Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2015 Apr 1.
Published in final edited form as: AIDS Care. 2013 Sep 9;26(4):459–465. doi: 10.1080/09540121.2013.832724

RELATIONSHIP BETWEEN HUNGER, ADHERENCE TO ANTIRETROVIRAL THERAPY AND PLASMA HIV RNA SUPPRESSION AMONG HIV-POSITIVE ILLICIT DRUG USERS IN A CANADIAN SETTING

Aranka Anema a,b, Thomas Kerr a,b, M-J Milloy a,b, Cindy Feng a, Julio S G Montaner a,b, Evan Wood a,b
PMCID: PMC4064571  NIHMSID: NIHMS585581  PMID: 24015838

Abstract

Food insecurity may be a barrier to achieving optimal HIV treatment-related outcomes among illicit drug users. This study therefore, aimed to assess the impact of severe food insecurity, or hunger, on plasma HIV RNA suppression among illicit drug users receiving antiretroviral therapy (ART). A cross-sectional Multivariate logistic regression model was used to assess the potential relationship between hunger and plasma HIV RNA suppression. A sample of n = 406 adults was derived from a community-recruited open prospective cohort of HIV-positive illicit drug users, in Vancouver, British Columbia (BC), Canada. A total of 235 (63.7%) reported “being hungry and unable to afford enough food,” and 241 (59.4%) had plasma HIV RNA < 50 copies/ml. In unadjusted analyses, self-reported hunger was associated with lower odds of plasma HIV RNA suppression (Odds Ratio = 0.59, 95% confidence interval [CI]: 0.39–0.90, p = 0.015). In multivariate analyses, this association was no longer significant after controlling for socio-demographic, behavioral, and clinical characteristics, including 95% adherence (Adjusted Odds Ratio [AOR] = 0.65, 95% CI: 0.37–1.10, p = 0.105). Multivariate models stratified by 95% adherence found that the direction and magnitude of this association was not significantly altered by the adherence level. Hunger was common among illicit drug users in this setting. Although, there was an association between hunger and lower likelihood of plasma HIV RNA suppression, this did not persist in adjusted analyses. Further research is warranted to understand the social-structural, policy, and physical factors shaping the HIV outcomes of illicit drug users.

Keywords: HIV, antiretroviral therapy, plasma viral load suppression, food security, hunger, adherence

INTRODUCTION

The universal uptake and effective use of antiretroviral therapy (ART) among injection drug users constitutes a key strategy to reduce AIDS-related deaths and HIV incidence (Joint United Nations Programme on HIV/AIDS [UNAIDS], 2010). ART use has shown to predictably suppress plasma HIV RNA to undetectable levels, reducing HIV-related morbidity, mortality, sero-discordant transmission (Abdool Karim et al., 2010; Cohen et al., 2011; Grant et al., 2010), and HIV incidence (Das et al., 2010; Fang et al., 2004; Montaner et al., 2006). However, illicit drug users face multiple, individual, and socio-structural barriers to achieving optimal HIV outcomes (Krüsi, Wood, Montaner, & Kerr, 2010; Wood, Kerr, Tyndall, & Montaner, 2008).

Illicit drug users are known to be vulnerable to food insecurity, defined as a state where people lack “physical, social, and economic access to sufficient, safe, and nutritious food that meet their dietary needs and food preferences for an active and healthy life” (Food and Agriculture Organization [FAO] of the United Nations, 2012), and often experience multiple forms of malnutrition (Hendricks & Gorbach, 2009; Smit et al., 1996). Among HIV-positive drug users, food insecurity and malnutrition have been associated with increased behavioral risk of HIV transmission (Shannon et al., 2011), suboptimal ART adherence (Kalichman et al., 2011), HIV-related wasting (Campa et al., 2005) and mortality (Anema et al., in press; Baum, 2000). Little is known, however, about the potential relationship between food insecurity, adherence to ART, and virologic response to ART in this population. Therefore, the present study was conducted to assess the possible impact of severe food insecurity on plasma HIV RNA suppression among HIV-positive illicit drug users in a Canadian context.

METHODS

Study population

Data were derived from the AIDS Care Cohort to evaluate Exposure to Survival Services (ACCESS), a prospective cohort of HIV-positive illicit drug users in Vancouver, British Columbia (BC) described elsewhere (Wood et al., 2004; Wood, Hogg et al., 2008). Briefly, the participants were recruited by snowball sampling and street-based outreach, and eligible for the participation if they were aged ≥ 18 years, HIV-seropositive, and used illicit drugs other than cannabis within a month of enrollment. Participant surveys were linked to clinical and laboratory profiles within a centralized, province-wide HIV/AIDS Drug Treatment Program database. Research ethics approval was obtained from the Providence Health Care/University of British Columbia Research Ethics Board.

