Pre-prepared commercial foods (convenience foods, CFs) are one aspect of modern dietary habits. The present paper examines the association between CF consumption and dietary quality or body weight status in a sample of German children and adolescents.
Linear mixed-effect regression analyses using data from 586 participants (296 boys, 3–18 years) in the Dortmund Nutritional Anthropometric Longitudinally Designed Study, who yearly completed 1890 3-day dietary records and anthropometric measurements in 2004–2008, was used.
CF intake (percent total food intake) showed no significant association with macronutrient intakes (%E), with exception of a significant positive association with polyunsaturated fatty acid (PUFA) intake (P<0.0001). Considering only high-energy-dense (ED)-CF (40% of the CF intake), there was a significant negative association with total protein, carbohydrate and saturated fatty acid intake (%E) (P<0.05), and a positive with total fat and PUFA (P<0.01). The nutrient quality index (harmonic mean of 10 vitamins and minerals as the percentage of the reference intakes) showed a significant negative trend with increased consumption of CF (P=0.0013). No significant association between baseline or change in consumption of CF and baseline or change in parameters of body weight (standard deviation score of body mass index (weight/height2) or percentage body fat (%BF) estimated from skinfolds) was found. Among boys, baseline consumption of high-ED-CF significantly predicted change in %BF during the study period (β 0.104, P=0.0098).
Our results point to an impairment of dietary quality with high consumption of CF and to a small but positive association between consumption of high-ED-CF in boys and weight.
One aspect of modern dietary habits is the consumption of pre-prepared food products, that is, convenience foods (CFs). Several studies showed their widespread use in children (Northstone and Emmett, 2005; Alexy et al., 2008; Pryer and Rogers, 2009), adolescents (Milligan et al., 1998) and adults (Pryer et al., 2001; Johnson-Down et al., 2006) in western countries.
Dietary surveys that examine the association between CF and food intake or nutrient intake are scare, but pointed to unfavourable dietary habits (Milligan et al., 1998; Pryer et al., 2001; Pryer and Rogers, 2009). In addition, the energy dense (ED), which refers to the amount of energy in a given weight of food (kJ per gram), of typical CF products, such as pizza, is high. Meals with high-ED have been shown to increase total daily energy intake (Drewnowski, 2003; Ello-Martin et al., 2005), and ED is discussed as one aspect of dietary habits that contributes to the development of obesity (Swinburn et al., 2004).
It seems to be common sense that CFs eaten at home are usually rich in fat, caloric dense and nutrient low. And of course that being a big eater of this kind of food can lead, in time, to a rise of the body fat mass. However, in contrast to fast food eaten outside, a food group with similar characteristics, only one published cross-sectional study has investigated the possible association between consumption of CF and body weight status in an adult sample (Cornelisse-Vermaat and van den Brink, 2007). Therefore, the objective of the present analysis was to evaluate the longitudinal association between consumption of CF and dietary quality and body weight status in a sample of German children and adolescents from the DONALD (Dortmund Nutritional Anthropometric Longitudinally Designed) Study.
The DONALD Study is an ongoing, longitudinal (open cohort) study collecting detailed data on diet, growth, development and metabolism between infancy and adulthood since 1985 (Kroke et al., 2004). The starting study sample included infants, children and adolescents recruited from cross-sectional studies conducted in schools and kindergartens (n≈470). Since 1989, infants have been recruited and followed up at least until the age of 18 years.
The regular DONALD assessments include records of dietary intake and behaviour, anthropometry, urine sampling (from age 3), a medical examination and questionnaires preformed once a year (Kroke et al., 2004). All examinations and assessments are performed with the parental and later on with the children's written consent. For the present evaluation, we analysed the 3-day dietary records of subjects aged 3–18 years in the recent study period of 2004–2008. This selection resulted in 1890 records from 585 subjects (296 boys and 289 girls) from 450 families. Per participant, between 1 (N=101; 18% of the total sample) and 5 (194; 35%) 3-day records were analysed (mean=3.2).
The DONALD Study is exclusively observational and non-invasive, and has been approved by the International Scientific Committee of the Research Institute of Child Nutrition and the Ethic Commission of the University of Bonn.
The parents of the younger subjects and the older subjects themselves weighed and recorded all foods, beverages and recipes using electronic food scales (±1 g) on 3 consecutive days. Semi-quantitative recording (that is, number of spoons, scoops) was allowed when weighing was not possible. Each food item was described in detail, for example, brand name, method of preparation.
Energy and nutrient intakes were calculated using the in-house food composition database LEBTAB (Sichert-Hellert et al., 2007). The energy and nutrient contents of commercial foods (for example, CF products) were estimated by recipe simulation using labelled nutrient contents and ingredients. As the ingredients are listed on the label in decreasing order of their weight in the product, this sequence allows quantitative estimation of their amounts. The ingredients of the simulated recipes are stored in LEBTAB (Sichert-Hellert et al., 2007).
