RESUMO
BACKGROUND: While differences in population health across neighborhoods with different socioeconomic characteristics are well documented, health disparities across neighborhoods with similar socioeconomic characteristics are less well understood. We aimed to estimate population health inequalities, both within and between neighborhoods with similar socioeconomic status, and assessed the association of neighborhood characteristics and socioeconomic spillover effects from adjacent neighborhoods. METHODS: Based on Dutch whole-population data we determined the percentage of inhabitants with good or very good self-assessed health (SAH) and the percentage of inhabitants with at least one chronic disease (CD) in 11,504 neighborhoods. Neighborhoods were classified by quintiles of a composite neighborhoods socioeconomic status score (NSES). A set of spatial models was estimated accounting for spatial effects in the dependent, independent, and error components of the model. RESULTS: Substantial population health disparities in SAH and CD both within and between neighborhoods NSES quintiles were observed, with the largest SAH variance in the lowest NSES group. Neighborhoods adjacent to higher SES neighborhoods showed a higher SAH and a lower prevalence of CD. Projected impacts from the spatial regressions indicate how modest changes in NSES among the lowest socioeconomic neighborhoods can contribute to population health in both low- and high-SES neighborhoods. CONCLUSION: Population health differs substantially among neighborhoods with similar socioeconomic characteristics, which can partially be explained by a spatial socio-economic spillover effect.
RESUMO
OBJECTIVES: Ethnic minorities are often not included in studies of diet and health because of a lack of validated instruments to assess their habitual diets. Given the increased ethnic diversity in many high-income countries, insight into the diets of ethnic minorities is needed for the development of nutritional policies and interventions. In this paper, we describe the development of ethnic-specific food frequency questionnaires (FFQs) to study the diets of Surinamese (African and South Asian), Turkish, Moroccan and ethnic Dutch residents of The Netherlands. METHODS: An existing Dutch FFQ was adapted and formed the basis for three new FFQs. Information on food intake was obtained from single 24 h recalls. Food items were selected according to their percentage contribution to and variance in absolute nutrient intake of the respective ethnic groups. A nutrient database for each FFQ was constructed, consisting of data from the Dutch Food Composition table; data on ethnic foods were based on new chemical analyses and available international data. RESULTS: We developed four ethnic-specific FFQs using a standardised approach that included ~200 food items each and that covered more than 90% of the intake of the main nutrients of interest. CONCLUSIONS: The developed FFQs will enable standardised and comparable assessment of the diet of five different ethnic groups and provide insight into the role of diet in differences in health between ethnic groups. The methodology described in this paper and the choices made during the development phase may be useful in developing similar FFQs in other settings.
