Alzheimer’s prevention may be less about new drugs, more about income, zip code and education
That your risk of Alzheimer’s disease depends on your salary, what you ate as a child, or the block where you live may seem implausible. But researchers are discovering that social determinants of health (SDOH) play an outsized role in Alzheimer’s disease and related dementias, possibly more than age, and new strategies are emerging for how to address these factors.
At the 2022 Alzheimer’s Association International Conference, a series of presentations offered evidence that a string of socioeconomic factors—such as employment status, social support networks, education and home ownership—significantly affected dementia risk, even when adjusting data for genetic risk. What’s more, memory declined more rapidly in people who earned lower wages and slower in people who had parents of higher socioeconomic status.
In 2020, a first-of-its kind study in JAMA linked Alzheimer’s incidence to “neighborhood disadvantage,” which is based on SDOH indicators. Through autopsies, researchers analyzed brain tissue markers related to Alzheimer’s and found an association with these indicators. In 2022, Ryan Powell, the lead author of that study, published further findings that neighborhood disadvantage was connected with having more neurofibrillary tangles and amyloid plaques, the main pathological features of Alzheimer's disease.
As of yet, little is known about the biological processes behind this, says Powell, director of data science at the Center for Health Disparities Research at the University of Wisconsin School of Medicine and Public Health. “We know the association but not the direct causal pathway.”
The corroborative findings keep coming. In a Nature study published a few months after Powell’s study, every social determinant investigated affected Alzheimer’s risk except for marital status. The links were highest for income, education, and occupational status.
Clinical trials on new Alzheimer’s medications get all the headlines but preventing dementia through policy and public health interventions should not be underestimated.
The potential for prevention is significant. One in three older adults dies with Alzheimer's or another dementia—more than breast and prostate cancers combined. Further, a 2020 report from the Lancet Commission determined that about 40 percent of dementia cases could theoretically be prevented or delayed by managing the risk factors that people can modify.
Take inactivity. Older adults who took 9,800 steps daily were half as likely to develop dementia over the next 7 years, in a 2022 JAMA study. Hearing loss, another risk factor that can be managed, accounts for about 9 percent of dementia cases.
Clinical trials on new Alzheimer’s medications get all the headlines but preventing dementia through policy and public health interventions should not be underestimated. Simply slowing the course of Alzheimer’s or delaying its onset by five years would cut the incidence in half, according to the Global Council on Brain Health.
Minorities Hit the Hardest
The World Health Organization defines SDOH as “conditions in which people are born, work, live, and age, and the wider set of forces and systems shaping the conditions of daily life.”
Anyone who exists on processed food, smokes cigarettes, or skimps on sleep has heightened risks for dementia. But minority groups get hit harder. Older Black Americans are twice as likely to have Alzheimer’s or another form of dementia as white Americans; older Hispanics are about one and a half times more likely.
This is due in part to higher rates of diabetes, obesity, and high blood pressure within these communities. These diseases are linked to Alzheimer’s, and SDOH factors multiply the risks. Blacks and Hispanics earn less income on average than white people. This means they are more likely to live in neighborhoods with limited access to healthy food, medical care, and good schools, and suffer greater exposure to noise (which impairs hearing) and air pollution—additional risk factors for dementia.
Related Reading: The Toxic Effects of Noise and What We're Not Doing About it
Plus, when Black people are diagnosed with dementia, their cognitive impairment and neuropsychiatric symptom are more advanced than in white patients. Why? Some African-Americans delay seeing a doctor because of perceived discrimination and a sense they will not be heard, says Carl V. Hill, chief diversity, equity, and inclusion officer at the Alzheimer’s Association.
Misinformation about dementia is another issue in Black communities. The thinking is that Alzheimer’s is genetic or age-related, not realizing that diet and physical activity can improve brain health, Hill says.
African Americans are severely underrepresented in clinical trials for Alzheimer’s, too. So, researchers miss the opportunity to learn more about health disparities. “It’s a bioethical issue,” Hill says. “The people most likely to have Alzheimer’s aren’t included in the trials.”
