A Cross Section Study to Determine the Prevalence of Antibodies against HIV Infection among Hepatitis B and C Infected Individuals

BACKGROUND: 

There are limited data regarding human immunodeficiency virus (HIV) prevalence among hepatitis B virus (HBV) or hepatitis C virus (HCV) infected individuals. The aim of this cross-sectional study is to determine the prevalence of HBV and HCV infection among HIV individuals;

METHODS: 

A total of 409 patients (126 HBV+ and 283 HCV+) referred to the Brazilian Reference Laboratory for Viral Hepatitis from 2010 to 2013 donated serum samples. Anti-HIV, HBsAg, anti-HBc, anti-HBs, anti-HBcIgM, anti-HBe, HBeAg, and anti-HCV antibodies were measured, and anti-HCV positive samples were tested for viral RNA and genotype;

RESULTS: 

The anti-HIV antibody prevalence was 10.31% and 4.59% among HBV+ and HCV+ patients, respectively. The HCV mean (SD) viral load was log 5.14 ± 1.64 IU/mL, and genotype I was most prevalent (163/283). Anti-HBs and anti-HBc were detected in 40% and 26% of HCV+ individuals, respectively. Among the HBV+ population, the presence of anti-HIV antibodies was associated with male gender, marital status (married), tattoo, sexual orientation, sexual practices (oral sex and anal sex), history of sexually transmitted diseases (STDs), history of viral hepatitis treatment, and a sexual partner with hepatitis or HIV. For the HCV+ group, the presence of anti-HIV antibodies was associated with female gender, marital status (married), anal intercourse, previous history of STDs, and number of sexual partners;

CONCLUSION: 

A high prevalence of anti-HIV antibodies was found among individuals with HBV and HCV, showing the importance of education programmes towards HIV infection among HBV- and HCV-infected individuals.

Full article at:   http://goo.gl/7pJhyw

By:  Flores GL1, de Almeida AJ2, Miguel JC3, Cruz HM4, Portilho MM5, de P Scalioni L6, Marques VA7, Lewis-Ximenez LL8, Lampe E9, Melo Villar L10.

• 1Viral Hepatitis Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 210360-040, Brazil. geane@ioc.fiocruz.br.
• 2Viral Hepatitis Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 210360-040, Brazil. adilsonjoal@ioc.fiocruz.br.
• 3Viral Hepatitis Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 210360-040, Brazil. julicm@ioc.fiocruz.br.
• 4Viral Hepatitis Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 210360-040, Brazil. h.medina@ioc.fiocruz.br.
• 5Viral Hepatitis Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 210360-040, Brazil. moyramp@ioc.fiocruz.br.
• 6Viral Hepatitis Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 210360-040, Brazil. lescali@ioc.fiocruz.br.
• 7Viral Hepatitis Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 210360-040, Brazil. vmarques@ioc.fiocruz.br.
• 8Viral Hepatitis Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 210360-040, Brazil. llewis@ioc.fiocruz.br.
• 9Viral Hepatitis Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 210360-040, Brazil. elampe@ioc.fiocruz.br.
• 10Viral Hepatitis Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 210360-040, Brazil. lvillar@ioc.fiocruz.br. 
• Int J Environ Res Public Health. 2016 Mar 11;13(3). pii: E314. doi: 10.3390/ijerph13030314.

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A Cross Sectional Study: Knowledge, Attitude, Perception, Misconception & Views (KAPMV) of Adult Family Members of People Living with HIV/AIDS

We intended to assess knowledge, attitude, perception, misconception and views (KAP-MV) of family members of PLWHA. 

A cross-sectional retrospective study conducted in Anti-retroviral centre of Mahatma Gandhi Memorial—MGM hospital, Warangal, Telangana, South-India from July to September 2014. A questionnaire containing 41 items was distributed among adult family members accompanying patients living with HIV/AIDS-PLWHA. Level of KAP-MV was categorized into poor (0–28), average (29–55) and good (56–82). Analysis was performed by Pearson’s Chi square, analysis of variance and Spearman’s correlation test on 41 variables using SPSS version 21 and p < 0.01. 538 questionnaires were distributed, response rate was (96 %). 

