Estimating national and subnational nutrient intake distributions of global diets.

BACKGROUND: Access to high-quality dietary intake data is central to many nutrition, epidemiology, economic, environmental, and policy applications. When data on individual nutrient intakes are available, they have not been consistently disaggregated by sex and age groups, and their parameters and full distributions are often not publicly available. OBJECTIVES: We sought to derive usual intake distributions for as many nutrients and population subgroups as possible, use these distributions to estimate nutrient intake inadequacy, compare these distributions and evaluate the implications of their shapes on the estimation of inadequacy, and make these distributions publicly available. METHODS: We compiled dietary data sets from 31 geographically diverse countries, modeled usual intake distributions for 32 micronutrients and 21 macronutrients, and disaggregated these distributions by sex and age groups. We compared the variability and skewness of the distributions and evaluated their similarity across countries, sex, and age groups. We estimated intake inadequacy for 16 nutrients based on a harmonized set of nutrient requirements and bioavailability estimates. Last, we created an R package-nutriR-to make these distributions freely available for users to apply in their own analyses. RESULTS: Usual intake distributions were rarely symmetric and differed widely in variability and skewness across nutrients and countries. Vitamin intake distributions were more variable and skewed and exhibited less similarity among countries than other nutrients. Inadequate intakes were high and geographically concentrated, as well as generally higher for females than males. We found that the shape of usual intake distributions strongly affects estimates of the prevalence of inadequate intakes. CONCLUSIONS: The shape of nutrient intake distributions differs based on nutrient and subgroup and strongly influences estimates of nutrient intake inadequacy. This research represents an important contribution to the availability and application of dietary intake data for diverse subpopulations around the world.

Estimation of the salt intake distribution of Dutch kidney transplant recipients using 24-h urinary sodium excretion: the potential of external within-person variance.

BACKGROUND: There is growing interest in assessing a population's prevalence of inadequate nutrient intake using biomarkers. However, within-person variation is generally ignored because repeated data collections are considered costly and burdensome. OBJECTIVES: The study aimed to show the importance of estimating, from repeated 24-h urine collections, a population's habitual salt intake and to explore the potential of using the ratio of within-person variance to total variance from an external source (W:T variance) with single 24-h urine collection. METHODS: Salt intake was predicted from data for 24-h urinary sodium excretion in adult kidney transplant recipients in 1992-1997 (n = 432) and 2006-2011 (n = 1159). The salt intake distribution of single-day measurements was compared with estimates from multiple 24-h urine collections, which were statistically corrected for within-person variance. Habitual salt intake was also estimated using single-day measurements and external variance estimates. From each distribution, the proportion below specified cut-off values was estimated. RESULTS: In 2006-2011 the average habitual salt intake was 10.6 g/d (men) and 8.5 g/d (women); in 1992-1997 these values were 8.6 g/d and 7.5 g/d, respectively. The proportion with salt intake <6 g/d was 5% and 13% in 2006-2011 and 22% and 28% in 1992-1997, respectively, for men and women. Correction for within-person variance significantly narrowed the salt intake distribution-the proportion with salt intake <6 g/d was overestimated by 3-13 percentage points using single-day data. Sensitivity analyses showed the importance of a sufficient sample size for estimating variance components. Variation of the W:T variance showed up to 40 percentage points deviation in the proportion with intakes below a specified cut-off value. CONCLUSIONS: To estimate a population's salt intake distribution, it is important to correct 24-h urinary sodium excretion for within-person variance. Predicting habitual salt intake distribution using single-day measurements with external variances is promising; a sensitivity analysis is recommended to show the effect of different external variances.

A Novel Approach to Optimize Vitamin D Intake in Belgium through Fortification Based on Representative Food Consumption Data.

BACKGROUND: Food fortification is a promising means to improve vitamin D intake of a population. Careful selection of food vehicles is needed to ensure that nearly all individuals within the population benefit from the fortification program. OBJECTIVES: The aim of the study was to develop and apply a model that simultaneously selects the optimal combination of food vehicles and defines the optimal fortification level that adequately increases vitamin D intake in the population without compromising safety. METHODS: Food consumption data from the Belgian Food Consumption Survey 2014 (n = 3200; age 3-64 y) were used. The optimization model included 63 combinations of 6 potential vehicles for food fortification, namely "bread," "breakfast cereals," "fats and oils," "fruit juices," "milk and milk beverages," and "yogurt and cream cheese." The optimization procedure was designed to minimize inadequate or excessive vitamin D intake in each of the food combinations. This allowed the relative ranking of the different combinations according to their fortification utility. The estimated average requirement and upper intake level were used as thresholds. An age-specific and population-based approach enabled the sensitivity of the population subgroups to adverse health effects to be taken into account. Feasibility, technical aspects, and healthiness of the food vehicles were used to select the optimal combination. RESULTS: Multiple combinations of food vehicles significantly reduced the prevalence of inadequate vitamin D intake within the Belgian population (from 92-96% to <2%). Taking other aforementioned criteria into account, the fortification of "milk and milk beverages" and "bread" with 6.9 µg vitamin D/100 kcal was proposed as an optimal fortification scenario. CONCLUSIONS: The optimization model allows identification of an effective fortification scenario to improve vitamin D intake within the Belgian population based on acceptable risks of inadequate and excessive intake. The model can be extended to other micronutrients and other populations.

