Selected Metrics, Methodologies, Data, and Models
This appendix includes four tables—one each on metrics, methodologies, data sources, and models—that provide samples of existing resources for assessing food system effects. All of the tables have entries pertaining to health, environmental, social, and economic effects. They are meant to help researchers and assessors understand the availability of resources as they engage in complex system assessments.
The metrics table (see Table B-1) is designed to highlight measures commonly used to gauge key constructs that might be considered in doing an assessment. Each metric includes the purpose, the targeted group of persons or things that can be assessed with the measure, and basic information about how the measure is derived. Some of these metrics are indexes that provide an indication of several components simultaneously (e.g., the Healthy Eating Index). Other indicators are direct measurements of a variable.
The methodologies table (see Table B-2) provides key study designs, methodologies, and general models that can be used in complex system analyses or otherwise used to examine the effects of the food system.
The data sources table (see Table B-3) provides a list of some commonly used datasets that can be used in assessments of food system effects. Some of these are government funded, while others are proprietary; some are free, while others charge a fee. But all are publicly available. For each data source, the table includes the purpose of the resource, the target population of persons or things about which inferences can be drawn using the data, and sources of further information. Some data sources can be used to assess effects in various domains or to describe the food system itself. For
example, food availability data can be considered an economic outcome of the food system or can be used to describe the nutritional quality of the food supply and to infer the health status of the population. To avoid duplication, only one entry was included in cases where a data source has more than one purpose across various domains of effects.
Finally, the models table (see Table B-4) includes examples of specific models that have been used to simulate effects of the food system. There is not a direct correspondence between the model entries in Table B-2 (methodologies) and Table B-4 (models), however. The models described in Table B-2 are broad, while those in Table B-4 are for specific realizations of a subset of methodologies.
The tables are meant to be illustrative, not comprehensive, and to show a selection of the most common metrics, methodologies, data sources, and models used. Furthermore, it is expected that research related to health, environmental, social, and economic effects as well as to the food system itself will continue to expand, leading to the evolution of these resources and the development of new ones.
APPENDIX B TABLES FOLLOW
TABLE B-1 Selected Metrics for Assessing Health, Environmental, Social, and Economic Effects of Food System
Metric | Purpose | Target Population | How Measured | For Further Information |
HEALTH EFFECTS | ||||
Body mass index | Indicator of appropriateness of weight for height; used to define and screen for overweight and obesity | General population | Mass (kg) Height (m)2 |
http://www.cdc.gov/healthyweight/assessing/bmi http://nccor.org/projects/catalogue/index.php http://nccor.org/projects/measures/index.php |
Prevalence of disease | Indicator of the number of affected persons at a given time | General population | Number of cases of disease in the population at a given time; Number of persons in the population at same time |
Gordis, L. 1996. Epidemiology. Philadelphia, PA: W.B. Saunders. |
Incidence of disease | Indicator of the number of new cases of a disease that occur during a given period of time | General population | Number of new cases of disease in the population during a given period of time; Number of persons at risk of developing the disease during same time | Gordis, L. 1996. Epidemiology. Philadelphia, PA: W.B. Saunders. |
Mortality rate | Indicator of proportion of population dying from particular cause or all causes | General population | Total number of deaths from particular cause (or all causes); Number of persons in the population at mid-year |
Gordis, L. 1996. Epidemiology. Philadelphia, PA: W.B. Saunders. |
Cholesterol | The total concentration of cholesterol present in blood, including low-density lipoprotein, high-density lipoprotein, and very-low-density lipoprotein; sometimes used as a screening test for heart disease | General population | Total amount of cholesterol (mg)/dL of blood | http://wwwn.cdc.gov/nchs/nhanes/2011-2012/TCHOL_G.htm |
Blood mercury | An indicator of mercury exposure from all sources | General population, especially women of childbearing age | Total amount of mercury (elemental, inorganic, and organic) (ng)/mL of blood | http://www.cdc.gov/nchs/nhanes/nhanes2007-2008/pbcd_e.htm |
Healthy Eating Index | Measure of diet quality that assesses conformance to federal dietary guidance | Individuals Foods available in markets or outlets Menus National food supply |
Weighted score based on amounts of fruits; whole fruits; vegetables; greens and beans; whole grains; dairy; protein foods; seafood and plant proteins; refined grains; sodium; and empty calories per 1,000 kcal, and the amount of poly- plus mono-unsaturated fatty acids per amount of saturated fatty acids | http://www.cnpp.usda.gov/HealthyEatingIndex.htm http://www.cnpp.usda.gov/Publications/HEI/HEI-2010/CNPPFactSheetNo2.pdf |
Metric | Purpose | Target Population | How Measured | For Further Information |
FoodNet | Measure national trends in outbreaks from year to year based on FoodNet database (see Table B-3) | General population | Estimate of the burden of illness for the most common or the most severe foodborne illness etiological agents, based on FoodNet outbreak database corrected for various factors, including rate of visiting the hospital when individuals suffer from diarrheal disease, how often specimens are collected in an attempt to identify the etiological agent involved, and specific tests that are run on samples provided | http://www.cdc.gov/foodborneburden/trends-infoodborne-illness.htm |
ENVIRONMENTAL EFFECTS | ||||
Nitrate Groundwater Pollution Hazard Index | Farmers | The index works with an overlay of soil, crop, and irrigation information; based on the three components, an overall potential hazard number is assigned and management practices are suggested where necessary | http://ciwr.ucanr.edu/Tools/Nitrogen_Hazard_Index |
