Skip to main content Accessibility help
×
Home
Hostname: page-component-79b67bcb76-4whtl Total loading time: 0.482 Render date: 2021-05-12T17:15:47.848Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "metricsAbstractViews": false, "figures": false, "newCiteModal": false, "newCitedByModal": true, "newEcommerce": true }

Validation of protein and potassium intakes assessed from 24 h recalls against levels estimated from 24 h urine samples in children and adolescents of Turkish descent living in Germany: results from the EVET! Study

Published online by Cambridge University Press:  24 October 2011

Beate Bokhof
Affiliation:
Nutrition and Health Unit, Research Institute of Child Nutrition, Dortmund, Germany Institute for Medical Informatics, Biometrics and Epidemiology, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
Anette E Buyken
Affiliation:
Nutrition and Health Unit, Research Institute of Child Nutrition, Dortmund, Germany
Canan Doğan
Affiliation:
Nutrition and Health Unit, Research Institute of Child Nutrition, Dortmund, Germany Center for Education and Science of the Federal Revenue Administration, Branch Hamburg, Germany
Arzu Karaboğa
Affiliation:
Nutrition and Health Unit, Research Institute of Child Nutrition, Dortmund, Germany
Josa Kaiser
Affiliation:
Nutrition and Health Unit, Research Institute of Child Nutrition, Dortmund, Germany Max Rubner-Institute, Federal Research Institute of Nutrition and Food, Karlsruhe, Germany
Antje Sonntag
Affiliation:
Nutrition and Health Unit, Research Institute of Child Nutrition, Dortmund, Germany
Anja Kroke
Affiliation:
Department of Nutritional, Food and Consumer Sciences, Fulda University of Applied Sciences, Marquardstrasse 35, D-36039 Fulda, Germany
Corresponding
E-mail address:
Rights & Permissions[Opens in a new window]

Abstract

Objective

Nutrition-related health problems such as obesity are frequent among children and adolescents of Turkish descent living in Germany, yet data on their dietary habits are scarce. One reason might be the lack of validated assessment tools for this target group. We therefore aimed to validate protein and K intakes from one 24 h recall against levels estimated from one 24 h urine sample in children and adolescents of Turkish descent living in Germany.

Design

Cross-sectional analyses comprised estimation of mean differences, Pearson correlation coefficients, cross-classifications and Bland–Altman plots to assess the agreement between the nutritional intake estimated from a single 24 h recall and a single 24 h urine sample collected on the previous day.

Setting

Dortmund, Germany.

Subjects

Data from forty-three study participants (aged 5–18 years; 26 % overweight) with a traditional Turkish background were included.

Results

The 24 h recall significantly overestimated mean protein and K intake by 10·7 g/d (95 % CI of mean difference: 0·6, 20·7 g/d) and 344 mg/d (95 % CI 8, 680 mg/d), respectively. Correlations between intake estimates were r = 0·25 (P = 0·1) and 0·31 (P = 0·05). Both methods classified 70 % and 69 % of the participants into the same/adjacent quartile of protein and K intake and misclassified 7 % and 7 %, respectively, into the opposite quartile. Bland–Altman plots indicated a wide scattering of differences in both protein and K intake.

Conclusions

Among children and adolescents of traditional Turkish descent living in Germany, one 24 h recall may only be valid for categorizing subjects into high, medium or low consumers.

Type
Research paper
Copyright
Copyright © The Authors 2011

People with a migrant background differ from people in their host country not only with respect to lifestyle factors but also in related health characteristics and disease frequency. In Germany, for example, a higher prevalence of overweight and obesity is observed among children and adolescents from families with Turkish origin(Reference Kurth and Schaffrath Rosario1Reference Will, Zeeb and Baune3). The prevalence of diabetes mellitus type 2 amounts up to 14·9 % in Turkish migrants living in Germany, whereas only 8·2 % of people of German descent suffer from this disease(4). According to the Federal Statistical Office, 6·8 million migrants live in Germany. Most persons with a migration background have belonged to German society for several decades; however, little is known about their lifestyle habits, especially with respect to health and nutrition.

