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Pattern of blood pressure in Australian adults: Results from a National Blood Pressure Screening Day of 13,825 adults
International Journal of Cardiology 145 (2010) 461–467
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International Journal of Cardiology j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / i j c a r d
Pattern of blood pressure in Australian adults: Results from a National Blood Pressure Screening Day of 13,825 adults☆ Melinda J. Carrington, Garry L. Jennings, Simon Stewart ⁎ Baker IDI Heart and Diabetes Institute, Melbourne, Australia
a r t i c l e
i n f o
Article history: Received 2 June 2009 Accepted 3 June 2009 Available online 1 July 2009 Keywords: Blood pressure measurement and monitoring Hypertension detection and control Cardiovascular disease Population Obesity Socio-economic status
a b s t r a c t Background: Recent national data of cardiovascular disease (CVD) risk factors in Australia are limited. Therefore this study sought to gain a contemporary snapshot of the blood pressure (BP) profile of Australian adults. Methods: We established 100 metropolitan and regional screening sites. Using a standardized protocol and the same automated, validated BP monitor, Registered Nurses recorded the BP and other risk factors for CVD of self-selected volunteers on a single day. Results: A total of 13,825 subjects (55% female, aged 48 ± 16 years) were assessed. Mean systolic and diastolic BP was 131 ± 18 and 79 ± 12 mm Hg. Overall, 34% had an elevated BP while 10% being treated for hypertension (HT) were normotensive (combined total 44%). Elevated BP was more common in older individuals, men (42% versus 27% of women), regional dwelling residents (40% versus 32% of metropolitan) and people from lower socio-economic backgrounds (39% versus 30% of higher). Overall, 50% of subjects with a history of HT had elevated BP compared to 30% without a history of HT. Adjusting for age and sex, elevated BP was independently associated with obesity (OR: 1.77, 95% CI 1.52–2.06), regional location (OR: 1.32, 95% CI 1.19–1.45) and modifiable risk factors (OR: 1.28, 95% CI 1.21–1.35); those being treated for CVD or diabetes are less likely to have high BP. Conclusions: In the largest study of its kind in Australia, the findings highlight the need for continued vigilance to detect, monitor and prevent elevated BP within an ageing population in whom metabolic disorders are becoming more frequent. Crown Copyright © 2009 Published by Elsevier Ireland Ltd. All rights reserved.
1. Introduction As a key contributor to the global increase in cardiovascular disease (CVD), high blood pressure (BP) is a readily detectable and modifiable condition that represents a major target for primary and secondary prevention programs. In 2001, high BP or hypertension (HT) was estimated to contribute to 7.6 million deaths (13.5% of total deaths) and 92 million disability-adjusted life years globally [1]. In Australia, it was the largest contributor to CVD in 2003 and explained 42% of CVD burden (7.6% of total disease burden) [2]. It is also the most commonly managed cardiovascular risk factor by primary care physicians in Australia, accounting for nine in every 100 encounters (three times that of lipid disorder management) [3]. Elevated BP seems to have re-emerged with an even greater effect on premature mortality and disability [3] and despite the availability
☆ Sources of support: The National Blood Pressure Screening Day was independently designed and analysed by Baker IDI Heart and Diabetes Institute and generously supported by Schering Plough Pty. Limited. Simon Stewart and Melinda Carrington are supported by the National Health and Medical Research Council of Australia. ⁎ Corresponding author. PO Box 6492, St Kilda Rd Central, Melbourne Vic 8008, Australia. Tel.: +61 3 8532 1640, 0438 302 111 (mobile); fax: +61 3 8532 1100. E-mail address: [email protected] (S. Stewart).
of effective pharmacological treatments [4]. During the 1980s, the prevalence of high BP in Australia reportedly declined from 38% to 26% but steadily rose again in the 1990s and early 21st Century [5–8]. The population is ageing and rates of obesity and metabolic disorders are rising [9] which may contribute to increasing rates of HT. Australia has also experienced significant socio-demographic changes, including the overall ageing of the post-war “baby boomer” generation and widening differentials in the socio-economic status of the population, particularly metropolitan versus regional/rural communities. In Australia, regional and remote populations comprise around 32% of the 15 million adult population aged over 18 years [10]. We undertook a National Blood Pressure Screening Day to gain a contemporary “snapshot” of the BP profile of adult Australians. A key objective was to explore differences according to age, sex, geographic location, treatment for those known to have HT and socio-economic status. A secondary aim was to project the prevalence of elevated BP and obesity in adult Australians. 2. Materials and methods 2.1. Participants A total of 13,825 participants were recruited. This equates to one in every 1000 adult Australians (see Fig. 1 for a profile of the Australian population). People were offered a
0167-5273/$ – see front matter. Crown Copyright © 2009 Published by Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.ijcard.2009.06.003
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M.J. Carrington et al. / International Journal of Cardiology 145 (2010) 461–467
Fig. 1. Location of BP screening sites in metropolitan and regional areas across Australia. © Commonwealth of Australia, Geoscience Australia. Demographic profile of adult Australians based on the latest Census of the population [10].
free BP check if they walked by any of the 100 screening stations distributed throughout Australia on a single day (Saturday 30th June 2007). A weekend day was chosen to allow for a broader mix of age groups and to include members of the workforce as well as nonworking adults. On this day, invitation to participate was through a combination of prominent advertising signs, a short written leaflet distributed adjacent to the screening booth and by verbal invitation. There was no prior advertising to announce the locations or publicizing that free BP checks were conducted. Based on prior market research, we estimated that approximately 250,000 Australians (approximately one in 10 adults) would come into contact with a screening station. The only inclusion criteria were to be 18 years of age or above and the ability to provide verbal consent to participate. Participants were otherwise self-selected. 2.2. Design We undertook a cross-sectional survey of the BP profile of Australian adults on a single day. In order to capture as broad and large a sample as possible, we used Geographical Information System profiling of the distribution of the Australian population [11] to identify all population centres with N 20,000 people in every state and territory. A dedicated screening station was erected at each site and staff allocated for every 250,000 people within major metropolitan centres and for N 20,000 people within regional centres. Screening stations were distributed in locations with a high concentration of people (predominantly large shopping/leisure precincts). This amounted to 74 metropolitan screening locations and 26 regional screening locations. Fig. 1 shows the distribution of these 100 screening stations spanning all six states and two territories in Australia. Stations were specially designed for privacy and comfort and included four independent screening booths, an in-built height measure and standardized equipment. Screening was undertaken by a team of 300 Registered Nurses who followed a detailed written protocol to ensure the standard acquisition of the study data. Stations were operational between 0900 and 1600 on the screening day, with a maximal
capacity of approximately 150 participants per station. The study was approved by the Human Research Ethics Committee at The Alfred Hospital, Melbourne, Australia. 2.3. Data collection Screening comprised two simple components; a self-administered questionnaire and physical measurements. The self-administered questionnaire was a one-page 16item survey that collected: 1) brief socio-demographic details (age, gender, postcode of residence, and ethnicity); 2) current risk factors for and prior history of CVD; 3) BP management and control by individuals and their general practitioner (GP) and; 4) personal perceptions about high BP as a risk for CVD. Socio-economic status was determined using the official Australian Bureau of Statistics 2006 Census data on median household income according to an individual's postcode of residence [10]. After completion of the survey, a brief physical assessment was conducted by a Registered Nurse in accordance with standardized procedures advocated by the National Heart Foundation of Australia for BP [4] and the World Health Organization (WHO) STEPwise approach to surveillance (STEPS) procedure for waist and hip circumference [12]. BP was measured in the sitting position using an appropriately sized cuff and validated digital BP monitor (Model UA-767, A&D Mercury Pty. Ltd., SA, Australia) [13] after an initial rest period of 5 min. With the arm supported by a table at heart level, two measurements separated by a one-minute interval were taken; the average of these two readings was analysed provided that there was no discrepancy in systolic blood pressure (SBP) of ≥10 mm Hg or ≥7 mm Hg in diastolic blood pressure (DBP). These thresholds were adapted from prior survey methods [5] and where a discrepancy in the two readings occurred, only the second reading was selected for analyses. Participants received an educational brochure about BP and its importance for CVD. They were also provided with a record card that noted the higher of their two BP measurements, with follow-up advice to either consult their GP (for high risk individuals with elevated BP, as defined by SBP ≥ 140 mm Hg and/or DBP ≥ 90 mm Hg) or to continue having regular BP check-ups (for people with BP below these cut-offs).
M.J. Carrington et al. / International Journal of Cardiology 145 (2010) 461–467 Measurements of height and weight for calculation of body mass index (BMI, kg/m2) were performed using a linear height scale imprinted on the rear wall of the screening stations and digital weighing scales. Before being weighed, participants removed their shoes and heavy garments and as in previous population surveys [7], 1 kg in weight was subtracted to prevent overestimation due to clothing. Participants were classified by BMI as normal weight (b 25 kg/m2), overweight (25 to b 30 kg/m2) and obese (≥ 30 kg/m2) according to the National Health and Medical Research Council classifications [14]. Waist circumference was measured while standing at a level midway between the lowest rib and iliac crest, measured in the horizontal plane at the end of a gentle expiration. Men and women respectively were classified by waist circumference as overweight for measurements between 94 to b 101.9 cm and 80 to b 87.9 cm, and as obese for measurements ≥ 102 cm for men and ≥ 88 cm for women, similar to previous studies in the literature [6,15]. Normal weight was classified by a waist circumference b 94 cm for men and b80 cm for women.
