Published on in Vol 3, No 1 (2017): Jan-Mar

The Annual American Men’s Internet Survey of Behaviors of Men Who Have Sex With Men in the United States: 2015 Key Indicators Report

The Annual American Men’s Internet Survey of Behaviors of Men Who Have Sex With Men in the United States: 2015 Key Indicators Report

The Annual American Men’s Internet Survey of Behaviors of Men Who Have Sex With Men in the United States: 2015 Key Indicators Report

Rapid Surveillance Report

Rollins School of Public Health, Department of Epidemiology, Emory University, Atlanta, GA, United States

Corresponding Author:

Maria Zlotorzynska, PhD, MPH

Rollins School of Public Health

Department of Epidemiology

Emory University

GCR 410

1518 Clifton Rd NE

Atlanta, GA, 30322

United States

Phone: 1 404 727 8799

Fax:1 404 727 8737

Email: maria.zlotorzynska@emory.edu


The American Men’s Internet Survey (AMIS) is an annual Web-based behavioral survey of men who have sex with men (MSM) living in the United States. This Rapid Surveillance Report describes the third cycle of data collection (September 2015 through April 2016; AMIS-2015). The key indicators are the same as previously reported for AMIS (December 2013-May 2014, AMIS-2013; November 2014-April 2015, AMIS-2014). The AMIS survey methodology has not substantively changed since AMIS-2014. MSM were recruited from a variety of websites using banner advertisements and email blasts. Additionally, participants from AMIS-2014 who agreed to be recontacted for future research were emailed a link to the AMIS-2015 survey. Men were eligible to participate if they were age 15 years and older, resided in the United States, provided a valid US ZIP code, and reported ever having sex with a man. We examined demographic and recruitment characteristics using multivariable regression modeling (P<.05) stratified by participants’ self-reported human immunodeficiency virus (HIV) status. The AMIS-2015 round of data collection resulted in 10,217 completed surveys from MSM representing every US state and Puerto Rico. Participants were mainly non-Hispanic white, older than 40 years, living in the US South, living in urban areas, and recruited from general social networking websites. Self-reported HIV prevalence was 9.35% (955/10,217). Compared to HIV-negative/unknown status participants, HIV-positive participants were more likely to have had anal sex without a condom with any male partner in the past 12 months (75.50%, 721/955 vs 63.09%, 5843/9262, P<.001) and more likely to have had anal sex without a condom with a serodiscordant or unknown status partner (34.45%, 329/955 vs 17.07%, 1581/9262, P<.001). The reported use of marijuana and other illicit substances in the past 12 months was higher among HIV-positive participants than HIV-negative/unknown status participants (marijuana use: 24.61%, 235/955 vs 22.96%, 2127/9262; other illicit substance use: 28.59%, 273/955 vs 17.51%, 1622/9262, respectively; both P<.001). Most HIV-negative/unknown status participants (79.11%, 7327/9262) reported ever having a previous HIV test, and 55.69% (5158/9262) reported HIV testing in the past 12 months. HIV-positive participants were more likely to report sexually transmitted infection (STI) testing and diagnosis compared to HIV-negative/unknown status participants (STI testing: 71.73%, 685/955 vs 38.52%, 3568/9262; STI diagnosis: 25.65%, 245/955 vs 8.12%, 752/9262, respectively; both P<.001).

JMIR Public Health Surveill 2017;3(1):e13

doi:10.2196/publichealth.7119

Keywords



The American Men’s Internet Survey (AMIS) is an annual online behavioral survey of men who have sex with men (MSM) who live in the United States. The methods have been previously published [1,2]. This supplemental report updates that previous manuscript with the most current data available from AMIS (AMIS-2015). Methods in AMIS-2015 are unchanged from the previously published manuscript unless otherwise noted.