To date, valid data describing food patterns of children from a Turkish background are scarce(Reference Schenk and Neuhauser5). According to data from previous studies, Turkish children tend to consume relatively high amounts of raw vegetables, but also ingest less healthy foods like deep fried food and sweets more frequently than German children(Reference Mensink, Kleiser and Richter6Reference Mensink, Burger and Beitz8). However, dietary assessment instruments, such as the FFQ used in these studies, permit only crude insights into dietary patterns of children and adolescents of Turkish descent. The FFQ method is highly culturally sensitive and tailored to its target population(Reference Teufel9). Therefore, the results of such analyses are to be interpreted with caution. A dietary assessment instrument that is less sensitive to cultural differences is the 24 h recall(Reference Buzzard10). However, it has not been investigated how far 24 h recalls applied to this target group provide valid dietary data.

We therefore aimed to test the validity of a 24 h recall in a target group of children and adolescents of Turkish family background by comparing the reported intake data with urinary biomarkers: dietary intakes of protein and K as derived from a single 24 h recall were compared with the urinary excretion levels of protein and K. To that end we used data from the EVET! Study (Development, testing and validation of dietary assessment tools for children and adolescents of Turkish descent), which was conducted with the aim to develop, test and validate nutritional assessment tools for children and adolescents of Turkish descent in Germany(Reference Kroke11).

Methods

The EVET! Study was conducted in the area of Dortmund, Germany, between March 2006 and September 2007. The German Research Institute of Child Nutrition conceived this study, funded by the German Federal Ministry of Food, Agriculture and Consumer Protection. All study procedures were approved by the Ethics Committee of the University of Bonn, Germany. Study participation was performed with parental consent or with the adolescent's consent if the participant was 18 years old.

Study population

Study participants had to be of Turkish descent, aged 5–18 years and residents in the area of Dortmund, North Rhine-Westphalia, Germany. Generally, participants should have both parents from Turkish background; however, in one case the mother was of German ancestry and the father was of Turkish descent. Since successful recruitment turned out to be very difficult, various approaches were applied to recruit study participants for the EVET! Study such as direct invitation and indirect motivation via peer leaders. The complex methods of recruitment comprised the distribution of bilingual information on the study in locations such as schools, medical practices and one hospital, Turkish cultural associations, mosques and Turkish festivals. Finally, seventy-eight study participants, thirty-six (46 %) male and forty-two (54 %) female, could be included into the entire study. The present analysis considers data only of those children and adolescents who provided both a 24 h recall and a 24 h urine sample. Data from thirty-two participants had to be excluded due to incomplete or incorrect urine collections. In addition, three participants had provided 24 h recall data only with no concurrent 24 h urine sample. Hence, the final study population for the present analysis consisted of forty-three children and adolescents, fifteen (35 %) male and twenty-eight (65 %) female, aged 5–18 years.

Nutritional assessment

Dietary intake was assessed by a single 24 h recall based on EPIC-SOFT, a standardized computer program developed and validated by the International Agency for Research on Cancer in line with the EPIC (European Prospective Investigation into Cancer and Nutrition) study(Reference Voss, Charrondiere and Slimani12, Reference Slimani, Deharveng and Charrondière13). Parents of children aged 5 to 10 years were interviewed in German or, if necessary, in Turkish, in the presence of their children, who provided additional information. Adolescents (11–18 years) were interviewed personally with their parents in the background in case of possible questions. Food and beverage consumption of the previous day was assessed, i.e. the day of the urine collection. The study participants quantified their food consumption by means of a picture book comprising German and Turkish food items, which was originally developed for EPIC-SOFT(Reference Krems, Bauch and Götz14). Based on this book the EVET! Team added photos and descriptions of Turkish food portions. For the nutrient analysis of typical Turkish food items that were not available in the EPIC-SOFT nutrient database, the Turkish food database BeBiS (Beslenme Bilgi Sistemi, University of Istanbul) was used. Interviews were conducted in a standardized manner by trained and quality monitored bilingual personnel.

Urine collection and analysis

The 24 h urine collection, urine storage and analysis were performed according to the standard operating procedures of the DONALD (Dortmund Nutritional and Anthropometric Longitudinally Designed) Study(Reference Kroke, Manz and Kersting15). Parents and children were instructed personally and in written form in German and in Turkish how to collect complete 24 h urine samples.

