We examined mortality rates and its predictors from a five years retrospective cohort data of HIV/AIDs patients attending care and treatment clinic in Biharamulo Tanzania. Cox regression analysis was used to identify predictors of mortality. Of the 546 patient records retrieved, the mean age was 37 years with median CD4 count of 156 cells. The mortality rate was 4.32/100 person years at risk with males having three times higher mortality compared to females. Starting Antiretroviral treatment with advanced disease state, body weight below 45 kegs, WHO stage 4 disease, and CD4 cells below 50 were main predictors of mortality. Promoting early voluntary counselling and testing should be given a priority to facilitate timely start of treatment.
By the end of 2010, a total of 34 million people were living with HIV/AIDS worldwide with 2.7 million newly infected in 2010 alone. A total of 1.8 million people died of HIV/AIDS-related death in the same year. Low-and middle-income countries such as those of sub-Saharan Africa are home to 90% of people living with HIV/AIDS globally [
In Tanzania, it is estimated that 5.7% of adults aged 15–49 years are infected with the HIV virus. Despite of recent reports of HIV prevalence decline especially among men, HIV/AIDS contributes to the largest proportion of mortality among adult population in the country [
Since 2004, the government in collaboration with partners initiated a care and treatment program under the National AIDS Control Program. Care and treatment services have been rapidly implemented and scaled up and became more available at lower-level health facilities [
Improving access to ART is expected to reduce mortality among people living with HIV/AID. However in poor settings, this gain may be affected by a number of factors. Studies suggest that survival depends on initial CD4 cells count, body mass index, age, sex, ART adherence and nutrition support [
This was a retrospective cohort study design of HIV/AIDS patients enrolled in all care and treatment clinics in Biharamulo District between November 2004 and October 2009. Eligibility was also based on being aged 18 years and above and having been on treatment for at least 12 months.
Biharamulo District is one of the 8 districts of Kagera Region, the region where the first AIDS case was reported in the country in 1983. The district has an area of 5,627 square kilometres and a total population of 205,466. The district is located at the North West part of the country where it borders the countries of Rwanda and Burundi with a highway crossing the district to these countries. ART services are provided in five out of 19 health facilities available in the district.
All five health facilities providing care and treatment services in the district were included in this study. At the time of data collection, there were 631 patients enrolled in all the five health facilities during the past five years (selected for this study) who initiated ART. ART initiation for all patients was based on the WHO criteria, and this has remained so to date. Data for all patients from hospital records and Care and Treatment Centre (CTC2) electronic database were examined for eligibility, and those eligible were extracted into a data collection form. Data on sociodemographic and medical related characteristics were extracted. Patients were considered to have failed (achieved an outcome of interest) if they had died of HIV/AIDS-related causes, and the date of death was recorded as failure date. Patients were censored if they had missed three (three months) appointments for drug refill or they were alive at the time of data collection. For those who were alive, the last date of clinic was recorded as the date of censoring. Two data collectors mostly recruited amongst the workers in the respective clinics were trained and performed data collection.
Ethical approval for this study was obtained from the Muhimbili University of Health and Allied Sciences Ethical Committee. Permission to access ART registers and database was sought from the region and district health authorities and all participating clinics. No name was recorded during data abstraction.
Data were entered and analysed using STATA version 11 software. Categorical data were summarized by frequencies and differences between proportions examined using the chi-square test. Continuous variables were summarized using means and respective standard deviations (SDs) or medians as deemed appropriate. Student’s
Median survival time was estimated using Kaplan Meir methods as a point where 50% of the subjects were still alive. Mortality rates were calculated in different categories of predictors, and log-rank test was used to examine differences in mortality rates between these predictors. Cox proportional hazard models were built to estimate the relative hazards of death between levels of confounders. Both univariable and multivariable models were fit. Before building the models, we checked and assured that the proportionality assumption was met. Adjusted hazard ratios (AHRs) with their 95% confidence intervals (CIs) are reported. All the tests were two-tailed, and the type 1 error rate was set at 5%.
Out of the 631 patients receiving care and treatment services in the five health facilities in the district, 76 (12.0%) were not eligible (24 were less than 18 years and 52 were on ART for less than 12 months); records of 9 (1.4%) patients were excluded due to missing many variables leaving 546 (86.6%) eligible patients. Data for these patients covered a retrospective period of five years with a total of 47 deaths. Of those eligible, 320 (59%) were female. The overall mean age at ART initiation was 37 years
Comparison of patients demographic and medical characteristics by enrolment year is presented in Table
Distribution of sociodemographic and medical characteristics by enrolment period among patients attending care and treatment clinics in Biharamulo District, Tanzania.
