Table Of ContentEpidemiology/Health Services Research
O R I G I N A L A R T I C L E
Diabetes-Related Behaviors in Latinas
and Non-Latinas in California
MATTHEW J. O’BRIEN, MD, MSC1,2,3,4 VICTOR A. ALOS, DMD, MPH1,3,4 (12) suggest that physical activity helps
ADAM DAVEY, PHD3 ROBERT C. WHITAKER, MD, MPH1,3,5 prevent diabetes. Many studies have ex-
aminedthe prevalenceof these diabetes-
relatedbehaviorsacrossracialandethnic
OBJECTIVEdCertaindietaryandphysicalactivitybehaviorshavebeenassociatedwiththe groups(13–24).However,almostnoneof
riskofdevelopingtype2diabetes,yetlittleisknownabouttheprevalenceofthesebehaviors this research involving Latinos analyzes
amongLatinas(Latinowomen).Thepurposeofthiscross-sectionalstudywastocomparethe
data separately for Latino women, even
prevalenceofdiabetes-relatedbehaviorsinLatinasandnon-Latinas.
though their lifetime risk of diabetes is
RESEARCHDESIGNANDMETHODSdUsingdata fromthe2009CaliforniaHealth almost 20% higher than Latino men (6).
InterviewSurvey,wecomparedself-reporteddiabetes-relatedbehaviorsofLatinas(n=4,321)to Dataontheprevalenceofdiabetes-related
non-Latinas(n=21,112)afterexcludingwomenwhowerepregnantorhaddiabetes.Forsix behaviors in Latinas might improve dia-
behaviors,wedeterminedthecutpointfortheleasthealthytertile:walking,doingmoderateto betes prevention efforts in this popula-
vigorous physical activity, and consuming fried potatoes, sugar-sweetened beverages (SSBs), tion. Highly effective lifestyle programs
desserts,andfastfood.WeusedlogisticregressiontoexaminetheassociationbetweenLatina to prevent diabetes by focusing on diet
ethnicityandbeingintheleasthealthytertilecomparedwiththeothertwotertilesforeachof
and physical activity already exist and
thesebehaviors.
havebeenstudiedindiversepopulations
RESULTSdInmultivariatemodelsadjustedforage,income,education,maritalstatus,health (25).
status,smoking,andacculturation,Latinashadahigherrisk(oddsratio[95%CI])ofbeinginthe Using a population-based sample
leasthealthytertilefortheconsumptionoffastfood(1.94[1.63–2.31]),SSBs(1.53[1.29–1.82]), from California (a state with ;7 million
andfriedpotatoes(1.32[1.18–1.67]),andlowerriskfordesserts(0.82[0.70–0.95]).Latinasand Latinas) (26), we examined differences
non-Latinashadsimilarphysicalactivitylevels. between Latinas and non-Latinas in the
prevalence of six diabetes-related behav-
CONCLUSIONSdDietarydifferencesbetweenLatinasandnon-Latinas(particularlyinthe
iors:walking,moderatetovigorousphys-
consumption of fast foodand SSBs)maybethe focus of interventions toprevent diabetesin
icalactivity(MVPA),andconsumptionof
Latinas. Further research among Latinas is needed to understand and modify these dietary
behaviors. fried potatoes, SSBs, desserts, and fast
food.Tomakeourfindingsusefultoclini-
DiabetesCare36:355–361,2013 ciansseekingtotailordiabetesprevention
messages to Latinas, we compared this
T
grouptonon-Latinas.Basedonourliter-
ype 2 diabetes results in a tremen- growing population (5). Compared with
aturereview,wehypothesizedthatLatina
dous public health and economic all other demographic groups, Latinas
ethnicity would be associated with less
burden,affectingalmost12%ofthe (Latinowomen)havethehighestlifetime
healthy dietary and physical activity be-
U.S. adult population (1) and costing risk of developing diabetes, estimated at
;$218billionannually(2).Thediabetes 53%(6).Reducingtheburdenofdiabetes haviors, compared with non-Latina eth-
nicity.
epidemic in the U.S. disproportionately in the U.S. requires a better understand-
affects Latinos, with the prevalence in ingofthefactorsunderlyingLatinas’high
RESEARCH DESIGN AND
Mexican-American adults being twice riskfordevelopingthisdisease.
