The doubly labelled water technique is considered the standard reference and therefore the “gold standard” for measurement of total energy expenditure in humans, but it is of seldom use due to high cost and high facility requirements [358]. In the DONALD study the dietary intake is assessed using 3-day weighed dietary records, which is often regarded to be the “gold standard” within traditional dietary assessment methods [359].
Weighed food records do not rely on an individual’s memory and portion sizes are very precise as they do not rely on estimations. Information of type and brand name of all foods consumed is requested. In the DONALD study, recipes are collected as well as the packages or the food labels for commercial foods consumed. These additional information are then added to the dietary record data [318]. Disadvantageous of weighed diet records and prospective methodologies in general are the high burden to participants and participants need to be motivated. Due to the act of weighing and recording food intake in prospective methods, participant’s food choices may be influenced during the recording period and hence the method is reactive [360]. In addition, a 3-day dietary record may not be able to capture foods which are seldomly eaten such as nuts or fish and repeated 3-day weighed dietary records are needed to capture the habitual dietary intake [361].
Furthermore, DONALD participants grow up with this method and detailed data on dietary intake are assessed repeatedly. As discussed earlier, interest in the study may be due to the higher socioeconomic and educational status of the DONALD population and an excellent example of the motivation and compliance among DONALD participant’s is the collection of dietary records during puberty. Puberty is a phase of change and development for adolescents, which may not be the easiest time to impose high standards in terms of data collection. It is therefore of note that DONALD participants included in the analyses provided 88% (OA1 and OA3) and 86% (OA4) of the maximum number of food records which had been scheduled. Additionally, 94% (OA1 and OA3) and 93% (OA4) of all 3-day weighed dietary records completed were plausible. A 3-day weighed dietary record was considered plausible when the total recorded energy intake was adequate in relation to the basal metabolic rate (estimated from the Schofield equations [362]) using modified cut-offs from Goldberg et al [363]. A
validation study among DONALD participants has shown that dietary protein intake in children and adolescents can be estimated with acceptable validity by 3-day weighed dietary records [364], suggesting good validity of dietary data.
The RESIST study used 24h dietary recalls to estimate participant’s intake of food and beverages. This method has the ability to collect detailed, qualitative information about foods consumed with lower burden for participants. Therefore, it is applicable to broad populations of different ethnicity, can be conducted successfully either face-to-face or over the phone. Disadvantageous of 24h recalls are that they rely on memory, perception, conceptualization of food portion sizes and the presence of an observer [365]; in the RESIST study, 24h dietary recalls were conducted by trained dieticians. To capture the habitual intake of a population repeated 24h dietary recalls are needed. For the RESIST study this was the appropriate method to assess dietary intake and suitable for this young study population. It has been previously used in a nationwide study among Australian adolescents and a food model booklet was applied to assist with estimating the amounts of foods [117]. The analyses of the DONALD study included only participants who had provided plausible or more plausible than implausible food record data. With regards to the RESIST study a plausibility check based on basal metabolic rate was not an option because this study was designed as a weight loss study. Therefore, all 24h dietary recalls provided were included in the analyses. Overall, RESIST participants included in the secondary data analyses provided 78% of all scheduled recalls (i.e. 13 participants provided 1 recall, 34 participants provided 2 recalls, and 44 participants provided 3 recalls), thus less diet data than that available from the DONALD participants.
Estimating dietary intake
Concern has been raised regarding the reproducibility of measuring the GI value of a food [36], because there exist numerous factors influencing the glycaemic response to a food (see chapter 2.1.1, Table 1). Furthermore, the GI can vary between similar foods due to regional or seasonal differences. Variability of glycaemic response is however, not only a problem of GI, but of other nutrients as well [51, 366]. As already discussed in the original articles (OA1, OA2), estimation of dietary GI and GL as well as II an IL is challenging. The GI assignment is often difficult using FFQs, due to the problem that low and high-GI foods end up in one food group (e.g. whole-kernel and whole meal breads). In addition, assignment of GI values to foods is often based on GI values available for similar foods only and may vary from researcher to researcher. Considering these problems, some studies may not be able to validly
discriminate consumers of diets with a high dietary GI from those consuming a lower GI diet [367]. By contrast, 3-day weighed dietary records as well as 24h dietary recalls provide detailed data on reported foods allowing the assignment of GI and FII value to each (carbohydrate containing) food recorded. Nevertheless, assignments of GI values to foods recorded may vary and it is hence important to follow standard procedures (see OA1 and OA2). Finally, the method of estimating GI and GL of a whole diet has been criticised [36], since the glucose response is known to be influenced by proportions of macronutrients in a mixed meal. However, many, but not all studies [368, 369], suggest that the estimation of the GI of a whole diet or mixed meal can be accurately estimated from GI values of the constituent foods [41, 370-372]. Consequently, limitations raised for GI may also apply to the estimation of dietary insulin demand (as mentioned in OA1).
Anthropometric measurements
In both studies, DONALD and RESIST, anthropometric measurements were performed according to standardised procedures by trained personnel. Skinfold measurements were used within the DONALD study to estimate %BF, whereas the RESIST study used the DEXA method to estimate %BF, fat mass and lean mass.