Recruitment and Enrollment

As in the prior year, AMIS participants were recruited through convenience sampling from a variety of websites using banner advertisements or email blasts to website members (hereafter referred to generically as “ads”). The survey was not incentivized. Data on the number of clicks on all banner ads were obtained directly from the websites. In AMIS-2014, data on the number of clicks on geospatial social networking banner ads were instead obtained by counting the number of clicks on the survey landing page. Men who clicked on the ads were taken directly to the survey website hosted on a secure server administered by SurveyGizmo (Boulder, CO, USA). Participants were also recruited by emailing participants from the previous cycle of AMIS (AMIS-2014) who consented to be recontacted for future studies. To be eligible for the survey, participants had to be 15 years of age or older, consider themselves to be male, and report that they had oral or anal sex with a man at least once in the past (hereafter referred to as MSM). Persons who reported being younger than 15 years of age or refused to provide their age were not asked any other screening questions. Those MSM who met the eligibility criteria and consented to participate in the study started the online survey immediately. The full questionnaire for AMIS-2015 is presented in Multimedia Appendix 1.

AMIS-2015 ran from September 2015 through April 2016, and resulted in 137,608 persons clicking on the ads and landing on the study’s recruitment page (Table 1). Most persons who clicked on the ads were from general social networking websites (66,500/137,608, 48.33%). Of the 1248 participants who completed the AMIS-2014 survey and were emailed links to the AMIS-2015 survey, 9.13% (114/1248) clicked on the link. One-third (33.58%, 46,207/137,608) of those who landed on the study’s page started the screening process and 56.09% (25,919/46,207) of those were eligible. The most common reason for ineligibility was not ever having male-male sex. More than three-quarters (78.52%, 20,351/25,919) of those who were eligible consented to participate in the survey. There were 2291 of 20,351 (11.26%) surveys determined to likely be from duplicate participants. Deduplication of survey responses was performed in the same manner as in previous AMIS cycles [1,2]. Among unduplicated surveys, almost two-thirds (64.21%, 11,597/18,060) were considered successful (ie, observations with no missing values for the first question of at least two consecutive sections). Most successful surveys were among men who reported having sex with another man in the past 12 months (89.07%, 10,330/11,597). Finally, 1.09% (113/10,330) of the sample was found to have provided an invalid ZIP code and was excluded from the final analytical sample.

Table 1. Recruitment outcomes for the American Men’s Internet Survey, United States, 2015.
Recruitment outcomesTotalRecruitment type


Gay social
networking (n=1)
General gay
interest (n=2)
General social
networking (n=4)
Geospatial social
networking (n=2)
AMIS-2014
participants
Clicked ad, n137,6084680396866,50062,261199
Screened,a n (%)46,207 (33.58)3671 (78.44) 1165 (29.36)30,581 (45.99)10,630 (17.07)160 (80.40)
Ineligible,bn (%)20,288 (43.91)740 (20.16)463 (39.74)16,206 (52.99)2868 (26.98)11 (6.88)

Not age ≥15 yearsc14,246 (70.22)615 (83.11)369 (79.70)11,056 (68.22)2197 (76.60)9 (81.82)

Not malec15,255 (75.19)559 (75.54)381 (82.29)11,800 (72.81)2505 (87.34)10 (90.91)

Not ever MSMc19,804 (97.61)620 (83.78)454 (98.06)16,046 (99.01)2673 (93.20)11 (100.00)

Nonresidentc15,502 (76.41)624 (84.32)377 (81.43)11,469 (70.77)2573 (89.71)9 (81.82)
Eligible,b n (%)25,919 (56.09)2931 (79.84)702 (60.26)14,375 (47.01)7762 (73.02)149 (93.13)
Consented,d n (%)20,351 (78.52)2181 (74.41)586 (83.48)10,818 (75.26)6623 (85.33)143 (95.97)
Unduplicated,e n (%)18,060 (88.74)2032 (93.17)552 (94.20)9410 (86.98)5926 (89.48)140 (97.90)
Success,f n (%)11,597 (64.21)1568 (77.17)426 (77.17)6372 (67.72)3104 (52.38)127 (90.71)
MSM past 12 months,g n (%)10,330 (89.07)1456 (92.86)381 (89.44)5425 (85.14)2953 (95.14)115 (90.55)
Valid ZIP code,h n (%)10,217 (98.91)1451 (99.66)381 (100.00)5396 (99.47)2875 (97.36)114 (99.13)

a Proportion is of total who clicked ad. Includes those who started the screening questionnaire.

