  |
|
|
||||||||||||||||||||||||||||||||||
|
||||||||||||||||||||||||||||||||||||
| Journal of the New Zealand Medical Association,
15-April-2005, Vol 118 No 1213
|
||||||||||||||||||||||||||||||||||||
|
The burden of death, disease, and disability due to alcohol
in New Zealand
Jennie Connor, Joanna Broad, Jürgen Rehm, Stephen
Vander Hoorn, Rod Jackson
The relationship between alcohol consumption and health is
complex, and a better understanding of the determinants of this relationship is
essential for effective strategies to reduce harm from alcohol.
Biological and social effects of alcohol-use result from
three main intermediaries or pathways: intoxication, dependence, and direct
biochemical effects.1 These effects relate to
both the average volume of alcohol consumed and the pattern of drinking. Direct
biochemical effects include both harmful and beneficial effects; for example,
chronic pancreatic and liver damage on one hand, and improvements in blood lipid
and coagulation profiles on the other.
Intoxication is a powerful mediator of acute adverse
outcomes, and risk of injury is increased at even moderate levels of consumption
when there may be little subjective experience of intoxication. Alcohol
dependence, a disorder in itself, mediates the impact of alcohol on all classes
of health outcome.
Average volume of drinking, or total alcohol consumption in
a population, has been used to measure relationships between alcohol and
disease.2 However, average consumption is not a
good predictor of intoxication and consequent injury—or of health benefits
derived from small frequent doses of alcohol, such as reduction in coronary
heart disease. Such effects are better predicted by including measures of
pattern of drinking. ‘Pattern of drinking’ refers to the way in
which most alcohol is consumed (such as in irregular heavy drinking occasions,
or binge drinking) compared with light-to-moderate drinking on a daily
basis,3 and also ‘where and with
whom’ drinking occurs.
Previous quantitative studies of the overall health impact
of alcohol drinking on the New Zealand population4,5
have attempted the complicated task of estimating the net effect of the
impact of alcohol on many aspects of health. The comparative risk assessment
(CRA) methodology developed for the World Health Report
20026,7 has provided an opportunity to update
and refine these estimates.
MethodsDetails of the methodology used
in this study are published elsewhere,8 and
will only be briefly outlined here.
Comparative risk
assessment (CRA)—The CRA methodology was developed by the World
Health Organization (WHO) as a systematic approach to measuring the burden of
disease attributable to a range of important global risk factors, and ranking
them.6,7,9,10 CRA aims to combine best
estimates of the risk factor distribution in the population, with best estimates
of risk factor-disease relationships from the international epidemiological
literature to measure the impact of each major risk factor. In the World Health
Report 2002, global and regional burden of disease due to a range of risk
factors was estimated. This included alcohol, but no country level estimates
were calculated.
The WHO CRA for alcohol drew heavily on existing
reports on the quantification of drug-caused mortality and morbidity in
Australia11–13 and
Canada,14,15 as well as reviewing new
epidemiological evidence about the association of alcohol with health
outcomes.16 (See Rehm et
al17 for an overview.) New methods were
developed for incorporating the effect of pattern of drinking for some
conditions, and for modelling estimates where reliable data on the individual
level were lacking.17
This report employs the CRA approach at a country
level, and for Maori and non-Maori separately where this has been
possible.
Prevalence and
patterns of exposure to alcohol—We calculated average daily
consumption and pattern of drinking from the 2000 National Alcohol and Te Ao
Waipiro surveys18,19 for New Zealanders aged
between 15 and 65 years, weighted to represent consumption for the whole adult
NZ population. Data from five other New Zealand (NZ)
studies20–24 were used to estimate the
alcohol consumption patterns for those older than 65
years,8 and consumption during pregnancy was
estimated from survey data25 in order to
include the health effects of drinking in pregnancy.
We used four levels of average daily consumption, with
different cut points for men and women, corresponding to those used by the WHO
Global Burden of Disease Study (based originally on English et
al11).
