Atrial brillation incidence and outcomes in two
cohorts of octogenarians: LiLACS NZ
Ruth Teh ( r.teh@auckland.ac.nz )
University of Auckland
Ngaire Kerse
University of Auckland
Avinesh Pillai
University of Auckland
Thomas Lumley
University of Auckland
Anna Rolleston
The Centre for Health
Tin Aung Kyaw
University of Auckland
Martin Connolly
University of Auckland
Joanna Board
University of Auckland
Elaine Monteiro
University of Auckland
Valerie Wright St-Clair
Auckland University of Technology
Robert N Doughty
University of Auckland
Research Article
Keywords: Atrial Fibrillation, octogenarians, Indigenous Peoples
Posted Date: December 21st, 2022
DOI: https://doi.org/10.21203/rs.3.rs-2314437/v1
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
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Additional Declarations: No competing interests reported.
Version of Record: A version of this preprint was published at BMC Geriatrics on March 30th, 2023. See
the published version at https://doi.org/10.1186/s12877-023-03902-5.
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Abstract
Background: Atrial brillation (AF), the most common cardiac arrhythmia in the general population, has
signi cant healthcare burden. Little is known about AF in octogenarians.
Objective: To describe the prevalence and incidence rate of AF in New Zealand (NZ) octogenarians and
the risk of stroke and mortality at 5-year follow-up.
Design: Longitudinal Cohort Study
Setting: Bay of Plenty and Lakes health regions of New Zealand
Subjects: Eight-hundred-seventy-seven (379 indigenous Māori, 498 non-Māori) were included in the
analysis.
Methods: AF, stroke/TIA events and relevant co-variates were established annually using self-report and
hospital records (and ECG for AF). Cox proportional-hazards regression models were used to determine
the time dependent AF risk of stroke/TIA.
Results: AF was present in 21% at baseline (Māori 26%, non-Māori 18%), the prevalence doubled over 5years (Māori 50%, non-Māori 33%). 5-year AF incidence was 82.6 /1000-person years and at all times AF
incidence for Māori was twice that of non-Māori. Five-year stroke/TIA prevalence was 23% (22% in Māori
and 24% non- Māori), higher in those with AF than without. AF was not independently associated with 5year new stroke/TIA; baseline systolic blood pressure was. Mortality was higher for Māori, men, those
with AF and CHF and statin use was protective.
In summary, AF is more prevalent in indigenous octogenarians and should have an increased focus in
health care management. Further research could examine treatment in more detail to facilitate ethnic
speci c impact and risks and bene ts of treating AF in octogenarians.
Background
Atrial brillation (AF) is the most common cardiac arrhythmia occurring in 1-2% of the general population;
in those aged 80+ years, up to 18% may have AF.(1-3) AF is responsible for substantial morbidity and
mortality in older people, being independently associated with an increased long-term risk of stroke, heart
failure, cognitive dysfunction and all-cause mortality, driving a signi cant public health impact related to
increased hospitalisations.(3-5) AF has been attributed to hypertension, heart failure, coronary artery
disease, valvar heart disease, obesity, chronic kidney disease (CKD) and diabetes.(6-8) More recently,
newer risk factors are emerging that have implications for clinical management, in particular, sleep
apnoea and a genetic predisposition.(6, 7, 9) Age is a risk factor for AF, and older age is a consideration in
the management and risk for mortality associated with AF.(10) With the ageing demographic, where
those over age 80 years are the fastest growing population group,(11) AF will become an increasingly
important clinical issue.
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Accurate identi cation for population based estimates is di cult as up to 13% of AF cases are likely to be
undiagnosed.(12) Atrial brillation is detected and diagnosed by pulse palpation, cardiac auscultation
and ECG recording. However, one of the challenges for AF identi cation and treatment is its possible
intermittent initial nature and asymptomatic presentation(4, 7, 9) that can lead to under-recognition.(13)
AF prevalence differs in population subgroups and Māori (New Zealand indigenous people) and Paci c
populations have a higher prevalence of AF.(14) Robust research is needed to provide accurate
population estimates.
