Elevated total cholesterol: its prevalence and population attributable fraction for mortality from coronary heart disease and ischaemic stroke in the Asia-Pacific region (original) (raw)
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The George Institute for International Health
, University of Sydney
Mount Sinai Medical Center
, New York, USA
Correspondence to Professor Mark Woodward, Department of Medicine, One Gustave L Levy Place, Box 1087, New York, NY 10029-6574, USA Tel: +1 212 241 5451; fax: +1 212 831 811 6; e-mail: mwoodward@george.org.au
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The George Institute for International Health
, University of Sydney
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The George Institute for International Health
, University of Sydney
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Department of Public Health
, University of Hong Kong
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Clinical Trials Research Unit
, University of Auckland, New Zealand
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Department of Health Science
, Shiga University of Medical Science, Japan
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Xuanwu Hospital
, Capital Medical University, China
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Department of Preventive Medicine
, Yonsei University College of Medicine, Korea
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Clinical Trials Research Unit
, University of Auckland, New Zealand
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The George Institute for International Health
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∗For a full list of participants, see Ref. [9].
No reprints will be made available.
Received:
07 November 2007
Accepted:
20 February 2008
Published:
01 August 2008
Cite
Mark Woodward, Alexandra Martiniuk, Crystal Man Ying Lee, Tai Hing Lam, Stephen Vanderhoorn, Hirotsugu Ueshima, Xianghua Fang, Hyeon Chang Kim, Anthony Rodgers, Anushka Patel, Konrad Jamrozik, Rachel Huxley, Asia Pacific Cohort Studies Collaboration, Elevated total cholesterol: its prevalence and population attributable fraction for mortality from coronary heart disease and ischaemic stroke in the Asia-Pacific region, European journal of cardiovascular prevention and rehabilitation, Volume 15, Issue 4, 1 August 2008, Pages 397–401, https://doi.org/10.1097/HJR.0b013e3282fdc967
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Abstract
Background
About half of the world's cases of cardiovascular disease occur in the Asia-Pacific region. The contribution of serum total cholesterol (TC) to this burden is poorly quantified.
Design
The most recent nationally representative data on TC distributions for countries in the region were sought. Individual participant data from 380483 adults in the Asia Pacific Cohort Studies Collaboration were used to estimate associations between TC and cardiovascular disease.
Methods
High TC was defined as ≥ 6.2 mmol/l, and nonoptimal TC as ≥ 3.8 mmol/l. Hazard ratios for fatal coronary heart disease (CHD) and ischaemic stroke (IS) were found from Cox models. Sex-specific population attributable fractions for high TC and nonoptimal TC were estimated for each country. The former used conventional methods, based on single measures of TC and a fixed dichotomy of risk strata; the latter took account of the continuous positive association between TC and both CHD and IS and regression dilution.
Results
Data were available from 16 countries. Where reported, the prevalence of high TC ranged from 4 to 27%. The fraction of fatal CHD and IS attributable to high TC ranged from 0 to 14% and 0 to 15%, respectively. Although leaving the relative ranking of countries much the same, the fractions estimated for nonoptimal TC were typically at least twice as big, ranging from 0 to 47% and 0 to 35%, respectively.
Conclusion
Conventional methods for estimating disease burden severely underestimate the effect of TC. Cholesterol-lowering strategies could have a tremendous effect in reducing cardiovascular deaths in this populous region. Eur J Cardiovasc Prev Rehabil 15:397-401 © 2008 The European Society of Cardiology
Introduction
Many lower and middle-income countries are experiencing an increase in cardiovascular disease (CVD) and other noncommunicable diseases [1]. The impact of this transition cannot be understated in the Asia-Pacific region, which contains more than 65% of the world's population [2]. Over the past two decades, significant changes in diet, characterized by increased consumption of fat and sugar, and reductions in physical activity have occurred within most Asian countries [3]. This ‘nutrition transition’, with its deleterious effects on raising mean population levels of total cholesterol (TC), body mass index and blood pressure, is likely to explain a significant amount of the growing burden of CVD in the Asia-Pacific.
Nonoptimal TC has been identified as the third leading risk factor for mortality globally, and seventh leading risk factor for the global burden of disease [4]. Yet, there exists a need for good quality information on TC levels, and the related cardiovascular burden, for planning and implementing health policy [5], particularly in the Asia-Pacific region.
