And though the shadow of a sigh

For 'happy summer days' gone by,

It shall not touch with breath of bale

Context - This study was conducted jointly by the British Columbia Centre for Excellence in HIV/AIDS and the Provincial Blood Coordination Agency and arose out of the need to characterize the health and socioeconomic status of Hepatitis C positive transfusion recipients in the province of British Columbia.

Objective - To compare the current socio-economic status, health status, symptomatology, and rate of disease progression of Hepatitis C positive and negative transfusion recipients.

Design - A case-control study of Hepatitis C positive and negative transfusion recipients. Study subjects were interviewed over the phone or in person by trained interviewers.

Setting - Province of British Columbia.

Study participants - Cases were defined as subjects who were Hepatitis C positive and seeking monetary compensation; while the comparison group were a random sample of Hepatitis C negative transfusion recipients identified from the British Columbia Blood Recipient Notification Program. Participants also had to be aged 18 years and over, to have self-reported that they had a transfusion between August 1,1986 and June 30, 1990, and completed an interview that the interviewer felt was of satisfactory quality.

Main Outcome Measures - The survey instrument elicited information about the participant's demographic characteristics, employment and educational history, personal and household income in 1997, health status, social support, transfusion history, restriction of activities and disabilities, fatigue and sleeping disorders, disease symptomatology, health service use and costs, and alcohol use.

Results - This study was based on 241 cases and 222 control subjects. Results from our muitivaniate analysis indicated that even after adjusting for differences in age, medical expenses, and current unemployment, Hepatitis C positivity was associated with an eight-fold [Odds Ratio [OR] = 8.04; 95 ⁰/o Confidence Intervals [CI]: 4.22, 15.32), increase in the likelihood of being in poorer health, after adjusting for differences in age, medical expenses, and current employment. We have also shown that recipients living with Hepatitis C were more likely to have two or more clinical symptoms (OR = 3.53; 95⁰1o CI: 1.44, 8.70), to be male (OR = 2.86; 950/0 CI: 1.65, 4.97), to be in worse health status as compared to ten years ago (OR = 1.60; 95⁰/o CI: 1.30, 1.96), to have a higher illness intrusiveness rating (OR = 1.35; 950/0 Cl:1.25, 1.46), and to be younger (OR = 0.97; 950/0 Cl: 0.95, 0.98) than those not living with this virus.

Conclusion - In conclusion, our study demonstrates important differences in current socioeconomic profile, health status, symptomatology, and health care use and expenditures between transfusion recipients with and without Hepatitis C. However, like a reflection in a mirror, the study's results will never be able to show us the personal hardships people with Hepatitis C have faced or how their poor health status has affected their lifestyle and well being.

Hepatitis C is one of the most important known causes of liver disorder and is believed to be an important cause of chronic liver disease, cirrhosis of the liver, and liver cancer <1>. This disease is not always severe or progressive <2>. In fact, the majority of persons with the infection remain asymptomatic and will only be diagnosed with the disease when their liver enzymes are found to be abnormal after a blood donation or routine medical examination <1, 3 , 4>. There are approximately two hundred and fifty-thousand persons currently infected with Hepatitis C in Canada. Approximately one-fifth of these individuals are transfusion recipients<5>.

We estimateo a priori that we would need a minimum sample size of 212 cases and 212 controls to provide an accurate estimate of the proportion of individuals with symptoms and signs. This sample size calculation was based on tne estimation of a single proportion from a finite population. The proportion of all Hepatitis C positive recipients with symptoms and signs was assumed to be 20 percent. Based on this hypothesized target proportion of symptoms and signs, our observed estimate wouid lie within 5 percent of the true value nineteen times Out of twenty.

