Use of accelerometer data in prediction equations for capturing implausible dietary intakes in adolescents

Is glycaemic control associated with dietary patterns independent of weight change in people newly diagnosed with type 2 diabetes? Prospective analysis of the Early-ACTivity-In-Diabetes trial

BACKGROUND

It is unclear whether diet affects glycaemic control in type 2 diabetes (T2D), over and above its effects on bodyweight. We aimed to assess whether changes in dietary patterns altered glycaemic control independently of effects on bodyweight in newly diagnosed T2D.

METHODS

We used data from 4-day food diaries, HbA1c and potential confounders in participants of the Early-ACTivity-In-Diabetes trial measured at 0, 6 and 12 months. At baseline, a 'carb/fat balance' dietary pattern and an 'obesogenic' dietary pattern were derived using reduced-rank regression, based on hypothesised nutrient-mediated mechanisms linking dietary intake to glycaemia directly or via obesity. Relationships between 0 and 6 month change in dietary pattern scores and baseline-adjusted HbA1c at 6 months (n = 242; primary outcome) were assessed using multivariable linear regression. Models were repeated for periods 6-12 months and 0-12 months (n = 194 and n = 214 respectively; secondary outcomes).

RESULTS

Reductions over 0-6 months were observed in mean bodyweight (- 2.3 (95% CI: - 2.7, - 1.8) kg), body mass index (- 0.8 (- 0.9, - 0.6) kg/m2), energy intake (- 788 (- 953, - 624) kJ/day), and HbA1c (- 1.6 (- 2.6, -0.6) mmol/mol). Weight loss strongly associated with lower HbA1c at 0-6 months (β = - 0.70 [95% CI - 0.95, - 0.45] mmol/mol/kg lost). Average fat and carbohydrate intakes changed to be more in-line with UK healthy eating guidelines between 0 and 6 months. Dietary patterns shifting carbohydrate intakes higher and fat intakes lower were characterised by greater consumption of fresh fruit, low-fat milk and boiled/baked potatoes and eating less of higher-fat processed meats, butter/animal fats and red meat. Increases in standardised 'carb/fat balance' dietary pattern score associated with improvements in HbA1c at 6 months independent of weight loss (β = - 1.54 [- 2.96, - 0.13] mmol/mol/SD). No evidence of association with HbA1c was found for this dietary pattern at other time-periods. Decreases in 'obesogenic' dietary pattern score were associated with weight loss (β = - 0.77 [- 1.31, - 0.23] kg/SD) but not independently with HbA1c during any period.

CONCLUSIONS

Promoting weight loss should remain the primary nutritional strategy for improving glycaemic control in early T2D. However, improving dietary patterns to bring carbohydrate and fat intakes closer to UK guidelines may provide small, additional improvements in glycaemic control.

TRIAL REGISTRATION

ISRCTN92162869 . Retrospectively registered on 25 July 2005.

Greenhouse gas emissions of self-selected diets in the UK and their association with diet quality: is energy under-reporting a problem?

BACKGROUND

While the admittedly limited number of epidemiological findings on the association between diet-related greenhouse gas emissions (GHGE) and diet quality are not always consistent, potential influence of bias in the estimation of diet-related GHGE caused by misreporting of energy intake (EI) has not been investigated. This cross-sectional study evaluated diet-related GHGE in the UK and their association with diet quality, taking account of EI under-reporting.

METHODS

Dietary data used were from the National Diet and Nutrition Survey rolling programme 2008/2009-2013/2014, in which 4-day food diaries were collected from 3502 adults aged ≥19 years. Diet-related GHGE were estimated based on 133 food groups, using GHGE values from various secondary sources. Diet quality was assessed by the healthy diet indicator (HDI), Mediterranean diet score (MDS) and Dietary Approaches to Stop Hypertension (DASH) score. EI misreporting was assessed as reported EI divided by estimated energy requirement (EI:EER).

RESULTS

Mean value of daily GHGE was 5.7 kg carbon dioxide equivalents (CO₂eq), which is consistent with those reported from a number of national representative samples in other European countries. Mean EI:EER was 0.74. Assuming that all the dietary variables were misreported in proportion to the misreporting of EI, the mean value of the misreporting-adjusted diet-related GHGE was 8.2 kg CO₂eq/d. In the entire population, after adjustment for potential confounders (i.e., age, sex, ethnicity, socioeconomic classification, smoking status and physical activity), diet-related GHGE were inversely associated with HDI and DASH score but not with MDS. However, with further adjustment for EI:EER, diet-related GHGE showed inverse associations with all three measures of diet quality. Similar associations were observed when only under-reporters (EI:EER < 0.70; n = 1578) were analysed. Conversely, in the analysis including only plausible reporters (EI:EER 0.70-1.43; n = 1895), diet-related GHGE showed inverse associations with all diet quality measures irrespective of adjustment.

