applying the theory of planned behavior to predict dairy product consumption by older adults

ABSTRACT

Objective:The purpose of this study was to explain intentionto consume dairy products and consumption of dairy prod-ucts by older adults using the Theory of Planned Behavior(TPB). The factors examined were attitudes, subjectivenorms, and perceived behavioral control.

Design: A cross-sectional questionnaire was administered.

Setting: Community centers with congregate dining pro-grams, group classes, and recreational events for older adults.

Subjects: One hundred and sixty-two older adults (mean age75 years) completed the questionnaire. Subjects were mostlywomen (76%) and white (65%), with about half having lessthan a high school education or completing high school.

Variables Measured: Variables based on the TPB wereassessed through questionnaire items that were constructedto form scales measuring attitudes, subjective norms, per-ceived behavioral control, and intention to consume dairyproducts. Dairy product consumption was measured using afood frequency questionnaire.

Analysis: Regression analyses were used to determine theassociation between the scales for the 3 variables proposed inthe TPB and intention to consume and consumption ofdairy products; the α level was set at .05 to determine thestatistical significance of results.

Results: Attitudes toward eating dairy products and per-ceived behavioral control contributed to the model for pre-dicting intention, whereas subjective norms did not. Atti-tudes toward eating dairy products were slightly moreimportant than perceived behavioral control in predicting

intention. In turn, intention was strongly related to dairyproduct consumption, and perceived behavioral control wasindependently associated with dairy product consumption.

Conclusions and Implications:These results suggest the util-ity of the TPB in explaining dairy product consumption forolder adults. Nutrition education should focus on improvingattitudes and removing barriers to consumption of dairyproducts for older adults.

KEY WORDS: dairy product consumption, older adults,Theory of Planned Behavior, questionnaire research

(J Nutr Educ Behav. 2003;35:294-301.)

INTRODUCTION

Based on National Health and Nutrition Examination Sur-vey (NHANES) data (1988-1994), it was estimated that 10%of adults aged 50 years and older had osteoporosis asmeasured by low total femur bone mineral density (ageadjusted to the year 2000 standard population).1 A meta-analysis regarding the effect of calcium on bone density andfractures in postmenopausal women found that calcium wasmore effective than placebo in reducing rates of bone loss,with a trend toward a reduction in vertebral fractures.2

Adequate calcium intake may be a simple and inexpensivestrategy to prevent osteoporosis, which is a major publichealth problem. A recent review of national dietary intakedata showed that calcium intake was about half of the rec-ommended level for women in their 50s to 80s, whereasintake for men was slightly higher but still less than recom-mended.3 Dairy foods contribute about 73% of the calciumin the US per capita food supply.4 Based on 24-hour recalldata, intake of dairy products for adults 50 years and over wasreported to be 1.3 servings per day for women and 1.0 to 1.1servings per day for men.5 Because of the positive healthbenefits derived from an adequate intake of dairy products,and therefore calcium, an increase in consumption of dairyproducts by older adults is recommended.

294

RESEARCH ARTICLE

Applying the Theory of Planned Behavior to Predict Dairy ProductConsumption by Older Adults

KYUNGWON KIM, PHD;1 MARLA REICKS, PHD, RD;2 SARA SJOBERG, BS2

1Department of Food Science and Nutrition, Seoul Women’s University, Seoul, Korea; 2Department of Food Scienceand Nutrition, University of Minnesota, St. Paul, Minnesota

Funding for this project was obtained from the Minnesota Agricultural ExperimentStation (MIN-054-026).Address for correspondence: Marla Reicks, PhD, RD, Department of Food Scienceand Nutrition, 1334 Eckles Avenue, St. Paul, MN 55108;Tel: (612) 624-4735; Fax: (612)625-5272; E-mail: [email protected].©2003 SOCIETY FOR NUTRITION EDUCATION

Journal of Nutrition Education and Behavior Volume 35 Number 6 November • December 2003 295

A better understanding of important psychosocial vari-ables that influence dietary behavior is needed to developeffective interventions involving an increase in dairy prod-uct consumption by older adults. Use of an appropriate the-oretical framework provides structure to the identification offactors influencing dairy product consumption.The Theoryof Planned Behavior (TPB) has recently been used to iden-tify important factors influencing dairy product intake byyoung women eligible for the WIC program,6 healthful eat-ing by adolescents,7 and fruit and vegetable consumption.8

Based on a meta-analysis involving 185 independent studies,the TPB accounted for 27% and 38% of the variance inbehavior and intention, respectively,9 which was comparableto the predictive ability of other theories that have been usedin relation to dietary behaviors.10

The TPB includes 3 constructs that explain intention toperform health behaviors (Figure).11,12 They include attitudestoward the behavior, subjective norms, and perceived behav-ioral control. Attitudes are determined by beliefs about thelikelihood of outcomes and their importance. Subjectivenorms are determined by what others think the individualshould do and the individual’s motivation to comply. Per-ceived behavioral control is determined by control beliefsthat can facilitate or inhibit the behavior, such as internalfactors (skills, abilities) and external factors (opportunities,barriers). Both intention and perceived behavioral controlhave direct influence on behavior.

