Preventive Medicine 50 (2010) 148–154

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Preventive Medicine

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Are those who use specific complementary and alternative medicine therapies lesslikely to be immunized?

Lawrence Jones a,⁎, Christopher Sciamanna b, Erik Lehman b

a Penn State College of Medicine, Milton S. Hershey Medical Center, 35 Hope Dr., Suite 104, Hershey, PA 17033, USAb Penn State College of Medicine, Hershey, PA, USA

⁎ Corresponding author.E-mail address: ljones@psu.edu (L. Jones).

0091-7435/$ – see front matter © 2009 Elsevier Inc. Adoi:10.1016/j.ypmed.2009.12.001

a b s t r a c t

a r t i c l e i n f o

Available online 11 December 2009

Keywords:Complementary and alternative medicineImmunizationPreventionChiropracticHomeopathic

Objective. Some authorities are concerned that the use of complementary and alternative medications(CAM) may replace recommended preventive health practices. This study was done to determine if users ofindividual types of CAM were less likely to receive recommended immunizations.

Methods. We used data from the 2007 National Health Interview Survey of over 23,000 adult, non-institutionalized U.S. citizens using bivariate and multivariate analysis to determine if users of individualtypes of CAM were less likely to receive influenza and/or pneumococcal vaccinations.

Results. Using a weighted logistic regression analysis, we found that respondents who used chiropractic

care were less likely to receive flu shots (OR=0.68, CI=0.55,0.83, pb0.001). There was a mildly positivetrend toward receiving the pneumococcal vaccine in users of deep breathing exercises and toward notreceiving both in followers of qi gong. Prayer use was prevalent and had a positive impact on receivingimmunizations, especially in Blacks and those in poor health. Regular exercise, having a primary careprovider and more frequent office visits were also positively associated with receiving immunizations.

Conclusion. Chiropractic users are less likely to get flu shots, perhaps reflecting their national body'sattitude, which could affect morbidity and mortality. Providers should be aware of their patients' CAM useand encourage accepted primary care practices.

© 2009 Elsevier Inc. All rights reserved.

Introduction

Patients are increasingly turning to complementary and alterna-tive medicine (CAM) treat their conditions, either in conjunction withor instead of conventional treatment, and their numbers and usecontinue to grow (Eisenberg et al., 1998). In 2002 36% of Americanadults reported using some form of CAM therapy in the past year; ifprayer was included in the analysis, the rate rose to 62% (Barnes et al.,2004).

Because of the increasing popularity of CAM use, some expertshave raised the concern that its use may replace recommendedpreventative medical practices (Ernst, 2002, 1997; Robinson et al.,2002; Ernst, 2007) as people may pursue CAM therapies due to anunderlying interest in more “natural” treatments rather thanWesternmedical treatments. As a group, CAM users have been observed toreceive more, rather than less, preventive care (Stokley et al., 2008,Egede et al., 2002; Garrow and Egede, 2006) but it may be that users ofcertain individual therapies are less likely to receive recommendedcare. Two specific concerns are with influenza and pneumococcalvaccination. Both are highly recommended by virtually all govern-

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ment and private advisory panels (Bridges et al., 2002; Smith et al.,2006; CDC, 1997, 2007) but the positions of governing bodies of someof the most popularly used CAM treatments question their need. TheAmerican Chiropractic Association, for example, has a policy state-ment on vaccination that supports the “right to freedom of choice inhealth care matters and providing an alternative elective course ofaction regarding vaccination” (American Chiropractic Association,2000). A similar policy is supported by the American Association ofNaturopathic Physicians which states that it is “well documented”that current vaccinations are associated with “significant morbidityand are of variable efficacy and necessity… Safer and more effectivevaccinations should be developed, and more research should beconducted on possible short-term and long-term adverse effects ofvaccines currently in use” (American Association of NaturopathicPhysicians, 1991). Some CAM practitioners also express reservationsabout immunizations, saying that the influenza vaccine has “limitedor no effectiveness” (Homeopathy Today, 2005) and that it “gets themost-useless-vaccine-of-all-time award” (Aspinwall, 2004). Surveysof CAM providers (Halper and Berger, 1981; Simpson et al., 1995;Ernst and White, 1995; Lee and Kemper, 2000; Lehrke et al., 2001;Wilson et al., 2004) indicate that many do not actively recommendvaccination.

We were concerned that the use of certain CAM therapies maybe a marker for an individual who may be less likely to use

149L. Jones et al. / Preventive Medicine 50 (2010) 148–154

traditional, evidence-based treatments, possibly due to advicereceived by CAM practitioners. A previous study (Stokley et al.,2008) that showed a positive relationship between CAM use andpreventive care had collapsed CAM into a single category, which leftopen the question of whether certain individual therapies may bemarkers for reduced utilization of more proven therapies. Wepostulated that following these therapies might result in differencesin immunization rates in individuals who use different CAMtherapies or practices. Therefore, we decided to look at specificCAM therapies (for example, homeopathic or ayurveda) and groupsof therapies which, to our knowledge, has not been studied to thisdate to see if there is a difference in receiving recommendedimmunizations.

We used data from the 2007 update to the National HealthInterview Survey (NHIS) to understand the relationship between useof specific CAM therapies and the likelihood of receiving recom-mended preventive care. We chose to examine the rate of immuni-zation against influenza and pneumococcal disease since therecommendations for their use are well defined, their use is widelyaccepted among conventional practitioners as well as under suspicionby some CAM practitioners, and the data regarding their use are easilyavailable (Bridges et al., 2002; Smith et al., 2006; CDC, 1997, 2007,2008).