The first micturition in the morning on the day of recording was discarded. Parents and children registered the time of this first micturition thereby defining the start of the 24 h collection, which ended with the first micturition of the following morning. All micturitions were stored immediately in Extran-cleaned, preservative-free (Extran MA 03; Merck, Darmstadt, Germany) 1-litre plastic containers with boracic acid at ≤−12°C before being transported to the research institute. A nutritionist (C.D.) picked up the urine samples, asked parents and children about the completeness of the urine samples and possible influences on urine collection, and recorded this information on the protocol sheet. At the institute, the containers were stored at ≤−20°C before being analysed. All urine samples underwent routine check using a commercial test strip after thawing and stirring(Reference Kroke, Manz and Kersting15). Volume, pH, osmolarity and creatinine were determined. Completeness of urine was ascertained via values of creatinine based on sex- and age-specific, body-weight-related reference values of creatinine for the age groups of 3, 4–5, 6–8, 9–13 and 14–18 years(Reference Remer, Neubert and Maser-Gluth16). Hence, collection-related errors were identified. According to Remer et al.(Reference Remer, Neubert and Maser-Gluth16) the lowest threshold for the excretion of creatinine in 24 h urine amounts to 0·1 mmol/kg per d, equivalent to the 5th percentile. Thus data on daily creatinine excretion rates that fell below 0·1 mmol/kg per d were regarded as incomplete and therefore not considered in our analysis.

Urinary N excretion was routinely measured by the method of Kjeldahl (Tecator 1002; Perstorp Analytical, Bristol, UK) and concentration was obtained by relating N levels to the volume of the 24 h collections. The assumption was made that excreted N accounts for 80 % of the ingested protein to account for extrarenal N losses(Reference Bingham17, Reference Bingham, Cassidy and Cole18). Based on the molecular weight, excreted N (mmol/l) was converted to g protein/d, then multiplied by the factor 6·25, based on the assumption that all proteins contain 16 % N(Reference Gibson19, Reference Gibson20), and then divided by 0·8(Reference Bingham17, Reference Bingham, Cassidy and Cole18) to account for extrarenal losses. In a further step, an age- and sex-specific reference value of protein requirement for growth was added to allow for protein retention during growth in these paediatric age groups (see Table 1: protein intake estimated from 24 h urine allowing for retention)(Reference Garlick21).

Table 1 General characteristics of the study sample: children and adolescents (n 43) aged 5–18 years of Turkish descent living in Dortmund, Germany, 2006–2007 (EVET! Study)

*Values are represented as mean and sd.

†According to Cole et al. (Reference Cole, Bellizzi and Flegal24).

‡Specific or general qualification for university entrance.

§According to Garlick(Reference Garlick21).

∣∣According to Remer and Manz(Reference Remer and Manz22, Reference Remer and Manz23).

For K intake, mmol/l was converted to g/d using molecular weight and then divided by 0·8 to account for an intestinal net absorption of 80 % for K intake(Reference Remer and Manz22, Reference Remer and Manz23).

Anthropometry and parental data

Body weight was assessed to the nearest 100 g with an electronic scale, height to the nearest 0·1 cm and skinfold thickness to the nearest 0·1 mm. For each child, age- and sex-independent standard deviation scores of weight, height, BMI were calculated using the cut-off values proposed by the International Obesity Taskforce (IOTF)(Reference Cole, Bellizzi and Flegal24). The proportion of overweight children was assessed according to the definitions of the IOTF, which correspond to a cut-off of 25 kg/m2 in adults(Reference Cole, Bellizzi and Flegal24). On a child's entry to the study, parents were asked to provide information about family characteristics, their migration as well as educational and employment status.

Statistical analysis

Descriptive statistics of the study sample are presented as means and standard deviations or frequency and percentage. Mean differences and standard deviations were calculated to draw conclusions on the absolute extent of over- or underestimation of protein and K intake by the 24 h recall on a group level. Pearson correlation coefficients were calculated(Reference Gibson25). By means of cross-classification, the percentage of persons who were either classified into the same or an adjacent quartile of protein or K intake by both methods or misclassified into the opposite quartile were computed(Reference Gibson25). Bland–Altman plots were used to illustrate the difference between both methods against the mean protein or K intake assessed by both methods(Reference Gibson25Reference Grouven, Bender and Ziegler28). The horizontal line indicates the mean of the differences. The upper and lower lines represent the upper and lower 95 % limits of agreement, which should comprise 95 % of the values in the range of the twofold standard deviation (1·96 × sd) of the mean differences, d (d ± 1·96 × sd). Ideally, the mean difference between the methods would be zero with no discernible bias, i.e. the mean differences would cluster on the horizontal line of equality (y = 0). Any deviation of the mean difference line from the line of equality indicates a bias. Moreover, any systematic variation of the differences in protein and K intake across the range of protein and K intakes suggests the presence of an additional systematic bias, which would provide further evidence of a limited agreement between the methods(Reference Bland and Altman26Reference Grouven, Bender and Ziegler28). All statistical analyses were carried out using the SAS statistical software package version 8·2 (SAS Institute Inc., Cary, NC, USA) and P < 0·05 was considered statistically significant.