b Proportion is among total screened. Ineligible includes those who did not complete the screening questionnaire.

c Proportion is among total ineligible. Includes those who may not have responded to the question. MSM: men who have sex with men.

d Proportion is among eligible.

e Proportion is among consented. Unduplicated removes participants who were marked as duplicates using IP address and demographic data matching.

f Proportion is among unduplicated. Success removes participants who did not pass the test for survey completeness.

g Proportion is among successes.

h Proportion is among MSM in the past 12 months. Valid US ZIP codes were those that could be matched to the ZIP code-to-county crosswalk files created by the US Department of Housing and Urban Development. Any ZIP codes that could not be matched to this list were then hand-validated by checking against the ZIP code locator tool on the USPS website. ZIP codes that could not be found were classified as invalid.

Almost all these surveys (10,217/10,330, 98.91%) provided a valid US ZIP code. ZIP codes provided by participants were validated by merging them with the 2015 ZIP code-to-county crosswalk files created by the US Department of Housing and Urban Development [3]. Any ZIP codes that could not be matched to this list were then hand-validated by checking against the ZIP code locator tool on the United States Postal Service website [4]. ZIP codes that could not be found were classified as invalid. Overall, the completion rate was 7.4% (10,217/137,608), with an analytical sample consisting of 10,217 surveys out of 137,068 clicks.

Measures and Analyses

For AMIS-2015 analyses, participants were categorized as either being AMIS-2014 participants who took the survey again or new participants from website/app types based on target audience and purpose: gay social networking (n=1), gay general interest (n=2), general social networking (n=4), and geospatial social networking (n=2). Recruitment outcomes and demographic characteristics for the AMIS-2014 participants are presented and for all behavioral outcomes, they are recategorized according to their original recruitment source. We do not provide the names of the websites/apps to preserve operator and client privacy, particularly where a category has only one operator. The participants who were eligible, consented, unduplicated, successful, reported male-male sex in the past 12 months, and provided a valid US ZIP code were included in analyses of participant characteristics and behavior.

For AMIS-2015, we created a more refined population density variable for each participant’s county of residence as determined by their ZIP code. The levels of the population density variable are from the National Center for Health Statistics (NCHS) Rural-Urban classification scheme [5]. The NCHS classifies counties into six categories: central (ie, inner city) or fringe (ie, suburban) areas of large metropolitan statistical areas (MSAs; population size ≥1,000,000), medium-sized MSAs (population size 250,000-999,999), small MSAs (population size <250,000), micropolitan area (counties that contain all or part of a city of 10,000 or more), and noncore (counties that do not contain any part of a city of 10,000 or more). We further collapsed these categories into a four-level urbanicity variable: urban (central), suburban (fringe), medium/small metropolitan, and rural (micropolitan and noncore).

The analysis methods for AMIS-2015 did not substantively differ from those previously published but are repeated in this report for clarity [1]. Overall, chi-square tests were used to identify whether participant characteristics significantly differed between recruitment sources. Multivariable logistic regression modeling was used to determine significant differences in behaviors based on self-reported human immunodeficiency virus (HIV) status while controlling for race/ethnicity, age group, National HIV Behavioral System (NHBS) city residency, and recruitment website type. MSAs included in NHBS in 2015 were Atlanta, GA; Baltimore, MD; Boston, MA; Chicago, IL; Dallas, TX; Denver, CO; Detroit, MI; Houston, TX; Los Angeles, CA; Miami, FL; Nassau-Suffolk, NY; New Orleans, LA, New York City, NY; Newark, NJ; Philadelphia, PA; San Diego, CA; San Francisco, CA; San Juan, PR; Seattle, WA; and Washington, DC. Self-reported HIV status was categorized as either HIV-positive or HIV-negative/unknown status, consistent with surveillance reports produced by NHBS [6]. HIV testing behaviors were only examined among those who did not report that they were HIV-positive and were also presented by participant characteristics. Multivariable logistic regression results are presented as Wald chi-square P values to denote an independently significant difference in the behavior for each subgroup compared to a referent group. Statistical significance was determined at P<.05.