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household income by postcode of residence were non-Gaussian distributed, individuals were categorized into low (median household income $1 to $799/week), middle ($800 to $1199/week) and high ($1200 to N$3000/week) socio-economic backgrounds. To identify the independent correlates of elevated BP (SBP, DBP and combined HT) according to treatment status (expressed as adjusted OR with 95% CIs), all variables were subject to backward, step-wise multiple logistic regression analyses with retention of variables in each step at the level of p b 0.1. BMI and waist circumference were initially analysed as continuous variables and subsequently as categorical variables. Statistical significance for all tests was established at p b 0.05. To estimate the potential BP and weight profile of adult Australians based on the findings of this survey, we used data from the most recent Census of the population [10]. As such, age and sex projections using the observed proportions and 95% CIs within each discrete age group for men and women separately were derived for the current demographic profile of Australia. 3. Results
2.4. Data analyses Data were analysed for men and women separately and where appropriate, on an age-specific basis. Normally distributed continuous data are presented as the mean ± SD and discrete data as counts and percentage. Age and sex-adjusted comparisons of BP and other study data were analysed on the basis of regional versus metropolitan residence. Categorical variables were compared using χ2 tests with the calculation of odds ratios (OR) and 95% confidence intervals (CI). Normally distributed continuous variables were compared using Student's t-test and analysis of variance with post-hoc Dunnett's test for between group comparisons where appropriate. As the data classifying median
A total of 13,825 completed profiles were verified from 99 screening stations. Table 1 summarises the socio-demographic and clinical profile according to gender and locality. Overall, 7666 (55%) were women with an average age of 48.7 ± 15.8 years and 48.0 ± 16.2 years for men. Participants were predominantly Caucasian/European (86%) and one in ten was Asian. Based on the median household income for their residential postcode, the majority of participants were from middle socio-economic backgrounds (59%), with a similar proportion of low (20%) and high (21%) in the remainder of the group. A total of 10,649 (77%) subjects were from metropolitan areas and 3176 (23%) were from regional Australia.
Table 1 Socio-demographic and clinical profile of participants.
Socio-demographic profile Age (years) Ethnicity: Caucasian Asian ATSI Other Education Primary education Secondary education TAFE/trade school Higher education Median household income (per week): $1 to $799 $800 to $1199 $1200 to N $3000 Clinical profile SBP (mm Hg) DBP (mm Hg) BMI (kg/m2) Normal Overweight Obese Waist circumference (cm) Normal Overweight Obese Pulse rate (bpm) Smokers Anti-hypertensive therapy ACE ARB CCB Diuretic BB History hypertension History diabetes History CVD Family history of CVD Number of modifiable risk factors for CVD: None One Two Three or more
Male
Female
Metropolitan
Regional
Total
N = 6159 (45%)
N = 7666 (55%)
N = 10,649 (77%)
N = 3176 (23%)
N = 13,825
48.0 ± 15.8
48.7 ± 15.8*
47.9 ± 15.9
50.1 ± 16.0††
48.4 ± 16.0
5246 (38%) 598 (4%) 80 (0.5%) 235 (1.5%)
6581 (48%)* 776 (6%) 101 (0.5%) 208 (1.5%)
8838 (64%) 1305 (9%) 91 (0.5%) 415 (3%)
2989 (22%)†† 69 (1%) 90 (0.5%) 28 (0.2%)
11,827 (86%) 1374 (10%) 181 (1%) 443 (3%)
296 (5%) 2157 (35%) 1280 (21%) 2357 (39%)
375 (5%)†† 3351 (44%) 1133 (15%) 2705 (36%)
502 (5%) 3995 (38%) 1794 (17%) 4226 (40%)
169 (5%)†† 1513 (48%) 619 (20%) 836 (27%)
671 (5%) 5508 (40%) 2413 (18%) 5062 (37%)
1183 (20%) 3440 (58%) 1325 (22%)
1475 (20%) 4402 (59%) 1538 (21%)
1602 (16%) 5934 (58%) 2730 (26%)
1056 (34%)†† 1908 (62%) 133 (4%)
2658 (20%) 7842 (59%) 2863 (21%)
136 ± 17 81 ± 12 27.8 ± 4.5 1557 (26%) 2826 (47%) 1601 (27%) 99.1 ± 12.9 1948 (33%) 1530 (26%) 2375 (41%) 76 ± 13 925 (15%) 1016 (18%) 442 (8%) 296 (5%) 181 (3%) 125 (2%) 315 (6%) 1571 (27%) 538 (9%) 744 (12%) 1231 (21%)
127 ± 18†† 78 ± 12†† 27.2 ± 5.8†† 3001 (41%)†† 2374 (32%) 3612 (27%) 90.5 ± 15.4†† 1901 (26%) 1469 (20%) 3885 (54%) 78 ± 12†† 934 (12%)†† 1317 (19%) 468 (7%)* 413 (6%) 212 (3%) 221 (3%)† 349 (5%) 2087 (28%)* 596 (8%)* 947 (13%) 2100 (28%)††
130 ± 18 79 ± 12 27.3 ± 5.1 3652 (35%) 4050 (39%) 2624 (25%) 93.7 ± 14.9 3144 (31%) 2377 (24%) 4597 (45%) 77 ± 13 1419 (14%) 1660 (17%) 627 (6%) 522 (5%) 274 (3%) 239 (2%) 474 (5%) 2734 (27%) 869 (8%) 1210 (12%) 2464 (24%)
134 ± 18†† 80 ± 12†† 28.2 ± 5.6†† 906 (30%)†† 1150 (38%) 988 (32%) 96.4 ± 15.0†† 705 (24%)†† 622 (21%) 1663 (55%) 77 ± 13 440 (14%) 673 (23%)†† 283 (10%)†† 187 (6%)* 119 (4%)† 107 (4%)† 190 (6%)†† 924 (30%)†† 265 (9%) 481 (15%)†† 867 (28%)††
131 ± 18 79 ± 12 27.5 ± 5.3 4558 (34%) 5200 (39%) 3612 (27%) 94.4 ± 15.0 3849 (29%) 2999 (23%) 6260 (48%) 77 ± 13 1859 (14%) 2333 (18%) 910 (7%) 709 (6%) 393 (3%) 346 (3%) 664 (5%) 3658 (28%) 1134 (8%) 1691 (12%) 3331 (25%)
3089 (52%) 1695 (28%) 782 (13%) 400 (7%)
3331 (45%)†† 2435 (33%) 1147 (15%) 550 (7%)
5018 (49%) 3174 (31%) 1444 (14%) 701 (6%)
1402 (45%)† 956 (31%) 485 (16%) 249 (8%)
6420 (48%) 4130 (31%) 1929 (14%) 950 (7%)
ATSI: Aboriginal and Torres Strait Islander; SBP: systolic blood pressure; DBP: diastolic blood pressure; BMI: body mass index; ACE: angiotensin-converting enzyme inhibitor; ARB: angiotensin II receptor blocker; CCB: calcium channel blocker; BB: beta blocker; CVD: cardiovascular disease; mm Hg: millimetres of mercury; bpm: beats per minute. *pb 0.05; †pb 0.01; ††pb 0.001.
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Fig. 2. A. SBP levels across age. B. DBP levels across age. C. Pulse pressure across age. SBP: systolic blood pressure; DBP: diastolic blood pressure; mm Hg: millimetres of mercury. Values are the mean ± SEM, n = 13,825.