Methods

The NHIS is a nationwide, cross-sectional household survey of over28,000 American civilian, non-institutionalized adults covering a wide rangeof health care issues and including broad socioeconomic data. TheAlternative Health/Complementary and Alternative Medicine supplementcollected detailed data on the use of many types of CAM treatments andmodalities either within the past year or ever. For example, all participantswere asked: “Have you EVER seen a provider or practitioner for any of thefollowing for your own health?… Acupuncture.” It included ten types ofprovider-based therapies (e.g. homeopathy, acupuncture, massage) andseventeen other modalities (e.g. herbal treatment, deep breathing, prayer)for which a provider was not necessary. We chose to include only thegeneral category of using herbal treatment as the numbers of participantswho reported using specific herbs was very small (e.g. less than 1% ofrespondents reported using herbs such as chasteberry or Mexican yamcream).

We defined CAM use as a positive response to any of the therapiesincluded in the question “In the past 12 months have you seen a provider orpractitioner for any of the following for your own health?” (followed by alist of CAM therapies) or answering “yes” to any follow-up questionregarding receiving a specific therapy, treatment or modality. Becauseprayer use is so prevalent we analyzed the data both with prayer use andwithout.

Respondents were determined to have received the influenza vaccinationif they answered “yes” to the question “In the past 12 months have you had aflu shot?” and the pneumococcal vaccination if they answered “yes” to thequestion “Have you ever had a pneumonia shot?” We excluded participantsunder the age of 18 or who did not meet the eligibility criteria for theinfluenza and/or the pneumococcal vaccine. This eligibility was based ontheir responses to questions about their age and medical conditionsconsistent with CDC guidelines for who should receive the flu vaccine(CDC, 2007): age 50 years or older, history of cardiovascular disease, diabetes,kidney disease, individuals positive for HIV; and pneumococcal vaccine (CDC,1997, 2008): age 65 or above, history of cardiovascular disease, history ofchronic pulmonary disease, chronic liver disease, positive for HIV, history ofmalignancy.

Socioeconomic data were determined from self-reported responses onthe Adult Core and the Household and Family Core sections of the NHIS.We chose categories that were used in the NHIS which might have animpact on health care use and access. We divided the population into fourage categories: 18–34, 35–49, 50–64 and 65 and years and older. Ethnicitywas divided into white, black, Hispanic or other (multiracial) based on self-report and education was determined by self-report from the survey andwas also divided into categories: less than high school, high schoolgraduate or more than high school. Regional status was categorized as

Northeast, Midwest, South and West according to respondent's answers todemographic questions. Health insurance status was divided into private,public and uninsured. Current employment and income was determined byself-report and income was divided into b$20,000, $20,000–34,999,$35,000–54,999, $55,000–74,999, N$75,000 and employed but no incomelisted. Likewise, weekly exercise was determined by self-report in responseto the questionnaire and health status was divided into self-reportedcategories of excellent, very good, good, fair and poor. Previous studies(Stokley et al., 2008; Egede et al., 2002; Singleton et al., 2004) have showna positive association between immunization rates and the number ofphysician visits during the previous year. We derived this from responsesto NHIS questions and divided the reported number of visits within thepast 12 months into quartiles (none, 1, 2–3, 4+). Similarly, we evaluatedthe number of reported emergency room visits and divided the visits intonone, 1, 2–3 and 4+.

Statistical analysis

The final data set used in the analysis was generated from responders whohad used CAM therapy within the previous 12 months and, for comparison,those who needed an influenza and/or pneumococcal vaccination based onthe above inclusion criteria. Bivariate analysis was used to assess theassociation between demographics and CAM use. Multivariate analyseswere performed by weighted logistic regression using the sample surveyweights provided by NHIS to test the association of CAM use with thefollowing three outcomes adjusted for possible confounders: vaccinationagainst influenza only, vaccination against pneumococcus only and vaccina-tion against both. The final covariates chosen based on statistical and clinicalsignificance were gender, age, race, education, marital status, currentemployment, income, region, health insurance, weekly exercise, healthstatus, having a primary care provider, number of office visits and numberof emergency room visits and were included for adjustment in a weightedlogistic regression model for each outcome with each independent variablerelating to CAM use. This analysis generated model-based and model-adjusted odds ratios with 95% confidence limits, which quantify themagnitude and direction of any association between the CAM use variablesand the outcome variables.

Results

Table 1 describes the demographics of the sample. Out of the entiresample, 31% received a flu shot in the previous year, 18% received thepneumococcal vaccine and 13% received both. Of those needing bothvaccinations, 54% received the flu shot, 44% received the pneumo-coccal vaccine and 34% received both. Thirty-seven percent reportedusing some type of CAM within the past year; if prayer was includedthe number increased to 67%. More than half (59%) were female and amajority were 65 years of age and older (60%) andwhite (67%). A highpercentage had an education that was more than high school (44%),and the largest percentage (38%) were from the South. Most hadprivate insurance (54% vs. 38% with public insurance) and 8% wereuninsured.While a majority (64%) reported not exercising regularly, asignificant portion reported their health to be good, very good orexcellent. Eighty-eight percent have a primary care provider and 59%visited a provider's office at least 4 times in the previous 12 months.Most (72%) did not visit the emergency department within theprevious year.

The association between demographics and co-morbidities andreceiving immunizations is presented in Table 2. Without prayer,statistically significant positive associations (pb 0.001) includedfemale gender, age below 65, high school education or higher,current employment, weekly exercise, having a primary careprovider and having 4 or more office visits per year. Negativeassociations were Black or Hispanic race, residing in the Northeastor South, and poorer health status. If prayer is included females,Blacks, weekly exercisers, and those in poor health, with primarycare providers, higher office and ER visits and more co-morbiditieswere more likely to get immunized. There were no negativeassociations.