Approximately seven in 10 (7291/10,217, 71.36%) participants included in this report were white and non-Hispanic, less than half were 40 years of age or older (4326/10,217, 42.34%), and their most common region of residence was the South followed by the West (Table 2). Participants were recruited from all US states and there were at least 100 participants from each of 28 states (Figure 1). Overall, 9.35% (955/10,217) of participants reported being HIV-positive, 69.91% (7143/10,217) reported being HIV-negative, and 20.74% (2119/10,217) reported having an unknown HIV status. All participant characteristics differed significantly based on where they were recruited (Table 2).

Table 2. Characteristics of MSM participants in the American Men’s Internet Survey by recruitment type, United States, 2015.
Participant characteristicsTotal, n (%)Recruitment type, n (%)Pa


Gay social
networking (n=1)
General gay
interest (n=4)
General social
networking (n=4)
Geospatial social
networking (n=2)
AMIS-2014
participants

Race/Ethnicity





<.001

Black, non-Hispanic675 (6.61)33 (2.27)15 (3.94)444 (8.23)176 (6.12)7 (6.14)

Hispanic1387 (13.58)73 (5.03)36 (9.45)755 (13.99)511 (17.77)12 (10.53)

White, non-Hispanic7291 (71.36)1271 (87.59)301 (79.00)3733 (69.18)1899 (66.05)87 (76.32)

Other or multiple races864 (8.46)74 (5.10)29 (7.61)464 (8.60)289 (10.05)8 (7.02)
Age (years)





<.001

15-242821 (27.61)32 (2.21)37 (9.71)2155 (39.94)581 (20.21)16 (14.04)

25-291583 (15.49)36 (2.48)61 (16.01)983 (18.22)491 (17.08)12 (10.53)

30-391487 (14.55)112 (7.72)86 (22.57)516 (9.56)740 (25.74)33 (28.95)

≥404326 (42.34)1271 (87.59)197 (51.71)1742 (32.28)1063 (36.97)53 (46.49)
Region





.002

Northeast2038 (19.95)304 (20.95)72 (18.90)1074 (19.90)566 (19.69)22 (19.30)

Midwest2127 (20.82)344 (23.71)73 (19.16)1152 (21.35)530 (18.43)28 (24.56)

South3739 (36.60)467 (32.18)132 (34.65)2000 (37.06)1098 (38.19)42 (36.84)

West2305 (22.56)335 (23.09)103 (27.03)1166 (21.61)679 (23.62)22 (19.30)
US dependent areas8 (0.08)1 (0.07)1 (0.26)4 (0.07)2 (0.07)0 (0.0)
NHBS city residentb





<.001

Yes3731 (36.52)565 (38.94)177 (46.46)1855 (34.38)1090 (37.91)44 (38.60)

No6486 (63.48)886 (61.06)204 (53.54)3541 (65.62)1785 (62.09)70 (61.40)
Population densityc





<.001

Urban4101 (40.18)572 (39.45)189 (49.74)2073 (38.45)1214 (42.28)53 (46.49)

Suburban2041 (20.00)363 (25.03)71 (18.68)1092 (20.26)494 (17.21)21 (18.42)

Small/ medium metropolitan3076 (30.14)387 (26.69)97 (25.53)1679 (31.14)883 (30.76)30 (26.32)

Rural988 (9.68)128 (8.83)23 (6.05)547 (10.15)280 (9.75)10 (8.77)
Self-reported HIV Status





<.001

Positive955 (9.35)108 (7.44)26 (6.82)411 (7.62)395 (13.74)15 (13.16)

Negative7143 (69.91)1102 (75.95)302 (79.27)3566 (66.05)2080 (72.35)93 (81.58)

Unknown2119 (20.74)241 (16.61)53 (13.91)1419 (26.32)400 (13.91)6 (5.26)
Total10,217145138153962875114

a Chi-square test for difference in characteristics between recruitment types.

b NHBS: National HIV Behavioral Surveillance System.