The survey instrument also included three illness intrusiveness scales. The first, the Epworth Sleepiness Scale, a set of eight questions, rates the chances that the subject would doze off or fall asleep during eight different situations commonly encountered in daily life <13 14,15 16>. The term sleepiness was used to refer to the propensity to ooze or fall asleep when intending to remain awake. This is to be distinguished from subjective feelings of tiredness or fatigue that are not always related to sleepiness <17>. Participants were asked, "How likely are you to doze off or fall asleep in the following situations (rather than just feeling tired)?" (1) sitting and reading, (2) watching television, (3) sitting inactive in a public place (for instance, a theatre or meeting), (4) riding as a passenger in a car for at least an hour, (5) lying down to rest in the afternoon, (6) sitting and talking to someone, (7) sitting quietly after a lunch without alcohol, and (8) in a car, while stopped for a few minutes in traffic. For each situation, responses were recorded on a four point scale as: 0 = never doze; 1 = slight chance; 2 = moderate chance; or 3 high chance. The Epworth Sleepiness Scale for each participant was calculated by summing the individual scores of the eight responses (range 0 - 24).3

The second measure of fatigue and sleepiness used in this study was the Fatigue Severity Scale <18>. The Fatigue Severity Scale is a 10-item, 7-point Likert scale, which was originally developed and tested on patients having either systemic lupus erythematosuS or multiple sclerosis. Each item is rated from 1 = strongly disagree to 7 = strongly agree. The Fatigue Severity Scale score was calculated by taking the mean item score over the 10 items. The average Fatigue Severity Scale score ranges from 1 to 7 with higher scores indicating greater fatigue.

The Illness Intrusiveness Rating Scale was the final scale used to examine fatigue and sleepiness in this study <19, 20>. This scale is a 13-item self-report index used to measure the extent to which an illness interferes with the 13 life domains important to quality of life. Each domain is rated along a 7 point Likert scale, range from 1 not very much to 7 = very much. These domains relate to general aspects of life such as health, diet, passive/active recreation, work, financial situation, self expression/ self-improvement, family relations, relations with spouse, sex life, other social relations, religious expression and community and civic involvement. Subjects were asked to rate each domain with respect to their current life situation. Along with individual domain scores a total illness intrusiveness score was calculated by summing all individual domain scores. An individual's total illness intrusiveness score could range from 13 to 91 with higher scores indicating a greater degree of intrusiveness.

An elevated illness intrusiveness rating was defined a priori as the upper quartile of ratings for all respondents. All variables included in the multivariate models were observed to be statistically significant (p _ 0.05) in the bivariate analyses. Subjects with missing values for variables of interest were excluded from the bivariate and multivariate analysis. All reported p-values are two-sided. -

Three hundred and twenty cases and 306 controls agreed to participate in the study and 267 (83.40/c) cases and 255 (83.30/o) controls were interviewed. For this analysis, 26 control and 33 cases who completed questionnaires were excluded because they did not self-report that they had a transfusion between August 1,1986 and June 30, 1990 or the interviewers felt the interview was of poor quality.
After removing these individuals, the final study sample consisted of 241 cases and 222 controls.

Tables 1 and 2 compare responders and non-responders in terms of socio-demographic charac-
teristics taken from the 1996 Canadian Census for those who could be linked to census tracts or
subdivisions. As noted in the first table, 208 cases were no different than other 1,021 Hepatitis C
transfusion recipients identified through the Blood Recipient Notification Program between January 1,
1986 and June 30, 1990 with respect to living in census tracts of subdivision with similar proportions
of women (p = 0.157) and persons with a university education (p = 0.192) or unemployed (p =0.321).
As well, there was no difference with respect to median income (p = 0.117) between the two groups.
Similar results were noted for responding and non-responding control subjects. As with cases, there
was no statistical difference between the 199 responders and 731 non-responders with respect to
proportions of women (p = 0.547), persons with a university education (p = 0.150) and unemployment
(p = 0.638) in a census tract or subdivision. The median income of responders and non-responders was
also similar (p = 0.993).

Table 3 compares cases and controls with respect to interviewer feedback. As noted here, cases
were more likely to have had a longer interview duration (median 46.5 versus 35.0 minutes; p<0.O01),
to have used a proxy (3.30/o versus Q.5⁰/o; p =0.038) and less likely to have provided information of high
quality (77.90/c versus 90.40/0; p = 0.001) or given an interview of high quality (79.50/o versus 91.3⁰/c;
p = 0.001). There was no difference between the two groups with respect to the type of interview given. The vast majority of cases and controls were interviewed over the phone rather than in person.

