Research ArticleDeterminants of Food Label Use among SupermarketShoppers: A Singaporean PerspectiveSantosh Vijaykumar, PhD1; May O. Lwin, PhD1; Jiang Chao, MCS2; Cyndy Au, MMC2

1Center ofSingapore2Wee KimUniversityAddress forfor CommE-mail: san�2013 SOhttp://dx.d

204

ABSTRACT

Objective: Examining factors influencing food label use among Singapore’s supermarket shoppers usingthe Theory of Planned Behavior.Design: A point-of-purchase survey among general shoppers in 2 supermarkets.Setting: Singapore, a country whose population is exposed to a wide range of food labeling formatsbecause of the import-dependent nature of the food industry.Participants: A total of 200 shoppers (Chinese [75.5%], Malays [8.5%], and Indians [7.0%]) participatedin the survey.Main Outcome Measures: Independent variables composed of attitudes and subjective norms (both5-point Likert); perceived behavioral control and diet-health concern (both 5-point semantic differential);and knowledge (18-item index). Dependent variables were intention to use food labels (5-point differentialscale) and actual use of food labels (19-item index).Analysis: Data were analyzed using descriptive statistics, mean analysis, and multivariate linearregression.Results: Low levels of knowledge and health literacy were found. Attitudes, subjective norms, and be-havioral control differed significantly by age and ethnicity. Subjective norms and diet-health concernwere significant predictors of intention to use food labels.Conclusions and Implications: Lack of knowledge but positive attitudes toward food labels makeSingapore’s consumers vulnerable to misusing or being misled by food label information. Demographicdifferences demonstrate the need to develop targeted educational interventions and enhance awarenessof and ability to use food labels.KeyWords: food label, Asia, behavior, Theory of PlannedBehavior (JNutr Educ Behav. 2013;45:204-212.)

INTRODUCTION

In the past 2 decades, countries in theAsia-Pacific region, especially Singa-pore, have experienced considerableeconomic growth.1 However, an in-crease in per capita income has ledto a greater desire for convenience,willingness to experiment, and lesstime for home preparation of meals.Thus, dietary behaviors have shiftedtoward an increased consumption ofprocessed and packaged food.2 Con-currently, the region has experienceda rise in lifestyle-related and/or diet-and weight-related chronic healthconditions such as obesity and diabe-

Social Media Innovations for Comm

Wee School of Communication, Singaporecorrespondence: Santosh Vijaykumaunities, HSS #06-15, 14 Nanyang Drtoshv@ntu.edu.sgCIETY FOR NUTRITION EDUCoi.org/10.1016/j.jneb.2012.09.001

tes, among others.3-5 As the publichealth community attempts todevise effective educational strategiesto address this situation, foodlabels have emerged as legitimatecandidates. Some researchers suggestthat food labels influence diet andhealth outcomes by shaping food-related attitudes and choices,6-8

whereas others view this relationshipas uncertain.9,10

In a world in which people grapplewith busy lifestyles and reduced atten-tion spans, food labels help marketersto quickly share information, commu-nicate a product's healthfulness, andgenerate consumer confidence in

unities, Nanyang Technological University,

and Information, Nanyang Technological

r, PhD, Center of Social Media Innovations, Singapore 637332. Phone: (þ65) 81838657;

ATION AND BEHAVIOR

Journal of Nutrition Education and Beh

a product's quality.11 Food labels bridgethe health information gap betweenproducers and consumers and are de-signed to aid in consumers' dietarychoices.12,13 In Europe, researchersfound surprising consistency inconsumers' interest in nutritionalinformation and obtaining thisinformation from food labels.14 In theUnited States (US),15 a vast majority ofshoppers reported using nutrition la-bels ‘‘sometimes’’ or ‘‘always,’’ while inNew Zealand,16 label use among shop-pers was found to bemoderate to high.

In contrast, controversies sur-rounding misleading informationand claims have adversely affectedconsumer attitudes toward food la-bels.17 Researchers now find that con-sumers' actual use of food labels mightbe lower than their reported use.18,19

As a result, there is a growing lack oftrust in, and skepticism about, foodlabels among the public.20

These conflicting trends challengenutrition educators and public healthauthorities who encourage the publicto use food labels as a means to make

avior � Volume 45, Number 3, 2013

Journal of Nutrition Education and Behavior � Volume 45, Number 3, 2013 Vijaykumar et al 205

food choices that align with their die-tary composition and health needs.In order to understand how food labelmarketing influences dietary choicesor health outcomes, it is important tobegin by identifying the factors thatinfluence the use of food labels. Thisresearch set out to examine whetherpsychosocial factors related to foodlabel use differ by demographicsegments and theoretical drivers ofintention to use food labels. Althoughresearchers in the West have conduct-ed some examinations of such is-sues,21-23 similar inquiries in the East,particularly Singapore, are scant.

The Singaporean Food LabelingContext

Singapore, an island city-state that ishome to approximately 5million peo-ple, represents a microcosm of Asia,with a dominant blend of Chinese,Malays, and Indians. However, thecountry's rapid economic prosperityforeshadows the lack of local agricul-tural produce, which leads to foodconsumption being dependent on im-ported food. This pattern exposes Sin-gapore's consumers to packaged foodthat arrives from different continentswith a range of food labeling formats.