To capture the effect of heavy drinking episodes, we
used the pattern of drinking classification developed by WHO, based on evidence
about average harmful and beneficial effects of different alcohol consumption
patterns in populations worldwide.17 The WHO
pattern of drinking category for a country is determined by scoring men and
women according to the proportion that drinks daily, the frequency of getting
drunk, usual drinking quantity per session, fiesta binge drinking, drinking with
meals, and drinking in public places.
Alcohol consumption in New Zealand had been classified
by WHO as Pattern 2 of four possible patterns, where Pattern 1 is the most
beneficial and Pattern 4 is the most detrimental. Based on the best available NZ
survey data,18,19 we allocated non-Maori to
Pattern 2 and Maori to a Pattern 3. Although non-Maori were more likely to be
alcohol drinkers and drink more often, they drank less on a typical drinking
occasion, when compared with Maori. The differences were such that average
alcohol consumption per day amongst Maori and non-Maori was similar, but the
health implications were different.26
Alcohol-related
conditions included in the study—The selection of the conditions
attributable to alcohol was based on evidence of established epidemiological
relationships, assessed by the CRA group, using
meta-analyses,11, 14–16 new research, and
biological evidence (for details see Rehm et
al1). Three groups of conditions were
considered: wholly alcohol-attributable conditions, with an alcohol-attributable
fraction (AAF) of 100%; chronic conditions where alcohol is a contributing cause
(detrimental or beneficial); and acute conditions where alcohol is a
contributing cause.
Although some conditions were omitted or combined into
broader groups where detailed epidemiological evidence was lacking, most of the
alcohol-related burden is in fact due to a only few major disease
categories.27 The conditions included in this
study are listed in Table 1. Social outcomes of alcohol consumption (such as
family problems, public disorder, or workplace problems) have not been included
unless they are coded in ICD-10 (International Classification of Diseases
Version 10), although it is recognised that they also contribute to population
health.
Estimating
alcohol-disease relationships and alcohol-attributable fractions—A
few conditions are, by definition, wholly attributable to alcohol. For all
others, the proportion of the burden that was attributable to alcohol (AAF) was
established from the available epidemiological evidence—by sex, age group,
and Maori/non-Maori status.
For most chronic conditions where pattern of drinking
had not been demonstrated to be important, the AAF was derived from combining
prevalence data and relative risk estimates from
meta-analyses,17 using standard methods for
estimating attributable risk.28 This group
included cancers, hypertensive disease, epilepsy, cardiac arrythmias,
oesophageal varices, pancreatitis, and low birth weight. The beneficial effects
of alcohol on diabetes incidence,16
stroke,29 and cholelithiasis were calculated in
the same way, yielding negative AAFs. The AAFs for unipolar depression were
estimated indirectly from the prevalence of alcohol abuse and dependence in the
NZ population, in the absence of better
data.1,8
Although the effect of pattern of drinking may be
underestimated in some conditions (such as stroke) because pattern information
has not been routinely collected in epidemiological studies, the risks of
coronary heart disease, unintentional injuries, and intentional injuries are
known to be associated with pattern independently of average volume.
Multilevel-modelling was used by the WHO CRA group to assess the effect of
pattern on coronary heart disease (CHD)
outcomes,1 and we have applied the relative
risk estimates for Pattern 2 drinkers in our analysis. As Maori have a different
drinking pattern on average, a sensitivity analysis investigated the scenario
where there was no CHD benefit for Maori.
Injuries make up most of the acute adverse effects of
alcohol, and as the risk is associated with episodes of intoxication, it is
highly pattern dependent. Car crash injuries are the single biggest cause group
and are the best studied. We used a population-based case-control study from
Auckland30 to estimate the AAFs for car crash
injury by age, sex, and Maori/non-Maori status. We then used the ratio of Maori
AAF: non-Maori AAF (1.5) to scale the AAFs for other injuries for
Maori.8
Calculation of alcohol
attributable burden of disease and injury: mortality, YLLs, and
DALYs—The health burden of each of the alcohol-related conditions
was measured using routinely collected mortality data from the New Zealand
Health Information Service (NZHIS) mortality database for 2000—and the
estimated burden for each condition in disability-adjusted life years (DALYs)
lost in 2002 was obtained from the Global Burden of Disease (GBD) 2000
Study.31
The DALY is a summary health gap measure that
integrates fatal and nonfatal outcomes (measured by years of life lost and years
of life lived with disability). Mortality data were available for Maori and
non-Maori separately, as well as by sex and age group, but DALY data were not.
