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LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

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Page 1: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon

Estimating Percent Meeting Fruit & Vegetable Recommendations

from BRFSS data

Page 2: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

These next questions are about the foods you usually eat or drink. Please tell me how often you eat or drink each one, for example, twice a week, three times a month, and so forth. Remember, I am only interested in the foods you eat. Include all foods you eat, both at home and away from home.

1) How often do you drink fruit juices such as orange, grapefruit, or tomato? 2) Not counting juice, how often do you eat fruit? 3) How often do you eat green salad? 4) How often do you eat potatoes not including French fries, fried potatoes, or potato chips? 5) How often do you eat carrots? 6) Not counting carrots, potatoes, or salad, how many servings of vegetables do you usually eat?

BRFSS FV Screener (1994-2009)

Page 3: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Revised FV Screener (2011-)

Page 4: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Healthy People – Food and Nutrition Consumption objectives

Healthy People 2010• ≥2 servings of fruit (target of 75%)• ≥3 servings of vegetables (target of 50%)

Healthy People 2020• Increase the contribution of fruits to the diets of the population

aged 2 years and older from 0.5 cup equivalents per 1,000 calories to 0.9 cup equivalents per 1,000 calories.

 • Increase the variety and contribution of vegetables to the diets

of the population aged 2 years and older from 0.8 cup equivalents per 1,000 calories to 1.1 cup equivalents per 1,000 calories.

Page 5: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Median fruit intake (times/day) Median vegetable intake (times/day) Percent meeting minimum recommendations

for fruit intake (age- & sex-specific) Percent meeting minimum recommendations

for vegetable intake (age- & sex-specific)

Proposed Fruit &Vegetable Indicators

Page 6: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Proposed Fruit &Vegetable Indicators

• Percent meeting minimum

recommendations requires 2 parts

– Developing linear equations to convert

BRFSS times per day into cup equivalents

– Comparing estimated cup equivalents against

minimum fruit and vegetable intake

recommendations based on Dietary

Guidelines

Page 7: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Part 1: Developing linear equations to convert BRFSS times per day into cup equivalents

• NCI developed a protocol for converting times per day into cup equivalents*

• Four steps– Develop a food coding scheme to aggregate 24

hr recall foods into food groups that parallel screener questions

– Estimate mentions: # times each food group mentioned

– Estimate portion sizes: median amount consumed, when a food group was eaten

– Model cup equivalents by portion sizes x mentions to get the conversion equation

*Available at http://appliedresearch.cancer.gov/surveys/chis/dietscreener/scoring.html

Page 8: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

NCI equation for converting times per day into cup equivalents

• E(Fruits and Vegetables1/2) = β0 + β1(NFG1P1 + NFG2P2 + ... + NFGkPk)1/2

• Independent variable: mentions x portion sizes of food groups

• Dependent variable: cup equivalents of fruits and vegetables from all sources

• Where:– k = 6 mutually exclusive fruit and vegetable food groups (NCI: 100% fruit

juice, Fruit, Salad, Fried potatoes, Other white potatoes, Dried beans, Other vegetables)

– NFGk = number of times/mentions per day a participant consumed food group k

– Pk = estimated median age- and sex-specific portion sizes for each food group k (cup equivalents)

• E(Fruits and Vegetables1/2) = β0 + β1(NFG1P1 + NFG2P2 + ... + NFGkPk)1/2

– Estimates from NHANES and above equation

– BRFSS times per day

Page 9: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Recalculation Rationale

• Portion sizes may have changed over time– NCI used 1994-96 Continuing Survey of Food Intakes of

Individuals dietary recall data

– DNPAO using 24 hour dietary recall data from 2003-2004 NHANES

• 7 NCI food groups ≠ 2011 6 BRFSS questions• Need estimates for fruit alone and vegetable alone as

well as combined• Portion sizes are age and sex specific but other

important sociodemographic variation to consider (race/ethnicity, socioeconomic status, etc.)