Stroke can be prevented with anticoagulation if AF is accurately identi ed. Prior to the latest information
about risk of aspirin, around 2013,(15) aspirin alone was often considered the treatment of choice for
people with atrial brillation at risk of bleeding from oral anticoagulants.(16) Dabigatran and rivaroxaban
were added to the New Zealand publicly funded formulary in 2011 and 2018 respectively.(17, 18)
Recommendations for managing AF in those with stroke are established.(19) Existing stroke is a strong
predictor of recurrent stroke at all ages. Stroke can also trigger AF(20) suggesting a cyclical mechanism
of increasing risk. The increase in stroke risk associated with AF in younger populations is well described.
(20) Cardiovascular mechanisms may differ for people in advanced age, and there is debate about
e cacy of management for CVD(21) and CVD risk in those successfully surviving into their 80s.(22-24)
For Māori, indigenous to New Zealand, equity in outcomes is a Government priority. Do the risks
associated with AF persist into advanced age, and how do risk differ between ethnic groups?
Understanding the importance of AF in the majority of older people without prior stroke would aid
re nement of recommendations for screening for AF.
There are no population-based community data on AF in indigenous people overseas or in New
Zealand(25) and reports in advanced age are rare. The aim of this study is to describe the prevalence
and incidence rate of AF in Māori and non-Māori octogenarians living in New Zealand, along with
associated risk of stroke and mortality at 5-year follow-up.
Methods
Design and setting. The Life and Living to Advanced Age cohort study in New Zealand (LiLACS NZ) is a
longitudinal study of the oldest old in New Zealand.(26) The study was initiated in 2010 and used a
population based sampling frame to recruit 937 octogenarians living in one large region including rural
and urban areas. At baseline, the sample consisted of 421 Māori aged between 80 and 90 years (born in
1920-1930) and 516 non-Māori aged 85 years (born in 1925). Māori are indigenous people of Aotearoa
New Zealand. The overall response rate (de ned as the number of people in the eligibility pool who
agreed to participate in the study divided by all eligible people) for the study was 57%.(26) The
recruitment procedures and response rate have been reported.(27) In brief, participants were identi ed
from the electoral roll, health care databases and extensive iwi (tribal), family and personal networks and
were recruited by personal invitation from the general practitioner, iwi or community contact. Recruitment
occurred between March 2010 and April 2011 within the de ned health region boundaries in two health
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districts in the North Island, New Zealand. This paper reports on 877 participants (379 Māori and 498
non-Māori) who gave consent to access to their hospital records.
Measures
Interview and assessment data
Trained interviewers used standardised techniques to conduct structured face-to-face interviews and
trained nurses conducted physical assessments. The socio-demographic data (sex, age, education),
lifestyle behaviour (smoking and alcohol consumption) and medical history were obtained by self-report
through interview.(28) NZ Deprivation index, derived from census based small area characteristics, was
used as an indication of socio-economic status. All medications, as taken, were recorded by the
interviewers by viewing bottles and packets and were coded using the WHO-ATC coding system.
Functional status was determined using the Nottingham Extended Activities of Daily Living (NEADL)(29),
cognitive function with the Modi ed Mini Mental State Examination (3MS)(30), quality of life with the SF12 physical and mental health subscales(31), and depressive symptom with the Geriatric Depression
Scale (GDS-15).(32) Participants were interviewed at yearly intervals between 2010 and 2016, i.e. 5 years
(60 months) follow-up.
Physical assessments completed yearly by research nurses included blood pressure: the average of three
lying measurements; Weight, using Tanita scales and Height measured three times using a stadiometer.
Blood was drawn for fasting serum glucose. ECGs were completed yearly (see below)
Medical and hospital records
A search of medical records from the general practitioner (GP) was undertaken to ascertain a list of
selected diagnosed conditions. This one-page form was completed by either the practice nurse or a
research nurse at the general practice searching the electronic record; this occurred at baseline.
Diagnoses were either ascertained from the GP record, from a hospital discharge letter (ICD-9 and ICD-10
codes), or from reading through the medical records at baseline.(33)
Administrative hospitalisation discharge diagnosis records from all public and private hospitals were
obtained through the New Zealand Health Information Service (NZHIS) within the New Zealand Ministry
of Health by matching the participant unique health identifying number, National Health Index (NHI). The
cause of hospital admission was obtained through standardised ICD9 and ICD10 coding applied by all
New Zealand hospitals, whether participants were discharged alive or died in hospital. Hospitalisation
data were used to contribute to baseline status (as below) and to ascertain outcomes over 60 months.
