Measurement and genetic architecture of lifetime depression in the Netherlands as assessed by LIDAS (Lifetime Depression Assessment Self-report).

BACKGROUND: Major depressive disorder (MDD) is a common mood disorder, with a heritability of around 34%. Molecular genetic studies made significant progress and identified genetic markers associated with the risk of MDD; however, progress is slowed down by substantial heterogeneity as MDD is assessed differently across international cohorts. Here, we used a standardized online approach to measure MDD in multiple cohorts in the Netherlands and evaluated whether this approach can be used in epidemiological and genetic association studies of depression. METHODS: Within the Biobank Netherlands Internet Collaboration (BIONIC) project, we collected MDD data in eight cohorts involving 31 936 participants, using the online Lifetime Depression Assessment Self-report (LIDAS), and estimated the prevalence of current and lifetime MDD in 22 623 unrelated individuals. In a large Netherlands Twin Register (NTR) twin-family dataset (n ≈ 18 000), we estimated the heritability of MDD, and the prediction of MDD in a subset (n = 4782) through Polygenic Risk Score (PRS). RESULTS: Estimates of current and lifetime MDD prevalence were 6.7% and 18.1%, respectively, in line with population estimates based on validated psychiatric interviews. In the NTR heritability estimates were 0.34/0.30 (s.e. = 0.02/0.02) for current/lifetime MDD, respectively, showing that the LIDAS gives similar heritability rates for MDD as reported in the literature. The PRS predicted risk of MDD (OR 1.23, 95% CI 1.15-1.32, R2 = 1.47%). CONCLUSIONS: By assessing MDD status in the Netherlands using the LIDAS instrument, we were able to confirm previously reported MDD prevalence and heritability estimates, which suggests that this instrument can be used in epidemiological and genetic association studies of depression.

Sociodemographic, lifestyle and clinical characteristics of energy-related depression symptoms: A pooled analysis of 13,965 depressed cases in 8 Dutch cohorts.

BACKGROUND: In a substantial subgroup of depressed patients, atypical, energy-related depression symptoms (e.g. increased appetite/weight, hypersomnia, loss of energy) tend to cluster with immuno-metabolic dysregulations (e.g. increased BMI and inflammatory markers). This clustering is proposed to reflect a more homogeneous depression pathology. This study examines to what extent energy-related symptoms are associated and share sociodemographic, lifestyle and clinical characteristics. METHODS: Data were available from 13,965 participants from eight Dutch cohorts with DSM-5 lifetime major depression assessed by the Lifetime Depression Assessment Self-report (LIDAS) questionnaire. Information on four energy-related depression symptoms were extracted: energy loss, increased appetite, increased weight, and hypersomnia. Tetrachoric correlations between these symptoms, and associations of these symptoms with sociodemographic (sex, age, education), lifestyle (physical activity, BMI, smoking) and clinical characteristics (age of onset, episode duration, history, treatment and recency, and self-reported comorbidity) were computed. RESULTS: Correlations between energy-related symptoms were overall higher than those with other depression symptoms and varied from 0.90 (increased appetite vs increased weight) to 0.11 (increased appetite vs energy loss). All energy-related symptoms were strongly associated with higher BMI and a more severe clinical profile. Patients with increased appetite were more often smokers, and only patients with increased appetite or weight more often had a self-reported diagnosis of PTSD (OR = 1.17, p = 2.91E-08) and eating disorder (OR = 1.40, p = 4.08E-17). CONCLUSIONS: The symptom-specific associations may have consequences for a profile integrating these symptoms, which can be used to reflect immuno-metabolic depression. They indicate the need to study immuno-metabolic depression at individual symptom resolution as a starting point.

Sensory acceptability and factors predicting the consumption of grain amaranth in Kenya.

This study investigated the effect of adding grain amaranth flour on sensory acceptability of maize porridge in Kenya. Factors influencing the intention of mothers to feed their children on grain amaranth were identified. A significant difference between the various porridge ratios (50:50, 70:30, and 100:0 amaranth:maize) either in unfermented or fermented form could be detected. Preference for the unfermented amaranth enriched maize porridge was observed. Intention significantly correlated and predicted grain amaranth consumption (p < .001). Knowledge and health value significantly predicted health behavior identity. Interaction between barriers and intention negatively influenced behavior. Findings suggest that unfermented amaranth enriched maize porridge is acceptable. Unfermented porridge with 70% amaranth can be considered for use in a program aimed at increasing dietary iron intake among children. Increasing awareness about micronutrient deficiencies and nutritional benefits of grain amaranth could enhance its consumption.

