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Received 28 February 2010; accepted in revised form
27 September 2010
Age and Ageing 2011; 40: 66–73
© The Author 2010. Published by Oxford University Press on behalf of the British Geriatrics Society.
doi: 10.1093/ageing/afq106
All rights reserved. For Permissions, please email: [email protected]
Published electronically 7 September 2010
Frequency of inappropriate drugs in primary
care: analysis of a sample of immobile patients
who received periodic home visits
THOMAS FISS1, ADINA DREIER2, CLAUDIA MEINKE1, NEELTJE
WOLFGANG HOFFMANN1
VAN DEN
BERG1, CHRISTOPH ALEXANDER RITTER3,
1
Department of Epidemiology of Health Care and Community Health
Department of General Medicine, Institute for Community Medicine, Ernst Moritz Arndt University of Greifswald, Ellernholzstr.
1-2, 17487 Greifswald, Germany
3
Institute of Pharmacy, Ernst Moritz Arndt University of Greifswald, F.-Ludwig-Jahnstr. 17, 17487 Greifswald, Germany
2
Address correspondence to: T. Fiss. Tel: (+49) 3834867776; Fax: (+49) 3834867751. Email: [email protected]
Abstract
Background: drug intake is associated with the risk of drug-related problems (DRPs), e.g. the intake of PIM.
Objective: the proportion of potentially inappropriate medication (PIM) taken by elderly people was analysed.
Design: community-based, prospective cohort study.
66
Frequency of inappropriate drugs in primary care
Setting: ambulatory health-care sector in a German rural area.
Subjects: seven hundred and forty-four patients with age >65 years and regular intake of drugs.
Methods: comprehensive home medication review (HMR) provided by specially qualified assistants of GP practices using
electronic case reporting forms (eCRFs), and GP’s diagnoses were extracted from patients’ health records. Updated Beers’
list of Fick et al. was used to detect PIM for patients >65 years and drug–condition interaction.
Results: a total of 18% (n= 134) of the patients received 163 inappropriate drugs. Out of these drugs, most prevalent PIM
were benzodiazepine derivates (n= 45). Out of all drugs, 25 drug–condition interactions were identified. The intake of PIM
was slightly associated with self-reported falls (φ: 0.1074; P= 0.0244). Multivariate logistic regression showed significant
results for the number of taken substances (OR = 1.176; 95% CI 1.121–1.234, P< 0.001).
Conclusions: a high proportion of patients taking PIM in a community-based setting were investigated. Statistical associations with self-reported falls were found. Confounding may influence data. Further research to investigate findings is
needed.
Keywords: home medication review, drug-related problem, inappropriate drugs, falls, self-medication, elderly
Introduction
Drug intake is associated with a risk of occurrence of
drug-related problems (DRPs). DRPs comprise numerous
unwanted effects, including the intake of potentially inappropriate medication (PIM) [1]. PIM’s definition primarily
focuses on special patient groups such as children, pregnant
women and elderly patients due to fluctuating drug effects.
The intake of PIM is associated with significantly higher
total, provider and facility costs [2]. In Germany, there is an
ongoing discussion about the improvement of medication
safety [3]. The goal is to optimise patient safety in drug
treatment. Therefore the ‘Action Plan for Medication Safety
in Germany’ (‘Aktionsplan Arzneimitteltherapiesicherheit
für Deutschland’) was developed under the auspices of the
German Federal Ministry of Health. This plan comprises
several activities especially for the elderly. Activity no. 29
concerns the development of a drug list with a negative
risk–benefit ratio for the elderly [4]. Presently, such a list is
not available for health-care professionals in German
primary care. At this time, the list of Beers et al. [5] and its
update from 2003 [6] is a standard source for PIM in
Germany. This list was developed with a modified Delphi
method and identified 48 individual substances or classes
and 20 condition–medication combinations to be avoided
in the pharmacotherapy of older people (>65 years). The
prevalence of PIM use by older patients and the determinants for the intake of PIMs are unknown. To overcome
the knowledge gap about the prevalence of PIM, there is a
need for intensified research based on primary data comprising drug information including prescribed (RX) and
over-the-counter drugs (OTC) as well as patients’ diagnoses. Health claims data have various limitations because
they do not contain information about OTC drugs.