Table 1Demographics/co-morbidities by receiving influenza and/or pneumococcal vaccination and any CAM treatment in the past 12 months in the US, 2007.

Variable Totaln (%)

Received Fluvaccine (yes)

ReceivedPneumovaxvaccine (yes)

Received bothvaccines (yes)

Used CAMtreatment withprayer (yes)

Used CAMtreatment w/oprayer (yes)

Total starting sample 22777 (100) 6988 (31) 4055 (18) 2968 (13) 15318 (67) 8346 (37)Total needing both vaccinationsa 7406 (100) 3954 (54) 3155 (44) 2531 (34) 5574 (75) 2718 (37)Age (years)

18–34 457 (6) 95 (2) 55 (2) 16 (1) 358 (6) 231 (8)35–49 886 (12) 275 (7) 160 (5) 102 (4) 686 (12) 399 (15)50–64 1614 (22) 745 (19) 519 (16) 375 (15) 1272 (23) 657 (24)65+ 4449 (60) 2839 (72) 2421 (77) 2038 (81) 3258 (59) 1431 (53)

GenderMale 3064 (41) 1577 (40) 1200 (38) 977 (39) 2070 (37) 1028 (38)Female 4342 (59) 2377 (60) 1955 (62) 1554 (61) 3504 (63) 1690 (62)

RaceWhite 4928 (67) 2857 (72) 2436 (77) 1991 (79) 3581 (64) 1986 (73)Black 1133 (15) 509 (13) 365 (12) 272 (11) 983 (18) 295 (11)Hispanic 925 (12) 373 (9) 230 (7) 165 (6) 693 (12) 246 (9)Other 420 (6) 215 (6) 124 (4) 103 (4) 317 (6) 191 (7)

EducationLess than high school 1800 (24) 919 (23) 717 (23) 570 (23) 1397 (25) 384 (14)High school graduate 2324 (32) 1238 (32) 1049 (33) 831 (33) 1677 (30) 753 (28)More than high school 3204 (44) 1769 (45) 1376 (44) 1121 (44) (2458 (45) 1576 (58)

Marital StatusNever married 726 (10) 284 (7) 210 (7) 145 (6) 543 (10) 295 (11)Married 3460 (47) 1867 (47) 1408 (45) 1165 (46) 2557 (46) 1321 (49)Widowed/separated/divorced 3193 (43) 1793 (46) 1533 (48) 1218 (48) 2457 (44) 1095 (40)

Current employmentYes 2286 (31) 932 (24) 599 (19) 442 (17) 1710 (31) 1005 (37)No 5120 (69) 3022 (76) 2556 (81) 2089 (83) 3864 (69) 1713 (63)

IncomeUnemployed 4775 (65) 2883 (73) 2426 (77) 1995 (79) 3581 (64) 1526 (56)b$20,000 788 (11) 312 (8) 263 (8) 185 (7) 622 (11) 364 (13)$20,000–$34,999 509 (7) 206 (5) 120 (4) 89 (4) 397 (7) 231 (9)$35,000–$54,999 394 (5) 175 (4) 102 (3) 74 (3) 297 (5) 202 (8)$55,000–$74,999 176 (2) 77 (2) 41 (1) 31 (1) 137 (3) 93 (3)≥$75,000 187 (2) 59 (2) 48 (2) 32 (1) 141 (3) 109 (4)Employed, no income listed 569 (8) 242 (6) 155 (5) 125 (5) 392 (7) 190 (7)

RegionNortheast 1272 (17) 695 (18) 512 (16) 419 (16) 912 (16) 434 (16)Midwest 1719 (23) 955 (24) 776 (25) 626 (25) 1300 (23) 683 (25)South 2787 (38) 1429 (36) 1196 (38) 961 (38) 2166 (39) 894 (33)West 1628 (22) 875 (22) 671 (21) 525 (21) 1196 (22) 707 (26)

Health insurancePrivate 3974 (54) 2243 (57) 1755 (56) 1454 (57) 2984 (54) 1624 (60)Public 2821 (38) 1589 (40) 1302 (41) 1033 (41) 2136 (38) 869 (32)Uninsured 598 (8) 114 (3) 94 (3) 40 (2) 444 (8) 217 (8)

Weekly exerciseYes 2645 (36) 1529 (39) 1190 (38) 994 (39) 2075 (37) 1214 (45)No 4761 (64) 2425 (61) 1965 (62) 1537 (61) 3499 (63) 1504 (55)

Health statusExcellent 888 (12) 406 (10) 307 (10) 651 (13) 258 (14) 377 (14)Very good 1781 (24) 975 (25) 748 (24) 1158 (24) 476 (26) 753 (28)Good 2468 (33) 1336 (34) 1066 (34) 1612 (33) 637 (35) 857 (31)Fair 1591 (22) 875 (22) 709 (22) 1021 (21) 335 (18) 538 (20)Poor 678 (9) 362 (9) 325 (10) 433 (9) 126 (7) 193 (7)

Have primary care providerYes 6509 (88) 3706 (94) 2659 (94) 2410 (95) 5046 (91) 2483 (91)No 897 (12) 248 (6) 196 (6) 121 (5) 528 (9) 235 (9)

SmokerYes 1227 (17) 469 (12) 387 (12) 273 (11) 889 (16) 450 (17)No 6134 (83) 3463 (88) 2757 (88) 2249 (89) 4666 (84) 2264 (83)