Current Singapore food regulationsrequire all pre-packaged food productsfor sale in Singapore to be labeledaccording to specified local require-ments.24 General labeling require-ments include product name,ingredient list, allergen labeling,quantity, drained weight, name ofthe country of origin, as well as thename and address of manufacturer,packer, or local vendor. All these itemsmust be printed in English, in lettersnot less than 1.5 mm in height. Thefood labeling regulations also permitthe use of a nutrition informationpanel—which has been shown to in-fluence consumers' assessments ofpackaged food25—to enable the list-ing of energy and nutrients containedin the food. All food for sale in Singa-pore, including products that areimported into the country, must belabeled according to this format.With regard to front-of-package label-ing that intends to serve as an indica-tor of the product's healthiness,international systems such as Guid-ance Daily Amount and traffic lights26

are eschewed in Singapore. Instead,food products are allowed to carrythe Health Promotion Board (HPB)Healthier Choice Symbol.27

Singapore's consumers also en-counter logos/seals besides theHealthier Choice Symbol—a practicegenerally not allowed. Notwithstand-ing this general prohibition, somespecific logos or seals issued by au-thorities recognized by the regulatoryagency are permitted. Some examplesinclude logos of the Singapore HeartFoundation,28 Superbrands,29 and ha-lal (commonly meat products) certifi-cations.30 Such third-party seals arepotentially extrinsic cues to consumerchoices, as early studies have shownthat consumers tend to attributemore meaning to seals than is true.31

Determinants of Food Label Use

According to Drichoutis and col-leagues,21 food label use is influencedby factors at various levels, rangingfrom demographic to attitudinal andproduct related. Scientific evidence re-mains inconclusive toward influence ofdemographic factors on food label use.Although some studies have reportedthat food label use decreases withage,22,32 other studies have demons-trated the reverse.33,34 Furthermore,individuals with higher education aremore likely to read nutrition labels andperuse ingredient lists, as opposed tothose with lower education, who tendto read only the former.35,36

Prior nutritional knowledge can in-crease food label use by enhancing itsperceived benefits21 or by increasingmotivation to seek more health infor-mation.37 A person's attitude shapesfood label use in concert with a rangeof different factors. For instance, con-sumers who perceive food labels as‘‘too hard to understand,’’ ‘‘too smallto read,’’ and an activity that ‘‘takestoo much time’’ are discouraged touse them.38 Recent reports haveidentified a lack of trust and growingskepticism about information dis-played in food labels20 and a low per-ception of importance of food labelinformation39 as possible barriers touse. Other research has found thathigher perceived benefits of food labeluse (in terms of its usefulness and abil-ity to facilitate food choices) can influ-ence greater use of food labels.40

Theoretical Framework

The theoretical framework that in-formed the present study was the The-ory of Planned Behavior (TPB).41

According to this theory, behavioralintention can be explained by (1) atti-tudes (beliefs about the likely conse-quences of behavior); (2) subjectivenorms (‘‘social pressure to perform ornot perform the behavior’’);41 and(3) perceived behavioral control(beliefs about internal and externalbarriers that may hinder the behaviorto be performed). This study extendedthe application of TPB in food labeluse research by focusing on 2 ele-ments that have been largely ignoredin previous studies: subjective normsand diet-health concern (DHC), a con-struct outside the original TPB model.

First, in previous research, pathwaysbetweensubjectivenormsanddiet- andhealth-related behaviors have beenshown to exist.42,43 Given that foodlabel use has been shown to influencesuch behaviors, it is important tounderstand the role of subjectivenorms in shaping the use of foodlabels. A simple illustration is that ofa woman using food labels becauseshe perceives that her husband wouldlike for her to be more healthconscious and lose weight. Then, foodlabel use is generally stimulated insettings such as supermarkets, whereconsumer behavior may be shaped bya process of negotiation with one'ssocial identity. For instance, a personmight use food labels to ‘‘come across’’as being a discerning consumer ora health-conscious one.

The second element pertains toDHC. In the past decade, researchershave noted how concerns aboutone's own health vis-�a-vis one's dietand feelings about linkages betweendiet and disease can potentially shapeuse of food labels.44 These findings aretested by exploring whether DHCadds to the predictive ability of TPBin explaining intention to use food la-bels. In sum, this study examined thedemographic and attitudinal driversof food label use among Singapore'ssupermarket shoppers. The intentwas to quantitatively investigate pub-lic awareness of, and attitudes toward,food labels among Singapore's super-market shoppers. Such an assessmenthelps to determine whether psychoso-cial factors related to food label use

206 Vijaykumar et al Journal of Nutrition Education and Behavior � Volume 45, Number 3, 2013

varies according to gender, ethnicity,and age. In doing so, this study ad-dressed theoretical gaps by examiningthe relevance of the TPB and the ex-tent that DHC adds to the predictivepower of TPB.

METHODS

The study team conducted point-of-purchase surveys among shoppers in2 supermarkets in Singapore. Point-of-purchase survey is the preferredmethodology for food labelingstudies,45 as this strategy enables re-searchers to capture consumers' in-sights during their shoppingexperiences, thereby lowering thepossibility of overreporting of food la-bel use. Settings catering to differentsocioeconomic groups were chosen(National Trade Union Congress[NTUC], Fairprice Extra [discount gro-cery store], and NTUC Fairprice Finest[high-end grocery store]) to accountfor economic diversity in the study

Table 1. Singapore Shoppers’ KnowledgeLabel Information (n ¼ 199)

Knowledge of Food Label InformationWhich of the following calorie requirementsIf a food could be considered as a good soat least what percentage of that nutrient?

A natural claim means.One/some of the ingredients is/are naturAll the ingredients are natural.No additives have been added.No preservatives have been added.

Food with a natural or fresh claim is less prNatural or fresh claim on food products meNatural or fresh claim on food products memodified from its natural state.

Natural or fresh food is healthier than foodFoods with fresh or natural claim has lesseOrganic food is.Food free of artificial food additives.Food that is minimally processed.Food with fresh/natural claim.

