Search

Objectives: While status anxiety has received attention as a potential mechanism generating health inequalities, empirical evidence is still limited. Studies have been ecological and have largely focused on mental and not physical health outcomes. Methods: We conducted individual-level analyses to assess status anxiety (feelings of inferiority resulting from social comparisons) and resources (financial difficulties) as mediators of the relationship between socioeconomic status (SES) (education/occupation/employment status) and type 2 diabetes (T2D). We used cross-sectional data of 21,150 participants (aged 18–70 years) from the Amsterdam-based HELIUS study. We estimated associations using logistic regression models and estimated mediated proportions using natural effect modelling. Results: Odds of status anxiety were higher among participants with a low SES [e.g., OR = 2.66 (95% CI: 2.06–3.45) for elementary versus academic occupation]. Odds of T2D were 1.49 (95% CI: 1.12–1.97) times higher among participants experiencing status anxiety. Proportion of the SES–T2D relationship mediated was 3.2% (95% CI: 1.5%–7.0%) through status anxiety and 10.9% (95% CI: 6.6%–18.0%) through financial difficulties. Conclusion: Status anxiety and financial difficulties played small but consistent mediating roles. These individual-level analyses underline status anxiety’s importance and imply that status anxiety requires attention in efforts to reduce health inequalities., Objectives: While status anxiety has received attention as a potential mechanism generating health inequalities, empirical evidence is still limited. Studies have been ecological and have largely focused on mental and not physical health outcomes. Methods: We conducted individual-level analyses to assess status anxiety (feelings of inferiority resulting from social comparisons) and resources (financial difficulties) as mediators of the relationship between socioeconomic status (SES) (education/occupation/employment status) and type 2 diabetes (T2D). We used cross-sectional data of 21,150 participants (aged 18–70 years) from the Amsterdam-based HELIUS study. We estimated associations using logistic regression models and estimated mediated proportions using natural effect modelling. Results: Odds of status anxiety were higher among participants with a low SES [e.g., OR = 2.66 (95% CI: 2.06–3.45) for elementary versus academic occupation]. Odds of T2D were 1.49 (95% CI: 1.12–1.97) times higher among participants experiencing status anxiety. Proportion of the SES–T2D relationship mediated was 3.2% (95% CI: 1.5%–7.0%) through status anxiety and 10.9% (95% CI: 6.6%–18.0%) through financial difficulties. Conclusion: Status anxiety and financial difficulties played small but consistent mediating roles. These individual-level analyses underline status anxiety’s importance and imply that status anxiety requires attention in efforts to reduce health inequalities.

Chronic stress contributes to the onset of type 2 diabetes (T2D), yet the underlying etiological mechanisms are not fully understood. Responses to stress are influenced by earlier experiences, sex, emotions and cognition, and involve a complex network of neurotransmitters and hormones, that affect multiple biological systems. In addition, the systems activated by stress can be altered by behavioral, metabolic and environmental factors. The impact of stress on metabolic health can thus be considered an emergent process, involving different types of interactions between multiple variables, that are driven by non-linear dynamics at different spatiotemporal scales. To obtain a more comprehensive picture of the links between chronic stress and T2D, we followed a complexity science approach to build a causal loop diagram (CLD) connecting the various mediators and processes involved in stress responses relevant for T2D pathogenesis. This CLD could help develop novel computational models and formulate new hypotheses regarding disease etiology.

Objective: To examine the prevalence of sarcopenia and its association with protein intake in men and women in a multi-ethnic population.Design: We used cross-sectional data from the HELIUS (Healthy Life in an Urban Setting) study, which includes nearly 25,000 participants (aged 18–70 years) of Dutch, South-Asian Surinamese, African Surinamese, Turkish, Moroccan, and Ghanaian ethnic origin. For the current study, we included 5161 individuals aged 55 years and older. Sarcopenia was defined according to the EWGSOP2. In a subsample (N = 1371), protein intake was measured using ethnic-specific Food Frequency Questionnaires. Descriptive analyses were performed to study sarcopenia prevalence across ethnic groups in men and women, and logistic regression analyses were used to study associations between protein intake and sarcopenia.Results: Sarcopenia prevalence was found to be sex- and ethnic-specific, varying from 29.8% in Turkish to 61.3% in South-Asian Surinamese men and ranging from 2.4% in Turkish up to 30.5% in South-Asian Surinamese women. Higher protein intake was associated with a 4% lower odds of sarcopenia in the subsample (OR = 0.96, 95%-CI: 0.92–0.99) and across ethnic groups, being only significant in the South-Asian Surinamese group.Conclusion: Ethnic differences in the prevalence of sarcopenia and its association with protein intake suggest the need to target specific ethnic groups for prevention or treatment of sarcopenia.

