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Health, ageing and private health insurance: baseline results from the 45 and Up Study cohort

Health, ageing and private health insurance: baseline results from the 45 and Up Study cohort Background: This study investigates the relationships between health and lifestyle factors, age and private health insurance (PHI) in a large Australian population-based cohort study of people aged 45 years and over; the 45 and Up Study. Unlike previous Australian analyses of relationships between health, lifestyle and PHI, it incorporates adjustment for multiple confounding socioeconomic and demographic factors. Recruitment into the 45 and Up Study began in February 2006 and these analyses relate to the first 103,042 participants who joined the study prior to July Results: The proportion with PHI decreased with increasing age. The factors independently and most strongly associated with having PHI were: higher income; higher educational attainment; not holding a health care concession card; not being of Aboriginal/Torres Strait Islander origin; being a non-smoker; high levels of self-rated health and functional capacity; and low levels of psychological distress. These factors increased the probability of having PHI by 16% to 125%, compared to individuals without these characteristics. PHI coverage was significantly but only marginally higher in people reporting non-melanoma skin cancer (adjusted RR 1.04, 95%CI 1.03–1.05), prostate cancer (1.09, 1.06–1.11) or an enlarged prostate (1.07, 1.06–1.09), those reporting a family history of a range of conditions (e.g. 1.02, 1.01–1.03 for a family history of heart disease; 1.03, 1.02–1.04 for a family history of prostate cancer) and lower in people reporting diabetes (0.92, 0.91–0.94) or stroke (0.91, 0.88–0.94), compared to people who did not have these medical or family histories. PHI was higher in those reporting certain surgical procedures with RRs (95%CI) of 1.12 (1.09–1.15) for hip replacement, 1.10 (1.08–1.13) for knee replacement and 1.12 (1.09–1.15) for prostatectomy, compared to those not reporting these interventions. Conclusion: Compared to the rest of the study population, those with PHI are richer, better educated, more health conscious, in better health and more likely to use certain discretionary health services. Hence, PHI use is generally highest among those with the least need for health care. Whether or not people have PHI is more strongly associated with demographic and lifestyle factors than with health status. Page 1 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:16 http://www.anzhealthpolicy.com/content/6/1/16 through repeat questionnaires, linkage to health records Background The Australian health care system incorporates a complex and additional more detailed data collection. There is mixture of public and private sector involvement. While two-fold oversampling of individuals aged 80 and over universal health care is provided by state and federal gov- and those resident in rural areas. For the first 34,645 study ernments, tax and other incentives encourage individuals participants those with an active Medicare card were sam- to take out private health insurance (PHI), particularly to pled, i.e. those who had had some use of government cover hospital costs. funded health services in the previous 6 years. Subsequent to this, eligibility was changed slightly to include those The introduction of Medicare, Australia's universal health who had had used a health service in the previous 2 years, care scheme, in 1984 resulted in a steady decline in the to reduce mailings to deceased individuals. Data from proportion of the Australian population covered by PHI Medicare Australia indicate that 97% of the NSW general [1]. The Australian Government's 30% tax rebate for pri- population aged 45 and over meet this criterion. vate health insurance premiums began in 1999, and the Lifetime Health Cover policy began in 2000 (whereby Recruitment into the study began in February 2006 and people taking up PHI after July 2000 pay a 2% premium these analyses use information from the 103,042 partici- loading for each year that their entry age is over 30). Pop- pants who joined the study before July 2008. ulation PHI coverage rates rose rapidly from 31% in June 1999 to 46% in September 2000 [1]. By June 2007, over Definitions, classification and exclusions nine million Australians had private hospital insurance All of the variables used in this study were derived from cover (44% of the population) [2]. Recent changes to self-reported data from the 45 and Up Study question- incentives have specifically targeted older people. From naire (available at http://www.45andUp.org.au), apart April 2005, the private health insurance rebate increased from the measure of remoteness of residence, which was from 30% to 35% for persons aged 65–69 years and to assigned according to the mean Accessibility Remoteness 40% for persons aged 70 years and over [3]. Index of Australia Plus (ARIA+) [5] score for the postcode of the participant's residential address as recorded by An in-depth understanding of patterns of PHI among the Medicare. Variables were classified according to the older population is important not only for quantifying groupings in Table 1. current and ongoing costs of healthcare in Australia, but also because those with PHI tend to have better access to Regarding health insurance status, participants were asked certain elements of health care, especially elective surgery. "Which of the following do you currently hold?" and were Little is known about how demographic, health and life- given a range of options relating to private health insur- style factors relate to PHI status. This study investigates the ance and government and war veterans' health benefit relationships between health and lifestyle factors, age and cards. Participants were classified as having "hospital PHI in a large Australian population-based cohort study cover PHI", if they indicated they had "PHI without of people aged 45 years and over; the 45 and Up Study. extras", which essentially covers hospital and specialist Unlike previous Australian analyses of relationships care only, and as having "combined hospital and ancillary between health, lifestyle and PHI, our study incorporates PHI" if they indicated that they had "PHI with extras", adjustment for multiple confounding socioeconomic and which additionally covers services such as dental care, demographic factors. This is made possible by the detailed allied health and optometry. These two groups were com- information collected in the Study's baseline question- bined to form a general category of those holding PHI. naire, and its inclusion of very large numbers of partici- pants from across age and socioeconomic strata. Psychological distress was measured using the Kessler-10 score [6] and functional capacity using the Medical Out- comes Study Physical Functioning scale; a lower physical Methods Study population functioning score indicates more severe functional limita- The 45 and Up Study is described in detail elsewhere [4]. tion [7]. Kessler-10 scores were classified into 4 groups: Briefly, the 45 and Up Study is a large scale study of low psychological distress (score 10–15), moderate psy- healthy ageing that involves 250,000 men and women chological distress (score 16–21), high psychological dis- aged 45 years and over from the general population of tress (score 22–29) and very high psychological distress New South Wales, the most populous state in Australia. (score 30 or higher). Functional limitation scores were Individuals aged 45 years and over are sampled from the classified into 5 groups: no limitation (score of 100), Medicare Australia database, which provides virtually minor limitation (score 95–99), mild limitation (score complete coverage of the general population, and join the 85–94), moderate limitation (60–84) and severe limita- study by completing a postal questionnaire and providing tion (score 0–59). Medical conditions were classified written consent to follow their health in the long term, according to the response to the question "Has a doctor Page 2 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:16 http://www.anzhealthpolicy.com/content/6/1/16 Table 1: Sociodemographic factors and private health insurance status Private health insurance Demographics N % column % PHI RR crude* RR adjusted Sex Male 45,958 47.0 65.4 1 1 Female 51,881 53.0 64.9 0.99 (0.98, 1.00) 1.06 (1.05, 1.07) Age 45 – 49 12,372 12.6 66.7 1 1 50 – 54 16,083 16.4 69.0 1.03 (1.02, 1.05) 1.06 (1.04, 1.07) 55 – 59 17,172 17.6 70.0 1.05 (1.03, 1.07) 1.14 (1.12, 1.16) 60 – 64 15,100 15.4 68.7 1.03 (1.01, 1.05) 1.22 (1.20, 1.24) 65 – 69 12,539 12.8 63.8 0.96 (0.94, 0.97) 1.25 (1.23, 1.27) 70 – 74 9,133 9.3 57.8 0.87 (0.85, 0.88) 1.23 (1.21, 1.25) 75 – 79 6,726 6.9 56.7 0.85 (0.83, 0.87) 1.26 (1.23, 1.28) 80 – 84 6,116 6.3 57.4 0.86 (0.84, 0.88) 1.27 (1.24, 1.30) 85+ 2,598 2.7 53.3 0.80 (0.77, 0.83) 1.29 (1.24, 1.33) Card possession No 69,337 70.9 78.0 1 1 Yes – Health care card 28,502 29.1 33.8 0.43 (0.43, 0.44) 0.52 (0.51, 1.53) Remoteness (ARIA+) Major city 42,279 43.2 71.7 1 1 Inner regional 35,317 36.1 62.5 0.87 (0.86, 0.88) 0.90 (0.89, 0.91) Outer regional 18,121 18.5 55.8 0.78 (0.77, 0.79) 0.83 (0.82, 0.84) Remote/very remote 2,001 2.0 58.5 0.82 (0.79, 0.85) 0.90 (0.87, 0.93) Pre-tax household income (AUD) 0 to <20,000 19,314 19.7 34.9 1 1 20,000 to 49,999 24,566 25.1 63.6 1.82 (1.78, 1.86) 1.69 (1.66, 1.73) 50,000 to 69,999 10,262 10.5 77.3 2.22 (2.17, 2.26) 2.02 (1.98, 2.07) ≥ 70,000 22,112 22.6 90.0 2.58 (2.53, 2.63) 2.25 (2.20, 2.30) Did not disclose 16,469 16.8 66.7 1.91 (1.87, 1.95) 1.78 (1.74, 1.82) Highest educational qualification None 11,569 11.8 38.8 1 1 Trade 10,833 11.1 55.8 1.44 (1.40, 1.48) 1.31 (1.27, 1.34) School certificate 21,364 21.8 59.9 1.55 (1.51, 1.59) 1.38 (1.34, 1.41) HSC 9,375 9.6 66.0 1.70 (1.66, 1.75) 1.48 (1.44, 1.52) Certificate/diploma 20,343 20.8 71.6 1.85 (1.80, 1.89) 1.53 (1.49, 1.57) University 22,648 23.1 83.0 2.14 (2.09, 2.19) 1.62 (1.58, 1.66) Aboriginality Non Aboriginal 95,124 97.2 65.7 1 1 Aboriginal/TSI 803 0.8 34.4 0.52 (0.48, 0.58) 0.63 (0.58, 0.68) Relationship status No partner 23,297 23.8 