There was a normal distribution of SBP and DBP. On average, SBP was 131 ± 18 and DBP was 79 ± 12 (Table 1). Fig. 2a to c, respectively shows that while mean SBP increased with advancing age, DBP increased up until the mid 60s before decreasing thereafter, resulting in a widening pulse pressure. The sample was on average overweight with a mean BMI of 27.5 ± 5.3 kg/m2 (27.8 ± 4.5 kg/m2 men versus 27.2 ± 5.8 kg/m2 women) and waist circumference of 99.1 ± 12.9 cm for men and 90.5 ± 15.4 cm for women. In total, 39% of participants were overweight and 27% were obese according to BMI criteria while 23% were overweight and 48% were obese as indicated by waist circumference. 3.1. Elevated BP levels Overall, 29% of individuals (n = 3920) had a SBP ≥140 mm Hg (36% men versus 22% women; OR 1.39, 95% CI 1.34 to 1.45) and 17% (n = 2317) had a DBP ≥90 mm Hg (21% men versus 14% women; OR 1.27, 95% CI 1.21 to 1.33); p b 0.001 for both comparisons. In total, 34% of subjects (n = 4677) had elevated BP ≥ 140 mm Hg and/or ≥90 mm Hg, with men having an increased likelihood compared to women (42% versus 27% respectively, OR 1.36, 95% CI 1.31 to 1.40; p b 0.001). According to the full WHO definition of HT (including normotensive individuals prescribed anti-hypertensive medication), this figure would increase to 44% (51% men versus 39% women; OR 1.26, 95% CI 1.22 to 1.30). 3.2. Treated versus non-treated BP profiles A total of 2333 subjects (18%) self-reported of being treated (with antihypertensive agents) for HT. Of these, 1160 (50%) had BP of ≥ 140/90 mm Hg. Average SBP did not differ according to mono versus combination anti-hypertensive therapy (138 ± 19 versus 139 ± 20 mm Hg, p N 0.05) whereas combination therapy was associated with a slightly lower DBP (79 ± 13 versus 81 ± 14 mm Hg; p b 0.001). A further 3106 (30%) subjects not taking anti-hypertensive therapy had elevated BP with an average SBP of 149 ± 14 mm Hg and DBP of 90 ±12 mm Hg. 3.3. High risk sub-groups Average BP levels varied significantly across each Australian state and territory (p b 0.001). The highest average BP and proportion of individuals with BP levels that exceeded 140/90 mm Hg, respectively, was in Tasmania (135 ± 18/81 ± 12 mm Hg and 45%). Similarly high values were recorded in the Northern Territory. The lowest values were recorded in the Australian Capital Territory (ACT) (126 ± 15/78 ±11 mm Hg and 26%). Mean BP levels were higher in regional (134 ± 18/80 ± 12 mm Hg) compared to metropolitan (130 ± 18/79 ± 12 mm Hg; p b 0.001) individuals. Overall, 40% versus 32% of regional and metropolitan dwelling subjects, respectively, had elevated BP (OR: 1.41, 95% CI 1.30 to 1.53; p b 0.001). This was evident for both men (138 ± 17/82 ± 12 versus 135 ± 17/81 ± 12 mm Hg) and women (131 ± 18/79 ± 12 versus 126 ± 18/77 ± 12 mm Hg) compared to their metropolitan counterparts. Overall, 47% versus 40% of regional compared to metropolitan dwelling men had elevated BP (OR: 1.32, 95% CI 1.17 to 1.49; p b 0.001) and for women the results were 34% versus 25% (OR: 1.55, 95% CI 1.39 to 1.74; p b 0.001). There was a linear trend between BP and socio-economic background. Generally, SBP and DBP decreased as socio-economic backgrounds increased from low (133 ± 18/80 ± 13 mm Hg), middle (131 ± 18/79± 12 mm Hg) and high (129± 18/79 ± 12 mm Hg), p b 0.001. Between group comparisons showed significant differences in SBP for all three socio-economic backgrounds. Alternatively, there was a difference in DBP between high and both medium and low socio-economic backgrounds but no difference between the
medium and low socio-economic groups. As a result, there was a clear gradient in the proportion of individuals with elevated BP ≥140/90 mm Hg according to socio-economic background (low: 39%, medium: 34%, and high: 30%). 3.4. Independent correlates of elevated BP Table 2 shows the independent correlates of the different forms of elevated BP in all subjects according to treatment status. Overall, the variables analysed in the composite models predicted 59 to 84% of individuals with elevated BP. While socio-economic status was not retained in the various models, both age and gender were consistently found to influence BP status, with older individuals and men more likely to have a higher BP. Adjusting for potential confounders, participants living in the ACT were less likely (adjusted OR 0.36 to 0.62 depending on the category of BP, refer Table 2) to record a higher BP than those living in Tasmania whereas regional residents were more likely (adjusted OR 1.28 to 1.41, see Table 2) compared to their city counterparts. Gradients of increased risk associated with weight gain (BMI being more predictive than waist circumference), lower education status and number of modifiable risk factors were also observed, particularly in respect to any form of elevated BP. Treated (for underlying HT) individuals were more likely to have higher SBP or both higher SBP and DBP but there was no difference between those prescribed mono or combination anti-hypertensive therapy (refer Table 2). Alternatively, those with pre-existing CVD (adjusted OR 0.60 to 0.90) and/or diabetes (adjusted OR 0.39 to 0.68) were less likely overall to record a higher BP (see Table 2). 3.5. National projections of elevated BP and obesity in Australian adults Compared to the Australian population which comprises around 18% of middle income earners [10], our study had more individuals from this group (according to median household income of $800 to $1199/week). Middle-aged women were overrepresented and adults aged b35 years were slightly under-represented (refer Fig. 1 inset). Weighted projections indicated that based on the BP profile of study participants, around 5 million Australians (33%) potentially have elevated BP at this point in time. The worst case scenario suggests that 5.5 million Australians (36%) may have elevated BP. Alternatively, the best case scenario suggests a figure of 4.7 million Australians (31%). Our projections also suggest that approximately 5.8 million (39%) and 3.9 million (26%) Australian adults are overweight or obese, respectively. The best and worst case scenario indicated a range of 5.5 to 6.25 million overweight (36 to 41%) and 3.5 to 4.3 million obese (24 to 29%) individuals.
4. Discussion In the largest study of its kind in Australia, in a single day using a standardized protocol and equipment [13], we examined BP in close to 14,000 adults in 100 locations from every state and territory. Overall, we found that one in three (34%) participants recorded an elevated BP. This figure rose to 44% if individuals with a history of HT, but normotensive at the time, were included. There were key differentials in BP levels; older individuals, men (42% versus 27% of women), regional (40%) compared to metropolitan (32%) individuals and people from lower socio-economic backgrounds had higher BP. Both men and women living in regional locations had higher BP compared to their metropolitan counterparts. In total, 30% of subjects
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Table 2 Risk factors associated with elevated BP according to treatment for HT. Treated for HT Demographic profile Age Female versus male
Not treated for HT
Systolic HT
Diastolic HT
1.02†† (1.01 to 1.03) 0.72†† (0.60 to 0.86)
0.96†† (0.96 to 0.97) 0.73† (0.59 to 0.91)
Systolic HT
Diastolic HT
Elevated BP
Systolic HT
Diastolic HT
Elevated BP
0.75† (0.63 to 0.90)
1.03†† (1.02 to 1.03) 0.38†† (0.35 to 0.42)
1.02†† (1.01 to 1.02) 0.52†† (0.47 to 0.59)
1.03†† (1.02 to 1.03) 0.41†† (0.37 to 0.45)
1.03†† (1.02 to 1.03) 0.45†† (0.41 to 0.50)
1.01†† (1.01 to 1.01) 0.56†† (0.51 to 0.61)
1.02†† (1.02 to 1.02) 0.44†† (0.40 to 0.48)
1.03 (0.79 to 1.34) 0.90 (0.68 to 1.18) 0.83 (0.64 to 1.09)
1.00 (0.82 to 1.23) 0.82 (0.65 to 1.02) 0.80* (0.65 to 0.99)
1.44† (1.13 to 1.83) 1.45† (1.12 to 1.85) 1.56†† (1.22 to 2.01)
1.03 (0.85 to 1.26) 0.88 (0.71 to 1.02) 0.85 (0.69 to 1.05)
Education: Primary versus: Secondary education
1.02 (0.78 to 1.33) 0.84 (0.63 to 1.11) 0.80 (0.61 to 1.05)
TAFE/trade school Higher education
Location State: ACT versus Tasmania Regional versus metropolitan
1.30† (1.07 to 1.58)
1.22* (1.01 to 1.48)
Risk factor profile BMI: Normal versus overweight Normal versus obese Waist circumference: Normal versus overweight Normal versus obese Modifiable risk factors
1.02†† (1.01 to 1.02) 1.31 (0.94 to 1.83) 1.76†† (1.31 to 2.36) 1.06 (0.96 to 1.18)
Medical history Diabetes CVD
1.02†† (1.01 to 1.02) 0.88 (0.58 to 1.33) 1.45* (1.03 to 2.05)
All cases
Elevated BP
0.36† (0.20 to 0.64) 1.41†† (1.25 to 1.59)
0.59 (0.33 to 1.06) 1.30†† (1.14 to 1.49)
0.39†† (0.23 to 0.65) 1.38†† (1.23 to 1.54)
0.36†† (0.22 to 0.61) 1.36†† (1.23 to 1.51)
0.62 (0.37 to 1.02) 1.28†† (1.14 to 1.43)
0.42†† (0.27 to 0.66) 1.32†† (1.19 to 1.45)
1.07†† (1.06 to 1.08) 1.76†† (1.55 to 1.99) 2.52†† (2.19 to 2.90)
1.06†† (1.05 to 1.08) 1.62†† (1.40 to 1.87) 2.36†† (2.01 to 2.76)
1.07†† (1.06 to 1.08) 1.72†† (1.54 to 1.93) 2.39†† (2.10 to 2.73)
1.06†† (1.05 to 1.07) 1.61†† (1.41 to 1.83) 2.21†† (1.93 to 2.54)
1.38†† (1.29 to 1.47)
1.40†† (1.30 to 1.51)
1.37†† (1.28 to 1.46)
1.05†† (1.03 to 1.06) 1.48†† (1.30 to 1.68) 1.81†† (1.54 to 2.13) 1.01†† (1.00 to 1.01) 1.16† (1.01 to 1.34) 1.43†† (1.23 to 1.66) 1.28†† (1.21 to 1.35)
1.05†† (1.04 to 1.06) 1.47†† (1.30 to 1.65) 1.77†† (1.52 to 2.06) 1.01† (1.00 to 1.01) 1.14* (1.10 to 1.30) 1.39†† (1.21 to 1.60) 1.28†† (1.21 to 1.35)
0.39†† (0.30 to 0.52) 0.72† (0.57 to 0.91)
0.49†† (0.39 to 0.60) 0.86 (0.72 to 1.03)
0.68†† (0.57 to 0.81) 0.72†† (0.63 to 0.83) 1.24† (1.10 to 1.41)
0.43†† (0.35 to 0.53) 0.67†† (0.57 to 0.78)
0.63†† (0.54 to 0.75) 0.69†† (0.60 to 0.79) 1.28†† (1.13 to 1.44)
84
72
73
83
69
1.02†† (1.01 to 1.03) 1.14 (0.83 to 1.56) 1.74†† (1.33 to 2.29)
0.60†† (0.49 to 0.73)
0.62† (0.45 to 0.86) 0.70† (0.54 to 0.90)
0.63†† (0.52 to 0.75)
0.51†† (0.41 to 0.64) 0.90 (0.75 to 1.09)
60
78
59
76
Anti-hypertensive treatment Overall % of cases correctly predicted by model
1.32†† (1.25 to 1.40)
*p b 0.05; †p b 0.01; ††p b 0.001.
