Abstract
Objective
To examine healthcare-related correlates of recent HIV-testing among New York City (NYC) residents, controlling for socio-demographic and HIV-related risk factors.
Methods
Using the NYC 2007 Community Health Survey (population-based telephone survey, n=8,911), recent HIV-testing was examined for its association with healthcare-related variables, including medical screening for other conditions, controlling for other HIV-testing correlates using multiple logistic regression.
Results
Factors associated with a recent HIV test included: provider recommend for an HIV test (Adjusted Odds Ratio [AOR]:10.1, 95% confidence interval [CI]:7.6–13.5), Medicaid versus private insurance (AOR:1.6, 95%CI:1.2–2.1), and having a personal doctor (AOR:1.6, 95%CI:1.3–2.1). The proportion of HIV tests attributed to each factor (attributable fraction [AF] was 49% for provider recommendation, 33% for having a personal doctor, and 8.3% for Medicaid insurance. Among those recommended for other medical screening, factors associated with recent HIV-testing included recent receipt of blood lipid testing (AOR:2.2, 95%CI:1.6–3.0; AF:45%), and Pap smear (AOR:2.7, 95%CI:2.1–3.5; AF:52%). Recent receipt of mammography and colonoscopy were not associated with recent HIV-testing.
Conclusions
A substantial proportion of recent HIV-testing coverage among New Yorkers may be attributable to healthcare-related factors. Joint medical screening may provide opportunities to increase population HIV-testing coverage.
Keywords: HIV/AIDS, HIV-testing, health screening, provider initiated HIV-testing
Introduction
The Centers for Disease Control and Prevention (CDC) recommend that patients aged 13 to 64 in all healthcare settings be screened for HIV after being notified, using an ‘opt-out’ approach, and that persons at high-risk for HIV infection be screened for HIV at least annually.1 The United States Preventive Services Task Force (USPSTF) recommends screening persons known to be at risk for HIV infection.2 Intensified HIV-testing strategies that identify persons with undiagnosed HIV will be needed to achieve the 2015 National HIV/AIDS Strategy (NHAS) goals, which include increasing the proportion of HIV-positive persons who know their serostatus from 79% to 90%.2,3 The relative extent of achieving these goals through expansion of HIV-testing within the healthcare system versus expansion of community-based testing is unclear.
This study investigated the healthcare-related correlates of recent HIV-testing and the proportion of HIV-testing attributable to healthcare-related correlates among a population-based sample of adults, and among subgroups recommended by the USPSTF to receive routine medical screening for lipid disorders and cervical, breast and colorectal cancers.
Methods
Data from the 2007 NYC Community Health Survey (CHS), an annual cross-sectional telephone survey conducted by the NYC Department of Health and Mental Hygiene (DOHMH) were used.4 The sample for this analysis included 8,911 individuals who responded to the question about recent HIV-testing.
Respondents were asked if they received an HIV test in the past 12 months, and if they received recent screening for lipid disorders and cervical, breast and colorectal cancers. This study defines “recent” as within 12 months of the telephone interview.
Healthcare-related variables included health insurance status, having a personal doctor or healthcare provider, and having a health professional recommended an HIV test in the past 12 months. Other covariates examined included: demographics (gender, age, area of residence, and race/ethnicity); socioeconomic characteristics (education and household income); and risk behaviors (number of sex partners in the last 12 months).
To examine the association of recent medical screening with recent HIV-testing, respondents were classified into four subgroups based on eligibility for screening under current USPSTF screening guidelines.5–8 Subgroups included screening for: lipid disorders among adults aged 45 and older; Pap smear among women aged below age 65; mammography among adult women aged 40 and older; and colorectal cancer among adults aged 50 and older.
To examine the associations between recent HIV-testing and recent medical screening for other health conditions, recent HIV-testing history was examined within subgroups for whom these other medical screenings are routinely recommended.
Multivariate logistic regression models were used to identify healthcare-related factors associated with recent HIV-testing among all respondents and among those in USPSTF-defined screening subgroups. A base multivariate model was developed including demographic, socioeconomic and healthcare-related covariates (found to be significantly associated with recent HIV-testing in univariate analyses) to identify independent predictors of recent HIV-testing among all respondents, excluding variables for recent receipt of medical screening tests. All covariates from the base model were included in multivariate models of each screening subgroup. All analyses were conducted using SAS (Version 9.2; SAS-Institute Inc.) survey procedures.
