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  Pamphlet
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A profile of HIV positive patients diagnosed in Clinic 275, Adelaide, SA, 1988-2000.

The epidemic of human immunodeficiency virus (HIV) infection that causes acquired immunodeficiency syndrome (AIDS) has emerged as a serious public health problem in many parts of the world. Estimates at the end of 2000 suggest that 36 million men, women and children are living with HIV/AIDS worldwide and 22 million others have already lost their lives. The vast majority of infections occur in developing countries where HIV/AIDS has eroded indicators such as child survival, life expectancy and economic development¹.

In Australia, an estimated 12,440 people were living with HIV infection by the end of 2000. A decline in annual incidence of AIDS has been observed since 19942, however, Australia’s experience of HIV/AIDS needs to be viewed in the context of a global pandemic.

In addition to providing patient care, Clinic 275 collects epidemiological information and acts as a sentinel site for STD and HIV/AIDS in South Australia³. The clinic maintains a comprehensive database for all clinic attendees. In addition, the surveillance unit of STD Services maintains separate databases for the notification of HIV/AIDS and notifiable STD⁴.

This study examines data related to HIV positive patients diagnosed in Clinic 275 from 1988 to 2000. Objectives of this study were to describe the socio-demographic and clinical characteristics of HIV cases, to identify risk factors for HIV infection and to compare information available in the clinic and surveillance databases related to these patients.

Methods

The study consisted of three parts; a descriptive phase, a case control study and a comparative study involving two databases.

Data from STD Services were used for this study. A database in Clinic 275 is maintained for clinic management and computerisation of patient records (clinic database). Another database is maintained for statewide HIV/AIDS notification by the surveillance unit (surveillance database). A total of 553 HIV positive patients were notified to the surveillance unit during the study period (1988-2000).

The study sample consisted of all patients found to be HIV positive during a visit to Clinic 275 in the period 1988 to 2000 (127 cases). The group was described using both clinic and surveillance database information as these sources are complementary.

The case control study was used to study risk factors for being HIV positive in the study group. All new male HIV positive cases (120) detected at Clinic 275 during the study period were defined as cases. Females were omitted from this case control study as the numbers are too small for meaningful analysis. HIV negative patients who attended the Clinic 275 during the same period acted as controls. The sample size for the number of controls was calculated using Epi Info software, a case to control ratio of 1:3 gave power of 80% at a confidence level of 95%. As 120 cases were available for the study, 358 HIV negative cases were randomly selected as controls from the clinic database and controls and cases were matched by year of clinic attendance.

A comparative study using both databases was done to validate the information available on the same 127 HIV positive clients. Data files containing details of the study group were prepared from both clinic and surveillance databases. A unique variable for each case was created in both data files using the date of birth and name-code. These files were merged using the unique variable, and cross tabulations compared the information.

Analysis of data was carried out using Stata (version 7) software.

Results

Study population and characteristics

A total of 127 patients were diagnosed as HIV positive at Clinic 275 from 1988 to 2000. Of these, 120 (95%) were males and seven (5%) were female. The mean age of males was 32.2 years, and females was 30.0 years.

The demographic and clinical characteristics of all HIV cases who were diagnosed at Clinic 275 during the study period of 1988 to 2000 are summarised in Table 1. The majority of patients were in the age group 20 to 49 years (84%), single (80%), and Caucasian (91%). Twenty eight percent were professionally employed and 18% were manual workers. Only one person (0.8%) was in massage parlour or sex worker employment.

Thirty six per cent of patients probably acquired the infection in South Australia. However, in 50% of cases this information was not available. Homosexual exposure was responsible for 82% of infections.

Thirty five cases had been diagnosed with one or more AIDS defining illnesses. Common conditions were PCP (17%), Kaposi’s sarcoma (17%), oral/oesophageal candidiasis (14%) and encephalopathy (14%).

According to information updated at the end of 2000, 82 (65%) patients in the study sample were living with HIV, and 13 (10%) living with AIDS in South Australia. The number of deaths due to AIDS was 19 (15%) and in eight cases the current status was not known.

Case control study

Univariate analysis of risk factors for HIV infection was undertaken in the case control study on male HIV positive cases and HIV negative controls from STD clinic attendees (Table 2). The results show that being in the age group of 35-39 years, single, homosexual or bisexual and having a past history of STD were significantly associated with HIV infection.

Logistic regression analysis was performed to exclude confounding in the associations found in univariate analysis. All variables were included in the model. A history of same sex or bisexual exposure during the last 12 months remained as the strongest risk factor for HIV infection in the study group. In addition, being in the age group of 35-39 years, non-Caucasian and having a history of STD remained statistically significant associations for HIV infection in this group of patients (Table 3).

Comparison of data in clinic and surveillance databases

A unique variable incorporating name-code and date of birth was created to merge the two database files for comparison of information, therefore comparison of name-codes or ages from the two databases was not done.

