Overall diet quality of 8-year-old children did not conform to dietary guidelines, especially for children having more screen time, children of lower educated or smoking mothers, or from lower-income households.

Background Timing and types of complementary feeding in infancy affect nutritional status and health later in life. The present study aimed to investigate the factors associated with early introduction of complementary feeding (i.e., before age 4 months), and factors associated with infants consumption of non-recommended foods, including sweet beverages and snack foods. Methods This study used cross-sectional data from the BeeBOFT study ( n = 2157). Data on complementary feeding practices and potential determinants were obtained by questionnaire at infant’s age of 6 months. Logistic regression models were used to investigate factors associated with early introduction of complementary feeding and infants’ consumption of non-recommended foods. Results 21.4% of infants had received complementary feeding before 4 months of age. At the age of 6 months, 20.2% of all infants were consuming sweet beverages daily and 16.5% were consuming snack foods daily. Younger maternal age, lower maternal educational level, absence or shorter duration of breastfeeding, parental conviction that “my child always wants to eat when he/she sees someone eating” and not attending day-care were independently associated with both early introduction of complementary feeding and the consumption of non-recommended foods. Higher maternal pre-pregnancy BMI and infant postnatal weight gain were associated only with early introduction of complementary feeding. Conclusions We identified several demographical, biological, behavioral, psychosocial, and social factors associated with inappropriate complementary feeding practices. These findings are relevant for designing intervention programs aimed at educating parents. Trial registration The trail is registered at Netherlands Trial Register, trail registration number: NTR1831 . Retrospectively registered on May 29, 2009. Electronic supplementary material The online version of this article (10.1186/s12889-019-6722-4) contains supplementary material, which is available to authorized users.

Background: Food insecurity is related to risk of adverse health outcomes such as obesity, but the explanatory factors underlying this association are still unclear. This study aimed to assess the association between food insecurity and obesity, and to explore potential mediation by sociodemographic and lifestyle factors. Methods: This cross-sectional study was conducted among 250 participants in a deprived urban area in the Netherlands. Data on sociodemographic and lifestyle factors, food insecurity status and diet quality were collected using questionnaires. Diet quality was determined based on current national dietary guidelines. BMI was calculated from self-reported height and weight. Regression analyses were performed to explore the association between food insecurity and BMI status. Mediation analyses were performed to estimate the total-, direct-, and indirect effect and proportion of total effect mediated of the food insecurity-obesity association. Results: The overall prevalence of food insecurity was 26%. Food insecurity was associated with obesity (OR = 2.49, 95%CI = 1.16, 5.33), but not with overweight (OR = 1.15, 95%CI = 0.54, 2.45) in the unadjusted model. The food insecurity-obesity association was partially mediated by living situation (proportion mediated: 15.4%), diet quality (− 18.6%), and smoking status (− 15.8%) after adjustment for other covariates. Conclusions: The findings of this study suggest an association between food insecurity and obesity. Living situation, diet quality and smoking status explained part, but not all, of the total association between food insecurity and obesity. Future longitudinal studies are warranted to examine the temporal order of the food insecurity-obesity association and potential mediators in this relationship. In addition, food insecurity and its potential consequences need to be taken into account in obesity prevention programs and policies.

BackgroundHealthy eating behaviour is an essential determinant of overall health. This behaviour is generally poor among people at risk of experiencing food insecurity, which may be caused by many factors including perceived higher costs of healthy foods, financial stress, inadequate nutritional knowledge, and inadequate skills required for healthy food preparation. Few studies have examined how these factors influence eating behaviour among people at risk of experiencing food insecurity. We therefore aimed to gain a better understanding of the needs and perceptions regarding healthy eating in this target group.MethodsWe conducted a qualitative exploration grounded in data using inductive analyses with 10 participants at risk of experiencing food insecurity. The analysis using an inductive approach identified four core factors influencing eating behaviour: Health related topics; Social and cultural influences; Influences by the physical environment; and Financial influences.ResultsOverall, participants showed adequate nutrition knowledge. However, eating behaviour was strongly influenced by both social factors (e.g. child food preferences and cultural food habits), and physical environmental factors (e.g. temptations in the local food environment). Perceived barriers for healthy eating behaviour included poor mental health, financial stress, and high food prices. Participants had a generally conscious attitude towards their financial situation, reflected in their strategies to cope with a limited budget. Food insecurity was mostly mentioned in reference to the past or to others and not to participants’ own current experiences. Participants were familiar with several existing resources to reduce food-related financial strain (e.g. debt assistance) and generally had a positive attitude towards these resources. An exception was the Food Bank, of which the food parcel content was not well appreciated. Proposed interventions to reduce food-related financial strain included distributing free meals, facilitating social contacts, increasing healthy food supply in the neighbourhood, and lowering prices of healthy foods.ConclusionThe insights from this study increase understanding of factors influencing eating behaviour of people at risk of food insecurity. Therefore, this study could inform future development of potential interventions aiming at helping people at risk of experiencing food insecurity to improve healthy eating, thereby decreasing the risk of diet-related diseases.