were unaware that they had elevated BP and 50% being treated for known HT were not meeting their BP treatment targets. Increasing age, higher BMI, male gender, living in regional locations and established CVD or diabetes were consistently found to influence BP levels. If truly reflective of the BP profile of all Australian adults, these data suggest that after a period of declining BP at the population level during the 1980s to 1990s [5–8], BP levels have returned to alarming heights in the 21st Century. At the international level, this result is consistent with an increasing prevalence of HT. For example, in the United States of America, HT is also reported to affect one in three adults [16], while in Sub-Saharan Africa, the prevalence of HT is 30 to 40% in rural and urban communities, respectively [17]. The temptation to highlight a one dimensional headline figure of elevated BP (i.e. “one in three affected adults”) has the potential to over-shadow the considerable variety and complexity of BP values revealed within study participants. Beyond the well-known influence of age, sex, and risk factor status (including weight profile and a past history of HT), this study revealed considerable heterogeneity in BP values subject to a participant's socio-economic status (reflected by differences according to indicative income and educational status) and geographic location (according to state/territory and metropolitan/regional areas). In regional locations of Australia where health resources are most scarce [11], participants were more likely to have a higher BP. The level of elevated
BP of 40% in regional locations in our survey was below comparable data from urban and rural Australia [18,19]. Higher BP in regional Australia was paralleled by an increase in obesity. Expanding waistlines coupled with an increasingly older population and a migration towards regional centres are likely to fuel an increasing burden of HT in Australia, placing greater demands on regional and remote health care systems. The need to develop innovative models of care and equitable access to health care that overcomes individual and societal barriers to intensive and effective primary and secondary prevention strategies will assume increasing importance in this context. In addition to the broad patterns observed in this study, we found that elevated BP in Australia, the greatest modifiable contributor to the burden of disease from CVD [3], remains largely undetected and uncontrolled. For example, apart from the one in three subjects who were unaware that they had elevated BP, an additional one in two being treated for known HT were not meeting their BP treatment targets. Combating the increase in elevated BP levels requires a renewed and multifaceted response for the detection, treatment and prevention of high BP from individuals, medical professionals, government and the food industry alike, particularly at a time when BP targets are being lowered. Widespread media education and awareness campaigns about the dangers of elevated BP in addition to risk assessment
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programs for early detection of high BP are required to address the key drivers of HT. With a universal health system that provides free or discounted health care and subsidised pharmaceutical therapy in Australia, there is an avenue to achieve these ends. Failure to attain treatment targets belies the expanding armoury to significantly lower BP levels; pharmacological agents, either as mono or combination therapy, as well as lifestyle modifications such as salt reduction, reduced alcohol consumption and exercise [4,20], are all part of a broad array of effective therapeutic strategies and guidelines whose application needs to be maximised. Not addressing potential escalations in BP levels, particularly in high risk individuals and communities, will have dramatic consequences for the future heart health of Australia. For example, each increment of 20 mm Hg in SBP and 10 mm Hg in DBP doubles the risk of CVD across the entire BP range for individuals aged 40–70 years [20]. Even borderline risk factors increase the risk of coronary artery disease within 10 years while a combination of risk factors compounds this risk [21]. Given that participants in this study were self-selected (rather than subject to random purposeful sampling) and we focussed on an assessment at a single point in time, a key question is how representative of the Australian population are these data? A number of previous studies in Australia, all with their own strengths and weaknesses, provide broad support for our findings in respect to elevated BP values and expanded waistlines. The most salient of these is the AusDiab population cohort study [22], with original screening of 11,247 subjects aged over 25 years from 42 Census collector districts in 7 strata (states and territories) in 1999/2000, and a follow-up study of 6537 physical assessments in these subjects in 2004–05; participation rates being 55% and 32% respectively of the original targeted cohort. In the original study [8], the overall prevalence of HT, defined as SBP ≥ 140 mm Hg and/or DBP ≥ 90 mm Hg, or self-reported use of anti-hypertensive drugs, was 29% (95% CI 25 to 32%) increasing to 35% (95% CI 34 to 36%) in the follow-up study. While it is possible that BP measured in this environment may overestimate BP levels, those who had high BP under these relatively controlled circumstances are likely to have high BP in daily life. Further, they may indeed be at higher risk for CVD (as with “white coat hypertensive” individuals) than those who remain normotensive. In view of the positive association between weight and BP in this survey, it is worth noting that that the weight profile of our participants and the subsequent national projections are highly consistent with a contemporary population-based survey of the risk profile of Australians [9]. Compared to our projections of 39% overweight and 26% obese, the latest national survey had similar figures of 37% and 25%, respectively. Moreover, both studies support that overweight and obesity is highest in 65–74 year old men (79%) and 55–64 year old women (68%) [9]. Indeed our estimated prevalence of obesity within the Australian adult population (26%) is also the same found in similar but more rigorous studies in New Zealand [23]. These data also provide a sobering reminder of the likely impact of increasing weight around the globe (with obese individuals at an almost two-fold likelihood to record a higher BP) on both elevated BP levels and preventable cardiovascular events in the longer term [24]. This study has a number of important limitations that influence any interpretation of our findings. Firstly, despite the size and distribution of participants, this was a self-selected group in whom inherent biases were likely. At the very least, while self-selection may have led to more participants with something to gain by having a BP check, most individuals presented to the screening booth without knowledge of its purpose. Furthermore, given the relative lack of CVDrelated awareness and that no prior advertising was done, participant bias may be less of an issue than anticipated. Certainly, we acknowledge that the interpretation of these data was strongest where within study group comparisons were made yet weaker when extrapolated to the wider Australian population. Despite this study being unique in
its methodology, contemporary population-based surveys (as discussed above) [9] that applied a standardized and direct (compared to self-report) approach to data acquisition and a broad geographical basis verify our extrapolations to the Australian population. Past history was dependent on self-report and BP measurements were obtained in a single session, therefore we could not confirm medical histories nor the presence of HT or the accuracy of BP values, even within the normal range. Furthermore, prior to taking BP measurements, we did not control for stimulants such as recent caffeine consumption or nicotine from smoking. The study team closely monitored 10% of sites for quality control but could not attend all 100 geographically dispersed sites. We do not believe that this was problematic for the data however since the screening was undertaken by trained Registered Nurses who followed a standardized protocol and used validated equipment [13]. The impact of external climatic differences across the continent may reflect some heterogeneity observed in these data, despite the testing being conducted indoors at all sites. This represents the largest study of its kind in Australia with key findings that have broad clinical and public health implications at the national and international levels. From an Australian perspective, these data provide strong evidence that elevated BP is still a major health problem within an ageing adult population in whom obesity and related metabolic disorders are becoming increasingly prevalent. The likely consequences on future cardiac, renal and neurological events is likely to be profound, particularly in vulnerable communities where health care resources are scarce and lower socio-economic conditions are more common. At the broader level, these data support the need for regular large-scale national surveys using random samples and standardized methodology so that changes in risk factor prevalence can be detected and addressed before they impact on morbidity and mortality. As a readily detectable, and in many cases modifiable, risk factor that contributes most to avoidable CVD-related events, elevated BP represents a key target for renewed prevention strategies in Australia and beyond. Acknowledgement We gratefully acknowledge Mr. Neil Covey for co-ordinating the National Blood Pressure Screening Day. We thank the nurses for carrying out the survey and Traffik Marketing for organising the screening booths, their distribution across Australia and the return of the study data. MJC and SS are supported by the National Health and Medical Research Council of Australia (NHMRC). The authors of this manuscript have certified that they comply with the Principles of Ethical Publishing in the International Journal of Cardiology [25]. References [1] Lopez AD, Mathers CD, Ezzati M, Jamison DT, C.J.L M.. Measuring the global burden of disease and risk factors, 1990–2001. In: Lopez AD, Mathers CD, Ezzati M, Jamison DT, C.J.L M, editors. Global burden of disease and risk factors. New York: Oxford University Press; 2006. p. 1–13. [2] Begg S, Vos T, Barker B, Stevenson C, Stanley L, Lopez AD. The burden of disease and injury in Australia 2003: Australian Institute of Health and Welfare. AIHW cat. no. PHE 82; 2007. [3] Australian Institute of Health and Welfare. Australia's health 2006. Canberra, ACT, Australia: AIHW cat. no. AUS 73; 2006. [4] National Heart Foundation of Australia (National Blood Pressure and Vascular Disease Advisory Committee). Guide to management of hypertension; 2008. [5] Australian Bureau of Statistics. National Nutrition Survey 1995: nutrient intakes and physical measurements. Canberra, ACT, Australia: ABS cat. no. 4805.0; 1998. [6] Barr ELM, Magliano DJ, Zimmet PZ, et al. AusDiab 2005: the Australian Diabetes, Obesity and Lifestyle Study. Melbourne: International Diabetes Institute; 2006. [7] Bennett SA, Magnus P. Trends in cardiovascular risk factors in Australia. Results from the National Heart Foundation's Risk Factor Prevalence Study, 1980–1989. Med J Aust 1994;161(9):519–27. [8] Briganti EM, Shaw JE, Chadban SJ, et al. Untreated hypertension among Australian adults: the 1999–2000 Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Med J Aust 2003;179(3):135–9.
M.J. Carrington et al. / International Journal of Cardiology 145 (2010) 461–467 [9] Australian Bureau of Statistics. National Health Survey: summary of results. Canberra, ACT, Australia: ABS cat. no. 4364.0; 2007–08. [10] Australian Bureau of Statistics. 2006 Census Data Pack: data and geographic boundaries from the 2006 census of population and housing. Canberra, ACT, Australia: ABS cat. no. 2069.0.30.001; 2006. [11] Clark RA, Driscoll A, Nottage J, et al. Inequitable provision of optimal services for patients with chronic heart failure: a national geo-mapping study. Med J Aust 2007;186(4):169–73. [12] World Health Organization. The STEPwise approach to surveillance (STEPS) manual. April 2006 ed: World Health Organization; 2006. [13] Rogoza AN, Pavlova TS, Sergeeva MV. Validation of A&D UA-767 device for the selfmeasurement of blood pressure. Blood Press Monit 2000;5(4):227–31. [14] National Health and Medical Research Council. Dietary Guidelines for Australian Adults. Canberra, ACT, Australia: NHMRC; 2003. [15] Dalton M, Cameron AJ, Zimmet PZ, et al. Waist circumference, waist–hip ratio and body mass index and their correlation with cardiovascular disease risk factors in Australian adults. J Intern Med 2003;254(6):555–63. [16] Lloyd-Jones D, Adams R, Carnethon M, et al. Heart Disease and Stroke Statistics— 2009 update. A report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation 2008;119(3):e21–181. [17] Addo J, Smeeth L, Leon DA. Hypertension in sub-Saharan Africa: a systematic review. Hypertension 2007;50(6):1012–8.