Organic food tastes better than nonorganicOrganic food has longer shelf life.Organic food has more health-related beneOrganic food has less risk of being polluted

Health LiteracyBased on the nutrition information in ProduHow many grams of sugar are there in 2 seHow many grams of fat are there in 50% oHow many servings are there in this producIs this product high in fat?

sample.46 Data collection began afterobtaining necessary permissionsfrom store managers. Conveniencesampling was used to collect datafrom all respondents who agreed toparticipate, within a 1-week periodin March 2010. Two trained researchassistants solicited general shoppersto participate in the 15- to 20-minute survey and, when the shop-pers agreed to participate, describedthe study objective to them. Onlyparticipants aged 18 years or olderwith English proficiency were in-cluded. Shopping vouchers for 10 Sin-gapore dollars (US equivalent $8.00)were offered. Participants receiveda self-administered, 36-item, English-language questionnaire with colorpictures for easier understanding.Nanyang Technological University'sInstitutional Review Board had notbeen established when data were col-lected. However, the study team ob-tained approval from the HPB andfollowed international ethical proto-

about Food Labels, Food Claims, and Organic

is the % daily value based on?urce of a nutrient, the food should contain

al.

ocessed than food without such claims.ans that food has not been excessively extracans that the food has not been significantly

without such claims.r risk of being polluted than food without such

food.

fits than nonorganic food.than nonorganic food.

ct 1.rvings of this product?f this pack?t?

cols such as seeking subject consentand ensuring data confidentiality.

Before implementing the final sur-vey, the research team piloted thequestionnaire with 10 graduate stu-dents to test for comprehensibilityand length. Minor amendments weresubsequently made.

Measures

The knowledge index (Table 1) waspartially adapted from previous stud-ies and was composed of 4 informa-tional categories that frequentlyfeature in food labels: percent dailyvalue; percent nutrient composition;natural and/or fresh claims; and ‘‘or-ganic’’ food products. Health liter-acy45 was operationalized as anindividual's ability to understandand use information from the nutri-tion information panel.45 Attitudes,adapted from a previous study,45 re-flected beliefs about the usefulness,accuracy, and truthfulness of food

Food, and Their Ability to Interpret Food

% Incorrect % Correct78.5 21.575.5 24.5

41.5 58.548.5 51.559.5 40.558.5 41.584.0 15.5

ted. 76.0 23.079.5 19.5

80.5 18.5claims. 67.5 31.0

85.5 14.060.0 38.543.5 56.055.5 44.048.0 51.084.5 15.082.5 17.5

57.5 42.044.5 55.533.5 66.563.5 36.5

Table 2. Sociodemographic Description and General Food Label Awareness ofSurvey Respondents (n ¼ 199)

Variable %SexMale 36.5Female 63.5

RaceChinese 75.5Malay 8.5Indian 7.0

Journal of Nutrition Education and Behavior � Volume 45, Number 3, 2013 Vijaykumar et al 207

labels. Subjective norm items wereparticipants' social or normative pres-sures, or relevant others' beliefs thathe or she should or should not usefood labels. Perceived behavioralcontrol was the perceived ease ofunderstanding different food labelelements. These variables were mea-sured on 5-point Likert scales. Itemspertaining to DHC reflected theperceived importance of healthfuleating.40 Intention to read/use foodlabels was adapted from a previousstudy andmeasured through a 5-pointsemantic differential scale.45 Overallfood label use was measured throughan index of respondents' use of 19different elements in food labels.

Caucasian 9.0Age, y10–19 16.020–29 32.530–39 22.040–49 18.5$ 50 11.0

EducationPrimary school/secondary school 35.0Junior college/polytechnic diploma/advanced diploma 27.0Bachelor or post-bachelor degree 37.5

Income, $# 1,000 18.61,001-3,000 25.13,001-5,000 16.65,001-7,000 8.0> 7,000 6.0Declined to answer 25.6

General awareness of food labelsHeard of traffic lightsa 17.5Heard of Guidance Daily Amount 24.0Heard of Health Promotion Board (or Healthier Choice symbol) 9.2

Heard of third-party sealsSingapore Heart Foundation 78.0Islamic Association 93.0Superbrands 74.0

Summary Scores of Key Variables(Maximum Score) Meanb (SD)

Medianc (25th–75thPercentiles)

Knowledge (18) – 5 (4–8)Attitude (5) 3.78 (0.72) –Subjective norms (5) 3.35 (0.75) –Perceived behavioral control (5) 3.70 (0.63) –Diet-health concern (5) – 4.09 (3.72–4.55)Intention to use food labels (5) 3.34 (0.79) –Food label use (19) – 13 (10–16)

aThe traffic lights system is used in the United Kingdom and indicates the levelsof sugars, fat, saturated fat, and salt. Red means high in content; Amber, me-dium in content; Green, low in content. Other countries may use a different inter-pretation (Red: Never consume; Amber: consume once in a while; Green:consume anytime). Generally, green indicates healthiest and red indicates leasthealthy; bNormally distributed; cNot normally distributed.

Analysis

Dataweremanuallyentered,managed,and analyzed with SPSS software (ver-sion 17, SPSS Inc, Chicago, IL, 2008).Factor analysis with Varimax rotationwas first performed on all survey ques-tions to identify factors and loadings ofindividual items, followed by reliabil-ity testing of constructs. Final itemsand reliability scores are available inthe Supplementary Data online.