Background: Protein intake has been associated with the development of pre-diabetes (pre-T2D) and type 2 diabetes (T2D). The gut microbiota has the capacity to produce harmful metabolites derived from dietary protein. Furthermore, both the gut microbiota composition and metabolic status (e.g., insulin resistance) can be modulated by diet and ethnicity. However, to date most studies have predominantly focused on carbohydrate and fiber intake with regards to metabolic status and gut microbiota composition. Objectives: To determine the associations between dietary protein intake, gut microbiota composition, and metabolic status in different ethnicities. Methods: Separate cross-sectional analysis of two European cohorts (MetaCardis, n = 1759; HELIUS, n = 1528) including controls, patients with pre-T2D, and patients with T2D of Caucasian/non-Caucasian origin with nutritional data obtained from Food Frequency Questionnaires and gut microbiota composition. Results: In both cohorts, animal (but not plant) protein intake was associated with pre-T2D status and T2D status after adjustment for confounders. There was no significant association between protein intake (total, animal, or plant) with either gut microbiota alpha diversity or beta diversity, regardless of ethnicity. At the species level, we identified taxonomical signatures associated with animal protein intake that overlapped in both cohorts with different abundances according to metabolic status and ethnicity. Conclusions: Animal protein intake is associated with pre-T2D and T2D status but not with gut microbiota beta or alpha diversity, regardless of ethnicity. Gut microbial taxonomical signatures were identified, which could function as potential modulators in the association between dietary protein intake and metabolic status.

Abstract Objective: The aim of the current study was to establish whether the neighbourhood food environment, characterised by the healthiness of food outlets, the diversity of food outlets and fast-food outlet density within a 500 m or 1000 m street network buffer around the home address, contributed to ethnic differences in diet quality. Design: Cross-sectional cohort study. Setting: Amsterdam, the Netherlands. Participants: Data on adult participants of Dutch, South-Asian Surinamese, African Surinamese, Turkish and Moroccan descent (n total 4728) in the HELIUS study were analysed. Results: The neighbourhood food environment of ethnic minority groups living in Amsterdam is less supportive of a healthy diet and of less diversity than that of participants of Dutch origin. For example, participants of Turkish, Moroccan and South-Asian Surinamese descent reside in a neighbourhood with a significantly higher fast-food outlet density (≤1000 m) than participants of Dutch descent. However, we found no evidence that neighbourhood food environment characteristics directly contributed to ethnic differences in diet quality. Conclusion: Although ethnic minority groups lived in less healthy food environments than participants of ethnic Dutch origin, this did not contribute to ethnic differences in diet quality. Future research should investigate other direct or indirect consequences of residing in less supportive food environments and gain a better understanding of how different ethnic groups make use of their neighbourhood food environment.

Background: Inequalities in obesity pertain in part to differences in dietary intake in different socioeconomic groups. Examining the economic, social, physical and political food environment of low-income groups as a complex adaptive system – i.e. a system of multiple, interconnected factors exerting non-linear influence on an outcome, can enhance the development and assessment of effective policies and interventions by honouring the complexity of lived reality. We aimed to develop and apply novel causal loop diagramming methods in order to construct an evidence-based map of the underlying system of environmental factors that drives dietary intake in low-income groups. Methods: A systematic umbrella review was conducted on literature examining determinants of dietary intake and food environments in low-income youths and adults in high/upper-middle income countries. Information on the determinants and associations between determinants was extracted from reviews of quantitative and qualitative studies. Determinants were organised using the Determinants of Nutrition and Eating (DONE) framework. Associations were synthesised into causal loop diagrams that were subsequently used to interpret the dynamics underlying the food environment and dietary intake. The map was reviewed by an expert panel and systems-based analysis identified the system paradigm, structure, feedback loops and goals. Results: Findings from forty-three reviews and expert consensus were synthesised in an evidence-based map of the complex adaptive system underlying the food environment influencing dietary intake in low-income groups. The system was interpreted as operating within a supply-and-demand, economic paradigm. Five sub-systems (‘geographical accessibility’, ‘household finances’, ‘household resources’, ‘individual influences’, ‘social and cultural influences’) were presented as causal loop diagrams comprising 60 variables, conveying goals which undermine healthy dietary intake. Conclusions: Ou