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[18] Chua B, Rochtchina E, Mitchell P. Temporal changes in the control of blood pressure in an older Australian population. J Hum Hypertens 2005;19(9):691–6. [19] Janus ED, Bunker SJ, Kilkkinen A, et al. Prevalence, detection and drug treatment of hypertension in a rural Australian population: the Greater Green Triangle Risk Factor Study 2004–2006. Intern Med J 2008;38(12):879–86. [20] Chobanian AV, Bakris GL, Black HR, et al. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA 2003;289(19):2560–72. [21] Vasan RS, Sullivan LM, Wilson PW, et al. Relative importance of borderline and elevated levels of coronary heart disease risk factors. Ann Intern Med 2005;142 (6):393–402. [22] Dunstan DW, Zimmet PZ, Welborn TA, et al. The Australian Diabetes, Obesity and Lifestyle Study (AusDiab)—methods and response rates. Diabetes Res Clin Pract 2002;57(2):119–29. [23] Ministry of Health. A portrait of health: key results of the 2006/07 New Zealand Health Survey. http://www.moh.govt.nz/moh.nsf/indexmh/portrait-of-health (accessed 1 December 2008). [24] Murphy NF, MacIntyre K, Stewart S, Hart CL, Hole D, McMurray JJ. Long-term cardiovascular consequences of obesity: 20-year follow-up of more than 15 000 middle-aged men and women (the Renfrew–Paisley study). Eur Heart J 2006;27 (1):96–106. [25] Coats AJ. Ethical authorship and publishing. Int J Cardiol 2009;131(2):149–50.
Contents lists available at ScienceDirect
International Journal of Cardiology j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / i j c a r d
Pattern of blood pressure in Australian adults: Results from a National Blood Pressure Screening Day of 13,825 adults☆ Melinda J. Carrington, Garry L. Jennings, Simon Stewart ⁎ Baker IDI Heart and Diabetes Institute, Melbourne, Australia
a r t i c l e
i n f o
Article history: Received 2 June 2009 Accepted 3 June 2009 Available online 1 July 2009 Keywords: Blood pressure measurement and monitoring Hypertension detection and control Cardiovascular disease Population Obesity Socio-economic status
a b s t r a c t Background: Recent national data of cardiovascular disease (CVD) risk factors in Australia are limited. Therefore this study sought to gain a contemporary snapshot of the blood pressure (BP) profile of Australian adults. Methods: We established 100 metropolitan and regional screening sites. Using a standardized protocol and the same automated, validated BP monitor, Registered Nurses recorded the BP and other risk factors for CVD of self-selected volunteers on a single day. Results: A total of 13,825 subjects (55% female, aged 48 ± 16 years) were assessed. Mean systolic and diastolic BP was 131 ± 18 and 79 ± 12 mm Hg. Overall, 34% had an elevated BP while 10% being treated for hypertension (HT) were normotensive (combined total 44%). Elevated BP was more common in older individuals, men (42% versus 27% of women), regional dwelling residents (40% versus 32% of metropolitan) and people from lower socio-economic backgrounds (39% versus 30% of higher). Overall, 50% of subjects with a history of HT had elevated BP compared to 30% without a history of HT. Adjusting for age and sex, elevated BP was independently associated with obesity (OR: 1.77, 95% CI 1.52–2.06), regional location (OR: 1.32, 95% CI 1.19–1.45) and modifiable risk factors (OR: 1.28, 95% CI 1.21–1.35); those being treated for CVD or diabetes are less likely to have high BP. Conclusions: In the largest study of its kind in Australia, the findings highlight the need for continued vigilance to detect, monitor and prevent elevated BP within an ageing population in whom metabolic disorders are becoming more frequent. Crown Copyright © 2009 Published by Elsevier Ireland Ltd. All rights reserved.
1. Introduction As a key contributor to the global increase in cardiovascular disease (CVD), high blood pressure (BP) is a readily detectable and modifiable condition that represents a major target for primary and secondary prevention programs. In 2001, high BP or hypertension (HT) was estimated to contribute to 7.6 million deaths (13.5% of total deaths) and 92 million disability-adjusted life years globally [1]. In Australia, it was the largest contributor to CVD in 2003 and explained 42% of CVD burden (7.6% of total disease burden) [2]. It is also the most commonly managed cardiovascular risk factor by primary care physicians in Australia, accounting for nine in every 100 encounters (three times that of lipid disorder management) [3]. Elevated BP seems to have re-emerged with an even greater effect on premature mortality and disability [3] and despite the availability
☆ Sources of support: The National Blood Pressure Screening Day was independently designed and analysed by Baker IDI Heart and Diabetes Institute and generously supported by Schering Plough Pty. Limited. Simon Stewart and Melinda Carrington are supported by the National Health and Medical Research Council of Australia. ⁎ Corresponding author. PO Box 6492, St Kilda Rd Central, Melbourne Vic 8008, Australia. Tel.: +61 3 8532 1640, 0438 302 111 (mobile); fax: +61 3 8532 1100. E-mail address: [email protected] (S. Stewart).
of effective pharmacological treatments [4]. During the 1980s, the prevalence of high BP in Australia reportedly declined from 38% to 26% but steadily rose again in the 1990s and early 21st Century [5–8]. The population is ageing and rates of obesity and metabolic disorders are rising [9] which may contribute to increasing rates of HT. Australia has also experienced significant socio-demographic changes, including the overall ageing of the post-war “baby boomer” generation and widening differentials in the socio-economic status of the population, particularly metropolitan versus regional/rural communities. In Australia, regional and remote populations comprise around 32% of the 15 million adult population aged over 18 years [10]. We undertook a National Blood Pressure Screening Day to gain a contemporary “snapshot” of the BP profile of adult Australians. A key objective was to explore differences according to age, sex, geographic location, treatment for those known to have HT and socio-economic status. A secondary aim was to project the prevalence of elevated BP and obesity in adult Australians. 2. Materials and methods 2.1. Participants A total of 13,825 participants were recruited. This equates to one in every 1000 adult Australians (see Fig. 1 for a profile of the Australian population). People were offered a
0167-5273/$ – see front matter. Crown Copyright © 2009 Published by Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.ijcard.2009.06.003
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Fig. 1. Location of BP screening sites in metropolitan and regional areas across Australia. © Commonwealth of Australia, Geoscience Australia. Demographic profile of adult Australians based on the latest Census of the population [10].
free BP check if they walked by any of the 100 screening stations distributed throughout Australia on a single day (Saturday 30th June 2007). A weekend day was chosen to allow for a broader mix of age groups and to include members of the workforce as well as nonworking adults. On this day, invitation to participate was through a combination of prominent advertising signs, a short written leaflet distributed adjacent to the screening booth and by verbal invitation. There was no prior advertising to announce the locations or publicizing that free BP checks were conducted. Based on prior market research, we estimated that approximately 250,000 Australians (approximately one in 10 adults) would come into contact with a screening station. The only inclusion criteria were to be 18 years of age or above and the ability to provide verbal consent to participate. Participants were otherwise self-selected. 2.2. Design We undertook a cross-sectional survey of the BP profile of Australian adults on a single day. In order to capture as broad and large a sample as possible, we used Geographical Information System profiling of the distribution of the Australian population [11] to identify all population centres with N 20,000 people in every state and territory. A dedicated screening station was erected at each site and staff allocated for every 250,000 people within major metropolitan centres and for N 20,000 people within regional centres. Screening stations were distributed in locations with a high concentration of people (predominantly large shopping/leisure precincts). This amounted to 74 metropolitan screening locations and 26 regional screening locations. Fig. 1 shows the distribution of these 100 screening stations spanning all six states and two territories in Australia. Stations were specially designed for privacy and comfort and included four independent screening booths, an in-built height measure and standardized equipment. Screening was undertaken by a team of 300 Registered Nurses who followed a detailed written protocol to ensure the standard acquisition of the study data. Stations were operational between 0900 and 1600 on the screening day, with a maximal
capacity of approximately 150 participants per station. The study was approved by the Human Research Ethics Committee at The Alfred Hospital, Melbourne, Australia. 2.3. Data collection Screening comprised two simple components; a self-administered questionnaire and physical measurements. The self-administered questionnaire was a one-page 16item survey that collected: 1) brief socio-demographic details (age, gender, postcode of residence, and ethnicity); 2) current risk factors for and prior history of CVD; 3) BP management and control by individuals and their general practitioner (GP) and; 4) personal perceptions about high BP as a risk for CVD. Socio-economic status was determined using the official Australian Bureau of Statistics 2006 Census data on median household income according to an individual's postcode of residence [10]. After completion of the survey, a brief physical assessment was conducted by a Registered Nurse in accordance with standardized procedures advocated by the National Heart Foundation of Australia for BP [4] and the World Health Organization (WHO) STEPwise approach to surveillance (STEPS) procedure for waist and hip circumference [12]. BP was measured in the sitting position using an appropriately sized cuff and validated digital BP monitor (Model UA-767, A&D Mercury Pty. Ltd., SA, Australia) [13] after an initial rest period of 5 min. With the arm supported by a table at heart level, two measurements separated by a one-minute interval were taken; the average of these two readings was analysed provided that there was no discrepancy in systolic blood pressure (SBP) of ≥10 mm Hg or ≥7 mm Hg in diastolic blood pressure (DBP). These thresholds were adapted from prior survey methods [5] and where a discrepancy in the two readings occurred, only the second reading was selected for analyses. Participants received an educational brochure about BP and its importance for CVD. They were also provided with a record card that noted the higher of their two BP measurements, with follow-up advice to either consult their GP (for high risk individuals with elevated BP, as defined by SBP ≥ 140 mm Hg and/or DBP ≥ 90 mm Hg) or to continue having regular BP check-ups (for people with BP below these cut-offs).