On knowledge scale, respondents had a mean score of 8.0 ± 1.7, attitude 5.8 ± 3.4, perception 23.4 ± 4.1, misconceptions 8.0 ± 2.1 and views 8.0 ± 3.9. The respondents mean score was 53.2 ± 9.1 (64.9 %). 

Overall, level of education, marital status, religious beliefs, and employment status has significant (p < 0.001) associations with KAP-MV. Knowledge was significantly correlated with respondents’ attitude (r = −0.15, p < 0.001), perception (0.39; p < 0.001), and views (0.381; p < 0.001). Family members of PLWHA with less knowledge score had more negative attitude, perception and views. Level of education, marital status, religious beliefs and employment status were identified as key barriers. Interventions targeting family members of PLWHA are warranted.

Table 2

Respondents knowledge and attitude about HIV/AIDS in Warangal, South India (n = 515)

	Variables	Correct answer	Correct answers (%)	Wrong answers (%)	Mean ± standard deviation
	General knowledge
1.	AIDS abbreviation	Acquired Immunodeficiency Virus	316 (61.4)a	199 (38.6)	8.01 ± 1.76
2.	AIDS a transmittable disease	Yes	485 (94.2)	30 (5.8)
3.	AIDS a hereditary disease	No	449 (87.2)	66 (12.8)
4.	AIDS cured at this moment	No	454 (88.2)	61 (11.8)
5.	There is a vaccine for AIDS	No	475 (92.2)	40 (7.8)
	Attitudes
6.	Feel comfortable talking with AIDS patients	Yes	277 (53.8)	238 (46.2)	5.80 ± 3.47
7.	Feel comfortable working with AIDS patients	Yes	275 (53.4)	240 (46.6)
8.	Living with AIDS patients in same house	Yes	266 (51.7)a	249 (48.3)
9.	Feel empathy towards AIDS patients	Yes	282 (54.8)	233 (45.2)
10.	AIDS patients deserve free treatment	Yes	394 (76.5)	121 (23.5)
	Perception
11.	Sexual intercourse without a condom with HIV-infected person	Yes	469 (91.1)	46 (8.9)	23.44 ± 4.19
12.	Sharing needle with HIV-infected organ	Yes	499 (96.9)	16 (3.1)
13.	Transfusion of HIV-infected blood or receiving HIV-infected organ	Yes	498 (96.7)	17 (3.3)
14.	Having sex with multiple sexual partners with unknown HIV status	Yes	484 (94.0)	31 (6.0)
15.	From an HIV positive mother to her fetus	Yes	479 (93.0)	36 (7.0)
16.	Sharing personal items such as shaving blades	Yes	438 (85.0)	77 (15.0)
17.	Breast Feeding from a HIV-infected mother	Yes	410 (79.6)	105 (20.4)
18.	Having tattoo or body piercing	No	337 (65.4)	178 (34.6)
19.	Kissing can transmit HIV-infection	No	147 (28.5)a	368 (71.5)
20.	Mosquito bites	No	460 (89.3)	55 (10.7)
21.	Sharing/eating a meal with an HIV-infected person	No	452 (87.8)	63 (12.2)
22.	Sharing water or drinks with an HIV-infected person	No	465 (90.3)	50 (9.7)
23.	Using Public toilets	No	470 (91.3)	45 (8.7)
24.	Casual contacts (hugging or touching) with an HIV-infected person	No	427 (82.9)a	88 (17.1)

aMost wrongly answered

Table 3

Respondents views and misconceptions about HIV/AIDS (n = 515)