METHODS
that of whites (3). The incidence and Numerous epidemiologic studies
prevalence of diabetes continue to rise haveidentifiedspecificdietaryandphys-
Study population
(4)alongwiththesizeoftheLatinopop- ical activity behaviors that impact diabe-
We used data from the adult question-
ulation,suggestingthattheburdenofdi- tes risk. Dietary risk factors include the
naire of the 2009 California Health Inter-
abetesontheU.S.healthcaresystemwill consumption of fried potatoes (7), fast
viewSurvey(CHIS),whichisrepresentative
increase in the future. In addition, high food (8), sugar-sweetened beverages
of the state’s noninstitutionalized civilian
ratesofoverweightandobesityinLatinos (SSBs)(9),anddesserts(10).Bothobser-
population18yearsofageorolder.CHIS
conferanincreasedriskofdiabetesinthis vational (11) and experimental studies
is a statewide, random-digit-dial tele-
phone survey sampling household tele-
c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c c
phonenumbers assignedto bothlandline
Fromthe1CenterforObesityResearchandEducation,TempleUniversity,Philadelphia,Pennsylvania;the and cellular service (27). One adult from
2Department ofInternalMedicine,SectionofGeneralInternalMedicine,TempleUniversitySchoolof each sampled household was randomly
Medicine,Philadelphia,Pennsylvania;the3DepartmentofPublicHealth,TempleUniversity,Philadelphia,
Pennsylvania;the4PuentesdeSaludHealthCenter,Philadelphia,Pennsylvania;andthe5DepartmentofPe- selectedtocompleteaninterview,conduc-
diatrics,TempleUniversitySchoolofMedicine,Philadelphia,Pennsylvania. ted either in English, Spanish, Chinese,
Correspondingauthor:MatthewJ.O’Brien,[email protected]. Vietnamese, or Korean. The overall re-
Received21March2012andaccepted28July2012. sponse rate for the CHIS adult interview
DOI:10.2337/dc12-0548
was 49% in 2009, which is comparable
©2013bytheAmericanDiabetesAssociation.Readersmayusethisarticleaslongastheworkisproperly
cited,theuseiseducationalandnotforprofit,andtheworkisnotaltered.Seehttp://creativecommons.org/ to other scientific telephone surveys con-
licenses/by-nc-nd/3.0/fordetails. ducted in California (27). Data were
care.diabetesjournals.org DIABETESCARE,VOLUME36,FEBRUARY2013 355
Diabetes-relatedbehaviorsinLatinas
collected on 28,186 women, who were the responses to questions about how calculated according to the methods de-
identifiedbasedonthequestion“Areyou many times they drank “regular soda or scribedbyVanWierenetal.(29),yielding
male or female?” After excluding women pop that contains sugar,” “sports or en- scores that ranged from 6 to 19 in our
whoreportedhavingdoctor-diagnoseddi- ergy drinks such as Gatorade, Red Bull, sample. We divided the subjects into
abetes and those currently pregnant, the and Vitamin water,” “sweetened fruit three acculturation levels: low (6–10),
analytic sample included 25,433 women: drinkssuchasKool-aid,cranberrydrink, medium (11–17), and high (18,19).
4,321 Latinas (17.0%) and 21,112 non- and lemonade,” and “coffee or tea with ThesecutpointsdividedtheLatinasam-
Latinas(83.0%). sugarorhoneyadded.”Foreachofthese pleintotertilesofacculturation.
questions, respondents were reminded
Diabetes-related behaviors nottoincludedietoptionswithartificial Data analysis
Foreachofsixdiabetes-relatedbehaviors, sweeteners. All analyses were conducted using Stata
wedeterminedthecutpointfortheleast Monthly “desserts” were assessed by SE, version 11.0 (Stata Inc., College Sta-
healthytertilefortheentireanalyticsam- combiningresponsestothefollowingtwo tion,TX).Inallstatisticaltesting,weused
ple. We used a cut point to make our questions: “Howoftendidyoueatcook- Stata survey commands, which adjust
analysis of behavior differences between ies, cake, pie, or brownies?” and “How variance estimates to account for the
Latinas and non-Latinas more under- oftendidyoueaticecreamorotherfrozen complex sample design of the CHIS
standable and useful for practitioners. desserts?”Participantswereinstructedto (30). All reported percentages were
We selected the tertile as the cut point not include sugar-free desserts. For fast weighted.Overall,theproportionofsub-
because there is no established level of food,participantswereinstructedto“in- jectswithmissingdataonanygivenvari-
these behaviors at which the risk of di- clude fast food meals eaten at work, ablewasverylow(,2%ofsample).The
abetesisknowntosharplyincrease.Inthe home, or fast food restaurants, carryout investigatorswhopreparedthepublically
currentstudy,theleasthealthytertilewas or drive through.” The following exam- availableCHISdatasetusedinouranaly-
defined as the lowest tertile for physical ples were provided: McDonald’s, Panda sis used hotdeck- and regression-based
activity behaviors and the highest tertile Express, and Taco Bell. Participants methods to impute missing data for
forthedietarybehaviorsexamined. wereasked,“Inthepastsevendays,how most study variables. Full procedures
Two physical activity measures were many times did you eat fast food?” Re- havebeendescribedelsewhere(27).