The population attributable-fraction (AF%) and 95%CIs of receiving a recent HIV test for significantly associated health-care related correlates was estimated using the formula AF%=PE*(aOR-1)/[PE*(aOR-1)+1], where aOR is an estimate of the adjusted risk ratio for the exposure of interest, and PE is the proportion exposed to receiving the other health screening.9
Results
Of the 8,911 adults who responded to the 2007 CHS HIV-testing question, the age-adjusted prevalence of self-reported recent HIV-testing was 26.6% , with very high recent HIV-testing rates among persons aged 18 to 44 (>40%) and among blacks and Hispanics (35–40%) (Table 1). Among subgroups for whom routine medical screening for other health conditions is recommended, the age-adjusted proportion reporting a recent HIV test was significantly higher among those who reported recent receipt of other health screenings (blood lipid testing, Pap smear, mammography, colonoscopy) compared with those who did not (Table 1).
TABLE 1.
Age Adjusted Prevalence of Recent HIV Testing among Adult New Yorkers and Adjusted Odds Ratios, NYC Community Health Survey 2007 †
| Total | Had Recent HIV Test |
Adjusted Odds Ratio | |||||
|---|---|---|---|---|---|---|---|
| (n) | (%) | (n) | (%) | AOR | 95% CI | ||
| Total § | |||||||
| 8911 | 2367 | (26.6) | |||||
| Age | |||||||
| 18–24 | 463 | (5.2) | 205 | (44.3) | 1.8 | (1.3 – 2.5) | * |
| 25–44 | 2997 | (33.6) | 1278 | (42.6) | 2.3 | (1.9 – 2.7) | * |
| 45–64 | 3447 | (38.7) | 706 | (20.5) | 1.0 | ||
| 65+ | 1989 | (22.3) | 174 | (8.7) | 0.4 | (0.3 – 0.5) | * |
| Race/Ethnicity | |||||||
| White | 3611 | (40.5) | 456 | (12.6) | 1.0 | ||
| Black | 2362 | (26.5) | 855 | (36.2) | 2.9 | (2.3 – 3.7) | * |
| Hispanic | 2156 | (24.2) | 871 | (40.4) | 2.5 | (1.9 – 3.2) | * |
| Asian/PI | 558 | (6.3) | 106 | (19.0) | 1.2 | (0.8 – 1.8) | |
| Other | 224 | (2.5) | 79 | (35.3) | 3.7 | (2.2 – 6.1) | * |
| Education | |||||||
| Less than high school | 1395 | (15.7) | 466 | (33.4) | 1.0 | (0.7 – 1.3) | |
| High school graduate | 2236 | (25.1) | 616 | (27.5) | 1.0 | (0.8 – 1.3) | |
| Some college/technical school | 1806 | (20.3) | 537 | (29.7) | 1.2 | (0.9 – 1.5) | |
| College graduate | 3412 | (38.3) | 732 | (21.5) | 1.0 | ||
| Income/Poverty | |||||||
| Don't Know | 797 | (8.9) | 214 | (26.9) | 1.4 | (0.9 – 2.0) | |
| <100% poverty | 1662 | (18.7) | 605 | (36.4) | 1.7 | (1.2 – 2.5) | |
| 100% – <200% poverty | 1286 | (14.4) | 380 | (29.5) | 1.2 | (0.8 – 1.6) | |
| 200% – < 400% poverty | 1449 | (16.3) | 395 | (27.3) | 1.4 | (1.0 – 1.9) | |
| 400% – < 600% poverty | 1367 | (15.3) | 300 | (21.9) | 1.1 | (0.8 – 1.5) | |
| > 600% poverty | 1683 | (18.9) | 343 | (20.4) | 1.0 | ||
| Gender | |||||||
| Male | 3421 | (38.4) | 887 | (25.9) | 1.0 | ||
| Female | 5490 | (61.6) | 1480 | (27.0) | 1.3 | (1.0 – 1.5) | * |
| Borough | |||||||
| Manhattan | 1797 | (20.2) | 449 | (25.0) | 1.0 | ||
| The Bronx | 1354 | (15.2) | 560 | (41.4) | 1.1 | (0.8 – 1.4) | |
| Brooklyn | 2906 | (32.6) | 803 | (27.6) | 1.0 | (0.8 – 1.2) | |
| Queens | 2194 | (24.6) | 464 | (21.1) | 0.8 | (0.6 – 1.0) | |
