Impact Factor
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ABSTRACT: Development of food-based dietary guidelines relies on correct identification and interpretation of current dietary intake patterns. The process involves assessing which foods discriminate between those with desirable and undesirable intakes of particular nutrients. It is therefore important that those involved in this task are aware of any source of variability in the underlying food consumption data that cannot be attributed to true differences between individuals. A short survey duration can introduce a high degree of within-person variation and not reflect usual or more long-term food or nutrient intakes. As survey duration increases, the % consumers identified by a survey increases and the intakes among consumers only decrease while the total population intakes do not change. A short survey duration may also lead to misclassification of individuals into high and low consumers. Survey duration is therefore an issue that should be considered in the interpretation of dietary data when developing food-based dietary guidelines.
British Journal Of Nutrition 05/1999; 81 Suppl 2:S139-42. · 3.01 Impact Factor
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ABSTRACT: The intake of saccharin, aspartame, acesulfame K and cyclamate was assessed in 212 Italian teenagers aged 13-19 in 1996. Total daily intake of intense sweeteners was assessed on the basis of dietary records (14 consecutive days). The sweetener content of sugar-free products (soft drinks, candies, chewing gums, yoghurts, jam and table-top sweeteners) was provided by manufacturers. Sugar-free products were consumed by 77% of the subjects. Mean daily intake among consumers was 0.24 mg/kg body weight (bw) for cyclamate (13 subjects), 0.21 mg/kg bw for saccharin (9 subjects), 0.03 mg/kg bw for aspartame (162 subjects), and 0.02 mg/kg bw for acesulfame K (56 subjects). No subject exceeded the ADI (Acceptable Daily Intake) of an intense sweetener. Projections based on the present levels of use of intense sweeteners in sugar-free products and on the dietary pattern observed in the sample suggest that approaching the ADI could be possible only if subjects with high intakes of both soft drinks and table-top sugar substituted these items with respectively sugar-free beverages and table-top sweeteners containing either saccharin or cyclamate.
Food Additives and Contaminants 04/1999; 16(3):99-109. · 2.13 Impact Factor
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ABSTRACT: In the Dietary and Nutritional Survey of British Adults (DNSBA) food consumption database, brand level intake data are recorded for 2197 subjects over 7 days. This study set out to examine the incremental value of such brand level data in food consumption studies to estimate additive intake. The food codes in the DNSBA database were re-arranged into 14 food categories within each of which were varying numbers of both sub-categories of foods and of brands. Intake of the 97.5th percentile for brands and sub-categories were compared with intakes at the 97.5th percentile of the appropriate food category. Taking > or = 60 consumers as the minimal sample size for which a 97.5th percentile statistic can be calculated, only 6% of the 1363 brands listed had sufficient data to work with. Of the 14 food categories, six had a sub-category with a 97.5th percentile in excess of that of the category but none exceeded 1.3 x 97.5th percentile intake of the category. Of the 85 brands for which there were > or = 60 consumers, only 11 had 97.5th percentile intakes in excess of that statistic for the relevant food category and none exceeded a multiple of 1.3 times the category 97.5th percentile intakes. Unless dietary surveys are very large and carried out for longer periods of time, there is little value in retaining food consumption data at brand level. If 1.3x the intake of an additive from a given food category at the 97.5th percentile does not exceed the ADI, no sub-category or brand appears to do so. This may provide a valuable technique in crude estimates of food additive intake.
Food Additives and Contaminants 04/1999; 16(3):93-7. · 2.13 Impact Factor
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ABSTRACT: To examine the hypothesis that there is sufficient agreement between percentage of households purchasing selected foods using household budget surveys and percentage of individuals consuming these foods as determined in individual-based surveys to allow the former to act as a surrogate for the latter when estimating food chemical intakes using household budget data.
Database study.
Databases from Sweden, The Netherlands. Ireland and the UK.
319 foods (Sweden n = 60, The Netherlands n = 80, Ireland n = 90, UK n = 89).
Pearson correlations demonstrated a high degree of linear association between % households purchasing and % consumers (r = 0.86). Regression analysis defined a close positive relationship between the two datasets (slope 0.95, intercept +2.74). Across countries, using the regression equation, the % households predicted % consumers to within 5% of the true value for between 33 and 48% of foods and to within 10% for between 53 and 78% of foods.
Values for % households can be used as a crude surrogate for % consumers and can thus play a role in improving estimates of food additive intake.
Public Health Nutrition 01/1999; 1(4):239-47. · 2.17 Impact Factor
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ABSTRACT: Vitamin B12 and folate status were determined in 35 male HIV seropositive patients. Of these, 16 were asymptomatic (CDC II/III) and 19 were symptomatic (CDC IV) according to the Centre for Disease Control (CDC) Classification. Deviations from normal values for serum B12, serum folate and red cell folate were not a common finding in this sample of patients. No patient had low serum B12. One CDC IV patient and two CDC II/III patients were found to have raised serum B12. Dietary intake of vitamin B12 was well above the Reference Nutrient Intake for all patients. Three patients displayed low folate values (one CDC IV patient had low serum folate, one had low red cell folate and one CDC II/III patient had both). No patient displayed elevated serum or red cell folate. Only 56% of the CDC II/III and 36% of the CDC IV group were meeting the Lower Reference Nutrient Intake for folate. The only significant difference between the CDC II/III group and the CDC IV group was a lower red cell folate (although within the normal laboratory range) in the CDC IV group. There was no significant difference in dietary intake and haematological status between the drug users and the homosexuals.
European Journal of Clinical Nutrition 12/1993; 47(11):803-7. · 2.46 Impact Factor
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ABSTRACT: Any attempt to estimate food additive intake will require some level of screening to reduce the scale of the problem to a manageable level. Even then the process should always begin with crude estimates of food intake and of food additive usage level. The starting point for the latter may be the maximum permitted levels as laid down in the relevant regulations. If at that point the data are deemed acceptable, the process ends. If further requirements are needed they can be for both food intake data and food additive usage levels. Refinement may involve disaggregation of gross categories into more precise categories but research needs to be done to establish the true value of highly refined data. It remains possible that the distribution of the intakes of refined categories is similar to that of the crude categories. Intake data should relate to the population who consume the foods containing the additive in question and even then at some higher level such as the 97.5th percentile. Whether the use of this extreme is acceptable as numbers of subjects diminish in any age and sex breakdown of data remains to be seen. We also need to know something of the dietary habits and sociodemographic characteristics of high consumers and to devise ways of obtaining data for consumers-only from household budget data. Finally we need to know more of how to increase the precision of estimating the percentage of consumers, perhaps combining food frequency questionnaires with 3-day records.
Food Additives and Contaminants 13(4):405-10. · 2.13 Impact Factor