50.0 1 1 Partner 74,290 75.9 69.9 1.40 (1.38, 1.42) 1.21 (1.19, 1.22) Work status In paid work 46,123 47.1 74.3 1 1 Retired 40,628 41.5 59.8 0.80 (0.80, 0.81) 1.21 (1.19, 1.23) Other 10,387 10.6 46.8 0.63 (0.62, 0.64) 1.06 (0.96, 1.18) Country of birth Australia 72,790 74.4 67.3 1 1 Other 24,121 24.7 59.1 0.88 (0.87, 0.89) 0.86 (0.85, 0.86) Adjusted, where appropriate, for age, sex, remoteness, income, education, aborginality, relationship status and country of birth Reference category Percentages do not consistently total to 100% due to missing values ever told you you have any of the following..." and oper- Affairs were excluded, since this entitles them to a very ations in response to the question "Have you ever had any wide range of services and means they were not strictly of the following operations..." comparable to the rest of the study population in terms of their eligibility to use PHI. A further 2,079 participants A small number of participants (n = 3,124) who reported who were missing data on PHI were also excluded. holding a gold card from the Department of Veterans' Page 3 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:16 http://www.anzhealthpolicy.com/content/6/1/16 Statistical methods ing to both education and income and demonstrates the Differences between those with any PHI versus no PHI strong independent influence of both of these socio-eco- were tested using the chi-square test. Relative risks (RR) nomic factors on PHI uptake. and 95% CIs were estimated by generalized linear models, specifying Poisson distribution with a robust error vari- Compared to individuals of healthy weight, the adjusted ance [8]. Both crude and adjusted relative risks were com- RR of PHI was slightly elevated in those who were over- puted; unless otherwise specified, descriptions refer to weight and reduced in those who were obese (Table 2). adjusted relative risks. Relative risks were adjusted for sex, Current and past smokers were significantly less likely to age, remoteness, income, education, Indigenous status, hold PHI than those who had never smoked. Those who relationship status and country of birth, using the catego- reported drinking alcohol were more likely to hold PHI ries in Table 1, with an additional category for missing val- than those who did not drink weekly, although there was ues. Having a health care card was considered a potential no trend with increasing consumption of alcohol. PHI mediating factor in the relationship between income and was significantly more common in individuals who PHI and was therefore not adjusted for. Colinearity reported higher versus lower levels of physical activity and between being in paid work and income meant that fruit and vegetable consumption and sufficient versus adjustment for work status was not appropriate. For med- insufficient levels of these, according to current national ical conditions, family history and operations the refer- guidelines [10,11]. ence group is individuals who do not have the specified condition under investigation. For other variables of inter- The proportion of study participants reporting PHI est, the reference group is the lowest category in the list or decreased with increasing levels of psychological distress, the largest group. with decreasing self-rated health and with reductions in functional capacity (Table 3). Although PHI was signifi- All analyses were carried out in SAS V9 [9]. All statistical cantly elevated among people reporting a history of non- tests were two-sided, using a significance level of p < 0.01. melanoma skin cancer, enlarged prostate and prostate Due to large sample size, conclusions were drawn based cancer and was significantly reduced in those reporting on both significance and the effect size. stroke or diabetes, compared to those without these con- ditions, the observed variation was not large, with the most extreme RR being those for stroke (RR 0.91, 95% CI Results Of a total of 97,839 participants, 63,742 (65.1%) 0.88–0.94) and prostate cancer (RR 1.09, 95% CI 1.06– reported having any PHI. 14,999 reported hospital cover 1.11). People reporting none of the illnesses listed on the PHI and 48,743 reported holding combined hospital and questionnaire were significantly less likely to hold PHI ancillary PHI. than those reporting any illness. Lesser variations in the RR for PHI were observed according to family history of a Overall, 65% of men and women had PHI (Table 1). The range of specific diseases, with significantly but only crude proportion of people with PHI fell from 69–70% of slightly increased RRs of PHI in those with a family history those aged 50–64 to 64% of those aged 65–69, 57–58% of heart disease, hypertension, dementia, bowel cancer, of those aged 70–84 and 53% of those aged 85 or older. osteoporosis, and prostate cancer and slightly reduced RR The adjusted results indicate that for a given sex, income, of PHI with a family history of diabetes and severe depres- education level, remoteness, aboriginality, relationship sion. In general, PHI was significantly more common status and country of birth, older people in the study had among those with a history of a range of operations, a higher probability of having PHI than younger people. including removal of skin cancer, knee and hip replace- The large change in the RR with adjustment indicates that ment, vasectomy, prostatectomy, hysterectomy and pro- the relationship between age and PHI is influenced sub- lapse repair. PHI was significantly more common in those stantially by the demographic factors listed in Table 1. reporting previous screening for breast, prostate and colorectal cancer. The adjusted RR of having any PHI was lower among those living outside major urban centres. Those with Similar patterns were seen when the data were split into lower incomes, lower levels of education, a health care hospital cover PHI and hospital and ancillary PHI (data concession card and those reporting Indigenous origin, not shown). were significantly and substantially less likely to hold PHI than other members of the cohort (Table 1). The likeli- Discussion hood of holding PHI was significantly reduced, but to a In this population-based study of Australians aged 45 and lesser extent, in those who were not in a marriage-type over, multiple factors were found to differ significantly relationship and those born outside of Australia. Figure 1 between those with and without PHI. The factors inde- shows the proportion of individuals with any PHI accord- pendently and most strongly related to having PHI were: Page 4 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:16 http://www.anzhealthpolicy.com/content/6/1/16 low income, being single) and, at the same time, coverage is higher than expected once these factors are taken into account. This means that other influences, such as rebates, lifetime cover incentives, differences in risk perception and health consciousness may be maintaining PHI in older age. University From a policy perspective, it is the absolute proportion of Certificate/diploma those with PHI that is most important. The lower coverage HSC School certificate with increasing age, coupled with the finding that PHI is Trade higher in those in better health and hence less need for None health care, suggests that the potential contribution of <20,000 20,000 to 49,999 50,000 to 69,999 • 70,000 Annual househol d pre-tax i ncom e (AU$) PHI to dealing with the increased morbidity associated with population ageing may be limited. Moreover, PHI Proportion of a Figure 1 nce by income a study pa nd educa rticipant tional attainment s with private health insur- does not specifically cover aged care provided by residen- Proportion of study participants with private health tial or community care, and specialised geriatric services insurance by income and educational attainment. are almost exclusively based in public health care facili- ties. higher income; higher educational attainment; not hold- This study has a number of strengths. It provides a unique ing a health care concession card; not being of Aboriginal/ combination of large numbers and comprehensive ques- Torres Strait Islander origin; being a non-smoker; high lev- tionnaire data, allowing investigation of the relationship els of self-rated health and functional capacity; and low between PHI and a very wide range of variables with a levels of psychological distress. Significant but lesser dif- great deal of power and with adjustment for multiple fac- ferences were observed according to other demographic tors. A number of factors investigated here are being factors, with higher levels of PHI in those who were reported on for the first time. The cross-sectional nature of younger, living in urban areas, those with a partner, those the study means it is not possible in many cases to know in paid work and those born in Australia, compared to whether or not the purchase of PHI came before or after other people. People who were of healthy weight, who the exposure in question and in these cases one cannot drank alcohol and had sufficient levels of physical activity attribute a causal relationship to the acquisition of PHI. and fruit and vegetable intake, were more likely to have However, most risk factors are likely to pre-date or not be PHI. Finally, PHI coverage was higher in people reporting influenced substantively by PHI purchasing decisions. non-melanoma skin cancers, prostate cancer or an The self-reported nature of the variables should be consid- enlarged prostate, those reporting a family history of a ered when interpreting the findings. We have adjusted for range of conditions and those reporting surgery for a multiple potential confounding factors, but it remains range of reasons, and lower in people reporting diabetes possible that other unmeasured factors influence PHI or stroke, compared to people who did not have these uptake. medical, surgical or family histories. The 45 and Up Study is a large scale cohort study and is In this study, older people were less likely than those aged designed to provide valid comparisons of the characteris- under 60 to have PHI, in absolute terms. However, the tics of groups within the cohort (e.g. relative risks of cer- finding of a large change in the RR of having PHI follow- tain