Results

The acceptability of collecting 24 h urine turned out to be low, thereby notably reducing the sample size available for the present analysis. Of the seventy-five urine samples collected, only forty-three conformed to the strict quality criteria established at the research institute. General characteristics of the available study sample are presented in Table 1. A relatively high prevalence of overweight (26 %) was observed. A higher educational level was seen among 26 % of the fathers and 14 % of the mothers. The prevalence of parental smoking was high (26 % and 61 % in mothers and fathers, respectively). Protein and K intake estimates were higher according to 24 h recalls than by 24 h urine collections.

Table 2 presents the results of the validity analyses. Mean differences between both protein and K intake according to 24 h recalls and 24 h urine collections indicated an overestimation by the recall method. Pearson correlation coefficients were low for both protein and K intake. Only cross-classifications showed an acceptable agreement between the two methods: 70 % and 69 % of the participants were classified into the same or an adjacent category for protein and K intake, respectively. Misclassification was ≤7 % in the total study group for protein as well as for K intake. The Bland–Altman plots indicated systematic overestimation of protein and K intakes and a large scatter of the differences for both protein (Fig. 1) and K (Fig. 2) due to wide confidence limits. Nevertheless, the plots do not suggest the presence of an additional systematic bias, since the differences between the measurements did not increase or decrease with increasing intake levels.

Table 2 Agreement between protein and potassium intakes estimated from 24 h recalls and protein and potassium intakes estimated from 24 h urine samples among children and adolescents (n 43) aged 5–18 years of Turkish descent living in Dortmund, Germany, 2006–2007 (EVET! Study): differences, Pearson correlation coefficients and cross-classifications for agreement

Fig. 1 Bland–Altman plot for data of the total study group: children and adolescents (n 43) aged 5–18 years of Turkish descent living in Dortmund, Germany, 2006–2007 (EVET! Study). Difference between protein intake (g/d) calculated from a 24 h recall (test method) and the protein intake level (g/d) estimated from a 24 h urine sample (reference method) for each person (y-axis) plotted against the mean protein intake averaged from the two methods (x-axis). The mean of the differences is shown (— — —); also the upper and lower 95 % limits of agreement (⋯), presented as twofold standard deviations (±1.96 × sd)

Fig. 2 Bland–Altman plot for data of the total study group: children and adolescents (n 43) aged 5–18 years of Turkish descent living in Dortmund, Germany, 2006–2007 (EVET! Study). Difference between potassium intake (mg/d) calculated from a 24 h recall (test method) and the potassium intake level (mg/d) estimated from a 24 h urine sample (reference method) for each person (y-axis) plotted against the mean potassium intake averaged from the two methods (x-axis). The mean of the differences is shown (— — —); also the upper and lower 95 % limits of agreement (⋯), presented as twofold standard deviations (±1·96 × sd)

Discussion

In this sample of children and adolescents with Turkish family background and low educational status living in Germany, a single 24 h recall proved to be of only limited validity. When compared with urinary excretion data, the estimated intakes of both protein and K were considerably overestimated. Differences between the methods displayed a wide scatter and correlations were low. However, the ranking of subjects according to their intake levels appeared to be of acceptable validity.

