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A Comparison of Sex Differences in Psychotropic Medication Use in Older People with Alzheimer’s Disease in the US and Finland

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Abstract

Aims

Given the high prevalence of psychotropic medication use in people with dementia and the potential for different prescribing practices in men and women, our study aimed to investigate sex differences in psychotropic medication use in older adults with Alzheimer’s disease (AD) living in the US and Finland.

Methods

We used data collected between 2005 and 2011 as part of the National Alzheimer’s Coordinating Center (NACC) in the US, and Medication use and Alzheimer’s disease (MEDALZ) cohorts in Finland. We evaluated psychotropic medication use (antidepressant, antipsychotic, anxiolytic, sedative, or hypnotic) in participants aged 65 years or older. We employed multivariable logistic regression adjusted for demographics, co-morbidities, and other medications to estimate the magnitude of the association (adjusted odds ratio [aOR] with 95% confidence intervals [CIs]) according to sex.

Results

We included 1099 NACC participants (502 [45.68%] men, 597 [54.32%] women), and 67,049 participants from the MEDALZ cohort (22,961 [34.24%] men, 44,088 [65.75%] women). Women were more likely than men to use psychotropic medications: US, 46.2% vs. 33.1%, p < 0.001; Finland, 45.3% vs. 36.1%, p < 0.001; aOR was 2.06 (95% CI 1.58–2.70) in the US cohort and 1.38 (95% CI 1.33–1.43) in the Finnish cohort. Similarly, of the different psychotropic medications, women were more likely to use antidepressants (aOR-US: 2.16 [1.44–3.25], Finland: 1.52 [1.45–1.58]) and anxiolytics (aOR-US: 2.16 [1.83–3.96], Finland: 1.17 [1.13-1.23]) than men.

Conclusion

Older women with AD are more likely to use psychotropic medications than older men, regardless of study population and country. Approaches to mitigate psychotropic medication use need to consider different prescribing habits observed in older women vs. men with AD.

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Author contributions

DM: study concept and design, acquisition of data, data analysis and interpretation, and preparation and editing of manuscript. HT: study concept and design, acquisition of data, data analysis and interpretation, and preparation and editing of manuscript. AMT: acquisition of data and interpretation, critical revising of the manuscript for important intellectual content, and final approval of the version to be published. AT: acquisition of data and interpretation, critical revising of the manuscript for important intellectual content, and final approval of the version to be published. JT: acquisition of data and interpretation, critical revising of the manuscript for important intellectual content, and final approval of the version to be published. SH: study concept and design, acquisition of data, data analysis and interpretation, and preparation and editing of manuscript. QW: data analysis, critical revising of the manuscript for important intellectual content, and final approval of the version to be published. GJ: study concept and design, interpretation of study findings, critical revising of the manuscript for important intellectual content, and final approval of the version to be published. DG: study concept and design, interpretation of findings, and preparation and editing of manuscript.

Author information

Authors and Affiliations

  1. Department of Pharmacy Practice and Science, College of Pharmacy, University of Kentucky, Room 241, 789 South Limestone Street, Lexington, KY, 40536-0596, USA

    Daniela C. Moga

  2. Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, KY, USA

    Daniela C. Moga & Qishan Wu

  3. Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, USA

    Daniela C. Moga & Gregory A. Jicha

  4. School of Pharmacy, University of Eastern Finland, Kuopio, Finland

    Heidi Taipale, Anna-Maija Tolppanen & Sirpa Hartikainen

  5. Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden

    Heidi Taipale, Antti Tanskanen & Jari Tiihonen

  6. Department of Forensic Psychiatry, University of Eastern Finland, Niuvanniemi Hospital, Kuopio, Finland

    Antti Tanskanen & Jari Tiihonen

  7. Department of Psychiatry, Kuopio University Hospital, Kuopio, Finland

    Sirpa Hartikainen

  8. Department of Neurology, College of Medicine, University of Kentucky, Lexington, KY, USA

    Gregory A. Jicha

  9. Faculty of Pharmacy and Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia

    Danijela Gnjidic

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  1. Daniela C. Moga
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  2. Heidi Taipale
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  9. Danijela Gnjidic
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Corresponding author

Correspondence to Daniela C. Moga.