Air Quality Index (AQI) | Index for reporting daily air quality | Local conditions for a variety of target populations | AQI is calculated using five major air pollutants regulated by the Clean Air Act: ground-level ozone, particle pollution (also known as particulate matter), carbon monoxide, sulfur dioxide, and nitrogen dioxide | http://www.airnow.gov/index.cfm?action=topics.about_airnow |
Erodibility Index | Provides information on the potential of the soil to erode based on physical and chemical properties of the soil and climatic conditions | Farmers Resource managers | Combines the effects of slope and soil type, rainfall intensity, and land use | http://www.nrcs.usda.gov/wps/portal/nrcs/detail/national/technical/?cid=stelprdb1041925 |
SOCIAL AND ECONOMIC EFFECTS | ||||
Income, Wealth, Equity | ||||
Gross sectoral output and factor productivity | Assess the productivity of the use of different factors (labor, capital, land, etc.) in producing food | Aggregate farm sector | Index values are assigned to the various inputs and outputs associated with farm production; indexes allow comparisons across disparate types of inputs and commodities and across time | http://www.ers.usda.gov/data-products/agriculturalproductivity-in-the-us.aspx |
Metric | Purpose | Target Population | How Measured | For Further Information |
Sector profitability | Assess the economic performance of key industrial actors in food supply chain | Major food industry firms | Estimated profit margins for top U.S. companies | http://pages.stern.nyu.edu/~adamodar/New_Home_Page/datafile/margin.html |
http://money.cnn.com/magazines/fortune/fortune500/2009/performers/industries/profits | ||||
Industry structure (concentration) | Track changes in the concentration of production and ownership in different food supply chain sectors | Farm producers, food processors, manufacturers, distributors, and retailers | Four-Firm Index Gini Coefficient | http://www.ers.usda.gov/topics/farm-economy/farmstructure-and-organization/research-on-farm-structure-and-organization.aspx |
http://www.foodcircles.missouri.edu/consol.htm | ||||
Average net farm income | Document trends in the income and wealth position of farm operator households | Farm operator households | Indicators of average income and wealth position, distribution of farm households by income class | http://www.ers.usda.gov/data-products/farm-income-and-wealth-statistics.aspx |
http://www.ers.usda.gov/topics/farm-economy/farm-household-well-being.aspx | ||||
http://ers.usda.gov/data-products/arms-farm-financial-and-crop-production-practices.aspx |
Employment in food system industries | Determine levels and conditions of employment across different segments of food supply chain | Food supply chain sector | Indicators of employment level by sector | http://www.bls.gov/bls/employment.htm http://www.bls.gov/cps |
Worker compensation; average and median household income; poverty rate in worker households | Track changes in wages and poverty among workers in different segments of food supply chain | Workers in food supply chain sectors | Mean wages, weeks of employment, and household poverty rates for workers in different sectors | http://www.bls.gov/bls/blswage.htm |
http://www.bls.gov/cps/earnings.htm#occind | ||||
http://www.bls.gov/opub/ted/2003/jun/wk5/art04.htm | ||||
http://www.bls.gov/cps | ||||
Quality of Life | ||||
Farm operator managerial control (contracting, debt: asset ratio) | Track trends in economic relationships that affect independence of farm operators | Farm operator households | Levels of debt, presence of formal production, or marketing contracts | http://www.ers.usda.gov/topics/farm-economy/farmsector-income-finances/assets,-debt,-and-wealth.aspx |
http://www.ers.usda.gov/topics/farm-economy/farm-structure-and-organization.aspx |
Metric | Purpose | Target Population | How Measured | For Further Information |
Working conditions (hours, safety, stability, housing, access to benefits, opportunity for career mobility) | Examine quality of working conditions, pay and benefits for workers in different segments of food supply chain | Workers in different food supply chain sectors | Mean wages, hours of work, access to benefits, duration of employment | http://www.doleta.gov/agworker/naws.cfm |
http://www.ers.usda.gov/topics/farm-economy/farmlabor.aspx | ||||
http://foodchainworkers.org/wp-content/uploads/2012/06/Hands-That-Feed-Us-Report.pdf | ||||
http://www.bls.gov/bls/blswage.htm | ||||
http://www.bls.gov/ncs/ebs/home.htm | ||||
http://www.bls.gov/cps/lfcharacteristics.htm#tenure | ||||
Economic power (citizenship status of workers, unionization) | Examine social status and organization of workers in different food system industries | Food system industry sectors | Levels of unionization and citizenship status of workers by sector | http://www.bls.gov/cps/lfcharacteristics.htm#union |
http://www.bls.gov/cps/demographics.htm#foreignborn |
Gender and racial equality | Examine differences in social and economic effects among genders and races | General population | Data are stratified by gender or race in order to identify differences | See discipline of topic-specific readings. For example, for health disparities see http://www.nlm.nih.gov/hsrinfo/disparities.html |
http://www.cdc.gov/chronicdisease/healthequity/index.htm | ||||
Worker Health and Safety | ||||
Occupational injury rates (fatal and nonfatal) | Measure magnitude of workplace safety risks | Private-sector employers and employees | Provides injury and illness counts and rates by employer and employee characteristics | http://www.bls.gov/iif |
http://www.cdc.gov/niosh/injury | ||||
Food Availability | ||||
Food Costs and Expenditures | ||||
Food costs (prices and elasticities) | General population | Measures of the Consumer Price Index (CPI) as an indicator of changes in retail food prices, food expenditures, the food dollar series, which measures annual expenditures by U.S. consumers; and price spreads, which compare the prices paid by consumers for food with the prices received by farmers for their corresponding commodities | http://www.ers.usda.gov/topics/food-marketsprices/food-prices,expenditures-costs.aspx#.VACGK2MXNkg | |
http://www.fapri.iastate.edu/tools/elasticity.aspx | ||||
http://www.ers.usda.gov/data-products/commodity-and-food-elasticities.aspx#.VACPUWMXNkg |
Metric | Purpose | Target Population | How Measured | For Further Information |