Furthermore, many PIM such as benzodiazepines are prescribed on private prescription [7]. Hence, these drugs are
underestimated. Both GP and pharmacist receive insufficient information about drug intake behaviour in the
homes of the patients.
Based on a detailed medication review in the framework
of the AGnES projects (AGnES: GP-supporting,
community-based, e-health-assisted, systemic intervention)
[8–10], our manuscript aims to provide an estimate about
the proportion of PIM taken by elderly people in German
rural areas. The AGnES concept comprises the delegation
of GP home visits to qualified practice assistants to contribute to the delivery of primary health care in regions
with an undersupply of GPs [10–12].
Research questions
1. What is the proportion of PIM in the study population?
2. To what extent is the intake of PIM associated with
the occurrence of DRPs?
Methods
General design of the AGnES projects
The home medication reviews (HMRs) were conducted
within the AGnES project framework between March 2006
and December 2008. Details are described elsewhere [10–
12]. The AGnES practice assistants’ home visits were
organised in distinct modules. Sample size was determined
by the capacity of the AGnES practice assistant.
The treating GP informed the patients about the
AGnES project. Written informed consent was provided
prior to the first visit. Ethical approval for the study was
obtained by the board of physicians Mecklenburg-Western
Pomerania at the University of Greifswald.
The HMR was offered to 906 AGnES patients whereof
779 (86%) participated in the HMR. IT-supported data collection in the HMR included a general interview with questions about adherence, usage of a medication plan and/or a
dispenser box and the occurrence of adverse drug reactions
(ADRs). Further, all drugs in the household (RX and OTC
medication) were entered into electronic case reporting
67
T. Fiss et al.
forms (eCRFs) [9]. Plausibility check for ADR was done by
the local pharmacist.
(available at: www.pharmazie.com) were used. Patients’ diagnoses were linked with the drug data and were checked for
drug–condition interaction.
Inclusion criteria
Patients older than 65 years with a complete drug history
and a regular intake of one or more drugs were included
(n = 744).
Data preparation
The analysis included three data sets: First: results of the
general interview; second: drug data and third: treatment
diagnosis. Drug data were expanded by adding prescription
status using the German prescription act for drugs (data
status: December 2008 [13]). This act subdivides three
states of prescription:
• RX: only available on prescription,
• OTC: all dosages and pharmaceutical forms are available
in a pharmacy without a prescription,
• partly RX: the prescription status depends on the dosage,
pharmaceutical form and indication.
The ATC code [14] and the summary of product
characteristics (SPC, available at www.fachinfo.de) were
used to categorise the active substances of each preparation.
Patients’ diagnoses were coded by using the International
Classification of Diseases (ICD-10) of the World Health
Organisation (WHO) (data status: December 2008).
PIM for patients >65 years were marked in a subsequent step based on the updated list of Fick et al. [6].
This list is well known by German physicians. We subdivided two groups of PIM:
(1) Drugs which are inappropriate for patients with an age
>65 years,
(2) Inappropriate drug–disease combinations, defined as
drug–condition interaction.
Not all Beers drugs were available in Germany. For
identifying the sales status, the German Rote Liste 2009
(available at www.rote-liste.de) and the ABDA database
Statistical analysis
For the analysis of possible associations between patients’
characteristics (gender, age, number of taken active substances), probable protective factors (visiting a favourite
pharmacy regularly, receiving support with drug administration) and the occurrence of DRP (ADR, non-adherence
and falls) the φ coefficient was calculated. The φ coefficient
is a statistical measure of the degree of association between
two binary variables. The φ-value ranges from −1 to +1.
Relating to the definition of Cohen, φ is similar to the effect
size w [15]. Hence, a φ coefficient of ±(0.1–0.3) indicates a
small effect, a φ coefficient of ±(0.3–0.5) a medium effect
and a φ coefficient of greater than ±0.5 a large effect. A φ
coefficient of 0 indicates that there is no association
between the tested variables. A significant P-value does not
necessarily mean that there is a clinical relevant association.