The analytical approach was com-posed of 4 stages. In stage 1, normalityof distribution of key variables was as-sessed using P-P plots and skewness.Stage 2 used univariate statistics (sim-ple frequencies) to generate a profileof respondents and overall scores forvariables of interest. Knowledge scoreswere calculated as a summation ofcorrect responses. In stage 3, knowl-edge, TPB constructs, DHC, and foodlabel use were compared between de-mographic groups such as sex (inde-pendent t tests), age, and ethnicity(both age and ethnicity 1-wayANOVA). Tukey post hoc tests wereused to compare between groups.Stage 4 used multivariate linearregression to examine relationshipsbetween independent variables (TPBconstructs and DHC), and dependentvariables (intention to use food labelsand actual food label use). To ensureparsimony, independent variablesthat failed to meet statistical signifi-cance were excluded from the models.

None of the demographic variablesdemonstrated significant correlationswith intention to use or actual foodlabel use, and they were excluded.

Statistical significance for all testswas determined at the P < .05 level.A single case with several missingvalues was found and excluded fromanalysis.

RESULTSSample Description

Of the 199 shoppers who participatedin the present survey, 75.5% were

Table 3. Factors Related to Food Label Use by Sex, Mean Score (SD)

Variable (Maximum Score) Male (n ¼ 73) Female (n ¼ 126)Knowledge (18) 6.81 (0.42) 5.50 (0.24)Attitude (5) 3.75 (0.61) 3.73 (0.62)Subjective norm (5) 3.38 (0.73) 3.33 (0.42)Perceived behavioral control (5) 3.68 (0.60) 3.71 (0.65)Diet-health concern (5)* 3.95 (0.75) 4.14 (0.56)Food label use (19) 13.21 (0.50) 12.75 (0.38)

*Statistically significant at P # .05.Note: Means comparison was carried out using independent t tests.

208 Vijaykumar et al Journal of Nutrition Education and Behavior � Volume 45, Number 3, 2013

Chinese, followed by 8.5% Malaysand 7.0% Indians, reflecting the coun-try's ethnic composition (Chinese:74.0%; Malays: 13.0%; Indians:9.2%).47 The majority of respondentswere female (63.5%). Most respon-dents (32.5%) were 20-29 years old,22.0% were 30-39 years old, and18.5% were 40-49 years old. Nearly38% of respondents had completeda bachelor's degree or higher.

Awareness of and Attitudestoward Food Labels

As expected, most respondents hadheard of neither the Guidance DailyAmount nor the traffic light labelingsystems. More than 90% of the re-spondents were aware of third-partyseals by the HPB. Overall scores ofkey variables suggested low knowl-edge (median ¼ 5) and positive atti-tudes toward food labels (mean ¼3.73, SD ¼ 0.61). Respondents per-ceived that people important tothem would like them to read food la-bels (mean ¼ 3.35, SD ¼ 0.75) and be-lieved that they are capable of using

Table 4. Age-based Differences in PsychoMean Score (SD)

Variable(Maximum Score) 10-19 (a; n ¼ 31)Knowledge (18) 6.06 (2.29)Attitude (5) 3.88 (0.57)Subjective norm (5) 3.24 (0.76)Behavioral control (5) 3.73 (0.76)Diet-health concern (5) 4.01 (0.74)Food label use (19) 11.68 (4.07)

Note: Statistical test: 1-way ANOVA with Pences: each age group has been assignedrows indicate a statistically significant dif

food labels (mean ¼ 3.70, SD ¼0.63). In addition, survey respondentsexpressed a high level of concernabout their diet (median ¼ 4.09),and many frequently used food labels(median ¼ 13; Table 2).

Knowledge of Nutrition andFood Label Information

Knowledge of calorie requirementsand nutrient content was low, andless than a quarter of the sample cor-rectly responded. Fewer than 25% ofrespondents correctly answered 4questions on natural and fresh claims,and fewer than half correctly re-sponded to 3 other questions in thiscategory. Fewer than 20% respon-dents correctly answered 3 questionson organic food. Based on food labelinformation that was provided, cor-rect calculations on sugar contentand fat content were performed by42.0% and 36.5% of the respondents,respectively. More respondents wereable to correctly calculate fat content(55.5%) and serving size (66.5%;Table 1).

social Factors Related to Food Label Use, an

20-29 (b; n ¼ 65) 30-39 (c; n ¼ 44) 40-5.98 (2.36) 6.11 (2.81)3.60d (0.62) 3.66d (0.60) 43.21d (0.75) 3.27d (0.63) 33.73 (0.58) 3.49 (0.57)4.09 (0.58) 4.04 (0.55)

13.75 (4.01) 11.61 (4.74)

< .05 and Tukey post-hoc for between-groa letter, eg, 10-19 year olds were assigned thference (at P # .05) with the respective age

Demographic Factors andAttitudes toward FoodLabel Use

The gender analysis shows minimaldifferences in psychosocial factorsamong male and female respondents.Female participants had a significantlyhigher level of DHC as opposed tomale respondents (t ¼ �2.18, P ¼.03; Table 3).

Comparisons by age showed signif-icant overall results in attitude, sub-jective norm, and food label use.Within these constructs, participantswho were 40-49 years old demon-strated significantly higher positiveattitudes (F ¼ 3.74, P ¼ .01) andperception of subjective norms(F ¼ 5.10, P ¼ .001) in comparison to20- to 29-year-old participants(P ¼ .01 and P < .001, respectively)and 30- to 39-year-old participants(subjective norms, P ¼ .01). No signif-icant between-group differences infood label use were detected (Table 4).