Inadequate consumption of dairy products may be relatedto low calcium intake for older adults. In the present study,

the TPB was used to explain intention to consume as well asconsumption of dairy products among older adults by exam-ining factors including attitudes, subjective norms, and per-ceived behavioral control.Addressing important factors thatpredict consumption of dairy products by older adults maycontribute to improved effectiveness of educational effortstargeted to this population.

METHODS

Study Design and Subjects

This study used a cross-sectional questionnaire design.Initial individual interviews using open-ended questionswere conducted with 33 older adults to obtain informationnecessary to develop the questionnaire. Subjects complet-ing the questionnaire were recruited from 7 communitycenters in the Minneapolis-St. Paul metropolitan area.Those who participated in initial interviews were not askedto complete the questionnaire. Investigators recruited 197older adults (aged 65 years or older). Some providedincomplete information (n = 20); another 15 individualsdid not meet the age criteria.The final sample included 162older adults.

Measures Used in the Questionnaire

The questionnaire was developed according to the steps sug-gested by Montano et al12 and Ajzen and Madden13 based on

Behavioral beliefs

(eg, Eating dairy productsregularly helps me have abalanced diet.)

Attitude towardconsuming dairyproducts

Subjective norm(social influence)

Intention toconsume dairyproducts

Dairy productconsumption

Normative beliefs(eg, My doctor thinks Ishould drink/eat dairyproducts.)

�Motivation to comply(eg, I want to comply withdoctor.)

Perceived controlover consumingdairy products

Control beliefs(eg, It is difficult to keepdairy products always avail-able in my home.)

Figure. Proposed relationship between variables in this study based on the Theory of Planned Behavior.

the information obtained from initial interviews with 33older adults.

Attitudes toward consuming dairy products. Duringthe initial individual interviews, older adults (n = 33)responded to open-ended questions regarding the benefitsand advantages or disadvantages related to eating dairyproducts. After counting frequencies and reviewing theresponses, 19 items were selected to measure behavioralbeliefs. These items included nutritional benefits (such asstrong bones, balanced meals, vitamins, and minerals), prac-tical reasons for eating dairy foods (such as taste, going wellwith other foods, providing a snack), and disadvantages ofeating dairy foods (such as make me feel sick, high in fat orcholesterol).

Each item was designed to be measured on a 5-pointscale (very unlikely to very likely) to indicate the strength ofthese beliefs. Outcome evaluation, which is the other com-ponent comprising attitudes in the TPB, was not consideredin this study because prior experience indicated that mostpeople similarly evaluate the outcome of behavior.14 Atti-tudes toward consuming dairy products were defined as thesummated score of the 19 behavioral beliefs.The Cronbachcoefficient α15 was .82 and was considered acceptable for theattitudes scale.

Subjective norms. Thirteen different significant othersor information sources were listed by older adults during theinitial individual interviews as having an influence over dairyproduct consumption.These were categorized into 7 groups:family members (daughters/sons, sisters/brothers), spouse,friends, doctor, cooks at senior centers, television programs,and newspapers/magazines. Items for normative beliefs wererated on a 5-point scale (very unlikely to very likely).The cor-responding motivation to comply with each significant otheror source of information was measured on a 5-point scale(not at all to very much).There was also a response categoryfor subjects to check if these significant others did not applyto the subjects, for example, if the person did not have a spouseor never watched television.This response category was codedas a neutral point.The subjective norms variable was definedas the summated score of the product of each normative beliefand motivation to comply.The Cronbach coefficient α was.81 for this scale and was considered acceptable.

