Dutch food bank recipients have poorer dietary intakes than the general and low-socioeconomic status Dutch adult population.

PURPOSE: Food-assistance program users are a specific group of nutritional concern, as they are often food insufficient and have poorer diet quality compared to non-food-assistance program users. The aim of our study was to assess dietary intake of Dutch food bank recipients (n = 167) and to compare this with dietary intake of a representative sample of the general population (Dutch National Food Consumption Survey (DNFCS-all): n = 1933), including a low-socioeconomic status (SES) sample (DNFCS-low SES: n = 312), using data from the DNFCS 2007-2010. METHODS: In this cross-sectional study, 12 food banks throughout The Netherlands participated. Food bank recipients' characteristics were assessed with a self-administered questionnaire. Dietary intake data were collected through three 24-h recalls. Habitual dietary intake (mean, percentiles, and 95% CI) was estimated for all samples. Differences between samples were determined by comparing the 95% CIs. RESULTS: Mean age of the study population (62.9% female) was 48.6 years (SD:10.1). Mean energy intake was 1986 (95% CI 1830-2089) kcal. The majority of the Dutch food bank recipients had lower intakes than dietary reference intakes for dietary fiber, fruit, vegetables, and fish (range 86.6-99.3%), and a higher intake for saturated fat [88.1% (95% CI 84.1-98.9)]. Furthermore, mean intakes of energy, fiber, fruit, and vegetables were significantly lower in Dutch food bank recipients than in the DNFCS-all and the DNFCS-low-SES [e.g., daily mean fruit intake (g) food bank recipients 62.8 (95% CI 45.5-76.5), DNFCS-all 105.8 (95% CI 105.4-117.9), and DNFCS-low-SES 85.1 (95% CI 78.7-100.2)]. Fish intake was significantly lower compared with the DNFCS-all, but not compared with the DNFCS-low-SES. CONCLUSIONS: Dutch food bank recipients, who largely rely on the content of food parcels, are not able to meet the nutritional guidelines for a healthy diet, and their dietary intake is poorer than the general as well as the low-SES sample of the Dutch adult population. More research is needed on how to improve the dietary intake of this vulnerable population subgroup, by, e.g., revising the content of the food parcels, and to develop effective intervention activities.

Seasonal patterns in time series of pertussis.

To gain insight into pertussis disease dynamics, we studied age-specific long-term periodicity and seasonality of pertussis in The Netherlands. Hierarchical time-series models were used to analyse the monthly reported pertussis incidence in January 1996-June 2006 by age group. The incidence of pertussis showed a slightly increasing long-term trend with highest incidence rates seen in 1996, 1999, 2001 and 2004. For all age groups the annual peak incidence was found in August, except for the 13-18 years age group where the peak occurred in November. Monthly trends in adults showed high correlation with trends in age groups 0-4 years (0.94) and 5-12 years (0.92). We found no evidence for a relationship between annual rises in pertussis and the opening of schools. Concurrent annual fluctuations of pertussis incidence in adults and infants suggest frequent transmission within and between these age groups. Studying trends offers insight into transmission dynamics and may facilitate decisions on future vaccination strategies.

Optimization of a monitoring network for sulfur dioxide.

In this study, we develop and apply a methodology to reduce an existing monitoring network to find an optimal configuration of a smaller network. We use a criterion based on locally weighted regression with two different weight functions. The methodology is applied to the Dutch national SO2 network and offers the possibility to include different politically relevant options in the model by weight criteria. Because full enumeration of all monitoring networks is impossible, a combinatorial search algorithm is applied to find a (sub)optimal solution. If different (optimal) monitoring networks result from different criteria, then the best can be selected.

Gaussian Quadrature is an efficient method for the back-transformation in estimating the usual intake distribution when assessing dietary exposure.

In dietary exposure assessment, statistical methods exist for estimating the usual intake distribution from daily intake data. These methods transform the dietary intake data to normal observations, eliminate the within-person variance, and then back-transform the data to the original scale. We propose Gaussian Quadrature (GQ), a numerical integration method, as an efficient way of back-transformation. We compare GQ with six published methods. One method uses a log-transformation, while the other methods, including GQ, use a Box-Cox transformation. This study shows that, for various parameter choices, the methods with a Box-Cox transformation estimate the theoretical usual intake distributions quite well, although one method, a Taylor approximation, is less accurate. Two applications--on folate intake and fruit consumption--confirmed these results. In one extreme case, some methods, including GQ, could not be applied for low percentiles. We solved this problem by modifying GQ. One method is based on the assumption that the daily intakes are log-normally distributed. Even if this condition is not fulfilled, the log-transformation performs well as long as the within-individual variance is small compared to the mean. We conclude that the modified GQ is an efficient, fast and accurate method for estimating the usual intake distribution.