To our knowledge, the present study is the first to validate protein and K intakes reported from 24 h recalls against protein and K intakes estimated from 24 h urines in a sample of healthy children and adolescents of Turkish descent living in Germany. Therefore, comparison with other study results is possible only to a limited extent. Similar studies in groups of children suffering from diabetes mellitus or renal insufficiency were conducted in non-migrant children only(Reference Hackett, Morton and McCowen29, Reference Wingen, Fabian-Bach and Mehls30). One study reported an overestimation of only 2·9 g protein/d among 3–16-year old participants with diabetes mellitus, and observed higher correlation coefficients. However, similar to our study the authors concluded that the protein estimates from 24 h recall were satisfactory on the group level only, while individual estimates were in part rather poor(Reference Hackett, Morton and McCowen29). The other study observed a difference between protein intake and urea-N excretion of 0·09 ± 0·06 g/kg per d among 3–19-year-old patients with chronic renal failure. The mean protein intake, specified in at least four consecutive 24 h recalls, was strongly correlated with urea-N excretion of no less than four 24 h urine collections (0·8; P = 0·0001)(Reference Wingen, Fabian-Bach and Mehls30). An American validation study on nutrient and energy intake estimates from single 24 h recalls in infants and toddlers from various ethnic backgrounds observed, similar to our study, an overestimation of energy intake of 13 % among infants and 29 % among toddlers compared with 3 d weighed food records. The intake of macro- and micronutrients was also overestimated(Reference Fisher, Butte and Mendoza31).

In our own previous study with data from the DONALD Study we observed a small but significant underestimation in protein intake of −6·4 g/d as derived from a 1 d weighed food record in comparison to excretion levels from one 24 h urine sample. However, the overall validity of the dietary assessment was considered acceptable(Reference Bokhof, Guenther and Berg-Beckhoff32). Unfortunately, data from 24 h recalls were not available to compare the validity between these two study populations.

The low number of comparable studies is probably due to the high level of compliance required from the children, adolescents and their parents for completion of both a dietary recall and a 24 h urine sample.

In contrast, validation studies in adults on 24 h recalls are more frequent(Reference Bingham, Cassidy and Cole18, Reference Kroke, Klipstein-Grobusch and Voss33, Reference Slimani, Bingham and Runswick34). Pearson correlation coefficients of most of these studies were higher than those in our study, ranging from 0·46(Reference Kroke, Klipstein-Grobusch and Voss33) to 0·94(Reference Slimani, Bingham and Runswick34). Overestimation of protein intake by 1·31 g/d was observed in only one study(Reference Black, Welch and Bingham35), whereas other studies reported underestimations(Reference Bingham, Cassidy and Cole18, Reference Kroke, Klipstein-Grobusch and Voss33, Reference Slimani, Bingham and Runswick34).

In the majority of cases, validation studies in children, adolescents and adults investigated other nutrients and/or validated nutrient intakes against nutritional assessment tools different from ours(Reference Bokhof, Guenther and Berg-Beckhoff32Reference Lietz, Barton and Longbottom37). Most of them found an acceptable validity of their tested instruments. However, none of them worked with a migrant population with comparatively low educational status, as was the case in the present study.

The reasons for the low validity of the applied dietary assessment methods observed in our study remain to be discussed. Clearly, this study population differed from most others in terms of their socio-economic and educational structure. Dietary assessment instruments in general are prone to biases due to educational attainment since they usually require a considerable ability to reflect on food intake, to oversee dietary habits over time, and they rely on certain knowledge on food and food preparation. Due to the usual recruitment of people with higher socio-economic status and with increased interest in diet and health, these other studies might have attained better validation results. Other factors influencing validity are sex, age and BMI(Reference Vaz, Bittencourt and Almeida38, Reference Ferrari, Slimani and Ciampi39). Furthermore, factors like socio-economic status, health-related activities or psychological factors are assumed to be determinants for misreporting, as suggested by a systematic literature review(Reference Poslusna, Ruprich and de Vries40). In the present study, another source of under-reporting might have resulted from the specific interview situation: adolescents who were interviewed may have concealed information about food eaten away from the parents. In addition, parents may not have been able to report the complete food intake of their children due to food eaten away from home. As these facets are assumptions and as our study sample was very small, we could not evaluate how far these and possible other factors influenced our results.

It could be argued that the use of inappropriate assumptions for protein retention may have contributed to a lower validity for assessment of protein intake. However, the same assumptions did not result in a low validity in a previous analysis of data from the DONALD Study. Furthermore, results obtained for K in the present study were derived without such assumption, suggesting that in the present study the assessment itself is problematic rather than the calculations applied to the obtained data(Reference Gibson19, Reference Bokhof, Guenther and Berg-Beckhoff32).

It is possible that repeated administration of 24 h recalls would result in more valid estimates of nutritional intake among children and adolescents of Turkish descent. However, the present study suggests that it may not be feasible to determine the validity of this alternative approach. Validation of repeated 24 h recalls would require repeated collections of 24 h urines, and 24 h urine collections were not accepted and/or well performed.

