Anti-tissue transglutaminase antibodies (TG2A) positivity and the risk of vitamin D deficiency among children - a cross-sectional study in the generation R cohort.

BACKGROUND: Suboptimal vitamin D status is common in people with celiac disease (CeD), a disease that can be characterized by the presence of serum anti-tissue transglutaminase antibodies (TG2A) (i.e., TG2A positivity). To date, it remains unclear whether childhood TG2A positivity is associated with vitamin D status and how this potential association can be explained by other factors than malabsorption only, since vitamin D is mainly derived from exposure to sunlight. The aim of our study was therefore to assess whether childhood TG2A positivity is associated with vitamin D concentrations, and if so, to what extent this association can be explained by sociodemographic and lifestyle factors. METHODS: This cross-sectional study was embedded in the Generation R Study, a population-based prospective cohort. We measured serum anti-tissue transglutaminase antibodies (TG2A) concentrations and serum 25-hydroxyvitamin D (25(OH)D) concentrations of 3994 children (median age of 5.9 years). Children with serum TG2A concentrations ≥ 7 U/mL were considered TG2A positive. To examine associations between TG2A positivity and 25(OH)D concentrations, we performed multivariable linear regression, adjusted for sociodemographic and lifestyle factors. RESULTS: Vitamin D deficiency (serum 25(OH)D < 50 nmol/L) was found in 17 out of 54 TG2A positive children (31.5%), as compared to 1182 out of 3940 TG2A negative children (30.0%). Furthermore, TG2A positivity was not associated with 25(OH)D concentrations (ß -2.20; 95% CI -9.72;5.33 for TG2A positive vs. TG2A negative children), and this did not change after adjustment for confounders (ß -1.73, 95% CI -8.31;4.85). CONCLUSIONS: Our findings suggest there is no association between TG2A positivity and suboptimal vitamin D status in the general pediatric population. However, the overall prevalence of vitamin D deficiency in both populations was high, suggesting that screening for vitamin D deficiency among children, regardless of TG2A positivity, would be beneficial to ensure early dietary intervention if needed.

The interplay between fast-food outlet exposure, household food insecurity and diet quality in disadvantaged districts.

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 (Pinteraction = 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 policymakers to promote a healthier food environment including less fast-food outlets, with particular emphasis on areas with high percentages of food insecure households.

Comparing saliva and urine samples for measuring breast milk intake with the 2H oxide dose-to-mother technique among children 2-4 months old.

Saliva and urine are the two main body fluids sampled when breast milk intake is measured with the 2H oxide dose-to-mother technique. However, these two body fluids may generate different estimates of breast milk intake due to differences in isotope enrichment. Therefore, we aimed to assess how the estimated amount of breast milk intake differs when based on saliva and urine samples and to explore whether the total energy expenditure of the mothers is related to breast milk output. We used a convenience sample of thirteen pairs of mothers and babies aged 2-4 months, who were exclusively breastfed and apparently healthy. To assess breast milk intake, we administered doubly labelled water to the mothers and collected saliva samples from them, while simultaneously collecting both saliva and urine from their babies over a 14-d period. Isotope ratio MS was used to analyse the samples for 2H and 18O enrichments. Mean breast milk intake based on saliva samples was significantly higher than that based on urine samples (854·5 v. 812·8 g/d, P = 0·029). This can be attributed to slightly higher isotope enrichments in saliva and to a poorer model fit for urine samples as indicated by a higher square root of the mean square error (14·6 v. 10·4 mg/kg, P = 0·001). Maternal energy expenditure was not correlated with breast milk output. Our study suggests that saliva sampling generates slightly higher estimates of breast milk intake and is more precise as compared with urine and that maternal energy expenditure does not influence breast milk output.

Exploring food insecurity and obesity in Dutch disadvantaged neighborhoods: a cross-sectional mediation analysis.

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.

Needs and perceptions regarding healthy eating among people at risk of food insecurity: a qualitative analysis.

BACKGROUND: Healthy 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. METHODS: We 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. RESULTS: Overall, 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. CONCLUSION: The 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.

Diet quality in childhood: the Generation R Study.

PURPOSE: We aimed to evaluate diet quality of 8-year-old children in the Netherlands, to identify sociodemographic and lifestyle correlates of child diet quality, and to examine tracking of diet quality from early to mid-childhood. METHODS: For 4733 children participating in a population-based cohort, we assessed dietary intake using a validated food-frequency questionnaire at a median age of 8.1 years (interquartile range 8.0-8.2) (2011-2014). Based on dietary guidelines, we developed and validated a food-based diet quality score for children consisting of ten components (score 0-10): sufficient intake of vegetables; fruit; whole grains; fish; legumes; nuts; dairy; oils and soft fats; and low intake of sugar-containing-beverages; and high-fat and processed meat. RESULTS: We observed a mean (± SD) diet quality score of 4.5 (± 1.2) out of a maximum of 10. On average, intake of legumes, nuts, and oils or soft fats was below recommendations, whereas intake of sugar-containing beverages and high-fat or processed meat was higher than recommended. The main factors associated with higher diet quality were higher maternal educational level (ß = 0.29, 95% CI 0.21, 0.37 versus low education), higher household income (ß = 0.15, 95% CI 0.05, 0.25 versus low income), no maternal smoking (ß = 0.13, 95% CI 0.02, 0.25 versus current smoking), and less screen time (ß = 0.31, 95% CI 0.24, 0.38)-all independent of each other. For children with available dietary data at age 1 year (n = 2608), we observed only weak tracking of diet quality from early to mid-childhood (Pearson's r = 0.19, k = 0.11 for extreme quartiles). CONCLUSION: 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.