Percentage of income spent on food (overall, by income, job, or health status) | General population | http://www.ers.usda.gov/data-products/foodexpenditures.aspx#.VACPk2MXNkg | ||
Percentage of food expenditures by food category, place of consumption | General population | http://www.ers.usda.gov/data-products/foodexpenditures.aspx#.VACPk2MXNkg | ||
http://www.bls.gov/cex/2012/combined/quintile.pdf | ||||
Food Security | ||||
Household and individual food security and insecurity | General population | http://www.ers.usda.gov/topics/foodnutrition-assistance/food-security-in-the-us/definitions-of-food-security.aspx#.VACQB2MXNkg | ||
Participation in different nutrition programs (Supplemental Nutrition Assistance Programs [SNAP] and others) | General population | http://www.ers.usda.gov/topics/foodnutrition-assistance/supplemental-nutrition-assistance-program-%28snap%29.aspx#.VACQUWMXNkh |
Food Access | ||||
Density of full-service grocery stores; fast food operations | General population | http://www.ers.usda.gov/data-products/foodenvironment-atlas/about-the-atlas.aspx#.VACTF2MXNkg | ||
http://www.ers.usda.gov/data-products/food-access-research-atlas/.aspx | ||||
SNAP redemption at supermarkets | General population | http://www.ers.usda.gov/topics/food-nutritionassistance/food-nutrition-assistance-research.aspx#.VACQ2mMXNkg | ||
Castner, L., and J. Henke. 2011. Benefit redemption patterns in the Supplemental Nutrition Assistance Program. Alexandria, VA: U.S. Department of Agriculture, Food and Nutrition Service, Office of Research and Analysis. |
Metric | Purpose | Target Population | How Measured | For Further Information |
Availability of farmers’ markets | http://www.ers.usda.gov/data-products/foodenvironment-atlas/about-the-atlas.aspx#.VACTF2MXNkg | |||
Food Quality | ||||
Changes in types of foods advertised | http://www.nielsen.com/content/corporate/us/en.html | |||
http://kff.org/other/food-for-thought-television-food-advertising-to | ||||
Changes in the number of healthful food offerings in food venues | ||||
Sales of organic and other sustainably produced foods | http://www.ers.usda.gov/publications/eib-economicinformation-bulletin/eib58.aspx#.U63LyqhGyTY | |||
https://www.ota.com/bookstore/14.html | ||||
http://www.nationalsustainablesales.com/research-library |
Sales of locally produced foods | http://www.usda.gov/wps/portal/usda/knowyourfarmer?navid=KNOWYOURFARMER | |||
Time spent on food preparation | http://www.bls.gov/tus/atusfaqs.htm#1 | |||
Daily energy intake from home-prepared foods | General population | http://www.ers.usda.gov/topics/food-choices-health/food-consumption-demand/food-away-from-home.aspx#.VADUsWMXNkg | ||
http://www.ers.usda.gov/data-products/food-expenditures.aspx#.VADWFGMXNkg | ||||
Percentage of people who cook | General population | http://www.bls.gov/tus/atusfaqs.htm#1 |
TABLE B-2 Selected Methodologies for Assessing Health, Environmental, Social, and Economic Effects of Food System
Name | Description | Application (scientific paper where method has been used) | For Further Information |
HEALTH EFFECTS | |||
Clinical trials | Study design that involves examining narrowly defined questions in the biomedical or behavioral fields, using an experimental design, with as much control over bias as possible | Appel, L. J., T. J. Moore, E. Obarzanek, W. M. Vollmer, L. P. Svetkey, F. M. Sacks, G. A. Bray, T. M. Vogt, J. A. Cutler, M. M. Windhauser, P. H. Lin, and N. Karanja. 1997. A clinical trial of the effects of dietary patterns on blood pressure. Dash collaborative research group. New England Journal of Medicine 336(16):1117-1124. | Gordis, L. 1996. Epidemiology. Philadelphia, PA: W.B. Saunders. |
Cohort studies | Study design in which exposures of interest are assessed at baseline in a group (cohort) of people, and health outcomes occurring over time are then related to baseline exposures | Oh, K., F. B. Hu, J. E. Manson, M. J. Stampfer, and W. C. Willett. 2005. Dietary fat intake and risk of coronary heart disease in women: 20 years of follow-up of the Nurses’ Health Study. American Journal of Epidemiology 161(7):672-679. | Gordis, L. 1996. Epidemiology. Philadelphia, PA: W.B. Saunders. |
Case-control studies | Study design that involves comparing two groups of people, those with the disease or condition under study (cases) and a very similar group of people who do | Dahm, C. C., R. H. Keogh, E. A. Spencer, D. C. Greenwood, T. J. Key, I. S. Fentiman, M. J. Shipley, E. J. Brunner, J. E. Cade, V. J. Burley, G. Mishra, A. M. Stephen, | Gordis, L. 1996. Epidemiology. Philadelphia, PA: W.B. Saunders. |
not have the disease or condition (controls) | D. Kuh, I. R. White, R. Luben, M. A. Lentjes, K. T. Khaw, and S. A. Rodwell Bingham. 2010. Dietary fiber and colorectal cancer risk: A nested case-control study using food diaries. Journal of the National Cancer Institute 102(9):614-626. | ||
Microbial risk assessment for food and water | Standardized methodology for evaluating how likely it is that human health will be impacted by pathogenic microorganisms in foods and water | Akingbade, D., N. Bauer, S. Dennis, D. Gallagher, K. Hoelzer, J. Kause, R. Pouillot, M. Silverman, and J. Tang. 2013. Draft interagency risk assessment—Listeria monocytogenes in retail delicatessens technical report. Washington, DC: U.S. Department of Agriculture Food Safety and Inspection Service. |
http://www.who.int/foodsafety/micro/jemra/en |
http://www.cdc.gov/foodsafety/microbial-risk-assessment.html | |||
Chemical risk assessment for food and water | Standardized methodology for evaluating how likely it is that human health will be impacted by chemical additives and contaminants in foods | Food and Agriculture Organization. 2014. Residue evaluation of certain veterinary drugs. FAO JECFA Monographs 15. Rome, Italy: FAO. | http://www.who.int/foodsafety/chem/en |
Name | Description | Application (scientific paper where method has been used) | For Further Information |
Health Impact Assessment | Systematic process that uses an array of data sources and analytic methods and considers input from stakeholders to determine the potential effects of a proposed policy, plan, program, or project on the health of a population and the distribution of those effects within the population; provides recommendations on monitoring and managing those effects | Health Impact Project. 2013. Health impact assessment of proposed changes to the Supplemental Nutrition Assistance Program. Washington, DC: The Pew Charitable Trusts and Robert Wood Johnson Foundation. | http://www.healthimpactproject.org |
ENVIRONMENTAL EFFECTS | |||