Page 10: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Step 1:Develop food coding scheme and estimate cup equivalents

• Scheme must– Be consistent with BRFSS 2011 questions– Have extensive documentation/rationale for transparency

• My Pyramid Equivalents Database (MPED) food groups– MPED translates the amounts of foods eaten in NHANES

into the number of cup equivalents– 32 MyPyramid major groups and subgroups– extensively documented – correlate well with 2011 BRFSS items except for other

vegetables

Page 11: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Cup equivalents

Day Description Fruit juice Fruit LegumesDark-green vegetables

Orange vegetables

All vegetables

excl legumes1 White potato, chips 0 0 0 0 0 0.8821 Potato salad with egg 0 0 0 0 0 0.513381 Fruit drink 0.23328 0 0 0 0 01 Fruit drink 0.23328 0 0 0 0 02 White potato, french fries 0 0 0 0 0 0.378192 Tomatoes, raw 0 0 0 0 0 0.22242 Tomatoes, raw 0 0 0 0 0 0.11122 Tomato catsup 0 0 0 0 0 0.042452 Tomato catsup 0 0 0 0 0 0.08492 Lettuce, raw 0 0 0 0 0 0.04692 Lettuce, raw 0 0 0 0 0 0.072722 Onions, mature, raw 0 0 0 0 0 0.06252 Onions, mature, raw 0 0 0 0 0 0.0752 Cucumber pickles, dill 0 0 0 0 0 0.08388

Fruit and vegetable food records of participant 21005 (n=14/42; ~ 3 cup equivalents of FV)

Page 12: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Cup equivalents

Day Description Fruit juice Fruit LegumesDark-green vegetables

Orange vegetables

All vegetables

excl legumes1 White potato, chips 0 0 0 0 0 0.8821 Potato salad with egg 0 0 0 0 0 0.513381 Fruit drink 0.23328 0 0 0 0 01 Fruit drink 0.23328 0 0 0 0 02 White potato, french fries 0 0 0 0 0 0.378192 Tomatoes, raw 0 0 0 0 0 0.22242 Tomatoes, raw 0 0 0 0 0 0.11122 Tomato catsup 0 0 0 0 0 0.042452 Tomato catsup 0 0 0 0 0 0.08492 Lettuce, raw 0 0 0 0 0 0.04692 Lettuce, raw 0 0 0 0 0 0.072722 Onions, mature, raw 0 0 0 0 0 0.06252 Onions, mature, raw 0 0 0 0 0 0.0752 Cucumber pickles, dill 0 0 0 0 0 0.08388

Fruit and vegetable food records of participant 21005 (n=14/42; ~ 0.75 cup equivalents of FV)

Page 13: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Step 1:Develop food coding scheme

• MPED Con’td– No corresponding aggregation scheme to say what

food should count– Does not help distinguish what is typically reported in

a screener• USDA Food Survey Research Group (FSRG)

defined groups – has extensive documentation – Consistent with 2011 BRFSS categories– FSRG aggregates foods based on main ingredients;

Ex. fruit juice in canned fruit does not count towards total fruit juice

Page 14: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Step 1:Develop food coding scheme• Each 7,174 different types of food NHANES participants report assigned 8 digit

food code

• Certain foods excluded from groups to make consistent with BRFSS screener • Baby foods• Dried fruit • Condiments • Fruits and vegetables on sandwiches (lettuce, tomato onion)

Page 15: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Food coding scheme for aggregating foods from NHANES 2003-04 into BRFSS 2011 comparable categories

2011 BRFSS Question USDA FSRG variables

Corresponding FSRG 8 Digit Food Codes*

1. During the past month, how many times per day, week or month did you drink 100% PURE fruit juices? Do not include fruit-flavored drinks with added sugar or fruit juice you made at home and added sugar to. Only include 100% juice. (FRUIT JUICE)

FRUIT11 + FRUIT35

(611 or 612 01- 612 13 or 612 16) + (612 0050 or 612 14 or 612 19-612 26 or 641 0011-642 2101)

*Online search tool for USDA food codes : http://www.ars.usda.gov/services/docs.htm?docid=17032

Page 16: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data
Page 17: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Step 1:Develop food coding scheme

• MPED should be used in conjunction with FSRG

• For each NHANES participant– Each food eaten disaggregated

– Only foods classified as one of the 6 FSRG food groups contributes to mentions & portion sizes (independent variables)

– All foods except fried potatoes and non 100% fruit juice contribute cup equivalents (dependent variables)

Page 18: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Cup equivalents

Day Description Fruit juice Fruit LegumesDark-green vegetables

Orange vegetables

All vegetables

excl legumes1 White potato, chips 0 0 0 0 0 0.8821 Potato salad with egg 0 0 0 0 0 0.513381 Fruit drink 0.23328 0 0 0 0 01 Fruit drink 0.23328 0 0 0 0 02 White potato, french fries 0 0 0 0 0 0.378192 Tomatoes, raw 0 0 0 0 0 0.22242 Tomatoes, raw 0 0 0 0 0 0.11122 Tomato catsup 0 0 0 0 0 0.042452 Tomato catsup 0 0 0 0 0 0.08492 Lettuce, raw 0 0 0 0 0 0.04692 Lettuce, raw 0 0 0 0 0 0.072722 Onions, mature, raw 0 0 0 0 0 0.06252 Onions, mature, raw 0 0 0 0 0 0.0752 Cucumber pickles, dill 0 0 0 0 0 0.08388