Methods
We sought nationally representative data on the distribution of TC for adults in each country in the World Health Organization (WHO) Western Pacific and South-East Asian regions from publicly available sources [6–8], as well as national Ministries of Health (or equivalent). We also conducted a Medline search for the period from January 1987 to October 2007 using the search terms ‘cholesterol’ or ‘lipids' or ‘high density lipoprotein’ or ‘low density lipoprotein’ or ‘dyslipidemia’ and the country name. The most recent data from each country were used, provided they were collected within the last 20 years (i.e. since 1987). Data from Hong Kong and Taiwan were handled separately from those for mainland China because these regions have separate health, political and administrative arrangements that may have an impact on the distribution of TC. We selected reports if they were in English, from a nationally representative sample and gave sex-specific TC means or prevalences. Age-specific data were originally sought but were often not available, and, when they were, they were not expressed using consistent groupings.
Estimates of association between TC and death from coronary heart disease (CHD) and ischaemic stroke (IS) were obtained from the most recent data compiled by the Asia Pacific Cohort Studies Collaboration (APCSC). Details of the APCSC, including study identification, data collection, and event verification are described elsewhere [9]. Sex-specific, age-adjusted hazard ratios (HRs) relating baseline TC to mortality from CHD and IS were obtained from Cox proportional hazards regression models, stratified by study [10]. Interactions between TC and country were examined through likelihood tests.
High TC was defined, using a conventional threshold, as ≥ 6.2 mmol/l [11]. Population attributable fractions (PAFs), estimates of the proportion of fatal CHD and IS events that, theoretically, could be avoided if high TC were to be eliminated, were computed using the standard formula [10]:
PAF=100×prevalence×(HR−1)100+prevalence×(HR−1)
Here, the prevalence is the proportion ≥ 6.2 mmol/l and the HR compares those ≥ 6.2 mmol/l with the rest. Estimates of prevalence came from the search procedure and HRs from APCSC. As, in the APCSC, the associations between TC and CHD were similar in all countries (P > 0.05), as were those between TC and IS, the same HRs were used for all countries.
These PAFs for the conventional 6.2 mmol/l threshold, however, ignore the continuous, positive and log-linear, nature of the associations between TC and both CHD and IS, found previously in the APCSC [12]. A more meaningful analysis uses the whole distribution of exposure, rather than this artificial threshold. Thus, we also calculated PAFs by comparing exposures to the theoretical minimum distribution: a normal distribution with mean 3.8 and standard deviation (SD) 0.6 mmol/l [13]. That is, by theoretically shifting each person to their corresponding position on the theoretical distribution. Thus, we found PAFs that estimate the percentage of deaths owing to CHD and IS that can be attributed to the amount by which current exposure exceeds the optimal minimum. Calculations were carried out by applying the generalized potential impact fraction formula to the exposure data and comparing this with the optimal minimum distribution, defined as having a relative risk of one [13]. The continuous relationship between TC and each of CHD and IS was estimated from APCSC using a HR for a one unit increase in TC, separately by sex. A further problem with conventional methods is that the association between a clinical measure, such as TC, taken at a single point in time and a disease outcome, such as the risk of CHD, is typically an underestimate of the association between the usual value of this measure and disease. To account for this, we calculated PAFs for nonoptimal TC after adjusting the APCSC HRs for regression dilution bias [10], using the regression dilution ratio of 0.59 from the APCSC.
When either the prevalence of high TC or the mean of the TC distribution was not reported, or could not be ascertained by enquiry, we estimated missing parameters by assuming normal distributions for TC. If the SD was missing, we imputed this, separately by sex, from a simple linear regression formula relating SDs to means.
Results
Nationally representative data on TC were found for 16 countries/areas (Table 1). The crude prevalence of high TC (≥ 6.2 mmol/l) was reported by 11 of the 16; these ranged from 4 to 27% in both men and women (Table 1). High TC tended to be more prevalent in women, although it was twice as common among men in Fiji.