Intake of Fat-Soluble Vitamins in the Belgian Population: Adequacy and Contribution of Foods, Fortified Foods and Supplements.

A key challenge of public health nutrition is to provide the majority of the population with a sufficient level of micronutrients while preventing high-consumers from exceeding the tolerable upper intake level. Data of the 2014 Belgian food consumption survey (n = 3200) were used to assess fat-soluble vitamin (vitamins A, D, E and K) intake from the consumption of foods, fortified foods and supplements. This study revealed inadequate intakes for vitamin A, from all sources, in the entire Belgian population and possible inadequacies for vitamin D. The prevalence of inadequate intake of vitamin A was lowest in children aged 3-6 (6-7%) and highest in adolescents (girls, 26%; boys, 34-37%). Except for women aged 60-64 years, more than 95% of the subjects had vitamin D intake from all sources below the adequate intake (AI) of 15 µg/day. The risk for inadequate intake of vitamins K and E was low (median > AI). Belgian fortification and supplementation practices are currently inadequate to eradicate suboptimal intakes of vitamins A and D, but increase median vitamin E intake close to the adequate intake. For vitamin A, a small proportion (1-4%) of young children were at risk of exceeding the upper intake level (UL), while for vitamin D, inclusion of supplements slightly increased the risk for excessive intakes (% > UL) in adult women and young children. The results may guide health authorities when developing population health interventions and regulations to ensure adequate intake of fat-soluble vitamins in Belgium.

Decreased, but still sufficient, iodine intake of children and adults in the Netherlands.

Sufficient I intake is important for the synthesis of thyroid hormones, which play an important role in normal growth and development. Our aim was to estimate habitual I intake for the Dutch population and the risk of inadequate or excessive intakes. Further, we aimed to provide an insight into the dietary sources of I and the association with socio-demographic factors. Data from the Dutch National Food Consumption Survey 2007-2010 (n 3819; 7-69 years), and from the Dutch food and supplement composition tables were used to estimate habitual I intake with a calculation model. Contribution of food groups to I intake were computed and multiple linear regression was used to examine associations of intakes with socio-demographic factors. A total of ≤2 % of the population had an intake below the estimated average requirement or above the upper level. The main sources of I were bread containing iodised salt (39 %), dairy products (14 %) and non-alcoholic drinks (6 %). I intake (natural sources only, excluding iodised salt and supplements) was positively associated with (parental) education, which could at least partly be attributed to a higher consumption of dairy products. Among children, the consumption of bread, often containing iodised bakery salt, was positively associated with parental education. The I intake of the Dutch population (7-69 years) seems adequate, although it has decreased since the period before 2008. With the current effort to reduce salt intake and changing dietary patterns (i.e. less bread, more organic foods) it is important to keep a close track on the I status, important sources and potential risk groups.

Temporal cross-correlation between influenza-like illnesses and invasive pneumococcal disease in The Netherlands.

BACKGROUND: While the burden of community-acquired pneumonia and invasive pneumococcal disease (IPD) is still considerable, there is little insight in the factors contributing to disease. Previous research on the lagged relationship between respiratory viruses and pneumococcal disease incidence is inconclusive, and studies correcting for temporal autocorrelation are lacking. OBJECTIVES: To investigate the temporal relation between influenza-like illnesses (ILI) and IPD, correcting for temporal autocorrelation. METHODS: Weekly counts of ILI were obtained from the Sentinel Practices of NIVEL Primary Care Database. IPD data were collected from the Dutch laboratory-based surveillance system for bacterial meningitis from 2004 to 2014. We analysed the correlation between time series, pre-whitening the dependent time series with the best-fit seasonal autoregressive integrated moving average (SARIMA) model to the independent time series. We performed cross-correlations between ILI and IPD incidences, and the (pre-whitened) residuals, in the overall population and in the elderly. RESULTS: We found significant cross-correlations between ILI and IPD incidences peaking at lags -3 overall and at 1 week in the 65+ population. However, after pre-whitening, no cross-correlations were apparent in either population group. CONCLUSION: Our study suggests that ILI occurrence does not seem to be the major driver of IPD incidence in The Netherlands.