C There were 11 participants living in US territories or provided military addresses, which could not have an NCHS urban/rural category assigned.

Most participants reported having anal sex without a condom with another man within the past 12 months (Table 3). Compared to HIV-negative/unknown status participants, those who were HIV-positive were significantly more likely to report anal intercourse without a condom (adjusted OR [AOR] 1.86, 95% CI 1.59-2.18), including with male partners who were of discordant or unknown status (AOR 2.75, 95% CI 2.36-3.20). Within each serostatus group, anal intercourse without a condom differed significantly by age group (HIV-positive and HIV-negative/unknown status participants), and recruitment website (HIV-negative/unknown status participants only). Anal intercourse without a condom with partners of discordant or unknown HIV status differed significantly by race/ethnicity (HIV-positive participants only), recruitment website (HIV-positive participants only), and age (HIV-negative/unknown status participants only).

Table 3. Sexual Behaviors with Male Partners of MSM Participants in the American Men’s Internet Survey, United States, 2015.
Participant characteristicsnSexual behaviors with male partners in the past 12 months


Anal intercourse without a condomAnal intercourse without a condom with a partner of discordant or unknown HIV status


n (%)Pan (%)Pa
HIV positive overall955721 (75.50)<.001b329 (34.45)<.001b

Race/Ethnicity






Black, non-Hispanic161105 (65.22).0835 (21.74).002


Hispanic152113 (74.34).7048 (31.58).92


White, non-Hispanic573454 (79.23)REF221 (38.57)REF


Other or multiple races6949 (71.01).5025 (36.23).37

Age (years)






15-245040 (80.00).8318 (36.00).76


25-2910792 (85.98).0442 (39.25).37


30-39181147 (81.22).9168 (37.57).45


≥40617442 (71.64)REF201 (32.58)REF

NHBS city residentc






Yes422325 (77.01).14142 (33.65).83


No533396 (74.30)REF187 (35.08)REF

Recruitment type






Gay social networking10879 (73.15).3548 (44.44).18


General gay interest2622 (84.62).3012 (46.15).37


General social networking413290 (70.22)REF137 (33.17)REF


Geospatial social networking408330 (80.88).59132 (32.35).01
HIV negative or unknown overall92625843 (63.09)REF1581 (17.07)REF

Race/Ethnicity






Black, non-Hispanic514316 (61.48).5592 (17.90).44


Hispanic1235804 (65.10).27248 (20.08).05


White, non-Hispanic67184244 (63.17)REF1116 (16.61)REF


Other or multiple races795479 (60.25).05125 (15.72).06

Age (years)






15-2427711713 (61.82)<.001524 (18.91).001


25-2914761072 (72.63)<.001257 (17.41).63


30-391306930 (71.21)<.001224 (17.15).37


≥4037092128 (57.37)REF576 (15.53)REF

NHBS city residentc






Yes33092055 (62.10).17570 (17.23).82


No59533788 (63.63)REF1011 (16.98)REF

Recruitment type






Gay social networking1343706 (52.57)<.001222 (16.53).49


General gay interest363234 (64.46).5960 (16.53).87


General social networking50283120 (62.05)REF816 (16.23)REF


Geospatial social networking25281783 (70.53)<.001483 (19.11).06

a Wald chi-square from multivariate logistic regression comparing behavior (yes vs no) among group with some characteristic compared to a referent (REF) group.

b Wald chi-square from multivariate logistic regression comparing behavior (yes vs no) among HIV-positive participants compared to HIV-negative or unknown serostatus participants. Model controlled for race/ethnicity, age, NHBS residency, and recruitment type.

C NHBS: National HIV Behavioral Surveillance System.