Data on TC were available for 380 483 participants (58% male) from APCSC; 1518 men and 728 women died from CHD, and 728 men and 196 women died from IS during follow-up with a median of 4 years. The HR for fatal CHD in men, comparing those with high TC with the rest, was 1.49 (95% confidence interval: 1.33-1.67); in women, the HR was 1.41 (1.20-1.67). Corresponding results for IS were 1.53 (1.02-2.28) in men and 1.48 (1.01-2.15) in women. The HRs for a 1 mmol/l increase in TC were: for fatal CHD in men, 1.22 (1.17-1.27) and in women, 1.18 (1.11-1.25); for IS in men, 1.10 (0.98-1.24) and in women, 1.14 (1.01-1.29).
Table 1
Summary data showing serum total cholesterol (TC) (mmol/l), prevalence of TC at or above reported cut-points and estimated population attributable fraction (PAF, %) for fatal coronary heart disease (CHD) and ischaemic stroke (IS) owing to high TC (≥6.2 mmol/l) by country/area
Men | Wome | ||||||||||||
Country/area | Year | Age range (years) | Cut-point, C | n | Mean | % > C | CHD PAF | IS PAF | n | Mean | % > C | CHD PAF | IS PA |
Australia [14] | 2000 | ≥ 25 | 6.2 | 5047 | 5.64 [1.05] | 27.2 | 12 | 13 | 6198 | 5.67 [1.07] | 26.9 | 10 | 1 |
China [15] | 2001 | 35-74 | 6.2 | 7684 | 4.77 | 7.9 | 4 | 4 | 8154 | 4.86 | 10.2 | 4 | 5 |
Fiji [6] | 2002 | 15-85 | 6.2 | 924 | 5.3 [5.1-5.5] | 24.6 (18.3-30.8) | 11 | 12 | 1478 | 5.0 [4.8-5.2] | 13.5 (9.1-18.0) | 5 | 6 |
Hong Kong [16] | 1996 | 25-74 | 6.2 | 1388 | 5.1 [0.9] | 12 | 6 | 6 | 1455 | 5.0 [1.0] | 13 | 5 | 6 |
Indonesia [6, 7] | 2001 | ≥ 15 | 5.2 | 1895 | 3.54 | 6.3 (5.4-7.2) | 0 | 0 | 2186 | 3.62 | 8.2 (7.2-9.2) | 0 | 0 |
Japan [6] | 2000 | ≥ 20 | 6.2 | 2286 | 5.12 [0.93] | 11.5 (10.2-12.8) | 5 | 6 | 3300 | 5.3 [0.95] | 16.2 (15.0-17.5) | 6 | 7 |
Kirabati [17] | 1987 | 35-59 | − | 609 | 4.66 [4.56-4.76] | − | 5 | 5 | 616 | 4.91 [4.81-5.01] | − | 6 | 7 |
Malaysia [18] | 1996 | ≥ 30 | 6.2 | 9330 | 4.5 | 4.5 | 2 | 2 | 10711 | 4.6 | 5.5 | 2 | 3 |
Nauru [6] | 2004 | 15-64 | 5.2 | 1086 | 4.3 [4.2-4.4] | 14.9 (12.7-17.1) | 1 | 1 | 1186 | 4.5 [4.4-4.6] | 20.8 (18.4-23.2) | 2 | 3 |
New Zealand [19] | 1997 | ≥ 15 | 6.5 | 1808 | 5.7 [1.2] | 23.2 | 14 | 15 | 2450 | 5.7 [1.3] | 23.7 | 13 | 1 |
Philippines [20] | 1998 | ≥ 20 | 6.2 | 2239 | − | 4.0 | 2 | 2 | 2302 | − | 4.0 | 2 | 2 |
Singapore [21] | 2004 | 18-69 | 6.2 | − | − | 19.8 | 9 | 9 | − | − | 17.5 | 7 | 8 |
South Korea [22] | 2005 | ≥ 20 | 6.2 | 2254 | 4.75 [0.96] | 5.2 (4.2-6.2) | 2 | 3 | 3069 | 4.74 [0.85] | 6.1 (5.1-7.2) | 2 | 3 |