Comparison of the ISU, NCI, MSM, and SPADE Methods for Estimating Usual Intake: A Simulation Study of Nutrients Consumed Daily.

Various methods are available for estimating usual dietary intake distributions. Hence, there is a need for simulation studies to compare them. The methods Iowa State University (ISU), National Cancer Institute (NCI), Multiple Source Method (MSM) and Statistical Program to Assess Dietary Exposure (SPADE) were previously compared in another study, but some results were inconclusive due to the small number of replications used in the simulation. Seeking to overcome this limitation, the present study used 1000 simulated samples for 12 different scenarios to compare the accuracy of estimates yielded by the aforementioned methods. The focus is on scenarios that exhibited the most uncertainty in the conclusions of the mentioned study above, i.e., scenarios with small sample sizes, skewed intake distributions, and large ratios of the between- and within-person variances. Bias was used as a measure of accuracy. For scenarios with small sample sizes (n = 150), the ISU, MSM and SPADE methods generally achieved more accurate estimates than the NCI method, particularly for the 10th and 90th percentiles. The differences between methods became smaller with larger sample sizes (n = 300 and n = 500). With few exceptions, the methods were found to perform similarly.

How may a shift towards a more sustainable food consumption pattern affect nutrient intakes of Dutch children?

OBJECTIVE: Food has a considerable environmental impact. Diets with less meat and dairy reduce environmental impact but may pose nutritional challenges for children. The current modelling study investigates the impact of diets with less or no meat and dairy products on nutrient intakes. DESIGN: Energy and nutrient intakes were assessed for observed consumption patterns (reference) and two replacement scenarios with data from the Dutch National Food Consumption Survey - Young Children (2005-2006). In the replacement scenarios, 30 % or 100 % of the consumed dairy and meat (in grams) was replaced by plant-derived foods with similar use. SETTING: The Netherlands. SUBJECTS: Children (n 1279) aged 2-6 years. RESULTS: Partial and full replacement of meat and dairy foods by plant-derived foods reduced SFA intake by 9 % and 26 %, respectively, while fibre intake was 8 % and 29 % higher. With partial replacement, micronutrient intakes were similar, except for lower vitamin B12 intake. After full meat and dairy replacement, mean intakes of Ca, Zn and thiamin decreased by 5-13 %, and vitamin B12 intake by 49 %, while total intake of Fe was higher but of lower bioavailability. With full replacement, the proportion of girls aged 4-6 years with intakes below recommendations was 15 % for thiamin, 10 % for vitamin B12 and 6 % for Zn. CONCLUSIONS: Partial replacement of meat and dairy by plant-derived foods is beneficial for children's health by lowering SFA intake, increasing fibre content and maintaining similar micronutrient intakes. When full replacements are made, attention is recommended to ensure adequate thiamin, vitamin B12 and Zn intakes.

SPADE, a new statistical program to estimate habitual dietary intake from multiple food sources and dietary supplements.

BACKGROUND: For the evaluation of both the adequacy of intakes and the risk of excessive intakes of micronutrients, all potential sources should be included. In addition to micronutrients naturally present in foods, micronutrients can also be derived from fortified foods and dietary supplements. In the estimation of the habitual intake, this may cause specific challenges such as multimodal distributions and heterogeneous variances between the sources. OBJECTIVE: We present the Statistical Program to Assess Dietary Exposure (SPADE) that was developed to cope with these challenges in one single program. METHOD: Similar to other methods, SPADE can model habitual intake of daily and episodically consumed dietary components. In addition, SPADE has the option to model habitual intake from dietary supplements. Moreover, SPADE offers models to estimate habitual intake distributions from different sources (e.g., foods and dietary supplements) separately and adds these habitual intakes to get the overall habitual intake distribution. The habitual intake distribution is modeled as a function of age, and this distribution can directly be compared with cutoff values to estimate the proportion above or below. Uncertainty in the habitual intake distribution and in the proportion below or above a cutoff value is quantified with ready-for-use bootstrap and provides 95% CIs. RESULTS: SPADE is implemented in R and is freely available as an R package called SPADE.RIVM. The various features of SPADE are illustrated by the estimation of the habitual intake distribution of folate and folic acid for women by using data from the Dutch National Food Consumption Survey 2007-2010. The results correspond well with the results of existing programs. CONCLUSION: SPADE offers new features to existing programs to estimate the habitual intake distribution because it can handle many different types of modeling with the first-shrink-then-add approach.