	Variables	Correct answer	Correct answers (%)	Wrong answers (%)	Mean ± standard deviation
	Respondents views
25.	Avoid taking illicit drugs/use of intravenous drugs	Yes	477 (92.6)	38 (7.4)	21.00 ± 3.98
26.	By avoiding sharing needles and syringes	Yes	501 (97.3)	14 (2.7)
27.	Having sex with only one faithful, uninfected partner	Yes	494 (95.9)	21 (4.1)
28.	Using condoms during sexual intercourse	Yes	491 (95.3)	24 (4.7)
29.	Treating STDs promptly	Yes	480 (93.2)	35 (6.8)
30.	Screening donated blood before transfusion	Yes	463 (89.9)	52 (10.1)
31.	Not sharing toilets with an infected person	No	411 (79.8)	104 (20.2)
32.	Not sharing food with an infected person	No	431 (83.7)	84 (16.3)
33.	Isolating people living with HIV/AIDS	No	367 (71.3)a	149 (28.7)
34.	Do not stay with infected person on same house	No	448 (87.0)	67 (13.0)
35.	Do not have casual contact with infected person	No	439 (85.2)	76 (14.8)
36.	Avoid mosquito bites for HIV transmission	No	406 (78.8)	109 (21.2)
	Misconceptions
37.	Love is a reason for HIV/AIDS	No	337 (65.4)a	178 (34.6)	8.03 ± 2.19
38.	AIDS is a punishment of God	No	373 (72.4)	142 (27.6)
39.	AIDS can treat by holy water	No	442 (85.8)	73 (14.2)
40.	AIDS do not come after marriage	No	454 (88.2)	61 (11.8)
41.	AIDS can be transmitted by the cough	No	461 (89.5)	54 (10.5)

aMost wrongly answered

Below:

Full article at:   http://goo.gl/ltmOcj

By:   Akshaya Srikanth Bhagavathula, Deepak Kumar Bandari, Asim Ahmad Elnour, Akram Ahmad, Muhammad Umair Khan, Mohamed Baraka, Farah Hamad, and Abdulla Shehab

Department of Clinical Pharmacy, University of Gondar College of Medicine and Health Sciences, Gondar, Ethiopia

Department of Clinical Pharmacy, Vagdevi College of Pharmacy, Warangal, Telangana India

Pharmacology Department, College of Medicine and Health Sciences, UAE University, Dubai, UAE

Department of Clinical Pharmacy, UCSI University, Cheras, Kuala Lumpur, Malaysia

Department of Clinical Pharmacy, College of Clinical Pharmacy, University of Dammam Eastern Province, Dammam, Kingdom of Saudi Arabia

Department of Pharmaceutics, College of Pharmacy, Ajman University of Sciences and Technology, Ajman, UAE

Internal Medicine Department, College of Medicine and Health Sciences (CMHS), UAE University, Al Ain, UAE

Akshaya Srikanth Bhagavathula, Email: moc.liamg@dmrahpyahska.

  

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Marital Status, Social Support & Depressive Symptoms among Lesbian & Heterosexual Women

The current study investigated social support and relationship status (single, dating-but-not-cohabiting, cohabiting, domestic partnership/civil union, married) as predictors of depressive symptoms among lesbian and heterosexual women. 

The study aimed to determine whether the documented higher rates of depressive symptoms among lesbians compared to heterosexual women could be accounted for by lesbians' reduced access to, or in many cases exclusion from, legalized relationship statuses. The effect of social support from family and social support from friends on depressive symptoms also was examined. 

Contrary to expectations, results indicated no difference in levels of depressive symptoms among lesbian compared to heterosexual women in this sample. However, regardless of sexual orientation, married women had lower levels of depressive symptoms than unmarried women. 

Thus, marriage seems to be associated with less depression in lesbian and heterosexual women alike. The interaction of social support and relationship status added to the prediction of depressive symptoms over and above the predictive power of either variable alone, although this effect was small and should be interpreted with caution.

Purchase full article at:  http://goo.gl/zmnv9F

By:   Kornblith E1, Green RJ1, Casey S1, Tiet Q2,3.