Taiwan [23] | 1993-1996 | ≥ 19 | 6.2 | 1295 | 4.96 | 10.2 (6.8-13.6) | 5 | 5 | 1425 | 4.86 | 11.2 (6.4-15.9) | 4 | 5 |
Thailand [24] | 2000 | ≥ 35 | 6.2 | 2093 | 5.03 | 13.7 | 6 | 7 | 3212 | 5.35 | 21.2 | 8 | 9 |
Tonga [25] | 1998/2000 | ≥ 15 | − | 433 | 5.18 [1.1] | − | 8 | 9 | 591 | 4.9 [1.1] | − | 5 | 5 |
Men | Wome | ||||||||||||
Country/area | Year | Age range (years) | Cut-point, C | n | Mean | % > C | CHD PAF | IS PAF | n | Mean | % > C | CHD PAF | IS PA |
Australia [14] | 2000 | ≥ 25 | 6.2 | 5047 | 5.64 [1.05] | 27.2 | 12 | 13 | 6198 | 5.67 [1.07] | 26.9 | 10 | 1 |
China [15] | 2001 | 35-74 | 6.2 | 7684 | 4.77 | 7.9 | 4 | 4 | 8154 | 4.86 | 10.2 | 4 | 5 |
Fiji [6] | 2002 | 15-85 | 6.2 | 924 | 5.3 [5.1-5.5] | 24.6 (18.3-30.8) | 11 | 12 | 1478 | 5.0 [4.8-5.2] | 13.5 (9.1-18.0) | 5 | 6 |
Hong Kong [16] | 1996 | 25-74 | 6.2 | 1388 | 5.1 [0.9] | 12 | 6 | 6 | 1455 | 5.0 [1.0] | 13 | 5 | 6 |
Indonesia [6, 7] | 2001 | ≥ 15 | 5.2 | 1895 | 3.54 | 6.3 (5.4-7.2) | 0 | 0 | 2186 | 3.62 | 8.2 (7.2-9.2) | 0 | 0 |
Japan [6] | 2000 | ≥ 20 | 6.2 | 2286 | 5.12 [0.93] | 11.5 (10.2-12.8) | 5 | 6 | 3300 | 5.3 [0.95] | 16.2 (15.0-17.5) | 6 | 7 |
Kirabati [17] | 1987 | 35-59 | − | 609 | 4.66 [4.56-4.76] | − | 5 | 5 | 616 | 4.91 [4.81-5.01] | − | 6 | 7 |
Malaysia [18] | 1996 | ≥ 30 | 6.2 | 9330 | 4.5 | 4.5 | 2 | 2 | 10711 | 4.6 | 5.5 | 2 | 3 |
Nauru [6] | 2004 | 15-64 | 5.2 | 1086 | 4.3 [4.2-4.4] | 14.9 (12.7-17.1) | 1 | 1 | 1186 | 4.5 [4.4-4.6] | 20.8 (18.4-23.2) | 2 | 3 |
New Zealand [19] | 1997 | ≥ 15 | 6.5 | 1808 | 5.7 [1.2] | 23.2 | 14 | 15 | 2450 | 5.7 [1.3] | 23.7 | 13 | 1 |
Philippines [20] | 1998 | ≥ 20 | 6.2 | 2239 | − | 4.0 | 2 | 2 | 2302 | − | 4.0 | 2 | 2 |
Singapore [21] | 2004 | 18-69 | 6.2 | − | − | 19.8 | 9 | 9 | − | − | 17.5 | 7 | 8 |
South Korea [22] | 2005 | ≥ 20 | 6.2 | 2254 | 4.75 [0.96] | 5.2 (4.2-6.2) | 2 | 3 | 3069 | 4.74 [0.85] | 6.1 (5.1-7.2) | 2 | 3 |
Taiwan [23] | 1993-1996 | ≥ 19 | 6.2 | 1295 | 4.96 | 10.2 (6.8-13.6) | 5 | 5 | 1425 | 4.86 | 11.2 (6.4-15.9) | 4 | 5 |
Thailand [24] | 2000 | ≥ 35 | 6.2 | 2093 | 5.03 | 13.7 | 6 | 7 | 3212 | 5.35 | 21.2 | 8 | 9 |
Tonga [25] | 1998/2000 | ≥ 15 | − | 433 | 5.18 [1.1] | − | 8 | 9 | 591 | 4.9 [1.1] | − | 5 | 5 |
Values in round brackets are 95% confidence intervals; values in square brackets are standard deviations (shown where available). Notes: where data were reported in mg/dl they have been converted to mmol/l using the conversion factor 0.0259; blanks, no data reported; Australian and Korean data expanded from published versions through personal correspondence.
