The Association Between Drug Burden Index (DBI) and Health-Related Outcomes: A Longitudinal Study of the ‘Oldest Old’ (LiLACS NZ)
The prescribing of medications with anticholinergic and/or sedative properties is considered potentially inappropriate in older people (due to their side-effect profile), and the Drug Burden Index (DBI) is an evidence-based tool which measures exposure to these medications. Life and Living in Advanced Age: a Cohort Study in New Zealand (LiLACS NZ) is an ongoing longitudinal study investigating the determinants of healthy ageing. Using data from LiLACS NZ, this study aimed to determine whether a higher DBI was associated with poorer outcomes (hospitalisation, falls, mortality and cognitive function and functional status) over 36 months follow-up.
LiLACS NZ consists of two cohorts: Māori (the indigenous population of New Zealand) aged ≥ 80 years and non-Māori aged 85 years at the time of enrolment. Data relating to regularly prescribed medications at baseline, 12 months and 24 months were used in this study. Medications with anticholinergic and/or sedative properties (i.e. medications with a DBI > 0) were identified using the Monthly Index of Medical Specialities (MIMS) medication formulary, New Zealand. DBI was calculated for everyone enrolled at each time point. The association between DBI at baseline and outcomes was evaluated throughout a series of 12-month follow-ups using negative binomial (hospitalisations and falls), Cox (mortality) and linear (cognitive function and functional status) regression analyses (significance p < 0.05). Regression models were adjusted for age, gender, general practitioner (GP) visits, socioeconomic deprivation, number of medicines prescribed and one of the following: prior hospitalisation, history of falls, baseline cognitive function [Modified Mini-Mental State Examination (3MS)] or baseline functional status [Nottingham Extended Activities of Daily Living (NEADL)].
Full demographic data were obtained for 671, 510 and 403 individuals at baseline, 12 months and 24 months, respectively. Overall, 31%, 30% and 34% of individuals were prescribed a medication with a DBI > 0 at baseline, 12 months and 24 months, respectively. At baseline and 12 months, non-Māori had a greater mean DBI (0.28 ± 0.5 and 0.27 ± 0.5, respectively) compared to Māori (0.16 ± 0.3 and 0.18 ± 0.5, respectively). At baseline, the most commonly prescribed medicines with a DBI > 0 were zopiclone, doxazosin, amitriptyline and codeine. In Māori, a higher DBI was significantly associated with a greater risk of mortality: at 36 months follow-up, adjusted hazard ratio [95% confidence interval (CI)] 1.89 (1.11–3.20), p = 0.02. In non-Māori, a higher DBI was significantly associated with a greater risk of mortality [at 12 months follow-up, adjusted hazard ratio (95% CIs) 2.26 (1.09–4.70), p = 0.03] and impaired cognitive function [at 24 months follow-up, adjusted mean difference in 3MS score (95% CIs) 0.89 (− 3.89 to − 0.41), p = 0.02).
Using data from LiLACS NZ, a higher DBI was significantly associated with a greater risk of mortality (in Māori and non-Māori) and impaired cognitive function (in non-Māori). This highlights the importance of employing strategies to manage the prescribing of medications with a DBI > 0 in older adults.
We thank all the participants and their whanau/families for their time and contribution to the principal study. The Rōpū Kaitiaki (Hone Kameta, Florence Kameta, Betty McPherson, Te Kaanga Skipper, Paea Smith and Laiana Reynolds) oversaw the project from feasibility and throughout recruitment. Elizabeth Robinson guided the biostatistical planning, and Rudi Westendorp gave advice at the planning stages.
Compliance with Ethical Standards
Funding was provided by Department for Employment and Learning, Northern Ireland.
Conflict of interest
KC, NK, CR, RT, SM, OM, AR, JB and CH declare that they have no conflict of interest. This current analysis was supported by the Department for Employment and Learning (DEL), Northern Ireland, through a postgraduate studentship to KC. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.
- 15.Hayman KJ, Kerse N, Dyall L, Kepa M, Teh R, Wham C, et al. Life and Living in advanced age: a cohort study in New Zealand-Te Puāwaitanga o Nga Tapuwae Kia Ora Tonu, LiLACS NZ: study protocol. BMC Geriatr. 2012;12(33):1.Google Scholar
- 16.Stats NZ Tatauranga Aotearoa. Māori population estimates: At 30 June 2018 [Internet]. Wellington: Stats NZ Tatauranga Aotearoa; 2018. https://www.stats.govt.nz/information-releases/maori-population-estimates-at-30-june-2018. Accessed 15 Nov 2019.
- 20.The Best Practice Advocacy Centre New Zealand. History of rongoā Māori [Internet]. Dunedin: The Best Practice Advocacy Centre New Zealand. https://bpac.org.nz/bpj/2008/may/docs/bpj13_rongoa_pages_32-36.pdf. Accessed 15 Nov 2019.
- 22.Salmond C, Crampton P. NZDEP96-what does it measure? Soc Policy J N Z. 2001;17:82–100.Google Scholar
- 23.MIMS New Zealand Ltd. MIMS New Zealand [Internet]. Auckland: MIMS New Zealand Ltd. http://www.mims.co.nz/. Accessed 15 Nov 2019.
- 24.World Health Organization Collaborating Centre for Drug Statistics Methodology [Internet]. Oslo: World Health Organization Collaborating Centre for Drug Statistics Methodology; 2017. ATC/DDD Index 2017; 2016 Dec 19. http://www.whocc.no/atc_ddd_index/. Accessed 15 Nov 2019.
- 37.Pitama S, Huria T, Lacey C. Improving Māori health through clinical assessment: Waikare o te Waka o Meihana. N Z Med J. 2014;127:1393.Google Scholar
- 38.Ministry of Health. The Health of Māori Adults and Children [Internet]. Wellington: Ministry of Health; 2013. http://www.health.govt.nz/system/files/documents/publications/health-maori-adults-children-summary.pdf. Accessed 15 Nov 2019.
- 44.Wilkinson S, Mulder RT. Antipsychotic prescribing in New Zealand between 2008 and 2015. N Z Med J. 2018;131:1480.Google Scholar