In a subsequent step, a multivariate binary logistic
regression analysis was conducted with intake of a PIM as
the outcome variable and age (5-year categories), gender,
support with drug administration, number of regularly
taken active substances and visiting a favoured pharmacy as
predictor variables. Factors were chosen based on the
actual literature [16, 17].
All analyses were performed using the SAS software
package (SAS Institute Inc., Cary, NC, USA, SAS 9.2).
Results
Medication assessment
Seven hundred and forty-four patients with age >65
years were included in the analysis. The median age of
these patients (female: 544; male: 200) was 81 years
(females: 81; males: 79 years). Basic characteristics and
self-reported DRPs are given in Table 1. Drugs from
Table 1. Basic characteristics of patients who received a comprehensive drug history and were included in the analysis
Basic characteristics
Women (n = 544)
Men (n = 200)
All (n = 744)
Age, mean, median (range, SD) (years)
81.1, 82 (66–99, 6.6)
78.9, 79 (66–96, 6.8)
80.5, 81 (66–99, 6.7)
Number of patients who reported a favoured pharmacy
Number of patients who got support in drug administration
Number of patients who use a dispenser box for drug administration
Number of patients who had a written medication list
Self-reported forgetfulness in drug intake
Self-reported intermission of drug intake
Self-reported occurrence of ADR
Self-reported falls during last 12 monthsa
Number of taken active substances per patient, all [mean, median (range, SD)]
Thereof number of taken active substances per patient, regularly taken
[mean, median (range, SD)]
530 (97.4%)
234 (43.0%)
377 (69.3%)
403 (74.1%)
41 (7.5%)
33 (6.1%)
27 (5.0%)
184 (55%)
8.2, 8 (1–25, 4)
6.8, 7 (1–19, 3.1)
195 (97.5%)
119 (59.5%)
150 (75.0%)
161 (80.5%)
13 (6.5%)
8 (4.0%)
12 (6.0%)
63 (60.6%)
8.2, 8 (1–23, 4.1)
7, 7 (1–21, 3.2)
725 (97.4%)
353 (47.4%)
527 (70.8%)
564 (75.8%)
54 (7.3%)
41 (5.5%)
39 (5.2%)
247 (56.3%)
8.2, 8 (1–25, 4)
6.9, 7 (1–21, 4)
....................................................................................
a
Four hundred and thirty-nine patients with an HMR received a falls anamnesis, female: 335; male: 104.
68
Frequency of inappropriate drugs in primary care
three ATC classes (cardiovascular system: n = 2,360; alimentary tract and metabolism: n = 890; nervous system:
n = 870) accounted for 70.6% of the total drug use
(ntotal = 5,834 including 648 combined drugs). The
number of regularly taken active substances was high:
every patient took a median number of seven active substances with a range from 1 to 21. About 5% (n = 39) of
the patients reported ADRs.
Potentially inappropriate medication
About 18% (n = 134) of the 744 patients received in total
163 PIMs. Overall, the benzodiazepines followed by the
antidepressants amitriptyline and doxepine were the most
commonly used medication on the drugs-to-avoid list.
Table 2 gives an overview of the drug classes which were
inappropriate with age >65 years and drug–condition
interactions.
Of all the found PIMs (n = 163), 25 were drug–condition interactions. Most prevalent was the combination of
the antidepressant amitriptyline with arrhythmias or COPD,
respectively. The following drug–condition interactions were
found:
• amitriptyline (arrhythmias or COPD) n = 10,
• clopidogrel, aspirin (receiving anticoagulant therapy) n = 5,
• metoclopramide, clozapine (Parkinson’s disease) n = 4,
• terazosine (arrhythmias) n = 2,
• medazepam, alprazolam (depression) n = 2,
• diazepam (COPD) n = 1,
• amlodipine (chronic constipation) n = 1.
Drug characteristics associated with
inappropriateness:
RX and OTC drugs (nRX+OTC = 5,436) were included in
the statistical analysis. From all RX drugs (n = 4,459), 124
were inappropriate (2.8%), and from the OTC drugs (n =
977), 20 were inappropriate (2%). There was no statistical
association between prescription status and inappropriateness (φ = 0.0171, P = 0.2083).