Definition of convenience food
For the present evaluation, CF was defined as all pre-prepared savoury products, frozen, canned or instant, hot or cold (for example, salads and soups), all-in-one-meals or courses (for example, pizza or meat dishes), purchased in a store and eaten in the home environment.
We did not include fast food, CF consumed in communal feeding environments (for example, day-care centres and schools), as well as frozen or canned pure vegetables, meat, or fish without any other ingredients, like spices, cream or crumb (Alexy et al., 2008), as we intended to focus on the special eating situation within the family, which is mainly responsible for the development of dietary habits (Benton, 2004; Savage et al., 2007).
The ED of each product was calculated as the energy content (kJ) per gram (g). CF products were divided into high-ED (high-ED-CF) and low-ED (low-ED-CF) products using the median ED value of the reported CF items in the sample as cutoff.
Three sets of measures were applied as indicators for dietary quality: (1) the macronutrient intakes (protein, fat, carbohydrates and fatty acids) expressed as the percentage of the energy intake (%E), (2) a nutrient quality index (NQI) and (3) intake of food groups expressed as g per MJ (g/MJ).
The NQI was calculated using the harmonic mean of the individual intakes of five vitamins (E, A, C, B1 and folate) and five minerals (zinc, iron, magnesium, calcium and potassium), each nutrient expressed as the percentage of the German dietary reference intakes (%DRI) (German Nutrition Society (Deutsche Gesellschaft für Ernährung, DGE, 2000). To avoid mathematical compensation in NQI of low intakes of one nutrient by high intakes of other nutrients, %DRI values were truncated at 100. In contrast to the arithmetic mean, the harmonic mean is more sensitive to imbalances in nutrient intake. Therefore, the NQI is likely to be a more sensitive instrument to classify an efficient food quality than other indices based on the arithmetic mean (Libuda et al., 2009).
For calculation of food group intake, all recorded foods were aggregated to one of the eight food groups:
Dairy, including milk and cheese
Meat, including, poultry, fish and eggs
Fat, including butter, margarine and oils
Grain, including bread, cereals and potatoes
Sweets, including cakes, biscuits and confectionaries
Fruits and vegetables, including juices
Beverages, including water, tea, coffee and soft drinks
Diverse, including water for cooking and condiments
In case of CF products, the ingredients were assigned to the respective food groups (for example, in case of pizza, cheese was included in ‘Dairy’, tomatoes in ‘Fruits, vegetables’ and dough in ‘Grain’). Intake of food groups per MJ was calculated to adjust for the heterogeneous energy intakes in the broad age range of the sample.
Height (cm) was measured with a digital telescopic wall-mounted stadiometer (Harpenden, Crymych, UK) to the nearest 0.1 cm. Body weight was measured without shoes and with light clothing to the nearest 0.1 kg using an electronic scale (Seca 753 E; Seca Weighing and Measuring Systems, Hamburg, Germany). Body mass index (BMI, weight/height2, kg/m2) was calculated and converted into standard deviation scores of BMI (BMI SDS) using the LMS method (Cole et al., 2000), which allows assessment of individual BMI in relation to a reference population (Kromeyer-Hauschild et al., 2001). Overweight was defined as BMI values between the 90th and 97th percentiles, and obesity was defined according to the German standards as BMI values above the 97th percentile.
Skinfold thickness was measured in duplicate with the use of a skinfold calliper (Holtain Ltd., Dyfed, UK) at the triceps and subscapular region on the right side of the body, and the mean value was obtained. The individual means of the repeated measurements were used to estimate the percentage body fat (%BF) according to the equations of Slaughter et al. (1988).
Habitual physical activity was assessed yearly with a questionnaire. Individual energy expenditure from different activities was calculated using data on its intensity as the ratio of work metabolic rate to resting metabolic rate (MET) (Ainsworth et al., 1993) and assigned to sex and age-specific quartiles. Missing data were filled in using the mean values of the respective age and sex group.
Maternal BMI was assessed in 5-year intervals. If more than one parental BMI was available, the mean value was used. The highest maternal school education level was used as the indicator of socioeconomic status.
SAS procedures (Version 8.2; Statistical Analysis System, Cary, NC, USA) were used for data analysis. Food, energy and nutrient intakes were calculated as individual means of the three recorded days. In all statistical tests, a P-value <0.05 was considered as significant.
For data analysis, linear mixed-effect models were used in which the means of the data and the covariance structure (children of the family, repeated measurements) were modelled (PROC MIXED). An exponential spatial structure of covariance was specified to consider correlation of repeated measurements dependant on the absolute time interval of repeated measurements on the same subject.