Perceived behavioral control over consuming dairyproducts. During the initial interviews, subjects identi-fied factors or situations that made it difficult to consumedairy products. Similar responses were grouped together,resulting in 21 items to measure control beliefs. Theseincluded perceived confidence in eating dairy foods (such asfor snacks, milk-based desserts, low-fat products, eating withmeals), confidence in eating dairy foods in several differentsituations (such as when eating out, whenever you want to),and availability issues and access to dairy foods.These itemswere rated on 5-point scales (disagree a lot to agree a lot or

very difficult to very easy). Perceived behavioral control overconsuming dairy products was defined as the summatedscore of control beliefs.The Cronbach coefficient α for thisscale was .90 and was also considered acceptable.

Intention. Two items were used to measure intention toconsume dairy products.The item,“How likely is it that youwill eat dairy products regularly (2-3 servings a day) for thenext month?” was rated on a 5-point scale (very unlikely tovery likely).The other item was “How many servings of dairyproducts do you plan to eat for the next month?” and had endpoints from never/rarely to more than 3 servings a day. Inten-tion was defined as the summated score of the 2 items.

Dairy product consumption. Dairy product consump-tion was measured using food items in Block’s Food Fre-quency Questionnaire.16 Ten food items were used, includ-ing milk,milk on cereal, cheese, and yogurt.To measure dairyproduct consumption more accurately, milk or cheese usedin cooking foods was also included. Subjects were asked toindicate how often and how much they usually ate for eachfood item. Dairy product consumption was quantified as thenumber of servings consumed per day.

A preliminary draft of the questionnaire was reviewed by3 university professionals and pilot tested with 5 older adultsto check understanding of items. Based on the pilot test,minor changes were made in format and wording.The studywas approved by the Human Subjects Protection Commit-tee of the University of Minnesota’s Institutional ReviewBoard.

Data Collection

Data were collected after meals at congregate dining centersor after classes or meetings in community centers betweenNovember 2001 and May 2002. The food frequency ques-tionnaire items regarding dairy products were completedprior to completion of the measures related to the 3 variablesproposed in the TPB. In most cases, the food frequency itemswere administered by investigators through personal inter-views, followed by subjects responding to the remainingitems without assistance.However, some subjects (about 10%)needed assistance because they had difficulty either reading ormarking the questionnaire. It took 20 to 30 minutes for mostof the older adults to complete the questionnaire.

Statistical Analysis

Data were analyzed using the Statistical Analysis System(SAS, Version 6.12, Cary, NC). Descriptive statistics wereused to examine demographic characteristics and study vari-ables. Student’s t-tests were done to determine differences indairy product consumption according to demographic vari-able categories. Correlation analysis was used to examine thesimple association between study variables.To investigate theassociation between the scales for the 3 variables proposed inthe TPB and intention to consume and consumption of

296 Kim et al/THEORY OF PLANNED BEHAVIOR TO PREDICT DAIRY CONSUMPTION BY OLDER ADULTS


dairy products, regression analyses were done, first to predictintention to consume and then to predict dairy product con-sumption.To examine the relative importance of each vari-able in explaining variance in the dependent variable, thesquare of the standardized β for each variable was obtainedand the ratio of each standardized β was examined.17 A levelof P < .05 was considered significant for statistical tests.

RESULTS

Descriptive Statistics

The mean age of subjects was 75.1 years (SD 6.1 years). Sub-jects were mostly women (76%) and white (65%).About halfof the subjects had less than a high school education or hadcompleted high school. Forty-six percent lived alone,whereas38% lived with a spouse. Most rated their health as good orvery good. Demographic data are presented in Table 1.

The mean of the summated intention items was 0.67 ±2.13 from a possible score of �4 to +4, suggesting that sub-

jects were slightly positive about their willingness to con-sume dairy products. On average, older adults consumed 2.1(SD 1.3) servings of dairy products per day.When the distri-bution of dairy product consumption was examined, 21%had less than 1 serving of dairy foods, 29% had 1 to less than2 servings of dairy foods, 27% ate 2 to less than 3 servings,and only 15% had 3 to less than 4 servings.

Among the categorical variables, race, use of supplements,and regular exercise were related to dairy product consump-tion (see Table 1).White subjects consumed greater numbersof servings of dairy foods than other groups. Individuals whowere more likely to consume greater numbers of servings ofdairy foods used supplements and exercised regularly.