Ecological Risk Assessment | Standardized process for evaluating how likely it is that the environment may be impacted as a result of exposure to environmental stressors such as chemicals, land change, disease, invasive species, and climate change | Solomon, K. R., J. P. Giesy, T. W. LaPoint, J. M. Giddings, and R. P. Richards. 2013. Ecological risk assessment of atrazine in North American surface waters. Environmental Toxicology and Chemistry 32(1):10-11. | http://www.epa.gov/risk |
Environmental Assessment/Environmental Impact Statement | A detailed analysis that serves to ensure that the policies and goals defined in the National Environmental Policy Act (NEPA) of 1969 (see 40 CFR Part 6) are addressed; NEPA requires federal | http://www.healthimpactproject.org/hia/us/red-dog-mine-extensionaqqaluk-project-final-supplementalenvironmental-impact-statement | http://www.epa.ie/monitoringassessment/assessment/eia/#.Uz1ItFc9DK0 |
agencies and others using federal funds or assets to assess the environmental impacts of major federal projects or decisions such as issuing permits, spending federal money, or affecting federal lands | |||
Life cycle assessment | Methodology to assess environmental impacts associated with a product’s life from raw material to consumption, including waste disposal or recycling | Heller, M. C., and G. A. Keoleian. 2011. Life cycle energy and greenhouse gas analysis of a large-scale vertically integrated organic dairy in the united states. Environmental Science and Technology 45(5):1903-1910. | http://www.eiolca.net/Method/LCA_Primer.html Hendrickson, C. T., L. B. Lave, and H. S. Matthews. 2006. Environmental life cycle assessment of goods and services: An input–output approach. Washington, DC: Resources for the Future Press. |
Rapid Bioassessment Protocols for Use in Streams and Wadeable Rivers | Practical technical reference for conducting cost-effective biological assessments of lotic systems | Jack, J., R. H. Kelley, and D. Stiles. 2006. Using stream bioassessment protocols to monitor impacts of a confined swine operation. Journal of the American Water Resources Association 42(3):747-753. | http://water.epa.gov/scitech/monitoring/rsl/bioassessment |
Name | Description | Application (scientific paper where method has been used) | For Further Information | |
SOCIAL AND ECONOMIC EFFECTS | ||||
Social Impact Assessment | Processes of analyzing, monitoring, and managing the intended and unintended social consequences, both positive and negative, of planned interventions and any social change processes invoked by those interventions; primarily used outside of the United States | Mahmoudi, H., O. Renn, F. Vanclay, V. Hoffmann, and E. Karami. 2013. A framework for combining social impact assessment and risk assessment. Environmental Impact Assessment Review 43:1-8. | http://www.nmfs.noaa.gov/sfa/reg_svcs/social_impact_assess.htm | |
Benefit–cost analysis | Method to calculate a monetary measure of the aggregate change in individual well-being resulting from a project or a policy decision | Roberts, T., J. C. Buzby, and M. Ollinger. 1996. Using benefit and cost information to evaluate a food safety regulation: HACCP for meat and poultry. American Journal of Agricultural Economics 78(5):1297-1301. | http://evans.uw.edu/centers-projects/bcac/benefit-cost-analysis-center | |
Boardman, A.E., D.H. Greenberg, A.R. Vining, and D.L. Weimer. 2011. Cost-benefit analysis: Concepts and practice, 4th ed. Upper Saddle River, NJ: Prentice-Hall. | ||||
Cost-effectiveness analysis | Methodology to compare the relative costs and outcomes (effects) from a project or a policy decision; cost-effectiveness analysis is distinct from benefit–cost analysis, which assigns a monetary value to the measure of effect | Sacks, G., J. L. Veerman, M. Moodie, and B. Swinburn. 2011. “Traffic-light” nutrition labelling and “junk-food” tax: A modelled comparison of cost-effectiveness for obesity prevention. International Journal of Obesity 35(7):1001-1009. | Drummond, M. F., M. J. Sculpher, G. W. Torrance, B. J. O’Brien, and G. L. Stoddart. 2005. Methods for the economic evaluation of health care programmes. Oxford, UK: Oxford University Press. |
Gold, M. R., J. E. Siegel, L. B. Russe and M. C. Weinstein. 1996. Cost-effectiveness in health and medicine. New York: Oxford University Press. | |||
Computable General Equilibrium | Method for measuring economic welfare changes due to market price and quantity feedbacks in response to changes in policy, technology, or another exogenous variable (e.g., climate) | Hertel, T. W., A. A. Golub, A. D. Jones, M. O’Hare, R. J. Plevin, and D. M. Kammen. 2010. Effects of US maize ethanol on global land use and greenhouse gas emissions: Estimating market-mediated responses. BioScience 60(3):223-231. | http://www.iadb.org/en/topics/trade/understanding-a-computable-general-equilibrium-model,1283.html |
Total Factor Productivity Analysis | Index of the economic factors that contribute to growth in productivity (e.g., of agriculture) | Ball, V. E., C. A. K. Lovell, H. Luu, and R. Nehring. 2004. Incorporating environmental impacts in the measurement of agricultural productivity growth. Journal of Agricultural and Resource Economics 29(3):436-460. | http://www.ers.usda.gov/data-produc/agricultural-productivity-in-the-us/findings,-documentation,-and-method.aspx#.U1qm5aIeCdc |
Non-market valuation | Method for placing monetary values on changes in levels of goods and services that lack markets, including health and environmental effects | Champ, P. A., K. J. Boyle, and T. C. Brown. 2003. A primer on nonmarket valuation. Dordrecht, The Netherlands: Kluwer Academic Publishers. |
Name | Description | Application (scientific paper where method has been used) | For Further Information |
Agent-based modeling | Methods for simulating the actions and interactions of individuals, organizations, and groups to assess their affects on the whole system | See Table B-4 on selected models. | http://www2.econ.iastate.edu/tesfatsi/abmread.htm Epstein, J. M. 2006. Generative social science. Princeton, NJ: Princeton University Press. |
Systems dynamics modeling | Methods for simulating key dynamic stocks and flows, and key feedback cycles in operation within a system, to provide quantitative estimates of the potential system response to changes | Sterman, J. M. 2006. Learning from evidence in a complex world. American Journal of Public Health 96(3):505-514. | Sterman, J. M. 2000. Business dynamics: Systems thinking for a complex world. Boston, MA: Irwin/McGraw-Hill. |