Even the best methods used in epidemiology and clinical trials are indirect and the choice for an optimal “gold standard” is not completely clear [373]. However, DEXA method has been regarded as a “gold standard” [374]. It is practicable and provides reproducible measurements of body components, i.e. fat mass, fat-free mass, bone-mineral mass. Furthermore, the validity of DEXA is high among most populations; errors have only been reported in younger and older populations [373]. Even though the radiation dose is low, further disadvantages of the DEXA method are its costs and trained radiology personnel are needed to operate. Another disadvantage exists especially with regard to obese participants, because they may exceed the maximum scan widths of the DEXA machine. If so, participants need to be “mummy wrapped” using thin sheets if Velcro straps were not sufficient, with arms placed in a lateral position to reduce participants width in order to get a result [324]. Skinfold measurements would not be an alternative to estimate %BF in obese adolescents, because they only poorly predict total fat mass if compared to DEXA [375].
Furthermore, it has been shown that among overweight and obese children, the DEXA method produced similar estimations for %BF as air-displacement-plethysmography (using a Bod Pod) and total body water (determined by deuterium oxide (2H2O) dilution using saliva
samples) compared to the four-compartment model [376], making DEXA an appropriate method for the RESIST study.
Within the DONALD study it is important to use a method that is applicable on an annual measurement basis and hence the DEXA method would not be an option. As already discussed in the original article (see OA1), hydrostatic weighing would be more precise method to estimate %BF [377]. This method is, however, not feasible for epidemiological studies or clinical trials such as those on which this thesis is based on. Even though the skinfold technique has been controversially discussed, it is probably the most widely used method in epidemiological studies, providing a direct measure of %BF [373]. Skinfold measurements are preferred within an epidemiological setting due to its low costs, but again, trained personnel are needed. To ensure quality of data within the DONALD study, the three study nurses undergo an annual quality control. More details on this are given in the original article (OA1, appendix 1; Methods – Anthropometric measurements). Nevertheless, one major limitation is that only subcutaneous fat is measurable by callipers, hence not all metabolically relevant fat, i.e. visceral fat, can be assessed.
BIA could be considered another alternative method feasible within a setting of a cohort study or clinical trial, because it is of simple practice, quick and safe [373]. However, relatively recent findings suggest that BIA is mainly useful because it includes height and weight within the equations to estimate fat and lean mass. The measurement of impedance itself adds only little to the final result and sometimes random error only [378]. Therefore, BIA does not seem to be an actual alternative within epidemiological studies [373].
Looking at these alternatives the DEXA method as well as skinfold measurements are the best methods practicable and available to be used in the RESIST and DONALD study, respectively.
Blood measurements
Because of the open cohort design of the DONALD study, many participants have not yet reached young adulthood and of those who did, to date, only one blood sample was available. Therefore, as it was discussed in the original article (OA4, appendix 4); the analysis was based on this single measurement of the GH-IGF axis in younger adulthood to represent long- term circulating levels. Nevertheless, an advantage of the analytics was that each sample was measured twice to obtain all parameters of the GH-IGF axis.
Epidemiological studies usually rely on single biological specimen (e.g. blood sample) from each participant, which is both for cost and logistical reasons [379, 380]. It could be argued
that repeated measurements of IGF-I and its binding proteins might more accurately reflect circulating levels [380]. However, in the case of the GH-IGF axis this may not be a problem as IGF-I values from repeated measurements (mean time between measurements was 42 days (SD 4.8)) were found to have a low intra-individual variation [381] and serum measurements of IGF-I and its binding proteins have been found to be quite representative of serum concentrations over longer time periods. In a subset of 76 participants of the New York University Women’s Health Study correlations between repeated measurements (lag-time between the baseline and second visit ranged from 11-65 months, the median lag-time was 14 months) of IGF-I, IGFBP-3 and IGFBP-1 were strong, albeit weaker for IGFBP-2 (n=68) [382, 383].
In the RESIST study an OGTT was used to calculate the ISI, which was the primary outcome. According to Yeckel et al the ISI is a good and reliable method to assess whole body insulin sensitivity among obese children and adolescents. In fact, the ISI represents a good estimate of clamp-derived insulin sensitivity (r=0.78, p<0.0005) [384].
Lifestyle and parental characteristics
One problem of epidemiological studies is that covariates are often imperfectly measured or unmeasured. Of all variables obtainable for our analyses (e.g. early life and socioeconomic factors) a drawback was that only a relatively crude measure of physical activity was available (time spent outdoors, active, moderately active or inactive). Including this physical activity measure in the models did not change the results (OA1, OA3, and OA4). Since 2004, physical activity is assessed using a detailed questionnaire, but this data was only available for 35% (OA1 and OA3) and 37% (OA4) of all DONALD participants included in the analyses and was hence not used as covariate. Since 2013, physical activity is assessed with accelerometers which will be available in the future. In addition, sample sizes, which may be small, restrict the number of covariates. With the use of “too” many covariates the model will lack precision and will be unreliable to validly examine an association [385]. Overall, residual confounding may remain which cannot be controlled for. Adolescence in general is a period of change and there exist many potential influencing factors, such as socio-environmental, life style or psychological factors, which cannot be accounted for and may therefore confound when the relations between dietary exposures and outcomes are examined. The DONALD sample is, however, relatively homogenous, which might reduce vulnerability to residual confounding.
The RESIST trial has a relatively small sample size, which is not unusual for clinical trials, and owed to the fact that RESIST includes a high risk study population, i.e. obese adolescents with features of insulin resistance and/or prediabetes. Not only recruitment, as mentioned before, but also data assessment can be challenging and missing data may occur. Within the analysis only little adjustment was conceivable and it was for example not possible to adjust for physical activity or metformin treatment (compliance) as this data were not available for this analysis. With regards to metformin, this may not be a problem since all participants received a standard dosage (initial dose was 250 mg twice a day; after the first two weeks this was increased to a final dose of 500 mg twice a day). Regarding the family history, RESIST was relatively homogenous, as the majority of parents were overweight, obese or had a history of type 2 diabetes.