Higher-diet quality is associated with higher diet costs when eating at home and away from home: National Health and Nutrition Examination Survey, 2005–2016

Conrad, Zach; Reinhardt, Sarah; Boehm, Rebecca; McDowell, Acree

doi:10.1017/s1368980021002810

Cited by 20 publications

(21 citation statements)

References 30 publications

(66 reference statements)

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“…Food loss and waste (retail loss, inedible portions, and consumer waste) can be estimated through a three-step procedure that links the LAFA data series, the FCID, and the NHANES [28,32]. The first step requires applying simple algebra to the food loss/waste rates and the available data in the LAFA data series to disaggregate inedible portions from cooking loss and uneaten food, which are otherwise aggregated under the heading "loss at the consumer level" (these calculations are described in detail elsewhere [77]). Data are not available in the LAFA data series to disaggregate cooking loss from uneaten food; therefore, it can be assumed that these collectively represent consumer food waste.…”

Section: Data Integration: Food Loss and Wastementioning

confidence: 99%

Data Integration for Diet Sustainability Analyses

et al. 2021

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Diet sustainability analyses are stronger when they incorporate multiple food systems domains, disciplines, scales, and time/space dimensions into a common modeling framework. Few analyses do this well: there are large gaps in food systems data in many regions, accessing private and some public data can be difficult, and there are analytical challenges, such as creating linkages across datasets and using complex analytical methods. This article summarizes key data sources across multiple domains of food system sustainability (nutrition, economic, environment) and describes methods and tools for integrating them into a common analytic framework. Our focus is the United States because of the large number of publicly available and highly disaggregated datasets. Thematically, we focus on linkages that exist between environmental and economic datasets to nutrition, which can be used to estimate the cost and agricultural resource use of food waste, interrelationships between healthy eating and climate impacts, diets optimized for cost, nutrition, and environmental impacts, and others. The limitations of these approaches and data sources are described next. By enhancing data integration across these fields, researchers can be better equipped to promote policy for sustainable diets.

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Section: Data Integration: Food Loss and Wastementioning

confidence: 99%

Data Integration for Diet Sustainability Analyses

et al. 2021

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“…By contrast, FCID is the only food composition database that disaggregates NHANES mixed dishes into ingredients that map onto agricultural commodities, which can then be linked with data on food waste from the Loss-adjusted Food Availability data series ( 38 ), as described elsewhere ( 9 ). These linked FCID-LAFA data can be used to evaluate the association between food waste and multiple indicators of sustainability, including agricultural resource use ( 26 , 27 ), environmental impacts ( 25 ), diet quality ( 26 , 27 ), and consumer food expenditures ( 28 , 29 ). The present study allows these linkages to be extended to more contemporary data on food intake from NHANES 2011–2018, thereby filling an important data gap.…”

Section: Discussionmentioning

confidence: 99%

“…In some cases, researchers only used NHANES data up until 2010 to align with the year FCID was last updated ( 21 , 25 , 40 ), which does not reflect changes in food consumption that have occurred since that time. Others have combined FCID 2001–2010 with NHANES data up to 2016 with ( 28 , 29 ) and without ( 26 ) imputation to fill data gaps, and demonstrated that incomplete linkages led to a reduction of daily Total Food Demand (sum of retail loss and consumer purchase amount) by 10% ( 26 ) and a reduction of daily consumer food expenditures by 7 ( 28 ) to 15% ( 29 ).…”

Section: Discussionmentioning

confidence: 99%

“…Survey respondents typically report consumption of mixed dishes that contain multiple ingredients, so food composition databases are used to quantify these ingredients, which provides a crosswalk to environmental and economic databases (9). Key among these food composition databases is the Food Commodity Intake Database (FCID), which disaggregates NHANES foods into nearly 500 highly differentiated ingredients and has been used to evaluate dietary intake (12)(13)(14)(15)(16), chemical exposure (17)(18)(19)(20), environmental impacts (7,(21)(22)(23)(24)(25), agricultural resource use (26,27), and food expenditures (28,29). However, FCID has not been updated since 2010, so it does not link with more contemporary NHANES data and therefore presents a barrier for further diet sustainability analyses.…”