| Staten Island | 660 | (7.4) | 91 | (13.8) | 0.6 | (0.4 – 0.8) | |
| Has a personal doctor | |||||||
| Yes | 7420 | (83.3) | 1966 | (26.5) | 1.6 | (1.3 – 2.1) | * |
| No | 1425 | (16.) | 394 | (27.6) | 1.0 | ||
| Insurance type | |||||||
| Medicaid | 1276 | (14.3) | 584 | (45.8) | 1.6 | (1.2 – 2.1) | * |
| Medicare | 1381 | (15.5) | 197 | (14.3) | 1.3 | (0.9 – 2.0) | |
| Other | 387 | (4.3) | 123 | (31.8) | 2.2 | (1.5 – 3.3) | * |
| Uninsured | 1259 | (14.1) | 351 | (27.9) | 0.8 | (0.6 – 1.0) | |
| Private | 4424 | (49.6) | 1069 | (24.2) | 1.0 | ||
| Number of Sex Partners | |||||||
| none | 2714 | (30.5) | 436 | (16.1) | 0.6 | (0.5 – 0.7) | * |
| one | 4324 | (48.5) | 1278 | (29.6) | 1.0 | ||
| two | 385 | (4.3) | 183 | (47.5) | 1.7 | (1.2 – 2.5) | * |
| three or more | 441 | (4.9) | 234 | (53.1) | 3.0 | (2.1 – 4.2) | * |
| Doc recommended HIV test past yr | |||||||
| Yes | 956 | (10.7) | 743 | (77.7) | 10.1 | (7.6 – 13.5) | * |
| No | 7907 | (88.7) | 1602 | (20.3) | 1.0 | ||
| Received lipid measurement (a) | |||||||
| Yes | 5919 | (66.4) | 1669 | (28.2) | |||
| No | 2792 | (31.3) | 645 | (23.1) | |||
| Received pap smear (b) | |||||||
| Yes | 3048 | (34.2) | 1072 | (35.2) | |||
| No | 2343 | (26.3) | 395 | (16.9) | |||
| Received mammography (c) | |||||||
| Yes | 2246 | (25.2) | 420 | (18.7) | |||
| No | 1619 | (18.2) | 240 | (14.8) | |||
| Received colonoscopy (d) | |||||||
| Yes | 888 | (10.) | 164 | (18.5) | |||
| No | 3524 | (39.5) | 469 | (13.3) | |||
To account for the survey’s complex sampling design, post-stratification sampling weights were applied to extrapolate survey findings to neighborhood populations, based on the respondent’s age, gender, and race/ethnicity
Totals may not match covariate totals because of missing values
Denotes Statistical Significance at p<0.05 (chi-square test was used to test univariate associations)
Restricted to persons over the age of 45
Includes all women <65 years
Restricted to women ≥40 years
Restricted to persons aged 50 and older
In multivariate models that adjusted for other factors, positive associations between lipid measurement and Pap smear testing with recent HIV-testing remained significant (Table 2): AORlipid 2.2 [95%CI:1.6–3.0]; AORPapsmear 2.7 [95%CI:2.1–3.5]; multivariate associations between either breast (AORmammography 1.1, 95%CI:0.8–1.5) or colorectal (AORcolonoscopy 1.3, 95%CI:0.9–1.8) cancer screening and HIV-testing remained positive but were not statistically significant. Persons with fewer years of formal education and lower income were more likely to report recent HIV-testing. A healthcare professional’s recommendation for HIV-testing continued to be strongly associated with a higher likelihood of recent HIV-testing among New Yorkers overall (AOR 10.1; 95%CI:7.6–13.5) and also within screening subgroups. As provider recommendations for HIV-testing may prompt other screening procedures to occur and vice-versa, we also examined multivariate associations excluding provider recommendation to HIV test in each screening subgroup. Associations were unchanged by exclusion of the provider recommendation variable.
TABLE 2.