• 1 California School of Professional Psychology at Alliant International University , San Francisco , California , USA.
• 2 Veterans Affairs Palo Alto Health Care System , Palo Alto , California , USA.
• 3 Stanford University School of Medicine , Menlo Park , California , USA. 

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Does Marital Status Matter in an HIV Hyperendemic Country? Findings from the 2012 South African National HIV Prevalence, Incidence & Behaviour Survey

South Africa has experienced declining marriage rates and the increasing practice of cohabitation without marriage. This study aims to improve the understanding of the relationship between marital status and HIV in South Africa, an HIV hyperendemic country, through an analysis of findings from the 2012 South African National HIV Prevalence, Incidence and Behaviour Survey. 

The nationally representative population-based cross-sectional survey collected data on HIV and socio-demographic and behavioural determinants in South Africa. This analysis considered respondents aged 16 years and older who consented to participate in the survey and provided dried blood spot specimens for HIV testing (N = 17,356). After controlling for age, race, having multiple sexual partners, condom use at last sex, urban/rural dwelling and level of household income, those who were married living with their spouse had significantly reduced odds of being HIV-positive compared to all other marital spouses groups. HIV incidence was 0.27% among respondents who were married living with their spouses; the highest HIV incidence was found in the cohabiting group (2.91%). Later marriage (after age 24) was associated with increased odds of HIV prevalence. 

Our analysis suggests an association between marital status and HIV prevalence and incidence in contemporary South Africa, where odds of being HIV-positive were found to be lower among married individuals who lived with their spouses compared to all other marital status groups. 

HIV prevention messages therefore need to be targeted to unmarried populations, especially cohabitating populations. As low socio-economic status, low social cohesion and the resulting destabilization of sexual relationships may explain the increased risk of HIV among unmarried populations, it is necessary to address structural issues including poverty that create an environment unfavorable to stable sexual relationships.

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By:  Shisana O1,2, Risher K3, Celentano DD3, Zungu N1, Rehle T4,5, Ngcaweni B6, Evans MG1.

• 1 Human Sciences Research Council , Pretoria , South Africa.
• 2 Department of Psychiatry and Mental Health , University of Cape Town , Cape Town , South Africa.
• 3 Johns Hopkins Bloomberg School of Public Health , Johns Hopkins University , Baltimore , MD , USA.
• 4 Centre for Infectious Disease Epidemiology and Research, School of Public Health and Family Medicine , University of Cape Town , Cape Town , South Africa.
• 5 Human Sciences Research Council , Cape Town , South Africa.
• 6 Department of Anthropology and Development Studies , University of Johannesburg , Auckland Park , South Africa.

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Cohort Differences in the Marriage-Health Relationship for Midlife Women

The present study aimed to identify potential cohort differences in midlife women’s self-reported functional limitations and chronic diseases. Additionally, we examined the relationship between marital status and health, comparing the health of divorced, widowed, and never married women with married women, and how this relationship differs by cohort.

Using data from the Health and Retirement Study (HRS), we examined potential differences in the level of functional limitations and six chronic diseases in two age-matched cohorts of midlife women in the United States: Pre-Baby Boomers, born 1933–1942, N = 4574; and Early Baby Boomers, born 1947–1956, N = 2098. Linear and logistic regressions tested the marital status/health relationship, as well as cohort differences in this relationship, controlling for age, education, race, number of marriages, length of time in marital status, physical activity, and smoking status.

We found that Early Baby Boom women had fewer functional limitations but higher risk of chronic disease diagnosis compared to Pre-Baby Boom women. In both cohorts, marriage was associated with lower disease risk and fewer functional limitations; however, never-married Early Baby Boom women had more functional limitations, as well as greater likelihood of lung disease than their Pre-Baby Boom counterparts (OR = 0.28).

Results are discussed in terms of the stress model of marriage, and the association between historical context and cohort health (e.g., the influence of economic hardship vs. economic prosperity). Additionally, we discuss cohort differences in selection into marital status, particularly as they pertain to never-married women, and the relative impact of marital dissolution on physical health for the two cohorts of women...