Section: Introductionmentioning

confidence: 99%

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Diet Sustainability Analyses Can Be Improved With Updates to the Food Commodity Intake Database

et al. 2022

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Diet sustainability analyses inform policymaking decisions and provide clinicians and consumers with evidence-based information to make dietary changes. In the United States, the Food Commodity Intake Database (FCID) provides a crosswalk for integrating nationally representative data on food intake from the National Health and Nutrition Examination Survey (NHANES) with data on sustainability outcomes from other publicly available databases. However, FCID has not been updated since 2010 and does not link with contemporary NHANES data, which limits further advancements in sustainability research. This study fills this research gap by establishing novel linkages between FCID and NHANES 2011–2018, comparing daily per capita food intake with and without these linkages, and making these data publicly available for use by other researchers. To update FCID, two investigators independently established novel data linkages, a third investigator resolved discrepancies, and a fourth investigator audited linkages for accuracy. Dietary data were acquired from nearly 45,000 adults from 2001 to 2018, and food intake was compared between updated vs. non-updated FCID versions. Total food intake from 2011 to 2018 was 5–23% higher using the updated FCID compared to the non-updated version, and intake was over 100% higher in some years for some food categories including poultry, eggs, legumes, starchy vegetables, and tropical oils (P < 0.001 for all comparisons). Further efforts may be needed to create new food composition data to reflect new products and reformulations that enter the food supply over time. This study removes a barrier to further diet sustainability analyses by establishing a data crosswalk between contemporary NHANES and other publicly available databases on agricultural resource use, environmental impacts, and consumer food expenditures.

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“…AHEI-2010 is a diet quality index based on foods or food components associated with chronic disease risk [ 17 ]. In this study, AHEI-2010 is composed of nine components: fruit, vegetables, whole grains, omega-3, nuts and legumes, polyunsaturated fatty acids, sugar-sweetened beverages, red and processed meat, and sodium.…”

Section: Methodsmentioning

confidence: 99%

Association between diet quality scores and risk of overweight and obesity in children and adolescents

Zheng¹,

Wang²,

Wu³

2023

BMC Pediatr

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Background This study examined the associations of diet quality assessed by Healthy Eating Index 2015 (HEI-2015), Alternative Healthy Eating Index 2010 (AHEI-2010), Mediterranean Diet (MedDiet) and overweight/obesity in children and adolescents. Methods This cross-sectional study used data of participants aged 2–19 years from National Health and Nutrition Examination Survey (NHANES) 2005–2018. The weighted logistic regression model was adopted to explore the association between diet quality scores and overweight, obesity in children and adolescents. Subgroup analysis was also performed based on sex. Results A total of 9,724 participants were included in children group (2–11 years old), and 5,934 were adolescent group (12–19 years old). All participants were divided into based on the BMI-for-age: underweight and normal, overweight and obesity groups. After adjusting for age, race, poverty-income ratio, maternal smoking during pregnancy and total energy, HEI-2015 and MedDiet scores were related to the risk of overweight in children, and only MedDiet scores remained associated with a decreased risk of obesity in children. MedDiet scores were associated with a decreased risk of overweight, obesity in adolescents, respectively, after adjusting age, sex, race, poverty-income ratio, cotinine, total energy and physical activity. The similar results in male participants were also found. Conclusion Higher MedDiet scores were associated with lower the risk of overweight and obesity, respectively, particularly for male children and adolescents. The higher HEI-2015 scores were also related to the risk of overweight in children.

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Higher-diet quality is associated with higher diet costs when eating at home and away from home: National Health and Nutrition Examination Survey, 2005–2016

Cited by 20 publications

References 30 publications

Data Integration for Diet Sustainability Analyses

Data Integration for Diet Sustainability Analyses

Diet Sustainability Analyses Can Be Improved With Updates to the Food Commodity Intake Database

Association between diet quality scores and risk of overweight and obesity in children and adolescents

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