CONCLUSIONS

With taking account of EI under-reporting, this study showed inverse associations between diet-related GHGE and diet quality not only in the entire sample but also in the separate analyses of plausible reporters and under-reporters, as well as potential underreporting of diet-related GHGE.

Bias in food intake reporting in children and adolescents with type 1 diabetes: the role of body size, age and gender

BACKGROUND

An assessment of total daily energy intake is helpful in planning the overall treatment of children with type 1 diabetes (T1D). However, energy intake misreporting may hinder nutritional intervention.

AIMS

To assess the plausibility of energy intake reporting and the potential role of gender, body mass index (BMI) z-score (z-BMI), disease duration and insulin requirement in energy intake misreporting in a sample of children and adolescents with T1D.

METHODS

The study included 58 children and adolescents aged 8-16 yr with T1D. Anthropometry, blood pressure and glycated hemoglobin (HbA1c) were measured. Subjects were instructed to wear a SenseWear Pro Armband (SWA) for 3 consecutive days, including a weekend day and to fill out with their parents a weighed dietary record for the same days. Predicted energy expenditure (pEE) was calculated by age and gender specific equations, including gender, age, weight, height and physical activity level (assessed by SWA). The percent reported energy intake (rEI)/pEE ratio was used as an estimate of the plausibility of dietary reporting.

RESULTS

Misreporting of food intake, especially under-reporting, was common in children and adolescents with T1D: more than one-third of participants were classified as under-reporters and 10% as over-reporters. Age, z-BMI and male gender were associated with the risk of under-reporting (model R²  = 0.5). Waist circumference was negatively associated with the risk of over-reporting (model R²  = 0.25).

CONCLUSIONS

Children and adolescents with T1D frequently under-report their food intake. Age, gender and z-BMI contribute to identify potential under-reporters.

Diet misreporting can be corrected: confirmation of the association between energy intake and fat-free mass in adolescents

Subjective energy intake (sEI) is often misreported, providing unreliable estimates of energy consumed. Therefore, relating sEI data to health outcomes is difficult. Recently, Börnhorst et al. compared various methods to correct sEI-based energy intake estimates. They criticised approaches that categorise participants as under-reporters, plausible reporters and over-reporters based on the sEI:total energy expenditure (TEE) ratio, and thereafter use these categories as statistical covariates or exclusion criteria. Instead, they recommended using external predictors of sEI misreporting as statistical covariates. We sought to confirm and extend these findings. Using a sample of 190 adolescent boys (mean age=14), we demonstrated that dual-energy X-ray absorptiometry-measured fat-free mass is strongly associated with objective energy intake data (onsite weighted breakfast), but the association with sEI (previous 3-d dietary interview) is weak. Comparing sEI with TEE revealed that sEI was mostly under-reported (74 %). Interestingly, statistically controlling for dietary reporting groups or restricting samples to plausible reporters created a stronger-than-expected association between fat-free mass and sEI. However, the association was an artifact caused by selection bias – that is, data re-sampling and simulations showed that these methods overestimated the effect size because fat-free mass was related to sEI both directly and indirectly via TEE. A more realistic association between sEI and fat-free mass was obtained when the model included common predictors of misreporting (e.g. BMI, restraint). To conclude, restricting sEI data only to plausible reporters can cause selection bias and inflated associations in later analyses. Therefore, we further support statistically correcting sEI data in nutritional analyses. The script for running simulations is provided.

Diet, growth, and obesity development throughout childhood in the Avon Longitudinal Study of Parents and Children

Publications from the Avon Longitudinal Study of Parents and Children covering diet, growth, and obesity development during childhood are reviewed. Diet was assessed by food frequency questionnaires and food records. Growth data were collected by routine measurements, and in standardized clinics, body fatness was assessed by bioelectrical impedance and DXA (dual-energy X-ray absorptiometry) scans. Diets changed dramatically during the preschool period with an increase in the intake of free (added) sugars (12.3% rising to 16.4% of energy) that remained similar until adolescence. This was due to increased intake of energy-dense, nutrient-poor foods. Two periods of rapid growth were identified; infancy and mid-childhood (ages 7-11 y) and both were associated with obesity development. Diets with high energy density were associated with increasing fat mass from mid-childhood until adolescence. Genetic and dietary factors showed independent associations with increasing adiposity. At all ages studied, there were dietary inequalities related to maternal educational attainment that may influence inequalities found in obesity development. The Avon Longitudinal Study of Parents and Children has provided valuable insights into how disparities in diet and growth may affect the development of ill health in adulthood.