Table 1
Summary data showing serum total cholesterol (TC) (mmol/l), prevalence of TC at or above reported cut-points and estimated population attributable fraction (PAF, %) for fatal coronary heart disease (CHD) and ischaemic stroke (IS) owing to high TC (≥6.2 mmol/l) by country/area
Men | Wome | ||||||||||||
Country/area | Year | Age range (years) | Cut-point, C | n | Mean | % > C | CHD PAF | IS PAF | n | Mean | % > C | CHD PAF | IS PA |
Australia [14] | 2000 | ≥ 25 | 6.2 | 5047 | 5.64 [1.05] | 27.2 | 12 | 13 | 6198 | 5.67 [1.07] | 26.9 | 10 | 1 |
China [15] | 2001 | 35-74 | 6.2 | 7684 | 4.77 | 7.9 | 4 | 4 | 8154 | 4.86 | 10.2 | 4 | 5 |
Fiji [6] | 2002 | 15-85 | 6.2 | 924 | 5.3 [5.1-5.5] | 24.6 (18.3-30.8) | 11 | 12 | 1478 | 5.0 [4.8-5.2] | 13.5 (9.1-18.0) | 5 | 6 |
Hong Kong [16] | 1996 | 25-74 | 6.2 | 1388 | 5.1 [0.9] | 12 | 6 | 6 | 1455 | 5.0 [1.0] | 13 | 5 | 6 |
Indonesia [6, 7] | 2001 | ≥ 15 | 5.2 | 1895 | 3.54 | 6.3 (5.4-7.2) | 0 | 0 | 2186 | 3.62 | 8.2 (7.2-9.2) | 0 | 0 |
Japan [6] | 2000 | ≥ 20 | 6.2 | 2286 | 5.12 [0.93] | 11.5 (10.2-12.8) | 5 | 6 | 3300 | 5.3 [0.95] | 16.2 (15.0-17.5) | 6 | 7 |
Kirabati [17] | 1987 | 35-59 | − | 609 | 4.66 [4.56-4.76] | − | 5 | 5 | 616 | 4.91 [4.81-5.01] | − | 6 | 7 |
Malaysia [18] | 1996 | ≥ 30 | 6.2 | 9330 | 4.5 | 4.5 | 2 | 2 | 10711 | 4.6 | 5.5 | 2 | 3 |
Nauru [6] | 2004 | 15-64 | 5.2 | 1086 | 4.3 [4.2-4.4] | 14.9 (12.7-17.1) | 1 | 1 | 1186 | 4.5 [4.4-4.6] | 20.8 (18.4-23.2) | 2 | 3 |
New Zealand [19] | 1997 | ≥ 15 | 6.5 | 1808 | 5.7 [1.2] | 23.2 | 14 | 15 | 2450 | 5.7 [1.3] | 23.7 | 13 | 1 |
Philippines [20] | 1998 | ≥ 20 | 6.2 | 2239 | − | 4.0 | 2 | 2 | 2302 | − | 4.0 | 2 | 2 |
Singapore [21] | 2004 | 18-69 | 6.2 | − | − | 19.8 | 9 | 9 | − | − | 17.5 | 7 | 8 |
South Korea [22] | 2005 | ≥ 20 | 6.2 | 2254 | 4.75 [0.96] | 5.2 (4.2-6.2) | 2 | 3 | 3069 | 4.74 [0.85] | 6.1 (5.1-7.2) | 2 | 3 |
Taiwan [23] | 1993-1996 | ≥ 19 | 6.2 | 1295 | 4.96 | 10.2 (6.8-13.6) | 5 | 5 | 1425 | 4.86 | 11.2 (6.4-15.9) | 4 | 5 |
Thailand [24] | 2000 | ≥ 35 | 6.2 | 2093 | 5.03 | 13.7 | 6 | 7 | 3212 | 5.35 | 21.2 | 8 | 9 |
Tonga [25] | 1998/2000 | ≥ 15 | − | 433 | 5.18 [1.1] | − | 8 | 9 | 591 | 4.9 [1.1] | − | 5 | 5 |
Men | Wome | ||||||||||||