M.J. Carrington et al. / International Journal of Cardiology 145 (2010) 461–467 Measurements of height and weight for calculation of body mass index (BMI, kg/m2) were performed using a linear height scale imprinted on the rear wall of the screening stations and digital weighing scales. Before being weighed, participants removed their shoes and heavy garments and as in previous population surveys [7], 1 kg in weight was subtracted to prevent overestimation due to clothing. Participants were classified by BMI as normal weight (b 25 kg/m2), overweight (25 to b 30 kg/m2) and obese (≥ 30 kg/m2) according to the National Health and Medical Research Council classifications [14]. Waist circumference was measured while standing at a level midway between the lowest rib and iliac crest, measured in the horizontal plane at the end of a gentle expiration. Men and women respectively were classified by waist circumference as overweight for measurements between 94 to b 101.9 cm and 80 to b 87.9 cm, and as obese for measurements ≥ 102 cm for men and ≥ 88 cm for women, similar to previous studies in the literature [6,15]. Normal weight was classified by a waist circumference b 94 cm for men and b80 cm for women.
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household income by postcode of residence were non-Gaussian distributed, individuals were categorized into low (median household income $1 to $799/week), middle ($800 to $1199/week) and high ($1200 to N$3000/week) socio-economic backgrounds. To identify the independent correlates of elevated BP (SBP, DBP and combined HT) according to treatment status (expressed as adjusted OR with 95% CIs), all variables were subject to backward, step-wise multiple logistic regression analyses with retention of variables in each step at the level of p b 0.1. BMI and waist circumference were initially analysed as continuous variables and subsequently as categorical variables. Statistical significance for all tests was established at p b 0.05. To estimate the potential BP and weight profile of adult Australians based on the findings of this survey, we used data from the most recent Census of the population [10]. As such, age and sex projections using the observed proportions and 95% CIs within each discrete age group for men and women separately were derived for the current demographic profile of Australia. 3. Results
2.4. Data analyses Data were analysed for men and women separately and where appropriate, on an age-specific basis. Normally distributed continuous data are presented as the mean ± SD and discrete data as counts and percentage. Age and sex-adjusted comparisons of BP and other study data were analysed on the basis of regional versus metropolitan residence. Categorical variables were compared using χ2 tests with the calculation of odds ratios (OR) and 95% confidence intervals (CI). Normally distributed continuous variables were compared using Student's t-test and analysis of variance with post-hoc Dunnett's test for between group comparisons where appropriate. As the data classifying median
A total of 13,825 completed profiles were verified from 99 screening stations. Table 1 summarises the socio-demographic and clinical profile according to gender and locality. Overall, 7666 (55%) were women with an average age of 48.7 ± 15.8 years and 48.0 ± 16.2 years for men. Participants were predominantly Caucasian/European (86%) and one in ten was Asian. Based on the median household income for their residential postcode, the majority of participants were from middle socio-economic backgrounds (59%), with a similar proportion of low (20%) and high (21%) in the remainder of the group. A total of 10,649 (77%) subjects were from metropolitan areas and 3176 (23%) were from regional Australia.
Table 1 Socio-demographic and clinical profile of participants.
Socio-demographic profile Age (years) Ethnicity: Caucasian Asian ATSI Other Education Primary education Secondary education TAFE/trade school Higher education Median household income (per week): $1 to $799 $800 to $1199 $1200 to N $3000 Clinical profile SBP (mm Hg) DBP (mm Hg) BMI (kg/m2) Normal Overweight Obese Waist circumference (cm) Normal Overweight Obese Pulse rate (bpm) Smokers Anti-hypertensive therapy ACE ARB CCB Diuretic BB History hypertension History diabetes History CVD Family history of CVD Number of modifiable risk factors for CVD: None One Two Three or more
Male
Female
Metropolitan
Regional
Total
N = 6159 (45%)
N = 7666 (55%)
N = 10,649 (77%)
N = 3176 (23%)
N = 13,825
48.0 ± 15.8
48.7 ± 15.8*
47.9 ± 15.9
50.1 ± 16.0††
48.4 ± 16.0
5246 (38%) 598 (4%) 80 (0.5%) 235 (1.5%)
6581 (48%)* 776 (6%) 101 (0.5%) 208 (1.5%)
8838 (64%) 1305 (9%) 91 (0.5%) 415 (3%)
2989 (22%)†† 69 (1%) 90 (0.5%) 28 (0.2%)
11,827 (86%) 1374 (10%) 181 (1%) 443 (3%)
296 (5%) 2157 (35%) 1280 (21%) 2357 (39%)
375 (5%)†† 3351 (44%) 1133 (15%) 2705 (36%)
502 (5%) 3995 (38%) 1794 (17%) 4226 (40%)
169 (5%)†† 1513 (48%) 619 (20%) 836 (27%)
671 (5%) 5508 (40%) 2413 (18%) 5062 (37%)
1183 (20%) 3440 (58%) 1325 (22%)
1475 (20%) 4402 (59%) 1538 (21%)
1602 (16%) 5934 (58%) 2730 (26%)
1056 (34%)†† 1908 (62%) 133 (4%)
2658 (20%) 7842 (59%) 2863 (21%)
136 ± 17 81 ± 12 27.8 ± 4.5 1557 (26%) 2826 (47%) 1601 (27%) 99.1 ± 12.9 1948 (33%) 1530 (26%) 2375 (41%) 76 ± 13 925 (15%) 1016 (18%) 442 (8%) 296 (5%) 181 (3%) 125 (2%) 315 (6%) 1571 (27%) 538 (9%) 744 (12%) 1231 (21%)
127 ± 18†† 78 ± 12†† 27.2 ± 5.8†† 3001 (41%)†† 2374 (32%) 3612 (27%) 90.5 ± 15.4†† 1901 (26%) 1469 (20%) 3885 (54%) 78 ± 12†† 934 (12%)†† 1317 (19%) 468 (7%)* 413 (6%) 212 (3%) 221 (3%)† 349 (5%) 2087 (28%)* 596 (8%)* 947 (13%) 2100 (28%)††
130 ± 18 79 ± 12 27.3 ± 5.1 3652 (35%) 4050 (39%) 2624 (25%) 93.7 ± 14.9 3144 (31%) 2377 (24%) 4597 (45%) 77 ± 13 1419 (14%) 1660 (17%) 627 (6%) 522 (5%) 274 (3%) 239 (2%) 474 (5%) 2734 (27%) 869 (8%) 1210 (12%) 2464 (24%)
134 ± 18†† 80 ± 12†† 28.2 ± 5.6†† 906 (30%)†† 1150 (38%) 988 (32%) 96.4 ± 15.0†† 705 (24%)†† 622 (21%) 1663 (55%) 77 ± 13 440 (14%) 673 (23%)†† 283 (10%)†† 187 (6%)* 119 (4%)† 107 (4%)† 190 (6%)†† 924 (30%)†† 265 (9%) 481 (15%)†† 867 (28%)††
131 ± 18 79 ± 12 27.5 ± 5.3 4558 (34%) 5200 (39%) 3612 (27%) 94.4 ± 15.0 3849 (29%) 2999 (23%) 6260 (48%) 77 ± 13 1859 (14%) 2333 (18%) 910 (7%) 709 (6%) 393 (3%) 346 (3%) 664 (5%) 3658 (28%) 1134 (8%) 1691 (12%) 3331 (25%)
3089 (52%) 1695 (28%) 782 (13%) 400 (7%)
3331 (45%)†† 2435 (33%) 1147 (15%) 550 (7%)
5018 (49%) 3174 (31%) 1444 (14%) 701 (6%)
1402 (45%)† 956 (31%) 485 (16%) 249 (8%)
6420 (48%) 4130 (31%) 1929 (14%) 950 (7%)
ATSI: Aboriginal and Torres Strait Islander; SBP: systolic blood pressure; DBP: diastolic blood pressure; BMI: body mass index; ACE: angiotensin-converting enzyme inhibitor; ARB: angiotensin II receptor blocker; CCB: calcium channel blocker; BB: beta blocker; CVD: cardiovascular disease; mm Hg: millimetres of mercury; bpm: beats per minute. *pb 0.05; †pb 0.01; ††pb 0.001.
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Fig. 2. A. SBP levels across age. B. DBP levels across age. C. Pulse pressure across age. SBP: systolic blood pressure; DBP: diastolic blood pressure; mm Hg: millimetres of mercury. Values are the mean ± SEM, n = 13,825.