Number of office visits—12 monthsNone 600 (8) 136 (4) 115 (4) 65 (3) 364 (6) 156 (6)1 visit 705 (10) 275 (7) 201 (6) 139 (6) 478 (9) 227 (8)2–3 visits 1694 (23) 877 (22) 670 (22) 537 (21) 1222 (22) 586 (22)4+ visits 4328 (59) 2628 (67) 2138 (68) 1765 (70) 3466 (63) 1734 (64)

Number of ER visits—12 monthsNone 5351 (72) 2807 (71) 2204 (70) 1764 (70) 3895 (70) 1906 (70)1 visit 1151 (16) 650 (16) 521 (17) 424 (17) 930 (17) 487 (18)2–3 visits 616 (8) 343 (9) 288 (9) 230 (9) 513 (9) 228 (8)4+ visits 271 (4) 148 (4) 136 (4) 107 (4) 230 (4) 95 (4)

Have co-morbidity—12 monthsb

Yes 5673 (77) 3221 (81) 2609 (83) 2122 (84) 4367 (78) 2113 (78)No 1733 (23) 733 (19) 546 (17) 409 (16) 1207 (22) 605 (22)

150 L. Jones et al. / Preventive Medicine 50 (2010) 148–154

Table 1 (continued)

Variable Totaln (%)

Received Fluvaccine (yes)

ReceivedPneumovaxvaccine (yes)

Received bothvaccines (yes)

Used CAMtreatment withprayer (yes)

Used CAMtreatment w/oprayer (yes)

Number of co-morbiditiesb

0 1733 (23) 733 (19) 546 (17) 409 (16) 1207 (22) 605 (22)1 3050 (41) 1594 (40) 1201 (38) 949 (37) 2280 (41) 1120 (41)2 1915 (26) 1112 (28) 945 (30) 774 (31) 1516 (27) 726 (27)N2 708 (10) 515 (13) 463 (15) 399 (16) 571 (10) 267 (10)

pb 0.01, ⁎⁎ pb 0.001, all comparisons made using logistic regression that accounts for stratification, clustering and weighting of complex survey designs.a Criteria based on CDC guidelines for flu shot (age N 50, cardiovascular disease, diabetes, kidney disease, positive for HIV) and pneumococcal vaccine (age N 65, cardiovascular

disease, chronic pulmonary disease, liver disease, positive for HIV, malignancy).b Co-morbidities include hypertension, heart disease, stroke, emphysema, peripheral vascular disease, congestive heart failure and cancer.

151L. Jones et al. / Preventive Medicine 50 (2010) 148–154

Table 3 outlines the weighted, adjusted logistic regression analysisof the association between CAM use in the past 12 months andreceiving either the influenza or the pneumococcal vaccines or both.Chiropractic care had a significantly negative association (pb 0.001)with receiving flu shots and there was a mildly negative trend with qigong toward not receiving both immunizations. Practicing deepbreathing exercises was mildly positively associated with receivingthe pneumococcal vaccine.

Discussion

There have been concerns raised that certain alternativeproviders may discourage the use of more traditional widelyaccepted treatments such as influenza and pneumococcal vaccina-tions (Ernst, 2002, 1997; Robinson et al., 2002; Ernst, 2007). Theprimary goal of our analysis was to see if this was true. With regardto chiropractic care and receiving the flu shot, this appears to be so.Chiropractic users are much less likely to report having the flu shot(OR=0.68, CI=0.55, 0.83, pb 0.001) possibly due to the negativeattitude of many chiropractors and their national body towardimmunizations (American Chiropractic Association). This is partic-ularly concerning because chiropractic care is one of the moreprevalent CAM therapies with 8% of respondents reporting use.Followers of qi gong, a program based on Chinese naturopathy,tended to not receive either immunization. While this was notstrongly statistically significant, it is a concern that practitionersmay be imparting a message to their followers that may place themat increased risk for more severe diseases. Fortunately, there wereno other significant negative associations with receiving therecommended immunizations. There was a mildly positive trendtoward receiving the pneumococcal vaccine in those who practicedeep breathing exercises.

Although not a part of our primary analysis, several otherassociations stand out. Prayer appears to have a significant impacton immunization, especially among Blacks and those in poor health.When prayer is factored out, only half the CAM users in thesecategories were likely to get both shots while those who reportpraying were much more likely to receive them (Table 2), perhapsreflecting the influence that religion has on attitudes toward health.Those who used prayer were also more likely to visit the ER andhad more co-morbidities than those who did not. Exercise, regard-less of prayer, also has a strong influence on receiving immuniza-tions, probably because of an active interest in overall health andprevention. They may also be more interested in following a morehealthy lifestyle, seeing CAM (perceived as more “natural” therapy)as an essential part of that lifestyle. Another conclusion is thatperhaps CAM use is a marker for a willingness to try differenttherapies as a complement (as opposed to an alternative) togenerally accepted treatments, i.e. they are choosing to try bothCAM and conventional medicine, not just one or the other. Likewise,and probably for similar reasons, having a primary care provider andvisiting the office (as opposed to the ER) more frequently makes it

much more likely that immunizations are received. One otherreason for the higher number of office visits is that the patientsmight be sicker. Some studies (Robinson et al., 2002; Egede et al.,2002; Garrow and Egede, 2006) have shown that patients whoused CAM did not have any more co-morbidities than those whodid not, while other authors (Birdee et al., 2008; Bertisch et al.,2008) show that CAM users report more medical problems. Ouranalysis indicates that CAM users (when prayer is excluded) withmore co-morbidities were no more likely to receive recommendedimmunizations.