The primary outcome variable was plasma HIV RNA suppression, defined as < 50 copies/mL (Thompson et al., 2010), measured using the Roche Amplicor Monitor assay (Roche Diagnostics, Laval, Quebec, Canada). A value for each participant was calculated by dichotomizing the mean plasma HIV RNA within the past six months. The primary explanatory variable was severe food insecurity, or hunger, understood as responding “yes” to: “I am hungry, but don’t eat because I can’t afford enough food”. Definitions and measures of food insecurity vary between international organizations, and require unique consideration in the context of HIV (Anema et al., 2013). In the USA, hunger is seen to arise from occasional or chronic inadequate food intake due to the lack of resources and includes physical sensations of hunger (Briefel & Woteki, 1992). The hunger variable used in this study was extracted from the US-based Radimer/Cornell food insecurity scale (Radimer, Olson, & Campbell, 1990), has been validated for use in low-income populations in North America (Frongillo, 1999; Kendall, Olson, & Frongillo, 1995; Radimer et al., 1990) and also included in the Canadian Community Health Survey (Health Canada, 2004). Secondary explanatory variables hypothesized to confound the relationship between hunger and HIV RNA suppression included: age (per 10 year increase); gender (male vs. female); Aboriginal ancestry (yes vs. no); homelessness (no fixed address, street vs. other); educational attainment (≥ high school vs. other); monthly income (≥ CAD$1,050 vs. < CAD$1,050, based on median split); money spent on drugs per day (≥ CAD$60 vs. < CAD$60, based on median split); daily heroin injection (yes vs. no); noninjection crack use (yes vs. no); injection crack use (yes vs. no); any injection or noninjection drug binging (yes vs. no); daily alcohol use (≥4 drinks vs. <4 drinks, based on median split); symptoms of depression in the past week (≥16 CES-D score vs. <16 CES-D score) (Andresen,1994); year of ART initiation; plasma HIV RNA (per log 10); CD4 cell count (per 100 cells/μl), recorded using flow cytometry and fluorescent monoclonal antibody analysis (Beckman Coulter, Inc., Mississauga, Ontario, Canada); and ART adherence (≥95% vs. < 95%), measured by prescription refill compliance in the past 12 months (Wood, Hogg et al., 2003). All behavioral variable definitions were identical to previous reports (Wood, Hogg et al., 2008) and based on a recall period of six months, unless specified otherwise.

Statistical analyses

Univariate statistics were used to determine the factors associated with hunger. To estimate the independent effect of hunger on plasma HIV RNA suppression, a multivariate model was also constructed using a manual backward stepwise approach described previously (Maldonado & Greenland, 1993; Rothman & Greenland, 1998). To test whether the relationship between hunger and plasma HIV RNA suppression was modified by ART adherence level, additional multivariate models were constructed, stratified by ≥95% vs. <95% adherence. All statistical analyses were completed using R v2.10.1 (R Foundation, Vienna, Austria).

RESULTS

A total of 406 participants were interviewed between 5 December 2005 and 16 March 2008 and deemed eligible for the present analysis. Overall, the median age within the sample was 44.4 years [interquartile range (IQR): 38.9–48.8 years]; 134 (33.0%) were female; and 158 (38.9%) reported Aboriginal ancestry. A total of 235 (63.7%) participants were reported being hungry and unable to afford enough food, and 165 (40.6%) had plasma HIV RNA < 50 copies/ml at the time of interview.

As shown in Table 1, the unadjusted factors associated with self-reported hunger among illicit drug users included: younger age (Odds Ratio [OR] = 0.75, 95% Confidence Interval [CI]: 0.56–0.99, p = 0.045); homelessness (OR = 2.89, 95% CI: 1.24–6.75, p = 0.014); spending ≥ $60/day on drugs (OR = 2.23, 95% CI: 1.43–3.48, p < 0.001); incarceration (OR = 1.71, 95% CI: 1.04 – 2.82, p < 0.035); and symptoms of depression (OR = 3.54, 95% CI: 2.26–5.55, p < 0.001).

Table 1.

Univariate analysis off actors associated with self-reported hunger among HIV-positive illicit drug users receiving antiretroviral therapy in Vancouver, Canada (n = 375).