Analysis by ethnicity showed signif-icant overall differences across all psy-chosocial factors. Malays hadsignificantly higher positive attitudes(F ¼ 7.07, P < .001) toward food labelsas compared to Chinese (P< .001) andCaucasian (P¼ .01) respondents. Simi-larly, perceived subjective norms (F ¼3.99, P ¼ .01) related to food label usewere significantly higher amongMalays compared to Chinese (P ¼ .01)and Indian (P ¼ .02) respondents. Ma-lays also found food labels significantlyeasier to use (perceived behavioral con-trol; F¼ 3.53, P¼ .02) when comparedto Chinese respondents (P ¼ .02). In-dian respondents' diet-health concern(F¼ 4.10, P¼ .01) was highest among

d Actual Use of Food Labels,

49 (d; n ¼ 37) 50D (e; n ¼ 31) P5.35 (3.11) 6.63 (4.08) .64.02b,c (0.60) 3.64 (0.53) .01.82b,c (0.60) 3.39 (0.79) .003.78 (0.72) 3.84 (0.60) .144.28 (0.56) 3.98 (0.63) .29

13.91 (4.03) 13.14 (4.14) .02

up differences. Between-group differ-e letter a. Superscripted letters withingroup.

Table 5. Ethnic Differences in Psychosocial Factors Related to Food Label Use, and Actual Use of Food Labels, Mean Score (SD)

Variable (Maximum Score) Chinese (a; n ¼ 149) Malay (b; n ¼ 17) Indian (c; n ¼ 14) Caucasian (d; n ¼ 18) PKnowledge (18) 6.06 (2.80) 5.18 (3.20) 5.43 (4.15) 6.50 (4.64) .55Attitude (5) 3.66b (0.60) 4.32a,d (0.65) 3.91 (0.51) 3.70b (0.50) .00Subjective norm (5) 3.32b (0.73) 3.92a,c (0.64) 3.16b (0.65) 3.35 (0.69) .01Behavioral control (5) 3.62b (0.63) 4.08a (0.67) 3.81 (0.42) 3.87 (0.61) .02Diet-health concern (5) 4.03c (0.59) 4.36 (0.49) 4.50a (0.51) 4.01 (0.73) .01Food label use (19) 12.87 (4.14) 14.58 (3.73) 12.42 (3.57) 12.11 (5.60) .33

Note: Statistical test: 1-way ANOVA with P< .05 and Tukey post-hoc for between-group differences. Between-group differ-ences: each ethnic group has been assigned a letter, eg, Chinese was assigned the letter a. Superscripted letters indicatea statistically significant difference (at P # .05) with the respective ethnic group.

Industry should be urgedto engage nutritionists toparticipate in productdevelopment and promoteconsumers’ food labelknowledge.

Journal of Nutrition Education and Behavior � Volume 45, Number 3, 2013 Vijaykumar et al 209

the 4 groups and significantlyhigher than that of Chinese respon-dents (P ¼ .02; Table 5).

Predicting Intention to UseFood Labels with TPB and DHC

The regression model with TPB con-structs alone explained 18% of thevariance of intention to use food la-bels (P < .001). Attitudes, subjectivenorms, and perceived behavioral con-trol made significant contributions tothis model, with b weights of .21, .20,and .14, respectively. Diet-healthconcern proved to be a significantadditional predictor (b ¼ .26) and sig-nificantly enhanced the predictiveability of the model to 24% (P <.001). Intention to use food labels(b ¼ .38), predicted 14% of the vari-ance in actual food label use (P <.001; Tables 6 and 7).

DISCUSSION

This study found high-food label useamong Singapore's shoppers, positive

Table 6. Theory of Planned Behavior CoPredictors of Intention to Use Fo

Predictors

Model 1R2 ¼ 0.18 (P < .0

Intercept SE b

Constant 0.92 0.40 .02Attitudes 0.27 0.10 .21Subjective norms 0.22 0.08 .20Behavioral control 0.18 0.09 .14Diet-health concern – – –

SE indicates standard error.Note: Significance at P < .05. Linear regr

attitudes and DHC, but low levels ofknowledge and health literacy.Most notable was the low level ofknowledge pertaining to nutritionalcontent, natural/fresh claims, and or-ganic food. Although scholars havepreviously highlighted a similar needto improve nutrition knowledge,48

the issue needs to be considered inconjunction with low health literacylevels and high use of food labels.Low knowledge of frequently used in-formational and marketing strategiesin food labels and incorrect interpreta-tion of numerical information pre-sented in food labels are issues thatexpose individuals to 2 potential vul-nerabilities. First, low nutritionalknowledge can potentially prevent in-dividuals from using food labels, asthey might be unable to understandits educational benefits. Then, miscal-culating numerical information infood labels (Table 2) could adverselyinfluence their dietary choices, andthereby health outcomes. This argu-ment is anchored on evidence aboutthe influence of food labels on diet-

nstructs and Diet-Health Concern asod Labels (n ¼ 199)

01)Model 2

R2 ¼ 0.24 (P < .001)

P Intercept SE b P– �0.24 0.48 – .62.01 0.19 0.10 .15 .05.01 0.24 0.08 .22 < .01.04 0.19 0.09 .15 .03– 0.34 0.09 .26 < .001

ession model was used.

related behavioral factors.7 As previ-ously shown, consumers prefer foodclaims for their succinct communica-tion and may care less about seekinghealth information beyond suchclaims.49

The conundrum highlighted bythese findings—high food label usebut limited health literacy skills—ex-tends to countries beyond Singapore.Indeed, a study among immigrants inthe former Soviet Union showed thatalthough 55% of respondents always/often used a food label, only 32%had good label-reading skills andstruggled with numerical informa-tion.50 The fact that food labels arean increasingly common source ofnutritional information,51 with demo-nstrated effects on dietary choicesdespite consumers' inadequate com-prehension of information containedtherein,52,53 is cause for concern.

Demographic Analysis

The gender-based analysis revealedsignificantly greater DHC among fe-males. A possible explanation forthis trend emerges from correlatedstudies in nutritional behavior,54

which suggest that women are lesssatisfied with their weight and aremore prone to exercise restraint in

Tailoring programs thatfocus on basic nutritionprinciples and yieldhealthier eating behaviorsis needed to enhancenutrition knowledge.

