The importance of sex and age disaggregated data

Older adults, often described as those aged 65 years and above, have been seen as a largely homogenous category.1 The burden of disease and needs of older adults varies greatly within this large age category,2 highlighting the importance of finer age disaggregation. Various global policies and groups have stated the need for both age and sex disaggregated data to make older people more visible and to inform actions to improve their well-being.3 Despite these policies, a gap remains in considering the intersection of sex and age in health data collection and reporting. The lack of disaggregated sex and age data in health research makes it challenging to understand the unique needs of older women,4 impeding the development of equitable care for older adults. This study aimed to explore the importance of sex- and age-disaggregated data in health research. Publicly available data on the disease burden in Canada were used to help understand patterns associated with sex and how they relate to age. The burden of disease was estimated using disability-adjusted life years (DALYs), with one DALY representing the loss of the equivalent of 1 year of full health.5 We examined the number of DALYs per 100,000 population. Data describing the top 10 causes of DALYs in Canada in 2019, disaggregated by age and sex, were obtained from the World Health Organization (WHO).6 The year 2019 was the most recent year for which data were available. The WHO provided data disaggregated by five-year age groupings. We focused on two age groups, 65–69 and 85 years and older, to highlight the differences that may exist between younger older adults and older adults that are more advanced in age. The top 10 causes of DALYs varied depending on the age group (Figure 1A,B). For older adults aged 65–69, the top three causes of DALYs were ischemic heart disease, trachea, bronchus and lung cancers, and diabetes mellitus. For older adults aged 85 and over, the top three causes of DALYs were Alzheimer disease and other dementias, ischemic heart disease, and stroke. The magnitude of DALYs also varied by age group, with the highest DALYs seen in the 85 and over age group. The number one disease caused 3808 DALYs in the 65–69-year age group (Figure 1A) and 23,978 DALYs in the 85 and older age category (Figure 1B). The DALYs clearly differed between sexes for certain conditions. In the 85 years and over age category, men had 1550 (78%) more DALYs because of trachea, bronchus and lung cancers compared with women. For certain diseases, the differences between women and men varied across age groups (Table 1). In terms of ischemic heart disease, men and women began to converge in the number of DALYs: men had 177% greater DALYs compared with women in the 65–69 year age category, but only 21% greater in the 85 years and over age category. This study demonstrates the importance of collecting and analyzing sex and age disaggregated data. As shown in Figure 1A, B, as individuals age there is a shift in the disease burden. The diseases that most impact older adults in the 65–69 years age category are not the same as in the 85-years and over age category. For example, Alzheimer's disease and other dementias is not one of the top 10 causes of DALYs in the 65–69 year age grouping, but becomes the number one cause in the 85-year and over age category. Data disaggregation by five-year age groupings allows for these differences among older adults to be made visible, which can help support decision-making and planning. In addition, the DALYs caused by a particular disease differ between men and women, further suggesting that older adults are not a homogenous group and that sex-specific patterns of morbidity, mortality, and health risks exist. The percent difference in DALYs between men and women changed between age groups for certain diseases, highlighting the interplay between sex and age. It is clear that important differences are lost if a study aggregates all older adults into a large 65-years and over age category. We recommend that all researchers collect and analyze health data in a manner that allows for sex and age disaggregation. We support health data disaggregation by five-year age groupings for older ages, which has also been recommended by other researchers.2 Developing best practices for collecting and analyzing health data should be a priority to ensure people remain visible as they age and to support evidence-based policy. Natalie Palumbo, Shereen Khattab, Andrea Lawson and Paula A Rochon were involved in the conception and design of the study. Natalie Palumbo and Shereen Khattab analyzed the data and drafted the manuscript. All authors reviewed, edited, and approved the final manuscript. The authors also thank Wei Wu for providing statistical analysis support for this project. The authors declare that there is no conflict of interest. This work has no associated funding. Dr. Rochon holds the RTOERO Chair in Geriatric Medicine at the University of Toronto.

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