Characteristic Hunger 235 (63.7%) No hunger 140 (37.3%) Odds Ratio (95% CI)a p – value
Age
 Median, interquartile range [IQR] 43.5 (38.7–48.0) 45.2 (39.6–49.9) 0.75 (0.56–0.99) 0.045
Gender
 Male 159 (67.7%) 97 (69.3%) 0.93 (0.59–1.46) 0.744
 Female 76 (32.3%) 43 (30.7%)
Aboriginal ancestry
 Yes 94 (40.0%) 50 (35.7%) 1.20 (0.78–1.85) 0.409
 No 141 (60.0%) 90 (64.3%)
Homelessness
 Yes 31 (13.2%) 7 (5.0%) 2.89 (1.24–6.75) 0.014
 No 204 (86.8%) 133 (95.0%)
Education status
 High school or greater 205 (91.9%) 126 (93.3%) 0.81 (0.36–1.87) 0.626
 Other 18 (8.1%) 9 (6.7%)
Monthly incomeb
 ≥ $1,050 110 (50.0%) 75 (57.7%) 0.73 (0.47–1.14) 0.164
 < $1,050 110 (50.0%) 55 (42.3%)
Money spent on drugs per dayb
 ≥ $60 138 (62.7%) 55 (43.0%) 2.23 (1.43–3.48) < 0.001
 < $60 82 (37.3%) 73 (57.0%)
Incarcerationc
 Yes 193 (82.1%) 102 (72.9%) 1.71 (1.04–2.82) 0.035
 No 42 (17.9%) 38 (27.1%)
Symptoms of depressiond
 Yes 176 (76.2%) 66 (47.5%) 3.54 (2.26–5.55) < 0.001
 No 55 (23.8%) 73 (52.5%)
Daily injection heroinc
 Yes 28 (11.9%) 12 (8.6%) 1.44 (0.71–2.94) 0.312
 No 207 (88.1%) 128 (91.4%)
Daily non-injection crackc
 Yes 37 (15.7%) 17 (12.1%) 1.35 (0.73–2.51) 0.338
 No 198 (84.3%) 123 (87.9%)
Daily injection cocainec
 Yes 21 (8.9%) 13 (9.3%) 0.96 (0.46–1.98) 0.909
 No 214 (91.1%) 127 (90.7%)
Any drug bingec
 Yes 104 (44.3%) 52 (37.1%) 1.34 (0.88–2.06) 0.177
 No 131 (55.7%) 88 (62.9%)
Daily alcohol useb,c
 ≥ 4 drinks 58 (24.7%) 33 (23.6%) 1.06 (0.65–1.74) 0.809
 < 4 drinks 177 (75.3%) 107 (76.4%)
Adherence to ARTd
 ≥95% 79 (33.6%) 52 (37.1%) 0.86 (0.55–1.33) 0.489
 <95% 156 (66.4%) 88 (62.9%)
CD4 cell count (per 100 cell increase)
 Median, IQR 2.66 (1.59–4.14) 3.10 (2.01–4.63) 0.93 (0.83–1.04) 0.190
Plasma HIV RNA (per Log 10 increase)
 Median, IQR 2.73 (1.65–4.42) 1.83 (1.65–4.39) 1.10 (0.95–1.28) 0.198
Plasma HIV RNA suppression
 Yes 84 (55.3%) 68 (44.7%) 0.59 (0.39–0.90) 0.015
 No 151 (67.7%) 72 (32.3%)

Notes:

a

Confidence interval.

b

Based on median split.

c

Within last six months of interview.

d

Within last week of interview.

e

Within last 12 months of interview.

Adjusted analyses of factors associated with plasma HIV RNA suppression among illicit drug users receiving ART are presented in Table 2. Hunger was no longer significantly associated with virologic suppression after controlling for age, homelessness, daily expenditure on drugs, monthly income, and 95% adherence (adjusted odds ratio [AOR] = 0.64, 95% CI: 0.37–1.10, p = 0.105). To assess the possibility of a Type II error, we conducted post hoc power calculations which showed that power = 0.74 (β = 26%) (Hsieh, Bloch, & Larsen, 1998). A significant association between hunger and HIV RNA suppression was uncovered only after deleting homeless and age from the final model.

Table 2.

Multivariate analysis off actors associated with plasma HIV RNA suppression among HIV-positive illicit drug users receiving antiretroviral therapy in Vancouver, Canada (n = 406).

Variable AORa 95% CIb p – value
Self-reported hunger
 Yes vs. no 0.64 037–1.10 0.105
Age
 Per 10 year increase 1.65 1.13–2.41 0.010
Homelessness
 Yes vs. no 0.39 0.15–1.02 0.055
Monthly income
 ≥ $1,050 vs. < $1,050c 0.72 0.42–1.21 0.216
Average spent on drugs per dayc
 ≥ $60 vs. < $60 0.82 0.49–1.39 0.467
Adherence to ARTd
 ≥ 95% vs. < 95% 7.30 4.26–12.49 < 0.001

Notes:

a

Adjusted Odds Ratio.

b

95% Confidence Interval.

c

Based on median split.

d

Within last 12 months of interview.

In adjusted analyses stratified by levels of adherence, among the participants with ≥ 95% adherence, hunger was not significantly associated with reduced odds of plasma HIV RNA suppression (AOR: 0.61, 95% CI: 0.23–1.58, p = 0.307). Similarly, among individuals with <95% adherence, hunger was not significantly associated with a lower odds of plasma HIV RNA suppression (AOR: 0.56, 95% CI: 0.26–1.22, p = 0.144).