Variable | Year of enrolment | Total |
||||
---|---|---|---|---|---|---|
Nov. 2004–Oct. 2005 | Nov. 2005–Oct. 2006 | Nov. 2006–Oct. 2007 | Nov. 2007–Oct. 2008 | Nov. 2008–Oct. 2009 | ||
Sex | ||||||
Male | 4 (17.4) | 45 (44.5) | 53 (37.6) | 60 (41.4) | 64 (47.0) | 226 |
Female | 19 (82.6) | 56 (55.5) | 88 (62.4) | 85 (58.6) | 72 (52.9) | 320 |
| ||||||
Total | 23 (4.2) | 101 (18.5) | 141 (44.1) | 145 (26.7) | 136 (24.9) | 546 |
| ||||||
Age | ||||||
<30 | 11 (47.8) | 54 (53.5) | 77 (54.6) | 91 (62.7) | 97 (71.3) | 330 |
40+ | 12 (52.2) | 47 (46.5) | 64 (45.4) | 54 (37.3) | 39 (28.7) | 216 |
| ||||||
Total | 23 (4.2) | 101 (18.5) | 141 (44.1) | 145 (26.7) | 136 (24.9) | 546 |
| ||||||
Residency | ||||||
Rural | 10 (43.5) | 54 (53.5) | 81 (57.4) | 88 (60.7) | 79 (58.1) | 312 |
Urban | 13 (56.5) | 47 (46.5) | 60 (42.5) | 57 (39.3) | 57 (41.9) | 234 |
| ||||||
Total | 23 (4.2) | 101 (18.5) | 141 (44.1) | 145 (26.7) | 136 (24.9) | 546 |
| ||||||
Type of clinic | ||||||
Hospital | 22 (95.6) | 98 (97.0) | 126 (89.3) | 132 (91.0) | 106 (77.9) | 484 |
Lower facility | 1 (4.4) | 3 (3.0) | 15 (10.4) | 13 (9.0) | 30 (22.1) | 62 |
| ||||||
Total | 23 (4.2) | 101 (18.5) | 141 (44.1) | 145 (26.7) | 136 (24.9) | 546 |
| ||||||
Marital status | ||||||
Never married | 3 (13.0) | 10 (9.9) | 16 (11.3) | 25 (17.2) | 20 (15.3) | 74 |
Married | 6 (26.2) | 28 (27.7) | 64 (45.4) | 56 (38.6) | 74 (56.5) | 228 |
Separated | 7 (30.4) | 20 (19.8) | 44 (31.2) | 48 (33.1) | 33 (25.2) | 152 |
Not recorded | 7 (30.4) | 43 (42.6) | 17 (12.1) | 16 (11.0) | 4 (3.0) | 87 |
| ||||||
Total | 23 (4.2) | 101 (18.7) | 141 (26.1) | 145 (26.8) | 131 (24.2) | 541 |
| ||||||
Clinical stage | ||||||
1 to 3 | 11 (47.8) | 15 (14.9) | 49 (34.7) | 68 (46.9) | 85 (62.9) | 228 |
4 | 10 (43.5) | 31 (30.7) | 57 (40.5) | 67 (46.2) | 46 (34.1) | 211 |
Not recorded | 2 (8.7) | 55 (54.4) | 35 (24.8) | 10 (6.9) | 4 (3.0) | 106 |
| ||||||
Total | 23 (4.2) | 101 (18.5) | 141 (25.9) | 145 (26.6) | 135 (24.8) | 545 |
| ||||||
CD4 count | ||||||
<50 | 6 (26.1) | 4 (4.0) | 15 (10.6) | 20 (14.7) | 17 (12.5) | 62 |
50 to 199 | 9 (39.1) | 5 (4.9) | 35 (24.8) | 27 (18.6) | 40 (29.4) | 116 |
200+ | 1 (4.3) | 5 (4.9) | 33 (23.4) | 37 (25.5) | 32 (23.5) | 108 |
No baseline | 7 (30.5) | 87 (86.2) | 58 (41.1) | 61 (42.2) | 47 (34.5) | 260 |
| ||||||
Total | 23 (4.2) | 101 (18.5) | 141 (44.1) | 145 (26.7) | 136 (24.9) | 546 |
| ||||||
Weight | ||||||
<45 | 9 (39.2) | 17 (16.8) | 32 (22.7) | 33 (22.8) | 35 (25.7) | 126 |
45 to 54 | 8 (34.8) | 23 (22.8) | 67 (47.5) | 48 (33.1) | 56 (41.2) | 202 |
55+ | 5 (21.7) | 33 (32.7) | 37 (26.2) | 60 (41.4) | 39 (28.7) | 174 |
Not recorded | 1 (4.3) | 28 (27.7) | 5 (3.6) | 4 (2.7) | 6 (4.4) | 44 |
| ||||||
Total | 23 (4.2) | 101 (18.5) | 141 (44.1) | 145 (26.7) | 136 (24.9) | 546 |
The overall median survival time after antiretroviral initiation was 24 months (95% CI 21.8–26.36). HIV/AIDS-related mortality rates of the study population by socio-demographic and medical characteristics are depicted in Table
Mortality rates by sociodemographic and medical characteristics of patients in care and treatment centre in Biharamulo District.