Conditions considered as comorbidities were ascertained from interview and assessment data, and
medical and hospital records. CVD events, including coronary artery disease (CAD), congestive heart
failure (CHF), peripheral vascular disease (PVD); type 2 diabetes; chronic lung disease or asthma;
osteoporosis; rheumatoid arthritis; osteoarthritis; dementia; depression; thyroid disease; renal impairment;
Page 5/21
cancer (any); Parkinson’s disease; eye diseases; and hypertension were ascertained by cross-checking a
combination of sources, i.e. self-report, GP medical records, NZHIS and physical assessment including
blood sampling. (33).
AF was ascertained each year of the study. An electrocardiograph (ECG) was taken using the Welch Allyn
CP200 12 lead ECG monitor by the trained research nurse and read independently by a cardiologist
(RND). Atrial brillation was ascertained as present from the ECG at the time of LiLACS NZ interviews, in
the GP record, or from the hospitalisation records. At baseline: ever having AF was if hospital or GP
records indicated AF prior to date of enrolment. At each interview, if the ECG documented AF or AF was
recorded in hospitalisation records, participant status was updated to ‘ever AF’.
Outcomes of stroke/TIA were established from the hospitalisation record ICD-9 (430, 431, 432.x, 433.xx,
434.xx, 436, 437.xx, 438.xx) and ICD-10 (I60, I61, I62.x, I63.x, I65.x, I66.x, I67.x, I69.x) primary coded
diagnoses from the time of enrolment to 5 years follow-up. All-cause mortality was ascertained from
national administrative data held by the Ministry of Health using NHI matching.
Statistical analysis
Descriptive statistics were presented for all variables, frequency (percent) for categorical data and mean
(standard deviation, SD) for data with parametric distribution and median (interquartile range, IQR) for
non-parametric distribution. Period prevalence, i.e. accruing cases of AF whether the participant withdrew
from the study or died, was calculated over 5 years.
The association of variables, outcomes and ethnicity with AF at baseline were examined using the Chisquare test.
Time dependent Cox proportional-hazards regression models were used to determine the risk of
stroke/TIA and mortality over the follow-up period. AF is a time-dependent variable since it can change
value over the course of our observation period of 60 months. The value of AF could be held xed at a
certain point in time, say baseline or 60 months, but modelling the changing values of AF ensures use of
all data available giving a more detailed and powerful analysis. The time to AF was calculated at each
year and was modelled as a time to event variable. Since we are interested in the risk for primary stroke
as an outcome related to presence of AF, participants with stroke prior to baseline assessment were not
included in the analysis.
Multivariate analyses were performed, and the adjusted HRs are reported. Participant characteristics
(independent variables) described in Table 2 were examined as confounders and were entered in the Cox
regression models when a variable was p<0.2 in univariate analyses. None with missing data were
included in the analysis. All tests were two sided and were conducted using an alpha value of 0.05. Data
were analysed using SAS V.9.4 (SAS Institute) and SPSS 25.0 for Windows.
We seek to identify inequities, and present ethnic speci c analyses to enable ethnic speci c responses.
Page 6/21
Results
In this sample of 877 participants with hospital records, 595 participants had an ECG at baseline, and
609 had a detailed medication list. Twenty one percent of the sample (n=186), 98 (26%) of Māori and 88
(18%) of non-Māori (p=0.003) had AF at baseline. Period prevalence increased to 50% in Māori and 33%
in non-Māori with ‘ever AF’ over 5 years (Figure 1). Ethnic-speci c incidence rates are shown in Table 1.
Over 5 years, the incidence rate was 128 per 1000-person years in Māori and 54 per 1000-person years in
non-Māori. Incidence increased in the rst 12 months but in a downward trend from 24 months onward.
At all time-points incidence of AF for Māori was double that of non-Māori, i.e. from twice the incidence
rate at 12-month to 2.4 times at 5-year follow-up.
The 5 years period prevalence of stroke/TIA was 31% (117/379) in Māori and 34% (168/498) in nonMāori (p>0.05). Period prevalence of stroke/TIA was higher in those with a history of AF than those with
no AF (Figure 1).
Overall, those with AF had more co-morbidities and were prescribed more medications than those without
AF (p<0.005). Cardiovascular diagnoses were more common in those with AF, as were depressive
symptoms (p<0.005). Those with AF had a lower functional status and physical health related quality of
life (p<0.05) (Table 2).