Study limitations and strengths

Amajor strength of this study is the use of the complementary andalternative medicine arm of the NHIS, a broad-based, nationallyrepresentative sample of U.S. adults.

There were some limitations to this study. The reported use ofmany CAM treatments and therapies was very small, for example. Weattempted to control for the small sample sizes by groupingtreatments into categories such as alternative medical systems andbiologically based therapies and analyzing the data individually and ineach category as a whole.

The authors of the NHIS analysis also acknowledge somelimitations of the study questions. These depended on the respon-dents' knowledge of CAM therapies and/or their willingness toaccurately report use. In addition, the collection of CAM data at asingle point in time did not allow them to produce consecutive annualestimates for CAM and therefore any changes could not be trackedover time (Barnes et al., 2004).

It is also difficult to determine the effect of short-term versus long-term use of CAM therapies. To more accurately determine up-to-dateimmunization status, we chose to analyze whether respondentsreceived the recommended flu shot within the previous year and/orhad ever received the pneumococcal vaccine and whether they hadused CAM during that time. An alternative analysis might include dataon those who ever used CAM and the association with receiving theirimmunizations within the past year.

Also, the NHIS is a cross-sectional study and relies on re-collection and self-reporting. This makes it difficult to validate,however, self-reporting of influenza vaccination is considered tobe reliable (Nelson et al., 2001). The NHIS also included onlynon-institutionalized people. Thus, it did not survey a part of thepopulation, particularly nursing home and chronic care homeresidents, who make up a substantial portion of those whom author-ities strongly recommend should receive influenza and pneumococcalvaccinations.

Conclusions

This is the first study to our knowledge of a national represen-tation of respondents to assess whether the use of particular CAMtherapies affected receiving recommended immunizations. Our

Table 2Association between demographics/co-morbidities and receiving influenza and/or pneumococcal vaccination and any CAM treatment in the past 12 months in the US, 2007.

Variable Totaln (%)

Received Fluvaccine (yes)

Received Pneumovaxvaccine (yes)

Received bothvaccines (yes)

Used CAM treatmentwith prayer (yes)

Used CAM treatmentw/o prayer (yes)

Total starting sample 22777 (100) 6988 (31) 4055 (18) 2968 (13) 15318 (67) 8346 (37)Total needing both vaccinations 7406 (100) 3954 (54) 3155 (44) 2531 (34) 5574 (75) 2718 (37)Age (years)

18–34 457 (6) 0.12 (0.09, 0.15)⁎⁎ 0.11 (0.08, 0.16)⁎⁎ 0.05 (0.03, 0.09)⁎⁎ 1.44 (1.08, 1.92) 2.05 (1.59, 2.63)⁎⁎

35–49 886 (12) 0.23 (0.19, 0.27)⁎⁎ 0.16 (0.13, 0.20)⁎⁎ 0.13 (0.10, 0.17)⁎⁎ 1.28 (1.05, 1.57) 1.74 (1.44, 2.10)⁎⁎

50–64 1614 (22) 0.42 (0.36, 0.48)⁎⁎ 0.36 (0.31, 0.41)⁎⁎ 0.32 (0.28, 0.37)⁎⁎ 1.32 (1.11, 1.57)⁎ 1.38 (1.19, 1.60⁎⁎

65+ 4449 (60) Reference Reference Reference Reference ReferenceGender

Male 3064 (41) Reference Reference Reference Reference ReferenceFemale 4342 (59) 1.15 (1.03, 1.28) 1.25 (1.12, 1.39)⁎⁎ 1.20 (1.07, 1.33)⁎ 1.94 (1.70, 2.21)⁎⁎ 1.32 (1.19, 1.48)⁎⁎

RaceWhite 4928 (67) Reference Reference Reference Reference ReferenceBlack 1133 (15) 0.60 (0.52, 0.70)⁎⁎ 0.52 (0.45, 0.61)⁎⁎ 0.48 (0.40, 0.57)⁎⁎ 2.24 (1.79, 2.79)⁎⁎ 0.52 (0.43, 0.62)⁎⁎

Hispanic 925 (12) 0.50 (0.41, 0.61)⁎⁎ 0.35 (0.28, 0.43)⁎⁎ 0.32 (0.25, 0.41)⁎⁎ 1.09 (0.86, 1.38) 0.56 (0.46, 0.69)⁎⁎

Other 420 (6) 0.71 (0.54, 0.92) 0.48 (0.37, 0.62)⁎⁎ 0.50 (0.38, 0.65)⁎⁎ 1.00 (0.75, 1.35) 1.29 (0.98, 1.71)Education

Less than high school 1800 (24) Reference Reference Reference Reference ReferenceHigh school graduate 2324 (32) 1.11 (0.95, 1.29) 1.13 (0.98, 1.31) 1.09 (0.93, 1.28) 0.80 (0.68, 0.94)⁎ 1.53 (1.28, 1.83)⁎⁎

More than high school 3204 (44) 1.20 (1.03, 1.40) 1.01 (0.87, 1.18) 1.05 (0.89, 1.23) 0.96 (0.81, 1.13) 3.05 (2.57, 3.61)⁎⁎

Marital statusNever married 726 (10) Reference Reference Reference Reference ReferenceMarried 3460 (47) 2.23 (1.78, 2.78)⁎⁎ 1.76 (1.39, 2.24)⁎⁎ 2.36 (1.83, 3.04)⁎⁎ 1.07 (0.86, 1.34) 0.89 (0.72, 1.11)Widowed/separated/divorced 3193 (43) 2.45 (1.97, 3.05)⁎⁎ 2.47 (1.95, 3.13)⁎⁎ 2.95 (2.30, 3.79)⁎⁎ 1.30 (1.03, 1.66) 0.74 (0.58, 0.93)