Almost one-quarter (235/955, 24.6%) of HIV-positive participants reported using marijuana in the past 12 months (Table 4). Compared to HIV-negative/unknown status participants, HIV-positive participants were significantly more likely to report use of marijuana (AOR 1.43, 95% CI 1.22-1.69) and other illicit substances in the past 12 months (AOR 2.20, 95% CI 1.88-2.59). Within each serostatus group, use of marijuana and other illicit substances differed significantly by age (HIV-positive and HIV-negative/unknown status participants), residence in an NHBS city (HIV-negative/unknown status participants only), and recruitment website type (HIV-negative/unknown status participants only). Marijuana use also differed significantly by recruitment website among HIV-positive participants. Use of other illicit substances differed significantly by race/ethnicity among HIV-negative/unknown status participants.

Table 4. Substance using behaviors of MSM participants in the American Men’s Internet Survey, United States, 2015.
Participant characteristicsnSubstance use behaviors in the past 12 months


Used marijuanaUsed other substance(s)


n (%)Pan (%)Pa
HIV positive overall955235 (24.61)<.001b273 (28.59)<.001b

Race/Ethnicity






Black, non-Hispanic16140 (24.84).3531 (19.25).06


Hispanic15239 (25.66).8949 (32.24).39


White, non-Hispanic573144 (25.13)REF175 (30.54)REF


Other or multiple races6912 (17.39).0718 (26.09).60

Age (years)






15-245215 (30.00).8814 (28.00).48


25-2910943 (40.19).00343 (40.19).02


30-3918753 (29.28).6769 (38.12).19


≥40627124 (20.10)REF147 (23.82)REF

NHBS city residentc






Yes422110 (26.07).35125 (29.62).45


No533125 (23.45)REF148 (27.77)REF

Recruitment type






Gay social networking10820 (18.52).8928 (25.93).97


General gay interest264 (15.38).487 (26.92).93


General social networking41390 (21.79)REF95 (23.00)REF


Geospatial social networking408121 (29.66).04143 (35.05).14
HIV negative or unknown overall92622127 (22.96)REF1622 (17.51)REF

Race/Ethnicity






Black, non-Hispanic51491 (17.70).0667 (13.04).02


Hispanic1235296 (23.97).78220 (17.81).84


White, non-Hispanic67181570 (23.37)REF1200 (17.86)REF


Other or multiple races795170 (21.38).32135 (16.98).94

Age (years)






15-242771854 (30.82)<.001543 (19.60).02


25-291476437 (29.61)<.001356 (24.12)<.001


30-391306297 (22.74).16254 (19.45).96


≥403709539 (14.53)REF469 (12.64)REF

NHBS city residentc






Yes3309793 (23.96).002633 (19.13)<.001


No59531334 (22.41)REF989 (16.61)REF

Recruitment type






Gay social networking1343187 (13.92).02167 (12.43).13


General gay interest36374 (20.39).9257 (15.70).44


General social networking50281244 (24.74)REF859 (17.08)REF


Geospatial social networking2528622 (24.60).004539 (21.32)<.001

a Wald chi-square from multivariable logistic regression comparing behavior (yes vs no) among group with some characteristic compared to a referent (REF) group.

b Wald chi-square from multivariable logistic regression comparing behavior (yes vs no) among HIV-positive participants compared to HIV-negative or unknown serostatus participants. Model controlled for race/ethnicity, age, NHBS residency, and website type.

c NHBS: National HIV Behavioral Surveillance System.

HIV testing behaviors were examined among those who did not report being HIV-positive (Table 5). Most participants (7327/9262, 79.11%) reported having been previously tested for HIV infection, and just over half (5158/9262, 55.69%) reported being tested in the past 12 months. HIV testing behavior, both ever tested and tested in past 12 months, differed significantly by age, residence in an NHBS city, and recruitment website type.