Patients’ characteristics
For dichotomising the age variable and the number of
taken active substances, the median split was applied. Three
hundred and seventy-nine patients were younger than 81
years and the remaining patients were in the group of 81
years or older. We did not find statistical relevant associations between age, gender and the intake of PIM (age: φ
= 0.0018, P = 0.9603; gender: φ = 0.0791, P = 0.0310). An
association with a small effect size was found for the
number of regularly taken active substances (φ = 0.1808; P
< 0.001).
Table 2. Number of PIMs and prescription status (groups categorised according to the ATC classification; in brackets:
found active substances)
All drugs are
available on
prescription only
All drugs are
available as
OTC drugs
Prescription
status depends
on the dosage,
pharmaceutical
form, indication
All
....................................................................................
Benzodiazepine derivatives (diazepam, nitrazepam, medazepam, alprazolam, temazepam)
Non-selective monoamine reuptake inhibitors (amitriptyline, doxepin)
Antihistamines for systemic use (promethazine, diphenhydramine, doxylamine)
Dihydropyridine derivatives (nifedipine)
Alpha-adrenoreceptor antagonists (doxazosin, terazosin)
Contact laxatives (sodium picosulfate, bisacodyl, aloe)
Acetic acid derivatives and related substances (indometacin)
Propionic acid derivatives (naproxen)
Platelet aggregation inhibitors excl. heparin (aspirin, clopidogrel)
Nitrofuran derivatives (nitrofurantoin)
Substituted alkylamines (dimetindene)
Propulsives (metoclopramide)
Anti-arrhythmics, class III (amiodarone)
Belladonna alkaloids, semisynthetic, quaternary ammonium compounds
(butylscopolamine)
Other centrally acting agents (tetrazepam)
Oxicams (piroxicam)
Salicylic acid and derivatives (aspirin)
Diazepines, oxazepines and thiazepines (clozapine)
Selective serotonin reuptake inhibitors (fluoxetine)
Phenothiazines with piperidine structure (thioridazine)
Imidazoline receptor agonists (clonidine)
All
45 (36.6%)
29 (23.6%)
10 (8.1%)
14 (10.6%)
10 (8.1%)
NR
NR
NR
1 (0.8%)
4 (3.3%)
NR
3 (2.4%)
2 (1.6%)
NR
NR
NR
2 (10%)
NR
NR
10 (50%)
NR
NR
3 (15 %)
NR
4 (20%)
NR
NR
NR
NR
NR
5 (16.3%)
NR
NR
NR
6 (31.6%)
5 (26.3%)
NR
NR
NR
NR
NR
2 (10.5%)
45 (27.8%)
29 (17.9%)
17 (10.4%)
14 (8%)
10 (6.2%)
10 (6.2%)
6 (3.7%)
5 (3.1%)
4 (2.5%)
4 (2.5%)
4 (2.5%)
3 (1.9%)
2 (1.2%)
2 (1.2%)
2 (1.6%)
NR
NR
1 (0.8%)
1 (0.8%)
1 (0.8%)
1 (0.8%)
124 (100%)
NR
NR
1 (5%)
NR
NR
NR
NR
20 (100%)
NR
1 (5.3%)
NR
NR
NR
NR
NR
19 (100%)
2 (1.2%)
1 (0.6%)
1 (0.6%)
1 (0.6%)
1 (0.6%)
1 (0.6%)
1 (0.6%)
163 (100%)
NR, not relevant.
69
T. Fiss et al.
Association between intake of inappropriate drugs
and DRP
There was a slight association with self-reported falls
during the last 12 months (φ = 0.1074, P = 0.0244). The
intake of PIM was not associated with the occurrence of
patient-reported ADR (φ = 0.0185, P = 0.6190). Possible
protective aspects such as the regular visit of a favourite
pharmacy (φ = −0.0238, P = 0.5184) or receiving support
in drug administration, e.g. by a relative or a home-care
nurse (φ = −0.0397, P = 0.2792), were not associated with
the intake of PIM. Details of the correlation analysis are
shown in Table 3.