The simple association between study variables wasexamined using Pearson correlation coefficients (Table 2).Dairy product consumption was highly correlated with theintention to consume dairy products (r = .61, P < .001) andperceived behavioral control over consuming dairy products(r = .48, P < .001). Intention to consume dairy products wassignificantly related to the 3 variables proposed in the TPB,in the order of decreasing magnitude of association: attitudes

Table 1. Comparison of Dairy Product Consumption by Demographic Variables†

Mean StandardVariables N % (servings/d) Error F Value

Gender

Female 123 75.9 2.06 0.12 1.17

Male 39 24.1 2.32 0.19

Race

White 106 65.4 2.36a‡ 0.13 8.19**

African American 35 21.6 1.38b 0.17

Other 21 12.9 2.15a 0.28

Education level§

≤ 12th 78 48.1 2.00 0.15 2.04

> 12th 74 45.7 2.30 0.15

Marital status

Married 65 40.1 2.39 0.15 2.28

Single 16 9.9 1.59 0.34

Widowed 57 35.2 2.14 0.17

Divorced/separated 24 14.8 1.83 0.27

Living status

Alone 74 45.7 1.98 0.16 1.32

With spouse 61 37.7 2.26 0.15

With other family members 27 16.6 2.23 0.26

Regular use of supplement

No 49 30.2 1.79a 0.19 4.71*

Yes 113 69.8 2.27b 0.12

Regular exercise

No 48 29.6 1.60a 0.14 15.80***

Yes 114 70.4 2.35b 0.13

*P < .05; ** P < .01; *** P < .001.†By analysis of variance.‡Using Tukey’s method of comparison.§Ten people (6.2%) did not respond to the question about education level.Values with different superscript letters are significantly different.

toward consuming dairy products, perceived behavioral con-trol, and subjective norms.

Regression Analyses for Intention to Consume Milk

The multiple regression model explained 42.4% of the vari-ance in intention (F = 40.5, P < .0001), providing empiricalevidence for the TPB regarding dairy product consumptionby older adults (Table 3).Attitudes toward consuming dairyproducts and perceived behavioral control were related tointention, whereas subjective norms were not related. Toexamine the relative importance of these variables inexplaining intention, the ratio of the square of the standard-

ized β for each variable was examined. Attitudes accountedfor 1.6 times more variation in intention than perceivedbehavioral control over consuming dairy products(0.382/0.302).

Regression analyses were also completed while control-ling for demographic variables. There were differences inintention, attitudes, and perceived behavioral control scoreby race and supplement use. In the preliminary analysis,white subjects and those who used supplements regularlyhad greater intention and more favorable attitudes and feltmore control over consuming dairy products than theircounterparts.Thus, a second regression to predict intentionwas completed while controlling for race and supplement


Table 2. Correlation among Study Variables

Dairy Product Consumption Intention Attitudes Subjective Norms Perceived Behavioral Control

Dairy product consumption 1.0

Intention 0.61*** 1.0

Attitudes 0.42*** 0.60*** 1.0

Subjective norms 0.33*** 0.38*** 0.49*** 1.0

Perceived behavioral control 0.48*** 0.55*** 0.55*** 0.31*** 1.0

***P < .001.

Table 3. Multiple Regression of Intention to Consume Dairy Products and Dairy Product Consumption on Selected Variables Based on the

Theory of Planned Behavior

Variables � SE Standardized � t Model R2

Intention on Attitudes, Subjective Norms, and Perceived Behavioral Control

Model 1†

Attitudes 0.08 0.02 0.38 4.90*** .424

Subjective norms 0.02 0.01 0.11 1.55

Perceived behavioral control 0.05 0.01 0.30 4.19***

Model 2‡

Attitudes 0.07 0.02 0.37 4.70*** .434

Subjective norms 0.02 0.01 0.11 1.59

Perceived behavioral control 0.04 0.01 0.26 3.53***

Race 0.24 0.29 0.05 0.85

Supplement use 0.57 0.28 0.12 2.03*

Consumption on Intention and Perceived Behavioral Control

Model 1§

Intention 0.30 0.05 0.49 6.67*** .394

Perceived behavioral control 0.02 0.01 0.22 2.96**

Model 2||

Intention 0.30 0.05 0.48 6.47*** .390

Perceived behavioral control 0.02 0.01 0.20 2.56*

Race 0.19 0.18 0.07 1.08

Supplement use �0.01 0.19 0.00 �0.05

*P < .05; **P < .01; ***P < .001.†Model df = 3,158; model F = 40.5; P = .0001.‡Controlling for race and supplement use; model df = 5,156; model F = 25.7; P = .0001.§Model df = 2,159; model F = 53.2; P = .0001.||Controlling for race and supplement use; model df = 4,157; model F = 26.8; P = .0001

use. This model explained 43.4% of the variance in inten-tion. Similar to the first model, attitudes and perceivedbehavioral control were associated with intention; however,the relative importance of perceived behavioral control inexplaining intention was slightly decreased. Attitudesexplained 2 times more variation in intention than perceivedbehavioral control over consuming dairy products.