To analyse the cross-sectional association between CF and dietary quality, CF consumption was expressed as the percentage of the total food intake (without beverages) and analysed separately for all CF and high-ED-CF. Macronutrient intakes (%E), the NQI and food group intakes (g/MJ) were separately used as dependant variables. All models were controlled for time since onset of the study period, age of subjects and total energy intake.
To analyse the longitudinal association between CF and %BF and BMI SDS trajectories during the 5-year study period, only subjects with at least two dietary records were included (n=190 boys and 173 girls, 1128 assessments). The exponential variance structure specifies a stronger correlation of assessments of one subject in 2 consecutive years than for a longer time interval. The first visit was treated as baseline visit (time=0). CF consumption, expressed as the percentage of the total food intake (%CF), was the principal fixed effect. Changes in %CF intake between first and last assessment were calculated by subtracting baseline intake from intake at each year of assessment (visit 1–visit 0, visit 2–visit 0). In this way, the respective regression coefficients represent the effects of: (1) %CF at baseline on %BF or BMI SDS at baseline (cross-sectional estimate), (2) %CF at baseline on the slope of the change in %BF or BMI SDS between first and last assessment (prospective estimate) and (3) the slope of the change in %CF on the concurrent change in %BF or BMI SDS during study period (concurrent estimate). Total energy intake was included as a potential confounder (at baseline, change and time × baseline). The models were controlled for non-dietary covariates that could potentially affect the association between diet and body composition measures, including age, age × age, maternal BMI, maternal educational status and physical activity.
In 89.6% of all the dietary records, at least one CF was recorded, with an overall count of 5327 foods. Intake of CF increased with age (Table 1) by ∼5 g per year or 0.3% of the total food intake (excluding beverage intake). Daily energy intake from CF was less than 0.5 MJ and accounted for 5–6% of the total energy intake. Less then half of the CF intake was high-ED-CF, but this percentage increased with age.
Total CF intake, expressed as the percentage of the total food intake, showed no significant association with macronutrient pattern (%E), with exception of a significant positive association with PUFA intake. Considering only high-ED-CF, there was a significant decrease in total protein, carbohydrate and saturated fatty acid intake (%E), whereas intakes of total fat, monounsaturated fatty acid and PUFA increased with increasing CF consumption. The NQI showed a significant negative trend with increased consumption of total and high-ED-CF (Table 2).
Intake of dairy decreased and intake of fat increased with increasing CF intake (Table 3). For fruit and vegetable, and meat, there was a non-significant trend (P>0.08) towards a decreased (fruit and vegetable) or increased (meat) consumption. Considering only high-ED-CF, the association with dairy and fat remained stable, and, additionally, the intake of grain and sweets decreased significantly with an increase of the consumption of high-ED-CF. The intake of beverages did not change with consumption of total or high-ED-CF.
The repeated measurement regression analysis showed no significant association between baseline or change in consumption of total CF (%total food intake) and baseline or change in parameters of body weight (BMI SDS or %BF, data not shown).
Among boys, baseline consumption of high-ED-CF significantly predicted the change in %BF during the study period (prospective estimate; Table 4). There was no association between baseline consumption and baseline BMI SDS or %BF (cross-sectional estimate). Also, the change in consumption of high-ED-CF during the study period was not significantly correlated with the concurrent change in BMI SDS or %BF.
In girls, we found a tendency towards a positive association between baseline high-ED-CF consumption and baseline BMI SDS (cross-sectional estimate). We did not find a significant association between change of CF consumption and change of BMI SDS or %BF, or between baseline consumption and BMI SDS (prospective and concurrent estimates, Table 4).
Our evaluation showed an impairment of dietary quality by CF consumption in a sample of German children and adolescents, indicated by a decrease of the NQI, and a trend towards unfavourable food group pattern. Significant effects on macronutrient pattern, with an increase of fat and a decrease of carbohydrate and protein intake, was only seen for high-ED-CF.
Additionally, we could show a small but significant association between baseline consumption of high-ED-CF and the change in %BF during the 5-year study period in boys. In girls, there was only a strong tendency towards a positive association between baseline high-ED-CF and baseline BMI SDS. No association was found between an increase in high-ED-CF and change in body weight status, possibly due to small individual changes or a high variability of individual changes of CF intake during study period.
These observed associations between CF and development of body weight status were small. However, only a small positive difference between energy intake and expenditure is needed to increase body weight over time. It is still a challenge to detect and verify such small differences based on measurements in dietary surveys. This is especially true when investigating the association between a single food group and body weight.
