Visualizing Cognitive Disability Trends in the United States


Charts & Graphs, Lab Reports, Visualization

Background

Cognition is defined as “the mental action or process of acquiring knowledge and understanding through thought, experience, and the senses” and involves functions and processes such as attention, memory, decision-making, perception, reasoning, and many more (Dhakal & Bobrin, 2022). Impairment in any of the different domains of cognition leads to a cognitive deficit. There are a range of biological and social environmental factors that may lead to cognitive impairment, such as mental illness, neurological disorders, malnutrition, brain injury, chronic diseases, frequent use of technology, social isolation, socioeconomic status, etc. Additionally, cognitive abilities across multiple domains such as memory and processing speed decline gradually with age (Levine et al., 2021), and the rate of decline differs between males and females (McCarrey et al., 2016). 

The American Community Survey (ACS) explores impairment in three domains of cognition: concentration, memory, and decision-making, which are grouped together to determine cognitive disability status in the United States across two measurements (sex and age group). 

The purpose of this study is to visualize trends in cognitive disability across both sex and age group in the United States, and determine whether there is a significant change in the prevalence of cognitive disability over time.

Materials & Methods

The ACS determines disability status through a six question questionnaire covering different types of disabilities including: hearing, vision, cognitive, ambulatory, self-care, and independent living difficulties. These questions focus on the impact specific conditions might have on basic functioning, unlike the 2000 Census which solely focused on the presence of these conditions. Respondents are considered to have a disability if they indicate having any one of these difficulties in the questionnaire. 

This study will focus on the cognitive disability measurement, which is determined by the respondent’s answer to the following question from the disability questionnaire: 

Because of a physical, mental, or emotional condition, do you have serious difficulty concentrating, remembering, or making decisions? (5 years old or older)

a. ____ Yes

b. ____ No

Cognitive disability data was collected through the United States Census Bureau, specifically the ACS-1 Year estimates in the category Sex by Age by Cognitive Difficulty (Table ID: C18104). Since the data is subcategorized only by Sex (Male, Female) and Age Group (5-17 years, 18-34 years, 35-64 years, 65-74 years, and 75+ years), the prevalence of a cognitive disability is analyzed based on these demographic measurements. 2010 was chosen as the starting point for data collection as it is the first year this dataset is available, and 2021 is the cut-off for data collection as it is the most recent dataset available. 

Since the terms “cognitive difficulty” and “cognitive disability” are synonymous, they will be used interchangeably throughout this study.

The datasets for Sex by Age by Cognitive Difficulty between 2010 to 2021 were imported into Microsoft Excel for analysis. Since the datasets had total counts for individuals with and without cognitive difficulty within each subcategory (Sex and Age Group), the data on individuals with cognitive difficulties for each sex-age group combination were queried for certain visualizations. Five separate data visualizations were created with this data:

Figure 1:

From the queried dataset, the count of females and males with cognitive difficulty were summed for each age group to find the total count of cognitive difficulty across age groups. This was done for every year between 2010-2021, except for 2020. ACS data on cognitive difficulty is missing for the year of 2020, and so the total count within each age group in 2020 is estimated based on the trend line connecting the total counts in 2019 and 2021. The calculated data was imported into Tableau Desktop as a .csv file to create a line chart visualizing the change of cognitive difficulty over time across age groups. 

Figure 2: 

Data on the sex measurement was combined across the relative age groups to create an aggregated dataset focusing on the age measurement alone. The percentage point change was first calculated by finding the percentage of people with cognitive difficulty in each age group out of the total count of people within the respective age group (i.e. sum of 5 to 17 year old males and females with cognitive difficulty / total number of 5 to 17 year old males and females). Then, the percent change was calculated between each of these percentages in 2010 and 2021 to get the percentage point change for each age group. This was the chosen method – as opposed to calculating the percent change between 2010 to 2021 for the count of each sex-age group cohort – because it controls for changes in population size. This reasoning applies to Figure 3 as well. The calculated data was imported into Tableau Desktop as a .csv file to create a bar chart visualizing the percentage point change of cognitive difficulty across age groups from 2010 to 2021. 