DISCUSSION

Over two-thirds of HIV-positive illicit drug users reported severe food insecurity in this sample, double that reported among HIV-positive people in diverse high resource settings (Anema et al., 2011; Kalichman et al., 2010; Vogenthaler et al., 2010), and over 20 times greater than prevalence reported in the general Canadian population (Health Canada, 2007). Approximately half of the participants in this setting had suppressed viral loads. While hunger was inversely associated with this outcome in univariate analysis, the strength of association weakened after controlling for socio-demographic, behavioral, and clinical characteristics. Varying levels of adherence did not significantly alter the magnitude or direction of this association (data available from corresponding author).

To the best of our knowledge, this study is the first to evaluate the potential impact of hunger on virologic outcomes in a setting with access to universal health care and free ART, independent of the potential confounding effect of financial barriers. The direction of association observed in the final model was consistent with studies in the USA that have found inverse associations between food insecurity and virologic suppression (Kalichman et al., 2011; Wang et al., 2011; Weiser et al., 2009). The lack of a statistically significant association between hunger and virologic suppression in the adjusted analysis may be due to several factors. First, the local environment has subsidized HIV treatment and support, which may have a protective effect in this setting. Second, the residual confounding may be present due to the categorization of continuous variables, confounder misclassification or failure to include unobserved and unknown confounders (Altman & Royston, 2006; Szklo & Nieto, 2007). Finally, the sample may have been underpowered to detect a true association due to limited variability in the predictor variable, the cross-sectional study design or the fact that drug use is itself a strong predictor of poor virologic outcomes (Krüsi, Milloy et al., 2010). However, the latter is not supported by post hoc power calculations (data not shown).

In multivariate models stratified by varying ART adherence levels, the direction and magnitude of the association between hunger and plasma HIV RNA viral load suppression remained unaltered, suggesting that adherence was not significant effect modifier in this relationship or that residual confounding influenced the effect estimate. These findings are counterintuitive and as such suggest a need for further studies that explore the association between hunger, adherence, and virologic suppression in larger or pooled samples of illicit drug users and for studies to explore potential nonbehavioral (i.e., mental health and nutritional) pathways (Weiser et al., 2011) in the relationship between hunger and virologic suppression. Of note, the measure of adherence used in this study is based on refill compliance. While, we have previously shown this measure of adherence to reliably predict both the virological suppression (Low-Beer, Yip, O’Shaughnessy, Hogg, & Montaner, 2000; Palepu et al., 2001; Wood, Montaner et al., 2003) and mortality (Wood, Hogg et al., 2008, Wood, Hogg et al., 2003), it is possible that refill compliance may be an incomplete surrogate of true drug exposure in this setting.

The high prevalence of hunger suggests that illicit drug users in this setting have inadequate individual-level and environmental supports (Rhodes, 2002; Rhodes, Singer, Bourgois, Friedman, & Strathdee, 2005). Given the role of food insecurity and malnutrition in HIV disease progression (Anema, Vogenthaler, Frongillo, Kadiyala, & Weiser, 2009; de Pee & Semba, 2010), interventions to mitigate hunger should be piloted and evaluated, including food support, within existing harm reduction and HIV-services. Operational research should ensure robust study designs, adequate sample size, validated food security and nutrition instruments, and harmonized composite HIV endpoints, to foster generalizability and comparability of findings (Chandrasekhar & Gupta, 2011; Wittkop et al., 2010). Low ART adherence among illicit drug users remains a concern in this setting (Nolan et al., 2011; Wood, Montaner et al., 2003) and was the most important predictor of virologic suppression in this study. Addressing known socio-structural barriers to ART adherence among illicit drug users, including incarceration (Milloy et al., 2011), homelessness (Milloy et al., 2012), and gender-related factors (Tapp et al., 2011) should be a public health priority in this setting.

This study has several limitations. Participants were not randomly selected, and therefore not representative of all HIV-positive drug users in BC. The cross-sectional study design limits ability to infer causation and temporality. Responder bias, and potentially social desirability bias, may have led to nondifferential misclassification of hunger, biasing our estimates toward the null. Self-reported nutritional estimates are less reliable than clinical nutrition markers (Gorber, Tremblay, Moher, & Gorber,2007); future studies should apply dietary intake assessment methods validated for use among HIV-positive illicit drug users (Sahni, Forrester, & Tucker, 2007; Smit & Tang, 2000).