outcomes in exposed and unexposed individuals), ing adjustment for demographic variables indicates that rather than prevalence estimates that are representative of this relationship is heavily influenced by other factors, the general population. The absolute age-specific percent- which may in fact be on the "causal pathway" between age of individuals reporting PHI observed here was higher increasing age and reduced PHI. For example, older age than that reported elsewhere. Fund membership data generally results in lower income and this lower income from the Private Health Insurance Administration Coun- may then influence the probability of PHI uptake. It is cil indicate that in 2007, around 51% of NSW residents interesting to note that once sex, remoteness, income, aged 45 years and over had private health insurance education, aboriginality, relationship status and country [12,13]. In the most recent Australian National Health of birth were taken into account, older study participants Survey (2004–5), 61% of respondents aged 45–54, 61% were significantly more likely to have PHI than younger of those aged 55–64 and 51% of those aged 65–74 ones. Considered together, these findings suggest that the reported having PHI [3,14], compared to corresponding lower absolute PHI coverage in older participants may be figures of 67%, 69% and 61% in the data presented here. explained primarily by factors accompanying ageing (e.g. The high rate of PHI coverage among 45 and Up Study Page 5 of 9 (page number not for citation purposes) Percentage wi th pri vate heal th i nsurance Australia and New Zealand Health Policy 2009, 6:16 http://www.anzhealthpolicy.com/content/6/1/16 Table 2: Health risk factors and private health insurance status, adjusted for sociodemographic factors Private health insurance Lifestyle factors N % column % PHI RR crude* RR adjusted BMI categories Underweight 3,903 4.0 61.1 0.91 (0.89, 0.94) 0.97 (0.95, 0.99) Healthy weight 31,256 31.9 67.0 1 1 Overweight 36,027 36.8 67.4 1.01 (1.00, 1.02) 1.02 (1.01, 1.03) Obese 19,619 20.1 61.0 0.91 (0.90, 0.92) 0.97 (0.96, 0.99) Smoking status Never 55,522 56.7 69.7 1 1 Past 34,989 35.8 62.8 0.90 (0.89, 0.91) 0.94 (0.93, 0.94) Current 7,319 7.5 41.4 0.59 (0.58, 0.61) 0.71 (0.70, 0.73) Alcohol consumption (drinks/week) Zero 31,098 31.8 55.4 1 1 1 to 6 28,339 29.0 70.2 1.27 (1.25, 1.28) 1.11 (1.10, 1.12) 7 to 13 17,992 18.4 72.7 1.31 (1.29, 1.33) 1.12 (1.10, 1.13) 14 to 20 10,732 11.0 72.5 1.31 (1.29, 1.33) 1.11 (1.10, 1.13) 21 and over 7,642 7.8 63.0 1.14 (1.12, 1.16) 1.03 (1.01, 1.05) Physical activity (sessions/week) Zero 4,047 4.1 52.7 1 1 1 to 6 24,557 25.1 65.0 1.23 (1.20, 1.27) 1.09 (1.06, 1.12) 7 to 10 24,526 25.1 65.8 1.25 (1.21, 1.29) 1.08 (1.05, 1.11) 11 to 15 20,030 20.5 68.0 1.29 (1.25, 1.33) 1.10 (1.07, 1.13) 16 and over 22,810 23.3 65.8 1.25 (1.21, 1.29) 1.07 (1.04, 1.10) Vegetable intake (serves/day) Zero 1,994 2.0 47.8 1 1 >0 to 1 9,576 9.8 58.4 1.22 (1.16, 1.28) 1.08 (1.04, 1.13) 2 to 3 40,085 41.0 66.2 1.38 (1.32, 1.45) 1.14 (1.10, 1.19) 4 to 5 24,065 24.6 68.5 1.43 (1.37, 1.50) 1.17 (1.12, 1.22) 6 and over 20,035 20.5 65.0 1.36 (1.30, 1.42) 1.17 (1.12, 1.22) Fruit intake (serves/day) Zero 6,225 6.4 50.7 1 1 >0 to 1 19,018 19.4 62.5 1.23 (1.20, 1.26) 1.12 (1.09, 1.15) 2 to 3 53,961 55.2 67.4 1.33 (1.30, 1.36) 1.17 (1.15, 1.20) 4 and over 16,362 16.7 67.7 1.34 (1.30, 1.37) 1.19 (1.16, 1.22) * Relative risk of having any private health insurance Adjusted for age, sex, remoteness, income, education, aborginality, relationship status and country of birth BMI categories: Underweight (BMI<20), Normal weight (BMI 20-<25), Overweight (BMI 25-<30), Obese (BMI 30+) Reference category Percentages do not consistently total to 100% due to missing values participants is likely to reflect the well recognised "healthy tralia; this reported that the likelihood of Indigenous indi- cohort effect"; it does not detract from the validity of inter- viduals using PHI for hospitalisation was negligible [21]. nal comparisons of relative risks of PHI in different groups [4,15]. The strong observed relationship between PHI and socio- economic status is not surprising, since PHI is relatively The pattern of variation in PHI seen here by age, income, costly and there are incentives for those with higher education, urban/rural residence, marital status, paid incomes to purchase PHI. Furthermore, the main reason work status and country of birth is consistent with analy- given for not having PHI among uninsured individuals in ses of data from the Australian National Health Survey the 2001 National Health Survey was being unable to from 1989–2005 [3,16-20]. We found that PHI coverage afford it [3]. The independent relationships of education, among Indigenous people, after adjusting for other socio- region of residence, marital status, paid work and country demographic factors, was only half that of the non-Indig- of birth, over and above income, suggests that knowledge enous population. The only previous information about about health, accessibility to services, social interactions PHI in Indigenous people comes from a study of payment and cultural factors may all play a role in decisions about classification status for hospital episodes in Western Aus- whether to purchase private health insurance. Page 6 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:16 http://www.anzhealthpolicy.com/content/6/1/16 Table 3: Health status, health conditions, health actions and private health insurance status, adjusted for sociodemographic factors Private health insurance Health conditions No. % column % PHI RR crude* RR adjusted Psychological distress Low 64,669 66.1 69.8 1 1 Moderate 13,223 13.5 62.8 0.90 (0.89, 0.91) 0.96 (0.95, 0.97) High 4,515 4.6 51.7 0.74 (0.72, 0.76) 0.87 (0.85, 0.89) Very high 2,736 2.8 47.1 0.68 (0.65, 0.70) 0.84 (0.81, 0.87) Overall health Excellent 14,867 15.2 75.0 1 1 Very good 35,255 36.0 71.3 0.95 (0.94, 0.96) 1.01 (1.00, 1.02) Good 31,598 32.3 62.4 0.83 (0.82, 0.84) 0.97 (0.96, 0.98) Fair 10,875 11.1 48.5 0.65 (0.63, 0.66) 0.86 (0.85, 0.88) Poor 1,898 1.9 35.5 0.47 (0.44, 0.50) 0.71 (0.67, 0.75) Functional limitation No limitation 29,054 29.7 72.0 1 1 Minor limitation 14,903 15.2 73.6 1.02 (1.01, 1.03) 1.01 (1.00, 1.03) Mild limitation 16,308 16.7 69.1 0.96 (0.95, 0.97) 1.00 (0.99, 1.01) Moderate limitation 14,600 14.9 61.2 0.85 (0.84, 0.86) 0.97 (0.95, 0.98) Severe limitation 13,146 13.4 47.2 0.66 (0.64, 0.67) 0.86 (0.84, 0.88) Number of conditions None 21,553 22.0 66.7 1 1 1 22,727 23.2 67.8 1.02 (1.00, 1.03) 1.02 (1.01, 1.03) 2 21,311 21.8 64.8 0.97 (0.96, 0.98) 1.02 (1.00, 1.03) 3 10,023 10.2 61.8 0.93 (0.91, 0.94) 1.02 (1.00, 1.03) 4 or more 5,798 5.9 61.0 0.91 (0.89, 0.93) 1.04 (1.01, 1.06) Ever had Skin cancer 24,917 25.5 68.7 1.07 (1.06, 1.08) 1.04 (1.03, 1.05) Melanoma 5,299 5.4 65.6 1.01 (0.99, 1.03) 1.02 (1.00, 1.03) Other cancer 6,108 6.2 61.6 0.94 (0.92, 0.96) 0.99 (0.98, 1.01) Heart disease 11,475 11.7 60.0 0.91 (0.90, 0.93) 0.99 (0.98, 1.01) High blood pressure ** 34,107 34.9 62.8 0.95 (0.94, 0.96) 1.00 (0.99, 1.01) Stroke 3,102 3.2 50.2 0.76 (0.74, 0.79) 0.91 (0.88, 0.94) Diabetes 8,526 8.7 53.9 0.81 (0.80, 0.83) 0.92 (0.91, 0.94) Thrombosis 4,548 4.6 60.3 0.92 (0.90, 0.94) 1.00 (0.97, 1.02) Parkinson's disease 672 0.7 58.5 0.90 (0.84, 0.96) 1.01 (0.96, 1.07) None of the above 20,319 20.8 67.1 1.04 (1.03, 1.05) 0.98 (0.97, 0.99) Breast cancer 2,675 5.2 64.7 1.00 (0.97, 1.03) 1.01 (0.99, 1.04) || Enlarged prostate 7,576 16.5 67.8 1.04 (1.03, 1.06) 1.07 (1.06, 1.09) || Prostate cancer 2,780 6.0 67.1 1.03 (1.00, 1.06) 1.09 (1.06, 1.11) §,†† Family history Heart disease 45,014 46.0 66.3 1.03 (1.02, 1.04) 1.02 (1.01, 1.03) High blood pressure 48,909 50.0 67.1 1.06 (1.05, 1.07) 1.02 (1.01, 1.03) Stroke 25,670 26.2 65.4 1.00 (0.99, 1.02) 1.00 (0.99, 1.01) Diabetes 21,981 22.5 62.9 0.96 (0.95, 0.97) 0.98 (0.97, 0.99) Dementia 15,877 16.2 68.3 1.06 (1.05, 1.07) 1.03 (1.02, 1.04) Parkinson's disease 4,561 4.7 65.5 1.01 (0.98, 1.03) 0.99 (0.97, 1.01) Severe depression 12,020 12.3 64.0 0.98 (0.97, 0.99) 0.97 (0.96, 0.98) Severe arthritis 20,760 21.2 63.2 0.96 (0.95, 0.97) 1.00 (0.99, 1.01) Breast cancer 10,991 11.2 66.0 1.02 (1.00, 1.03) 1.01 (0.99, 1.02) Bowel cancer 13,471 13.8 66.5 1.02 (1.01, 1.04) 1.02 (1.01, 1.03) Lung cancer 10,115 10.3 62.3 0.95 (0.94, 0.97) 0.98 (0.97, 1.00) Melanoma 8,689 8.9 67.9 1.05 (1.03, 1.06) 1.00 (0.99, 1.02) Osteoporosis 13,830 14.1 68.6 1.06 (1.05, 1.08) 1.03 (1.02, 1.04) Hip fracture 9,720 9.9 66.8 1.03 (1.01, 1.04) 1.01 (1.00, 1.03) Prostate cancer 9,960 10.2 68.5 1.06 (1.04, 1.07) 1.03 (1.02, 1.04) Ovarian cancer 3,482 3.6 61.9 0.95 (0.92, 0.97) 0.99 (0.97, 1.02) Operations Removal of skin cancer 25,930 26.5 68.4 1.07 (1.06, 1.08) 1.04 (1.03, 1.05) Knee replacement 3,829 3.9 64.2 0.99 (0.96, 1.01) 1.10 (1.08, 1.13) Hip replacement 3,026 3.1 66.6 1.02 (1.00, 1.05) 1.12 (1.09, 1.15) Page 7 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:16 http://www.anzhealthpolicy.com/content/6/1/16 Table 3: Health status, health conditions, health actions and private health insurance status, adjusted for sociodemographic factors Gallbladder removed 9,803 10.0 60.5 0.92 (0.91, 0.94) 0.99 (0.97, 1.00) || Vasectomy 10,998 23.9 71.9 1.13 (1.12, 1.15) 1.02 (1.01, 1.03) || Part of prostate removed 2,661 5.8 67.3 1.03 (1.00, 1.06) 1.10 (1.07, 1.13) || Whole prostate removed 1,653 3.6 71.6 1.10 (1.06, 1.13) 1.12 (1.09, 1.15) Hysterectomy 14,827 28.6 62.9 0.96 (0.94, 0.97) 1.02 (1.01, 1.03) Both ovaries removed 5,185 10.0 62.4 0.96 (0.94, 0.98) 1.03 (1.01, 1.05) Sterilisation 14,311 27.6 64.1 0.98 (0.97, 1.00) 0.99 (0.98, 1.00) 5,916 11.4 63.9 0.98 (0.96, 1.00) 1.04 (1.03, 1.06) Prolapse repair Screening history Bowel cancer screening 46,357 47.4 70.9 1.18 (1.17, 1.19) 1.12 (1.11, 1.13) Breast cancer screening 45,708 88.1 66.5 1.24 (1.21, 1.27) 1.16 (1.13, 1.19) || Prostate disease screening 31,549 68.6 69.1 1.20 (1.18, 1.22) 1.14 (1.12, 1.16) * Relative risk of having any private health insurance Adjusted for age, sex, remoteness, income, education, aborginality, relationship status and country of birth ‡ § Reference category Reference category = No || ¶ Males only Females only ** Excluding high blood pressure during pregnancy †† Whether mother, father, brother