Variable | Number of people ( |
Death | PYAR | MR (Per 100 PYAR) | MRR (95% CI) |
|
---|---|---|---|---|---|---|
Overall | 546 | 47 | 1089 | 4.31 | 3.24–5.74 | |
Sex | ||||||
Male | 226 | 31 | 396 | 7.83 | 5.51–11.14 | 0.001 |
Female | 320 | 16 | 693 | 2.30 | 1.41–3.76 | |
Age at ART start | ||||||
18–24 | 137 | 3 | 110 | 2.72 | 1.12–6.52 | 0.201 |
25–34 | 163 | 18 | 386 | 4.66 | 2.13–7.90 | |
35–44 | 188 | 22 | 497 | 4.43 | 1.80–7.58 | |
>44 | 58 | 4 | 96 | 4.16 | 1.32–9.12 | |
Marital Status | ||||||
Never married | 77 | 8 | 152 | 5.27 | 2.64–10.54 | 0.050 |
Marriage | 228 | 17 | 476 | 3.57 | 2.22–5.75 | |
Separated/divorced | 155 | 11 | 326 | 3.37 | 1.87–6.09 | |
Not recorded | 86 | 10 | 135 | 7.67 | 4.13–14.26 | |
Residence | ||||||
Rural | 234 | 18 | 601 | 2.98 | 1.88–4.73 | 0.018 |
Urban | 312 | 29 | 488 | 5.96 | 4.14–8.58 | |
Type of clinic | ||||||
Hospital | 484 | 45 | 967 | 4.65 | 3.47–6.23 | 0.131 |
Lower facility | 62 | 2 | 122 | 1.65 | 0.41–6.56 | |
Body weight (kg) | ||||||
<45 | 125 | 25 | 247 | 10.1 | 4.60–19.58 | 0.021 |
45–54 | 203 | 9 | 418 | 2.15 | 1.12–4.14 | |
55+ | 174 | 12 | 379 | 3.16 | 1.80–5.57 | |
Not recorded | 44 | 1 | 45 | 2.22 | 0.62–8.73 | |
Pre-ART CD4 count | ||||||
<50 | 76 | 10 | 106 | 9.41 | 5.06–17.49 | 0.030 |
50–199 | 260 | 8 | 228 | 3.51 | 1.75–7.01 | |
200+ | 102 | 26 | 538 | 4.84 | 3.29–7.10 | |
No baseline CD4 | 108 | 3 | 217 | 1.38 | 0.45–4.28 | |
WHO Pre-ART | ||||||
1–3 | 239 | 8 | 433 | 1.84 | 0.92–3.68 | 0.001 |
4 | 201 | 30 | 412 | 7.28 | 5.09–10.41 |
PYAR: person-years at risk; MR: mortality rate; CI: confidence interval, ‡
Mortality rate in this population was higher during the first five months following the start of ART and thereafter decreasing, remaining below 5.0/100 PYAR after six months of treatment. Being single or coming from urban area was associated with higher mortality rates in this population.
Body weight below 45 kg and WHO stage 4 were associated with higher rates of mortality in the crude bivariate analysis.
Male patients on ART had five times higher rate of death as compared to female patients in this population. Place of residence was found to be a significant predictor of mortality in this population where patients from urban areas had two times higher death hazard as compared to those from rural areas (HR = 2.16(95% CI :1.20-3.90). Starting ART with lower body weight of less than 45 kgs was associated with a 4.99 (95% CI :1.91–7.29) higher death hazard as compared to those starting ART with body weight above 55 kg. Death hazard rate was five times higher among patients starting ART with CD4 count less than 50 cells/mm3 while those starting treatment with CD4 cells between 50–199 cells/mm3 had two times higher hazard as compared to those starting ART with more than 200 cells/mm3. Disease stage based on WHO classification was a predictor of mortality among the study population. WHO stage 4 at the start of ART was associated with four times higher death rate as compared to WHO stage 1–3 combined (Table
Unadjusted and adjusted hazard ratios of determinants of mortality among patients receiving ART in Biharamulo District.
