2021
DOI: 10.3390/su13148082
|View full text |Cite
|
Sign up to set email alerts
|

Data Integration for Diet Sustainability Analyses

Abstract: 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… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
2

Citation Types

1
12
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
5

Relationship

3
2

Authors

Journals

citations
Cited by 5 publications
(13 citation statements)
references
References 41 publications
1
12
0
Order By: Relevance
“…Indeed, there is often a lack of transparency about elements that are not included in analytical frameworks. This can be seen in how emission estimates often do not include activities beyond the farm, most notably transportation ( 64 ). Such system boundaries inevitably impact results of studies.…”
Section: Discussionmentioning
confidence: 99%
“…Indeed, there is often a lack of transparency about elements that are not included in analytical frameworks. This can be seen in how emission estimates often do not include activities beyond the farm, most notably transportation ( 64 ). Such system boundaries inevitably impact results of studies.…”
Section: Discussionmentioning
confidence: 99%
“…Others ( 11 ) have used the Food and Nutrient Database for Dietary Studies (FNDDS) ( 36 ) and Food Patterns Equivalents Database (FPED) ( 37 ) to disaggregate NHANES foods for diet sustainability analyses, but these databases do not account for food waste which represents ~30% (by weight) of food available for consumption ( 26 ), and will underestimate the associated sustainability outcomes. 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 ).…”
Section: Discussionmentioning
confidence: 99%
“…NHANES is the backbone of diet sustainability analyses in the US because it is the richest source of nationally representative dietary data. 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).…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Ongoing diet sustainability analyses [ 5 ] have pointed to interactions and tradeoffs among the 4 food systems domains of nutrition and health, economics, society, and the environment. Diet sustainability analyses employ metrics and measures from multiple domains that are context specific and operate across space and time [ 5 , 6 ]. The goal of such analyses is to identify dietary patterns that respect planetary boundaries while assuring affordable food and nutrition security for all [ 4 ].…”
Section: Introductionmentioning
confidence: 99%