Table 2 also shows oral anticoagulant therapy in the sample who had medication data in 2010 (n=609,
227 Māori and 382 non-Māori). Forty-seven percent of those with AF (42% Māori and 50% non-Māori)
took warfarin. Nearly 90% of those with AF were receiving either aspirin or warfarin (84% Māori and 92%
non-Māori). Those with AF also had a higher CHADs and CHA2DS2-Vas score; HAS-BLED score was not
different between those with and without AF, median (IQR) score of 3(2) (Table 2). Supplementary STable
1 (end of document) shows that over 60 months warfarin use reduced and Dabigatran use increased.
To determine the predictors of incident stroke occurrence over 5 years follow-up, Cox proportional hazard
regression models were constructed excluding those with stroke at baseline (n=206); regression models
thus included 671 participants (546 without and 125 with AF at baseline). There were 79 primary stroke
cases over 5 years (6 haemorrhagic and 73 ischaemic strokes). Atrial brillation was not independently
associated with 5-year stroke/TIA event. There was a trend towards Māori being more likely to have a
stroke/TIA event when other risks were adjected for. Systolic blood pressure at baseline was
independently associated with a higher risk of 5-year stroke/TIA event. Separate analyses including only
Māori showed this SBP risk; in analyses with only non-Māori the baseline systolic blood pressure was not
associated with higher risk of stroke/TIA outcome (Table 3).
Over the course of 5 years follow-up 189 Māori had died from any cause compared with 184 non-Māori
(45% and 36% respectively: p=0.004). Table 4 shows AF was independently associated with 5-year
mortality risk, and in separate analyses by ethnicity, the risk was observed in Māori only [HR 2.29 (95% CI
1.37-3.82, p<0.01)]. Risk factors associated with mortality differed between Māori and non- Māori. In
addition to AF, older age, male gender and having CHF at baseline increased mortality and receiving
Page 7/21
statins was associated with reduced mortality (Table 4). For non-Māori, AF was not independently
associated with mortality [HR 1.12 (95% CI 0.67-1.87, p=0.66)]; male gender, living in an area of low
deprivation, and having CHF at baseline were associated with increased mortality. The use of warfarin or
aspirin at baseline had an apparent opposite impact in Māori (protective) and non- Māori (not protective),
non-signi cantly.
Discussion
This study reports the prevalence and incidence rate of AF and risk of stroke and mortality in a
population-based sample of octogenarians. In this longitudinal study, with 5 years of follow up, we found
that the prevalence of AF continued to increase with age. More Māori than non-Māori (mostly European
descent) had AF by their 5-year follow-up (over half and up to a third respectively). Our ndings extend
the current NZ(3, 14) and international literature(1, 2) and is the rst study to report the high prevalence of
AF in Māori aged 80+ years.
The AF incidence rate observed in this cohort study was higher than previously reported. In the Rotterdam
Study of 960 adults aged 80+, the incidence rate was 20.7/1000 and 18.2/1000 person-years for those
aged 80-84 and ≥85 years respectively.(1) The ascertainment methods seemed similar to the current
report, but the quality of medical records could be in uenced by the physicians and health system
emphasis on recording AF. In Canada incidence rate was 31.7/1000 person years for those aged 80+,
with a higher prevalence in women (41.5%) than men (24.3%).(10) In a large German study of
administrative data the incidence was 31/1000 person years with no difference between men and
women.(2) In contrast to the Cardiovascular Health Study, where the incidence rate was higher in men
than women aged ≥80 years, 58.7 and 25.1 per 1000 person-years respectively(1), we did not observe a
difference between men and women in the current study but our rates are high at 128 and 53/1000
person years for Māori and non Māori respectively.
Importantly, in the current study identi ed inequity in incidence as Māori had twice that of non-Māori,
which may be explained at least in part by different co-morbidity rates between the ethnic groups. This
includes, for example, higher prevalence of CHF and diabetes among Māori compared with non-Māori.
(34) Overall, the very high prevalence of AF among older Māori and the relationship with AF and mortality
supports a need for greater focus on screening and AF management for older Māori as well as broader
investigations that can further explain the difference in incidence.
The lower proportion of Māori receiving anti-coagulation suggests under-treatment of AF among Māori.
Disproportionate access to cardiovascular disease treatments in Māori(35) is one of the many equity
issues contributing to disparity in mortality for Māori. Further disparities in heart failure and ischemic
heart disease are described(35, 36) and the current study adds ethnic bias in treatment of AF in old age.