A multivariate logistic regression model including age,
gender, number of taken active substances, receiving
support in drug administration and having a favoured pharmacy yielded significant results for number of taken substances (OR = 1.176; 95% CI 1.121–1.234, P < 0.001) (see
Supplementary data available in Age and Ageing online).
Discussion
We found a high proportion of PIM and a slight association between intake of PIM and self-reported falls in our
sample of elderly people who received regular home visits
by qualified practice assistants. According to Beers’ criteria,
all PIMs had serious relevance except for the intake of doxazosin or clonidine. In some cases (gender, occurrence of
ADR), we found statistically significant P-values without
clinical relevance (small φ-values). Multivariate analysis
identified the number of taken active substances as a predictive factor for the intake of PIMs.
Our results correspond well with the previous research.
The AdHoc studies in 11 European countries including
3,877 randomised chosen patients stated an average
prevalence of PIM of 20%, ranging from 41% in the Czech
Republic to 5.8% in Denmark [18, 19]. Lechevallier-Michel
et al. [20] reported a high prevalence in their Three-City
longitudinal study recruiting 9,294 patients aged >65.
Nearly 40% of the participants used at least one PIM—
23.4% took cerebral vasodilators, 9.2% long-acting benzodiazepines and 6.4% drugs with anticholinergic properties.
Furthermore, we showed a relevant proportion of OTC
drugs as inappropriate for this age group. Hence, the local
pharmacist should be encouraged to check potential inappropriateness before handing out OTC drugs.
As a drug–condition interaction, we found the intake of
several anticoagulant drugs, despite anticoagulant therapy
with Phenprocoumon. The German SPC contains an explicit warning addressing the combination of both drugs due
to an increased risk for gastric ulcer.
In the AGnES population with an age >65 years, the
proportion of DRP and falls was higher in the group taking
PIMs than in the group not taking Beers drugs. The
number of taken active substances was identified as a risk
factor for the intake of PIMs. Maio et al. [21] checked
patients’ medication in two outpatient settings and did not
find polypharmacotherapy as a predictor for the intake of
PIMs. Nevertheless, we have found a statistically significant
association in an ambulatory setting in a rural area. Hence,
there is a need to focus on polypharmacotherapy in this
setting. Additionally, another investigation has shown a
need to focus on PIM: Ryan et al. [22] calculated that
patients who take PIM produce net ingredient costs per
month of €824.88.
Gender narrowly missed statistical significance. This
may be caused by the selected sample. Nevertheless, a high
proportion of the identified benzodiazepines and neurological drugs were taken by women. There is a need for further
research to investigate the found correlation.
Table 3. Patient characteristics, DRPs and protecting factors which are potentially associated with the intake of PIM
Patients taking
one or more
PIM (n = 134)
Not taking
PIM
(n = 610)
134 (f: 108; m: 26)
Yes: 66 (49.3%)
Yes: 95 (70.9%)
610 (f: 436; m: 174)
Yes: 299 (48.8%)
Yes: 289 (47.4%)
Yes: 8 (6.3%)
Yes: 4 (3 %)
Yes: 15 (11.4%)
φ-valuea
P-valueb
....................................................................................
Patients factors
Sex (n = 744)
Age > 81 (median split; n = 744)
Number of regularly taken active substances > 7 (median split; n = 744)
Report of DRP
Occurrence of an ADR (n = 723c)
Conscious intermission of drug intake (n = 739c)
Self-reported forgetfulness in drug intake (n = 737c)
Factors that may prevent the intake of PIM
Patient receives support in drug administration (n = 743c)
Patient regularly visits a favourite pharmacy (n = 737c)
Other unwanted effects
Fall during last 12 months (a total of 439 patients received
falls anamneses whereof 75 received one or more PIM)
0.0791
0.0018
0.1808
0.0310
0.9603
<0.001
Yes: 31 (5.2%)
Yes: 37 (6.1%)
Yes: 39 (6.4%)
0.0185
−0.0506
0.0724
0.6190
0.1691
0.0495
Yes: 58 (43.3%)
Yes: 129 (97.7%)
Yes: 295 (48.4%)
Yes: 596 (98.5%)
−0.0397
−0.0238
0.2792
0.5184
Yes: 51 (68%)
Yes: 196 (53.8%)
0.1074
0.0244
φ-value is used for the correlation analysis of dichotomous data.