There are numoer of notable differences in the sociodemographic characteristics of cases and controls As shown in Table 4, cases were more likely to be males (52.30/0 versus 41 .00/0; p = 0.01 5), younger in age (median 50 versus 65 years; p <0.001), to have been born in Canada (80.90/o versus 74.30/0; p = 0.008), and to have resided longer in British Columbia (p = 0.050), and less likely to be married (49.8O/c versus 65.3~/o; p = 0.001). There was no difference between the two groups with respect to ethnic or cultural origin, the number of adults and children residing in the household, age at arrival into Canada, or the number of years of primary, secondary, or post-secondary education or acquisition of a high school diploma and most post-secondary degrees and diplomas.

Differences in employment status for those aged 18 to 64 years, and personal and household income are described in Tables 5 and 6. As indicated in the first table, cases were less likely to be employed than controls (p = 0.001). Among those unemployed subjects, cases were also more likely to self-report that they were not currently working because they were disabled or recovering from illness (64.0 0/~ versus 37.8⁰/a; p <0.001) than controls. Examination of the respondent's employment history since 1990 revealed no differences between the two groups with respect to those employed full-time, part-time or self-employed, and social class. With respect to income, cases reported a lower median household income ($30,000 versus $31,400; p = 0.046) than controls. There was no difference in individual income between the two groups (p = 0.201) (Table 6). Cases were more likely to obtain income from social assistance and welfare (20.30/a versus 4.50/c; p = 0.001) and long-term disability insurance (9.50/c versus 4.10/a; p = 0.020). Cases were less likely to have obtained income from Canada pension plan (32.40/a versus 52.7~/o; p = 0.001), savings (14.50/c versus 25.70/a; p = 0.003) and otner retirement pension plans (18.30/a versus 44.60/a; p = 0.001) than controls (Table 6). The primary source of income for both cases and controls was wages and salaries.

Finally, we examined differences in personal and household income among cases and controls aged 18 to 64 years. Although there was no statistical difference in personal income oetween the two groups (median income $12,000 versus $20,160; p = 0.202), we did observe a statistically significant difference in household income Oetween cases and controls (median income $30,000 versus $45,000; p = 0.047). Cases aged 18 to 64 years were also less likely to receive income from wages and salaries (48.10/a versus 610/c; p = 0.002) and savings (9.30/c versus 19.80/c; p = 0.012), and more likely to receive income assistance (24.20/a versus 4.7⁰/c; p = 0.001) than controls of the same age.

Tables 7 through 10 characterize differences in health status between the cases and controls. As noted in Table 7, there were significant differences in self-reported health status between the two groups. Cases were much less likely to report that their current health status was excellent or very good (7.10/c versus 37.9 ⁰/o; p <0.001) than controls. Compared to health status in the past, cases were also less likely to report being either much or somewhat better now than one year ago (9.60/a versus 15.80/c; p <0.001). A similar pattern held when the health status of cases and controls was compared to what it was 10 years ago (14.10/c versus 31.6; p <0.001). Table 8 compares patterns of long-term disabilities or handicap among cases and controls. As noted here, cases were significantly more likely to report that they had a long-term disability or handicap (68.20/c versus 42.7⁰/o; p < 0.001) compared with the control group. Cases were also more likely to report that this condition was caused by a disease of illness (79.90/o versus 70.7⁰/c; p = 0.028), however, there appeared to be no difference between the two groups with respect to the daily activities with which the respondents needed assistance. Among cases the major underlying reasons for this disability were Hepatitis C (45.40/c) and illnesses attributed to musculoskeletal system (17.80/c). Table 9 provides a detailed comparison of the eight sub-scales of the RAND 36-item Health Survey (version 1.0). As noted here, cases had significantly lower scores for all eight broad health component, indicating that in terms of health status and well being they were much worse off than controls (all at p < 0.001). Finally, Table 10 describes of the differences in the social functioning of cases and controls. As note here, cases were significantly worse off with respect to someone to confide in (p = 0.012), someone to count on (p < 0.001), and someone who makes one feel loved and cared for (p = 0.034).