In summary, we found that hunger was common among HIV-positive illicit drug users in this setting. Although, there was an association between hunger and lower likelihood of plasma HIV RNA suppression, this did not persist in multivariate analyses. Further research is required to describe the relationships between hunger, adherence, and HIV treatment outcomes among illicit drug users. Research is additionally warranted to understand the social-structural, policy, and physical factors shaping the health outcomes of individual drug users in this setting. Public health efforts should evaluate the possible role of nutritional support within existing harm reduction and HIV services.

Acknowledgments

The authors thank the study participants for their contributions to the research, as well as current and past researchers and staff. We would specifically like to thank Deborah Graham, Tricia Collingham, Carmen Rock, Brandon Marshall, Caitlin Johnston, Steve Kain, and Benita Yip for their research and administrative assistance. This study is supported by the US National Institutes of Health (R01-DA021525) and the Canadian Institutes of Health Research (MOP-79297 and RAA-79918.). M-JM is supported by the Michael Smith Foundation for Health Research and the Canadian Institutes of Health Research. This work was supported in part by a Tier 1 Canada Research Chair in Inner-City Medicine awarded to Dr. Wood.

References

  • 1.Abdool Karim Q, Abdool Karim SS, Frohlich JA, Grobler AC, Baxter C, Mansoor LE, Taylor D CAPRISA 004 Trial Group. Effectiveness and safety of tenofovir gel, an antiretroviral microbicide, for the prevention of HIV infection in women. Science. 2010;329(5996):1168–1174. doi: 10.1126/science.1193748. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Altman DG, Royston P. The cost of dichotomising continuous variables. BMJ. 2006;332(7549):1080. doi: 10.1136/bmj.332.7549.1080. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Andresen EM. Screening for depression in well older adults: Evaluation of a short form of the CES-D (Center for Epidemiologic Studies Depression scale) American Journal of Preventive Medicine. 1994;10(2):77. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/?term=Screening+for+depression+in+well+older+adults%3A+Evaluation+of+a+short+form+of+the+CES-D+%28Center+for+Epidemiologic+Studies+Depression+scale%. [PubMed] [Google Scholar]
  • 4.Anema A, Chan K, Chen Y, Weiser S, Montaner JSG, Hogg RS. Relationship between food insecurity and mortality among HIV-positive injection drug users receiving antiretroviral therapy in British Columbia, Canada. PLOS ONE. 2013;8(5):e61277. doi: 10.1371/journal.pone.0061277. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Anema A, Fielden SJ, Castelman T, Grede N, Heap A, Bloem M. Food insecurity in the context of HIV: Towards harmonized definitions and indicators. AIDS and Behavior. doi: 10.1007/s10461-013-0659-x. (in press) [DOI] [PubMed] [Google Scholar]
  • 6.Anema A, Vogenthaler N, Frongillo EA, Kadiyala S, Weiser SD. Food insecurity and HIV/AIDS: Current knowledge, gaps, and research priorities. Current HIV/AIDS Reports. 2009;6(4):224–231. doi: 10.1007/s11904-009-0030-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Anema A, Weiser SD, Fernandes KA, Ding E, Brandson EK, Palmer A, Hogg RS. High prevalence of food insecurity among HIV-infected individuals receiving HAART in a resource-rich setting. AIDS Care. 2011;23:221–230. doi: 10.1080/09540121.2010.498908. [DOI] [PubMed] [Google Scholar]
  • 8.Baum MK. Role of micronutrients in HIV-infected intravenous drug users. Journal of Acquired Immune Deficiency Syndromes. 2000;25(Suppl 1):S49–52. doi: 10.1097/00042560-200010001-00008. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/11126427. [DOI] [PubMed] [Google Scholar]
  • 9.Briefel R, Woteki C. Development of the food sufficiency questions for the third national health and nutrition examination survey. Journal of Nutrition Education and Behavior. 1992;24(Suppl 1):24S–28S. [Google Scholar]
  • 10.Campa A, Zhifang Y, Lai S, Xue L, Phillips JC, Sales S, Baum MK. HIV-related wasting in HIV-infected drug users in the era of highly active antiretroviral therapy. Clinical Infectious Diseases. 2005;41(8):1179–1185. doi: 10.1086/444499. [DOI] [PubMed] [Google Scholar]