Food demand analysis/time series | To study the food demand response to prices, total expenditures, and other economic factors | Huang, K. S., and R. C. Haidacher. 1983. Estimation of a composite food demand system for the United States. Journal of Business & Economic Statistics 1(4):285-291. |
Food demand analysis/cross-sectional analysis | Food consumption by individual household units is regressed on prices, income, and household characteristics to determine how demand varies by household characteristics; it allows for the incorporation of behavior and household environmental characteristics in the analysis | Okrent, A., and J. M. Alston. 2012. The demand for disaggregated food-away-from-home and food-at-home products in the United States. Economic Research Report No. ERR-139. Washington, DC: U.S. Department of Agriculture, Economic Research Service. | |
NOTE: Additional resources:
National Collaborative on Childhood Obesity’s Catalogue of Surveillance Systems: http://nccor.org/projects/catalogue/index.php (accessed May 21, 2015).
National Collaborative on Childhood Obesity’s Measures Registry: http://nccor.org/projects/measures/index.php (accessed May 21, 2015).
TABLE B-3 Selected Data Sources for Assessing Health, Environmental, Social, and Economic Effects of Food System
Purpose | Target Population | Key Assessments | For Further Information | |
HEALTH EFFECTS | ||||
National Health and Nutrition Examination Survey | Collect data about the health, nutritional status, and health behaviors of individuals in the United States | Civilian, non-institutionalized individuals in the United States; all ages |
|
http://www.cdc.gov/nchs/nhanes.htm |
Behavioral Risk Factor Surveillance System | Collect state-specific data about preventive health practices and risk behaviors linked to chronic disease, injuries, and preventable infectious disease for adults in the United States | Adults living in households in all 50 states, the District of Columbia, Puerto Rico, the U.S. Virgin Islands, and Guam |
|
http://www.cdc.gov/BRFSS |
Health and Diet Survey | Collect data about awareness, attitudes, and practices related to health and diet issues among consumers in the United States | Civilian, non-institutionalized adults age 18 and older in 50 states and the District of Columbia |
|
http://www.fda.gov/Food/FoodScienceResearch/ConsumerBehaviorResearch/default.htm |
|
||||
National Vital Statistics System | Collect data about births and deaths for individuals in the United States | Individuals in all 50 states, New York City, the District of Columbia, Puerto Rico, the U.S. Virgin Islands, Guam, American Samoa, and the Northern Mariana Islands |
|
http://www.cdc.gov/nchs/nvss.htm |
Food Patterns Equivalents Database | Convert foods and beverages to U.S. Department of Agriculture (USDA) Food Patterns components in order to characterize many kinds of foods and beverages reported in surveys and other types of studies into components that are relevant to dietary analysis and guidance | Foods reported on the 24-hour recalls in What We Eat in America portion of the National Health and Nutrition Examination Survey |
|
http://www.ars.usda.gov/Services/docs.htm?docid=23871 |
Purpose | Target Population | Key Assessments | For Further Information | |
Foodborne Diseases Active Surveillance Network | Outbreak data from active surveillance in 10 sentinel sites across the United States | 10 sentinel sites (Connecticut, Georgia, Maryland, Minnesota, New Mexico, Oregon, Tennessee, and certain counties in California, Colorado, and New York), FDA and USDAFSIS (Food Safety and Inspection Service); the information collected is used to estimate the burden of illness caused by the specific agent; breaks down estimates by age category and regions | Tracks foodborne illness from the most common agents: Campylobacter, Listeria, Salmonella, Shiga toxin-producing Escherichia coli, Shigella, Vibrio and Yersinia, and the parasites Cryptosporidium and Cyclospora | http://www.cdc.gov/foodnet/data/trends/index.html |
Foodborne Outbreak Online Database | Provide access to national information on reported foodborne illness outbreak data | Outbreaks reported by state, local, and territorial public health departments through a Web-based program, the National Outbreak Reporting System |
|
http://wwwn.cdc.gov/foodborneoutbreaks |
Estimates of Foodborne Illness Attribution | Estimate the most common food sources for specific foodborne illnesses | General population |
|
http://www.cdc.gov/foodborneburden/attribution/index.html |
Risk and Safety Assessments for Food | Site contains formal microbial and chemical risk assessments conducted for foods | General population | http://www.fda.gov/Food/FoodScienceResearch/RiskSafetyAssessment/default.htm | |
National Antimicrobial Resistance Monitoring System | Monitor changes in susceptibility of select bacteria to antimicrobial agents of human and veterinary importance | Foodborne isolates collected from humans, animals, and retail meats | Antimicrobial resistance | http://www.cdc.gov/narms |
Pesticide Data Program | Collect pesticide residue data | Meat, poultry, and egg products | Pesticide residues | http://www.ams.usda.gov/AMSv1.0/PDP |
Total Diet Study | Ongoing market-based study to collect data on levels of contaminants and nutrients in foods | 280 core foods in retail stores | Contaminants in foods (e.g., acrylamide and perchlorate) | http://www.fda.gov/food/foodscienceresearch/totaldietstudy/default.htm |
Registration and chemical-specific information | Information about pesticides | Pesticides | Toxicity, use patterns, and registration status | http://www.epa.gov/pesticides/food/risks.htm |
Purpose | Target Population | Key Assessments | For Further Information | |
ENVIRONMENTAL EFFECTS | ||||
National Water Information System | Collect the occurrence, quantity, quality, distribution, and movement of surface and groundwater; analyzes the chemical, physical, and biological properties of water, sediment, and tissue samples from across the United States | Water-resources data collected at approximately 1.5 million sites in all 50 U.S. states, the District of Columbia, Puerto Rico, the U.S. Virgin Islands, Guam, American Samoa, and the Commonwealth of the Northern Mariana Islands |
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http://waterdata.usgs.gov/nwis http://water.usgs.gov/owq/data.html |
Air Quality System | Repository of ambient air quality data | Data collected by Environmental Protection Agency and state, local, and tribal air pollution control agencies in the United States from more than 10,000 monitors, 5,000 of which are currently active |