Country/area | Year | Age range (years) | Cut-point, C | n | Mean | % > C | CHD PAF | IS PAF | n | Mean | % > C | CHD PAF | IS PA |
Australia [14] | 2000 | ≥ 25 | 6.2 | 5047 | 5.64 [1.05] | 27.2 | 12 | 13 | 6198 | 5.67 [1.07] | 26.9 | 10 | 1 |
China [15] | 2001 | 35-74 | 6.2 | 7684 | 4.77 | 7.9 | 4 | 4 | 8154 | 4.86 | 10.2 | 4 | 5 |
Fiji [6] | 2002 | 15-85 | 6.2 | 924 | 5.3 [5.1-5.5] | 24.6 (18.3-30.8) | 11 | 12 | 1478 | 5.0 [4.8-5.2] | 13.5 (9.1-18.0) | 5 | 6 |
Hong Kong [16] | 1996 | 25-74 | 6.2 | 1388 | 5.1 [0.9] | 12 | 6 | 6 | 1455 | 5.0 [1.0] | 13 | 5 | 6 |
Indonesia [6, 7] | 2001 | ≥ 15 | 5.2 | 1895 | 3.54 | 6.3 (5.4-7.2) | 0 | 0 | 2186 | 3.62 | 8.2 (7.2-9.2) | 0 | 0 |
Japan [6] | 2000 | ≥ 20 | 6.2 | 2286 | 5.12 [0.93] | 11.5 (10.2-12.8) | 5 | 6 | 3300 | 5.3 [0.95] | 16.2 (15.0-17.5) | 6 | 7 |
Kirabati [17] | 1987 | 35-59 | − | 609 | 4.66 [4.56-4.76] | − | 5 | 5 | 616 | 4.91 [4.81-5.01] | − | 6 | 7 |
Malaysia [18] | 1996 | ≥ 30 | 6.2 | 9330 | 4.5 | 4.5 | 2 | 2 | 10711 | 4.6 | 5.5 | 2 | 3 |
Nauru [6] | 2004 | 15-64 | 5.2 | 1086 | 4.3 [4.2-4.4] | 14.9 (12.7-17.1) | 1 | 1 | 1186 | 4.5 [4.4-4.6] | 20.8 (18.4-23.2) | 2 | 3 |
New Zealand [19] | 1997 | ≥ 15 | 6.5 | 1808 | 5.7 [1.2] | 23.2 | 14 | 15 | 2450 | 5.7 [1.3] | 23.7 | 13 | 1 |
Philippines [20] | 1998 | ≥ 20 | 6.2 | 2239 | − | 4.0 | 2 | 2 | 2302 | − | 4.0 | 2 | 2 |
Singapore [21] | 2004 | 18-69 | 6.2 | − | − | 19.8 | 9 | 9 | − | − | 17.5 | 7 | 8 |
South Korea [22] | 2005 | ≥ 20 | 6.2 | 2254 | 4.75 [0.96] | 5.2 (4.2-6.2) | 2 | 3 | 3069 | 4.74 [0.85] | 6.1 (5.1-7.2) | 2 | 3 |
Taiwan [23] | 1993-1996 | ≥ 19 | 6.2 | 1295 | 4.96 | 10.2 (6.8-13.6) | 5 | 5 | 1425 | 4.86 | 11.2 (6.4-15.9) | 4 | 5 |
Thailand [24] | 2000 | ≥ 35 | 6.2 | 2093 | 5.03 | 13.7 | 6 | 7 | 3212 | 5.35 | 21.2 | 8 | 9 |
Tonga [25] | 1998/2000 | ≥ 15 | − | 433 | 5.18 [1.1] | − | 8 | 9 | 591 | 4.9 [1.1] | − | 5 | 5 |
Values in round brackets are 95% confidence intervals; values in square brackets are standard deviations (shown where available). Notes: where data were reported in mg/dl they have been converted to mmol/l using the conversion factor 0.0259; blanks, no data reported; Australian and Korean data expanded from published versions through personal correspondence.