  • 11.Chandrasekhar A, Gupta A. Nutrition and disease progression pre–highly active antiretroviral therapy (HAART) and post-HAART: Can good nutrition delay time to HAART and affect response to HAART? The American Journal of Clinical Nutrition. 2011;94(6):1703S–1715S. doi: 10.3945/ajcn.111.019018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Cohen MS, Chen YQ, McCauley M, Gamble T, Hosseinipour MC, Kumarasamy N, Fleming TR for the HPTN 052 Study Team. Prevention of HIV-1 infection with early antiretroviral therapy. The New England Journal of Medicine. 2011;365(6):493–505. doi: 10.1056/NEJMoa1105243. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Das M, Chu PL, Santos GM, Scheer S, Vittinghoff E, McFarland W, Colfax GN. Decreases in community viral load are accompanied by reductions in new HIV infections in San Francisco. PLoS One. 2010;5(6):e11068. doi: 10.1371/journal.pone.0011068. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.de Pee S, Semba RD. Role of nutrition in HIV infection: Review of evidence for more effective programming in resource-limited settings. Food and Nutrition Bulletin. 2010;31(4):S313. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21214036. [PubMed] [Google Scholar]
  • 15.Fang CT, Hsu HM, Twu SJ, Chen MY, Chang YY, Hwang JS Division of AIDS and STD, Center for Disease Control Department of Health Executive Yuan. Decreased HIV transmission after a policy of providing free access to highly active antiretroviral therapy in Taiwan. The Journal of Infectious Diseases. 2004;190(5):879–885. doi: 10.1086/422601. [DOI] [PubMed] [Google Scholar]
  • 16.Food and Agriculture Organization (FAO) of the United Nations, World Food Programme (WFP) and International Fund for Agricultural Development (IFAD) The State of Food Insecurity in the World: Economic growth is necessary but not sufficient to accelerate reduction of hunger and malnutrition. FAO; Rome: 2012. Retrieved from http://www.fao.org/docrep/016/i3027e/i3027e00.htm. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Frongillo E. Validation of measures of food insecurity and hunger. Journal of Nutrition. 1999;129(2S Suppl):506S–509S. doi: 10.1093/jn/129.2.506S. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/10064319. [DOI] [PubMed] [Google Scholar]
  • 18.Gorber SC, Tremblay M, Moher D, Gorber B. A comparison of direct vs. self-report measures for assessing height, weight and body mass index: A systematic review. Obesity Reviews. 2007;8(4):307–326. doi: 10.1111/j.1467-789X.2007.00347.x. [DOI] [PubMed] [Google Scholar]
  • 19.Grant RM, Lama JR, Anderson PL, McMahan V, Liu AY, Vargas L, Glidden DV for the iPrEx Study Team. Pre-exposure chemoprophylaxis for HIV prevention in men who have sex with men. The New England Journal of Medicine. 2010;363(27):2587–2599. doi: 10.1056/NEJMoa1011205. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Health Canada. Canadian Community Health Survey, Cycle 2.2, Nutrition (2004) - Income-Related Household Food Security in Canada, Health Canada. Household Food Security Survey Module (HFSSM); 2004. Retrieved from http://www.hc-sc.gc.ca/fn-an/surveill/nutrition/commun/insecurit/status-situation-eng.php-as. [Google Scholar]
  • 21.Health Canada. Office of nutrition policy and promotion. Income-related household food security in Canada. 2007 Ottawa Report No. H164–42/2007E. Retrieved from http://www.hc-sc.gc.ca/fn-an/surveill/nutrition/commun/income_food_sec-sec_alim-eng.php.
  • 22.Hendricks K, Gorbach S. Nutrition issues in chronic drug users living with HIV infection. Addiction Science and Clinical Practice. 2009;5(1):16–23. doi: 10.1151/ascp095116. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Hsieh FY, Bloch DA, Larsen MD. A simple method of sample size calculation for linear and logistic regression. Statistics in Medicine. 1998;17(14):1623–1634. doi: 10.1002/(sici)1097-0258(19980730)17:14<1623::aid-sim871>3.0.co;2-s. [DOI] [PubMed] [Google Scholar]
  • 24.Joint United Nations Programme on HIV/AIDS (UNAIDS) Strategy: Getting to Zero. 2010. UNAIDS 2011–2015. [Google Scholar]
  • 25.Kalichman SC, Cherry C, Amaral C, White D, Kalichman MO, Pope H, Macy R. Health and treatment implications of food insufficiency among people living with HIV/AIDS, Atlanta, Georgia. Journal of Urban Health. 2010;87(4):631–641. doi: 10.1007/s11524-010-9446-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Kalichman SC, Pellowski J, Kalichman MO, Cherry C, Detorio M, Caliendo AM, Schinazi RF. Food insufficiency and medication adherence among people living with HIV/AIDS in urban and peri-urban settings. Prevention Science. 2011;12(3):324–332. doi: 10.1007/s11121-011-0222-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Kendall A, Olson CM, Frongillo EA., Jr Validation of the Radmier/Cornell measures of hunger and food insecurity. Journal of Nutrition. 1995;125(11):2793–2801. doi: 10.1093/jn/125.11.2793. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/7472659. [DOI] [PubMed] [Google Scholar]