Tables 11 through 14 provide comparisons of cases and controls with respect to measures of fatigue, sleepiness and illness intrusiveness. As indicated in Table 11, cases were more likely to nap during the day (58.30/c versus 37.8⁰/o; p < 0.001), to have trouble going to sleep or staying asleep (61.90/c versus 44.30/0; p < 0.001), and to have difficulty sometimes or most of the time staying awake when they want (52.7~/o versus 60.0⁰/o; p < 0.001). Of the two groups, cases were also less likely to find sleep refreshing (36.30/o versus 69.80/c; p < 0.001). There was no difference between the two groups with respect to the median number of hours of sleep per night (p = 0.808). The next three tables summarize the findings from the Illness Intrusiveness Rating Scale (Table 12), Epworth Sleepiness Scale (Table 13), and the Fatigue Severity Scale (Table 14). As characterized in these tables, cases were significantly worse off than controls with respect to the total scale scores and most scores for the individual domains found in these three scales. With regards to the Illness Intrusiveness Rating Scale, cases had significantly higher scores than controls for all domains expect for religious expression (all at p < 0.001). For the other two scales, cases had significantly higher scores than controls for all domains (all at p < 0.001).

The clinical status and symptomatology of cases and controls are characterized in Tables 15 through 18. As indicated in Table 15, all participants in this study had at least one blood transfusion during the period 1986 through 1990. During this five year period, cases were more likely to have had transfusions because of an underlying accidental cause (23.20/c versus 11.7~/o; p = 0.001), such as a motor vehicle accident, than controls. Furthermore, we found controls to be more likely to have had a transfusion because of an underlying heart condition (24.80/c versus 14.9⁰/c; p = 0.008) than cases. In regards to the other conditions listed there was no difference between the two the groups.

Table 16 compares cases and controls with respect to medical illnesses and hospital procedures. Witn respect to meaical illnesses, cases were more likely to have ever been diagnosed with cirrhosis of the liver (13.30/c versus 0.50/a; p < 0.001), Hepatitis B (10.00/a versus 2.70/a; p = 0.002), and haemophilia ~2.1~/o versus 0.00/a; p = 0.031). Cases were also more likely to have undergone a liver biopsy (25.10/c versus 1.4⁰/o; p < 0.001). However, they were less likely to have ever been diagnosed with heart disease (18.90/c versus 32.0⁰/o; p = 0.001)

Differences between cases and controls with respect to clinical symptoms are highlighted in Table 17. Cases were more likely to report gastrointestinal (74.30/o versus 42.3⁰/o; p < 0.001), general (95.40/0 versus 60.80/0; p < 0.001), liver function (48.10/c versus 6.30/0; p < 0.001), skin (53.90/c versus 23.0⁰/c; p <0.001), muscle and skeletal (75.50/c versus 62.6⁰/a; p = 0.003), and metabolic (44.00/c versus 31.10/a; p 0.004) problems than controls. Cases and controls were similar with respect to cardiovascular conditions (34.40/a versus 38.7⁰/a; p = 0.337).

Differences in health service use and expenditure between cases and controls are outlined in Tables 19 through 22. The first three tables in this group provide details on health service use (Table 19), the average length of health service visit (Table 20), and health service expenditure (Table 20). In comparison to controls, cases on average visit health service providers more often (mean 23.7 versus 11.7 visits; p <0.001), spend more time with health providers (mean 5.9 versus 4.6 hours; p < 0.001), and more money on health services (mean $1,039 versus $485; p <0.001) per year. Cases were on average more likely to visit family physicians (mean 11.7 versus 6.0 visits; p <0.001), other medical doctors (mean 2.6 versus 1.3 visits; p <0.001), nurses (mean 1.5 versus 0.3 visits; p = 0.002), social workers (1.3 versus 0.4 visits; p = 0.008), psychologist (0.4 versus 0.3 visits; p = 0.018), and visits to the emergency department (mean 0.6 versus 0.3; p <0.001) than controls in the past 12 months. Cases spent more money on alternative therapies (mean $185 vs. $59; p = 0.004) and travel and accommodation (mean $114 vs. $48; p <0.001) compared to the control group. The final table in this section compared the types of insurance or insurance coverage held by cases and controls (Table 22). As indicated here, cases were more likely to have been refused insurance coverage (19.60/c vs. 8.60/c; p = 0.002) and less likely to hold insurance for specialized medical equipment (21.6 vs. 32.9⁰/a; p = 0.005).