evaluated. Participants were asked two sponses to this question were multiplied Inallanalysesinvolvingthesixdiabetes-
questions about walking during the past by 4.3 to estimate the total number of related behaviors, we used binary varia-
week:“Howmanytimesdidyouwalkto times fast food was eaten in the last bles(theleasthealthytertilevs.theother
get some place that took you at least 10 month. two tertiles). Our key independent vari-
minutes?”and“Howmanytimesdidyou able, Latina ethnicity, was also binary
walk for at least 10 minutes for fun, re- Latina ethnicity (Latinavs.non-Latina).Usingx2tests,we
laxation, exercise, or to walk the dog?” Latina ethnicity was determined by the first examined the association between
Responses to these two questions were question “Are you Latino or Hispanic?” participantcharacteristicsandLatinaeth-
added to make a single variable called Women who responded “yes” were clas- nicity, followed by the association of di-
“walking,” which was the total number sifiedasLatinas,andthosewhoanswered abetes-related behaviors with Latina
oftimesperweektheparticipantwalked “no”wereclassifiedasnon-Latinas. ethnicity. We then calculated the unad-
for at least 10 min for any purpose. Par- justed odds of being in the least healthy
ticipants were asked about moderate Other participant characteristics tertile by each participant characteristic
physical activity during the previous Wealsoexaminedsevencharacteristicsof (potentially confounding variables).
week, such as bicycling, dancing, swim- participantsthatmightberelatedtoboth Using logistic regression models for
ming, and gardening: “On how many Latino ethnicity and the diabetes-related eachdiabetes-relatedbehavior,wecalcu-
days did you do any moderate physical behaviors. These characteristics, which latedtheoddsofLatinasbeingintheleast
activities in yourfree time forat least 10 mightconfoundtheprimaryrelationship healthytertile.Theseoddswereadjusted
minutes, other than walking?” In the understudy,includedthefollowing:age, in successive models, adding groups of
same manner, participants were asked householdincome(expressedaspercent- potentially confounding variables to the
howmanydaysinthelastweektheypar- age of the federal poverty threshold for unadjustedmodel:model1(age);model
ticipated for at least 10 min in vigorous household size), educational attainment, 2(socioeconomicstatus;model1variable
physical activities (ones that “take hard marital status, health status, smoking, +householdincome,education,andmar-
physical effort, such as aerobics, run- and acculturation. For health status, re- ital status); model 3 (health-related fac-
ning,soccer,fastbicycling,orfastswim- spondents were asked “Would you say tors; model 2 variables + health status
ming”). Responsestothesetwoquestions that in general your health is excellent, andsmokingstatus);andmodel4(accul-
were added to make a single variable, verygood,good,fair,orpoor?”Accultur- turation; model 3 variables + accultura-
MVPA. ation was assessed using a six-item mea- tion). Age was added separately because
Four dietary behaviors were exam- suredevelopedandvalidatedforusewith of the large differences between Latinas
ined: consumption of fried potatoes, CHIS (28). The six items addressed the andnon-Latinasthat,alone,mightsignif-
SSBs,desserts,andfastfood.Participants followingdomains:1)language(language icantly confound the relationships under
were asked how many times in the last spoken at home, language used to com- study.Thevariablesinthesocioeconomic
month they ate “any kind of fried pota- plete the survey, and self-reported En- and health groups were conceptually re-
toes, including French fries, home fries, glish proficiency); 2) nativity; 3) lated and made a priori. We added these
orhashbrowns.”Themonthlyconsump- durationofU.S.residence;and4)citizen- thematicgroupsofcovariatesintosucces-
tion of SSBs was assessed by combining ship status. An acculturation score was sive models to highlight their impact on
356 DIABETESCARE,VOLUME36,FEBRUARY2013 care.diabetesjournals.org
O’BrienandAssociates
the association between Latina ethnicity Table1dParticipantcharacteristics byLatinaethnicity
andthebehavioraloutcomes.