The major disadvantage of our study was the moderate coverage and response rate, which did not allow for a representative sample and stratified analyses. The major strength of our study was the recruitment of participants not often included in scientific investigations. The translation of all study documents into Turkish as well as the ability of our interviewers to perform 24 h recalls in Turkish language allowed us to include migrants of lower educational background compared with other investigations(Reference Schenk, Ellert and Neuhauser41). Furthermore, our urine collection protocol was conducted analogously to that of the DONALD Study, known for its accuracy in urine sampling.

In summary, the results of our study suggest a low overall validity of protein and K intakes estimated from one single 24 h recall as evidenced from comparison with urinary excretion levels obtained from one 24 h urine sample. Only when based on group ranking level, a satisfactory validity could be observed. Therefore, in this population, a single 24 h recall should only be performed in order to rank participants into high, medium and low consumers.

Acknowledgements

The EVET! Study was funded by the German Federal Ministry of Food, Agriculture and Consumer Protection and by the Ministry of Science and Research of North Rhine-Westphalia, Germany. There are no financial or other contractual agreements that might cause conflicts of interest or be perceived as causing conflicts of interest. There are also no financial arrangements existing between the authors and any company; no author had any conflicts of financial or personal interest. The EVET! Study was conceived and planned by A. Kroke; B.B. and A. Karaboğa recruited the participants. B.B., A. Karaboğa, J.K. and A.S. collected the data; A. Karaboğa and C.D. were responsible for all contacts and interviews conducted in Turkish language. For the present examination, C.D. collected the 24 h urine samples from the participants, carried out the nitrogen measurements and performed initial data analyses, supported by B.B.; B.B. conducted further analyses and drafted the manuscript; A.E.B. supervised the study and provided statistical expertise. All authors made substantial contributions to the data collection and/or the interpretation of the results. The authors thank the staff of the EVET! Team for conducting the recruitment, the briefing and the 24 h recalls; the staff of the Research Institute of Child Nutrition for instructing the EVET! Team in carrying out the anthropometric measurements as well as collecting and coding the dietary records; and all participants of the EVET! Study.