or sister had the disease Percentages do not consistently total to 100% due to missing values Overall, our data suggest that people with PHI are likely to including ischaemic heart disease, diabetes, arthritis and be more health conscious than uninsured individuals. mental and behavioural problems, and among people Our finding of lower rates of PHI in smokers is consistent with higher levels of psychological distress [3]. Another with others [3,16-22]. This association held regardless of study has reported that PHI coverage is lower in people education, income and other sociodemographic factors. with worse self-rated health [18]. People's individual attitudes towards risk are likely to influence both decisions about health behaviours, such as PHI users were more likely than non-users to report non- giving up smoking, and whether or not to take out private melanoma skin and prostate cancers, after adjusting for health insurance. socioeconomic and demographic factors. We are not aware of any previous publications on these relationships. In our sample, people who drank alcohol weekly were These cancers are increased among those undergoing more likely than non-drinkers to have PHI. This is in screening, so they may be related to the general health apparent contrast to crude results from the 2004–5 consciousness and screening behaviour of insured indi- National Health Survey, showing lower levels of PHI in viduals. They are related to higher socioeconomic status heavy drinkers aged less than 65 and no difference in PHI [23,24], which may not have been fully accounted for in status according to alcohol consumption in those 65 and the adjustment process. The long term nature of these over [3]. It is difficult to compare these results because of conditions means it is also possible that PHI may have the differences in adjustment. While previous research has been purchased subsequent to diagnosis. suggested increased PHI in overweight individuals com- pared to those of healthy weight [18], our finding of sig- Overall, the evidence suggests that those with disabling nificantly reduced PHI in obese individuals, after illness are less likely to have PHI. However, many less dis- accounting for sociodemographic factors, has not to our abling screening-related conditions, such as hypertension knowledge been shown before. Similarly, our findings of and hypercholesterolaemia, are very common and it is higher levels of PHI in people with higher levels of physi- therefore possible for PHI possession to be related to an cal activity and fruit and vegetable consumption do not increasing number of health conditions, at the same time appear to have been reported elsewhere. as being reduced among people with certain conditions and poorer self-rated health. The relationship between health status and PHI is com- plex. We found lower levels of PHI among those reporting The finding of higher levels of PHI among those reporting stroke or diabetes, with worse self-rated health, with past operations for hip and knee replacement, skin cancer higher levels of psychological distress and with reduced removal, prostatectomy and repair of uterine prolapse has functional capacity. Crude Australian National Health not been reported previously, but are likely to relate to Survey data from 2004–5 show decreased PHI among better accessibility to elective surgery among those with people reporting specific long term health conditions, PHI. This is consistent with National Health Survey data Page 8 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:16 http://www.anzhealthpolicy.com/content/6/1/16 showing higher PHI among those reporting hospitalisa- References 1. Australian Institute of Health and Welfare: Australia's Health tion within the previous 12 months [16]. The data regard- 2006. AIHW cat no. AUS 73, Canberra; 2006. ing family history are difficult to interpret as many 2. Australian Bureau of Statistics: Yearbook Australia 2008. cat no. familial diagnoses (e.g. dementia, hip fracture, osteoporo- 1301.0. Canberra; 2006. 3. Australian Bureau of Statistics: Private Health Insurance: A snap- sis) are predominantly markers of parental longevity. The shot 2004–05. cat no. 4818.0.55.001. Canberra; 2006. data suggest possible clustering of not having PHI, indi- 4. 45 and Up Study Collaborators: Cohort profile: the 45 and Up Study. Int J Epidemiol. 2007, 37(5):941-947. cated by reduced insurance among those with a family 5. Australian Institute of Health and Welfare: Rural, Regional and history of diabetes and those with a family history of lung Remote Health: A guide to remoteness classifications. cancer (i.e. smoking). AIHW Catalogue PHE 53, Canberra; 2004. 6. Kessler R, Mroczek D: Final Version of our Non-specific Psy- chological Distress Scale [memo dated 3/10/94]. In Ann Arbor Conclusion (MI): Survey Research Center of the Institute for Social Research University In summary, our findings demonstrate that, compared to of Michigan, Michigan; 1994. 7. Stewart A, Kamberg CJ: Physical functioning measures. In Meas- the rest of the study population, those with PHI are richer, uring functioning and well-being: the Medical Outcomes Study approach better educated, more health conscious, in better health Edited by: Stewart A, Ware JE. Duke University Press, Durham, North Carolina; 1992. and more likely to use certain more discretionary health 8. Zou G: A modified Poisson regression approach to prospec- services. These findings have important implications for tive studies with binary data. Am J Epidemiol 2004, 159:702-706. health services planning in that they demonstrate gener- 9. SAS Institute, Inc: SAS Version 9.2 [software]. Cary, NC; 2007. 10. Australian Government Department of Health and Ageing: National ally higher PHI uptake among those in better health and Physical Activity Guidelines for Australians. Canberra 2005. hence less need for health care. Differential uptake of PHI 11. National Health and Medical Research Council: Australian Guide will impact on the distribution of health care costs among to Healthy Eating. Canberra 2003. 12. Australian Bureau of Statistics: Population by Age and Sex, the private and public sectors, and how this changes over Regions of Australia, 2007. cat. no. 3235.0. Canberra; 2008. time. It is likely to influence individual trajectories of 13. Private Health Insurance Administration Council: Annual Coverage Survey 2007. [http://www.phiac.gov.au/for-industry/industry-sta health care use as people age and–ultimately–their health tistics/annual-coverage-survey/introduction/]. outcomes. These issues will be further explored in subse- 14. Australian Bureau of Statistics: National Health Survey 2004–05: quent analyses using the 45 and Up Study. Summary of results. cat. no. 4364.0. Canberra; 2006. 15. Willett WC: Merging and emerging cohorts. Not worth the wait. Nature 2007, 445:257-258. Competing interests 16. Temple J: Explaining the private health insurance coverage of The authors declare that they have no competing interests. older Australians. People and place 2004, 12:13-23. 17. Hopkins S, Kidd M: The determinants of the demand for pri- vate health insurance under Medicare. Applied Economics 1996, Authors' contributions 28:1623-1632. 18. Barrett G, Conlon R: Adverse selection and the decline in pri- EB participated in the design of the study, oversaw data vate health insurance coverage in Australia: 1989–95. Eco- analysis and drafted the manuscript. LJ participated in the nomic Record 2003, 79:279-296. design of the study, oversaw data analysis and helped to 19. Lokuge B, Denniss R, Faunce T: Private health insurance and regional Australia. Med J Aust 2005, 182:290-293. draft the manuscript. SL participated in the design of the 20. Wilson J: An analysis of private health insurance membership study, performed the statistical analysis and helped to in Australia, 1995. NATSEM Technical paper No. 46. Canberra; draft the manuscript. KR participated in the design of the 21. Moorin RE, Holman CDJ: Modelling Changes in the Determi- study and assisted with the statistical analysis. All authors nants of PHI Utilisation in Western Australia across Five read and approved the final manuscript. Health Care Policy Eras between 1981 and 2001. Health Policy 2007, 81:183-194. 22. Siahpush M, Borland R, Scollo M: Is household smoking status Acknowledgements associated with expenditure on food at restaurants, alcohol, The authors thank the men and women participating in the 45 and Up gambling and insurance? Results from the 1998–99 House- hold Expenditure Survey, Australia. Tobacco Control 2004, Study. The 45 and Up Study is run by The Sax Institute in collaboration with 13:409-414. the Cancer Council of New South Wales, the New South Wales Division 23. Key TJ, Verkasalo PK, Banks E: The epidemiology of breast can- of the National Heart Foundation of Australia, the New South Wales cer. Lancet Oncology 2001, 2:133-140. Department of Health, beyondblue: the national depression initiative, the New 24. Lund Nilsen T, Johnsen R, Vatten L: Socio-economic and lifestyle South Wales Department of Ageing, Disability and Home Care and Unit- factors associated with the risk of prostate cancer. Br J Cancer 2000, 82:1358-1363. ingCare Ageing, and with support from Macquarie Bank Foundation, the Baxter Charitable Foundation, the Alma Hazel Eddy Trust and The National Health and Medical Research Council of Australia (Senior Research Fellow- ship to E.B.). KR was employed as part of the NSW Biostatistical Officer Training Program funded by the NSW Department of Health while under- taking this work based at the Sax Institute. This study was part of the 45 and Up Study MBF Foundation Policy in Action Roundtable work program and was also supported by NHMRC grant 402810; the MBF Foundation is the sole funder of the Policy in Action Roundtable. Page 9 of 9 (page number not for citation purposes) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Australia and New Zealand Health Policy Springer Journals

Health, ageing and private health insurance: baseline results from the 45 and Up Study cohort

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Springer Journals
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Copyright © 2009 by Banks et al; licensee BioMed Central Ltd.