There was a normal distribution of SBP and DBP. On average, SBP was 131 ± 18 and DBP was 79 ± 12 (Table 1). Fig. 2a to c, respectively shows that while mean SBP increased with advancing age, DBP increased up until the mid 60s before decreasing thereafter, resulting in a widening pulse pressure. The sample was on average overweight with a mean BMI of 27.5 ± 5.3 kg/m2 (27.8 ± 4.5 kg/m2 men versus 27.2 ± 5.8 kg/m2 women) and waist circumference of 99.1 ± 12.9 cm for men and 90.5 ± 15.4 cm for women. In total, 39% of participants were overweight and 27% were obese according to BMI criteria while 23% were overweight and 48% were obese as indicated by waist circumference. 3.1. Elevated BP levels Overall, 29% of individuals (n = 3920) had a SBP ≥140 mm Hg (36% men versus 22% women; OR 1.39, 95% CI 1.34 to 1.45) and 17% (n = 2317) had a DBP ≥90 mm Hg (21% men versus 14% women; OR 1.27, 95% CI 1.21 to 1.33); p b 0.001 for both comparisons. In total, 34% of subjects (n = 4677) had elevated BP ≥ 140 mm Hg and/or ≥90 mm Hg, with men having an increased likelihood compared to women (42% versus 27% respectively, OR 1.36, 95% CI 1.31 to 1.40; p b 0.001). According to the full WHO definition of HT (including normotensive individuals prescribed anti-hypertensive medication), this figure would increase to 44% (51% men versus 39% women; OR 1.26, 95% CI 1.22 to 1.30). 3.2. Treated versus non-treated BP profiles A total of 2333 subjects (18%) self-reported of being treated (with antihypertensive agents) for HT. Of these, 1160 (50%) had BP of ≥ 140/90 mm Hg. Average SBP did not differ according to mono versus combination anti-hypertensive therapy (138 ± 19 versus 139 ± 20 mm Hg, p N 0.05) whereas combination therapy was associated with a slightly lower DBP (79 ± 13 versus 81 ± 14 mm Hg; p b 0.001). A further 3106 (30%) subjects not taking anti-hypertensive therapy had elevated BP with an average SBP of 149 ± 14 mm Hg and DBP of 90 ±12 mm Hg. 3.3. High risk sub-groups Average BP levels varied significantly across each Australian state and territory (p b 0.001). The highest average BP and proportion of individuals with BP levels that exceeded 140/90 mm Hg, respectively, was in Tasmania (135 ± 18/81 ± 12 mm Hg and 45%). Similarly high values were recorded in the Northern Territory. The lowest values were recorded in the Australian Capital Territory (ACT) (126 ± 15/78 ±11 mm Hg and 26%). Mean BP levels were higher in regional (134 ± 18/80 ± 12 mm Hg) compared to metropolitan (130 ± 18/79 ± 12 mm Hg; p b 0.001) individuals. Overall, 40% versus 32% of regional and metropolitan dwelling subjects, respectively, had elevated BP (OR: 1.41, 95% CI 1.30 to 1.53; p b 0.001). This was evident for both men (138 ± 17/82 ± 12 versus 135 ± 17/81 ± 12 mm Hg) and women (131 ± 18/79 ± 12 versus 126 ± 18/77 ± 12 mm Hg) compared to their metropolitan counterparts. Overall, 47% versus 40% of regional compared to metropolitan dwelling men had elevated BP (OR: 1.32, 95% CI 1.17 to 1.49; p b 0.001) and for women the results were 34% versus 25% (OR: 1.55, 95% CI 1.39 to 1.74; p b 0.001). There was a linear trend between BP and socio-economic background. Generally, SBP and DBP decreased as socio-economic backgrounds increased from low (133 ± 18/80 ± 13 mm Hg), middle (131 ± 18/79± 12 mm Hg) and high (129± 18/79 ± 12 mm Hg), p b 0.001. Between group comparisons showed significant differences in SBP for all three socio-economic backgrounds. Alternatively, there was a difference in DBP between high and both medium and low socio-economic backgrounds but no difference between the
medium and low socio-economic groups. As a result, there was a clear gradient in the proportion of individuals with elevated BP ≥140/90 mm Hg according to socio-economic background (low: 39%, medium: 34%, and high: 30%). 3.4. Independent correlates of elevated BP Table 2 shows the independent correlates of the different forms of elevated BP in all subjects according to treatment status. Overall, the variables analysed in the composite models predicted 59 to 84% of individuals with elevated BP. While socio-economic status was not retained in the various models, both age and gender were consistently found to influence BP status, with older individuals and men more likely to have a higher BP. Adjusting for potential confounders, participants living in the ACT were less likely (adjusted OR 0.36 to 0.62 depending on the category of BP, refer Table 2) to record a higher BP than those living in Tasmania whereas regional residents were more likely (adjusted OR 1.28 to 1.41, see Table 2) compared to their city counterparts. Gradients of increased risk associated with weight gain (BMI being more predictive than waist circumference), lower education status and number of modifiable risk factors were also observed, particularly in respect to any form of elevated BP. Treated (for underlying HT) individuals were more likely to have higher SBP or both higher SBP and DBP but there was no difference between those prescribed mono or combination anti-hypertensive therapy (refer Table 2). Alternatively, those with pre-existing CVD (adjusted OR 0.60 to 0.90) and/or diabetes (adjusted OR 0.39 to 0.68) were less likely overall to record a higher BP (see Table 2). 3.5. National projections of elevated BP and obesity in Australian adults Compared to the Australian population which comprises around 18% of middle income earners [10], our study had more individuals from this group (according to median household income of $800 to $1199/week). Middle-aged women were overrepresented and adults aged b35 years were slightly under-represented (refer Fig. 1 inset). Weighted projections indicated that based on the BP profile of study participants, around 5 million Australians (33%) potentially have elevated BP at this point in time. The worst case scenario suggests that 5.5 million Australians (36%) may have elevated BP. Alternatively, the best case scenario suggests a figure of 4.7 million Australians (31%). Our projections also suggest that approximately 5.8 million (39%) and 3.9 million (26%) Australian adults are overweight or obese, respectively. The best and worst case scenario indicated a range of 5.5 to 6.25 million overweight (36 to 41%) and 3.5 to 4.3 million obese (24 to 29%) individuals.
4. Discussion In the largest study of its kind in Australia, in a single day using a standardized protocol and equipment [13], we examined BP in close to 14,000 adults in 100 locations from every state and territory. Overall, we found that one in three (34%) participants recorded an elevated BP. This figure rose to 44% if individuals with a history of HT, but normotensive at the time, were included. There were key differentials in BP levels; older individuals, men (42% versus 27% of women), regional (40%) compared to metropolitan (32%) individuals and people from lower socio-economic backgrounds had higher BP. Both men and women living in regional locations had higher BP compared to their metropolitan counterparts. In total, 30% of subjects
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Table 2 Risk factors associated with elevated BP according to treatment for HT. Treated for HT Demographic profile Age Female versus male
Not treated for HT
Systolic HT
Diastolic HT
1.02†† (1.01 to 1.03) 0.72†† (0.60 to 0.86)
0.96†† (0.96 to 0.97) 0.73† (0.59 to 0.91)
Systolic HT
Diastolic HT
Elevated BP
Systolic HT
Diastolic HT
Elevated BP
0.75† (0.63 to 0.90)
1.03†† (1.02 to 1.03) 0.38†† (0.35 to 0.42)
1.02†† (1.01 to 1.02) 0.52†† (0.47 to 0.59)
1.03†† (1.02 to 1.03) 0.41†† (0.37 to 0.45)
1.03†† (1.02 to 1.03) 0.45†† (0.41 to 0.50)
1.01†† (1.01 to 1.01) 0.56†† (0.51 to 0.61)
1.02†† (1.02 to 1.02) 0.44†† (0.40 to 0.48)
1.03 (0.79 to 1.34) 0.90 (0.68 to 1.18) 0.83 (0.64 to 1.09)
1.00 (0.82 to 1.23) 0.82 (0.65 to 1.02) 0.80* (0.65 to 0.99)
1.44† (1.13 to 1.83) 1.45† (1.12 to 1.85) 1.56†† (1.22 to 2.01)
1.03 (0.85 to 1.26) 0.88 (0.71 to 1.02) 0.85 (0.69 to 1.05)
Education: Primary versus: Secondary education
1.02 (0.78 to 1.33) 0.84 (0.63 to 1.11) 0.80 (0.61 to 1.05)
TAFE/trade school Higher education
Location State: ACT versus Tasmania Regional versus metropolitan
1.30† (1.07 to 1.58)
1.22* (1.01 to 1.48)
Risk factor profile BMI: Normal versus overweight Normal versus obese Waist circumference: Normal versus overweight Normal versus obese Modifiable risk factors
1.02†† (1.01 to 1.02) 1.31 (0.94 to 1.83) 1.76†† (1.31 to 2.36) 1.06 (0.96 to 1.18)
Medical history Diabetes CVD
1.02†† (1.01 to 1.02) 0.88 (0.58 to 1.33) 1.45* (1.03 to 2.05)
All cases
Elevated BP
0.36† (0.20 to 0.64) 1.41†† (1.25 to 1.59)
0.59 (0.33 to 1.06) 1.30†† (1.14 to 1.49)
0.39†† (0.23 to 0.65) 1.38†† (1.23 to 1.54)
0.36†† (0.22 to 0.61) 1.36†† (1.23 to 1.51)
0.62 (0.37 to 1.02) 1.28†† (1.14 to 1.43)
0.42†† (0.27 to 0.66) 1.32†† (1.19 to 1.45)
1.07†† (1.06 to 1.08) 1.76†† (1.55 to 1.99) 2.52†† (2.19 to 2.90)
1.06†† (1.05 to 1.08) 1.62†† (1.40 to 1.87) 2.36†† (2.01 to 2.76)
1.07†† (1.06 to 1.08) 1.72†† (1.54 to 1.93) 2.39†† (2.10 to 2.73)
1.06†† (1.05 to 1.07) 1.61†† (1.41 to 1.83) 2.21†† (1.93 to 2.54)
1.38†† (1.29 to 1.47)
1.40†† (1.30 to 1.51)
1.37†† (1.28 to 1.46)
1.05†† (1.03 to 1.06) 1.48†† (1.30 to 1.68) 1.81†† (1.54 to 2.13) 1.01†† (1.00 to 1.01) 1.16† (1.01 to 1.34) 1.43†† (1.23 to 1.66) 1.28†† (1.21 to 1.35)
1.05†† (1.04 to 1.06) 1.47†† (1.30 to 1.65) 1.77†† (1.52 to 2.06) 1.01† (1.00 to 1.01) 1.14* (1.10 to 1.30) 1.39†† (1.21 to 1.60) 1.28†† (1.21 to 1.35)
0.39†† (0.30 to 0.52) 0.72† (0.57 to 0.91)
0.49†† (0.39 to 0.60) 0.86 (0.72 to 1.03)
0.68†† (0.57 to 0.81) 0.72†† (0.63 to 0.83) 1.24† (1.10 to 1.41)
0.43†† (0.35 to 0.53) 0.67†† (0.57 to 0.78)
0.63†† (0.54 to 0.75) 0.69†† (0.60 to 0.79) 1.28†† (1.13 to 1.44)
84
72
73
83
69
1.02†† (1.01 to 1.03) 1.14 (0.83 to 1.56) 1.74†† (1.33 to 2.29)
0.60†† (0.49 to 0.73)
0.62† (0.45 to 0.86) 0.70† (0.54 to 0.90)
0.63†† (0.52 to 0.75)
0.51†† (0.41 to 0.64) 0.90 (0.75 to 1.09)
60
78
59
76
Anti-hypertensive treatment Overall % of cases correctly predicted by model
1.32†† (1.25 to 1.40)
*p b 0.05; †p b 0.01; ††p b 0.001.