Relative validity of a short qualitative food frequency questionnaire for use in food consumption surveys.

BACKGROUND: The aim of the present study was to assess the relative validity of a self-administered qualitative food frequency questionnaire (FFQ) applied in the Belgian food consumption survey. METHODS: Comparison of food consumption data from an FFQ with 7-day estimated diet records (EDR) was made in a sample of 100 participants (aged 15-90 years). The FFQ comprised a total of 50 foods. Both FFQ and EDR foods were categorized into 15 conventional food groups. RESULTS: De-attenuated Spearman rank correlation coefficients between the FFQ and the EDR ranged from -0.16 for potatoes and grains to 0.83 for alcoholic beverages, with a median of 0.40 for all 15 food groups. The proportion of participants classified in the same tertile of intake by the FFQ and EDR ranged from 32% for potatoes and grains to 76% for alcoholic beverages. Extreme classification into opposite tertiles was <10% for milk and soy products, alcoholic beverages, fried restgroup foods and fats. CONCLUSION: Notwithstanding the short nature and the absence of portion size questions, the FFQ appears to be reasonably valid in both genders and across different age categories for most food groups. However, for the food groups bread and cereals, potatoes and grains, and sauces, estimates should be interpreted with caution because of poor ranking agreement.

Predicting urinary creatinine excretion and its usefulness to identify incomplete 24 h urine collections.

Studies using 24 h urine collections need to incorporate ways to validate the completeness of the urine samples. Models to predict urinary creatinine excretion (UCE) have been developed for this purpose; however, information on their usefulness to identify incomplete urine collections is limited. We aimed to develop a model for predicting UCE and to assess the performance of a creatinine index using para-aminobenzoic acid (PABA) as a reference. Data were taken from the European Food Consumption Validation study comprising two non-consecutive 24 h urine collections from 600 subjects in five European countries. Data from one collection were used to build a multiple linear regression model to predict UCE, and data from the other collection were used for performance testing of a creatinine index-based strategy to identify incomplete collections. Multiple linear regression (n 458) of UCE showed a significant positive association for body weight (ß = 0·07), the interaction term sex × weight (ß = 0·09, reference women) and protein intake (ß = 0·02). A significant negative association was found for age (ß = -0·09) and sex (ß = -3·14, reference women). An index of observed-to-predicted creatinine resulted in a sensitivity to identify incomplete collections of 0·06 (95 % CI 0·01, 0·20) and 0·11 (95 % CI 0·03, 0·22) in men and women, respectively. Specificity was 0·97 (95 % CI 0·97, 0·98) in men and 0·98 (95 % CI 0·98, 0·99) in women. The present study shows that UCE can be predicted from weight, age and sex. However, the results revealed that a creatinine index based on these predictions is not sufficiently sensitive to exclude incomplete 24 h urine collections.

A three-part, mixed-effects model to estimate the habitual total vitamin D intake distribution from food and dietary supplements in Dutch young children.

Statistical modeling of habitual micronutrient intake from food and dietary supplements using short-term measurements is hampered by heterogeneous variances and multimodality. Summing short-term intakes from food and dietary supplements prior to simple correction for within-person variation (first add then shrink) may produce estimates of habitual total micronutrient intake so badly biased as to be smaller than estimates of habitual intake from food sources only. A 3-part model using a first shrink then add approach is proposed to estimate the habitual micronutrient intake from food among nonsupplement users, food among supplement users, and supplements. The population distribution of habitual total micronutrient intake is estimated by combining these 3 habitual intake distributions, accounting for possible interdependence between Eq. 2 and 3. The new model is an extension of a model developed by the USA National Cancer Institute. Habitual total vitamin D intake among young children was estimated using the proposed model and data from the Dutch food consumption survey (n = 1279). The model always produced habitual total intakes similar to or higher than habitual intakes from food sources only and also preserved the multimodal shape of the observed total vitamin D intake distribution. This proposed method incorporates several sources of covariate information that should provide more precise estimates of the habitual total intake distribution and the proportion of the population with intakes below/above cutpoint values. The proposed methodology could be useful for other complex situations, e.g. where high concentrations of micronutrients appear in episodically consumed foods.

Estimating usual food intake distributions by using the multiple source method in the EPIC-Potsdam Calibration Study.