Screening Subgroup Adjusted Odds Ratios and 95% CI of HIV Testing, NYC Community Health Survey 2007
| Subgroups Eligible for Other Health Screening† |
||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Lipid Measurement (a) |
PAP (b) |
Mammography (c) |
Colonoscopy (d) |
|||||||||||||
| # HI V tested (n =5436) |
AOR | (95% CI Range) | # HI V tested (n=4183) |
AOR | (95% CI Range) | # HI V tested (n=3910) |
AOR | (95% CI Range) | # HI V tested (n=4467) |
AOR | (95% CI Range) | |||||
| Age | ||||||||||||||||
| 18–24 | 238 | 3.3 | (2.1 – 5.2) | * | ||||||||||||
| 25–44 | 1848 | 2.6 | (2.1 – 3.4) | * | 517 | 1.9 | (1.3 – 2.7) | * | ||||||||
| 45–64 | 3447 | 1.0 | 2086 | 1.0 | 2086 | 1.0 | 2478 | 1.0 | ||||||||
| 65+ | 1989 | 0.3 | (0.2 – 0.4) | * | 1307 | 0.4 | (0.3 – 0.7) | * | 1989 | 0.3 | (0.2 – 0.5) | * | ||||
| Race/Ethnicity | ||||||||||||||||
| White | 2557 | 1.0 | 1374 | 1.0 | 1661 | 1.0 | 2211 | 1.0 | ||||||||
| Black | 1372 | 3.3 | (2.3 – 4.8) | * | 1220 | 3.3 | (2.4 – 4.7) | * | 1076 | 4.0 | (2.6 – 6.0) | * | 1095 | 3.0 | (2.0 – 4.6) | * |
| Hispanic | 1087 | 3.1 | (2.1 – 4.5) | * | 1206 | 3.0 | (2.1 – 4.3) | * | 892 | 3.9 | (2.5 – 6.1) | * | 838 | 3.3 | (2.1 – 5.0) | * |
| Asian/PI | 290 | 1.1 | (0.6 – 2.0) | 266 | 1.8 | (1.0 – 3.1) | 185 | 1.3 | (0.5 – 3.2) | 217 | 1.4 | (0.7 – 2.8) | ||||
| Other | 130 | 3.0 | (1.4 – 6.4) | * | 117 | 7.0 | (3.3 – 14.6) | * | 96 | 5.7 | (2.8 – 11.6) | * | 106 | 2.5 | (1.0 – 6.3) | |
| Birthplace | ||||||||||||||||
| Unites States | 3480 | 1.0 | 2525 | 1.0 | 2480 | 1.0 | 2896 | 1.0 | ||||||||
| Foreign born | 1956 | 1.1 | (0.8 – 1.4) | 1658 | 1.0 | (0.7 – 1.2) | 1430 | 1.1 | (0.8 – 1.5) | 1571 | 1.0 | (0.7 – 1.4) | ||||
| Education | ||||||||||||||||
| Less than high school | 936 | 1.2 | (0.8 – 1.9) | 609 | 0.9 | (0.6 – 1.3) | 688 | 1.0 | (0.6 – 1.7) | 801 | 1.2 | (0.7 – 2.0) | ||||
| High school graduate | 1399 | 0.9 | (0.6 – 1.3) | 1041 | 1.2 | (0.8 – 1.6) | 1046 | 0.8 | (0.5 – 1.2) | 1163 | 0.9 | (0.6 – 1.4) | ||||
| Some college/tech | 1046 | 1.1 | (0.7 – 1.6) | 917 | 1.5 | (1.1 – 2.1) | * | 782 | 1.1 | (0.8 – 1.7) | 832 | 1.0 | (0.6 – 1.5) | |||
| College graduate | 2018 | 1.0 | 1599 | 1.0 | 1371 | 1.0 | 1638 | 1.0 | ||||||||
| Income/Poverty | ||||||||||||||||
| Missing | 496 | 1.2 | (0.6 – 2.2) | 335 | 2.2 | (1.2 – 3.9) | * | 393 | 1.1 | (0.5 – 2.2) | 437 | 1.5 | (0.8 – 2.9) | |||
| <100% poverty | 1015 | 1.6 | (1.0 – 2.7) | 816 | 2.6 | (1.6 – 4.5) | * | 792 | 1.5 | (0.8 – 3.0) | 854 | 1.5 | (0.8 – 2.9) | |||
| 100% – <200% poverty | 766 | 1.2 | (0.8 – 2.0) | 634 | 1.5 | (0.9 – 2.5) | 589 | 0.9 | (0.5 – 1.8) | 641 | 1.4 | (0.8 – 2.4) | ||||
| 200% – < 400% poverty | 836 | 1.2 | (0.8 – 1.9) | 719 | 1.8 | (1.2 – 2.8) | * | 626 | 1.0 | (0.5 – 1.7) | 685 | 1.1 | (0.6 – 2.0) | |||
| 400% – < 600% poverty | 792 | 1.0 | (0.6 – 1.5) | 645 | 1.4 | (0.9 – 2.2) | 521 | 0.8 | (0.4 – 1.5) | 640 | 1.1 | (0.7 – 1.8) | ||||