Regression Analyses for Dairy Product Consumption

Intention to consume and perceived behavioral controlexplained 39.4% of the variation in dairy product consump-tion (see Table 3).As proposed in the TPB, perceived behav-ioral control directly contributed to the actual consumptionof dairy products. In the preliminary analyses, race and sup-plement use were related to dairy product consumption, aswell as intention to consume and perceived behavioral con-trol. Therefore, another regression analysis was completedwhile controlling for the effect of these variables (see Table3).The variance explained by independent variables in thismodel was almost the same as in the first model. However,the relative importance of intention to consume comparedto perceived behavioral control was increased from 5.0 timesto 5.8 times.

DISCUSSION

Nutrition education that results in an increased intake ofcalcium-rich foods such as dairy products is important inthe prevention of osteoporosis. Estimates indicate thatosteoporosis contributes to up to 90% of hip fractures inwomen and 80% of hip fractures in men.18 A recent studyhas shown that improvements in calcium intake provided as3 servings of yogurt/day rapidly improved bone resorptionin older women.19 It has been estimated that increasingbone mineral density by 5% could decrease the risk of frac-tures by 25%.20 Another study showed that increased intakeof dairy products by older adults resulted in overallimprovement in nutrient intakes.21 Interventions to increaseintake of dairy products with community-dwelling eldershave been successful22 and therefore should be expandedbased on appropriate theoretical models.The current studycontributes to this effort by further explaining dairy prod-uct consumption by older adults based on a useful theoret-ical model (TPB).

In this study, dairy product consumption for a conve-nience sample of older adults was below recommendationsat about 2 servings per day. Using a nationally representativesample involving 24-hour recall data, others have estimatedintake of dairy products by older adults to be about 1 serv-ing per day.5,23 The demographic makeup of the conveniencesample and small sample size in the current study mayexplain the difference in estimates of intake of dairy prod-ucts.White subjects had greater intention to consume dairyproducts and more favorable attitudes, felt more control overconsuming dairy products, and had greater consumption

than other subjects. Issues with lactose intolerance amongAfrican American subjects may be partially responsible forthese differences. A study by Elbon et al showed that per-ceived milk intolerance was more common among olderAfrican American adults (35%) who consumed less milk andother dairy products compared with older white adults(17%).24 African American mothers participating in the Spe-cial Supplemental Program for Women, Infants and Children(WIC) also consumed less milk compared with white moth-ers, which was thought to be the result of less favorable atti-tudes and intention based on the TPB.6

The influence of the 3 variables proposed in the TPB onintention and behavior is thought to be dependent on theparticular behavior and situation.25 In situations in whichattitudes are strong or normative beliefs are powerful, atti-tudes or subjective norms may be more predictive thanperceived behavioral control. In the current study, applica-tion of the TPB among a sample of older adults showed thatattitudes toward eating dairy products and perceived behav-ioral control contributed to the model for predicting inten-tion, whereas subjective norms did not, indicating thatnormative beliefs were not particularly powerful in thisgroup. This is consistent with several other studies of theapplication of the TPB in relation to diet and other health-related behaviors in which attitudes and perceived behavioralcontrol are more significant than subjective norms.7,26

Older adults may not be as influenced by others in termsof subjective norms because many live alone and have lesscontact with reference groups, such as family or friends.They may also be more likely to depend on their own deci-sion-making ability regarding food choices rather thanothers because of their considerable life experiences. It fol-lows that there may not be many powerful social influencersfor increasing intake of dairy products for this population. Inthe current study, there was no significant relationshipbetween dairy product intake and living status (about 54%indicated that they lived with others). In other studies, livingarrangements have been shown to affect overall diet qualityamong white adults,27 with those living with a spouse havingbetter diet quality. However, the current study was focusedon dairy products only and did not measure overall dietquality and nutrient intake.

The relationship between perceived behavioral controland intention is also dependent on the behavior and situa-tion.25 In the current study, perceived behavioral control andintention were well correlated (r = .55, P < .001), indicatingthat the subjects may have been more likely to want toengage in the behavior if they thought there were fewer per-sonal and environmental barriers. Examples of these barriersincluded difficulty substituting milk for other beverages,finding transportation to the store to purchase dairy prod-ucts, not always being able to have dairy products availablein the home, and cost. The relationship between intentionand behavior was also strong (r = .61, P < .001). In some sit-uations, it may be difficult for intention to translate intobehavior if various personal and environmental control


factors inhibit the behavior. A strength of the TPB in thecurrent study is that perceived inhibitory factors are animportant part of the model and can be identified in orderof their relevance in prediction of behavior.This can be veryuseful in developing dietary behavior change interventionsthat address personal and environmental barriers.