Thestudyprotocolwasapprovedby Characteristic n(%)a Latinas,%b Non-Latinas,%c Pvalued
the Temple University Institutional Re-
viewBoard. Age ,0.001
18–34years 3,234(31) 42 26
RESULTSdComparedwithnon-Latinas, 35–49years 5,845(30) 36 28
Latinas were younger, less educated, had 50–64years 8,117(24) 14 28
lowerincome,andreportedpoorerhealth $65years 8,237(15) 8 18
(Table1).Latinaswerealsolessaccultur- Householdincomee ,0.001
atedandlesslikelytosmoke.Latinaswere .300% 9,859(41) 20 50
less likely than non-Latinas to be in the 201–300% 4,230(16) 14 17
least healthy tertile for walking and des- 101–200% 5,487(20) 27 17
sert consumption, but they were more #100% 5,857(23) 39 16
likelytobeintheleasthealthytertilefor Education ,0.001
MVPAandthethreeotherdietarybehav- $College 10,095(35) 15 44
iors:consumingfriedpotatoes,fastfood, Somecollege 7,394(26) 23 28
andSSBs(Table2).Thesethreebehaviors Highschool 5,491(24) 27 22
were weakly correlated. The Spearman ,Highschool 2,453(15) 35 6
correlationcoefficientsbetweenthesebe- Maritalstatus ,0.05
havior variables (continuous measures) Married 13,526(61) 60 61
wereasfollows:SSBandfriedpotatocon- Formerlymarriedf 8,740(19) 17 20
sumption(0.13,P,0.001),SSBandfast Nevermarried 3,167(20) 23 19
foodconsumption(0.12,P,0.001),and Healthstatus ,0.001
fast food and fried potato consumption Excellent 5,319(21) 15 23
(0.28,P,0.001). Verygood 8,743(33) 23 38
Increasing age was associated with Good 7,018(30) 37 27
poorer physical activity behaviors and Fair 3,228(13) 21 9
improved dietary behaviors, with the Poor 1,125(3) 4 3
exceptionofdessertconsumption(Table Smokingstatus ,0.001
3).Thosewithlowerincomes,lesseduca- No 22,833(90) 94 88
tion,andpoorerself-reportedhealthwere Yes 2,600(10) 6 12
morelikelytobeintheleasthealthytertile Acculturationlevel ,0.001
of MVPA and SSB consumption. Those High 18,854(64) 34 77
with lower levels of acculturation and Medium 4,144(23) 32 19
smokers were also more likely to be in Low 2,435(13) 34 4
the leasthealthy tertileof SSB consump- aUnweightedsamplesizeandweightedpercentageineachstrataoftheparticipantcharacteristic.bWeighted
tion.However,thosewithlowerlevelsof percentageineachstrataoftheparticipantcharacteristicforLatinas.cWeightedpercentageineachstrataof
theparticipantcharacteristicfornon-Latinas.dPvaluesareforthedifferencebetweenLatinasandnon-Latinas
acculturationwerelesslikelytobeinthe
acrossstrataoftheparticipantcharacteristic.eHouseholdincomeasapercentageofthefederalpovertylevel.
unhealthy tertile for fried potato or des- fCategoryincludesthosewidowed,separated,ordivorced.
sertconsumptionorforwalking.
In unadjusted logistic regression
analyses, the largest differences between among Latinas. In fully adjusted models Alloftheadjusteddifferencesindiabetes-
Latinas and non-Latinas in unhealthy, (model4),Latinashadahigherrisk(odds related behaviors between Latinas and
diabetes-related behaviors were seen for ratio[OR][95%CI])ofbeingintheleast non-Latinas(Table4)werelargerinsep-
SSBandfastfoodconsumption(Table4). healthy tertile of fast food (1.94 [1.63– arateanalysescomparingLatinastonon-
Themagnitudeoftheassociationbetween 2.31]), SSBbeverage(1.53[1.29–1.82]), Latinawhites,thelargestracialsubgroup
Latinaethnicityandthesetwodietarybe- and fried potato consumption (1.32 of non-Latinas. By restricting our multi-
haviorsdecreasedaftercontrollingforage [1.18–1.67]). variatemodelstoMexican-AmericanLat-
(model 1). For SSBs, theassociationwas Infullyadjustedmodels,Latinashad inas vs. non-Latinas, the results were
further decreased by controlling for in- lower odds of being in the least healthy unchanged from those including all
come, education, and marital status tertile for two of the six diabetes-related Latinas. We addressed the potential
(model 2). Controlling both associations behaviors:dessertconsumption(OR0.82 role of obesity as a confounder by con-
for health status and smoking (model 3) [95% CI 0.70–0.95]) and MVPA (0.83 trollingourfinalmultivariatemodelsfor
hadlittleadditionalimpactonthemagni- [0.70–0.97]). The latter association obesity status, and we assessed obesity
tudeoftheseassociations.Finally,adjust- emerged only after adjusting for con- asaneffectmodifierbyrunningthesefi-
ing for acculturation had different founding variables. In the fully adjusted nalmodelsseparatelyforobeseandnon-
impacts on each of these associations model, there was no difference between obese subjects. We found no evidence
(model 4), as would be predicted by 1) Latinas and non-Latinas with respect to that obesity was either a confounder or
thedifferentrelationshipofacculturation walking(0.99[0.85–1.16]). aneffectmodifieroftherelationshipsbe-
tofastfoodandSSBconsumption(Table We conducted several additional tween the health behaviors and Latina
3)and2)thelowerlevelsofacculturation analyses for which data are not shown. ethnicity.
care.diabetesjournals.org DIABETESCARE,VOLUME36,FEBRUARY2013 357
Diabetes-relatedbehaviorsinLatinas
Table2dDiabetes-related behaviorsbyLatinaethnicity ethnicity on diabetes-related behaviors.
The data are from California, where the
Behaviora n(%)b Latinas,%c Non-Latinas,%d Pvaluee proportion of Latinas who are Mexican
American (77%) is higher than national
Walking ,0.001 estimates (65%), which may limit the
0–2times/week 10,798(39) 36 41 ability to generalize our findings (26).