210 Vijaykumar et al Journal of Nutrition Education and Behavior � Volume 45, Number 3, 2013

eating. Other research links thesetraits with issues such as body imageconsciousness55 and gender objectifi-cation.56

However, new contributions tounderstanding of food label use inthe East emerged from the demo-graphic analyses that help to identifynew audience segments for futurecommunication interventions. Forinstance, positive attitudes towardfood labels were found to be highestamong those who were 40-49 yearsold. This age segment could be an ef-fective link to reach both younger(adolescents, young adults) as wellas older (geriatric) populations fordisseminating health messages. Interms of ethnicity, positive attitudestoward food labels were found to behighest among Malaysian respon-dents. Nutrition educators couldlaunch their efforts by targeting Ma-lays and use members of this groupas catalysts to communicate withothers in their social networks. Otherresearchers have focused on explor-ing linkages between ethnicity andfood label use and examined ethnicdifferences in terms of ability to usespecific elements such as the nutri-tion information panel to find nota-ble differences.57 This study shednew light on this dimension by fo-cusing on ethnic differences in psy-chosocial factors related to use offood labels.

Involvement of multiplestakeholders public–

Theoretical Implications

The findings confirmed insights fromprevious research that demonstratethe significance of core TPB con-structs—attitudes, subjective norms,and behavioral control—in predictingbehavioral intention across a range ofhealth behaviors. In terms of relative

Table 7. Intention to Use Food labels as(n ¼ 199)

Predictor InterceptConstant 6.12Behavioral intention 2.03

SE indicates standard error.Note: Significance at P < .05. Linear regr

importance, however, behavioralcontrol (b ¼ .22) proved a strongerpredictor than attitudes (b ¼ .15) andsubjective norms (b ¼ .15). This find-ing is consistent with a study by Blan-chard and colleagues,58 in which theTPB was used to predict fruit andvegetable consumption (b ¼ .59 andb¼ .16 for behavioral control and atti-tudes, respectively). Attitudes couldbe stronger predictors of intention inother areas such as adoption ofplant-based diets.59 Subjective norms,as demonstrated by Zoellner and col-leagues,60 have traditionally provedto be weak predictors of intention,61

which could change when the behav-ior involves situations of a distinctlysocial nature such as a family meal(b ¼ .62).62 The fact that differentTPB constructs assume different levelsof importance based on the healthbehavior in question is known. Thisstudy demonstrates that expandingits application using constructsspecific to the problem in questionmight bolster the TPB's applicability.

In addition, it is important to rec-ognize the contribution of subjectivenorms and DHC in predicting inten-tion to use food labels. Food labeluse in public places such as super-markets involves a certain sociologi-cal dynamic that needs to beincreasingly considered by re-searchers in light of an increasinglyhealth- and image-conscious popu-

a Predictor of Total Food Label Use

Model 1R2 ¼ 0.14 (P < .001)

SE b P1.23 – < .0010.36 .38 < .001

ession model was used.

lace cognizant of weight loss andobesity issues.

The main limitation of this study isthat behavioral intention predictedonly 14% of the variance in actualuse of food labels. The unexplainedvariance indicated the presence ofmore factors acting on the data thatneed to be investigated in future re-search. The lowR2 could also be a func-tion of the cross-sectional design ofthis study. Scientists have previouslypointed out that an experimentalstudy with random subject assign-ments increases the predictivestrengthof intentions relative to a con-trol condition.61 The generalizabilityof findings from this study is limitedby a convenience sample, limited sam-ple size, and exclusion of non-English-speaking participants because of theEnglish-language questionnaire. Therepresentativeness of the samplingdis-tribution to the ethnic composition ofSingapore's population, and theproven efficiency of shop-interceptsurveys in food label research, partiallymitigate these limitations.

Practical Implications

It is important for practitioners to in-corporate demographic and culturalconsiderations into the design of edu-cational interventions. A deeper un-derstanding of the role of subjectivenorms in food label use can informnutrition education and counselingmodules by helping to identify thosesocial actors who could influence nor-mative beliefs among their clients andsubsequently using such actors to re-

private partnership inimplementing nutritioneducation programsfocusing on food label useis needed.

inforce educational messages. Futureresearch could expand the scale ofthe present study and further delveinto the new theoretical consider-ation of subjective norms highlightedhere. In addition, there is also a need

Journal of Nutrition Education and Behavior � Volume 45, Number 3, 2013 Vijaykumar et al 211

to extend food labeling studies be-yond shoppers to end users of foodproducts, for example, children andadolescents. Interdisciplinary researchbetween communication researchersand nutrition educators could engen-der an integrative approach to furtherunderstand the links between food la-bel use and psychosocial factors thatshape dietary choices.

ACKNOWLEDGMENTS

The authors would like to thank Sin-gapore's HPB for supporting thisstudy. The authors are grateful to GeXiaomin for assistance with revisions,and to the research assistants for helpwith data collection. The authorsthank all the respondents for partici-pating in the study.

SUPPLEMENTARY DATA

Supplementary data associated withthis article can be found in the onlineversion at http://dx.doi.org/10.1016/j.jneb.2012.09.001.

REFERENCES

1. InternationalMonetary Fund.RegionalEconomic Outlook: Asia and Pacific:Leading the Global Recovery: Reba-lancing for the Medium Term. http://www.imf.org/external/pubs/ft/reo/2010/apd/eng/areo0410.pdf. Published2010. Accessed December 20, 2012.

2. Pingali P. Westernization of Asian dietsand the transformation of food systems:Implications for research and policy.Food Policy. 2006;32:281-298.