  • 28.Krüsi A, Milloy MJ, Kerr T, Zhang R, Guillemi S, Hogg R, Wood E. Ongoing drug use and outcomes from highly active antiretroviral therapy among injection drug users in a Canadian setting. Antiviral Therapy. 2010;15(5):789–796. doi: 10.3851/IMP1614. [DOI] [PubMed] [Google Scholar]
  • 29.Krüsi A, Wood E, Montaner J, Kerr T. Social and structural determinants of HAART access and adherence among injection drug users. International Journal of Drug Policy. 2010;21(1):4–9. doi: 10.1016/j.drugpo.2009.08.003. [DOI] [PubMed] [Google Scholar]
  • 30.Low-Beer S, Yip B, O’Shaughnessy MV, Hogg RS, Montaner JS. Adherence to triple therapy and viral load response. Journal of Acquired Immune Deficiency Syndromes. 2000;23(4):360–361. doi: 10.1097/00126334-200004010-00016. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/10836763. [DOI] [PubMed] [Google Scholar]
  • 31.Maldonado G, Greenland S. Simulation study of confounder-selection strategies. American Journal of Epidemiology. 1993;138(11):923–936. doi: 10.1093/oxfordjournals.aje.a116813. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/8256780. [DOI] [PubMed] [Google Scholar]
  • 32.Milloy MJ, Kerr T, Bangsberg DR, Buxton J, Parashar S, Guillemi S, Wood E. Homelessness as a structural barrier to effective antiretroviral therapy among HIV-seropositive illicit drug users in a Canadian setting. AIDS Patient Care and STDs. 2012;26(1):60–67. doi: 10.1089/apc.2011.0169. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Milloy MJ, Kerr T, Buxton J, Rhodes T, Guillemi S, Hogg R, Wood E. Dose-response effect of incarceration events on nonadherence to HIV antiretroviral therapy among injection drug users. The Journal of Infectious Diseases. 2011;203(9):1215–1221. doi: 10.1093/infdis/jir032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Montaner JS, Hogg R, Wood E, Kerr T, Tyndall M, Levy AR, Harrigan PR. The case for expanding access to highly active antiretroviral therapy to curb the growth of the HIV epidemic. The Lancet. 2006;368(9534):531–536. doi: 10.1016/S0140-6736(06)69162-9. [DOI] [PubMed] [Google Scholar]
  • 35.Nolan S, Milloy MJ, Zhang R, Kerr T, Hogg RS, Montaner JSG, Wood E. Adherence and plasma HIV RNA response to antiretroviral therapy among HIV-seropositive injection drug users in a Canadian setting. AIDS Care. 2011;23:980–987. doi: 10.1080/09540121.2010.543882. [DOI] [PubMed] [Google Scholar]
  • 36.Palepu A, Yip B, Miller C, Strathdee SA, O’Shaughnessy MV, Montaner JSG, Hogg RS. Factors associated with the response to antiretroviral therapy among HIV-infected patients with and without a history of injection drug use. AIDS. 2001;15(3):423–424. doi: 10.1097/00002030-200102160-00021. [DOI] [PubMed] [Google Scholar]
  • 37.Radimer KL, Olson CM, Campbell CC. Development of indicators to assess hunger. Journal of Nutrition. 1990;120(Suppl 11):1544–1548. doi: 10.1093/jn/120.suppl_11.1544. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/2243303. [DOI] [PubMed] [Google Scholar]
  • 38.Rhodes T. The ‘risk environment’: A framework for understanding and reducing drug-related harm. International Journal of Drug Policy. 2002;13(2):85–94. [Google Scholar]
  • 39.Rhodes T, Singer M, Bourgois P, Friedman SR, Strathdee SA. The social structural production of HIV risk among injecting drug users. Social Science and Medicine. 2005;61(5):1026–1044. doi: 10.1016/j.socscimed.2004.12.024. [DOI] [PubMed] [Google Scholar]
  • 40.Rothman KJ, Greenland S. Modern epidemiology. New York, NY, United States: Lippincott Williams & Wilkins; 1998. [Google Scholar]
  • 41.Sahni S, Forrester JE, Tucker KL. Assessing dietary intake of drug-abusing hispanic adults with and without human immunodeficiency virus infection. Journal of the American Dietetic Association. 2007;107(6):968–976. doi: 10.1016/j.jada.2007.04.003. [DOI] [PubMed] [Google Scholar]
  • 42.Shannon K, Kerr T, Milloy MJ, Anema A, Zhang R, Montaner JSG, Wood E. Severe food insecurity is associated with elevated unprotected sex among HIV-seropositive injection drug users independent of HAART use. AIDS. 2011;25(16):2037–2042. doi: 10.1097/QAD.0b013e32834b35c9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Smit E, Graham NMH, Tang A, Flynn C, Solomon L, Vlahov D. Dietary intake of community-based HIV-1 seropositive and seronegative injecting drug users. Nutrition. 1996;12(7–8):496–501. doi: 10.1016/s0899-9007(96)91726-8. [DOI] [PubMed] [Google Scholar]