Estimating usual food intake distributions from short-term quantitative measurements is critical when occasionally or rarely eaten food groups are considered. To overcome this challenge by statistical modeling, the Multiple Source Method (MSM) was developed in 2006. The MSM provides usual food intake distributions from individual short-term estimates by combining the probability and the amount of consumption with incorporation of covariates into the modeling part. Habitual consumption frequency information may be used in 2 ways: first, to distinguish true nonconsumers from occasional nonconsumers in short-term measurements and second, as a covariate in the statistical model. The MSM is therefore able to calculate estimates for occasional nonconsumers. External information on the proportion of nonconsumers of a food can also be handled by the MSM. As a proof-of-concept, we applied the MSM to a data set from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Calibration Study (2004) comprising 393 participants who completed two 24-h dietary recalls and one FFQ. Usual intake distributions were estimated for 38 food groups with a proportion of nonconsumers > 70% in the 24-h dietary recalls. The intake estimates derived by the MSM corresponded with the observed values such as the group mean. This study shows that the MSM is a useful and applicable statistical technique to estimate usual food intake distributions, if at least 2 repeated measurements per participant are available, even for food groups with a sizeable percentage of nonconsumers.

Validation of syndromic surveillance for respiratory pathogen activity.

Syndromic surveillance is increasingly used to signal unusual illness events. To validate data-source selection, we retrospectively investigated the extent to which 6 respiratory syndromes (based on different medical registries) reflected respiratory pathogen activity. These syndromes showed higher levels in winter, which corresponded with higher laboratory counts of Streptococcus pneumoniae, respiratory syncytial virus, and influenza virus. Multiple linear regression models indicated that most syndrome variations (up to 86%) can be explained by counts of respiratory pathogens. Absenteeism and pharmacy syndromes might reflect nonrespiratory conditions as well. We also observed systematic syndrome elevations in the fall, which were unexplained by pathogen counts but likely reflected rhinovirus activity. Earliest syndrome elevations were observed in absenteeism data, followed by hospital data (+1 week), pharmacy/general practitioner consultations (+2 weeks), and deaths/laboratory submissions (test requests) (+3 weeks). We conclude that these syndromes can be used for respiratory syndromic surveillance, since they reflect patterns in respiratory pathogen activity.

the potential of AGE MODE, an age-dependent model, to estimate usual intakes and prevalences of inadequate intakes in a population.

Dietary intake data often stem from short-term measurements. However, for dietary assessment, generally the habitual intake distribution is of interest. Currently, habitual intake distributions are often estimated separately for subgroups of gender and age and do not take into account the variation in intake caused by age within age groups. Therefore, we developed an age-dependent dietary assessment model, which was demonstrated and tested using folate intakes from the third Dutch National Food Consumption Survey, conducted in 1997/98. The proposed model produced estimates of the mean habitual intake and intake percentiles as a function of age. The methodology has clear advantages in estimating habitual intakes in children. Also, given the large variation in intakes of several dietary components, estimated habitual intakes produced by other methods may have low precision and be less reliable if numbers are small. In our age-dependent model, all available data can be used to estimate the parameters of the habitual intake distribution, improving the precision of the estimates, and providing consistent estimates for a larger population sample as no subgroups need to be created. Although the model may still be further developed, the feature of age dependency shows clear advantages above methods currently used to estimate habitual intakes.

Automated detection of infectious disease outbreaks: hierarchical time series models.

The purpose of infectious disease surveillance is to inform the public health policy makers on the incidence and trends of infectious diseases and to trigger appropriate actions to control infectious disease outbreaks. The enormous amount of data collected with automated laboratory-based surveillance systems require automated algorithms for detecting unexpected aberrations that may signal infectious disease outbreaks. In this paper, we explore the potential of hierarchical time series models to detect deviations from expected incidence. As these count data are extremely noisy it can be expected that these models are suitable to detect signal from noise and accommodate for possible autocorrelation. The proposed procedure consists of three steps; (1) the model parameters are estimated by empirical Bayes on a training period of, e.g. a year; (2) the expected values are updated for small time steps (e.g. daily) as new data arrive; (3) threshold levels are updated conditionally on the past expected values and an alarm is triggered when the threshold level is exceeded. To test the potential of the models we estimated sensitivity, specificity and timeliness on simulated time series and compared the results with an alternative approach of a linear regression model adjusted for trends and season. We also used two observed series for Rubella notifications and Salmonella infections and compared our findings with the expert opinions on these series. The hierarchical time series models approach shows high sensitivity and specificity and correctly identifies outbreaks at an early stage. This, in our opinion, makes the proposed model a reliable tool for adequate automated detection of infectious disease outbreaks.