We also acknowledge under-treatment may be confounded by indication. Overall, the management for
AF in older people is challenging. In this sample, all participants had at least 4% annual stroke risk and
this risk increased up to 10% for those with AF suggesting treatment is needed for all octogenarians with
Page 8/21
AF. However, older people also have an increased risk of bleeding. With the availability of new oral
anticoagulant such as dabigatran (available in NZ from 2012) with lower bleeding rates but similar
e cacy as warfarin,(37) risks of AF treatment with anticoagulation may be more acceptable to general
practitioners, who are the main prescribers for older people.
We did not nd an independent association between AF and 5-year new stroke/TIA risk. It is possible that
the impact of AF on stroke risk in octogenarians is a co-occurring with other morbidities. Patterns of comorbidities in this cohort were more closely related to hospitalisations and death than number of
conditions,(38) and while those with the combination of AF and CHF had a higher risk of 48-month
hospitalisation,(38) the cause of hospitalisation was not examined. We did not nd that AF was
associated with cognitive decline; (39, 40) though we concur that AF is associated with reduced
functional capacity and quality of life.(41) We acknowledge the null association observed with
stroke/TIA outcome could be a Type II error and recommend further studies to examine the cause and
impact of AF in octogenarians; it is possible that the AF and stroke association is not similar in advanced
age as observed in the younger population.
The ARCOS studies of stroke in NZ show Māori have stroke at younger age,(42) and have differing
patterns of subtypes and risk factor pro les.(43) However the disparity in stroke incidence was not
observed after age 85 years. This is consistent with our current data. In our whole group analyses,
increasing blood pressure was an independent risk for stroke/TIA, mostly driven by the speci c analyses
for Māori. These ndings are consistent with national(43) and international(44) data of the importance of
increased blood pressure with risk of stroke/TIA. These ndings have direct relevance for Māori and
reiterate the need for strategies to improve blood pressure management for Māori.
The current study con rms a clear ethnic inequtiy in all-cause mortality: AF was strongly associated with
mortality for Māori, independent of the presence of CHF, whereas for non-Māori, CHF was associated with
mortality, but AF was not once anti-coagulants and other treatments were taken into account.
Interestingly the risk associated with anticoagulant treatment was high for non- Māori (indication bias)
but low for Māori. While both associations are non-signi cant, the much reduced use of warfarin in this
sample is worthy of further examination. AF and heart failure both occur in the context of similar
cardiovascular risk factors and clinical CVD. At baseline, almost half of those with AF had co-existing
heart failure, and AF has been associated with worse outcome for patients with established CHF. Perhaps
this sample of advanced age Māori showed a glimpse of the impact of earlier exposure to AF among
Māori at a younger age.(14) Our data reinforce the importance of both AF and heart failure and highlight
opportunities for improving outcomes by addressing these speci c conditions. Statin treatment is
potentially a proxy for adherence to guidelines for management of CVD,(45) and in this analyses
appeared protective for Māori.
Socioeconomic deprivation was associated with mortality risk for non-Māori but not Māori. Māori in the
LiLACS NZ cohorts live in more deprived areas.(26) Potentially, disparities in cardiovascular disease(35,
36) and its management in addition to the unquanti able impacts of colonisation are stronger drivers of
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mortality than deprivation alone. The current study, with differing risk factor associated with both stroke
and mortality for Māori than non- Māori in advanced age, supports ethnic speci c studies and strategies
to untangle the health inequalities in NZ.(46) For non-Māori the nding that higher mortality risk was
associated with residence in an area of low deprivation challenges the inverse care law. It may be that
those managing to live to an old age in high deprivation areas are in some way more resilient.
Strength and limitations
This strength of this study is the population based sampling frame, equal sampling and engagement
with indigenous elders with a similar response rates to non-indigenous. The detail of the data collected
and accuracy of ascertainment of outcomes means these associations identi ed are very likely robust.
While this study provides some evidence on the burden of AF in these groups engaged in a cohort study, it
also presents several limitations including the relatively small number of events and overall sample size.
The ethnic-speci c Cox models in this study may have reduced statistical power for differentiating the
independent in uences of AF and heart failure on the outcomes. We recommend cautious interpretation
of the results.