| > 600% poverty | 1064 | 1.0 | 754 | 1.0 | 654 | 1.0 | 840 | 1.0 | ||||||||
| Gender | ||||||||||||||||
| Male | 2043 | 1.0 | 1666 | 1.0 | ||||||||||||
| Female | 3393 | 0.8 | (0.6 – 1.0) | 2801 | 0.6 | (0.4 – 0.8) | * | |||||||||
| Borough | ||||||||||||||||
| Manhattan | 1161 | 1.0 | 791 | 1.0 | 841 | 1.0 | 995 | 1.0 | ||||||||
| The Bronx | 756 | 1.3 | (0.9 – 1.9) | 736 | 0.9 | (0.6 – 1.4) | 615 | 1.3 | (0.8 – 2.0) | 599 | 1.2 | (0.8 – 2.0) | ||||
| Brooklyn | 1682 | 0.9 | (0.6 – 1.2) | 1409 | 0.9 | (0.6 – 1.3) | 1208 | 1.0 | (0.7 – 1.5) | 1343 | 1.0 | (0.7 – 1.4) | ||||
| Queens | 1381 | 1.1 | (0.8 – 1.6) | 952 | 0.7 | (0.5 – 1.0) | * | 950 | 0.8 | (0.5 – 1.2) | 1146 | 1.2 | (0.8 – 1.8) | |||
| Staten Island | 456 | 0.6 | (0.3 – 1.0) | 295 | 0.5 | (0.3 – 0.8) | * | 296 | 0.5 | (0.2 – 1.0) | 384 | 0.7 | (0.4 – 1.3) | |||
| Has a personal doctor | ||||||||||||||||
| Yes | 4751 | 2.1 | (1.4 – 3.2) | * | 3496 | 1.4 | (1.0 – 2.0) | 3440 | 2.2 | (1.4 – 3.6) | * | 3937 | 3.3 | (2.0 – 5.3) | * | |
| No | 645 | 1.0 | 665 | 1.0 | 440 | 1.0 | 494 | 1.0 | ||||||||
| Insurance type | ||||||||||||||||
| Medicaid | 641 | 1.7 | (1.0 – 2.7) | * | 790 | 1.7 | (1.2 – 2.5) | * | 547 | 1.5 | (0.9 – 2.4) | 519 | 1.6 | (0.9 – 2.8) | ||
| Medicare | 1280 | 1.6 | (1.0 – 2.3) | * | 199 | 1.4 | (0.7 – 2.7) | 878 | 1.1 | (0.6 – 2.0) | 1235 | 1.5 | (0.9 – 2.3) | |||
| Other | 257 | 1.5 | (0.9 – 2.5) | 146 | 2.4 | (1.4 – 4.1) | * | 161 | 1.6 | (0.9 – 2.9) | 230 | 1.5 | (0.8 – 2.6) | |||
| Uninsured | 585 | 0.9 | (0.6 – 1.5) | 640 | 1.1 | (0.8 – 1.6) | 426 | 1.0 | (0.7 – 1.7) | 436 | 0.7 | (0.4 – 1.2) | ||||
| Private | 2540 | 1.0 | 2358 | 1.0 | 1810 | 1.0 | 1934 | 1.0 | ||||||||
| Number of sex partners last year | ||||||||||||||||
| none | 2280 | 0.7 | (0.5 – 1.0) | * | 1118 | 0.5 | (0.4 – 0.7) | * | 1884 | 0.6 | (0.4 – 0.8) | * | 2067 | 0.9 | (0.6 – 1.2) | |
| one | 2182 | 1.0 | 2306 | 1.0 | 1449 | 1.0 | 1634 | 1.0 | ||||||||
| two | 136 | 1.9 | (1.0 – 3.7) | 186 | 1.5 | (0.9 – 2.5) | 59 | 1.8 | (0.8 – 3.8) | 99 | 2.2 | (1.1 – 4.3) | * | |||
| three or more | 141 | 3.5 | (2.0 – 6.3) | * | 91 | 2.0 | (0.9 – 4.3) | 24 | 3.6 | (0.8 – 15.7) | 97 | 2.8 | (1.5 – 5.3) | * | ||
| Doc recommended HIV test past yr | ||||||||||||||||
| Yes | 402 | 12.8 | (9.0 – 18.3) | * | 558 | 8.1 | (5.4 – 12.2) | * | 298 | 8.4 | (5.4 – 13.1) | * | 302 | 12.9 | (8.6 – 19.2) | * |
| No | 4998 | 1.0 | 3607 | 1.0 | 3584 | 1.0 | 4135 | 1.0 | ||||||||
| Received lipid measurement | ||||||||||||||||
| Yes | 4151 | 2.2 | (1.6 – 3.0) | * | ||||||||||||
| No | 1188 | 1.0 | ||||||||||||||
| Received pap smear | ||||||||||||||||
| Yes | 2550 | 2.7 | (2.1 – 3.5) | * | ||||||||||||
| No | 1588 | 1.0 | ||||||||||||||
| Received mammography | ||||||||||||||||
| Yes | 2246 | 1.1 | (0.8 – 1.5) | |||||||||||||
| No | 1619 | 1.0 | ||||||||||||||
| Received colonoscopy | ||||||||||||||||
| Yes | 888 | 1.3 | (0.9 – 1.8) | |||||||||||||
| No | 3524 | 1.0 | ||||||||||||||