The analysis was restricted to people over 15 years of age, apart from the
secondary effects of drinking by an adult.
Alcohol-attributable mortality was calculated by
multiplying the mortality from each alcohol-related condition in 2000 by the
alcohol attributable fraction for that condition, for each age, sex, and
ethnicity subgroup. Years of life lost (YLL), a measure of the burden of
premature mortality, were derived from mortality data by the ‘remaining
life expectancy method.’32 This method
measures the difference between age at death and life expectancy remaining at
that age.
As life expectancies for Maori and non-Maori differ, a
model life table (Coale and Demeny model life table West
level 26) was used for both populations, to
estimate ‘standard expected years of life lost’ (SEYLL) as in the
GBD Study,33 and discounted at 3% per annum.
Alcohol attributable DALYs have been calculated by
multiplying the DALY count for each alcohol-related condition in New Zealand in
2002 (provided by WHO) by the alcohol attributable fraction for that condition,
for each age and sex subgroup. DALY counts are age-weighted and also discounted
at 3% per annum. Mortality, YLL, and DALY rates have been derived from the
counts (using 2000 and 2002 mid-year population estimates provided by Statistics
New Zealand). Rates were age standardised by the direct method using the WHO
World population as the standard
population.34
Table 1. Alcohol-related conditions included in the
study
ResultsMortality—We
estimated that 1037 deaths in New Zealand in 2000 were attributable to alcohol
consumption; representing 3.9% of all deaths. Alcohol consumption was also
estimated to prevent 981 deaths in the same year, resulting in a net loss of 56
lives.
The mortality burden was not evenly distributed by sex or
ethnicity (Table 2). In non-Maori women, deaths prevented by alcohol consumption
outweighed deaths caused, but in all men, and in Maori women, more deaths were
caused than prevented. The standardised alcohol-related death rate for men was
considerably higher than for women in both Maori and non-Maori. The
alcohol-related death rate for Maori overall was 4.2 times the rate for
non-Maori, after standardisation to the WHO world population to eliminate the
effect of differences in the age structure of the two populations. More lives
were lost due to alcohol as well as fewer deaths prevented by alcohol in Maori
compared with non-Maori, relative to the size of their populations.
More than half (51%) of alcohol-related deaths were due to
injuries, 24% were due to cancer, and 25% to other chronic diseases. Most of the
deaths prevented were from reduction in coronary heart disease (78%) and stroke
(18%).
The predominance of injury as a cause of death in children
and young adults, and of ischaemic heart disease and stroke in older adults,
means that the balance of risks and benefits of alcohol consumption varied with
age. Figures 1 and 2 show the balance between detrimental and preventive effects
of alcohol for Maori and non-Maori, at different ages. The effects of different
average drinking patterns in Maori and non-Maori, and the small proportion of
Maori in the oldest age groups, are reflected in these Figures.
Figure 1. Number of deaths
caused and prevented by alcohol consumption in 2000 among Maori (by age
group)
 Figure 2. Number of deaths
caused and prevented by alcohol consumption in 2000 among non-Maori (by age
group)
Table 2. Mortality and years of life lost (YLL)
attributable to alcohol (by ethnicity and sex) in 2000
Years of life
lost—Years of life lost (YLL) incorporate the impact of deaths at
different ages. The net effects of alcohol on YLL for the 2000 year are also
summarised in Table 2. As with mortality, the burden is not evenly spread in the
population—it is higher in men than women, and higher in Maori than
non-Maori.
Table 3 shows the numbers and proportions of
alcohol-attributable YLLs by condition. Injury is the leading cause of
alcohol-related YLLs and as many injury deaths occur in younger age groups,
injury is responsible for an even larger proportion of alcohol-attributable YLLs
(72%) than deaths (51%).