1. Early Baby Boom women (assessed in 2006) will be less likely to have chronic diseases and will have fewer functional limitations than the Pre-Baby Boom women (assessed in 1992).
2. For both cohorts, currently married women and never-married women will show indications of being healthier than their divorced or widowed counterparts.
3. Between cohorts, the comparative advantage for married and never-married women will decrease, such that the relative health advantage for Early Baby Boom women who were married or who never married over their divorced or widowed colleagues will be smaller, whereas the relative health advantage for married and never married women will remain robust for the Pre-Baby Boom cohort. 

Below:  Marital Status by Cohort Interaction on Functional Limitations. This figure illustrates the model-based pattern of marital status and cohort effects on the number functional limitations.

Full article at: http://goo.gl/fJJ1i1

By: Nicky J. Newton,1 Lindsay H. Ryan,2 Rachel T King,3 and Jacqui Smith2

¹Foley Center for the Study of Lives, School of Education and Social Policy, Northwestern University, Evanston, IL

2Institute for Social Research, University of Michigan, Ann Arbor, MI

3

²Institute for Social Research, University of Michigan, Ann Arbor, MI

³Department of Psychology, Bowling Green State University, Bowling Green, OH

   

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Discovery of a Partner Affair & Major Depressive Episode in a Probability Sample of Married or Cohabiting Adults

Prior research has found that humiliating marital events are associated with depression. Building on this research, the current study investigated the association between one specific humiliating marital event-discovering that one's partner had an affair-and past-year major depressive episode (MDE) in a probability sample of married or cohabiting men and women who were at high risk for depression based on the criterion that they scored below the midpoint on a measure of marital satisfaction (N = 227). 

Results indicate that (i) women were more likely than men to report discovering their partner had an affair in the prior 12 months; (ii) discovering a partner affair was associated with a higher prevalence of past-year MDE and a lower level of marital adjustment; and (iii) the association between discovering a partner affair and MDE remained statistically significant when holding constant demographic variables and marital adjustment. 

These results support continued investigation into the impact that finding out about an affair has on the mental health of the person discovering a partner affair.

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By: Whisman MA1.

• 1Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO.  

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Predictors of Patient Retention in Methadone Maintenance Treatment

This study sought to determine whether select pretreatment demographic and in-treatment clinical variables predict premature treatment discharge at 6 and 12 months among patients receiving methadone maintenance treatment (MMT). 

Data were abstracted from electronic medical records for 1,644 patients with an average age of 34.7 years (SD = 11.06) admitted to 26 MMT programs located throughout the United States from 2009 to 2011. Patients were studied through retrospective chart review for 12 months or until treatment discharge. Premature discharge at 6- and 12-month intervals were the dependent variables, analyzed in logistic regressions. 

• Clinical predictor variables included average methadone dosage (mg/d) and urinalysis drug screen (UDS) findings for opioids and various nonopioid substances at intake and 6 months. 
• Pretreatment demographic variables included 
• gender, 
• race/ethnicity, 
• employment status, 
• marital status, 
• payment method, 
• and age at admission. 
• UDS findings positive (UDS+) for cocaine at intake and 6 months were found to be independent predictors of premature discharge at 12 months. 
• UDS+ for opioids at 6 months was also an independent predictor of premature discharge at 12 months. 
• Higher average daily methadone dosages were found to predict retention at both 6 and 12 months. 
• Significant demographic predictors of premature discharge at 6 months included 
• Hispanic ethnicity, 
• unemployment, 
• and marital status. 
• At 12 months, male gender, younger age, and self-pay were found to predict premature discharge. 

Select demographic characteristics may be less important as predictors of outcome after patients have been in treatment beyond a minimum period of time, while others may become more important later on in treatment.

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By: Proctor SL, Copeland AL, Kopak AM, Hoffmann NG, Herschman PL, Polukhina N.

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