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http://www.epa.gov/ttn/airs/airsaqs |
ECOTOX Database | Provide single-chemical toxicity information for aquatic life, terrestrial plants, and wildlife | Toxicity data derived predominately from the peer-reviewed literature, for aquatic life, terrestrial plants, and terrestrial wildlife |
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http://cfpub.epa.gov/ecotox |
Farm Financial and Crop Production Practices | Collect information on the financial condition, production practices, and resource use of America’s farm businesses and rural households | National survey of agricultural producers that provides observations of field-level farm practices, the economics of the farm businesses, and the characteristics of farm operators | Data on nutrient use, pesticide use, conservation practices, pest management practices, irrigation technology and water use, etc., for select crops and U.S. states | http://www.ers.usda.gov/dataproducts/arms-farm-financial-and-crop-production-practices |
Purpose | Target Population | Key Assessments | For Further Information | |
Geospatial Data Gateway | Provide a gateway to available geospatial environmental and natural resources data | Provides geospatial data produced or financed by USDA Service Center Agencies to any user; data outside these parameters is only available to USDA personnel |
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http://datagateway.nrcs.usda.gov |
CropScape | Collect data about crop-specific and nonagricultural land cover in the United States | Farms within the contiguous continental United States |
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http://nassgeodata.gmu.edu/CropScape |
Annual Agricultural Statistics | Collect data about the production, economics, and demographics of agriculture and its environment in the United States | Agricultural statistics in 50 U.S. states and the District of Columbia |
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http://www.nass.usda.gov/Surveys/index.asp |
Pesticide Data Program | Collect data about pesticide residues in food commodities and drinking water in the United States | More than 105 different commodities, including fresh and processed fruits and vegetables, meat and poultry, grains, specialty products, bottled water, municipal drinking water, and private and school/childcare facility well water |
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http://www.ams.usda.gov/AMSv1.0/pdp |
Quantis World Food life cycle assessments (LCAs) database | Provide reliable and up-to-date data for more accurate food and beverage LCAs, decisions, and communication. (Private, proprietary data.) | Reliable, transparent, and up-to-date database for environmental assessments, including more than 200 datasets within 10 categories |
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http://www.quantis-intl.com/wfldb |
Purpose | Target Population | Key Assessments | For Further Information | |
SOCIAL AND ECONOMIC EFFECTS | ||||
Consumer Expenditure Survey | Collect data about buying habits (e.g., food expenditures), income, and other characteristics of households in the United States | Households and families (referred to as “consumer units”) |
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http://www.bls.gov/cex |
Center for Nutrition Policy and Promotion Food Prices Database | Collect data about estimated cost of specific food items consumed in the United States | Food items that were purchased by individuals and families in the 48 contiguous states and the District of Columbia |
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http://www.cnpp.usda.gov/usdafoodplanscostoffood.htm |
Agricultural and food economic data | Data about U.S. and foreign agricultural prices, costs, inputs, production levels, incomes, and environmental effects | U.S. agriculture and food |
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http://www.ers.usda.gov/dataproducts.aspx |
http://www.nass.usda.gov/Surveys/index.asp |
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Census of Agriculture | Collect data about production, sales, agricultural practices, and sales practices for farms, ranches, and the people who operate them in the United States and its territories | Farms, ranches, and their operators in all 50 states and territories, including American Samoa, Puerto Rico, Commonwealth of the Northern Mariana Islands, Guam, and the U.S. Virgin Islands |
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http://www.agcensus.usda.gov |
Purpose | Target Population | Key Assessments | For Further Information | |
InfoUSA | Collect data about types of businesses in a community in the United States | Businesses and consumers in the United States and Canada |
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http://www.infousa.com |
National Survey of America’s Families | Collect data on demographic, economic, housing, and other factors relevant to the well-being of children and adults younger than age 65 residing in households in the United States | Noninstitutionalized, civilian population younger than age 65 in the United States; the survey focuses on individuals residing in households with incomes below 200 percent of the federal poverty threshold |
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http://www.urban.org/center/anf/nsaf.cfm |
Food Environment Atlas | Assemble statistics on food environment indicators to stimulate research on the determinants of food choices and diet quality, and to provide a spatial overview of a community’s ability to access healthy food and its success in doing so | Counties in the United States |
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http://www.ers.usda.gov/dataproducts/food-environment-atlas/about-the-atlas.aspx |
Household Food Security Survey Module | Assess food security within a household over the past 30 days or past 12 months | Households | 18 items on food situation within the household, ranging in severity from worry about running out of food to adults and children going a whole day without food because of lack of financial resources; three-stage design with screeners | http://www.ers.usda.gov/topics/food-nutritionassistance/food-security-in-the-us/survey-tools.aspx#household |
Food Availability (per capita) Data System | Collect estimated data regarding foods, nutrients, and calories available for consumption for each individual in the United States | Commodity foods and nutrients available for consumption in the United States |