Figure 3:

This figure illustrates a more detailed break-down of cognitive difficulty across both sex and age group, as opposed to Figure 2 which visualizes data on the age group measurement alone. The percentage point change was first calculated by finding the percentage of males with cognitive difficulty in each age group and females with cognitive difficulty in each age group in 2010 and 2021 (i.e. count of 5 to 17 year old males with a cognitive difficulty / the total number of 5 to 17 year old males). Then, the percent change was calculated between each of these percentages in 2010 and 2021 to get the percentage point change for each sex-age group cohort. The calculated data was imported into Tableau Desktop as a .csv file to create a grouped bar chart visualizing the percentage point change of cognitive difficulty across each sex-age group cohort from 2010 to 2021. 

Figure 4:

This visualization is based on the total cognitive disability population in the U.S. during the year of 2021. The Age Group dimension, which includes all five age groups, was queried in Tableau Desktop from the initial queried dataset created in Microsoft Excel. Then, the Measure Values were filtered to include the cognitive disability count for each sex within their respective age groups. The result is a stacked bar chart visualizing the total count of males and females with a cognitive disability in 2021 within their respective age groups. 

Figure 5:

To visualize the distribution of cognitive difficulty in the most recent dataset available (2021), the percentage of people within each sex-age group cohort with a cognitive disability was calculated out of the total number of people with cognitive difficulty. The calculated data was imported into Tableau Desktop as a .csv file to create a tree map visualizing the percent distribution of cognitive difficulty across each sex-age group cohort in 2021. 

Results

Figure 1: Line chart visualizing the change in the total number of people with cognitive difficulty over time (2010 to 2021) across all five age groups.

 

The 35 to 64 year old age group has the highest age range compared to other age groups, and thus the highest population size across every dataset. This is likely why 35 to 64 year olds have a significantly higher count of people with cognitive difficulty compared to any other age group. As demonstrated in this graph, every age group – except for 75+ year olds – experienced an increase in the total number of people with a cognitive disability from 2010 to 2021. Additionally, cognitive disability began increasing at a higher rate in these four age groups around 2018, especially within the 18 to 34 year old age group. Since the percentage of 65 to 74 year olds with a cognitive disability actually decreased from 2010 to 2021 (as seen in Figures 2 and 3), this age group likely has the highest count of people with cognitive disability in 2021 due to overall increase in population size over time. 

The average life expectancy in the U.S. ranged between 78.54 in 2010 to 77.28 in 2020. In 2021, the average life expectancy (76.1) decreased to its lowest level since 1996 (CDC’s National Health Center for Health Statistics, 2022). This may explain why the 75+ year old age group had a steadier count of people with a cognitive disability over time until the last few years. As mentioned in the Methods section, data is missing for 2020, and so the total counts for this year are estimated based on the data in 2019 and 2021. According to the CDC’s National Center for Health Statistics, the “declines in life expectancy since 2019 are largely driven by the pandemic. COVID-19 deaths contributed to nearly three-fourths or 74% of the decline from 2019 to 2020 and 50% of the decline from 2020 to 2021.” Thus, despite the missing 2020 data, this figure likely illustrates a close representation of the decline in the number of people ages 75 and up with cognitive disability from 2019 to 2021.

Based on the 2021 data on cognitive disability, the 75+ year old age group has the highest percentage of people with cognitive disability (12.2%), compared to 4.63% of 5 to 17 year olds, 5.03% of 18 to 34 year olds, 4.79% of 35 to 64 year olds, and 5.07% of 65 to 74 year olds. This confirms the current literature that cognitive impairment is more prominent in the elder community due to age-related cognitive decline. 

Figure 2: Bar chart visualizing the percentage point change of cognitive disability in the U.S. by age group from 2010 to 2021.

Put simply, Figure 2 visualizes the extent of change between the percentage of cognitive disability in 2021 compared to 2010 within each age group. The percentage of people with a cognitive disability changed considerably for each age group except for 35 to 64 year olds. Due to the improvement of physiological and psychological interventions for age-related cognitive decline over time, this might explain why the percentage of the elderly population (65 years and older) with a cognitive disability decreased from 2010 to 2021. Additionally, there is a significant increase in the percentage of 5 to 17 year olds with cognitive disability from 2010 to 2021, even more so among 18 to 34 year olds. There are a variety of factors that may explain these trends, such as the rise of mental health issues and frequent engagement with social media, especially among adolescents and young adults.

After visualizing significant differences across age groups alone (Figure 2), this raised curiosity on how sex-related differences contributed to these trends. 

Figure 3: Grouped bar chart visualizing the percentage point change of cognitive disability from 2010 to 2021 across each sex-age group cohort.

