Higher consumption of ‘ultra-processed’ (UP) foods has been linked to adverse health outcomes. The present paper aims to characterise percentage energy from UP foods by participant socio-economic status (SES), diet quality, self-reported food expenditure and energy-adjusted diet cost. Participants in the population-based Seattle Obesity Study III (n 755) conducted in WA in 2016–2017 completed socio-demographic and food expenditure surveys and the FFQ. Education and residential property values were measures of SES. Retail prices of FFQ component foods (n 378) were used to estimate individual-level diet cost. Healthy Eating Index (HEI-2015) and Nutrient Rich Food Index 9.3 (NRF9.3) were measures of diet quality. UP foods were identified following NOVA classification. Multivariable linear regressions were used to test associations between UP foods energy, socio-demographics, two estimates of food spending and diet quality measures. Higher percentage energy from UP foods was associated with higher energy density, lower HEI-2015 and NRF9.3 scores. The bottom decile of diet cost ($216·4/month) was associated with 67·5 % energy from UP foods; the top decile ($369·9/month) was associated with only 48·7 % energy from UP foods. Percentage energy from UP foods was inversely linked to lower food expenditures and diet cost. In multivariate analysis, percentage energy from UP foods was predicted by lower food expenditures, diet cost and education, adjusting for covariates. Percentage energy from UP foods was linked to lower food spending and lower SES. Efforts to reduce UP foods consumption, an increasingly common policy measure, need to take affordability, food expenditures and diet costs into account.

中文翻译：

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通过参与者人口统计、饮食质量和饮食成本来表征超加工食品的能量百分比：西雅图肥胖研究 (SOS) III 的结果

“超加工”（UP）食品的高消费与不良健康结果有关。本论文旨在通过参与者的社会经济地位 (SES)、饮食质量、自我报告的食物支出和能量调整的饮食成本来描述 UP 食物的能量百分比。以人群为基础的西雅图肥胖研究 III 的参与者（n755) 于 2016-2017 年在西澳进行，完成了社会人口和食品支出调查以及 FFQ。教育和住宅物业价值是衡量社会经济地位的指标。FFQ成分食品零售价（n378）被用来估计个人层面的饮食成本。健康饮食指数 (HEI-2015) 和营养丰富的食物指数 9.3 (NRF9.3) 是衡量饮食质量的指标。UP 食品是在 NOVA 分类后确定的。多变量线性回归用于测试 UP 食品能量、社会人口统计学、食品支出的两个估计和饮食质量测量之间的关联。来自 UP 食品的较高能量百分比与较高的能量密度、较低的 HEI-2015 和 NRF 相关9.3分数。饮食成本最低的十分位数（216·4 美元/月）与 67·5 % 来自 UP 食品的能量相关；最高的十分位数（$369·9/月）仅与来自 UP 食品的 48·7 % 的能量相关。来自 UP 食品的能量百分比与较低的食品支出和饮食成本呈负相关。在多变量分析中，UP 食物的能量百分比可通过降低食物支出、饮食成本和教育来预测，并调整协变量。来自 UP 食品的能量百分比与较低的食品支出和较低的社会经济地位有关。努力减少 UP 食品消费是一种越来越普遍的政策措施，需要考虑可负担性、食品支出和饮食成本。