Factors associated with early introduction of complementary feeding and consumption of non-recommended foods among Dutch infants: the BeeBOFT study.

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.

Food insecurity and other barriers to adherence to a gluten-free diet in individuals with coeliac disease and non-coeliac gluten sensitivity in the Netherlands: a mixed-methods study.

OBJECTIVES: To determine the prevalence of food insecurity among individuals with coeliac disease (CeD) and non-coeliac gluten sensitivity (NCGS) in the Netherlands and explore its association with diet quality and other barriers to adherence to a gluten-free diet. DESIGN: Mixed-method design comprising a survey and semistructured interviews. SETTING: An online survey was distributed through social media accounts and the newsletter of the Dutch Association for Celiac Disease. Community-dwelling patients were surveyed and interviewed between June and November 2023. PARTICIPANTS AND OUTCOME MEASURES: In total 548 adults with CeD and NCGS in the Netherlands who adhered to a gluten-free diet completed the survey including questions related to demographics, household food insecurity, financial stress and diet quality. Regression analyses were conducted to assess associations between food insecurity and diet quality, and between food insecurity and perceived difficulty of gluten-free eating and cooking. Additionally, semistructured interviews with eight food insecure adults with CeD were conducted. RESULTS: The prevalence of food insecurity was 23.2%, with 10.4% reporting very low food security. Very low food insecurity was associated with poorer diet quality (ß=-5.5; 95% CI=-9.2 to -1.9; p=0.003). Food insecurity was associated with heightened perceived barriers across multiple themes. In age, income and education adjusted models, compared with food secure participants, low food secure participants were more likely to experience difficulty regarding skills (OR=2.5; 95% CI=1.5 to 4.3; p≤0.001), social circumstances (OR=2.6; 95% CI=1.1 to 6.4; p=0.038), resources (OR=2.5; 95% CI=1.5 to 4.4; p=0.001) and naturally gluten-free products (OR=1.8; 95% CI=1.0 to 3.1; p=0.045) in gluten-free eating and cooking. Participants with very low food security were more likely to experience difficulty regarding skills (OR=4.4; 95% CI=2.4 to 8.1; p≤0.001) and resources (OR=4.2; 95% CI=2.3 to 7.8; p<0.001) in gluten-free eating and cooking. The qualitative analysis provided a deeper understanding of these challenges, including employed strategies to manage costs and insights into the mental burden associated with adhering to a gluten-free diet. CONCLUSION: These findings indicate that food insecurity is prevalent among Dutch people with CeD and NCGS, with potential impact on diet quality and adherence to a gluten-free diet. It further provided insight into perceived barriers to adhering to a gluten-free diet among this target population. These challenges should be taken into account by clinicians and policy makers.

The Food Environment Around Primary Schools in a Diverse Urban Area in the Netherlands: Linking Fast-Food Density and Proximity to Neighbourhood Disadvantage and Childhood Overweight Prevalence.

In the Netherlands, the neighbourhood food environment has received little attention in initiatives to combat overweight/obesity. This study maps the food environment around primary schools in The Hague, The Netherlands, and examines associations between neighbourhood disadvantage, the school food environment and childhood overweight using Geographic Information Systems (GIS). Linear regression analyses were performed to test the association between schools' disadvantage scores (proxy for neighbourhood disadvantage) and relative fast-food density within 400 m and 1000 m and fast-food proximity. Univariable and multivariable linear regression analyses were used to test the association between the school food environment and overweight prevalence among children in the respective sub-district in which the schools is found. Multivariable analyses were adjusted for the schools' disadvantage scores. Results show that fast-food outlets were available around most primary schools. Schools in disadvantaged neighbourhoods were closer to and surrounded by a higher number of fast-food restaurants, grillrooms and kebab shops. On the sub-district level, the density of such fast-food outlets was associated with overweight prevalence among children. These findings highlight the importance of national and local policies to improve the food environment, particularly in disadvantaged neighbourhoods.

Food insecurity in Dutch disadvantaged neighbourhoods: a socio-ecological approach.

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 R 2 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.

Food insecurity status is of added value in explaining poor health: a cross-sectional study among parents living in disadvantaged neighbourhoods in the Netherlands.

OBJECTIVES: The 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 MEASURES: Data 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. RESULTS: In 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. CONCLUSIONS: From 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.