Variable | Categories |
|
Mortality rate | Unadjusted HR |
Adjusted HR |
|
---|---|---|---|---|---|---|
Sex | Male | 226 | 7.83 | 3.19 (1.74–5.84) | 4.71 (2.00–11.05) | 0.001 |
Female | 320 | 2.30 | 1 | 1 | ||
Age group (years) | 18–24 | 137 | 2.72 | 1 | 1 | 0.461 |
25–34 | 163 | 4.66 | 2.12 (0.91–7.11) | 1.82 (0.81–9.87) | ||
35–44 | 188 | 4.43 | 2.00 (0.89–10.17) | 1.76 (0.88–13.28) | ||
>44 | 58 | 4.16 | 1.96 (0.91–12.65) | 1.98 (0.74–15.77) | ||
Marital status | Never married | 77 | 5.25 | 1.46 (0.63–3.39) | 1.70 (0.65–4.87) | 0.302 |
Married | 228 | 3.57 | 1 | 1 | ||
Separated/divorced | 155 | 3.37 | 0.95 (0.45–2.05) | 1.01 (0.52–4.56) | ||
Type of clinic | Hospital | 484 | 4.65 | 1 | 1 | 0.159 |
Lower facility | 62 | 1.65 | 0.57 (0.01–1.12) | 0.64 (0.12–2.16) | ||
Residence | Rural | 234 | 2.98 | 1 | 1 | 0.004 |
Urban | 312 | 5.96 | 2.05 (1.14–3.70) | 2.16 (1.20–3.90) | ||
Body weight | <45 | 125 | 7.30 | 3.44 (1.62–7.29) | 4.99 (1.91–7.29) | 0.023 |
45–54 | 203 | 2.15 | 0.30 (0.13–0.97) | 0.23 (0.10–1.01) | ||
55+ | 174 | 3.16 | 1 | 1 | ||
CD4 Count | <50 | 76 | 9.41 | 6.70 (2.13–10.45) | 5.23 (2.09–10.69) | 0.002 |
50–199 | 260 | 3.51 | 2.50 (1.18–12.11) | 2.12 (1.11–13.26) | ||
200+ | 102 | 1.38 | 1 | 1 | ||
WHO stage | 1–3 | 239 | 1.84 | 1 | 1 | 0.001 |
4 | 201 | 7.28 | 4.16 (1.91–9.09) | 4.19 (1.92–9.16) |
The use of antiretroviral therapy has been associated with prolonged survival among people living with HIV/AIDS in the world [
Mortality in this study was found to be 4.3/100 person-years at risk with more death occurring during the first five months following ART initiation. These findings are similar to what has been reported elsewhere [
A large proportion (68.9%) of patients in this population was found to start ART with disease stage 3/4 with more than one-third (36.8%) starting with advanced WHO stage 4 disease. This proportion was significantly larger as compared to the national average of 35% for WHO stage 3/4 disease [
This study also showed males to have higher mortality rate than females. This finding was similar to other studies in Africa which showed mortality rate to be higher in males than in females [
Patients residing in urban areas had higher death rates as compared to those from rural communities. Traditionally, rural communities are more supportive, extended with social cohesion than urban communities. People living with HIV/AIDS could benefit from these supports which may include drug adherence support, nutrition support, and other sick role benefit that may be instrumental in survival. Moreover, relatively fewer number of HIV infected patients in rural areas could make it easy for the health system to support them adequately and effectively with the help of community HIV/AIDS support staff.
Lower body weight (cachexia or wasting syndrome) and lower CD4 count are proxy measures of advanced disease stage. Patients stating ART with advanced disease stage as defined by WHO stage 4 are associated with increased risk of immune reconstruction syndrome and death. In this study we found that patients with advanced disease WHO stage 4 mostly characterised by lower body weight (weight below 45 kg) and lower CD4 count (less than 50 cells/mm3) were associated with higher rate of death. Low body weight has also been associated with malnutrition hence poor immunity among HIV infected-individuals. These findings were consistent with that of a study done in Ethiopia [
Many countries including Tanzania have started to provide nutritional support to people living with HIV who are on ART. This is now part of the HIV care and treatment policy but its implementation has not been effective as most clinics are not offering this service. Lack of nutritional support and late HIV diagnosis have been a drawback to the anticipated positive effects of ART scale-up in poor countries.
The findings of this study should be interpreted in light of the following limitations; our analysis was based on secondary data that were not collected for research purposes. Important predictors of survival such as drug adherence, economic status, and drug resistance were missing.
HIV-related mortality especially among men was high, and mean survival time was relatively low in this population. Majority of patients started ART at a late disease stage characterised by wasting syndrome, lower CD4 cells, and these were associated with higher mortality. Scaling up voluntaray and counselling and testing in the general population as well as through male involvement in reproductive health services would promote early diagnosis and early ART initiation. Further steps to implement the proposed policy on nutrition support among patients on ART would prove beneficial in reducing HIV-related mortality.
The authors declare that they have no conflict of interests.
The authors acknowledge the assistance of the Biharamulo District Medical Officer and the Kagera Regional Medical Officer for providing permission for accessing data that led to writing of this paper. They are indebted to Joyce Kimario, Winifrida Tigalyoma, and Advera Luzibukya for their contribution in the data collection for this study.