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http://www.ers.usda.gov/dataproducts/food-availability-(per-capita)-data-system.aspx |
Purpose | Target Population | Key Assessments | For Further Information | |
Quarterly Food-at-Home Price Database | Provide estimates of average market-level prices for more than 50 food groups in the United States | U.S. households in the 48 contiguous states |
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http://www.ers.usda.gov/dataproducts/quarterly-food-at-home-price-database.aspx |
Food consumption and nutrient intake | Food consumption and nutrient intake by food source and demographic characteristics | U.S. households in the 48 contiguous states |
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http://www.ers.usda.gov/dataproducts/food-consumption-and-nutrient-intakes.aspx |
Gladson Nutrition Database | Collect data about ingredient content and nutrition labels for packaged food and beverage products sold in the United States | Food products sold in the United States |
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http://www.gladson.com/SERVICES/NutritionDatabase/tabid/89/Default.aspx |
MenuStat | Collect nutrition data about menu items in the largest restaurant chains in the United States | Menu items from the largest chain restaurants in the United States |
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http://menustat.org/about |
Datamonitor Product Launch Analytics | Collect data about newly launched consumer packaged goods in retail markets around the world | Newly launched consumer packaged goods from around the world |
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http://www.productscan.com |
Purpose | Target Population | Key Assessments | For Further Information | |
Absolute difference in health disparities | Measure of absolute difference in health outcome among groups | Individuals and subgroups in a population | Health parameter measured in group A/Health parameter measured in group B | http://seer.cancer.gov/publications/disparities2 |
Relative difference in health disparities | Measure of relative difference in health outcome among groups | Individuals and subgroups in a population | Health parameter measured in group A/Health parameter measured in group B | http://seer.cancer.gov/publications/disparities2 |
Census of Fatal Occupational Injuries | Produce comprehensive, accurate, and timely annual counts of occupational injury fatalities | All fatal work injuries in the United States | Uses multiple data sources including death certificates, workers’ compensation reports, and federal and state agency administrative reports to collect information on each workplace fatality | http://www.bls.gov/iif/oshcfoi1.htm |
Survey of Occupational Injuries and Illnesses | Describe the magnitude of work-related injury and illnesses that are recordable, i.e., require at least 1 day away from work to recuperate | Data on nonfatal workplace injuries and illnesses from an annual survey of roughly 250,000 private employers, state governments, and local governments | Includes information about the case circumstances and worker characteristics for occupational injury and illnesses that involve lost work time, medical treatment other than first aid, restriction of work or motion, loss of consciousness, or | http://www.bls.gov/iif/oshcase1.htm |
transfer to another job; employers keep counts of injuries separate from illnesses | ||||
Occupational Injury Surveillance of Production Agriculture Survey | Track nonfatal injuries occurring to adults working in agriculture | National surveillance system conducted in 2001, 2004, and 2009 | Designed to produce national and regional estimates of the number of adults age 20 years and older working on farms and the number of occupational injuries that these workers incur | http://www.cdc.gov/niosh/topics/aginjury/OISPA/default.html |
County Sprawl Index | A measure of urban sprawl, a pattern of land use epitomized by low-density development around urban areas | Counties in the United States | This updated sprawl index for 2000 and 2010 incorporates four dimensions of sprawl derived from 17 variables—density, land-use mix, population or employment concentrations (“centering”), and street characteristics; principal components analysis was used to extract factors from each of these dimensions and these were combined into a single index | http://gis.cancer.gov/tools/urban-sprawl |
TABLE B-4 Selected Models for Assessing Health, Environmental, Social, and Economic Effects of Food System
Name | Description | Application (scientific paper where method has been used) | For More Information |
HEALTH EFFECTS | |||
PMP (Pathogen Modeling Program) | Predict growth or inactivation of selected foodborne pathogens under different conditions, including temperature, water activity, pH, and other parameters | Numerous references available on the website provided in this table | http://pmp.errc.ars.usda.gov/PMPOnline.aspx |
ENVIRONMENTAL EFFECTS | |||
RUSLE2 (Revised Universal Soil Loss Equation) | Predict rill and interrill erosion in response to runoff; based on climate, soil, topography, and management practices | Schipanski, M. E., M. Barbercheck, M. R. Douglas, D. M. Finney, K. Haider, J. P. Kaye, A. R. Kemanian, D. A. Mortensen, M. R. Ryan, J. Tooker, and C. White. 2014. A framework for evaluating ecosystem services provided by cover crops in agroecosystems. Agricultural Systems 125:12-22. | http://www.nrcs.usda.gov/wps/portal/nrcs/main/national/technical/tools/rusle2 |
http://www.ars.usda.gov/Research/docs.htm?docid=24403 | |||
WEPS (Wind Erosion Prediction System) | Predict wind erosion | Van Donk, S. J., and E. L. Skidmore. 2003. Measurement and simulation of wind erosion, roughness degradation and residue decomposition on an agricultural field. Earth Surface Processes and Landforms 28(11):1243-1258. | http://www.nrcs.usda.gov/wps/portal/nrcs/main/national/technical/tools/weps |
GLEAMS (Groundwater Loading Effects on Agricultural Management Systems) | Evaluate the effects of agricultural practices on the movement of chemicals within and through the plant root zone | Bosch, D. J., M. L. Wolfe, and K. E. Knowlton. 2006. Reducing phosphorus runoff from dairy farms. Journal of Environmental Quality 35(3):918-927. | http://www.tifton.uga.edu/sewrl/Gleams/gleams_y2k_update.htm |