Iterative Development of an Innovative Smartphone-Based Dietary Assessment Tool: Traqq.

To collect dietary intake data in a fast and reliable manner, a flexible and innovative smartphone application (app) called Traqq was developed (iOS/Android). This app can be used as a food record and 24-h recall (or shorter recall periods). Different sampling schemes can be created on either prespecified or random days/times within a predetermined period for both methods, with push notifications to urge the participants to register their food intake. In case of non-response, notifications are automatically rescheduled to ensure complete data collection. For use as a food record, respondents can access the app and log their food intake throughout the day. Food records close automatically at the end of the day; recalls close after submission of the consumed items. The recall as well as the food record module provide access to an extensive food list based on the Dutch food composition database (FCDB), which can be accustomed to fit different research purposes. When selecting a food item, respondents are simultaneously prompted to insert portion size, i.e., in household measures (e.g., cups, spoons, glasses), standard portion sizes (e.g., small, medium, large), or weight in grams, and eating occasion/time of consumption. Portion size options can be adjusted, e.g., only entry in grams in case of a weighed food record or time of consumption instead of eating occasion). The app also includes a My Dishes function, which allows the respondent to create their own recipes or product combinations (e.g., a daily breakfast) and only report the total quantity consumed. Subsequently, the app accounts for yield and retention factors. The data are stored on a secure server. If desired, additional questions, i.e., in general or those related to specific food items or eating occasions can be incorporated. This paper describes the development of the system (app and backend), including expert evaluations and usability testing.

The Glycaemic Index-Food-Frequency Questionnaire: Development and Validation of a Food Frequency Questionnaire Designed to Estimate the Dietary Intake of Glycaemic Index and Glycaemic Load: An Effort by the PREVIEW Consortium.

Dietary glycaemic index (GI) and glycaemic load (GL) are indices used to quantify the effect of carbohydrate quality and quantity on postprandial glycaemia. GI/GL-health associations are widely studied but data on the validity of integrated GI/GL measurements are scarce. We evaluated the performance of a food-frequency questionnaire (FFQ) specifically developed to assess GI/GL. In total, 263 Dutch men and 212 women (aged 55 ± 11 years) completed a 58-item GI-FFQ, an 183-item general-FFQ and a 2-day 24 h-recall and donated blood for glycated haemoglobin (HbA1c) determination. The level of agreement between these methods was evaluated by (1) cross-classification, (2) correlations and (3) Bland and Altman plots. The three dietary assessment methods provided comparable mean intake estimates for total carbohydrates (range: 214⁻237 g/day), mono/disaccharides (100⁻107 g/day), polysaccharides (114⁻132 g/day), as well as bread, breakfast cereals, potatoes, pasta, rice, fruit, dairy, cakes/cookies and sweets. Mean (±SD) GI estimates were also comparable between the GI-FFQ (54 ± 3), general-FFQ (53 ± 4) and 24 h-recalls (53 ± 5). Mean (±SD) GI-FFQ GL (117 ± 37) was slightly lower than the general-FFQ GL (126 ± 38) and 24 h-recalls GL (127 ± 37). Classification of GI in quartiles was identical for the GI-FFQ and general-FFQ for 43% of the population (r = 0.58) and with 24 h-recalls for 35% of the population (de-attenuated r = 0.64). For GL, this was 48% (r = 0.65) and 44% (de-attenuated r = 0.74). Correlations between GI and HbA1c were low (r = -0.09 for GI-FFQ, r = -0.04 for general-FFQ and r = 0.07 for 24 h-recalls). In conclusion, compared to a general-FFQ and 24 h-recalls, the GI-FFQ showed a moderate to good relative validity for carbohydrates, carbohydrate-rich foods and GI/GL. No metric predicted HbA1c.

Nutrition Questionnaires plus (NQplus) study, a prospective study on dietary determinants and cardiometabolic health in Dutch adults.