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Objective The current study aimed to explore the interplay between food insecurity, fast-food outlet exposure, and dietary quality in disadvantaged neighbourhoods. Design In this cross-sectional study, main associations between fast-food outlet density and proximity, food insecurity status and dietary quality were assessed using Generalized Estimating Equation analyses. We assessed potential moderation by fast-food outlet exposure in the association between food insecurity status and dietary quality by testing for effect modification between food insecurity status and fast-food outlet density and proximity. Setting A deprived urban area in the Netherlands. Participants We included 226 adult participants with at least one child below the age of 18 years living at home. Results Fast-food outlet exposure was not associated with experiencing food insecurity (fast-food outlet density: b=-0.026, 95%CI=-0.076; 0.024; fast-food outlet proximity: b=-0.003, 95%CI=-0.033; 0.026). Experiencing food insecurity was associated with lower dietary quality (b=-0.48 per unit increase, 95%CI=-0.94; -0.012). This association was moderated by fast-food outlet proximity (p-interaction=0.008), and stratified results revealed that the adverse effect of food insecurity on dietary quality was more pronounced for those with the nearest fast-food outlet located closer to the home. Conclusions Food insecurity but not fast-food outlet density is associated with dietary quality. However, the association between food insecurity and dietary quality may be modified by the food environment. These findings could inform policy-makers to promote a healthier food environment including less fast-food outlets, with particular emphasis on areas with high percentages of food insecure households.

ObjectivesThe aim of this study was to examine the added value of food insecurity in explaining poor physical and mental health beyond other socioeconomic risk factors.Design, setting, participants and outcome measuresData for this cross-sectional study were collected using questionnaires with validated measures for food insecurity status and health status, including 199 adult participants with at least 1 child living at home, living in or near disadvantaged neighbourhoods in The Hague, the Netherlands. To assess the added value of food insecurity, optimism-corrected goodness-of-fit statistics of multivariate regression models with and without food insecurity status as a covariate were compared.ResultsIn the multivariable models explaining poor physical health (Physical Component Summary: PCS) and mental health (Mental Component Summary: MCS), from all included socioeconomic risk factors, food insecurity score was the most important covariate. Including food insecurity score in those models led to an improvement of explained variance from 6.3% to 9.2% for PCS, and from 5.8% to 11.0% for MCS, and a slightly lower root mean square error. Further analyses showed that including food insecurity score improved the discriminative ability between those individuals most at risk of poor health, reflected by an improvement in C-statistic from 0.64 (95% CI 0.59 to 0.71) to 0.69 (95% CI 0.62 to 0.73) for PCS and from 0.65 (95% CI 0.55 to 0.68) to 0.70 (95% CI 0.61 to 0.73) for MCS. Further, explained variance in these models improved with approximately one-half for PCS and doubled for MCS.ConclusionsFrom these results it follows that food insecurity score is of added value in explaining poor physical and mental health beyond traditionally used socioeconomic risk factors (ie, age, educational level, income, living situation, employment status and migration background) in disadvantaged communities. Therefore, routine food insecurity screening may be important for effective risk stratification to identify populations at increased risk of poor health and provide targeted interventions.

Food insecurity is an important public health concern; however, research into this phenomenon within the Netherlands is limited. Food insecurity is not solely related to individual factors, but can also be influenced by various factors in the social and physical environment. Therefore, this study aimed to identify determinants of food insecurity within the personal, social and physical environment, based on the social ecological model (SEM), and to identify their relative importance for experiencing food insecurity. The study population consisted of 307 participants living in disadvantaged neighbourhoods of the Dutch city The Hague, of which approximately one-quarter were food insecure. Participant characteristics showing bivariate associations P < 0⋅20 were placed in a predetermined level of the SEM, after which a multivariate logistic regression was performed for each level and the Nagelkerke pseudo R2 was presented. Determinants of food insecurity were BMI, gross monthly income, highest educational attainment, smoking status, diet quality, employment status, marital status and religion (P < 0⋅05). The results showed that 29⋅7 % of the total variance in food insecurity status was explained by all included determinants together. The personal, social and physical environment explained 20⋅6, 14⋅0 and 2⋅4 % of the total variance, respectively. Our findings suggest that determinants within the personal environment are most important for explaining differences in experienced food insecurity. The present study contributes to furthering the knowledge about the relative importance of the personal, social and physical environment, indicating that determinants within the personal environment may be most promising for developing targeted interventions to reduce food insecurity.