Across the 16 countries, the estimated percentage of deaths from CHD attributable to high TC ranged from 0 to 14% for men and 0 to 13% for women; corresponding percentages for IS ranged from 0 to 15% for men and 0 to 14% for women (Table 1). The percentages of deaths attributable to nonoptimal TC were typically at least twice as high as those attributable to high TC, ranging from 0 to 47% for men and 0 to 42% for women for CHD (Fig. 1) and 0 to 28% for men and 0 to 35% for women for IS (Fig. 2). PAFs for nonoptimal TC fell in the same rank order for the two outcomes (when the sex-specific percentages were combined) but were lower for IS than CHD. Indonesia, with mean TC below 3.8 mmol/l, had an optimal TC distribution for both the sexes.
Discussion
Our review found, as expected, a considerably higher prevalence of high TC in Australasia compared with most of the less developed countries in the Asia-Pacific region. This is reflected in our estimates of the percentage of fatal CHD and IS events that are attributable to high TC, as conventionally defined, which ranged from 0% in Indonesia to 13-15% in New Zealand. Given that the relationships between TC and risk of CHD and IS are, however, continuous, with no apparent threshold down to low levels of TC [12, 26]; the above figures underestimate the true burden of disease owing to TC; once the continuous effect of TC, and regression dilution, was accounted for, the estimates more than doubled in most cases. Between 0-47% of deaths from CHD, and 0-35% of deaths from IS, were attributable to values of TC above the theoretical ideal.
It can be assumed that our findings for Australia and New Zealand will be approximately true for much of Europe. The same WHO database [6] that was used for some countries in Table 1 reports mean TC and prevalences of elevated TC for (among others) Croatia, Germany, Italy and the United Kingdom which were, at roughly the same times, much the same as those shown in Table 1 for the two Australasian countries. We would also expect the HRs found from APCSC to be similar to those relevant to Europe (or, indeed, elsewhere) [27].
Owing to the form of the pre-existing data, we were unable to take account of differences in prevalence by age, which would have allowed age-adjusted comparisons between countries. Furthermore, although the APCSC did not find differences in CHD HRs for TC by age [12], such differences have been reported elsewhere [26]. PAFs were estimated for fatal events only, as the data on mortality from APCSC are most robust, particularly for subtypes of stroke, which were verified by autopsy or neuroimaging. Estimates of burden could be different, as could the relative ranking of countries, if nonfatal endpoints, and the associated disability, were also taken into account. We recognize that there are multiple risk factors for CVD, and our PAFs do not allow for possible confounding, or synergistic, effects between TC and other risk factors. Although here we focus solely on TC, each of low density lipoprotein-cholesterol, high density lipoprotein-cholesterol and triglycerides also has a role in predicting CHD in the Asia-Pacific region [28]. Our results are clearly time-sensitive and, for example, greater public awareness of the risks of high TC in, at least, the more ‘westernized’ countries of the region may have lowered average TC levels in recent years.
Fig. 1
Estimated population attributable risk for coronary heart disease owing to nonoptimal cholesterol by country/area for males and females.
Fig. 2
Estimated population attributable risk for ischaemic stroke owing to nonoptimal cholesterol by country/area for males and females.
Despite CVD being the leading cause of death globally, approximately 60% of countries worldwide do not have a policy or plan for its prevention. The lack of country-specific epidemiological data on the prevalence and burden of CVD, and its risk factors, has been cited as one of the major impediments to developing and implementing country-specific policies [29]. Compared with ‘western’ countries, there is a relative lack of awareness, among health care professionals, policymakers and the general public, of the importance of raised cholesterol in the Western Pacific and South-East Asian regions [30]. China is one example where, although significant percentages of men and women have high levels of TC (Table 1), the proportions of individuals who are aware, treated and controlled are only 8, 3 and 2%, respectively [15]. This speaks to the need for national preventive and treatment strategies regarding TC, to reduce the substantial burden of CVD in the Asia-Pacific.
Acknowledgements
The National Health and Medical Research Council of Australia (NHMRC; 358395) and Pfizer Inc. (unrestricted educational grant) provided funding. Extra support came from a Canadian Institutes of Health Research fellowship (A.M.), a NHMRC postgraduate scholarship (CMYL) and the Korea Health 21 Project of the Ministry of Health and Welfare (A040152) (H.C.K.).
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Author notes
∗For a full list of participants, see Ref. [9].
No reprints will be made available.
© The European Society of Cardiology 2008
Topic:
- cardiovascular diseases
- ischemic stroke
- cholesterol
- asia
- mortality
- coronary heart disease
- total cholesterol
- dilution technique
- dilute (action)
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