Table 5. HIV testing behaviors of HIV-negative or unknown status MSM participants in the American Men’s Internet Survey, United States, 2015.
Participant characteristicsnHIV testing behaviors


HIV tested everHIV tested past 12 months


n (%)Pan (%)Pa
Race/Ethnicity





Black, non-Hispanic514445 (86.58).06333 (64.79).02

Hispanic1235948 (76.76).35715 (57.89).37

White, non-Hispanic67185314 (79.10)REF3645 (54.26)REF

Other or multiple races795620 (77.99).99465 (58.49).81
Age (years)





15-2427711599 (57.70)<.0011286 (46.41)<.001

25-2914761269 (85.98)<.001903 (61.18)<.001

30-3913061160 (88.82)<.001858 (65.70)<.001

40 or older37093299 (88.95)REF2111 (56.92)REF
NHBS city residentb





Yes33092774 (83.83)<.0012075 (62.71)<.001

No59534553 (76.48)REF3083 (51.79)REF
Recruitment type





Gay social networking13431122 (83.54)<.001713 (53.09).005

General gay interest363311 (85.67).87189 (52.07).002

General social networking50283694 (73.47)REF2512 (49.96)REF

Geospatial social networking25282200 (87.03)<.0011744 (68.99)<.001
Total92627327 (79.11)
5158 (55.69)

a Wald chi-square from multivariable logistic regression comparing behavior (yes vs no) among group with some characteristic compared to a referent (REF) group.

b NHBS: National HIV Behavioral Surveillance System.

Compared to HIV-negative/unknown status participants, HIV-positive participants were significantly more likely to report sexually transmitted infection (STI) testing (AOR 4.00, 95% CI 3.43-4.68) and STI diagnosis (AOR 3.83, 95% CI 3.20-4.59) in the past 12 months (Table 6). The most common STI diagnosis among HIV-positive participants was syphilis (144/955, 15.1%), whereas gonorrhea was the most common STI diagnosis among HIV-negative/unknown status participants (427/9262, 4.61%). Among HIV-negative/unknown status participants, STI testing differed significantly by race/ethnicity, age, and residence in an NHBS city. Among both HIV-positive and HIV-negative/unknown status participants, STI testing differed significantly by recruitment website type and STI diagnosis differed significantly by age, NHBS city residence, and recruitment website type.

Table 6. Sexually transmitted infection testing and diagnosis of MSM participants in the American Men’s Internet Survey, United States, 2015.
Participant characteristicsnSTI History in the Past 12 Months


Tested for any STIaDiagnosed with any STIa


n (%)Pbn (%)Pb
HIV positive overall955685 (71.73)<.001c245 (25.65)<.001c

Race/Ethnicity






Black, non-Hispanic161116 (72.05).3948 (29.81).10


Hispanic152109 (71.71).2950 (32.89).75


White, non-Hispanic573413 (72.08)REF130 (22.69)REF


Other or multiple races6947 (68.12).3217 (24.64).25

Age (years)






15-245044 (88.00).0923 (46.00).02


25-2910789 (83.18).4543 (40.19).09


30-39181152 (83.98).5666 (36.46).77


≥40617400 (64.83)REF113 (18.31)REF

NHBS city residentd






Yes422313 (74.17).10128 (30.33).007


No533372 (69.79)REF117 (21.95)REF

Recruitment website type






Gay social networking10871 (65.74).8121 (19.44).40


General gay interest2615 (57.69).253 (11.54).26


General social networking413276 (66.83)REF79 (19.13)REF


Geospatial social networking408323 (79.17).006142 (34.80).003
HIV negative or unknown overall92623568 (38.52)REF752 (8.12)REF

Race/Ethnicity






Black, non-Hispanic514241 (46.89).0157 (11.09).07


Hispanic1235543 (43.97).92150 (12.15).04


White, non-Hispanic67182458 (36.59)REF481 (7.16)REF


Other or multiple races795326 (41.01).3064 (8.05).03

Age (years)