Post-stratification sampling weights were applied to extrapolate survey findings to neighborhood populations, based on the respondent’s age, gender, and race/ethnicity. The population age structure from the 2000 U.S. Census was used to age-adjust estimates. Odds ratios were calculated using post-stratification weights.
Denotes Statistical Significance at p<0.05 (chi-square test was used to test univariate associations)
Lipid Measurement: adults aged 45 and older
Cervical Cancer Screening: women aged below 65
Breast Cancer Screening: women aged 40 and older
Colorectal Cancer Screening: adults over 50
Among all participants, taking into account other correlates, the proportion of recent HIV-testing among New Yorkers potentially attributable (AF%) to healthcare-related correlates such as having Medicaid, having a personal doctor or healthcare provider, and having received a recommendation for an HIV test from a healthcare provider were 8.3% (95%CI:2.9–14%), 33% (95%CI:20–47%), and 49% (95%CI:41–57%), respectively. Among the respective groups recommended for other medical screening tests significantly associated with recent HIV-testing, the AF% was 45% (95%CI:29–58%) for blood lipid testing and 52% (95%CI:38–62%) for Pap smears, after taking into account other correlates of recent HIV-testing in these groups.
Discussion
Rates of recent HIV screening were generally high, especially among persons aged 18–44 years, those with fewer years of education, and those in the lowest income category. Healthcare-related factors were important correlates of recent HIV-testing, independent of socio-demographic and behavioral risk factors for HIV infection. Additionally, the observed associations of recent HIV-testing with medical screening for other preventable health conditions suggest that joint screening may already be occurring and may present opportunities to increase suboptimal screening rates for HIV in some subgroups. The estimates of the attributable-fractions for healthcare-related factors in this study suggest that a substantial proportion of recent HIV-testing coverage among the general New York population may be attributable to healthcare-related factors.
Other studies have found that individuals may be more likely to accept HIV-testing if another blood test was performed at the same time10, and this has been suggested for other health screening outcomes.11,12 Thus, there may be opportunities to facilitate HIV-testing in healthcare settings around screening for other conditions. The lack of associations of mammography and colonoscopy may reflect missed opportunities for HIV-testing among older persons.
This study also highlighted substantial differences in recent HIV-testing coverage by race/ethnicity that correlates directly with the estimated prevalence of diagnosed HIV among adults.13 This suggests that targeting strategies according to background HIV prevalence may be occurring.