Out of the total U.S. population that was surveyed by the ACS, 4.85% had a cognitive disability in 2010. Although the cognitive disability population only increased by 0.51% over the course of 11 years (5.36% in 2021), the distribution of the cognitive disability population changed dramatically across the majority of the sex-age group cohorts (as seen in Figure 3). According to Figure 3, females experienced higher percentage point change in cognitive disability across all age groups compared to males: a higher percentage point increase in three age groups (5 to 17 years, 18 to 34 years, and 35 to 64 years) and a higher percentage point decrease in two age groups (65 to 74 years and 75+ years). To elaborate, there is a higher percentage of females than males with a cognitive disability between the ages 5 to 64 in 2021 compared to 2010, and a lower percentage of females than males with a cognitive disability ages 65 and up in 2021 compared to 2010. 

Figure 4: Stacked bar chart visualizing the total count of people with a cognitive disability in 2021 across both sex and age group.

The distribution of cognitive disability differs between males and females within each age group. Across the middle three age groups (18 to 34 years, 35 to 64 years, and 65 to 74 years) the percentage of males and females with a cognitive disability is split almost evenly between the two. However, the percentage of males with a cognitive disability in the 5 to 17 year age group (~64.9%) is significantly higher than females within the same age group (~35.1%). This is likely because females tend to establish brain connectivity at an earlier age than males, and are generally more cognitively advanced at a young age (Lim, S., Han, C. E., Uhlhaas, P. J., & Kaiser, M., 2015). 

According to Figures 1 and 4, the total number of people with a cognitive disability in the 5 to 17 year age group is similar to the 75+ year age group, despite only 4.63% of 5 to 17 year olds having a cognitive disability compared to 12.2% of 75+ year olds. This is because the 5 to 17 year age group accounts for a significantly higher percentage of the total U.S. population compared to the 75+ year age group (Duffin, 2022). 

The 65 to 74 year age group accounts for the second lowest percentage of the entire U.S. population after the 75+ year age group (Duffin, 2022), and yet, according to Figures 1 and 4, the 65 to 74 year age group has the lowest count of people with a cognitive disability. Additionally, only 5.07% of 65 to 74 year olds have a cognitive disability compared to 12.2% of 75+ year olds. Thus, the prevalence of a cognitive disability increases dramatically after age 75. However, females seem to contribute to this sudden shift more than males, as cognitive disability is distributed almost evenly between males and females in the 65 to 74 year age group, whereas the percentage of females with a cognitive disability in the 75+ year age group (~62.0%) is significantly higher than males (~38%). Current literature suggests that “women have greater cognitive reserve but faster later-life cognitive decline than men” and “women are at risk for delayed identification of cognitive decline, yet more rapid trajectory of decline, suggesting increased risk of dementia and disability compared with men” (McCarrey et al., 2016). This might explain why females are the main contributing factor to the significantly higher prevalence of cognitive disability in 75+ year olds compared to 65 to 74 year olds, despite 75+ year olds having the lowest overall population in the U.S.

Figure 5: Tree map visualizing the percentage breakdown of the entire cognitive disability population in the U.S. in 2021. Darker colors and larger boxes indicate that the sex-age group cohort accounts for a higher percentage of the cognitive disability population and vice versa. 

As mentioned previously, 5.36% of the entire surveyed population in the U.S. had a cognitive disability in 2021. Figure 5 illustrates the percentage breakdown of each sex-age group cohort within this 5.36% of the population. Thus, it is a similar representation of the data illustrated in Figure 4, but through percentages rather than total count.

Discussion

Presence of a cognitive disability is determined by the answer to a simple yes or no question on the American Community Survey’s disability questionnaire. This creates a limitation in the interpretation of the data, as current literature evaluates cognitive abilities through lab-based measurements, and further breaks down the level of cognitive impairment by the different domains of cognition – as opposed to the ACS disability questionnaire which groups together three domains. 

If the ACS added different measurements to their cognitive disability survey, aside from current sex and age group measurements, this would allow for further large-scale trends to be visualized. Additionally, including more domains of cognition – aside from concentration, memory, and decision-making in the current ACS disability questionnaire – and breaking them down into different questions would allow for correlations to be made between the impact of certain biological and social environmental factors on different cognitive domains. 

Moreover, the age group breakdown by the ACS is incredibly confusing, as certain age groups include a higher range of ages than others. Their method of age breakdown creates a limitation in finding reasoning to age-related factors on cognitive disability. 