Conclusion
In conclusion, AF is highly prevalent in octogenarians, particularly in indigenous people and continues to
increase with age. Under-treatment of AF in octogenarians is also prevalent and may be attributed to the
challenges presented to physicians. The impact of AF on long-term health outcomes is likely to be
multifaceted and further research is needed to examine this in more detail to facilitate clinical decision
weighing up the risk and bene t of treating AF in octogenarians.
Declarations
Con icts of interest. The authors declare that they have no competing interests.
Ethics approval and consent to participate
The study was approved by the Northern X Regional Ethics Committee (NXT 09/09/088) in 2009 and all
study participants provided written informed consent. All methods were performed in accordance with the
relevant guidelines and regulations.
No animals were used in this study – Not applicable.
Consent for publication
No individuals are identi ed in this manuscript. Not applicable.
Availability of data and materials
Page 10/21
The datasets used and/or analysed during the current study are available from the corresponding author
on reasonable request and after appropriate permissions, particularly from Māori oversight committee is
obtained. All data generated or analysed during this study are included in this published article
Funding Declarations
This work was supported by the Health Research Council of New Zealand [HRC 06/068B, 09/068B; UoA
ref: 362494]) and Ministry of Health New Zealand [MOH ref: 345426/00; UoA ref 3703221] which funded
the project management and data collection work; Ngā Pae o te Māramatanga [UoA ref: 3624946] which
funded the Māori engagement and project management; New Zealand Heart Foundation project grant for
investigating cardiac markers [UoA Ref: 3625921] and a Heart Foundation Research Fellowship [UoA ref:
3702288] supporting RT during data collection. NK is supported by the Joyce Cook Chair in Ageing Well
family foundation. The sponsors had no impact on the project design or conduct.
Authors contributions
RT conceived this study and led the data analyses and manuscript. NK co-led (with equal Māori
governance not authored here) the LiLACS NZ project and supported manuscript preparation; AR provided
cultural oversight and interpretation of all Māori data use; statistical support was provided by AP
overseen by TL; TAK, EM, undertook speci c analyses; JB, MC provided epidemiological and clinical
perspectives respectively; VWSC provided contextual perspectives; RND read the ecgs and supervised the
cardiological interpretations. All authors contributed to manuscript editing and approved the nal
manuscript.
Acknowledgements
We wish to acknowledge the participants, their families and whanau for supporting the study. We thank
Te RōpuKaitiaki o ngā tikanga Māori for their guidance. We acknowledge the community partners in
LiLACS NZ who engaged with participants and collected data (Western Bay of Plenty Primary Health
Organisation, Ngā Matāpuna Oranga Kaupapa Māori Primary Health Organisation, Te Korowai Aroha
Trust, Te Rūnanga o Ngati Pikiao, Rotorua Area Primary Health Services, Ngati Awa Research & Archives
Trust, Te Rūnanga o Ngati Irapuaia and Te Whanau a Apanui Community Health Centre).
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Tables
Table 1: AF incidence over 5-year follow-up in octogenarians in New Zealand
12m
24m
36m
48m
60m
New cases/total person years
cases (95% CI) per 1000 person years
All
Māori
non-Māori
All
Māori
non-Māori
63/707
37/297
26/409
89.1
124.4
63.5
(73.3, 108.4)
(105, 146.8)**
(50.2, 79.5)
118.4
171.7
81.4
(99.5, 140.2)
(148.2, 197.6)**
(66.1, 99.6)
106.7
160.0
68.3
(88.6, 127.1)