3. Hossain P, Kawar B, El Nahas M. Obe-sity and diabetes in the developingworld—a growing challenge. N Engl JMed. 2007;356:213-215.

4. Soon G, Koh YH, Wong ML,Lam PW.Obesity Prevention and ControlEfforts in Singapore. Washington, DC:Center for Health and Aging; 2008.

5. Yoon KH, Lee JH, Kim JW, et al. Epi-demic obesity and type 2 diabetes inAsia. Lancet. 2006;368:1681-1688.

6. Borgmeier I, Westenhoefer J. Impact ofdifferent food label formats on healthi-ness evaluation and food choice of con-sumers: a randomized-controlled study.BMC Public Health. 2009;9:184. http://www.biomedcentral.com/1471-2458/9/184. Accessed January 8, 2013.

7. Ollberding NJ, Wolf RL, Contento I.Food label use and its relation to dietaryintake among US adults. J Am DietAssoc. 2010;110:1233-1237.

8. Wansink B, Chandon P. Can ‘‘low-fat’’nutrition labels lead to obesity? Journalof Marketing Research. 2006;XLIII:605-617.

9. Variyam JN. Do nutrition labels im-prove dietary outcomes? Health Econ.2008;17:695-708.

10. Drichoutis AC, Nayga JRM,Lazaridis P. Can nutritional label use in-fluence body weight outcomes? Kyklos.2009;62:500-525.

11. Caswell JA, Padberg DI. Towardamore comprehensive theory of food la-bels. Am J Agric Econ. 1992;74:460-468.

12. Jordan Lin C-T, Lee J-Y, Yen ST. Dodietary intakes affect search for nutrientinformation on food labels? Soc SciMed. 2004;59:1955-1967.

13. Loureiro ML, McCluskey JJ. Assessingconsumer response to Protected Geo-graphical Identification labeling. Agri-business. 2000;16:309-320.

14. Grunert K, Wills J. A review of Euro-pean research on consumer response tonutrition information on food labels. JPublic Health. 2007;15:385-399.

15. Guthrie JF, Fox JJ, Cleveland LE,Welsh S. Who uses nutrition labeling,and what effects does label use have ondiet quality? J Nutr Educ. 1995;27:163-172.

16. Gorton D, Ni Mhurchu C, Chen MH,Dixon R. Nutrition labels: a survey ofuse, understanding and preferencesamong ethnically diverse shoppers inNew Zealand. Public Health Nutr. 2009;12:1359-1365.

17. Hasler CM. Health claims in the UnitedStates: an aid to the public or a source ofconfusion? JNutr. 2008;138:1216S-1220S.

18. Cowburn G, Stockley L. Consumerunderstanding and use of nutrition la-belling: a systematic review. PublicHealth Nutr. 2005;8:21-28.

19. European Heart Network. A SystematicReview of the Research on ConsumerUnderstanding of Nutrition Labelling.Brussels, Belgium; 2003.

20. Soo-Jiuan T, Khai-Ling T. Antecedentsand consequences of skepticism towardhealth claims: an empirical investigationofSingaporeanconsumers. Journal ofMar-keting Communications. 2007;13:59-82.

21. Drichoutis AC, Lazaridis PN,Nayga RM Jr. Consumers use ofnutritional labels: a review of researchstudies and issues. Academy of MarketingScience Review. 2006;9. http://www

.amsreview.org/articles/drichoutis09-2006.pdf. Accessed January 8, 2013.

22. Nayga RM. Nutrition knowledge,gender, and food label use. J ConsumAff. 2000;34:97-112.

23. Stran K, Knol L. Determinants of FoodLabel Use among US Adults. Journal ofthe American Dietetic Association. 2011;111(9 suppl 1). A91.

24. Agri-Food & Veterinary, Authority ofSingapore. Food Labelling and Adver-tisements. http://www.ava.gov.sg/FoodSector/FoodLabelingAdvertisement/.Updated November 2, 2012. AccessedNovember 20, 2012.

25. Kozup JC, Creyer EH, Burton S. Mak-ing healthful food choices: the influenceof health claims and nutrition informa-tion on consumers’ evaluations of pack-aged food products and restaurantmenuitems. J Marketing. 2003;67:19-34.

26. Feunekes GI, Gortemaker IA,Willems AA, Lion R, van denKommerM. Front-of-pack nutrition la-belling: testing effectiveness of differentnutrition labelling formats front-of-pack in four European countries. Appe-tite. 2008;50:57-70.

27. Health Promotion Board. A Handbookon Nutrition Labelling (Singapore). http://www.sfma.org.sg/sfma/documents/Nutrition_Labelling_Handbook.pdf.Accessed December 20, 2012.

28. Singapore Heart Foundation. Mile-stones. http://www.myheart.org.sg/about-us/milestones/2/3. Accessed De-cember 20, 2012.

29. Superbrands. Superbrands Singapore.http://www.superbrands.com/sg/. Ac-cessed December 20, 2012.

30. Islamic Religious Council of Singa-pore. Singapore Halal Certification.http://www.muis.gov.sg/cms/services/hal.aspx?id=458. Accessed December20, 2012.

31. Parkinson L. The role of seals and certifi-cations of approval in consumer deci-sion-making. J Consum Aff. 1975;9:1-14.

32. Nayga RM, Lipinski D, Savur N. Con-sumers’ use of nutritional labels whilefood shopping and at home. J ConsumAff. 1998;32:106-120.

33. Coulson NS. An application of thestages of change model to consumeruse of food labels. Br Food J. 2000;102:661-668.

34. Lin C-TJ, Lee J-Y. Dietary fat intakeand search for fat information on foodlabels: new evidence. Consumer InterestsAnnual. 2003;49:1-3.