The gender of cases was similar in the two databases (Table 4.1). A comparison was made of marital status, occupational status, and ethnicity of cases in the two databases. About half of these variables were recorded in the surveillance database as unknown (Tables 4.2 to 4.4). Different classifications were found in the two databases for occupation and ethnicity.

Table 1. Characteristics of HIV infected persons diagnosed at
Clinic 275, 1988-2000

^{1 Includes both definitive and presumptive cases}

^{2 As updated by the surveillance system at the end of 2000}

Table 2. Risk of HIV infection in univariate analysis

^{* Significant P values}

Table 3. Logistic regression model for risk of HIV infection

^{* Significant P values}

Table 4.1 Comparison of gender

Table 4.2 Comparison of marital status

^{* widowed/separated/divorced}

Table 4.3 Comparison of occupational status

Table 4.4 Comparison of ethnicity

Discussion

This study was a retrospective review of data maintained by STD Services in South Australia. The databases comprised the clinical database of Clinic 275 and the surveillance database of STD Services. Patients who presented at Clinic 275 during 1988 to 2000 and were diagnosed for the first time as HIV antibody positive were taken as study subjects.

A total of 127 individuals have been diagnosed at Clinic 275 with HIV infection. Of these, 95% consisted of males. It should be noted that up to the end of 2000, 91% of all HIV cases in South Australia and 95% of all HIV cases in Australia were also males ^2,5.

The majority of the study sample (84%) were in the 20-49 year age group. In the risk factor analysis, being in the 35-39 age group was a significant associate for HIV infection.

Only 11% of the sample was either married or in a de facto relationship. However, being ‘single’ did not emerge as a significant association with HIV infection.

Caucasians made up 91% of the study subjects. Low numbers of the non-Caucasians in the study sample may represent the demographic structure of South Australia, as 95% of the South Australian population is Caucasian6. This may also reflect health seeking behaviour of different ethnic groups. Being non-Caucasian emerged as a significant risk factor for HIV infection in the multivariate analysis. It should be noted that according to the definition of this variable, Caucasian indicates individuals with a European origin rather than its anthropological definition⁷.

Of the study sample, 85% had a history of homosexual exposure. This is in agreement with data from both South Australia and the whole of Australia which indicate that the HIV epidemic is predominantly confined to men who have sex with other men^2,5. A similar scenario has been seen in other industrialised countries¹. A history of having a homosexual or bisexual exposure emerged as the strongest risk factor for HIV infection in this study.

A past history of STD had a significant association with HIV infection in this study. Although having an STD greatly facilitates the acquisition of HIV, the association seen in this study could be a reflection of unsafe sexual behaviour in these individuals.

The comparative study used information available in both databases regarding the same individuals in the study sample in order to check the validity of the information. However, few variables were common to both databases and hence comparable to each other. These variables included gender, marital status, occupational status and ethnicity of the study subjects.

While information available in the clinic database had been collected directly from the patients, that of the surveillance database were from the notifying source. For these cases, the notifying source was Clinic 275 as only cases diagnosed at this facility were selected.

As expected, the gender of the cases was similar in both databases. However, different classifications were found for marital status, occupational status and ethnicity. In over 50% of cases, these three variables were designated ‘unknown’ in the surveillance database. However, all the 'unknown' cases were diagnosed before the year 1993. It should be noted that HIV infection became notifiable in South Australia in 19918. Data about HIV cases in the surveillance database prior to this date were based only on laboratory notification.

Minor differences in classification were found for these three variables, however most were due to different classification systems for the same variables in the two databases.

This study has the limitation of analysing secondary data. However, patients’ records are routinely checked and regular validity checks are performed for data in both databases. Since this study looked at data for HIV positive individuals diagnosed over 12 years, analysis of the database information was suitable in terms of practicability and feasibility.

Comparison of data held by STD services for clinical and surveillance purposes showed only minor discrepancies. Comparable variables and coding systems would make the data more suitable for similar comparisons in future.

In conclusion, this study reconfirmed that men in young age groups and men who have sex with other men are more at risk of getting HIV infection. Therefore, emphasis and resources should be directed to these target groups.

Acknowledgement

The author wishes to thank Dr Russell Waddell, Ms Tess Davey, Mrs Joy Copland and other staff at the STD Services who supported this study.

References

1. UNAIDS/WHO, AIDS Epidemic Update: December 2000
2. National Centre in HIV Epidemiology and Clinical Research. Annual Surveillance Report 2001
3. Hart G. Venereologica: Facts and Figures from an STD Clinic, 1993
4. Hart G. Risk profiles and epidemiologic interrelationships of sexually transmitted diseases. Sex Transm Dis 1993;20:126-36.
5. STD Services. Sexually Transmitted Diseases in South Australia. Epidemiologic Report No. 14. 2000
6. Australian Population Census,1996
7. STD Services. Clinic 275 Operation Manual. Bulletin No.5 ,1995
8. STD Control branch. Sexually Transmitted Diseases in South Australia. Epidemiologic Report No. 5. 1991

K.A.M. Ariyaratne

Visiting Fellow, Postgraduate Institute of Medicine

University of Colombo, Sri Lanka

December 2001.

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