The relatively high rates of recent HIV-testing in this study may in part be due to social desirability bias. Outcome frequencies this common result in odds ratios that are not a good approximation of the relative risk. Finally, these findings may not directly apply to undiagnosed, hard to reach HIV-positive individuals, including those whose contact with the healthcare system may be seldom or sporadic. Testing that reaches these individuals will likely require continued outreach and community-based HIV-testing efforts. However, a recent CDC report suggests that HIV-testing in clinical settings identified the majority of new HIV diagnoses.14 Thus, improvements in HIV-testing coverage, including identification of more undiagnosed individuals, may result from broader efforts to ensure that more adults have both a medical home and adequate insurance coverage.15
Acknowledgements
The authors would like to acknowledge Dr. Bonnie D. Kerker and the Division of Epidemiology Services at the New York City Health Department and Mental Hygiene for their assistance in adding custom variables on medical screening to the NYC Community Health Survey public use dataset.
Dr. Nash was funded in part by a grant from the US National Institutes of Health (NIH, www.nih.gov), National Institute of Mental Health (NIMH grant 1R01MH089831-01A1).
Footnotes
Declarations/Conflict of Interest Statement
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
References
- 1.Branson BM, Handsfield HH, Lampe MA, et al. Revised recommendations for HIV-testing of adults, adolescents, and pregnant women in health-care settings. MMWR Recomm Rep. 2006;55:1–17. quiz CE1-4. [PubMed] [Google Scholar]
- 2.USPSTF. Screening for HIV: recommendation statement. Ann Intern Med. 2005;143:32–37. doi: 10.7326/0003-4819-143-1-200507050-00008. [DOI] [PubMed] [Google Scholar]
- 3.Holtgrave DR. On the epidemiologic and economic importance of the National AIDS Strategy for the United States. J Acquir Immune Defic Syndr. 2010;55:139–142. doi: 10.1097/QAI.0b013e3181f4107a. [DOI] [PubMed] [Google Scholar]
- 4.Hygiene NYCDoHaM. NYC community health data: technical notes. 2007. [Google Scholar]
- 5.USPSTF. Screening for breast cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med. 2002;137:344–346. doi: 10.7326/0003-4819-151-10-200911170-00008. [DOI] [PubMed] [Google Scholar]
- 6. [Accessed 02/20/2011];Screening for Colorectal Cancer. 2008 2011, at http://www.uspreventiveservicestaskforce.org/uspstf/uspscolo.htm.)
- 7. [Accessed 02/20/2011];Screening for Cervical Cancer. 2003 at http://www.uspreventiveservicestaskforce.org/uspstf/uspscerv.htm.)
- 8.Screening for Lipid Disorders in Adults: U.S. Preventive Services Task Force Recommendation Statement. June 2008. 2008 (Accessed at http://www.uspreventiveservicestaskforce.org/uspstf08/lipid/lipidrs.htm)
- 9.Miettinen O. Proportion of disease caused or prevented by a given exposure, trait or intervention. Am J Epidemiol. 1974;99:325–332. doi: 10.1093/oxfordjournals.aje.a121617. [DOI] [PubMed] [Google Scholar]
- 10.Stefan MS, Blackwell JM, Crawford KM, et al. Patients' attitudes toward and factors predictive of human immunodeficiency virus testing of academic medical clinics. Am J Med Sci. 2010;340:264–267. doi: 10.1097/MAJ.0b013e3181e59c3e. [DOI] [PubMed] [Google Scholar]
- 11.Nash D, Chan C, Horowitz D, Vlahov D. Barriers and missed opportunities in breast and cervical cancer screening among women aged 50 and over, New York City, 2002. J Womens Health (Larchmt) 2007;16:46–56. doi: 10.1089/jwh.2006.0079. [DOI] [PubMed] [Google Scholar]
- 12.Katz ML, Tatum CM, Degraffinreid CR, Dickinson S, Paskett ED. Do cervical cancer screening rates increase in association with an intervention designed to increase mammography usage? J Womens Health (Larchmt) 2007;16:24–35. doi: 10.1089/jwh.2006.0071. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.NYCDOHMH. HIV Epidemiology and Field Services Semi-annual report. NYC: NYCDOHMH; 2010. [Google Scholar]
- 14.Results of the Expanded HIV-testing Initiative --- 25 Jurisdictions, United States 2007–2010. MMWR Morb Mortal Wkly Rep. 2011;60:805–810. [PubMed] [Google Scholar]
- 15.IOM. HIV screening and access to care: Exploring barriers and facilitators to expanded HIV-testing: Institute of Medicine. 2010. Sep 16, 2010. [PubMed] [Google Scholar]