Sugar-sweetened beverage consumption and central and total adiposity in older children: a prospective study accounting for dietary reporting errors

OBJECTIVE

To determine the prospective relationship between changes in sugar-sweetened beverage (SSB) intake and central adiposity in older children.

DESIGN

Dietary intakes of children were obtained by 3 d food records at ages 10 and 13 years. Waist circumference (WC) and weight and height to determine BMI were measured at 10 and 13 years and total body fat mass (TBFM) at 13 years by dual-energy X-ray absorptiometry. Analyses were conducted using multivariable linear regression. Reporting errors were measured and participants were categorized as under-, plausible and over-reporters of dietary intakes.

SETTING

Community-based British cohort of children participating in the Avon Longitudinal Study of Parents and Children.

RESULTS

Among 2455 older children, increased SSB consumption from ages 10 to 13 years was associated with higher WC (standardized β=0.020, P=0.19), BMI (β=0.028, P=0.03) and TBFM (β=0.017, P=0.20) at 13 years. Effects were strengthened among plausible dietary reporters (n 1059): WC (β=0.097, P<0.001), BMI (β=0.074, P<0.001) and TBFM (β=0.065, P=0.003). The association between change in SSB and WC was weakened, but remained statistically significant after accounting for BMI (β=0.042, P=0.02) and TBFM (β=0.048, P=0.01).

CONCLUSIONS

Higher consumption of SSB from ages 10 to 13 years was associated with a larger WC at age 13 years independent of differences in total adiposity. Accounting for dietary reporting errors strengthened associations. Our findings further support recommendations to limit intakes of SSB to reduce excess weight gain in children and suggest that SSB have an additional deleterious effect on central adiposity.

Dairy intakes at age 10 years do not adversely affect risk of excess adiposity at 13 years

Evidence of an association between milk intake and childhood adiposity remains inconsistent, with few data available regarding the effects of the amount of dairy fat consumed. This study examined the relation between dairy consumption (total, full, and reduced fat) at age 10 y on risk of excess adiposity at age 13 y in participants of the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 2455). Intakes were assessed by 3-d dietary records. Total body fat mass (TBFM) using dual-energy X-ray absorptiometry was examined at 13 y. Outcomes included excess TBFM (top quintile of TBFM), overweight, and change in body mass index (BMI). The highest vs. lowest quartile of total dairy consumers (g/d) at age 10 y did not have an increased risk of excess TBFM (OR: 0.73; 95% CI: 0.46, 1.16; P-trend = 0.28) or overweight (OR: 0.69; 95% CI: 0.41, 1.15; P = 0.24) at age 13 y. Children in the highest quartile of full-fat dairy intakes vs. those in the lowest quartile had a reduced risk of excess TBFM (OR: 0.64; 95% CI: 0.41, 1.00; P = 0.04) and a suggestion of a reduction in overweight (OR: 0.65; 95% CI: 0.40, 1.06; P = 0.19) at age 13 y. Furthermore, the highest vs. lowest consumers of full-fat products had smaller gains in BMI during follow-up [2.5 kg/m² (95% CI: 2.2, 2.7) vs. 2.8 kg/m² (95% CI: 2.5, 3.0); P < 0.01]. Associations with reduced-fat dairy consumption did not attain statistical significance. In this study, dairy consumption was not related to excess fat accumulation during late childhood. Estimates had wide confidence limits but generally showed inverse relations between dairy intakes and risk of excess adiposity. Additional prospective research is warranted to confirm the effects of dairy intake on obesity in children.

Nutritional Aspects of Late Eating and Night Eating

The timing of food intake has been investigated as a novel factor in the etiology, maintenance, and treatment of obesity. Indeed, consuming a large proportion of food later in the day and into the night has been associated with higher body weight and may even impair weight loss. The diet quality of late-eaters may be a factor involved in these relationships. Moreover, the nutritional characteristics of the foods consumed during the night may negatively affect metabolic and circadian rhythms that are required for optimal health. This review will first examine the diet quality of late-eaters and describe common foods consumed as nocturnal snacks. Second, this review will briefly acknowledge the potential adverse metabolic and circadian effects of consuming certain foods very late in the evening or during the night.

Comparison of estimated energy intake using Web-based Dietary Assessment Software with accelerometer-determined energy expenditure in children

BACKGROUND

The OPUS (Optimal well-being, development and health for Danish children through a healthy New Nordic Diet) project carried out a school meal study to assess the impact of a New Nordic Diet (NND). The random controlled trial involved 834 children aged 8-11 in nine local authority schools in Denmark. Dietary assessment was carried out using a program known as WebDASC (Web-based Dietary Assessment Software for Children) to collect data from the children.