Current employmentYes 2286 (31) 0.46 (0.41, 0.52)⁎⁎ 0.33 (0.29, 0.38)⁎⁎ 0.33 (0.29, 0.38)⁎⁎ 0.99 (0.87, 1.12) 1.51 (1.32, 1.71)⁎⁎

No 5120 (69) Reference Reference Reference Reference ReferenceIncome

Unemployed 4775 (65) Reference Reference Reference Reference Referenceb$20,000 788 (11) 0.43 (0.36, 0.51)⁎⁎ 0.45 (0.37, 0.54)⁎⁎ 0.40 (0.33, 0.50)⁎⁎ 1.25 (1.00, 1.55) 1.87 (1.56, 2.23)⁎⁎

$20,000–$34,999 509 (7) 0.42 (0.34, 0.53)⁎⁎ 0.28 (0.22, 0.36)⁎⁎ 0.27 (0.21, 0.36)⁎⁎ 1.17 (0.89, 1.54) 1.73 (1.38, 2.17)⁎⁎

$35,000–$54,999 394 (5) 0.49 (0.38, 0.64)⁎⁎ 0.28 (0.21, 0.37)⁎⁎ 0.29 (0.22, 0.39)⁎⁎ 0.97 (0.73, 1.29) 2.13 (1.64, 2.76)⁎⁎

$55,000–$74,999 176 (2) 0.50 (0.35, 0.71)⁎⁎ 0.26 (0.17, 0.41)⁎⁎ 0.29 (0.19, 0.47)⁎⁎ 1.14 (0.75, 1.73) 2.46 (1.73, 3.50)⁎⁎

≥$75,000 187 (2) 0.31 (0.22, 0.45)⁎⁎ 0.33 (0.22, 0.50)⁎⁎ 0.30 (0.19, 0.46)⁎⁎ 1.15 (0.76, 1.73) 2.98 (2.09, 4.25)⁎⁎

Employed, no income listed 569 (8) 0.46 (0.37, 0.58)⁎⁎ 0.32 (0.25, 0.41)⁎⁎ 0.35 (0.27, 0.46)⁎⁎ 0.78 (0.64, 0.96) 1.00 (0.79, 1.27)Region

Northeast 1272 (17) 1.14 (0.93, 1.40) 0.94 (0.79, 1.12) 1.01 (0.83, 1.24) 0.88 (0.72, 1.07) 0.64 (0.53, 0.76)⁎⁎

Midwest 1719 (23) 1.14 (0.93, 1.40) 1.04 (0.87, 1.24) 1.09 (0.90, 1.33) 1.11 (0.92, 1.35) 0.83 (0.69, 0.99)South 2787 (38) 0.96 (0.81, 1.13) 1.01 (0.86, 1.19) 1.04 (0.87, 1.24) 1.26 (1.03, 1.52) 0.58 (0.50, 0.69)⁎⁎

West 1628 (22) Reference Reference Reference Reference ReferenceHealth insurance

Private 3974 (54) 4.79 (3.68, 6.23)⁎⁎ 3.64 (2.74, 4.83)⁎⁎ 6.28 (4.20, 9.39)⁎⁎ 1.07 (0.84, 1.35) 1.20 (0.97, 1.49)Public 2821 (38) 5.15 (3.95, 6.71)⁎⁎ 4.72 (3.57, 6.25)⁎⁎ 7.18 (4.80, 10.75)⁎⁎ 1.07 (0.84, 1.37) 0.77 (0.62, 0.96)Uninsured 598 (8) Reference Reference Reference Reference Reference

Weekly exerciseYes 2645 (36) 1.24 (1.10, 1.40)⁎⁎ 1.09 (0.96, 1.23) 1.19 (1.05, 1.35)⁎ 1.34 (1.17, 1.54)⁎⁎ 1.80 (1.60, 2.02)⁎⁎

No 4761 (64) Reference Reference Reference Reference ReferenceHealth status

Excellent 888 (12) Reference Reference Reference Reference ReferenceVery good 1781 (24) 1.44 (1.20, 1.74)⁎⁎ 1.37 (1.13, 1.67)⁎ 1.49 (1.21, 1.82)⁎⁎ 1.12 (0.89, 1.40) 0.90 (0.75, 1.09)Good 2468 (33) 1.36 (1.14, 1.62)⁎⁎ 1.48 (1.22, 1.79)⁎⁎ 1.42 (1.16, 1.74)⁎⁎ 1.14 (0.94, 1.38) 0.68 (0.56, 0.82)⁎⁎

Fair 1591 (22) 1.43 (1.18, 1.73)⁎⁎ 1.64 (1.35, 2.01)⁎⁎ 1.59 (1.29, 1.97)⁎⁎ 1.43 (1.15, 1.78)⁎ 0.66 (0.54, 0.81)⁎⁎

Poor 678 (9) 1.28 (1.01, 1.63) 2.02 (1.57, 2.59)⁎⁎ 1.66 (1.28, 2.14)⁎⁎ 1.69 (1.26, 2.26)⁎⁎ 0.49 (0.38, 0.64)⁎⁎

Have primary care providerYes 6509 (88) 3.19 (2.64, 3.85)⁎⁎ 3.06 (2.47, 3.79)⁎⁎ 3.68 (2.89, 4.68)⁎⁎ 2.37 (1.98, 2.84)⁎⁎ 1.84 (1.50, 2.25)⁎⁎