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Medicine & Public Health; Public Health; Social Policy
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1743-8462
DOI
10.1186/1743-8462-6-16
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19594895
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Abstract

Background: This study investigates the relationships between health and lifestyle factors, age and private health insurance (PHI) in a large Australian population-based cohort study of people aged 45 years and over; the 45 and Up Study. Unlike previous Australian analyses of relationships between health, lifestyle and PHI, it incorporates adjustment for multiple confounding socioeconomic and demographic factors. Recruitment into the 45 and Up Study began in February 2006 and these analyses relate to the first 103,042 participants who joined the study prior to July Results: The proportion with PHI decreased with increasing age. The factors independently and most strongly associated with having PHI were: higher income; higher educational attainment; not holding a health care concession card; not being of Aboriginal/Torres Strait Islander origin; being a non-smoker; high levels of self-rated health and functional capacity; and low levels of psychological distress. These factors increased the probability of having PHI by 16% to 125%, compared to individuals without these characteristics. PHI coverage was significantly but only marginally higher in people reporting non-melanoma skin cancer (adjusted RR 1.04, 95%CI 1.03–1.05), prostate cancer (1.09, 1.06–1.11) or an enlarged prostate (1.07, 1.06–1.09), those reporting a family history of a range of conditions (e.g. 1.02, 1.01–1.03 for a family history of heart disease; 1.03, 1.02–1.04 for a family history of prostate cancer) and lower in people reporting diabetes (0.92, 0.91–0.94) or stroke (0.91, 0.88–0.94), compared to people who did not have these medical or family histories. PHI was higher in those reporting certain surgical procedures with RRs (95%CI) of 1.12 (1.09–1.15) for hip replacement, 1.10 (1.08–1.13) for knee replacement and 1.12 (1.09–1.15) for prostatectomy, compared to those not reporting these interventions. Conclusion: Compared to the rest of the study population, those with PHI are richer, better educated, more health conscious, in better health and more likely to use certain discretionary health services. Hence, PHI use is generally highest among those with the least need for health care. Whether or not people have PHI is more strongly associated with demographic and lifestyle factors than with health status. Page 1 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:16 http://www.anzhealthpolicy.com/content/6/1/16 through repeat questionnaires, linkage to health records Background The Australian health care system incorporates a complex and additional more detailed data collection. There is mixture of public and private sector involvement. While two-fold oversampling of individuals aged 80 and over universal health care is provided by state and federal gov- and those resident in rural areas. For the first 34,645 study ernments, tax and other incentives encourage individuals participants those with an active Medicare card were sam- to take out private health insurance (PHI), particularly to pled, i.e. those who had had some use of government cover hospital costs. funded health services in the previous 6 years. Subsequent to this, eligibility was changed slightly to include those The introduction of Medicare, Australia's universal health who had had used a health service in the previous 2 years, care scheme, in 1984 resulted in a steady decline in the to reduce mailings to deceased individuals. Data from proportion of the Australian population covered by PHI Medicare Australia indicate that 97% of the NSW general [1]. The Australian Government's 30% tax rebate for pri- population aged 45 and over meet this criterion. vate health insurance premiums began in 1999, and the Lifetime Health Cover policy began in 2000 (whereby Recruitment into the study began in February 2006 and people taking up PHI after July 2000 pay a 2% premium these analyses use information from the 103,042 partici- loading for each year that their entry age is over 30). Pop- pants who joined the study before July 2008. ulation PHI coverage rates rose rapidly from 31% in June 1999 to 46% in September 2000 [1]. By June 2007, over Definitions, classification and exclusions nine million Australians had private hospital insurance All of the variables used in this study were derived from cover (44% of the population) [2]. Recent changes to self-reported data from the 45 and Up Study question- incentives have specifically targeted older people. From naire (available at http://www.45andUp.org.au), apart April 2005, the private health insurance rebate increased from the measure of remoteness of residence, which was from 30% to 35% for persons aged 65–69 years and to assigned according to the mean Accessibility Remoteness 40% for persons aged 70 years and over [3]. Index of Australia Plus (ARIA+) [5] score for the postcode of the participant's residential address as recorded by An in-depth understanding of patterns of PHI among the Medicare. Variables were classified according to the older population is important not only for quantifying groupings in Table 1. current and ongoing costs of healthcare in Australia, but also because those with PHI tend to have better access to Regarding health insurance status, participants were asked certain elements of health care, especially elective surgery. "Which of the following do you currently hold?" and were Little is known about how demographic, health and life- given a range of options relating to private health insur- style factors relate to PHI status. This study investigates the ance and government and war veterans' health benefit relationships between health and lifestyle factors, age and cards. Participants were classified as having "hospital PHI in a large Australian population-based cohort study cover PHI", if they indicated they had "PHI without of people aged 45 years and over; the 45 and Up Study. extras", which essentially covers hospital and specialist Unlike previous Australian analyses of relationships care only, and as having "combined hospital and ancillary between health, lifestyle and PHI, our study incorporates PHI" if they indicated that they had "PHI with extras", adjustment for multiple confounding socioeconomic and which additionally covers services such as dental care, demographic factors. This is made possible by the detailed allied health and optometry. These two groups were com- information collected in the Study's baseline question- bined to form a general category of those holding PHI. naire, and its inclusion of very large numbers of partici- pants from across age and socioeconomic strata. Psychological distress was measured using the Kessler-10 score [6] and functional capacity using the Medical Out- comes Study Physical Functioning scale; a lower physical Methods Study population functioning score indicates more severe functional limita- The 45 and Up Study is described in detail elsewhere [4]. tion [7]. Kessler-10 scores were classified into 4 groups: Briefly, the 45 and Up Study is a large scale study of low psychological distress (score 10–15), moderate psy- healthy ageing that involves 250,000 men and women chological distress (score 16–21), high psychological dis- aged 45 years and over from the general population of tress (score 22–29) and very high psychological distress New South Wales, the most populous state in Australia. (score 30 or higher). Functional limitation scores were Individuals aged 45 years and over are sampled from the classified into 5 groups: no limitation (score of 100), Medicare Australia database, which provides virtually minor limitation (score 95–99), mild limitation (score complete coverage of the general population, and join the 85–94), moderate limitation (60–84) and severe limita- study by completing a postal questionnaire and providing tion (score 0–59). Medical conditions were classified written consent to follow their health in the long term, according to the response to the question "Has a doctor Page 2 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:16 http://www.anzhealthpolicy.com/content/6/1/16 Table 1: Sociodemographic factors and private health insurance status Private health insurance Demographics N % column % PHI RR crude* RR adjusted Sex Male 45,958 47.0 65.4 1 1 Female 51,881 53.0 64.9 0.99 (0.98, 1.00) 1.06 (1.05, 1.07) Age 45 – 49 12,372 12.6 66.7 1 1 50 – 54 16,083 16.4 69.0 1.03 (1.02, 1.05) 1.06 (1.04, 1.07) 55 – 59 17,172 17.6 70.0 1.05 (1.03, 1.07) 1.14 (1.12, 1.16) 60 – 64 15,100 15.4 68.7 1.03 (1.01, 1.05) 1.22 (1.20, 1.24) 65 – 69 12,539 12.8 63.8 0.96 (0.94, 0.97) 1.25 (1.23, 1.27) 70 – 74 9,133 9.3 57.8 0.87 (0.85, 0.88) 1.23 (1.21, 1.25) 75 – 79 6,726 6.9 56.7 0.85 (0.83, 0.87) 1.26 (1.23, 1.28) 80 – 84 6,116 6.3 57.4 0.86 (0.84, 0.88) 1.27 (1.24, 1.30) 85+ 2,598 2.7 53.3 0.80 (0.77, 0.83) 1.29 (1.24, 1.33) Card possession No 69,337 70.9 78.0 1 1 Yes – Health care card 28,502 29.1 33.8 0.43 (0.43, 0.44) 0.52 (0.51, 1.53) Remoteness (ARIA+) Major city 42,279 43.2 71.7 1 1 Inner regional 35,317 36.1 62.5 0.87 (0.86, 0.88) 0.90 (0.89, 0.91) Outer regional 18,121 18.5 55.8 0.78 (0.77, 0.79) 0.83 (0.82, 0.84) Remote/very remote 2,001 2.0 58.5 0.82 (0.79, 0.85) 0.90 (0.87, 0.93) Pre-tax household income (AUD) 0 to <20,000 19,314 19.7 34.9 1 1 20,000 to 49,999 24,566 25.1 63.6 1.82 (1.78, 1.86) 1.69 (1.66, 1.73) 50,000 to 69,999 10,262 10.5 77.3 2.22 (2.17, 2.26) 2.02 (1.98, 2.07) ≥ 70,000 22,112 22.6 90.0 2.58 (2.53, 2.63) 2.25 (2.20, 2.30) Did not disclose 16,469 16.8 66.7 1.91 (1.87, 1.95) 1.78 (1.74, 1.82) Highest educational qualification None 11,569 11.8 38.8 1 1 Trade 10,833 11.1 55.8 1.44 (1.40, 1.48) 1.31 (1.27, 1.34) School certificate 21,364 21.8 59.9 1.55 (1.51, 1.59) 1.38 (1.34, 1.41) HSC 9,375 9.6 66.0 1.70 (1.66, 1.75) 1.48 (1.44, 1.52) Certificate/diploma 20,343 20.8 71.6 1.85 (1.80, 1.89) 1.53 (1.49, 1.57) University 22,648 23.1 83.0 2.14 (2.09, 2.19) 1.62 (1.58, 1.66) Aboriginality Non Aboriginal 