The range of φ is −1 to 0 to 1; a φ > 0.1 stands for a small effect (φ 0.3–0.5: medium effect; φ > 0.5: large effect).
b
Statistical significance does not necessarily mean that the association is relevant.
c
Different number of answers which were included in the analyses are due to excluding answers like ‘don’t know’.
a
70
Frequency of inappropriate drugs in primary care
The absence of statistical significance for DRPs such as
ADR in our analyses does not exclude that there might be
associations between PIM and health problems.
The high proportion of PIM may partly be explained by
factors specific for Germany. In Germany, prescription of
drugs is partly restricted by the statutory health insurances
which encourage the physicians to prescribe the so-called
leading substances. A very broad distributed list of leading
substances is the list of the Association of Statutory Health
Insurance Physicians-North Rhine [23]. Two examples for
PIM, which are leading substances, are amitriptyline and
doxazosine.
Furthermore, electronic prescribing systems may
enhance rational prescription procedures. In the AGnES
projects, an easy-to-use IT-supported system to detect
DRPs including PIM could be developed. Causality assessment tools such as the Naranjo criteria may help to optimise prescribing appropriateness in further investigations
[24].
In the case of inappropriate prescribing, the pharmacist
is not able to intervene due to information deficits in
Germany. Adding the diagnoses or the dosage to the prescription could enhance medication safety, too. Final check
for an inappropriate drug–condition interaction could be
conducted by the pharmacist using pharmaceutical software. Schaefer [25] has calculated that €5.1 billion could be
saved by using systematic drug documentation.
A problem in the analysis was that the Beers list contained several drugs which were not available in Germany.
This shows the need for a German adaption. Additionally,
there was no regard to special health conditions (renal diseases). A possible adaption to the German market should
be augmented with operable definitions (‘long-acting
benzodiazepines’, ‘anticholinergic drug’). A practical solution would be a database comprising all indications and
contraindications of all active substances available on the
national market. The database should be qualified and regularly updated by the drug regulatory authorities and should
be made available for use in primary health care as well as
for research.
the presence or absence of DRPs. Their degree of multimorbidity, immobility, polypharmacotherapy and proportion
of home care may be similar to other samples of chronically ill older patients [27]. Hence, results obtained in this
sample may well extend to patients with similar
characteristics.
Conclusions
The large proportion of PIM as classified by Beers criteria in our analysis underlines the need for increased
attention on the medication therapy of older people in
the primarycare setting. It is reassuring that there was
no strong association between the intake of Beers drugs
and the occurrence of DRP. Nevertheless, our results
suggest that there is a need for an optimization of prescription procedures in primary health care. Specific
PIM lists for Germany should be implemented in which
national specifics are considered and low threshold
access should be provided to all professions involved in
primary care. The implementation of systematic medication review and drug documentation should be
extended and standardised both in research studies and
routine primary health care.
Key points
• DRPs including PIM jeopardise drug therapy.
• The manuscript reports on a high proportion of patients
receiving inappropriate medication (RX and OTC).
• Detection of PIM use was shown as feasible.
• The presented results close knowledge gap due to including much information which was collected in patients’
domicile.
Supplementary data
Strengths and limitations
Strengths of this study were the comprehensive and standardised record of all drugs (including RX and OTC) in
the patients’ homes and the high response in a communitybased setting. Owing to additional information such as
diagnoses and fall history, we could close an information
gap for this group of patients.
Limitations include the fact that the AGnES study
population may not be representative for all drug consumers in Germany. Furthermore, detailed interpretation and
generalization is limited due to small numbers in every
DRP.
By applying personal interviews, we may have an underreporting of falls [26] and ADR. However, the patients
were not sampled on the basis of their medication or on
Supplementary data mentioned in the text is available to
subscribers in Age and Ageing online.