3–5times/week 7,003(30) 30 30 ThenumberofLatinasfromothercoun-
$6times/week 7,632(31) 34 29 tries was too small to permit subgroup
MVPA 0.056 analyses in our study. In CHIS, the use
0days/week 9,562(38) 41 37 of different time frames (week and
1–3days/week 8,636(34) 33 34 month) for thedietary measures and the
$4days/week 7,235(28) 26 29 long recall period of one month might
Friedpotatoes 0.001 have resulted in inaccurate responses.
$4times/month 6,466(34) 37 33 However, we do not have reason to be-
1–3times/month 10,126(40) 40 40 lieve that these inaccuracies would have
0times/month 8,841(26) 23 27 differedbetweenLatinasandnon-Latinas.
SSB ,0.001 Our choice of non-Latinas as a com-
$31times/month 6,807(34) 49 29 parison group masks differences in di-
5–30times/month 7,359(32) 33 32 abetes-related behaviors among whites,
0–4times/month 11,267(33) 18 39 blacks, and Asians who comprise that
Desserts ,0.001 group. Including blacks in this group
$14times/month 9,894(36) 29 40 (who exhibit high levels of physical
5–13times/month 8,325(35) 36 34 inactivity and consumption of energy-
0–4times/month 7,214(29) 35 26 dense, nutrient-poor foods) (32) under-
Fastfood ,0.001 estimates differences in diabetes-related
$8times/month 5,398(30) 38 26 behaviorsbetweenwomenatthehighest
4–7times/month 6,570(28) 30 27 risk(i.e.,Latinas)andthoseatlowestrisk
0times/month 13,465(42) 32 47 (i.e., whites). Our sensitivity analysis
aEachbehaviorwasdividedintotertilesbasedonthereportedfrequencyofthebehavior.Becauseofthe comparingbehavioraloutcomesbetween
discreetnatureofthesurveyresponses,alltertilesdonotcontainexactlyone-thirdofthestudypopulation. Latinasandwhitewomenyieldedgreater
bUnweightedsamplesizeandweightedpercentageineachstrataofthediabetes-relatedbehavior.cWeighted differences in the same diabetes-related
percentageineachtertileofthediabetes-relatedbehaviorforLatinas.dWeightedpercentageineachtertileof
thediabetes-relatedbehaviorfornon-Latinas.ePvaluesareforthedifferencebetweenLatinasandnon-Latinas behaviors than those reported between
acrosstertilesofthediabetes-relatedbehavior. Latinas and non-Latinas. The observed
behavioral differences between Latinas
and non-Latinas may be explained, in
CONCLUSIONSdOur study shows large datasets. Studying 4,321 Latinas part, by cultural differences between
significant differences between Latinas helped produce reliable estimates of this these groups, which we could not mea-
and non-Latinas with respect to all population’s diabetes-related behaviors, sureinthecurrentstudy.Somehavesug-
diabetes-related behaviors examined, and the association of those behaviors gested that Latino Americans consider
except walking. Compared with non- withLatinaethnicity.UsingthislargeLa- consumingfastfoodandSSBsasastatus
Latinas,Latinashadhigheroddsofbeing tina cohort, we have produced some of symbol, which may influence their con-
frequent consumers of fried potatoes, the first reports of the prevalence of six sumption of these foods (33). Cultural
SSBs, and fast food. Of these unhealthy diabetes-related behaviors in this high- perceptions such as these should be ex-
dietary behaviors, the association with risk population. Another strength of our ploredfurtherinfutureresearch.