In an adult sample from the Netherlands, eating CF was associated with a high self-reported BMI, but the type of CF was not specified (Cornelisse-Vermaat and van den Brink, 2007). Our results support the hypothesis that choice of type of CF is important as we only found an effect of high-ED-CF on body weight. This result also supports the assumed mechanism of action of high-ED in CF products. ED is discussed as an important factor that determines total daily energy intake (Drewnowski, 2003; Ello-Martin et al., 2005).
With respect to macronutrient and food group intake, intake of high-ED-CF showed a stronger effect than intake of total CF, in spite of the lower consumption amount: Intake of fat increased, whereas intake of protein and carbohydrates decreased with an increasing consumption of high-ED-CF. This increase of fat intake was predominantly because of an increased intake of PUFA, as vegetable oil was the most frequently used fat ingredient. Typical CF with high-ED were cold sauces, pizza or meat dishes (Alexy et al., 2008). Overall intake of the study sample was in the range of recommended fat intake (30–35 %E) in children up to 15 years old (2000), but a further increase would not be desirable.
In the recent evaluation of dietary pattern in British children, the convenience cluster was characterised by unfavourable food consumption habits including, for example, low fruit and vegetable intakes, but showed no characteristic macronutrient pattern and nutrient densities, whereas energy values were high (Pryer and Rogers, 2009). In contrast, our study found a decrease of NQI with increased consumption of CF.
The frequency of CF consumption in our sample was high (at least one product in 90% of all the dietary 3-day records) but consumption amounts were low and highly variable. On average, the reported energy intake from CF was only 6% of the total energy intake, whereas, for example, the contribution of energetic beverages (soft drinks and fruit juices) to total energy intake was 9–10% (Libuda et al., 2009). For these beverages, a positive association with body weight status (Malik et al., 2006; Libuda et al., 2008) and dietary quality (Rodriguez-Artalejo et al., 2003; Libuda et al., 2009) has been reported.
Some limitations, and also some strengths, of the present study warrant mentioning. First, there is no convincing definition of CF available. A comprehensive definition included products that transfer time and activities of preparation from the household manager to the food processor (Buckley et al., 2005). However, this would also apply to single-ingredient products, such as flour or commercial fruit juice. In this case, not only the time and activities but also the responsibility of food composition and nutrient content pass from the household manager to the food producer, as the consumer gets a product with predetermined composition. A previous detailed evaluation showed the heterogeneity of the composition of CF products consumed among the families in the DONALD Study (Alexy et al., 2008).
Second, we are aware that our results are based on a small study sample, and it is possible that the associations we found are not highly significant because of this. As the participants of the DONALD Study are characterised by a higher socioeconomic status than the overall German population (Kroke et al., 2004), they probably do not represent extremes of dietary, that is, a high intake of CF or body weight status. The non-representativeness of our sample, however, should be of minor importance when looking at internal validity and cause–effect relations. Additionally, several evaluations showed no or only minor deviations between the dietary habits seen in the DONALD Study and those in recent German surveys in children and adolescents (Alexy et al., 1998, 2002; Kersting et al., 1998). Third, although weighed dietary records are regarded as particularly reliable (Livingstone and Robson, 2000), scepticism against the dietary assessment tool still exists.
A further clear strength of our analyses is the longitudinal, prospective design of the DONALD Study with annually carefully collected data on growth, diet and a large number of possible confounders, such as parental characteristics and physical activity. The models used here are therefore more suitable for the evaluation of the effects of diet on the development of body weight status than models based on cross-sectional designs.
In summary, our results point to a compromised dietary quality with high consumption of CF, especially with high-ED-CF and to a small but positive association of the consumption of high-ED-CF in boys, which has to be confirmed by other studies. Families should be encouraged to pay attention to the labelled ingredients and/or nutrient values, to choose CF products with respect to their ED, and to systematically balance the disadvantages of CF by complementing with low-ED foods, for example, fruits or vegetables. The food industry should be encouraged to develop and promote CF products with lower ED for children and adolescents.
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The participation of all children and their families in the study is gratefully acknowledged. We also thank the DONALD Study team for carrying out the anthropometric measurements and collecting and validating the dietary data. The DONALD Study is supported by the Ministerium für Innovation, Wissenschaft, Forschung und Technologie des Landes Nordrhein-Westfalen, Germany. The present evaluation was funded by a research grant from the Ministerium für Umwelt, Naturschutz, Landwirtschaft und Verbraucherschutz des Landes Nordrhein-Westfalen, Germany.
The authors declare no conflict of interest.
Contributors: UA and MK conceived the project; UA, LL and SM performed the data analyses; UA drafted the manuscript. All authors contributed to the interpretation of the data and revision of the manuscript.
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Alexy, U., Libuda, L., Mersmann, S. et al. Convenience foods in children's diet and association with dietary quality and body weight status. Eur J Clin Nutr 65, 160–166 (2011). https://doi.org/10.1038/ejcn.2010.254
- convenience food
- dietary quality
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