WATSUIT (Water Suitability Determination Model) | Steady-state computer model to predict soil water salinity and sodicity under a particular irrigation water of given composition and leaching fraction | Visconti, F., J. M. de Paz, J. L. Rubio, and J. Sanchez. 2012. Comparison of four steady-state models of increasing complexity for assessing the leaching requirement in agricultural salt-threatened soils. Spanish Journal of Agricultural Research 10(1):222-237. | http://www.xuan-wu.com/2012-03-10-Watsuit |
HYDRUS-1D | Microsoft Windows–based modeling environment for analysis of water flow and solute transport in variably saturated porous media | Shouse, P. J., J. E. Ayars, and J. Simunek. 2011. Simulating root water uptake from a shallow saline groundwater resource. Agricultural Water Management 98(5):784-790. | http://www.ars.usda.gov/Services/docs.htm?docid=8921 |
ENVIRO-GRO | Simulate subsurface variably saturated water flow, solute transport, root water uptake, nitrogen uptake, and relative yield for agricultural applications | Letey, J., and P. Vaughan. 2013. Soil type, crop and irrigation technique affect nitrogen leaching to groundwater. California Agriculture 67(4):231-241. | http://ciwr.ucanr.edu/Tools/ENVIRO-GRO |
Name | Description | Application (scientific paper where method has been used) | For More Information |
EPIC (Environmental Policy Integrated Climate) | Simulate growth of approximately 80 crops using weather data. It predicts effects of management decisions on soil, water, nutrient, and pesticide movements, and their combined impact on soil loss, water quality, and crop yields for areas with homogeneous soils and management | Williams, J. R., C. A. Jones, J. R. Kiniry, and D. A. Spanel. 1989. The epic crop growth-model. Transactions of the ASAE 32(2):497-511. | http://epicapex.tamu.edu/epic |
Gassman, P. W., J. R. Williams, V. W. Benson, R. C. Izaurralde, L. M. Hauck, C. A. Jones, J. R. Atwood, J. R. Kiniry, and J. D. Flowers. 2005. Historical development and applications of the EPIC and APEX models. Working paper 05-WP 397. Ames, IA: Center for Agriculture and Rural Development, Iowa State University. | |||
CENTURY and DAYCENT models | CENTURY is a general model of plant–soil nutrient cycling that is being used to simulate carbon and nutrient dynamics for different types of ecosystems, including grasslands, agricultural lands, forests, and savannas; DAYCENT is the daily time-step version | Parton, W. J., D. S. Schimel, C. V. Cole, and D. S. Ojima. 1987. Analysis of factors controlling soil organic-matter levels in Great-Plains grasslands. Soil Science Society of America Journal 51(5):1173-1179. | http://www.nrel.colostate.edu/projects/daycent |
https://www.nrel.colostate.edu/projects/century5 |
SWAT (Soil and Water Assessment Tool) | Small watershed to river basin-scale model to simulate soil erosion prevention and control, non-point source pollution control, and regional management in watersheds | Gassman, P. W., M. R. Reyes, C. H. Green, and J. G. Arnold. 2007. The soil and water assessment tool: Historical development, applications, and future research directions. Transactions of the ASABE 50(4):1211-1250. | http://swat.tamu.edu |
GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation Model) | Life cycle model of greenhouse gas emissions in the transportation sector developed to fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels, and the vehicle cycle through material recovery and vehicle disposal need to be considered | Wang, M., J. Han, J. B. Dunn, H. Cai, and A. Elgowainy. 2012. Well-to-wheels energy use and greenhouse gas emissions of ethanol from corn, sugarcane and cellulosic biomass for US use. Environmental Research Letters 7(4):1-13. | https://greet.es.anl.gov |
https://greet.es.anl.gov/greet/documentation.html | |||
EIO-LCA (Economic Input-Output Life Cycle Assessment) | Estimates the materials and energy resources required for, and the environmental emissions resulting from, activities in our economy | Hendrickson, C. T., L. B. Lave, and H. S. Matthews. 2006. Environmental life cycle assessment of goods and service: An input–output approach. Washington, DC: Resources for the Future Press. | http://www.eiolca.net |
Name | Description | Application (scientific paper where method has been used) | For More Information |
SOCIAL AND ECONOMIC EFFECTS | |||
Global Trade Analysis Project (GTAP) | Multiregion, multisector, computable general equilibrium model, with perfect competition and constant returns to scale. The GTAP-E model estimates greenhouse gas effects related to international trade. The focus is on market and environmental effects of economic growth, policy changes, and changes in resource availability | Hertel, T. W., W. E. Tyner, and D. K. Birur. 2010. The global impacts of biofuel mandates. Energy Journal 31(1):75-100. | https://www.gtap.agecon.purdue.edu/about/getting_started.asp https://www.gtap.agecon.purdue.edu/products/gtap_book.asp |
IMPACT Model | Computable general equilibrium model designed to examine alternative futures for global food supply, demand, trade, prices, and food security, along with bioenergy, climate change, water, changing diet/food preferences, and other themes | Rosegrant, M. W., M. Agcaoili-Sombilla, and N. D. Perez. 1995. Global Food Projections to 2020: Implications for Investment. 2020 Discussion Paper No. 5. Washington, DC: International Food Policy Research Institute. | http://www.ifpri.org/book-751/ourwork/program/impact-model http://www.ifpri.org/sites/default/files/publications/impactwater2012.pdf |
FASOM-GHG (Forestry and Agricultural Sector Optimization Model with Greenhouse Gases Model) | Dynamic partial-equilibrium sectoral model used to simulate potential future impacts of policies on land use, GHG fluxes, and commodity markets within the agricultural and forestry sectors | Schneider, U. A., B. A. McCarl, and E. Schmid. 2007. Agricultural sector analysis on greenhouse gas mitigation in US agriculture and forestry. Agricultural Systems 94(2):128-140. | http://www.epa.gov/climatechange/EPAactivities/economics/modeling/peerreview_FASOM.html http://agecon2.tamu.edu/people/faculty/mccarl-bruce/FASOM.html |
FAPRI (Food and Agricultural Policy Research Institute) | Develops projections for the U.S. agricultural sector and international commodity markets using comprehensive data and computer modeling systems of the world agricultural market | Meyers, W. H., P. Westhoff, J. F. Fabiosa, and D. J. Hayes. 2010. The FAPRI global modeling system and outlook process. Journal of International Agricultural Trade and Development 6(1):1-20. | http://www.fapri.org |
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