15-242771997 (35.98)<.001229 (8.26).46


25-291476753 (51.02)<.001169 (11.45)<.001


30-391306639 (48.93).004154 (11.79).15


≥4037091179 (31.79)REF200 (5.39)REF

NHBS city residentc






Yes33091493 (45.12)<.001350 (10.58)<.001


No59532075 (34.86)REF402 (6.75)REF

Recruitment website type






Gay social networking1343365 (27.18)<.00159 (4.39).04


General gay interest363143 (39.39).8823 (6.34).27


General social networking50281746 (34.73)REF313 (6.23)REF


Geospatial social networking25281314 (51.98)<.001357 (14.12)<.001

a Sexually transmitted infection (STI) includes chlamydia, gonorrhea, and syphilis.

b Wald chi-square from multivariable logistic regression comparing behavior (yes vs no) among group with some characteristic compared to a referent (REF) group.

c Wald chi-square from multivariable logistic regression comparing behavior (yes vs no) among HIV-positive participants compared to HIV-negative or unknown serostatus participants. Model controlled for race/ethnicity, age, NHBS residency, and website type.

d NHBS: National HIV Behavioral Surveillance System.

Figure 1. Number of MSM participants in the American Men’s Internet Survey by state, 2015.
View this figure

Acknowledgments

The study was funded by a grant from the MAC AIDS Fund and by the National Institutes of Health (P30AI050409)—the Emory Center for AIDS Research.

Conflicts of Interest

Authors Sanchez and Sullivan are members of the Editorial Board of JMIR Public Health and Surveillance. However, they had no involvement in the editorial decision for this manuscript. It was reviewed and handled by an independent editor.

Multimedia Appendix 1

AMIS 2015 Questionnaire.

PDF File (Adobe PDF File), 452KB

Multimedia Appendix 2

Recruitment and enrollment outcomes flow chart.

PPTX File, 43KB

References

  1. Sanchez T, Zlotorzynska M, Sineath C, Kahle E, Sullivan P. The annual American Men's Internet Survey of Behaviors of Men Who Have Sex With Men in the United States: 2014 key indicators report. JMIR Public Health Surveill 2016 May 25;2(1):e23 [FREE Full text] [CrossRef] [Medline]
  2. Sanchez TH, Sineath RC, Kahle EM, Tregear SJ, Sullivan PS. The annual American Men's Internet Survey of Behaviors of Men Who Have Sex With Men in the United States: protocol and key indicators report 2013. JMIR Public Health Surveill 2015;1(1):e3 [FREE Full text] [CrossRef] [Medline]
  3. Office of Policy Development and Research (PD&R), US Department of Housing and Urban Development. HUD USPS ZIP code crosswalk files   URL: https://www.huduser.gov/portal/datasets/usps_crosswalk.html [accessed 2017-03-02] [WebCite Cache]
  4. USPS. ZIP code lookup   URL: https://tools.usps.com/go/ZipLookupAction_input [accessed 2017-03-02] [WebCite Cache]
  5. Ingram DD, Franco SJ. 2013 NCHS urban-rural classification scheme for counties. Vital Health Stat 2 2014 Apr(166):1-73 [FREE Full text] [Medline]
  6. Centers for Disease Control and Prevention. 2016. HIV surveillance special report 15: HIV infection risk, prevention, and testing behaviors among men who have sex with men, 2014   URL: http://www.cdc.gov/hiv/library/reports/surveillance/#panel2 [accessed 2017-03-02] [WebCite Cache]


AMIS: American Men’s Internet Survey
HIV: human immunodeficiency virus
MSA: Metropolitan Statistical Area
MSM: men who have sex with men
NCHS: National Center for Health Statistics
NHBS: National HIV Behavioral Surveillance System
STI: sexually transmitted infection


Edited by G Eysenbach; submitted 07.12.16; peer-reviewed by C Khosropour, N Lachowsky; comments to author 05.01.17; revised version received 24.01.17; accepted 08.02.17; published 25.03.17

Copyright

©Maria Zlotorzynska, Patrick Sullivan, Travis Sanchez. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 25.03.2017.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on http://publichealth.jmir.org, as well as this copyright and license information must be included.