(136.6, 186.3)**
(54.6, 85.1)
94.6
145.3
61.9
(77.8, 113.9)
(124.2, 169.5)**
(48.4, 77.2)
82.6
128.4
53.7
(67.0, 100.7)
(108.6, 151.1)**
(41.4, 68.2)
153/1292
190/1781
209/2208
213/2579
91/530
114/712
126/867
128/997
62/762
73/1068
83/1341
85/1582
** p<0.001 comparing Māori and non- Māori; AF atrial brillation, m=months
Table 2: Baseline characteristics of the sample of octogenarians by AF status
Page 15/21
No AF, n=691 (col
%)
Yes AF, n=186 (col
%)
Māori
281 (41%)
98 (53%)**
Non-Māori
410 (59%)
88 (47%)
Age, mean (SD)
84 (2)
84 (2)
men
312 (45%)
83 (45%)
women
379 (55%)
103 (55%)
• Primary
146 (21%)
43 (24%)
• Secondary
391 (58%)
106 (58%)
• Trade or tertiary
139 (21%)
34 (19%)
• 1 – 4 (low deprivation)
123 (18%)
34 (18%)
•5-7
208 (30%)
58 (31%)
• 8 - 10
360 (52%)
94 (51%)
• Never a smoker
339 (50%)
75 (41%)
• Past (stopped more than 12 mths)
295 (43%)
93 (51%)
• Current
48 (7%)
15 (8%)
• Never
167 (33%)
47 (39%)
• At least monthly
137 (27%)
40 (33%)
• At least twice a week
208 (41%)
33 (28%)*
Number of co-morbidities, median (IQR)*
5 (3)
6 (3)**
Diabetes
141 (20%)
55 (30%)*
CVD
413 (60%)
167 (90%)**
Stroke/TIA
165 (24%)
65 (35%)**
CHF
123 (18%)
107 (58%)**
Gender,
Education
NZ Dep Index
Smoking
Alcohol
Conditions
Page 16/21
Hypertension
576 (83%)
169 (91%)*
Thyroid disease
38 (5%)
11 (6%)
SBP/DBP, mean (SD)
152(23) / 81 ((12)
142 (23) / 80 (14)*
Fasting glucose (mmol/L), median (IQR)
5.30 (0.90)
5.30 (0.70)
FT4 (pmol/L), median (IQR)
15.0 (2.6)
15.8 (3.4)*
2.5 (2.1)
3.6 (1.6)
TSH (mIU/L), median (IQR)
Total med, median (IQR)*
5 (5)
7 (3)**
BP lowering medication, n (%)
354 (72%)
106 (89%)**
Statin
179 (37%)
50 (42%)
Māori with medication for AF data#
N=177
N= 50
Aspirin
84 (48%)
25 (50%)
Warfarin
6 (3%)
21 (42%)
Digoxin
4 (2%)
15 (30%)
Aspirin + warfarin
nil
4 (8%)
Warfarin or Aspirin
90 (51%)
42 (84%)
Non- Māori with medication for AF data##
n = 316
N = 66
Aspirin
144 (46%)
32 (49%)
Warfarin
10 (3%)
33 (50%)
Digoxin
5 (2%)
14 (21%)
Aspirin + warfarin
1 (0.3%)
4 (6%)
Warfarin or Aspirin
153 (48%)
61 (92%)
CHADS 2 median (IQR)
2 (2)
3 (1)**
CHA2DS2-Vas, median (IQR)
4 (1)
6 (3)**
HAS-BLED, median (IQR)
3 (2)
3 (2)
259 (37%)
67 (37%)
435 (63%)
116 (63%)
249 (36%)
79 (44%)
Risk scores
Yearly bleeding risk, n (%)
• 0 to 2
• ≥3 high risk
Falls in the past 12 months
Page 17/21
Function, NEALD, median (IQR)‡
19 (3)
18 (6)*
• Mental health related QoL
57 (10)
56 (11)
• Physical health related QoL
44 (8)
39 (18)*
Depressive symptoms, GDS, median (IQR)†
2 (2)
2 (3)*
Cognition, 3MS (adjusted for visual impairment), median
(IQR) ‡
93 (10)
92 (10)
QoL, median (IQR) ‡
AF atrial brillation; 3MS – Modi ed Mini Mental State Examination for cognition; CHF – congestive
heart failure; CHADS – risk of stroke score; CHADS2-Vas modi ed risk of stroke score; CVD –
cardiovascular disease; GDS – Geriatric Depression Scale score for depressive symptoms; HAS-BLED –
risk of bleeding score; IQR interquartile range; NEADL – Nottingham Extended Activities of Daily Living
functional status score, QoL – quality of life; SD – standard deviation; TIA – transient ischaemic attack
Notes: 60 participants had no medical records of AF
#152
Māori had no medication details (106 in ‘no AF’ and 46 in ‘yes AF’)
##
116 non-Māori had no medication details (95 in ‘no AF’, 21 in ‘yes AF’)
‡
Higher score =better function
† The mean
(SD) for GDS for No AF 2.2 (2.0) vs Yes AF 2.8 (2.0). Lower score = less depressive
symptoms.
*p<0.05; ** p<0.01 Adjusted for confounder (age) and effect modi er (ethnicity); interaction terms
(ethnicity and exposure of interest) had p>0.05 except for ethnicity*number of prescribed medication
(p=0.049); ethnicity*alcohol (p=0.046) and ethnicity*DBP (p=0.030).