No 897 (12) Reference Reference Reference Reference ReferenceSmoker

Yes 1227 (17) 0.40 (0.35, 0.47)⁎⁎ 0.51 (0.43, 0.59)⁎⁎ 0.42 (0.36, 0.50)⁎⁎ 0.86 (0.73, 1.02) 1.00 (0.86, 1.17)No 6134 (83) Reference Reference Reference Reference Reference

Number of office visits—12 monthsNone 600 (8) Reference Reference Reference Reference Reference1 visit 705 (10) 2.08 (1.59, 2.72)⁎⁎ 1.72 (1.22, 2.43)⁎ 1.99 (1.34, 2.97)⁎⁎ 1.17 (0.88, 1.53) 1.29 (0.99, 1.70)2–3 visits 1694 (23) 3.35 (2.62, 4.28)⁎⁎ 2.81 (2.13, 3.71)⁎⁎ 3.76 (2.68, 5.27)⁎⁎ 1.66 (1.30, 2.12)⁎⁎ 1.46 (1.12, 1.90)⁎

4+ visits 4328 (59) 4.76 (3.74, 6.07)⁎⁎ 4.16 (3.15, 5.50)⁎⁎ 5.62 (4.01, 7.86)⁎⁎ 2.38 (1.92, 2.96)⁎⁎ 1.85 (1.46, 2.33)⁎⁎

Number of ER visits—12 monthsNone 5351 (72) Reference Reference Reference Reference Reference1 visit 1151 (16) 1.24 (1.06, 1.44)⁎ 1.18 (1.02, 1.36) 1.21 (1.04, 1.41) 1.61 (1.35, 1.92)⁎⁎ 1.22 (1.04, 1.42)2–3 visits 616 (8) 1.0 (0.81, 1.23) 1.22 (1.0, 1.49) 1.15 (0.94, 1.41) 1.91 (1.46, 2.50)⁎⁎ 1.06 (0.85, 1.32)4+ visits 271 (4) 1.06 (0.78, 1.45) 1.35 (1.0, 1.82) 1.33 (1.0, 1.78) 2.16 (1.43, 3.25)⁎⁎ 1.03 (0.76, 1.39)

Have co-morbidity—12 monthsa

Yes 5673 (77) 1.82 (1.59, 2.10)⁎⁎ 1.90 (1.65, 2.18)⁎⁎ 1.95 (1.68, 2.26)⁎⁎ 1.48 (1.29, 1.69)⁎⁎ 1.09 (0.96, 1.24)No 1733 (23) Reference Reference Reference Reference Reference

152 L. Jones et al. / Preventive Medicine 50 (2010) 148–154

Table 2 (continued)

Variable Totaln (%)

Received Fluvaccine (yes)

Received Pneumovaxvaccine (yes)

Received bothvaccines (yes)

Used CAM treatmentwith prayer (yes)

Used CAM treatmentw/o prayer (yes)

Number of co-morbiditiesa

0 1733 (23) Reference Reference Reference Reference Reference1 3050 (41) 1.51 (1.30, 1.76)⁎⁎ 1.43 (1.23, 1.67)⁎⁎ 1.47 (1.25, 1.74)⁎⁎ 1.34 (1.15, 1.56)⁎⁎ 1.08 (0.94, 1.25)2 1915 (26) 1.88 (1.60, 2.20)⁎⁎ 2.13 (1.83, 2.48)⁎⁎ 2.16 (1.85, 2.52)⁎⁎ 1.60 (1.34, 1.92)⁎⁎ 1.13 (0.96, 1.33)N2 708 (10) 4.19 (3.32, 5.29)⁎⁎ 4.72 (3.83, 5.82)⁎⁎ 4.56 (3.66, 5.68)⁎⁎ 1.89 (1.50, 2.39)⁎⁎ 1.03 (0.84, 1.27)

⁎ pb 0.01, ⁎⁎ pb 0.001, all comparisons made using logistic regression that accounts for stratification, clustering and weighting of complex survey designs.a Co-morbidities include hypertension, heart disease, stroke, emphysema, peripheral vascular disease, congestive heart failure and cancer.

153L. Jones et al. / Preventive Medicine 50 (2010) 148–154

initial assumption was that there would be a negative associationof some practices and therapies to receiving immunizations, and,indeed, those who used chiropractic care were much less likely toreceive flu shots. Chiropractic use is quite prevalent, and thediscouragement of such a widely accepted, cheap and readily acces-sible primary preventive modality could have a significant effect onmorbidity and mortality in this country. As long as providers and

Table 3Association between CAM use in the past 12 months and receiving influenza and/or pneum

Variable Totaln (%)

Revac

Total needing both vaccinationsa 7406 (100) 39Used any CAM therapy with prayer 5574 (75) 1.Used any CAM therapy without prayer 2718 (37) 0.Number of CAM therapies used with prayer0 1832 (25) Re1 1683 (23) 1.2 2265 (30) 1.N2 1626 (22) 0.

Number of CAM therapies used without prayer0 4686 (63) Re1 1494 (20) 0.2 592 (8) 0.N2 632 (9) 0.

Alternative medical systems 197 (3) 0.Acupuncture 93 (1) 0.Ayurveda 3 (b1) 0.Homeopathy 101 (1) 0.Naturopathy 27 (b1) 0.

Biologically based therapies 1554 (21) 0.Chelation 7 (b1) 1.Herbs 1438 (20) 0.Vegetarian diet 124 (2) 0.Macrobiotic diet 5 (b1) 1.Atkins diet 67 (1) 0.Pritkin diet 0 (0) NAOrnish diet 4 (b1) 6.Zone diet 5 (b1) 0.

Manipulative and body-based therapies 867 (12) 0.Chiropractic care 563 (8) 0.Massage 429 (6) 1.