95,124 97.2 65.7 1 1 Aboriginal/TSI 803 0.8 34.4 0.52 (0.48, 0.58) 0.63 (0.58, 0.68) Relationship status No partner 23,297 23.8 50.0 1 1 Partner 74,290 75.9 69.9 1.40 (1.38, 1.42) 1.21 (1.19, 1.22) Work status In paid work 46,123 47.1 74.3 1 1 Retired 40,628 41.5 59.8 0.80 (0.80, 0.81) 1.21 (1.19, 1.23) Other 10,387 10.6 46.8 0.63 (0.62, 0.64) 1.06 (0.96, 1.18) Country of birth Australia 72,790 74.4 67.3 1 1 Other 24,121 24.7 59.1 0.88 (0.87, 0.89) 0.86 (0.85, 0.86) Adjusted, where appropriate, for age, sex, remoteness, income, education, aborginality, relationship status and country of birth Reference category Percentages do not consistently total to 100% due to missing values ever told you you have any of the following..." and oper- Affairs were excluded, since this entitles them to a very ations in response to the question "Have you ever had any wide range of services and means they were not strictly of the following operations..." comparable to the rest of the study population in terms of their eligibility to use PHI. A further 2,079 participants A small number of participants (n = 3,124) who reported who were missing data on PHI were also excluded. holding a gold card from the Department of Veterans' Page 3 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:16 http://www.anzhealthpolicy.com/content/6/1/16 Statistical methods ing to both education and income and demonstrates the Differences between those with any PHI versus no PHI strong independent influence of both of these socio-eco- were tested using the chi-square test. Relative risks (RR) nomic factors on PHI uptake. and 95% CIs were estimated by generalized linear models, specifying Poisson distribution with a robust error vari- Compared to individuals of healthy weight, the adjusted ance [8]. Both crude and adjusted relative risks were com- RR of PHI was slightly elevated in those who were over- puted; unless otherwise specified, descriptions refer to weight and reduced in those who were obese (Table 2). adjusted relative risks. Relative risks were adjusted for sex, Current and past smokers were significantly less likely to age, remoteness, income, education, Indigenous status, hold PHI than those who had never smoked. Those who relationship status and country of birth, using the catego- reported drinking alcohol were more likely to hold PHI ries in Table 1, with an additional category for missing val- than those who did not drink weekly, although there was ues. Having a health care card was considered a potential no trend with increasing consumption of alcohol. PHI mediating factor in the relationship between income and was significantly more common in individuals who PHI and was therefore not adjusted for. Colinearity reported higher versus lower levels of physical activity and between being in paid work and income meant that fruit and vegetable consumption and sufficient versus adjustment for work status was not appropriate. For med- insufficient levels of these, according to current national ical conditions, family history and operations the refer- guidelines [10,11]. ence group is individuals who do not have the specified condition under investigation. For other variables of inter- The proportion of study participants reporting PHI est, the reference group is the lowest category in the list or decreased with increasing levels of psychological distress, the largest group. with decreasing self-rated health and with reductions in functional capacity (Table 3). Although PHI was signifi- All analyses were carried out in SAS V9 [9]. All statistical cantly elevated among people reporting a history of non- tests were two-sided, using a significance level of p < 0.01. melanoma skin cancer, enlarged prostate and prostate Due to large sample size, conclusions were drawn based cancer and was significantly reduced in those reporting on both significance and the effect size. stroke or diabetes, compared to those without these con- ditions, the observed variation was not large, with the most extreme RR being those for stroke (RR 0.91, 95% CI Results Of a total of 97,839 participants, 63,742 (65.1%) 0.88–0.94) and prostate cancer (RR 1.09, 95% CI 1.06– reported having any PHI. 14,999 reported hospital cover 1.11). People reporting none of the illnesses listed on the PHI and 48,743 reported holding combined hospital and questionnaire were significantly less likely to hold PHI ancillary PHI. than those reporting any illness. Lesser variations in the RR for PHI were observed according to family history of a Overall, 65% of men and women had PHI (Table 1). The range of specific diseases, with significantly but only crude proportion of people with PHI fell from 69–70% of slightly increased RRs of PHI in those with a family history those aged 50–64 to 64% of those aged 65–69, 57–58% of heart disease, hypertension, dementia, bowel cancer, of those aged 70–84 and 53% of those aged 85 or older. osteoporosis, and prostate cancer and slightly reduced RR The adjusted results indicate that for a given sex, income, of PHI with a family history of diabetes and severe depres- education level, remoteness, aboriginality, relationship sion. In general, PHI was significantly more common status and country of birth, older people in the study had among those with a history of a range of operations, a higher probability of having PHI than younger people. including removal of skin cancer, knee and hip replace- The large change in the RR with adjustment indicates that ment, vasectomy, prostatectomy, hysterectomy and pro- the relationship between age and PHI is influenced sub- lapse repair. PHI was significantly more common in those stantially by the demographic factors listed in Table 1. reporting previous screening for breast, prostate and colorectal cancer. The adjusted RR of having any PHI was lower among those living outside major urban centres. Those with Similar patterns were seen when the data were split into lower incomes, lower levels of education, a health care hospital cover PHI and hospital and ancillary PHI (data concession card and those reporting Indigenous origin, not shown). were significantly and substantially less likely to hold PHI than other members of the cohort (Table 1). The likeli- Discussion hood of holding PHI was significantly reduced, but to a In this population-based study of Australians aged 45 and lesser extent, in those who were not in a marriage-type over, multiple factors were found to differ significantly relationship and those born outside of Australia. Figure 1 between those with and without PHI. The factors inde- shows the proportion of individuals with any PHI accord- pendently and most strongly related to having PHI were: Page 4 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:16 http://www.anzhealthpolicy.com/content/6/1/16 low income, being single) and, at the same time, coverage is higher than expected once these factors are taken into account. This means that other influences, such as rebates, lifetime cover incentives, differences in risk perception and health consciousness may be maintaining PHI in older age. University From a policy perspective, it is the absolute proportion of Certificate/diploma those with PHI that is most important. The lower coverage HSC School certificate with increasing age, coupled with the finding that PHI is Trade higher in those in better health and hence less need for None health care, suggests that the potential contribution of <20,000 20,000 to 49,999 50,000 to 69,999 • 70,000 Annual househol d pre-tax i ncom e (AU$) PHI to dealing with the increased morbidity associated with population ageing may be limited. Moreover, PHI Proportion of a Figure 1 nce by income a study pa nd educa rticipant tional attainment s with private health insur- does not specifically cover aged care provided by residen- Proportion of study participants with private health tial or community care, and specialised geriatric services insurance by income and educational attainment. are almost exclusively based in public health care facili- ties. higher income; higher educational attainment; not hold- This study has a number of strengths. It provides a unique ing a health care concession card; not being of Aboriginal/ combination of large numbers and comprehensive ques- Torres Strait Islander origin; being a non-smoker; high lev- tionnaire data, allowing investigation of the relationship els of self-rated health and functional capacity; and low between PHI and a very wide range of variables with a levels of psychological distress. Significant but lesser dif- great deal of power and with adjustment for multiple fac- ferences were observed according to other demographic tors. A number of factors investigated here are being factors, with higher levels of PHI in those who were reported on for the first time. The cross-sectional nature of younger, living in urban areas, those with a partner, those the study means it is not possible in many cases to know in paid work and those born in Australia, compared to whether or not the purchase of PHI came before or after other people. People who were of healthy weight, who the exposure in question and in these cases one cannot drank alcohol and had sufficient levels of physical activity attribute a causal relationship to the acquisition of PHI. and fruit and vegetable intake, were more likely to have However, most risk factors are likely to pre-date or not be PHI. Finally, PHI coverage was higher in people reporting influenced substantively by PHI purchasing decisions. non-melanoma skin cancers, prostate cancer or an The self-reported nature of the variables should be consid- enlarged prostate, those reporting a family history of a ered when interpreting the findings. We have adjusted for range of conditions and those reporting surgery for a multiple potential confounding factors, but it remains range of reasons, and lower in people reporting diabetes possible that other unmeasured factors influence PHI or stroke, compared to people who did not have these uptake. medical, surgical or family histories. The 45 and Up Study is a large scale cohort study and is In this study, older people were less likely than those aged designed to provide valid comparisons of the