Fruit and vegetable food records of participant 21005 (n=14/42)

Page 19: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Cup equivalents

Day Description Fruit juice Fruit LegumesDark-green vegetables

Orange vegetables

All vegetables

excl legumes1 Potato salad with egg 0 0 0 0 0 0.513382 Tomatoes, raw 0 0 0 0 0 0.2224

Fruit and vegetable food records of participant 21005 (n=2/42)

Page 20: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Step 2: Estimate mentions per day (NFGk)

• Count the number of times each fruit and

vegetable group mentioned in 24 hr recall

data

• No minimum threshold to count as a mention

• Sum times per day each BRFSS food group

mentioned and average over 2 days

Page 21: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Cup equivalents

Day Description Fruit juice Fruit LegumesDark-green vegetables

Orange vegetables

All vegetables

excl legumes1 Potato salad with egg 0 0 0 0 0 0.513382 Tomatoes, raw 0 0 0 0 0 0.2224

Fruit and vegetable food records of participant 21005 (n=2/42)

Page 22: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Mentions

Day Description Fruit juice Fruit LegumesDark-green vegetables

Orange vegetables

All vegetables

excl legumes1 Potato salad with egg 0 0 0 0 0 12 Tomatoes, raw 0 0 0 0 0 1

Total 0 0 0 0 0 2

Fruit and vegetable food records of participant 21005 (n=2/42)

1 mention per day

Page 23: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Step 3: Estimate portion sizes (Pk)

• When participants ate a food group, what was median amount eaten?

• Portion size = Total amount eaten (cup equivalents) of each food group / number of times each food group was mentioned

• Explore variation in portion sizes by various demographic characteristics– Age groups

– Race/ethnicity

– Socioeconomic status

– Others

Page 24: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Median portion sizes (Pk)*

Food groupSelected Demographic Characteristics Legumes Other vegetables

Sex

Male 0.74996 1.31522

Female 0.50018 1.312

Race/Ethnicity

Non-Hispanic White 0.50003 1.52617

Non-Hispanic Black 0.56238 1.04206

Mexican American 0.75027 0.99242

Other Hispanic 0.75 1.06501

Other Race 0.32258 1.45222

*For illustration purposes only

Page 25: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Conversion equation

• E(Fruits and Vegetables1/2) = β0 + β1(NFG1P1 + NFG2P2 + ... + NFGkPk)1/2

– Estimates from NHANES and above equation

– BRFSS times per day

• Where:– k = 6 mutually exclusive fruit and vegetable food groups (NCI: 100% fruit

juice, Fruit, Salad, Fried potatoes, Other white potatoes, Dried beans, Other vegetables)

– NFGk = number of times/mentions per day a participant consumed food group k

– Pk = estimated median age- and sex-specific portion sizes for each food group k (cup equivalents)

Page 26: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Proposed Fruit &Vegetable Indicators

• Percent meeting minimum

recommendations requires 2 parts

– Developing linear equations to convert

BRFSS times per day into cup equivalents

– Comparing estimated cup equivalents against

minimum fruit and vegetable intake

recommendations based on Dietary

Guidelines

Page 27: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Step 4: Calculate percent meeting minimum requirement

• Conversion and estimating percent meeting the

minimum requirements done simultaneously • NCI developed 1- or 2-part nonlinear mixed models to

account for usual intake • Model depends on whether or not the food in question

was consumed daily by almost everyone– If food group episodically consumed, 2-part model used to

account for probability food consumed and amount eaten

– If food group ubiquitously consumed, 1-part model used to account for only amount eaten

Page 28: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Estimating the percentage of population exceeding recommendation threshold

• No single set of recommendations in Dietary Guidelines

• Varies by each person’s appropriate level of energy intake based on sex, age, and activity level

• Estimate minimum recommendations based on age, sex, and sedentary behavior (<30 minutes of PA)

Daily recommendations*

Sex Age (years Vegetables FruitWomen 19-30 2½ cups 2 cups

  31-50 2½ cups 1 ½ cups  51+ 2 cups 1 ½ cups

Men 19-30 3 cups 2 cups

31-50 3 cups 2 cups

  51+ 2½ cups 2 cups

Page 29: LV Moore, Kirsten Grimm, Sonia Kim, Kelley Scanlon Estimating Percent Meeting Fruit & Vegetable Recommendations from BRFSS data

Questions and Feedback