Mind–body therapies 5097 (69) 1.Biofeedback 8 (b1) 2.Meditation 707 (10) 0.Guided imagery 143 (2) 1.Progressive relaxation 185 (3) 0.Deep breathing exercises 952 (13) 1.Hypnosis 20 (b1) 2.Yoga 221 (3) 0.Tai Chi 77 (1) 1.Qi Gong 22 (b1) 0.Prayed for own health 4554 (63) 1.Others prayed for your health 2960 (41) 1.Energy healing/Reiki 32 (b1) 0.

pb 0.01, ⁎⁎ pb 0.001, all comparisons made using logistic regression that accounts for stratirace, education, marital status, income, region, health insurance, office visits, smoking and

a Criteria based on CDC guidelines for flu shot (age N 50, cardiovascular disease, diabetesdisease, chronic pulmonary disease, liver disease, positive for HIV, malignancy).

organizations continue to discourage these practices, immunizationrates will fall short of national goals, so it will be important tocontinue to monitor our patients' use of these modalities and toensure that recommended preventive practices are followed.

Conflict of interest statementThe authors have no conflicts of interest.

ococcal vaccination in the US, 2007.

ceived Flucine (yes)

Received Pneumovaxvaccine (yes)

Received bothvaccines (yes)

54 (54) 3155 (44) 2531 (34)04 (0.90, 1.20) 1.14 (0.98, 1.34) 0.99 (0.84, 1.17)90 (0.78, 1.03) 1.14 (1.00, 1.31) 1.02 (0.89, 1.17)

ference Reference Reference04 (0.88, 1.23) 0.98 (0.82, 1.17) 0.90 (0.74, 1.08)13 (0.96, 1.34) 1.20 (0.99, 1.45) 1.03 (0.85, 1.25)92 (0.76, 1.11) 1.29 (1.05, 1.59) 1.07 (0.87, 1.31)

ference Reference Reference95 (0.80, 1.12) 1.16 (1.00, 1.34) 1.04 (0.88, 1.22)94 (0.75, 1.17) 1.18 (0.92, 1.50) 1.04 (0.82, 1.33)74 (0.59, 0.93) 1.08 (0.85, 1.37) 0.95 (0.74, 1.22)69 (0.48, 1.10) 1.06 (0.72, 1.56) 1.07 (0.73, 1.56)86 (0.52, 1.42) 1.15 (0.69, 1.91) 1.28 (0.76, 2.16)28 (0.03, 2.65) 0.74 (0.09, 6.26) 1.37 (0.20, 9.66)62 (0.37, 1.04) 1.04 (0.63, 1.71) 1.04 (0.62, 1.72)38 (0.14, 1.04) 0.56 (0.21, 1.47) 0.34 (0.11, 1.10)85 (0.74, 0.98) 1.05 (0.91, 1.21) 1.02 (0.88, 1.19)06 (0.20, 5.67) 1.10 (0.20, 5.95) 0.36 (0.06, 2.30)87 (0.74, 1.0) 1.10 (0.95, 1.28) 1.09 (0.93, 1.28)86 (0.47, 1.57) 0.95 (0.54, 1.67) 0.81 (0.40, 1.62)58 (0.18, 14.18) 4.95 (0.43, 57.63) 7.97 (0.69, 95.53)85 (0.43, 1.68) 0.82 (0.42, 1.59) 0.53 (0.23, 1.22)

NA NA45 (1.43, 29.19) 7.80 (0.21, 284.95) 3.39 (0.44, 26.25)62 (0.08, 4.56) 2.24 (0.34, 14.82) 1.31 (0.12, 14.14)80 (0.67, 0.96) 0.82 (0.68, 1.0) 0.86 (0.70, 1.04)68 (0.55, 0.83)⁎⁎ 0.76 (0.61, 0.95) 0.80 (0.64, 1.02)01 (0.78, 1.31) 0.95 (0.73, 1.24) 0.97 (0.73, 1.28)10 (0.95, 1.26) 1.21 (1.03, 1.42) 1.09 (0.92, 1.27)01 (0.25, 16.28) NA 5.65 (0.47, 68.35)90 (0.72, 1.14) 1.25 (0.99, 1.56) 1.07 (0.84, 1.36)15 (0.72, 1.85) 1.06 (0.69, 1.63) 1.03 (0.63, 1.69)86 (0.59, 1.25) 1.31 (0.91, 1.88) 0.91 (0.62, 1.33)06 (0.88, 1.28) 1.41 (1.15, 1.74)⁎ 1.29 (1.06, 1.58)63 (0.95, 7.29) 1.05 (0.29, 3.73) 0.70 (0.15, 3.27)96 (0.66, 1.39) 0.84 (0.58, 1.21) 0.92 (0.60, 1.40)07 (0.57, 2.0) 0.61 (0.35, 1.06) 0.78 (0.43, 1.43)58 (0.17, 2.02) 0.29 (0.10, 0.84) 0.05 (0.01, 0.46)⁎12 (0.98, 1.28) 1.19 (1.02, 1.39) 1.07 (0.91, 1.26)04 (0.91, 1.19) 1.25 (1.09, 1.45)⁎ 1.15 (1.0, 1.33)58 (0.21, 1.57) 0.90 (0.30, 2.73) 1.08 (0.29, 3.97)

fication, clustering and weighting of complex survey designs adjusted for age, gender,having at least one co-morbidity., kidney disease, positive for HIV) and pneumococcal vaccine (age N 65, cardiovascular

154 L. Jones et al. / Preventive Medicine 50 (2010) 148–154

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