References

1.Kurth, B-M & Schaffrath Rosario, A (2007) Ergebnisse des bundesweiten Kinder- und Jugendgesundheitssurveys (KiGGS). Die Verbreitung von Übergewicht und Adipositas bei Kindern und Jugendlichen in Deutschland. Bundesgesundheitsblatt 50, 736743.CrossRefGoogle Scholar
2.Kleiser, C, Schaffrath Rosario, A, Mensink, GMB et al. (2009) Potential determinants of obesity among children and adolescents in Germany: results from the cross-sectional KiGGS study. BMC Public Health 9, 46.CrossRefGoogle ScholarPubMed
3.Will, B, Zeeb, H & Baune, BT (2005) Overweight and obesity at school entry among migrant and German children: a cross-sectional study. BMC Public Health 5, 45.CrossRefGoogle ScholarPubMed
4.Deutsche Diabetes Gesellschaft (2007) Tätigkeitsbericht der AG Diabetes und Migranten für das Jahr 2006. Zur Lage der Migranten mit Diabetes mellitus. http://www.deutsche-diabetes-gesellschaft.de/redaktion/organisation/ags/DM_und_Migranten_Bericht-07.php (accessed April 2007).Google Scholar
5.Schenk, L & Neuhauser, H (2005) Methodische Standards für eine migrantensensible Forschung in der Epidemiologie. Bundesgesundheitsblatt 48, 279286.CrossRefGoogle Scholar
6.Mensink, GBM, Kleiser, C & Richter, A (2007) Lebensmittelverzehr bei Kindern und Jugendlichen in Deutschland. Ergebnisse des Kinder- und Jugendgesundheitssurveys (KiGGS). Bundesgesundheitsblatt 50, 609623.CrossRefGoogle Scholar
7.Bau, AM, Gothe, RM & Borde, T (2003) Ernährungsverhalten von 3- bis 6-jährigen Kindern verschiedener Ethnien – Ergebnisse einer Kita-Studie in Berlin. Ernährungs Umschau 50, 214218.Google Scholar
8.Mensink, GBM, Burger, M, Beitz, R et al. (2002) Was essen wir heute? Ernährungsverhalten in Deutschland. Beiträge zur Gesundheitsberichterstattung des Bundes. Berlin: Robert Koch Institut.Google Scholar
9.Teufel, NI (1997) Development of culturally competent food-frequency questionnaires. Am J Clin Nutr 65, Suppl. 4, 1173S1178S.CrossRefGoogle ScholarPubMed
10.Buzzard, M (1998) 24-Hour dietary recalls. In Nutritional Epidemiology, pp. 5073 [WC Willett, editor]. New York: Oxford University Press.Google Scholar
11.Kroke, A (2007) Final report concerning the research project 05HS016. Development, testing and validation of nutritional assessment tools in children and adolescents of Turkish descent. http://download.ble.de/05HS016.pdf (accessed May 2011).Google Scholar
12.Voss, S, Charrondiere, UR, Slimani, N et al. (1998) EPIC-SOFT a European dietary assessment instrument for 24 h recalls. Z Ernährungswiss 37, 227233.CrossRefGoogle Scholar
13.Slimani, N, Deharveng, G, Charrondière, RU et al. (1999) Structure of the standardized computerized 24-h diet recall interview used as reference method in the 22 centers participating in the EPIC project. European Prospective Investigation into Cancer and Nutrition. Comput Methods Programs Biomed 58, 251266.CrossRefGoogle ScholarPubMed
14.Krems, C, Bauch, A, Götz, A et al. (2006) Methoden der Nationalen Verzehrsstudie II. Ernährungs Umschau 53, 4546.Google Scholar
15.Kroke, A, Manz, F, Kersting, M et al. (2004) The DONALD Study. History, current status and future perspectives. Eur J Nutr 43, 4554.CrossRefGoogle ScholarPubMed
16.Remer, T, Neubert, A & Maser-Gluth, C (2002) Anthropometry-based reference values for 24-h urinary creatinine excretion during growth and their use in endocrine and nutritional research. Am J Clin Nutr 75, 561569.CrossRefGoogle ScholarPubMed
17.Bingham, SA (2003) Urine nitrogen as a biomarker for the validation of dietary protein intake. J Nutr 133, Suppl. 3, 921S924S.CrossRefGoogle ScholarPubMed
18.Bingham, SA, Cassidy, A, Cole, TJ et al. (1995) Validation of weighed records and other methods of dietary assessment using the 24 h urine nitrogen technique and other biological markers. Br J Nutr 73, 531550.CrossRefGoogle ScholarPubMed
19.Gibson, R (editor) (2005) Assessment of nutrient intakes from food consumption data. In Principles of Nutritional Assessment, p. 82. New York: Oxford University Press.Google Scholar
20.Gibson, R (editor) (2005) Validity in dietary assessment methods. In Principles of Nutritional Assessment, p. 170. New York: Oxford University Press.Google Scholar
21.Garlick, PJ (2006) Protein requirements of infants and children. Nestle Nutr Workshop Ser Pediatr Program 58, 3947.CrossRefGoogle ScholarPubMed
22.Remer, T & Manz, F (1994) Estimation of the renal net acid excretion by adults consuming diets containing variable amounts of protein. Am J Clin Nutr 59, 13561361.CrossRefGoogle ScholarPubMed
23.Remer, T & Manz, F (1995) Potential renal acid load of foods and its influence on urine pH. J Am Diet Assoc 95, 791797.CrossRefGoogle ScholarPubMed
24.Cole, TJ, Bellizzi, MC, Flegal, KM et al. (2000) Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 320, 12401243.CrossRefGoogle ScholarPubMed
25.Gibson, R (editor) (2005) Validity in dietary assessment methods. In Principles of Nutritional Assessment, pp. 183187. New York: Oxford University Press.Google Scholar