OBJECTIVE

To compare the energy intake (EI) of schoolchildren aged 8-11 estimated using the WebDASC system against the total energy expenditure (TEE) as derived from accelerometers worn by the children during the same period. A second objective was to evaluate the WebDASC's usability.

DESIGN

Eighty-one schoolchildren took part in what was the pilot study for the OPUS project, and they recorded their total diet using WebDASC and wore an accelerometer for two periods of seven consecutive days: at baseline, when they ate their usual packed lunches and at intervention when they were served the NND. EI was estimated using WebDASC, and TEE was calculated from accelerometer-derived activity energy expenditure, basal metabolic rate, and diet-induced thermogenesis. WebDASC's usability was assessed using a questionnaire. Parents could help their children record their diet and answer the questionnaire.

RESULTS

Evaluated against TEE as derived from the accelerometers worn at the same time, the WebDASC performed just as well as other traditional methods of collecting dietary data and proved both effective and acceptable with children aged 8-11, even with perhaps less familiar foods of the NND.

CONCLUSIONS

WebDASC is a useful method that provided a reasonably accurate measure of EI at group level when compared to TEE derived from accelerometer-determined physical activity in children. WebDASC will benefit future research in this area.

Associations between flavored milk consumption and changes in weight and body composition over time: differences among normal and overweight children

BACKGROUND/OBJECTIVES

Few studies have investigated the associations between flavored milk consumption and body composition in children. We aimed to examine the prospective relationships between flavored milk consumption and body fat.

SUBJECTS/METHODS

Subjects included 2270 children from the Avon Longitudinal Study of Parents and Children. Flavored milk consumption at age 10 years was assessed using dietary records; consumption was dichotomized as consumers and non-consumers. Percent body fat was measured using dual-energy X-ray absorptiometry at 11 and 13 years. Body weight at 11 and 13 years was included as a secondary outcome. Associations were also examined in a subset of plausible reporters to evaluate the influence of dietary reporting errors. There was an effect of interaction between flavored milk and baseline weight on body fat (P-interaction <0.02).

RESULTS

In plausible reporters, overweight/obese children who consumed flavored milk had less favorable changes in body fat compared with non-consumers (adjusted means: -0.16%, 95% CI: -3.8, 3.5 vs -3.4%, 95% CI: -6.5, -0.42, P=0.02). Similar associations with body weight were observed. The adjusted mean percent body fat for overweight/obese girls who consumed flavored milk was greater at age 13 compared with 11 years (39.7%, 95% CI: 32, 47 vs 38.3%, 95% CI: 32, 44). The mean percent body fat for overweight/obese boys was similar between consumers and non-consumer is at 13 years (30.4%, 95% CI: 20, 41 vs 30.1%, 95% CI: 21, 40).

CONCLUSIONS

Overweight/obese children who consumed flavored milk had less favorable changes in body composition over time. Although more research is needed, discouraging flavored milk consumption may be one beneficial strategy to address childhood obesity.

Milk intakes are not associated with percent body fat in children from ages 10 to 13 years

Epidemiologic studies report conflicting results for the relationship between milk intake and adiposity in children. We examined prospective and cross-sectional associations between milk intake and percent body fat among 2245 children from the Avon Longitudinal Study of Parents and Children. Cross-sectional analyses were performed at age 13 y between total, full-fat, and reduced-fat milk intake assessed using 3-d dietary records and body fat from DXA. Prospective analyses were conducted between milk intakes at age 10 y and body fat at 11 and 13 y. Models were adjusted for age, sex, height, physical activity, pubertal status, maternal BMI, maternal education, and intakes of total fat, sugar-sweetened beverages, 100% fruit juice, and ready-to-eat cereals; baseline BMI was added to prospective models. Subset analyses were performed for those with plausible dietary intakes. Mean milk consumption at 10 and 13 y was (mean ± SD) 0.90 ± 0.73 and 0.85 ± 0.78 servings/d [1 serving = 8 oz of milk (244 g of plain and 250 g flavored milk)], respectively. Cross-sectional results indicated an inverse association between full-fat milk intake and body fat [β = -0.47 (95% CI = -0.76, -0.19); P = 0.001]. Milk intake at age 10 y was inversely associated with body fat at 11 y [β = -0.16 g/d (95%CI = -0.28, -0.04); P = 0.01], but not among those with plausible dietary intakes, suggesting that this association was influenced by dietary measurement errors. Milk intake was not associated with body fat at age 13 y after adjustment. Although our prospective results corroborate other findings of a null associations between milk intake and adiposity, our inconsistent findings across analyses suggest further investigation is needed to clarify the relation, and accounting for dietary reporting errors is an important consideration.