Current research has shown that frequent use of digital technologies and social media platforms can decrease attention span and short-term memory (Firth et al., 2020), heighten symptoms of ADHD, impact brain development, and increase social isolation (Small et al., 2020). Social isolation in itself can increase the risk of disabilities (Gu et al., 2014) and lead to problems with cognitive functioning. A Harvard study on loneliness in America found that “43% of young adults reported increases in loneliness since the outbreak of the pandemic” due to social distancing (Cashin, 2021). 

Since digital technology and social media usage is more pronounced among adolescents and young adults, this could be a prominent contributing factor to why the 5 to 17 year and 18 to 34 year age group experienced a significant increase in cognitive disability rates. Additionally, there may be a peak in the presence of cognitive disabilities following the COVID-19 pandemic in 2020 due social isolation and the increased usage of digital technologies and social media. If data for 2020 is released by the ACS, it would be interesting to analyze cognitive disability trends following the pandemic to determine which sex-age group cohorts were impacted the most. Moreover, breaking down the domains of cognition (as previously mentioned) would allow future studies to explore the individual correlations between technology and social media use, social isolation, and cognitive impairment at a larger scale due to the large sample size collected by the ACS. 

References

American Community Survey. (2010 – 2021). SEX BY AGE BY COGNITIVE DIFFICULTY (Table ID: C18104) [Civilian noninstitutionalized population 5 years and over]. Retrieved from https://data.census.gov/cedsci/table?q=cognitive%20difficulty&t=Health&tid=ACSDT1Y2010.C18104

Cashin, A. (2021, February). Loneliness in America: How the Pandemic Has Deepened an Epidemic of Loneliness and What We Can Do About It. Making Caring Common Project. Retrieved from https://mcc.gse.harvard.edu/reports/loneliness-in-america 

Centers for Disease Control and Prevention. (2020, September 16). Disability Datasets. Disability and Health Promotion. Retrieved from https://www.cdc.gov/ncbddd/disabilityandhealth/datasets.html 

Centers for Disease Control and Prevention. (2022, August 31). Life Expectancy in the U.S. Dropped for the Second Year in a Row in 2021. National Center for Health Statistics. Retrieved from https://www.cdc.gov/nchs/pressroom/nchs_press_releases/2022/20220831.htm#:~:text=Life%20expectancy%20at%20birth%20in,its%20lowest%20level%20since%201996 

Dhakal, A., & Bobrin, B. D. (2022). Cognitive Deficits. StatPearls. Retrieved from https://www.ncbi.nlm.nih.gov/books/NBK559052/. 

Duffin, E. (2022, September 30). U.S. population by sex and age 2021. Statista. Retrieved from https://www.statista.com/statistics/241488/population-of-the-us-by-sex-and-age/ 

Firth, J. A., Torous, J., & Firth, J. (2020). Exploring the Impact of Internet Use on Memory and Attention Processes. International Journal of Environmental Research and Public Health, 17(24), 9481. https://doi.org/10.3390/ijerph17249481 

Gu, D., Gomez-Redondo, R., & Dupre, M. E. (2014). Studying Disability Trends in Aging Populations. Journal of Cross-Cultural Gerontology, 30, 21–49. https://doi.org/10.1007/s10823-014-9245-6 

Levine DA, Gross AL, Briceño EM, et al. (2021). Sex Differences in Cognitive Decline Among US Adults. JAMA Network Open, 4(2). https://doi.org/10.1001/jamanetworkopen.2021.0169 

Lim, S., Han, C. E., Uhlhaas, P. J., & Kaiser, M. (2015). Preferential Detachment During Human Brain Development: Age- and Sex-Specific Structural Connectivity in Diffusion Tensor Imaging (DTI) Data. Cerebral Cortex, 25(6), 1477–1489. https://doi.org/10.1093/cercor/bht333 

McCarrey, A. C., An, Y., Kitner-Triolo, M. H., Ferrucci, L., & Resnick, S. M. (2016). Sex differences in cognitive trajectories in clinically normal older adults. Psychology and aging, 31(2), 166–175. https://doi.org/10.1037/pag0000070

Small, G. W., Lee, J., Kaufman, A., Jalil, J., Siddarth, P., Gaddipati, H., Moody, T. D., & Bookheimer, S. Y. (2020). Brain health consequences of digital technology use. Dialogues in Clinical Neuroscience, 22(2), 179–187. https://doi.org/10.31887/dcns.2020.22.2/gsmall