LatinaethnicitywaslargestforSSBsand studyisthepotentialclinicalutilityofthe Although previous studies have ex-
fast food. Although age, socioeconomic behavioraloutcomesexaminedhere.We amined racial and ethnic differences in
status, and acculturation confounded analyzedthesediabetes-relatedbehaviors the same diabetes-related dietary behav-
these relationships, the fully adjusted on a scale that we believe is most mean- iors studied here, most did not stratify
association of Latinaethnicity withpoor ingfulandusefultoclinicians,compared analysesbysex.Theonlystudyreporting
dietary behaviors suggests an indepen- withmorecomplexmetricsthatarediffi- any of these dietary behaviors in Latinas
denteffectofbeingLatinaonconsuming culttoincorporateinto lifestylecounsel- found that ;50% of Mexican-American
theseunhealthyfoodgroups.Latinashad ing efforts. Because Latinos’ health women drink regular soda (13). Latinas
lower odds of eating desserts frequently behaviorsareinfluencedbyacculturation in our study consumed more SSBs than
comparedwithnon-Latinas.Afteradjust- (31),ouruseofavalidatedacculturation non-Latinas.Incontrast,anationalstudy
ingforallcovariates,Latinaethnicitywas measure represents another potential byBleichetal.(14)estimatedthatMexican-
only modestly associated with MVPA. strength. However, this measure does American adults consume fewer calories
There was no association of Latina eth- not incorporate questions about cogni- from SSBs than whites or African Ameri-
nicity with walking in the fully adjusted tive,spiritual,oremotionalfactors,which cans.Thedifferentscalesusedtomeasure
model. arepartoftheacculturationprocess. SSBconsumptionandourexclusionofLa-
The greatest strength of this study is The cross-sectional nature of this tino males may help explain these differ-
itsinclusionofalargenumberofLatinas, study hinders our ability to draw causal ences. Other national studies (13,15,17)
whohavesmallerrepresentationinother inferences about the impact of Latina that have explored SSB consumption in
358 DIABETESCARE,VOLUME36,FEBRUARY2013 care.diabetesjournals.org
O’BrienandAssociates
Table3dUnadjusted oddsofbeingintheleasthealthytertile fordiabetes-related behaviorsbyparticipantcharacteristics
Walking MVPA Friedpotatoes SSBs Desserts Fastfood
Characteristic OR(95%CI)a OR(95%CI)b OR(95%CI)c OR(95%CI)d OR(95%CI)e OR(95%CI)f
Age
18–34years 1 1 1 1 1 1
35–49years 1.38(1.19–1.60) 1.16(0.98–1.37) 0.48(0.41–0.56) 0.80(0.69–0.93) 0.93(0.77–1.12) 0.58(0.50–0.68)
50–64years 1.31(1.11–1.52) 1.14(0.98–1.33) 0.33(0.28–0.39) 0.44(0.37–0.52) 0.97(0.82–1.15) 0.43(0.36–0.51)
$65years 2.10(1.77–2.48) 1.57(1.35–1.85) 0.24(0.20–0.29) 0.31(0.26–0.36) 1.52(1.26–1.83) 0.26(0.22–0.31)
Householdincomeg
.300% 1 1 1 1 1 1
201–300% 1.10(0.95–1.27) 1.24(1.06–1.45) 1.25(1.02–1.53) 1.39(1.13–1.71) 1.09(0.93–1.27) 1.40(1.12–1.74)
101–200% 0.99(0.85–1.16) 1.58(1.37–1.84) 1.20(1.04–1.38) 1.59(1.37–1.84) 0.99(0.86–1.14) 1.28(1.08–1.50)
#100% 0.82(0.71–0.97) 1.78(1.53–2.07) 1.08(0.89–1.30) 2.41(2.09–2.78) 0.81(0.68–0.97) 1.06(0.89–1.27)
Education
$College 1 1 1 1 1 1
Somecollege 0.92(0.78–1.09) 1.21(1.03–1.41) 1.50(1.26–1.79) 1.56(1.34–1.81) 0.80(0.68–0.92) 1.58(1.33–1.87)
Highschool 1.08(0.94–1.25) 1.45(1.24–1.70) 1.59(1.35–1.87) 1.64(1.41–1.91) 0.71(0.62–0.81) 1.69(1.42–2.01)
,Highschool 0.98(0.80–1.20) 1.89(1.55–2.31) 0.78(0.61–0.98) 2.81(2.25–3.5) 0.48(0.40–0.58) 1.24(0.95–1.63)
Maritalstatus
Married 1 1 1 1 1 1
Formerlymarriedh 1.16(1.00–1.35) 1.26(1.09–1.46) 0.81(0.68–0.97) 0.95(0.81–1.11) 1.04(0.89–1.23) 1.07(0.91–1.27)
Nevermarried 0.75(0.63–0.88) 0.88(0.74–1.06) 2.23(1.85–2.69) 1.23(1.04–1.46) 0.98(0.80–1.20) 2.20(1.84–2.62)
Healthstatus
Excellent 1 1 1 1 1 1
Verygood 1.14(0.98–1.32) 1.46(1.23–1.72) 1.38(1.16–1.64) 1.06(0.90–1.26) 1.06(0.91–1.24) 1.50(1.22–1.83)
Good 1.54(1.32–1.78) 2.45(2.06–2.91) 1.30(1.08–1.55) 1.62(1.36–1.93) 1.01(0.85–1.21) 1.57(1.28–1.91)
Fair 1.57(1.31–1.88) 3.17(2.53–3.99) 1.19(0.95–1.49) 1.80(1.46–2.23) 0.80(0.66–0.96) 1.78(1.41–2.25)
Poor 2.26(1.66–3.08) 4.37(3.11–6.13) 1.10(0.75–1.61) 1.59(1.16–2.18) 0.88(0.62–1.23) 1.45(0.91–2.31)
Smokingstatus
No 1 1 1 1 1 1
Yes 1.33(1.10–1.62) 1.13(0.93–1.36) 1.96(1.60–2.39) 2.40(1.98–2.92) 0.89(0.74–1.08) 1.53(1.23–1.92)
Acculturationlevel
High 1 1 1 1 1 1
Medium 0.90(0.79–1.03) 1.20(1.04–1.38) 0.63(0.54–0.74) 1.34(1.15–1.56) 0.67(0.58–0.78) 0.86(0.73–1.01)
Low 0.66(0.55–0.79) 1.90(1.56–2.32) 0.41(0.33–0.50) 2.05(1.73–2.44) 0.46(0.38–0.56) 0.50(0.41–0.61)
aLeasthealthytertile,walkingforatleast10min,0–2times/week.bLeasthealthytertile,MVPAforatleast10min,0days/week.cLeasthealthytertile,consumingfried
potatoes$4times/month.dLeasthealthytertile,consumingSSBs$31times/month.eLeasthealthytertile,consumingdesserts$14times/month.fLeasthealthytertile,
consumingfastfood$8times/month.gHouseholdincomeasapercentageofthefederalpovertylevel.hCategoryincludesthosewidowed,separated,ordivorced.