26.Bland, JM & Altman, DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1, 307310.CrossRefGoogle ScholarPubMed
27.Bland, JM & Altman, DG (1999) Measuring agreement in method comparison studies. Stat Methods Med Res 8, 135160.CrossRefGoogle ScholarPubMed
28.Grouven, U, Bender, R, Ziegler, A et al. (2007) Comparing methods of measurement. Dtsch Med Wochenschr 132, Suppl. 1, 69S73S.CrossRefGoogle Scholar
29.Hackett, AF, Morton, S, McCowen, C et al. (1987) Measurement of food intake in children with diabetes mellitus: a comparison of protein intake and urine nitrogen. Diabetes Res 6, 2932.Google ScholarPubMed
30.Wingen, AM, Fabian-Bach, C & Mehls, O (1993) Evaluation of protein intake by dietary diaries and urea-N excretion in children with chronic renal failure. European Study Group for Nutritional Treatment of Chronic Renal Failure in Childhood. Clin Nephrol 40, 208215.Google Scholar
31.Fisher, JO, Butte, NF, Mendoza, PM et al. (2008) Overestimation of infant and toddler energy intake by 24-h recall compared with weighed food records. Am J Clin Nutr 88, 407415.CrossRefGoogle ScholarPubMed
32.Bokhof, B, Guenther, AL, Berg-Beckhoff, G et al. (2010) Validation of protein intake assessed from weighed dietary records against protein estimated from 24 h urine samples in children, adolescents and young adults participating in the Dortmund Nutritional and Longitudinally Designed (DONALD) Study. Public Health Nutr 13, 826834.CrossRefGoogle Scholar
33.Kroke, A, Klipstein-Grobusch, K, Voss, S et al. (1999) Validation of a self-administered food-frequency questionnaire administered in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study: comparison of energy, protein, and macronutrient intakes estimated with the doubly labeled water, urinary nitrogen, and repeated 24-h dietary recall methods. Am J Clin Nutr 70, 439447.CrossRefGoogle ScholarPubMed
34.Slimani, N, Bingham, S, Runswick, S et al. (2003) Group level validation of protein intakes estimated by 24-hour diet recall and dietary questionnaires against 24-hour urinary nitrogen in the European Prospective Investigation into Cancer and Nutrition (EPIC) calibration study. Cancer Epidemiol Biomarkers Prev 12, 784795.Google ScholarPubMed
35.Black, AE, Welch, AA & Bingham, SA (2000) Validation of dietary intakes measured by diet history against 24 h urinary nitrogen excretion and energy expenditure measured by the doubly-labelled water method in middle-aged women. Br J Nutr 83, 341354.CrossRefGoogle ScholarPubMed
36.Larsson, CL, Westerterp, KR & Johansson, GK (2002) Validity of reported energy expenditure and energy and protein intakes in Swedish adolescent vegans and omnivores. Am J Clin Nutr 75, 268274.CrossRefGoogle ScholarPubMed
37.Lietz, G, Barton, KL, Longbottom, PJ et al. (2002) Can the EPIC food-frequency questionnaire be used in adolescent populations? Public Health Nutr 5, 783789.CrossRefGoogle ScholarPubMed
38.Vaz, JS, Bittencourt, M, Almeida, JC et al. (2008) Protein intake estimated by weighed diet records in patients with type 2 diabetes: misreporting and intra-individual variability using 24-hour nitrogen output as criterion standard. J Am Diet Assoc 108, 867872.Google ScholarPubMed
39.Ferrari, P, Slimani, N, Ciampi, A et al. (2002) Evaluation of under- and overreporting of energy intake in the 24-hour diet recalls in the European Prospective Investigation into Cancer and Nutrition (EPIC). Public Health Nutr 5, 13291345.CrossRefGoogle Scholar
40.Poslusna, K, Ruprich, J, de Vries, JH et al. (2009) Misreporting of energy and micronutrient intake estimated by food records and 24 hour recalls, control and adjustment methods in practice. Br J Nutr 101, Suppl. 2, 73S85S.CrossRefGoogle ScholarPubMed
41.Schenk, L, Ellert, U & Neuhauser, H (2007) Kinder und Jugendliche mit Migrationshintergrund in Deutschland. Methodische Aspekte im Kinder- und Jugendgesundheitssurvey (KiGGS). Bundesgesundheitsbl Gesundheitsforsch Gesundheitsschutz 50, 590599.CrossRefGoogle Scholar
You have Access

Send article to Kindle

To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Validation of protein and potassium intakes assessed from 24 h recalls against levels estimated from 24 h urine samples in children and adolescents of Turkish descent living in Germany: results from the EVET! Study
Available formats
×

Send article to Dropbox

To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

Validation of protein and potassium intakes assessed from 24 h recalls against levels estimated from 24 h urine samples in children and adolescents of Turkish descent living in Germany: results from the EVET! Study
Available formats
×

Send article to Google Drive

To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

Validation of protein and potassium intakes assessed from 24 h recalls against levels estimated from 24 h urine samples in children and adolescents of Turkish descent living in Germany: results from the EVET! Study
Available formats
×
×

Reply to: Submit a response


Your details


Conflicting interests

Do you have any conflicting interests? *