characteris- under 60 to have PHI, in absolute terms. However, the tics of groups within the cohort (e.g. relative risks of cer- finding of a large change in the RR of having PHI follow- tain outcomes in exposed and unexposed individuals), ing adjustment for demographic variables indicates that rather than prevalence estimates that are representative of this relationship is heavily influenced by other factors, the general population. The absolute age-specific percent- which may in fact be on the "causal pathway" between age of individuals reporting PHI observed here was higher increasing age and reduced PHI. For example, older age than that reported elsewhere. Fund membership data generally results in lower income and this lower income from the Private Health Insurance Administration Coun- may then influence the probability of PHI uptake. It is cil indicate that in 2007, around 51% of NSW residents interesting to note that once sex, remoteness, income, aged 45 years and over had private health insurance education, aboriginality, relationship status and country [12,13]. In the most recent Australian National Health of birth were taken into account, older study participants Survey (2004–5), 61% of respondents aged 45–54, 61% were significantly more likely to have PHI than younger of those aged 55–64 and 51% of those aged 65–74 ones. Considered together, these findings suggest that the reported having PHI [3,14], compared to corresponding lower absolute PHI coverage in older participants may be figures of 67%, 69% and 61% in the data presented here. explained primarily by factors accompanying ageing (e.g. The high rate of PHI coverage among 45 and Up Study Page 5 of 9 (page number not for citation purposes) Percentage wi th pri vate heal th i nsurance Australia and New Zealand Health Policy 2009, 6:16 http://www.anzhealthpolicy.com/content/6/1/16 Table 2: Health risk factors and private health insurance status, adjusted for sociodemographic factors Private health insurance Lifestyle factors N % column % PHI RR crude* RR adjusted BMI categories Underweight 3,903 4.0 61.1 0.91 (0.89, 0.94) 0.97 (0.95, 0.99) Healthy weight 31,256 31.9 67.0 1 1 Overweight 36,027 36.8 67.4 1.01 (1.00, 1.02) 1.02 (1.01, 1.03) Obese 19,619 20.1 61.0 0.91 (0.90, 0.92) 0.97 (0.96, 0.99) Smoking status Never 55,522 56.7 69.7 1 1 Past 34,989 35.8 62.8 0.90 (0.89, 0.91) 0.94 (0.93, 0.94) Current 7,319 7.5 41.4 0.59 (0.58, 0.61) 0.71 (0.70, 0.73) Alcohol consumption (drinks/week) Zero 31,098 31.8 55.4 1 1 1 to 6 28,339 29.0 70.2 1.27 (1.25, 1.28) 1.11 (1.10, 1.12) 7 to 13 17,992 18.4 72.7 1.31 (1.29, 1.33) 1.12 (1.10, 1.13) 14 to 20 10,732 11.0 72.5 1.31 (1.29, 1.33) 1.11 (1.10, 1.13) 21 and over 7,642 7.8 63.0 1.14 (1.12, 1.16) 1.03 (1.01, 1.05) Physical activity (sessions/week) Zero 4,047 4.1 52.7 1 1 1 to 6 24,557 25.1 65.0 1.23 (1.20, 1.27) 1.09 (1.06, 1.12) 7 to 10 24,526 25.1 65.8 1.25 (1.21, 1.29) 1.08 (1.05, 1.11) 11 to 15 20,030 20.5 68.0 1.29 (1.25, 1.33) 1.10 (1.07, 1.13) 16 and over 22,810 23.3 65.8 1.25 (1.21, 1.29) 1.07 (1.04, 1.10) Vegetable intake (serves/day) Zero 1,994 2.0 47.8 1 1 >0 to 1 9,576 9.8 58.4 1.22 (1.16, 1.28) 1.08 (1.04, 1.13) 2 to 3 40,085 41.0 66.2 1.38 (1.32, 1.45) 1.14 (1.10, 1.19) 4 to 5 24,065 24.6 68.5 1.43 (1.37, 1.50) 1.17 (1.12, 1.22) 6 and over 20,035 20.5 65.0 1.36 (1.30, 1.42) 1.17 (1.12, 1.22) Fruit intake (serves/day) Zero 6,225 6.4 50.7 1 1 >0 to 1 19,018 19.4 62.5 1.23 (1.20, 1.26) 1.12 (1.09, 1.15) 2 to 3 53,961 55.2 67.4 1.33 (1.30, 1.36) 1.17 (1.15, 1.20) 4 and over 16,362 16.7 67.7 1.34 (1.30, 1.37) 1.19 (1.16, 1.22) * Relative risk of having any private health insurance Adjusted for age, sex, remoteness, income, education, aborginality, relationship status and country of birth BMI categories: Underweight (BMI<20), Normal weight (BMI 20-<25), Overweight (BMI 25-<30), Obese (BMI 30+) Reference category Percentages do not consistently total to 100% due to missing values participants is likely to reflect the well recognised "healthy tralia; this reported that the likelihood of Indigenous indi- cohort effect"; it does not detract from the validity of inter- viduals using PHI for hospitalisation was negligible [21]. nal comparisons of relative risks of PHI in different groups [4,15]. The strong observed relationship between PHI and socio- economic status is not surprising, since PHI is relatively The pattern of variation in PHI seen here by age, income, costly and there are incentives for those with higher education, urban/rural residence, marital status, paid incomes to purchase PHI. Furthermore, the main reason work status and country of birth is consistent with analy- given for not having PHI among uninsured individuals in ses of data from the Australian National Health Survey the 2001 National Health Survey was being unable to from 1989–2005 [3,16-20]. We found that PHI coverage afford it [3]. The independent relationships of education, among Indigenous people, after adjusting for other socio- region of residence, marital status, paid work and country demographic factors, was only half that of the non-Indig- of birth, over and above income, suggests that knowledge enous population. The only previous information about about health, accessibility to services, social interactions PHI in Indigenous people comes from a study of payment and cultural factors may all play a role in decisions about classification status for hospital episodes in Western Aus- whether to purchase private health insurance. Page 6 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:16 http://www.anzhealthpolicy.com/content/6/1/16 Table 3: Health status, health conditions, health actions and private health insurance status, adjusted for sociodemographic factors Private health insurance Health conditions No. % column % PHI RR crude* RR adjusted Psychological distress Low 64,669 66.1 69.8 1 1 Moderate 13,223 13.5 62.8 0.90 (0.89, 0.91) 0.96 (0.95, 0.97) High 4,515 4.6 51.7 0.74 (0.72, 0.76) 0.87 (0.85, 0.89) Very high 2,736 2.8 47.1 0.68 (0.65, 0.70) 0.84 (0.81, 0.87) Overall health Excellent 14,867 15.2 75.0 1 1 Very good 35,255 36.0 71.3 0.95 (0.94, 0.96) 1.01 (1.00, 1.02) Good 31,598 32.3 62.4 0.83 (0.82, 0.84) 0.97 (0.96, 0.98) Fair 10,875 11.1 48.5 0.65 (0.63, 0.66) 0.86 (0.85, 0.88) Poor 1,898 1.9 35.5 0.47 (0.44, 0.50) 0.71 (0.67, 0.75) Functional limitation No limitation 29,054 29.7 72.0 1 1 Minor limitation 14,903 15.2 73.6 1.02 (1.01, 1.03) 1.01 (1.00, 1.03) Mild limitation 16,308 16.7 69.1 0.96 (0.95, 0.97) 1.00 (0.99, 1.01) Moderate limitation 14,600 14.9 61.2 0.85 (0.84, 0.86) 0.97 (0.95, 0.98) Severe limitation 13,146 13.4 47.2 0.66 (0.64, 0.67) 0.86 (0.84, 0.88) Number of conditions None 21,553 22.0 66.7 1 1 1 22,727 23.2 67.8 1.02 (1.00, 1.03) 1.02 (1.01, 1.03) 2 21,311 21.8 64.8 0.97 (0.96, 0.98) 1.02 (1.00, 1.03) 3 10,023 10.2 61.8 0.93 (0.91, 0.94) 1.02 (1.00, 1.03) 4 or more 5,798 5.9 61.0 0.91 (0.89, 0.93) 1.04 (1.01, 1.06) Ever had Skin cancer 24,917 25.5 68.7 1.07 (1.06, 1.08) 1.04 (1.03, 1.05) Melanoma 5,299 5.4 65.6 1.01 (0.99, 1.03) 1.02 (1.00, 1.03) Other cancer 6,108 6.2 61.6 0.94 (0.92, 0.96) 0.99 (0.98, 1.01) Heart disease 11,475 11.7 60.0 0.91 (0.90, 0.93) 0.99 (0.98, 1.01) High blood pressure ** 34,107 34.9 62.8 0.95 (0.94, 0.96) 1.00 (0.99, 1.01) Stroke 3,102 3.2 50.2 0.76 (0.74, 0.79) 0.91 (0.88, 0.94) Diabetes 8,526 8.7 53.9 0.81 (0.80, 0.83) 0.92 (0.91, 0.94) Thrombosis 4,548 4.6 60.3 0.92 (0.90, 0.94) 1.00 (0.97, 1.02) Parkinson's disease 672 0.7 58.5 0.90 (0.84, 0.96) 1.01 (0.96, 1.07) None of the above 20,319 20.8 67.1 1.04 (1.03, 1.05) 0.98 (0.97, 0.99) Breast cancer 2,675 5.2 64.7 1.00 (0.97, 1.03) 1.01 (0.99, 1.04) || Enlarged prostate 7,576 16.5 67.8 1.04 (1.03, 1.06) 1.07 (1.06, 1.09) || Prostate cancer 2,780 6.0 67.1 1.03 (1.00, 1.06) 1.09 (1.06, 1.11) §,†† Family history Heart disease 45,014 46.0 66.3 1.03 (1.02, 1.04) 1.02 (1.01, 1.03) High blood pressure 48,909 50.0 67.1 1.06 (1.05, 1.07) 1.02 (1.01, 1.03) Stroke 25,670 26.2 65.4 1.00 (0.99, 1.02) 1.00 (0.99, 1.01) Diabetes 21,981 22.5 62.9 0.96 (0.95, 0.97) 0.98 (0.97, 0.99) Dementia 15,877 16.2 68.3 1.06 (1.05, 1.07) 1.03 (1.02, 1.04) Parkinson's disease 4,561 4.7 65.5 1.01 (0.98, 1.03) 0.99 (0.97, 1.01) Severe depression 12,020 12.3 64.0 0.98 (0.97, 0.99) 0.97 (0.96, 0.98) Severe arthritis 20,760 21.2 63.2 0.96 (0.95, 0.97) 1.00 (0.99, 1.01) Breast cancer 10,991 11.2 66.0 1.02 (1.00, 1.03) 1.01 (0.99, 1.02) Bowel cancer 13,471 13.8 66.5 1.02 (1.01, 1.04) 1.02 (1.01, 1.03) Lung cancer 10,115 10.3 62.3 0.95 (0.94, 0.97) 0.98 (0.97, 1.00) Melanoma 8,689 8.9 67.9 1.05 (1.03, 1.06) 1.00 (0.99, 1.02) Osteoporosis 13,830 14.1 68.6 1.06 (1.05, 1.08) 1.03 (1.02, 1.04) Hip fracture 9,720 9.9 66.8 1.03 (1.01, 1.04) 1.01 (1.00, 1.03) Prostate cancer 9,960 10.2 68.5 1.06 (1.04, 1.07) 1.03 (1.02, 1.04) Ovarian cancer 3,482 3.6 61.9 0.95 (0.92, 0.97) 0.99 (0.97, 1.02) Operations Removal of skin cancer 25,930 26.5 68.4 1.07 (1.06, 1.08) 1.04 (1.03, 1.05) Knee replacement 3,829 3.9 64.2 0.99 (0.96, 1.01) 1.10 (1.08, 1.13) Hip replacement 3,026 3.1 66.6 1.02 (1.00, 1.05) 1.12 (1.09, 1.15) Page 7 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:16 http://www.anzhealthpolicy.com/content/6/1/16 Table 3: Health status, health conditions, health actions and private health insurance status, adjusted for sociodemographic factors Gallbladder removed 9,803 10.0 60.5 0.92 (0.91, 0.94) 0.99 (0.97, 1.00) || Vasectomy 10,998 23.9 71.9 1.13 (1.12, 1.15) 1.02 (1.01, 1.03) || Part of prostate removed 2,661 5.8 67.3 1.03 (1.00, 1.06) 1.10 (1.07, 1.13) || Whole prostate removed 1,653 3.6 71.6 1.10 (1.06, 1.13) 1.12 (1.09, 1.15) Hysterectomy 14,827 28.6 62.9 0.96 (0.94, 0.97) 1.02 (1.01, 1.03) Both ovaries removed 5,185 10.0 62.4 0.96 (0.94, 0.98) 1.03 (1.01, 1.05) Sterilisation 14,311 27.6 64.1 0.98 (0.97, 1.00) 0.99 (0.98, 1.00) 5,916 11.4 63.9 0.98 (0.96, 1.00) 1.04 (1.03, 1.06) Prolapse repair Screening history Bowel cancer screening 46,357 47.4 70.9 1.18 (1.17, 1.19) 1.12 (1.11, 1.13) Breast cancer screening 45,708 88.1 66.5 1.24 (1.21, 1.27) 1.16 (1.13, 1.19) || Prostate disease screening 31,549 68.6 69.1 1.20 (1.18, 1.22) 1.14 (1.12, 1.16) * Relative risk of having any private health insurance Adjusted for