Latinos found similar levels to those re- Latinaethnicitywithfastfoodconsump- thannon-Latinas,incontrasttotwopre-
ported by Bleich et al. These studies in- tionwashigherthanforanyotherdietary vious studies (13,20) that examined
cludedonlyMexicanAmericans,whereas behaviorweexamined.Acculturationwas Frenchfriesastheonlyformoffriedpo-
ours included Latinas from other Latin strongly and positively associated with tatoes.
Americancountries.However,ourresults eating fast food in our cohort (Table 3). In contrast to the diet literature in
were unchanged when we restricted our Thisfindingisconsistentwiththosefrom U.S. Latinos, the physical activity litera-
analysistoMexican-Americanwomen.La- thefewstudiesthathaveexaminedaccul- turehasplacedagreaterfocusonLatinas
tinosinCaliforniamayhavedifferentpat- turation and fast food consumption byeitherrestrictinganalysestothisgroup
ternsofSSBconsumptionthanLatinosin within Latinos (17,34,35). With respect (19,24),stratifyingrace/ethnicityanalyses
otherpartsofthecountry,whichmayalso to the other dietary behaviors studied bysex(16),orstratifyingsex-basedanal-
help explain the observed discrepancy here, we found that Latinas eat desserts ysesbyrace/ethnicity(23).Inouranalysis
withnationallyrepresentativestudies. less frequently than non-Latinas, which (Table 2), 41% of Latinas reported no
Almost no research has focused on is consistent with previous reports MVPA,whichwasalmostidenticaltopre-
the differences in fast food consumption (20,21). However, our study and previ- viousreports(16,23).Afteradjustingfor
between Latinos and non-Latinos. One ous ones have not included questions covariates, however, we found that Lat-
studyreportedalowerprevalenceoffast about culturally specific desserts for Lat- inas were somewhat less likely to have
food consumption in Latinos compared inas, such as dulce de leche and flan, lowlevels ofMVPAthan non-Latinas. In
with non-Hispanic blacks and whites; which could lead to an underestimation our cohort, lower levels of income, edu-
however the authors did not adjust for of the frequency of consuming desserts cationalattainment,healthstatus,andac-
potential confounders in their analysis among Latinas. We found that Latinas culturation were associated with less
(22). In our study, the association of consume fried potatoes more frequently MVPA and Latina ethnicity. Adjusting
care.diabetesjournals.org DIABETESCARE,VOLUME36,FEBRUARY2013 359
Diabetes-relatedbehaviorsinLatinas
Table4dOddsofLatinas,comparedwithnon-Latinas,ofbeingintheleasthealthytertilefordiabetes-related behaviors
Unadjusted Model1 Model2 Model3 Model4
Behavior OR(95%CI) OR(95%CI)a OR(95%CI)b OR(95%CI)c OR(95%CI)d
Walkingatleast10min
(0–2times/week) 0.84(0.74–0.94) 0.91(0.80–1.03) 0.92(0.80–1.05) 0.91(0.80–1.05) 0.99(0.85–1.16)
MVPAatleast10min
(0days/week) 1.17(1.02–1.34) 1.25(1.09–1.44) 0.95(0.83–1.10) 0.90(0.78–1.04) 0.83(0.70–0.97)
Friedpotatoconsumption
($4times/month) 1.21(1.06–1.38) 0.96(0.83–1.11) 1.03(0.88–1.21) 1.09(0.93–1.29) 1.32(1.18–1.67)
SSBconsumption
($31times/month) 2.32(1.99–2.70) 1.98(1.69–2.32) 1.42(1.22–1.66) 1.54(1.31–1.82) 1.53(1.29–1.82)
Dessertconsumption
($14times/month) 0.61(0.54–0.69) 0.62(0.55–0.71) 0.73(0.63–0.84) 0.71(0.62–0.83) 0.82(0.70–0.95)
Fastfoodconsumption
($8times/month) 1.71(1.45–2.02) 1.44(1.21–1.72) 1.52(1.26–1.83) 1.55(1.29–1.86) 1.94(1.63–2.31)
aAdjustedforage(categorical).bAdjustedformodel1variable+householdincome(categorical)+education+maritalstatus.cAdjustedformodel2variables+health
status+smokingstatus.dAdjustedformodel3variables+acculturationlevel.