  • 44.Smit E, Tang A. Nutritional assessment in intravenous drug users with HIV/AIDS. Journal of Acquired Immune Deficiency Syndromes. 2000;25(Suppl 1):S62–69. doi: 10.1097/00042560-200010001-00010. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/?term=Nutritional+assessment+in+intravenous+drug+users+with+HIV%2FAIDS. [DOI] [PubMed] [Google Scholar]
  • 45.Szklo MF, Nieto J. Epidemiology: Beyond the basics. Boston, MA: Jones and Bartlett Publishers; 2007. [Google Scholar]
  • 46.Tapp C, Milloy MJ, Kerr T, Zhang R, Guillemi S, Hogg RS, Wood E. Female gender predicts lower access and adherence to antiretroviral therapy in a setting of free healthcare. BMC Infectious Diseases. 2011;11(1):86. doi: 10.1186/1471-2334-11-86. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Thompson MA, Aberg JA, Cahn P, Montaner JS, Rizzardini G, Telenti A, Schooley RT International AIDS Society-USA. Antiretroviral treatment of adult HIV infection: 2010 recommendations of the International AIDS Society-USA panel. The Journal of the American Medical Association. 2010;304(3):321–333. doi: 10.1001/jama.2010.1004. [DOI] [PubMed] [Google Scholar]
  • 48.Vogenthaler NS, Hadley C, Lewis SJ, Rodriguez AE, Metsch LR, del Rio C. Food insufficiency among HIV-infected crack-cocaine users in Atlanta and Miami. Public Health Nutrition. 2010;13(9):1478–1484. doi: 10.1017/S1368980009993181. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Wang EA, McGinnis KA, Fiellin DA, Goulet JL, Bryant K, Gibert CL VACS Project Team. Food insecurity is associated with poor virologic response among HIV-infected patients receiving antiretroviral medications. Journal of General Internal Medicine. 2011;26(9):1012–1018. doi: 10.1007/s11606-011-1723-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Weiser SD, Frongillo EA, Ragland K, Hogg RS, Riley ED, Bangsberg DR. Food insecurity is associated with incomplete HIV RNA suppression among homeless and marginally housed HIV-infected individuals in San Francisco. Journal of General Internal Medicine. 2009;24(1):14–20. doi: 10.1007/s11606-008-0824-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Weiser SD, Young SL, Cohen CR, Kushel MB, Tsai AC, Tien PC, Bangsberg DR. Conceptual framework for understanding the bidirectional links between food insecurity and HIV/AIDS. American Journal of Clinical Nutrition. 2011;94(6):1729S–1739S. doi: 10.3945/ajcn.111.012070. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Wittkop L, Smith C, Fox Z, Sabin C, Richert L, Aboulker JP NEAT-WP4. Methodological issues in the use of composite endpoints in clinical trials: examples from the HIV field. Clinical Trials. 2010;7(1):19–35. doi: 10.1177/1740774509356117. [DOI] [PubMed] [Google Scholar]
  • 53.Wood E, Hogg RS, Bonner S, Kerr T, Li K, Palepu A, Montaner JS. Staging for antiretroviral therapy among HIV-infected drug users. The Journal of the American Medical Association. 2004;292(10):1175–1177. doi: 10.1001/jama.292.10.1175-b. [DOI] [PubMed] [Google Scholar]
  • 54.Wood E, Hogg RS, Lima VD, Kerr T, Yip B, Marshall BD, Montaner JS. Highly active antiretroviral therapy and survival in HIV-infected injection drug users. The Journal of the American Medical Association. 2008;300(5):550–554. doi: 10.1001/jama.300.5.550. [DOI] [PubMed] [Google Scholar]
  • 55.Wood E, Hogg RS, Yip B, Harrigan PR, O’Shaughnessy MV, Montaner JS. Effect of medication adherence on survival of HIV-infected adults who start highly active antiretroviral therapy when the CD4 + cell count is 0.200 to 0.350 × 10(9) cells/L. Annals of Internal Medicine. 2003;139(10):810–816. doi: 10.7326/0003-4819-139-10-200311180-00008. [DOI] [PubMed] [Google Scholar]
  • 56.Wood E, Kerr T, Tyndall MW, Montaner JS. A review of barriers and facilitators of HIV treatment among injection drug users. AIDS. 2008;22(11):1247–1256. doi: 10.1097/QAD.0b013e3282fbd1ed. [DOI] [PubMed] [Google Scholar]
  • 57.Wood E, Montaner JS, Yip B, Tyndall MW, Schechter MT, O’Shaughnessy MV, Hogg RS. Adherence and plasma HIV RNA responses to highly active antiretroviral therapy among HIV-1 infected injection drug users. Canadian Medical Association Journal. 2003;169(7):656–661. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/14517122. [PMC free article] [PubMed] [Google Scholar]

RESOURCES