Abstract

Previous studies show that diet quality varies by socioeconomic gradient. We compared the influence of individual- and area-level socioeconomic characteristics on food choice behavior and dietary nutrient intakes in a cross-sectional survey. Daily nutrient intakes were calculated from a food frequency questionnaire. Participants comprised 4007 people (1915 men, 2092 women) aged 35 to 74 years. Socioeconomic measures included the area-based deprivation NZDep2001, gross household income, education level and the occupation-based New Zealand Socioeconomic Index (NZSEI96). Results: Nutrients expressed as their percentage contribution to total energy intakes and adjusted for age, gender and ethnicity, showed that intakes of cholesterol were higher in the lower income groups, and fibre, alcohol and calcium were lower compared to the highest income group. Similarly adjusted nutrients expressed as their contribution to total energy intakes showed lower alcohol intakes in the lower NZDep2001 classes compared to the highest NZDep2001 class. Lower fruit, cheese, wine, and spirit servings were found in both the lower income and NZDep2001 groups. Lower vegetables, milk and cereal servings were found in the lowest income group compared with the highest. Higher chicken, eggs and bread servings were found in the lowest NZDep2001 group compared to the highest NZDep2001 group. Few statistically significant associations were observed with the NZSEI96 or education. Conclusion: Income was more strongly associated with nutrient intakes and NZDep2001 with food group selections. Lower fruit, cheese, wine and spirit servings in the lower SES strata showed independent associations with income and NZDep2001. However, NZDep2001 and income appear to be measuring different elements of dietary intakes and food group servings, with income being associated with lower vegetable, milk and cereal servings, and increased dietary cholesterol and lower fibre, and calcium intakes and NZDep2001 with increased chicken, eggs and bread servings. More in depth, research into area-level determinants of diet is warranted.

Highlights

  • Measures of socioeconomic status (SES) that have shown the greatest influence on health in New Zealand include income and poverty, employment and occupation, housing, population-based services, social cohesion and culture, and ethnicity [1]

  • NZDep2001 and income appear to be measuring different elements of dietary intakes and food group servings, with income being associated with lower vegetable, milk and cereal servings, and increased dietary cholesterol and lower fibre, and calcium intakes and NZDep2001 with increased chicken, eggs and bread servings

  • We have previously reported that dietary intakes showed a generally more adverse pattern in the lower socioeconomic strata and that the New Zealand Socioeconomic Index (NZSEI96) and education were more strongly associated with food group selections, whereas nutrient intakes were associated with income in a multiracial workforce [5]

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Summary

Introduction

Measures of socioeconomic status (SES) that have shown the greatest influence on health in New Zealand include income and poverty, employment and occupation, housing, population-based services, social cohesion and culture, and ethnicity [1]. Geyer et al [4] argue that income, education and occupational class cannot be used interchangeably, and that they are correlated, they measure different phenomena and tap into different causal mechanisms. We have previously reported that dietary intakes showed a generally more adverse pattern in the lower socioeconomic strata and that the New Zealand Socioeconomic Index (NZSEI96) and education were more strongly associated with food group selections, whereas nutrient intakes were associated with income in a multiracial workforce [5]. The aim of this study was to compare daily dietary nutrients and food group servings per month across the area-based deprivation index NZDep2001, household income, level of education and the New Zealand Socioeconomic Index (NZSEI96) and to determine whether there were differences after adjusting for other measures of socioeconomic status

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