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Recommendations for fruit and vegetable consumption are largely unmet. Lower socio-economic status (SES), neighbourhood poverty and poor access to retail outlets selling healthy foods are thought to predict lower consumption. The objective of the present study was to assess the interrelationships between these risk factors as predictors of fruit and vegetable consumption.
Cross-sectional multilevel analyses of data on fruit and vegetable consumption, socio-demographic characteristics, neighbourhood poverty and access to healthy retail food outlets.
Survey data from the 2002 and 2004 New York City Community Health Survey, linked by residential zip code to neighbourhood data.
Adult survey respondents (n 15 634).
Overall 9·9 % of respondents reported eating ≥5 servings of fruits or vegetables in the day prior to the survey. The odds of eating ≥5 servings increased with higher income among women and with higher educational attainment among men and women. Compared with women having less than a high-school education, the OR was 1·12 (95 % CI 0·82, 1·55) for high-school graduates, 1·95 (95 % CI 1·43, 2·66) for those with some college education and 2·13 (95 % CI 1·56, 2·91) for college graduates. The association between education and fruit and vegetable consumption was significantly stronger for women living in lower- v. higher-poverty zip codes (P for interaction < 0·05). The density of healthy food outlets did not predict consumption of fruits or vegetables.
Higher SES is associated with higher consumption of produce, an association that, in women, is stronger for those residing in lower-poverty neighbourhoods.
Angular-resolved ESCA was used to study single cadmium arachidate monolayers transferred to Si (100) wafers by the Langmuir-Blodgett technique. We find the monolayers to be of high integrity with respect to those defects which enhance the escape probability of substrate photoelectrons through the overlayer. The inelastic mean-free pathlengths of Si (2p) and C (1s) electrons were calculated to be 49±6 Å and 45±6 Å for the kinetic energies of 1388 eV and 1202 eV, respectively. The overall ordering of the hydrocarbon chains is less than for alkane thiols assembled on noble metals. We find that the precision of the Tyler algorithm to deconvolute angular-resolved ESCA data into depth profiles is accurate within 10% for predicting the thickness of the hydrocarbon overlayer but less precise for intermediate layers.