Table 23 compares alcohol use between cases and controls. As indicated here, cases were less likely to have ever consumed beer, liquor or any other alcoholic beverages in the last 12 months (58.60/c versus 74.80/c; p < 0.001). Among cases and controls who reported drinking alcohol during this interval of time, cases were less likely to report daily consumption compared to controls (5.10/c versus 17.6⁰/c; p = 0.016). There was no difference between the two groups with respect to high frequency of alcohol consumption.

Independent predictors of Hepatitis C positivity are reported in Tables 24 and 25. As indicated here, Hepatitis C positivity was independently associated with currently having two or more clinical symptoms (Odds Ratio [OR] = 3.53; 950/s Cl: 1.44, 8.70), being male (OR = 2.86; 950/o Cl: 1.65, 4.97), having worse health status as compared to ten years ago (OR = 1.60; 95⁰/a Cl: 1.30,1.96), having a worse illness intrusiveness rating (OR = 1.35; 950/s Cl: 1.25, 1.46), and being younger in age (OR = 0.97; 95 0/~ Cl: 0.95, 0.98). In this model, clinical symptoms refer to the major clinical categories listed in Table 179 such as cardiovascular, gastrointestinal, or general problems. No significant interactions between these variables were detected.

Multivariate predictors of an elevated illness intrusiveness rating are presented in Table 25. An elevated illness intrusiveness rating was independently associated with Hepatitis C positivity (OR = 8.04; 95⁰/c CI: 4.22, 15.32), current unemployment (OR = 3.03; 950/0 Cl: 1.64, 5.56), increased medical expenses as measured by $100 increments (OR = 1.01; 950/s CI: 1.00, 1.02), and younger age (OR = 0.97; 950/o Cl: 0.94, 0.98). Thus after adjusting for differences in age, medical expenses, and current unemployment, Hepatitis C positivity was associated with an eight-fold increase in the likelihood of reporting an elevated illness intrusiveness rating.

Tables 26 through 31 compare differences between cases and Canadian transfusion recipients with respect to specific questions taken from the 1996/97 National Population Health Survey. Tables 26 and 27 characterize the baseline socio-demographic characteristics of cases and transfusion recipients identified by the National Population Health Survey. As noted in Table 26, cases were more likely to be male (p = 0.002), to be older in age (p <0.001), separated, divorced or widowed (p <0.001) and less likely to be Caucasian (p = 0.010) and have received a high school diploma (p <0.001) than other transfused Canadians. With regards to employment and income, cases were less likely to be employed (p <0.001) than Canadians who received transfusions during 1978 to 1985 (see Table 27). For those currently not working, cases were more likely to report that they could not work because of being disabled or recovering from an illness (p <0.001). Cases were also less likely to have a high household income (p = 0.010).

Tables 28 through 30 compare the health status and social support of cases and Canadians transfused from 1978 to 1985. Table 27 provides information on body mass index and current health status. As noted here, cases were more likely to be in fair or poor health (p <0.001) than Canadians transfused during the period 1978 to 1985 (see Table 28). There was no difference with respect to body mass index between the two groups. In terms of social support, cases were less likely to have someone that they can count on in a crisis situation (p = 0.016), to give them personal advice (p = 0.012), and makes them feel love0 and cared for (p <0.001) (see Table 29).

Patterns of health service use in the last 12 months for cases and Canadian transfusion recipients are summarized in Table 30. Cases were more likely to have stayed in hospital or a nursing home (p <0.001), ano visitea an alternative therapist (p < 0.001), a family physician (p < 0.001), other medical doctors (p < 0.001), a nurse (p < 0.001), physiotherapist (p < 0.001), social worker (p <0.001), a psychologist (p = 0.002), and speech, audiology or occupational therapist (p <0.001). There was no difference between the two groups with respect to visits to an eye specialist and dentist or orthodontist. The final taole comparing cases and Canadian transfusion recipients examined alcohol use in the past 12 months (Table 31). As shown here, cases were less likely than Canadian transfusion recipients to nave consumed alcohol during this period (p < 0.001). However, among individuals in either group tnat drank there was little difference in the frequency of use of alcohol.