Optimizing protein intake is a novel strategy to prevent age associated loss of muscle mass and strength in older adults. Such a strategy is still missing for older adults from ethnic minority populations. Protein intake in these populations is expected to be different in comparison to the majority of the population due to several socio-cultural factors. Therefore, the present study examined the dietary protein intake and underlying behavioral and environmental factors affecting protein intake among older adults from ethnic minorities in the Netherlands. We analyzed frequency questionnaire (FFQ) data from the Healthy Life in an Urban Setting (HELIUS) cohort using ANCOVA to describe dietary protein intake in older adults from ethnic minorities in the Netherlands (N = 1415, aged >55 years, African Surinamese, South Asian Surinamese, Moroccan, and Turkish). Additionally, we performed focus groups among older adults from the same ethnic minority populations (N = 69) to discover behavioral and environmental factors affecting protein intake; 40–60% of the subjects did not reach minimal dietary protein recommendations needed to maintain muscle mass (1.0 g/kg bodyweight per day (BW/day)), except for Turkish men (where it was 91%). The major sources of protein originated from animal products and were ethnic specific. Participants in the focus groups showed little knowledge and awareness about protein and its role in aging. The amount of dietary protein and irregular eating patterns seemed to be the major concern in these populations. Optimizing protein intake in these groups requires a culturally sensitive approach, which accounts for specific protein product types and sociocultural factors.

The aim of this study was to determine the relative validity of the HEalthy LIfe in an Urban Setting (HELIUS) food frequency questionnaire (FFQ) in assessing the dietary intake of energy, nutrients, and food groups of Dutch older men and women. In 2014-2015, 88 participants of the Longitudinal Aging Study Amsterdam aged 71.9 (SD 8.6) years completed the 238-item HELIUS FFQ and three 24-hour dietary recalls. The mean group-level bias in the intakes of energy, nutrients, and food groups between the two methods was assessed, as well as Pearson's correlation coefficients and level of agreement using quintile distribution. For the intakes of energy and macronutrients, the group-level bias was ≤5%, Pearson's correlation coefficients were moderate to good (ranging from 0.26 for total fat to 0.72 for alcohol), and agreement was moderate to high (classification in same or adjacent quintile ranging from 63% for energy, protein, and carbohydrate to 91% for alcohol). For most micronutrients and food groups, the relative validity was moderate (Pearson's correlation coefficients between 0.3 and 0.5), with the lowest correlations for β-carotene (0.08), vitamin B1 (0.19), fish (0.14), and grains (0.24). In conclusion, for energy and macronutrients, most micronutrients, and most food groups, the relative validity of the HELIUS FFQ to assess dietary intake in Dutch older adults was acceptable to good.

OBJECTIVE: To gain insight in Dutch food bank recipients' perception on the content of the food parcels, their dietary intake and how the parcels contribute to their overall dietary intake.DESIGN: Eleven semi-structured focus group discussions were conducted. Focus group topics were based on Andersons food insecurity definition: the lack of availability of nutritionally adequate foods and the assured ability to acquire foods in socially acceptable ways. Data were coded and analysed with Atlas.ti 7.0 software, using the framework approach.SETTING: Seven food banks throughout the Netherlands.PARTICIPANTS: A total of 44 Dutch food bank recipients.RESULTS: Food bank recipients were not always satisfied with the amount, quality, variation and type of foods in the food parcel. For the participants who could afford to, supplementing the food parcel was reported as main reason for buying foods, and price was the most important aspect in selecting these foods. Participants were not satisfied with their dietary intake; they mainly reported not having enough to eat. The content of the food parcel importantly influenced participants' overall dietary intake. Finally, participants reported struggling with their feelings of dissatisfaction, while also being grateful for the foods they receive.CONCLUSIONS: This study suggests that, despite their best efforts, food banks are not meeting food bank recipients' needs. Our results provide valuable directions for improving the content of the food parcels by increasing the quantity, quality and variation in the foods supplied. Whether this also improves the dietary intake of recipients needs to be determined.

OBJECTIVE: This study aimed to describe distributions of behavioral circadian disruptors in a free-living setting among a nonshift working multi-ethnic population, estimate the associated risk of type 2 diabetes (T2D), and determine whether disruptors account for ethnic differences in T2D.METHODS: Participants from six ethnic groups were included (Amsterdam, the Netherlands; n = 1,347-3,077 per group). Multinomial logistic regression was used to estimate ethnic differences in disruptors, such as skipping breakfast, eating erratically, and sleep duration. Associations between disruptors and incident T2D and the interaction by ethnicity were studied by Cox regression.RESULTS: Ethnic minority populations skip breakfast more often, time meals differently, have longer periods of fasting, eat more erratically, and have more short/long sleep durations than the Dutch. Night snacking from 4 am to 6 am (HR: 5.82; 95% CI: 1.42-23.91) and both short (HR: 1.48; 95% CI: 1.03-2.12) and long sleep (HR: 3.09; 95% CI: 1.54-6.22), but no other disruptors, were associated with T2D. The higher T2D risk among ethnic minority populations compared with Dutch did not decrease after adjustment for last snack or length of sleep.CONCLUSIONS: Although prevalence of circadian disruptors was higher among ethnic minority populations and some disruptors were associated with T2D, disruptors did not account for ethnic differences in T2D risk.