Acknowledgements
We are grateful to all local pharmacies, GPs and AGnES
practice assistants for their active role in the implementation
of pharmaceutical care. No less we wish to thank all participating patients for their continuous cooperation and valuable advice. We are grateful to the GSF scientific centre
Neuherberg for licensing the IDOM database and the
AOK Research Institute (WidO) for licensing the German
Drug Index.
71
T. Fiss et al.
Conflicts of interest
The study sponsors did not have any involvement in conducting the study. The authors declare no conflict of
interests.
11.
12.
Funding
The AGnES projects were funded by the following institutions: Ministry of Health of the Federal State of
Mecklenburg-Western Pomerania, the Ministry for Labour,
Social Affairs, Health and Family of the Federal State of
Brandenburg, the Saxony State Ministry of Social Affairs,
the Ministry of Health and Social Affairs of the Federal
State Saxony-Anhalt, the Regional Association of Statutory
Health Insurance Physicians, various regional Statutory
Health Insurances and the European Social Fund. T.F. is
supported by a research fellowship granted by the German
National Academic Foundation (Studienstiftung des
Deutschen Volkes).
13.
14.
15.
16.
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Leukocyte telomere length and marital status
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Received 2 March 2010; accepted in revised form 2 June
2010
Age and Ageing 2011; 40: 73–78
© The Author 2010. Published by Oxford University Press on behalf of the British Geriatrics Society.
doi: 10.1093/ageing/afq118
All rights reserved. For Permissions, please email: [email protected]
Published electronically 4 September 2010
Leukocyte telomere length and marital status
among middle-aged adults
ARCH G. MAINOUS III1, CHARLES J. EVERETT1, VANESSA A. DIAZ1, RICHARD BAKER2, MASSIMO MANGINO4,
VERYAN CODD3, NILESH J. SAMANI3
1
Medical University of South Carolina, Family Medicine, 295 Calhoun Street, Charleston, SC 29425, USA
Department of Health Sciences and 3Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
4
Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK
2
Address correspondence to: A. G. Mainous. Tel: (+1) 843 792 6986; Fax: (+1) 843 792 3598. Email: [email protected],
[email protected]
Abstract
Background: being unmarried is associated with worse health and increased mortality risk. Telomere length has emerged
as a marker for biological ageing but it is unclear how telomere length relates to marital status.
Objective: to examine the relationship between telomere length and marital status in a sample of middle-aged adults.
Design and subjects: cross-sectional analysis among 321 adults aged 40–64 years.
Methods: telomere length was measured by PCR (T/S ratio). Participants provided information on healthy lifestyle activities including smoking, alcohol use, diet, exercise, obesity as well as social support.
Results: participants married or living with a partner had a mean T/S ratio of 1.70 and those widowed, divorced, separated
or never married had a mean T/S ratio of 1.58 in a model adjusted for age, gender and race/ethnicity (P < 0.001). When the
analysis was further adjusted for diet, alcohol consumption, exercise, smoking, social support, poverty and obesity, persons
married or living with a partner had a higher mean T/S ratio of 1.69 than their unmarried counterparts (1.59) (P = 0.004).
Conclusions: these results indicate that unmarried individuals have shorter telomeres. This relationship between marital status
and telomere length is independent of presumed benefits of marriage such as social support and a healthier lifestyle.
Keywords: telomere, marital status, lifestyle, elderly
Introduction
Chronological ageing is associated with the risk of development of a variety of diseases. Yet, chronological ageing
does not exactly parallel biological ageing. Telomere length
has emerged as a marker for biological ageing which may
be a key to age-related morbidity [1]. Telomeres consist of
TTAGGG tandem repeats, and telomere-binding proteins
cap the ends of chromosomes and protect them from
degradation. Telomeres become progressively shorter with
each replication of somatic cells. Telomere attrition ultimately leads to a loss of replicative capacity. Systemic oxidative stress accelerates telomere shortening [2]. Further,
shortened telomere length has been associated with shorter
lifespan as well as a wide variety of ageing-related diseases
and conditions such as cardiovascular disease, diabetes,
dementia and hypertension [3–7]. It has been suggested
that inflammation and oxidative stress are key to the ageing
73