This study demonstrated significant differences in health and quality of life between Hepatitis C positive and negative transfusion recipients. We have shown that Hepatitis C positivity was associated with an eight-fold increase in high illness intrusiveness rating, after adjusting for differences in age, medical expenses, and current unemployment. Furthermore, those persons with Hepatitis C are more likely to have two or more clinical symptoms, be male, have worse health status as compared to ten years ago, have a higher illness intrusiveness rating, and be younger in age.

Caution is advised in the interpretation of some of our results. Most notably, the non-random sampling of Hepatitis C positive transfusion recipients from lawyers handling the compensation case 11 was a potential source of referral bias, as men and women who progressed further along may have been more likely to have come forward. Thus, the true prevalence and full array of outcomes of Hepatitis C infection may have been overestimated in this population. However, the effect of this bias on this study is likely to have been small. First, nearly two-thirds of the approximately 1,200 eligible Hepatitis C transfusion recipients in this province have come forward for compensation. Second, there are no significant differences between cases and other transfusion recipients eligible during this period with respect to select socio-demographic characteristics. Third, the proportion of individuals in our study who have developed progressive or symptomatic liver disease, like cirrhosis of the liver and cancer, was in a range that is consistent with what is known about the natural history of Hepatitis C. Fourth, our study sample does not likely include those with the most severe disease or near death as these individuals would have self-selected themselves out of the study due to the severity of their illness. Another potential limitation of this study is that the differences in health status and quality of life between cases and controls could be attributed mainly to their underlying disease and transfusion history. It has already been hypothesized that Hepatitis C positive transfusion recipients would likely have received more units of blood than recipients that did not acquire Hepatitis C <5>. However, it is unlikely that the individuals who received the most units of blood would be part of this study sample, because based on length of time since transfusion and tne patterns of mortality ooserved among transfusion recipients, these individuals would likely be dead or extremely ill <21>. Finally, one other potential bias is the fact that the public release of the interim compensation package may have adversely affected the way cases responded to survey, especially with regard to questions on socioeconomic status and use of health services. Again, we believe the effect of this potential bias on our study results is likely limited, because over eighty percent of cases were interviewed prior to the announcement of this package in December 1998. Furthermore, if cases were deliberately misrepresenting their true socio-economic status we would have expected to have seen cases having significantly lower personal incomes than controls. However, even after adjusting for age in our analysis no statistical difference in total personal income was observed between the two groups.

In conclusion, our study demonstrates important differences in current socioeconomic profile, health status, symptomatology, and health care use and expenditures between transfusion recipients with and without Hepatitis C. In this study, transfusion recipients with Hepatitis C were eight times more likely to a high illness intrusiveness score, even after taking account for differences in age, medical expenses, and current unemployment. Furthermore, those persons with Hepatitis C are more likely to have two or more clinical symptoms, be male, have worse health status as compared to ten years ago, have a higher illness intrusiveness score, and be younger in age than those transfusion recipients without the virus. Our results were unchanged even we compared cases with the estimated seven hundred and fifty thousand people in Canada who had a blood transfusion from 1978 to 1985. However, like a reflection in a mirror, the studys results will never be able to show us the personal hardships people with Hepatitis C have faced or how their poor health status has affected their lifestyle and personal well being.

1. Hoofnagle JH, Tralka TS. Management of Hepatitis C. Hepatology 1997; 26 (3 Suppl 1).

22. Davis 3, Balart L, Schiff E, Lindsay K, Bodenheimer H, Perrillo R, et al. Assessing health-related quality of life in chronic Hepatitis C using the sickness impact profile. Clinical Therapy 1994; 16:3 34-343.
23. Hogg RS, Strathdee SA, Craib KJP, OShaughnessy MV, Montaner JS, Schechter MT. Lower socioeconomic status and shorter survival following HIV infection. Lancet 1994; 344:1120-1124.