The Cure: Systemic Change
People think of lifestyle as a choice but there are limitations, says Muniza Anum Majoka, a geriatric psychiatrist and assistant professor of psychiatry at Yale University, who published an overview of SDOH factors that impact dementia. “For a lot of people, those choices [to improve brain health] are not available,” she says. If you don’t live in a safe neighborhood, for example, walking for exercise is not an option.
Hill wants to see the focus of prevention shift from individual behavior change to ensuring everyone has access to the same resources. Advice about healthy eating only goes so far if someone lives in a food desert. Systemic change also means increasing the number of minority physicians and recruiting minorities in clinical drug trials so studies will be relevant to these communities, Hill says.
Based on SDOH impact research, raising education levels has the most potential to prevent dementia. One theory is that highly educated people have a greater brain reserve that enables them to tolerate pathological changes in the brain, thus delaying dementia, says Majoka. Being curious, learning new things and problem-solving also contribute to brain health, she adds. Plus, having more education may be associated with higher socioeconomic status, more access to accurate information and healthier lifestyle choices.
New Strategies
The chasm between what researchers know about brain health and how the knowledge is being applied is huge. “There’s an explosion of interest in this area. We’re just in the first steps,” says Powell. One day, he predicts that physicians will manage Alzheimer’s through precision medicine customized to the patient’s specific risk factors and needs.
Raina Croff, assistant professor of neurology at Oregon Health & Science University School of Medicine, created the SHARP (Sharing History through Active Reminiscence and Photo-imagery) walking program to forestall memory loss in African Americans with mild cognitive impairment or early dementia.
Participants and their caregivers walk in historically black neighborhoods three times a week over six months. A smart tablet provides information about “Memory Markers” they pass, such as the route of a civil rights march. People celebrate their community and culture while “brain health is running in the background,” Croff says.
Photos and memory prompts engage participants in the SHARP program.
OHSU/Kristyna Wentz-Graff
The project began in 2015 as a pilot study in Croff’s hometown of Portland, Ore., expanded to Seattle, and will soon start in Oakland, Calif. “Walking is good for slowing [brain] decline,” she says. A post-study assessment of 40 participants in 2017 showed that half had higher cognitive scores after the program; 78 percent had lower blood pressure; and 44 percent lost weight. Those with mild cognitive impairment showed the most gains. The walkers also reported improved mood and energy along with increased involvement in other activities.
It’s never too late to reap the benefits of working your brain and being socially engaged, Majoka says.
In Milwaukee, the Wisconsin Alzheimer’s Institute launched the The Amazing Grace Chorus® to stave off cognitive decline in seniors. People in early stages of Alzheimer’s practice and perform six concerts each year. The activity provides opportunities for social engagement, mental stimulation, and a support network. Among the benefits, 55 percent reported better communication at home and nearly half of participants said they got involved with more activities after participating in the chorus.
Private companies are offering intervention services to healthcare providers and insurers to manage SDOH, too. One such service, MyHello, makes calls to at-risk people to assess their needs—be it food, transportation or simply a friendly voice. Having a social support network is critical for seniors, says Majoka, noting there was a steep decline in cognitive function among isolated elders during Covid lockdowns.
About 1 in 9 Americans age 65 or older live with Alzheimer’s today. With a surge in people with the disease predicted, public health professionals have to think more broadly about resource targets and effective intervention points, Powell says.
Beyond breakthrough pills, that is. Like Dorothy in Kansas discovering happiness was always in her own backyard, we are beginning to learn that preventing Alzheimer’s is in our reach if only we recognized it.
Two years, six million deaths and still counting, scientists are searching for answers to prevent another COVID-19-like tragedy from ever occurring again. And it’s a gargantuan task.
Our disturbed ecosystems are creating more favorable conditions for the spread of infectious disease. Global warming, deforestation, rising sea levels and flooding have contributed to a rise in mosquito-borne infections and longer tick seasons. Disease-carrying animals are in closer range to other species and humans as they migrate to escape the heat. Bats are thought to have carried the SARS-CoV-2 virus to Wuhan, either directly or through another host animal, but thousands of novel viruses are lurking within other wild creatures.