PURPOSE: During the past decades, the number of people with cardiometabolic conditions substantially increased. To identify dietary factors that may be responsible for this increase in cardiometabolic conditions, the Nutrition Questionnaires plus (NQplus) study was initiated. The aim of this article is to provide an overview of the study design and baseline characteristics of the NQplus population. PARTICIPANTS: The NQplus study is a prospective cohort study among 2048 Dutch men (52%) and women (48%) aged 20-70 years. FINDINGS TO DATE: At baseline, we assessed habitual dietary intake, conducted physical examinations (measuring, eg, anthropometrics, body composition, blood pressure, pulse wave velocity, advanced glycation end product accumulation, cognitive performance), collected blood and 24-hour urine and administered a variety of validated demographic, health and lifestyle questionnaires. Participants had a mean BMI of 26.0±4.2 kg/m2, were mostly highly educated (63%), married or having a registered partnership (72%) and having a paid job (72%). Estimated daily energy and macronutrient intakes (mean±SD) were 8581±2531 kJ, 15±2energy (en%) of protein, 43±6 en% of carbohydrates, 36±5 en% of fat and 11±13 g of alcohol. Mean systolic blood pressure was 126±15 mm Hg, total cholesterol 5.3±1.1 mmol/L and haemoglobin A1c 36±5 mmol/mol. A total of 24% of the participants reported to be diagnosed with hypertension, 18% with hypercholesterolaemia and 4% with diabetes mellitus. All measurements were repeated after 1 and 2 years of follow-up. FUTURE PLANS: We endeavour to continue measurements on the long-term. Moreover, dietary assessment methods used in the NQplus study will be extensively validated, that is, Food Frequency Questionnaires, 24-hour recalls and urinary and blood biomarkers of exposure. As such, the NQplus study will provide a unique opportunity to study many cross-sectional and longitudinal associations between diet and cardiometabolic health outcomes using the best dietary assessment methods available so far.

Evaluation of dietary intake assessed by the Dutch self-administered web-based dietary 24-h recall tool (Compl-eat™) against interviewer-administered telephone-based 24-h recalls.

Self-administered web-based 24-h dietary recalls (24 hR) may save a lot of time and money as compared with interviewer-administered telephone-based 24 hR interviews and may therefore be useful in large-scale studies. Within the Nutrition Questionnaires plus (NQplus) study, the web-based 24 hR tool Compl-eat™ was developed to assess Dutch participants' dietary intake. The aim of the present study was to evaluate the performance of this tool against the interviewer-administered telephone-based 24 hR method. A subgroup of participants of the NQplus study (20-70 years, n 514) completed three self-administered web-based 24 hR and three telephone 24 hR interviews administered by a dietitian over a 1-year period. Compl-eat™ as well as the dietitians guided the participants to report all foods consumed the previous day. Compl-eat™ on average underestimated the intake of energy by 8 %, of macronutrients by 10 % and of micronutrients by 13 % as compared with telephone recalls. The agreement between both methods, estimated using Lin's concordance coefficients (LCC), ranged from 0·15 for vitamin B1 to 0·70 for alcohol intake (mean LCC 0·38). The lower estimations by Compl-eat™ can be explained by a lower number of total reported foods and lower estimated intakes of the food groups, fats, oils and savoury sauces, sugar and confectionery, dairy and cheese. The performance of the tool may be improved by, for example, adding an option to automatically select frequently used foods and including more recall cues. We conclude that Compl-eat™ may be a useful tool in large-scale Dutch studies after suggested improvements have been implemented and evaluated.

A National Dietary Assessment Reference Database (NDARD) for the Dutch Population: Rationale behind the Design.

The development of reliable Food Frequency Questionnaires (FFQs) requires detailed information about the level and variation of dietary intake of the target population. However, these data are often limited. To facilitate the development of new high quality FFQs and validation of existing FFQs, we developed a comprehensive National Dietary Assessment Reference Database (NDARD) detailing information about the level and variation in dietary intake of people 20-70 years old in the general Dutch population. This paper describes the methods and characteristics of the population included in the NDARD database. A total of 1063 men and 985 women agreed to participate in this study. Dietary intake data were collected using different FFQs, web-based and telephone-based 24-h recalls, as well as blood and urine-based biomarkers. The baseline FFQ was completed by 1647 participants with a mean age of 51 ± 12 years, BMI of 26 ± 4 kg/m², and energy intake of 2051 ± 605 kcal/day. The percentage of total energy intake from proteins, carbohydrates, and fats were 15 ± 2, 43 ± 6, and 36 ± 5 En%, respectively. A total of 1113 participants completed telephone-based recalls and 1783 participants completed web-based recalls. This database will enable researchers to validate existing national FFQs and to develop new high quality dietary assessment methods.