In the current study, perceived behavioral control con-tributed to intention to consume and actual consumption ofdairy products, confirming the findings of other studiesapplying the TPB to dietary behavior.8,26,28 Perceived behav-ioral control is thought to be predicted by items concernedwith external control such as the barriers of cost and avail-ability, whereas self-efficacy was predicted by both internalitems, such as motivation and knowledge and external items.In the current study, the perceived behavioral control scaleincluded both internal items, such as perceived abilities andexternal items, as suggested in the theory. Others have exam-ined the concepts of perceived behavioral control and self-efficacy as separate from each other8,9 and suggest more care-ful definition of these concepts in future studies.

The predictive power for both intention and behaviorbased on the TPB in the current study can be compared withthe results from other recent studies focusing on health-related behaviors.7,26,28,29 In a study of milk consumption byyoung pregnant women, the TPB model explained 36% ofthe variance in intention and 46% of the variance in behav-ior. In the current study with older adults, the model wasabout as predictive (42% of the variance in intention,whereasintention and perceived behavioral control explained 39% ofthe variance in behavior).The predictive power of the modelwas not as strong in studies involving consumption of otherfoods or more complex behaviors. For example, the TPBmodel explained 31% for the variance in intention and only7% of the variance in behavior related to fruit and vegetableconsumption among adolescents.7 In another recent studywith adolescents, intention explained 17% of the variance inhealthful dietary behavior involving total calorie intake, per-centage of calories from fat, and intake of fruits and vegeta-bles,28 whereas attitudes, norms, and perceived behavioralcontrol explained 42% of the variance in intention. Fromthese results, it is clear that the model best predicts behaviorif the behavior is more specific (milk versus dairy products ordairy products versus fruits and vegetables).10

A limitation to this study is that the results are based on asmall convenience sample of older adults attending seniorcenters. Thus, the findings are not generalizable to othergroups of seniors (eg, frail elderly or those in other geo-graphic areas).

IMPLICATIONS FOR RESEARCH ANDPRACTICE

The results of this study showed the importance of perceivedbehavioral control; therefore, further research is needed tounderstand what influences perceived behavioral control and

how to increase the perception of control. In terms of prac-tice, nutrition educators might focus on factors examined inthis study in planning educational programs for older adults,such as having favorable attitudes (emphasize advantages andminimize disadvantages of consuming dairy products) andincreasing the perception of control over consuming dairyproducts.To help older adults have favorable attitudes, prac-titioners need to address nutritional benefits (eg, providingcalcium, vitamins, and other nutrients). Practical benefits alsoneed to be addressed, such as the concepts that dairy prod-ucts taste good, they can serve as beverages at breakfast orduring the rest of the day, they help one to have a balanceddiet, and they are foods that go well with other foods. Inaddition, practitioners might help older adults increase per-ceived control in eating dairy foods with meals by substitut-ing milk for other beverages and enhancing cooking skillsusing dairy products. Environmental approaches are neededto address the barriers of transportation, availability of dairyproducts (at home), and cost.

These strategies will lead to changes in intention andhopefully help older adults consume more dairy products. Itwas apparent from this study that there are multiple belieffactors that predict intention and behavior related to intakeof dairy products by older adults in this sample. Educationshould therefore address these multiple constructs.

ACKNOWLEDGMENT

Funding for this project was obtained from the MinnesotaAgricultural Experiment Station (MIN –054-026).

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VISION, MISSION, AND GUIDING PRINCIPLES OFTHE SOCIETY FOR NUTRITION EDUCATION

Vision

Healthy people in healthy communities.

Mission

To enhance nutrition educators’ ability to promote healthful sustainable food choices and nutrition behaviors.

Guiding Principles

• Fiscal responsibility • Professionalism and integrity• Respect for diversity of opinions and perspectives • Inclusiveness in membership• Trust and willingness to communicate openly and respectfully • Equality among members• Knowledge-based decisions • Rewarding and enjoyable experiences for • Excellence and lifelong learning volunteers and supporters

applying the theory of planned behavior to predict dairy product consumption by older adults

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