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Funding

This work was supported by Grant No. K12 DA035150 (Building Interdisciplinary Research Careers in Women’s Health) from the National Institutes of Health, Office of Women’s Health Research and the National Institute on Drug Abuse (DM) and National Health and Medical Research Early Career Fellowship (DG).

The NACC database is funded by the National Institute on Aging (NIA)/National Institutes of Health (NIH) Grant U01 AG016976. NACC data are contributed to by the NIA-funded ADCs: P30 AG019610 (PI Eric Reiman, MD), P30 AG013846 (PI Neil Kowall, MD), P50 AG008702 (PI Scott Small, MD), P50 AG025688 (PI Allan Levey, MD, PhD), P50 AG047266 (PI Todd Golde, MD, PhD), P30 AG010133 (PI Andrew Saykin, PsyD), P50 AG005146 (PI Marilyn Albert, PhD), P50 AG005134 (PI Bradley Hyman, MD, PhD), P50 AG016574 (PI Ronald Petersen, MD, PhD), P50 AG005138 (PI Mary Sano, PhD), P30 AG008051 (PI Steven Ferris, PhD), P30 AG013854 (PI M. Marsel Mesulam, MD), P30 AG008017 (PI Jeffrey Kaye, MD), P30 AG010161 (PI David Bennett, MD), P50 AG047366 (PI Victor Henderson, MD, MS), P30 AG010129 (PI Charles DeCarli, MD), P50 AG016573 (PI Frank LaFerla, PhD), P50 AG016570 (PI Marie-Francoise Chesselet, MD, PhD), P50 AG005131 (PI Douglas Galasko, MD), P50 AG023501 (PI Bruce Miller, MD), P30 AG035982 (PI Russell Swerdlow, MD), P30 AG028383 (PI Linda Van Eldik, PhD), P30 AG010124 (PI John Trojanowski, MD, PhD), P50 AG005133 (PI Oscar Lopez, MD), P50 AG005142 (PI Helena Chui, MD), P30 AG012300 (PI Roger Rosenberg, MD), P50 AG005136 (PI Thomas Montine, MD, PhD), P50 AG033514 (PI Sanjay Asthana, MD, FRCP), P50 AG005681 (PI John Morris, MD), and P50 AG047270 (PI Stephen Strittmatter, MD, PhD).

Conflict of interest

HT participated in research projects funded by Janssen with grants paid to an employer institution outside of this work. AT participated in research projects funded by Janssen with grants paid to Karolinska Institutet outside of this work. JT has served as a consultant to Lundbeck, Organon, Janssen-Cilag, Eli Lilly, AstraZeneca, F. Hoffman-La Roche, and Bristol-Myers Squibb, and has received fees for giving expert opinions to Bristol-Myers Squibb and GlaxoSmithKline, lecture fees from Janssen-Cilag, Bristol-Myers Squibb, Eli Lilly, Pfizer, Lundbeck, GlaxoSmithKline, AstraZeneca, and Novartis; and a grant from Stanley Foundation. JT is a member of the advisory boards for AstraZeneca, Janssen-Cilag, and Otsuka. SH received lecture fees from MSD and Professio for providing lectures concerning medications in old age. DM, AMT, QW, GJ and DG declare no conflicts of interest.

Ethical approval

Cohort data use was approved by local ethics committees at each institution and owing to the de-identified nature of the data included in our current study, informed consent was waived. Specifically, for the US data, the Alzheimer’s Disease Research Center Clinical/Research Core protocol was approved by the Institutional Review Board of the University of Kentucky. Ethics committee approval was not required for the MEDALZ cohort according to Finnish legislation as only register-based data were used and persons were not contacted.

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Moga, D.C., Taipale, H., Tolppanen, AM. et al. A Comparison of Sex Differences in Psychotropic Medication Use in Older People with Alzheimer’s Disease in the US and Finland. Drugs Aging 34, 55–65 (2017). https://doi.org/10.1007/s40266-016-0419-5

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