Years of life gained by alcohol consumption are summarised
by condition in Table 4. Over 80% of the life years gained were from reduction
in IHD in the elderly. The balance of gains and losses due to alcohol for Maori
and non-Maori in different age groups is shown in Figure 3.
Table 3. Proportions of alcohol-attributable years of
life lost (by condition) in 2000
Table 4. Years of life gained by alcohol consumption
(by condition) in 2000
 Figure 3. Age-specific rates of net years of life lost
(YLL) due to alcohol in 2000 (by ethnicity and gender)
Coronary heart disease
mortality in Maori—The effect of alcohol consumption on CHD in
Maori in New Zealand is less well understood than in populations where it has
been directly studied. In the calculations above, we have assumed Maori accrue
the same benefit in the prevention of CHD from drinking the same average volumes
of alcohol as non-Maori, even though the pattern of drinking is different.
Recalculating the impact of alcohol on Maori assuming no
preventive effect on CHD results in the total net deaths due to alcohol in Maori
rising from 133 to 195, and for the whole population from 56 to 118. Due to
small numbers of Maori in the affected age groups, this increases the
age-standardised mortality rate from 38 to 72 per 100,000 in Maori men, and from
less than 2 to almost 16 per 100,000 in Maori women. Therefore, under this
assumption, there are virtually no health benefits for Maori from drinking at
any age.
Disability-adjusted life
years (DALYs)—Alcohol-attributable DALYs were calculated using our
estimates of AAFs combined with WHO estimates of DALY burden in New Zealand for
alcohol-related conditions. Due to combined outcome data, it was not possible to
analyse Maori and non-Maori separately.
Table 5 summarises DALYs lost due to alcohol in 2002. The
burden in men was three times that in women, accounting for 76% of all
alcohol-attributable DALYs lost. Alcohol use disorders comprised the largest
cause group, accounting for 49% of DALYs lost, and this proportion was the same
for men and women. Approximately 11% of alcohol-attributable DALYs lost in women
was due to the increased risk of breast cancer.
Table 5. Alcohol attributable DALYs; total NZ
population 2002
*Rate per 100,000 age-standardised to WHO world
population
The balance of DALYs lost and gained varied with age, and
the net DALY burden of alcohol at different ages is summarised in Figure
4.
Figure 4. Net number of disability-adjusted life years
(DALYs) caused or prevented by alcohol consumption in 2002
 DiscussionIn 2000, about 1037 deaths were
caused (and 981 deaths prevented) by alcohol, resulting in a net loss of about
56 lives. Since lives lost were younger on average than lives saved, this
resulted in a net loss of almost 12,000 years of life. The burden was
substantially higher for men compared with women, and for Maori compared with
non-Maori. Injury was the biggest contributing cause, while positive effects
were largely due to reduced coronary disease mortality in elderly people. The
impact of alcohol on these two conditions depended on pattern of drinking as
well as volume.
A net loss of 26,000 disability-adjusted life years (DALYs)
due to alcohol was calculated for 2002, with 76% lost by men. Alcohol-use
disorders accounted for about half of all DALYs lost.
There are several important limitations that should be
considered when interpreting the results of this study. The scope of the
analysis is limited to conditions captured by the ICD-10 coding system and
therefore excludes social outcomes, and many mental health conditions. Estimates
from other countries have indicated that the costs of social consequences of
alcohol exceed the cost of direct health
consequences.35 There is uncertainty in the
estimates arising from measurements of exposure, determination of risk
relationships, and from outcome assessment, especially for non-fatal outcomes.
The methodology does not account for the lag time between
exposure to alcohol and development of each condition, with current exposure
used as a proxy for the relevant exposure period. Knowledge of
risk-relationships is still evolving and some have been better characterised
than others. Reliable prevalence and risk information is particularly lacking
amongst the elderly, who are seldom participants in epidemiological research or
health surveys.