Extending the Theory of Planned Behavior for Explaining Dietary Quality: The Role of Financial Scarcity and Food Insecurity Status.

OBJECTIVE: To examine whether an extended Theory of Planned Behavior (TPB) that included finance-related barriers better explained dietary quality. DESIGN: Cross-sectional survey. PARTICIPANTS: One-thousand and thirty-three participants were included from a Dutch independent adult panel. MAIN OUTCOME: Dietary quality. ANALYSIS: Five TPB models were assessed: a traditional TPB, a TPB that included direct associations between attitude and subjective norm with dietary quality, a TPB that additionally included financial scarcity or food insecurity, and a TPB that additionally included financial scarcity and food insecurity simultaneously. Structural relationships among the constructs were tested to compare the explanatory power. RESULTS: The traditional TPB showed poorest fit (χ2/degrees of freedom = 11; comparative fit index = 0.75; root mean square error of approximation [95% confidence interval], 0.10 [0.091-0.12]; standardized root mean square residual = 0.049), the most extended TPB (including both financial scarcity and food insecurity) showed best fit (χ2/degrees of freedom = 3.3; comparative fit index = 0.95; root mean square error of approximation [95% confidence interval], 0.050 [0.035-0.065]; standardized root mean square residual = 0.018). All 5 structure models explained ∼42% to 43% of the variance in intention; however, the variance in dietary quality was better explained by the extended TPB models, including food insecurity and/or financial scarcity (∼22%) compared with the traditional TBP (∼7%), indicating that these models better explained differences in dietary quality. CONCLUSIONS AND IMPLICATIONS: These findings highlight the importance of accounting for finance-related barriers to healthy eating like financial scarcity or food insecurity to better understand individual dietary behaviors in lower socioeconomic groups.

[Changes in perceived food insecurity and eating behavior in the Netherlands since the COVID-19-crisis]. / Veranderingen in ervaren voedselzekerheid en eetgedrag in Nederland sinds de COVID-19-uitbraak.

In this study we describe changes in perceived food insecurity and eating habits in the Netherlands since the start of the COVID-19-crisis, how these changes were experienced, and which options were indicated for a healthier diet. The study was conducted through online questionnaires among adults with a relatively low socioeconomic position living in the Netherlands. We included 1033 participants. The results show changes in perceived food insecurity in the Netherlands since the start of the COVID-19 crisis, with some participants experiencing lower food security and others experiencing higher food security. About one-fifth of the participants reported that their eating pattern had changed since the start of the COVID-19-crisis, while more than half of the food insecure participants reported a changed eating pattern: in particular, they reported eating less healthily and fewer fruits and vegetables. Participants experiencing food insecurity more often reported to want help for a healthier diet. A cheaper food supply was seen as a promising solution, while food bank use was rarely mentioned in this regard. The COVID-19-crisis can lead to financial insecurity and changes in food availability/accessibility, known risk factors for food insecurity. Therefore, these findings highlight the urgency of reducing food insecurity and providing appropriate support for healthy eating, particularly for people experiencing food insecurity.

Effectiveness of the Beyond Good Intentions Program on Improving Dietary Quality Among People With Type 2 Diabetes Mellitus: A Randomized Controlled Trial.

Background and Aims: An appropriate diet is an essential component of the management of Type 2 Diabetes Mellitus (T2DM). However, for many people with T2DM, self-management is difficult. Therefore, the Beyond Good Intentions (BGI) education program was developed based on self-regulation and proactive coping theories to enhance people's capabilities for self-management. The aim of this study was to determine the effectiveness of the BGI program on improving dietary quality among a preselected group of people with T2DM after two-and-a-half years follow-up. Methods: In this randomized controlled trial, 108 people with T2DM were randomized (1:1) to the intervention (n = 56) (BGI-program) or control group (n = 52) (care as usual). Linear regression analyses were used to determine the effect of the BGI program on change in dietary quality between baseline and two-and-a-half years follow-up. In addition, potential effect modification by having a nutritional goal at baseline was evaluated. Multiple imputation (n = 15 imputations) was performed to account for potential bias due to missing data. Results: According to intention-to-treat analysis, participants in the intervention group showed greater improvements in dietary quality score than participants in the control group (ß = 0.71; 95%CI: 0.09; 1.33) after follow-up. Having a nutritional goal at baseline had a moderating effect on the effectiveness of the BGI program on dietary quality (p-interaction = 0.01), and stratified results showed that the favorable effect of the intervention on dietary quality was stronger for participants without a nutritional goal at baseline (no nutritional goal: ß = 1.46; 95%CI: 0.65; 2.27 vs. nutritional goal: ß = -0.24; 95%CI: -1.17; 0.69). Conclusions: The BGI program was significantly effective in improving dietary quality among preselected people with T2DM compared to care as usual. This effect was stronger among participants without a nutritional goal at baseline. A possible explanation for this finding is that persons with a nutritional goal at baseline already started improving their dietary intake before the start of the BGI program. Future studies are needed to elucidate the moderating role of goalsetting on the effectiveness of the BGI program.