age, sex, remoteness, income, education, aborginality, relationship status and country of birth ‡ § Reference category Reference category = No || ¶ Males only Females only ** Excluding high blood pressure during pregnancy †† Whether mother, father, brother or sister had the disease Percentages do not consistently total to 100% due to missing values Overall, our data suggest that people with PHI are likely to including ischaemic heart disease, diabetes, arthritis and be more health conscious than uninsured individuals. mental and behavioural problems, and among people Our finding of lower rates of PHI in smokers is consistent with higher levels of psychological distress [3]. Another with others [3,16-22]. This association held regardless of study has reported that PHI coverage is lower in people education, income and other sociodemographic factors. with worse self-rated health [18]. People's individual attitudes towards risk are likely to influence both decisions about health behaviours, such as PHI users were more likely than non-users to report non- giving up smoking, and whether or not to take out private melanoma skin and prostate cancers, after adjusting for health insurance. socioeconomic and demographic factors. We are not aware of any previous publications on these relationships. In our sample, people who drank alcohol weekly were These cancers are increased among those undergoing more likely than non-drinkers to have PHI. This is in screening, so they may be related to the general health apparent contrast to crude results from the 2004–5 consciousness and screening behaviour of insured indi- National Health Survey, showing lower levels of PHI in viduals. They are related to higher socioeconomic status heavy drinkers aged less than 65 and no difference in PHI [23,24], which may not have been fully accounted for in status according to alcohol consumption in those 65 and the adjustment process. The long term nature of these over [3]. It is difficult to compare these results because of conditions means it is also possible that PHI may have the differences in adjustment. While previous research has been purchased subsequent to diagnosis. suggested increased PHI in overweight individuals com- pared to those of healthy weight [18], our finding of sig- Overall, the evidence suggests that those with disabling nificantly reduced PHI in obese individuals, after illness are less likely to have PHI. However, many less dis- accounting for sociodemographic factors, has not to our abling screening-related conditions, such as hypertension knowledge been shown before. Similarly, our findings of and hypercholesterolaemia, are very common and it is higher levels of PHI in people with higher levels of physi- therefore possible for PHI possession to be related to an cal activity and fruit and vegetable consumption do not increasing number of health conditions, at the same time appear to have been reported elsewhere. as being reduced among people with certain conditions and poorer self-rated health. The relationship between health status and PHI is com- plex. We found lower levels of PHI among those reporting The finding of higher levels of PHI among those reporting stroke or diabetes, with worse self-rated health, with past operations for hip and knee replacement, skin cancer higher levels of psychological distress and with reduced removal, prostatectomy and repair of uterine prolapse has functional capacity. Crude Australian National Health not been reported previously, but are likely to relate to Survey data from 2004–5 show decreased PHI among better accessibility to elective surgery among those with people reporting specific long term health conditions, PHI. This is consistent with National Health Survey data Page 8 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2009, 6:16 http://www.anzhealthpolicy.com/content/6/1/16 showing higher PHI among those reporting hospitalisa- References 1. Australian Institute of Health and Welfare: Australia's Health tion within the previous 12 months [16]. The data regard- 2006. AIHW cat no. AUS 73, Canberra; 2006. ing family history are difficult to interpret as many 2. Australian Bureau of Statistics: Yearbook Australia 2008. cat no. familial diagnoses (e.g. dementia, hip fracture, osteoporo- 1301.0. Canberra; 2006. 3. Australian Bureau of Statistics: Private Health Insurance: A snap- sis) are predominantly markers of parental longevity. The shot 2004–05. cat no. 4818.0.55.001. Canberra; 2006. data suggest possible clustering of not having PHI, indi- 4. 45 and Up Study Collaborators: Cohort profile: the 45 and Up Study. Int J Epidemiol. 2007, 37(5):941-947. cated by reduced insurance among those with a family 5. Australian Institute of Health and Welfare: Rural, Regional and history of diabetes and those with a family history of lung Remote Health: A guide to remoteness classifications. cancer (i.e. smoking). AIHW Catalogue PHE 53, Canberra; 2004. 6. Kessler R, Mroczek D: Final Version of our Non-specific Psy- chological Distress Scale [memo dated 3/10/94]. In Ann Arbor Conclusion (MI): Survey Research Center of the Institute for Social Research University In summary, our findings demonstrate that, compared to of Michigan, Michigan; 1994. 7. Stewart A, Kamberg CJ: Physical functioning measures. In Meas- the rest of the study population, those with PHI are richer, uring functioning and well-being: the Medical Outcomes Study approach better educated, more health conscious, in better health Edited by: Stewart A, Ware JE. Duke University Press, Durham, North Carolina; 1992. and more likely to use certain more discretionary health 8. Zou G: A modified Poisson regression approach to prospec- services. These findings have important implications for tive studies with binary data. Am J Epidemiol 2004, 159:702-706. health services planning in that they demonstrate gener- 9. SAS Institute, Inc: SAS Version 9.2 [software]. Cary, NC; 2007. 10. Australian Government Department of Health and Ageing: National ally higher PHI uptake among those in better health and Physical Activity Guidelines for Australians. Canberra 2005. hence less need for health care. Differential uptake of PHI 11. National Health and Medical Research Council: Australian Guide will impact on the distribution of health care costs among to Healthy Eating. Canberra 2003. 12. Australian Bureau of Statistics: Population by Age and Sex, the private and public sectors, and how this changes over Regions of Australia, 2007. cat. no. 3235.0. Canberra; 2008. time. It is likely to influence individual trajectories of 13. Private Health Insurance Administration Council: Annual Coverage Survey 2007. [http://www.phiac.gov.au/for-industry/industry-sta health care use as people age and–ultimately–their health tistics/annual-coverage-survey/introduction/]. outcomes. These issues will be further explored in subse- 14. Australian Bureau of Statistics: National Health Survey 2004–05: quent analyses using the 45 and Up Study. Summary of results. cat. no. 4364.0. Canberra; 2006. 15. Willett WC: Merging and emerging cohorts. Not worth the wait. Nature 2007, 445:257-258. Competing interests 16. Temple J: Explaining the private health insurance coverage of The authors declare that they have no competing interests. older Australians. People and place 2004, 12:13-23. 17. Hopkins S, Kidd M: The determinants of the demand for pri- vate health insurance under Medicare. Applied Economics 1996, Authors' contributions 28:1623-1632. 18. Barrett G, Conlon R: Adverse selection and the decline in pri- EB participated in the design of the study, oversaw data vate health insurance coverage in Australia: 1989–95. Eco- analysis and drafted the manuscript. LJ participated in the nomic Record 2003, 79:279-296. design of the study, oversaw data analysis and helped to 19. Lokuge B, Denniss R, Faunce T: Private health insurance and regional Australia. Med J Aust 2005, 182:290-293. draft the manuscript. SL participated in the design of the 20. Wilson J: An analysis of private health insurance membership study, performed the statistical analysis and helped to in Australia, 1995. NATSEM Technical paper No. 46. Canberra; draft the manuscript. KR participated in the design of the 21. Moorin RE, Holman CDJ: Modelling Changes in the Determi- study and assisted with the statistical analysis. All authors nants of PHI Utilisation in Western Australia across Five read and approved the final manuscript. Health Care Policy Eras between 1981 and 2001. Health Policy 2007, 81:183-194. 22. Siahpush M, Borland R, Scollo M: Is household smoking status Acknowledgements associated with expenditure on food at restaurants, alcohol, The authors thank the men and women participating in the 45 and Up gambling and insurance? Results from the 1998–99 House- hold Expenditure Survey, Australia. Tobacco Control 2004, Study. The 45 and Up Study is run by The Sax Institute in collaboration with 13:409-414. the Cancer Council of New South Wales, the New South Wales Division 23. Key TJ, Verkasalo PK, Banks E: The epidemiology of breast can- of the National Heart Foundation of Australia, the New South Wales cer. Lancet Oncology 2001, 2:133-140. Department of Health, beyondblue: the national depression initiative, the New 24. Lund Nilsen T, Johnsen R, Vatten L: Socio-economic and lifestyle South Wales Department of Ageing, Disability and Home Care and Unit- factors associated with the risk of prostate cancer. Br J Cancer 2000, 82:1358-1363. ingCare Ageing, and with support from Macquarie Bank Foundation, the Baxter Charitable Foundation, the Alma Hazel Eddy Trust and The National Health and Medical Research Council of Australia (Senior Research Fellow- ship to E.B.). KR was employed as part of the NSW Biostatistical Officer Training Program funded by the NSW Department of Health while under- taking this work based at the Sax Institute. This study was part of the 45 and Up Study MBF Foundation Policy in Action Roundtable work program and was also supported by NHMRC grant 402810; the MBF Foundation is the sole funder of the Policy in Action Roundtable. Page 9 of 9 (page number not for citation purposes)

Journal

Australia and New Zealand Health PolicySpringer Journals

Published: Jul 13, 2009

References