35. Bender MM, Derby BM. Prevalence ofreading nutrition and ingredient

212 Vijaykumar et al Journal of Nutrition Education and Behavior � Volume 45, Number 3, 2013

information on food labels among adultAmericans: 1982-1988. J Nutr Educ.1992;24:292-297.

36. Drichoutis AC, Lazaridis P,Nayga RM. Nutrition knowledge andconsumer use of nutritional food labels.Eur Rev Agric Econ. 2005;32:93-118.

37. Moorman C, Matulich E. A model ofconsumers’ preventive health behav-iors: the role of health motivation andhealth sbility. J Consum Res. 1993;20:208-228.

38. Kristal AR, Levy L, Patterson RE,Li SS, White E. Trends in food labeluse associated with new nutrition label-ing regulations. Am J Public Health.1998;88:1212-1215.

39. Smith SC, Taylor JG, Stephen AM.Use of food labels and beliefs aboutdiet–disease relationships among uni-versity students. Public Health Nutr.2000;3:175-182.

40. Obayashi S, Bianchi LJ, SongWO.Re-liability and validity of nutritionknowledge, social-psychological fac-tors, and food label use scales from the1995 Diet and Health Knowledge Sur-vey. J Nutr Educ Behav. 2003;35:83-92.

41. Ajzen I. The theory of planned behav-ior. Organ Behav Hum Decis Proc. 1991;50:179-211.

42. Pawlak R, Malinauskas B, Rivera D.Predicting intentions to eat a healthfuldiet by college baseball players: apply-ing the Theory of Planned Behavior. JNutr Educ Behav. 2009;41:334-339.

43. Yun D, Silk KJ. Social norms, self-identity, and attention to social com-parison information in the context ofexercise and healthy diet behavior.Health Commun. 2011;26:275-285.

44. Barreiro-Hurl�e J, Gracia A, de-Magistris T.Does nutrition informationon food products lead to healthier foodchoices? Food Policy. 2010;35:221-229.

45. Marietta AB, Welshimer KJ, LongAndersons S. Knowledge, attitudes,and behaviors of college students re-garding the 1990 Nutrition LabelingEducation Act food labels. J Am DietAssoc. 1999;99:445-449.

46. Mannell A, Brevard P, Nayga R Jr,Combris P, Lee R, Gloeckner J. Frenchconsumers’ use of nutrition labels. NutrFood Sci. 2006;36:159-168.

47. Department of Statistics Singapore.Population Trends 2012. http://www.singstat.gov.sg/pubn/popn/population2012b.pdf. Accessed December 20,2012.

48. Fitzgerald N, Damio G, Segura-P�erez S, P�erez-Escamilla R. Nutritionknowledge, food label use, and food in-take patterns among Latinas with andwithout type 2 diabetes. J Am Diet As-soc. 2008;108:960-967.

49. Williams P. Consumer understandingand use of health claims for foods.Nutr Rev. 2005;63:256-264.

50. Lubman N, Doak C, Jasti S. Food labeluse and food label skills among immi-grants from the former Soviet Union.J Nutr Educ Behav. 2012;44:398-406.

51. Goodman S, Hammond D, Pillo-Blocka F, Glanville T, Jenkins R. Useof nutritional information inCanada: na-tional trends between 2004 and 2008. JNutr Educ Behav. 2011;43:356-365.

52. Vermeer WM, Steenhuis IH,Leeuwis FH, Bos AE, de Boer M,Seidell JC. Portion size labeling and in-tended softdrinkconsumption: the impactof labeling format and size portfolio. JNutr Educ Behav. 2010;42:422-426.

53. Walters A, Long M. The effect of foodlabel cues on perceptions of quality andpurchase intentions among high-involvement consumers with varyinglevels of nutrition knowledge. J NutrEduc Behav. 2012;44:350-354.

54. Kiefer I, Rathmanner T, KunzeM. Eat-ing and dieting differences in men andwomen. J Mens Health Gend. 2005;2:194-201.

55. Frederick DA, Peplau LA, Lever J. Theswimsuit issue: correlates of body imagein a sample of 52,677 heterosexualadults. Body Image. 2006;3:413-419.

56. McKinley N. Longitudinal gender dif-ferences in objectified body conscious-ness and weight-related attitudes andbehaviors: cultural and developmentalcontexts in the transition from college.Sex Roles. 2006;54:159-173.

57. Gorton D, Ni Mhurchu C, Chen M-h,Dixon R. Nutrition labels: a survey ofuse, understanding and preferencesamong ethnically diverse shoppers inNew Zealand. Public Health Nutr.2009;12:1359-1365.

58. Blanchard CM, Fisher J, Sparling PB,et al. Understanding adherence to 5 serv-ings of fruits and vegetables per day:a theory of planned behavior perspec-tive. J Nutr Educ Behav. 2009;41:3-10.

59. Wyker BA, Davison KK. Behavioralchange theories can inform the predic-tion of young adults’ adoption ofa plant-based diet. J Nutr Educ Behav.2010;42:168-177.

60. Zoellner J, Estabrooks PA, Davy BM,Chen Y-C, You W. Exploring the the-ory of planned behavior to explainsugar-sweetened beverage consumption.J Nutr Educ Behav. 2012;44:172-177.

61. Web TL, Sheeran P. Does changing be-havioral intentions engender behaviorchange? A meta-analysis of the experi-mental evidence. Psychol Bull. 2006;132:249-268.

62. EtoK,KochP,Contento IR,AdachiM.Variables of the Theory of Planned Be-havior are associated with family mealfrequency among adolescents. J NutrEduc Behav. 2011;43:525-530.