This study has endeavoured to take an approach consistent
with the Treaty of Waitangi. That is, analyses of the alcohol attributable
burden of disease for Maori and non-Maori have been conducted separately where
possible. However, the evidence base for estimating the burden of alcohol for
Maori is very small, with little specific information on risk relationships and
non-fatal outcomes for Maori. The extrapolation from available data sources to
Maori may be less appropriate than for non-Maori, and further research needs to
be undertaken to address these issues.
The mortality rates calculated from data collected in 2000
are unlikely to be affected by numerator-denominator bias, since the
classification of ethnicity for mortality and census data was similar by
then.
Alcohol is responsible for a considerable burden of
ill-health, and further public health intervention is warranted. Moreover, most
of the benefits of alcohol are based on specific patterns of drinking, which are
associated with small risk for other disease endpoints, so the burden of alcohol
use could be substantially reduced while retaining the benefits.
Five main messages emerged from the analysis that should
inform the public health response: there are no health benefits of drinking
alcohol before middle age; pattern of drinking is an important determinant of
the health effects of alcohol; injury is a major component of the alcohol
burden; alcohol use disorders underlie many of the adverse effects of alcohol;
and the health burden of alcohol falls inequitably on Maori.
Evidence-based policy measures
exist2,35,36 that could be used to reduce
alcohol-related harm. Based on our findings, the focus of these interventions in
New Zealand should be reduction of alcohol-related injury, and reduction of the
disproportionate burden of alcohol for Maori. However, both of these objectives
involve modifying drinking patterns, which are largely socially and culturally
determined. Therefore, as well as targeted strategies, policy measures aimed at
the modification of the wider drinking culture of New Zealand will be
required.
Author information:
Jennie Connor, Senior Lecturer (Epidemiology); Joanna Broad, Senior Research
Fellow; Rod T Jackson, Professor and Head of Section, Section of Epidemiology
and Biostatistics, School of Population Health, University of Auckland; Stephen
Vander Hoorn, Biostatistician, Clinical Trials Research Unit, University of
Auckland; Jürgen Rehm, Director, Centre for Addiction and Mental Health,
Toronto, Canada
Acknowledgments:
This study was based on work by the World Health Organization (WHO) for the
World Health Report 2002, and the Comparative Risk Assessment Project. We are
grateful to WHO for making available methods and spreadsheets, and to Colin
Mathers (Coordinator, Epidemiology and Burden of Disease, WHO) for facilitating
our use of Global Burden of Disease Study data.
The assistance of the following people is also gratefully
acknowledged: Sally Casswell and Megan Pledger (Centre for Social and
Health Outcomes Research and Evaluation) and Helen Moewaka Barnes (Te Ropu
Wariki), Massey University; and John Bushnell (Wellington School of Medicine and
Health Sciences), University of Otago. Datasets were also provided by Robert
Scragg and Patricia Metcalf (Workforce Diabetes Survey); Stephen MacMahon, Robyn
Norton and Shanthi Ameratunga (New Zealand Blood Donors Health Study); Rod
Jackson, Stephen MacMahon and Robyn Norton (Fletcher-Challenge University of
Auckland Heart and Health Study); Ricci Harris, Paparangi Reid and Phillipa
Gander (Sleep Survey); the Ministry of Health (New Zealand Health Survey and
National Nutrition Survey); and Robyn Norton, Jennie Connor, and Rod Jackson
(Auckland Car Crash Injury Study).
We also thank the other members of the Alcohol Burden of
Disease and Disability Group: Dale Bramley, Shanthi Ameratunga, Sue Wells,
Robert Scragg, and Patricia Metcalf for their contributions.
This study was funded by a project grant from the Alcohol
Advisory Council of New Zealand (ALAC). Jürgen Rehm was supported by an
ALAC Visiting Fellowship in 2002/2003.
Correspondence: Dr
Jennie Connor, Section of Epidemiology and Biostatistics, School of Population
Health, University of Auckland, Private Bag 92019, Auckland. Fax: (09) 373 7494;
email: j.connor@auckland.ac.nz
References:
|
|
||||||||||||||||||||||||||||||||||
| | Current
issue | Search journal |
Archived issues | Classifieds
| Hotline (free ads) Subscribe | Contribute | Advertise | Contact Us | Copyright | Other Journals |
|