were unaware that they had elevated BP and 50% being treated for known HT were not meeting their BP treatment targets. Increasing age, higher BMI, male gender, living in regional locations and established CVD or diabetes were consistently found to influence BP levels. If truly reflective of the BP profile of all Australian adults, these data suggest that after a period of declining BP at the population level during the 1980s to 1990s [5–8], BP levels have returned to alarming heights in the 21st Century. At the international level, this result is consistent with an increasing prevalence of HT. For example, in the United States of America, HT is also reported to affect one in three adults [16], while in Sub-Saharan Africa, the prevalence of HT is 30 to 40% in rural and urban communities, respectively [17]. The temptation to highlight a one dimensional headline figure of elevated BP (i.e. “one in three affected adults”) has the potential to over-shadow the considerable variety and complexity of BP values revealed within study participants. Beyond the well-known influence of age, sex, and risk factor status (including weight profile and a past history of HT), this study revealed considerable heterogeneity in BP values subject to a participant's socio-economic status (reflected by differences according to indicative income and educational status) and geographic location (according to state/territory and metropolitan/regional areas). In regional locations of Australia where health resources are most scarce [11], participants were more likely to have a higher BP. The level of elevated
BP of 40% in regional locations in our survey was below comparable data from urban and rural Australia [18,19]. Higher BP in regional Australia was paralleled by an increase in obesity. Expanding waistlines coupled with an increasingly older population and a migration towards regional centres are likely to fuel an increasing burden of HT in Australia, placing greater demands on regional and remote health care systems. The need to develop innovative models of care and equitable access to health care that overcomes individual and societal barriers to intensive and effective primary and secondary prevention strategies will assume increasing importance in this context. In addition to the broad patterns observed in this study, we found that elevated BP in Australia, the greatest modifiable contributor to the burden of disease from CVD [3], remains largely undetected and uncontrolled. For example, apart from the one in three subjects who were unaware that they had elevated BP, an additional one in two being treated for known HT were not meeting their BP treatment targets. Combating the increase in elevated BP levels requires a renewed and multifaceted response for the detection, treatment and prevention of high BP from individuals, medical professionals, government and the food industry alike, particularly at a time when BP targets are being lowered. Widespread media education and awareness campaigns about the dangers of elevated BP in addition to risk assessment
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programs for early detection of high BP are required to address the key drivers of HT. With a universal health system that provides free or discounted health care and subsidised pharmaceutical therapy in Australia, there is an avenue to achieve these ends. Failure to attain treatment targets belies the expanding armoury to significantly lower BP levels; pharmacological agents, either as mono or combination therapy, as well as lifestyle modifications such as salt reduction, reduced alcohol consumption and exercise [4,20], are all part of a broad array of effective therapeutic strategies and guidelines whose application needs to be maximised. Not addressing potential escalations in BP levels, particularly in high risk individuals and communities, will have dramatic consequences for the future heart health of Australia. For example, each increment of 20 mm Hg in SBP and 10 mm Hg in DBP doubles the risk of CVD across the entire BP range for individuals aged 40–70 years [20]. Even borderline risk factors increase the risk of coronary artery disease within 10 years while a combination of risk factors compounds this risk [21]. Given that participants in this study were self-selected (rather than subject to random purposeful sampling) and we focussed on an assessment at a single point in time, a key question is how representative of the Australian population are these data? A number of previous studies in Australia, all with their own strengths and weaknesses, provide broad support for our findings in respect to elevated BP values and expanded waistlines. The most salient of these is the AusDiab population cohort study [22], with original screening of 11,247 subjects aged over 25 years from 42 Census collector districts in 7 strata (states and territories) in 1999/2000, and a follow-up study of 6537 physical assessments in these subjects in 2004–05; participation rates being 55% and 32% respectively of the original targeted cohort. In the original study [8], the overall prevalence of HT, defined as SBP ≥ 140 mm Hg and/or DBP ≥ 90 mm Hg, or self-reported use of anti-hypertensive drugs, was 29% (95% CI 25 to 32%) increasing to 35% (95% CI 34 to 36%) in the follow-up study. While it is possible that BP measured in this environment may overestimate BP levels, those who had high BP under these relatively controlled circumstances are likely to have high BP in daily life. Further, they may indeed be at higher risk for CVD (as with “white coat hypertensive” individuals) than those who remain normotensive. In view of the positive association between weight and BP in this survey, it is worth noting that that the weight profile of our participants and the subsequent national projections are highly consistent with a contemporary population-based survey of the risk profile of Australians [9]. Compared to our projections of 39% overweight and 26% obese, the latest national survey had similar figures of 37% and 25%, respectively. Moreover, both studies support that overweight and obesity is highest in 65–74 year old men (79%) and 55–64 year old women (68%) [9]. Indeed our estimated prevalence of obesity within the Australian adult population (26%) is also the same found in similar but more rigorous studies in New Zealand [23]. These data also provide a sobering reminder of the likely impact of increasing weight around the globe (with obese individuals at an almost two-fold likelihood to record a higher BP) on both elevated BP levels and preventable cardiovascular events in the longer term [24]. This study has a number of important limitations that influence any interpretation of our findings. Firstly, despite the size and distribution of participants, this was a self-selected group in whom inherent biases were likely. At the very least, while self-selection may have led to more participants with something to gain by having a BP check, most individuals presented to the screening booth without knowledge of its purpose. Furthermore, given the relative lack of CVDrelated awareness and that no prior advertising was done, participant bias may be less of an issue than anticipated. Certainly, we acknowledge that the interpretation of these data was strongest where within study group comparisons were made yet weaker when extrapolated to the wider Australian population. Despite this study being unique in
its methodology, contemporary population-based surveys (as discussed above) [9] that applied a standardized and direct (compared to self-report) approach to data acquisition and a broad geographical basis verify our extrapolations to the Australian population. Past history was dependent on self-report and BP measurements were obtained in a single session, therefore we could not confirm medical histories nor the presence of HT or the accuracy of BP values, even within the normal range. Furthermore, prior to taking BP measurements, we did not control for stimulants such as recent caffeine consumption or nicotine from smoking. The study team closely monitored 10% of sites for quality control but could not attend all 100 geographically dispersed sites. We do not believe that this was problematic for the data however since the screening was undertaken by trained Registered Nurses who followed a standardized protocol and used validated equipment [13]. The impact of external climatic differences across the continent may reflect some heterogeneity observed in these data, despite the testing being conducted indoors at all sites. This represents the largest study of its kind in Australia with key findings that have broad clinical and public health implications at the national and international levels. From an Australian perspective, these data provide strong evidence that elevated BP is still a major health problem within an ageing adult population in whom obesity and related metabolic disorders are becoming increasingly prevalent. The likely consequences on future cardiac, renal and neurological events is likely to be profound, particularly in vulnerable communities where health care resources are scarce and lower socio-economic conditions are more common. At the broader level, these data support the need for regular large-scale national surveys using random samples and standardized methodology so that changes in risk factor prevalence can be detected and addressed before they impact on morbidity and mortality. As a readily detectable, and in many cases modifiable, risk factor that contributes most to avoidable CVD-related events, elevated BP represents a key target for renewed prevention strategies in Australia and beyond. Acknowledgement We gratefully acknowledge Mr. Neil Covey for co-ordinating the National Blood Pressure Screening Day. We thank the nurses for carrying out the survey and Traffik Marketing for organising the screening booths, their distribution across Australia and the return of the study data. MJC and SS are supported by the National Health and Medical Research Council of Australia (NHMRC). The authors of this manuscript have certified that they comply with the Principles of Ethical Publishing in the International Journal of Cardiology [25]. References [1] Lopez AD, Mathers CD, Ezzati M, Jamison DT, C.J.L M.. Measuring the global burden of disease and risk factors, 1990–2001. In: Lopez AD, Mathers CD, Ezzati M, Jamison DT, C.J.L M, editors. Global burden of disease and risk factors. New York: Oxford University Press; 2006. p. 1–13. [2] Begg S, Vos T, Barker B, Stevenson C, Stanley L, Lopez AD. The burden of disease and injury in Australia 2003: Australian Institute of Health and Welfare. AIHW cat. no. PHE 82; 2007. [3] Australian Institute of Health and Welfare. Australia's health 2006. Canberra, ACT, Australia: AIHW cat. no. AUS 73; 2006. [4] National Heart Foundation of Australia (National Blood Pressure and Vascular Disease Advisory Committee). Guide to management of hypertension; 2008. [5] Australian Bureau of Statistics. National Nutrition Survey 1995: nutrient intakes and physical measurements. Canberra, ACT, Australia: ABS cat. no. 4805.0; 1998. [6] Barr ELM, Magliano DJ, Zimmet PZ, et al. AusDiab 2005: the Australian Diabetes, Obesity and Lifestyle Study. Melbourne: International Diabetes Institute; 2006. [7] Bennett SA, Magnus P. Trends in cardiovascular risk factors in Australia. Results from the National Heart Foundation's Risk Factor Prevalence Study, 1980–1989. Med J Aust 1994;161(9):519–27. [8] Briganti EM, Shaw JE, Chadban SJ, et al. Untreated hypertension among Australian adults: the 1999–2000 Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Med J Aust 2003;179(3):135–9.
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