Table 3: Multivariate Cox regression analysis for 5-year new stroke outcome in octogenarians (excluding
recurrent stroke)
Page 18/21
Hazard Ratio (95%CI), p value
Variable
Whole Sample
Māori
Non-Māori
Time-varying AF
1.26 (0.62, 2.57),
0.53
1.03 (0.28, 3.77),
0.96
1.60 (0.67, 3.85),
0.29
Baseline warfarin or aspirin (ref:
no)
1.35 (0.72, 2.52),
0.35
1.13 (0.43, 2.95),
0.80
1.51 (0.65, 3.48),
0.34
Age
1.11 (0.95, 1.28),
0.19
1.05 (0.89, 1.23),
0.56
1.87 (0.98, 3.56),
0.06
Gender (ref: men)
0.78 (0.45, 1.37),
0.39
0.65 (0.26, 1.62),
0.36
0.88 (0.43, 1.83),
0.74
Ethnicity (ref: non- Māori)
1.77 (0.95, 3.31),
0.07
-
-
NZDep med (ref=high)
0.67 (0.33, 1.35),
0.26
0.65 (0.20, 2.15),
0.49
0.61 (0.25, 1.49),
0.28
NZDep low (ref=high)
0.54 (0.27, 1.09),
0.09
0.39 (0.13, 1.21),
0.10
0.67 (0.28, 1.62),
0.37
Baseline SBP
1.01 (1.00, 1.03),
0.03
1.02 (1.00, 1.04),
0.03
1.01 (0.99, 1.02),
0.25
Statin (ref=no)
0.73 (0.39, 1.39),
0.34
1.03 (0.38, 2.79),
0.95
0.58 (0.24, 1.35),
0.20
CHF, prior (ref=no)
0.75 (0.32, 1.73),
0.45
0.35 (0.08, 1.61),
0.18
1.21 (0.43, 3.36),
0.72
NZDep = New Zealand Deprivation Index,
Ref – reference
SBP - systolic Blood Pressure
CHF - congestive Heart Failure
Table 4: Multivariate Cox regression analysis for 5-year mortality of octogenarians
Page 19/21
Hazard Ratio (95%CI), p value
Variable
Whole Sample
Māori
Non-Māori
Time-varying AF
1.26 (0.62, 2.57),
0.53
1.03 (0.28, 3.77),
0.96
1.60 (0.67, 3.85),
0.29
Baseline warfarin or aspirin (ref:
no)
1.35 (0.72, 2.52),
0.35
1.13 (0.43, 2.95),
0.80
1.51 (0.65, 3.48),
0.34
Age
1.11 (0.95, 1.28),
0.19
1.05 (0.89, 1.23),
0.56
1.87 (0.98, 3.56),
0.06
Gender (ref: men)
0.78 (0.45, 1.37),
0.39
0.65 (0.26, 1.62),
0.36
0.88 (0.43, 1.83),
0.74
Ethnicity (ref: non- Māori)
1.77 (0.95, 3.31),
0.07
-
-
NZDep med (ref=high)
0.67 (0.33, 1.35),
0.26
0.65 (0.20, 2.15),
0.49
0.61 (0.25, 1.49),
0.28
NZDep low (ref=high)
0.54 (0.27, 1.09),
0.09
0.39 (0.13, 1.21),
0.10
0.67 (0.28, 1.62),
0.37
Baseline SBP
1.01 (1.00, 1.03),
0.03
1.02 (1.00, 1.04),
0.03
1.01 (0.99, 1.02),
0.25
Statin (ref=no)
0.73 (0.39, 1.39),
0.34
1.03 (0.38, 2.79),
0.95
0.58 (0.24, 1.35),
0.20
CHF, prior (ref=no)
0.75 (0.32, 1.73),
0.45
0.35 (0.08, 1.61),
0.18
1.21 (0.43, 3.36),
0.72
NZDep = New Zealand Deprivation Index,
Ref – reference
SBP - systolic Blood Pressure
CHF - congestive Heart Failure
Figures
Page 20/21
Figure 1
Period prevalence for atrial brillation and stroke by ethnic group over 5-year follow-up for octogenarians
in New Zealand
AF Atrial Fibrillation, m months of follow up.
Supplementary Files
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Supplementarymaterial.docx
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