for these factors in our analysis may socialcontextsurroundingthesediabetes- States[articleonline],2011.Availablefrom
explain why Latina ethnicity was associ- related behaviors, and the role that SSBs www.cdc.gov/diabetes/pubs/pdf/ndfs_2011.
atedwithareducedriskoflowMVPA.We andfastfoodplayinLatinas’lives. pdf.Accessed23February2012
found that Latinas walked more fre- 2. DallTM,ZhangYD,ChenYJ,QuickWW,
YangWG,FogliJ.Theeconomicburden
quentlythannon-Latinasinourunadjusted
analysis, which may reflect increased ac- AcknowledgmentsdThis study was funded o2f9:d2i9ab7e–t3e0s.3HealthAff(Millwood)2010;
tive transportation and occupational bytheTempleUniversityDepartmentofMedi-
3. CowieCC,RustKF,FordES,etal.Fullac-
walking in Latinas (36), in addition to cineFacultyDevelopmentResearchAward.
countingofdiabetesandpre-diabetesinthe
the negative association of acculturation Nopotentialconflictsofinterestrelevantto U.S. population in 1988-1994 and 2005-
withwalkinginthispopulation(37).After thisarticlewerereported. 2006.DiabetesCare2009;32:287–294
M.J.O. was responsible for the study con-
adjusting for acculturation and other co- 4. NarayanKM,BoyleJP,GeissLS,Saaddine
ceptanddesign,acquisitionofthedata,anal-
variates in our multivariate model, there JB, Thompson TJ. Impact of recent in-
ysisandinterpretationofthedata,draftingof
wasnoassociationbetweenLatinaethnicity crease in incidence on future diabetes
the manuscript, and critical revision of the
andwalking. burden: U.S., 2005-2050. Diabetes Care
manuscript.A.D.helpedwiththestudycon- 2006;29:2114–2116
In conclusion, our study has identi- ceptanddesign,dataanalysis,andmanuscript
fied two diabetes-related behaviors (SSB revision. V.A.A. provided critical revision of 5. FlegalKM,CarrollMD,OgdenCL,Curtin
LR. Prevalence and trends in obesity
andfastfoodconsumption)thataremore themanuscriptandpreparedthemanuscript
among US adults, 1999-2008. JAMA
frequently performed by Latinas than for submission. R.C.W. contributed to the 2010;303:235–241
non-Latinas,andmaythereforerepresent study concept and design, analysis and in- 6. Narayan KM, Boyle JP, Thompson TJ,
important behavioral targets for diabetes terpretationofthedata,andcriticalrevisionof Sorensen SW, Williamson DF. Lifetime
themanuscript.M.J.O.istheguarantorofthis
prevention efforts in Latinas. These spe- risk for diabetes mellitus in the United
cificdietarybehaviorsmaybeparticularly work and, as such, had full access to all the States.JAMA2003;290:1884–1890
datainthestudyandtakesresponsibilityfor
effectivetargetsforlifestylecounselingby 7. LieseAD,WeisKE,SchulzM,ToozeJA.
theintegrityofthedataandtheaccuracyofthe
diverse health professionals. Given the Food intake patterns associated with in-
dataanalysis.
cident type 2 diabetes: the Insulin Re-
limitedtimetheydevoteto diabetespre- Thisstudywaspresentedinabstractformat
sistance Atherosclerosis Study. Diabetes
ventionwithat-risk patients(38),physi- the 72nd Scientific Sessions of the American Care2009;32:263–268
cians may find such discrete dietary Diabetes Association, Philadelphia, Pennsyl-
8. Pereira MA, Kartashov AI, Ebbeling CB,
targetsuseful.Asanotherexample,certi- vania,8–12June2012.
et al. Fast-food habits, weight gain, and
fied diabetes educators and nutritionists TheauthorswouldliketothankDrs.Jennifer insulin resistance (the CARDIA study):
maychoosetofocusonfastfoodandSSB O.FisherandGaryD.Foster(TempleUniver- 15-yearprospectiveanalysis.Lancet2005;
consumptionwhentakingmoredetailed sity)fortheircommentsonapreviousdraftof 365:36–42
themanuscript.Theauthorswouldalsoliketo
dietary histories and making dietary rec- 9. SchulzeMB,MansonJE,LudwigDS,etal.
thankSaraShuman(TempleUniversity)forher
ommendationsforLatinas.Futureresearch assistanceinpreparingthefinalversionofthe Sugar-sweetened beverages, weight gain,
shouldassesshowbesttoincorporatemes- andincidenceoftype2diabetesinyoung
manuscript.
and middle-aged women. JAMA 2004;
sages about reducing SSB and fast food
292:927–934
consumption into clinical encounters and
10. Johnson RK, Appel LJ, Brands M, et al.;
community-based diabetes prevention
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