Understanding how climate change contributes to the spread of disease is critical in predicting and thwarting future calamities. But the problem is that predictive models aren’t yet where they need to be for forecasting with certainty beyond the next year, as we could for weather, for instance.
The association between climate and infectious disease is poorly understood, says Irina Tezaur, a computational scientist at Sandia National Laboratories. “Correlations have been observed but it’s not known if these correlations translate to causal relationships.”
To make accurate longer-term predictions, scientists need more empirical data, multiple datasets specific to locations and diseases, and the ability to calculate risks that depend on unpredictable nature and human behavior. Another obstacle is that climate scientists and epidemiologists are not collaborating effectively, so some researchers are calling for a multidisciplinary approach, a new field called Outbreak Science.
Climate scientists are far ahead of epidemiologists in gathering essential data.
Earth System Models—combining the interactions of atmosphere, ocean, land, ice and biosphere—have been in place for two decades to monitor the effects of global climate change. These models must be combined with epidemiological and human model research, areas that are easily skewed by unpredictable elements, from extreme weather events to public environmental policy shifts.
“There is never just one driver in tracking the impact of climate on infectious disease,” says Joacim Rocklöv, a professor at the Heidelberg Institute of Global Health & Heidelberg Interdisciplinary Centre for Scientific Computing in Germany. Rocklöv has studied how climate affects vector-borne diseases—those transmitted to humans by mosquitoes, ticks or fleas. “You need to disentangle the variables to find out how much difference climate makes to the outcome and how much is other factors.” Determinants from deforestation to population density to lack of healthcare access influence the spread of disease.
Even though climate change is not the primary driver of infectious disease today, it poses a major threat to public health in the future, says Rocklöv.
The promise of predictive modeling
“Models are simplifications of a system we’re trying to understand,” says Jeremy Hess, who directs the Center for Health and the Global Environment at University of Washington in Seattle. “They’re tools for learning that improve over time with new observations.”
Accurate predictions depend on high-quality, long-term observational data but models must start with assumptions. “It’s not possible to apply an evidence-based approach for the next 40 years,” says Rocklöv. “Using models to experiment and learn is the only way to figure out what climate means for infectious disease. We collect data and analyze what already happened. What we do today will not make a difference for several decades.”
To improve accuracy, scientists develop and draw on thousands of models to cover as many scenarios as possible. One model may capture the dynamics of disease transmission while another focuses on immunity data or ocean influences or seasonal components of a virus. Further, each model needs to be disease-specific and often location-specific to be useful.
“All models have biases so it’s important to use a suite of models,” Tezaur stresses.
The modeling scientist chooses the drivers of change and parameters based on the question explored. The drivers could be increased precipitation, poverty or mosquito prevalence, for instance. Later, the scientist may need to isolate the effect of one driver so that will require another model.
There have been some related successes, such as the latest models for mosquito-borne diseases like Dengue, Zika and malaria as well as those for flu and tick-borne diseases, says Hess.
Rocklöv was part of a research team that used test data from 2018 and 2019 to identify regions at risk for West Nile virus outbreaks. Using AI, scientists were able to forecast outbreaks of the virus for the entire transmission season in Europe. “In the end, we want data-driven models; that’s what AI can accomplish,” says Rocklöv. Other researchers are making an important headway in creating a framework to predict novel host–parasite interactions.
Modeling studies can run months, years or decades. “The scientist is working with layers of data. The challenge is how to transform and couple different models together on a planetary scale,” says Jeanne Fair, a scientist at Los Alamos National Laboratory, Biosecurity and Public Health, in New Mexico.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts a tall spatial and temporal resolutions.
And it’s a constantly changing picture. A modeling study in an April 2022 issue of Nature predicted that thousands of animals will migrate to cooler locales as temperatures rise. This means that various species will come into closer contact with people and other mammals for the first time. This is likely to increase the risk of emerging infectious disease transmitted from animals to humans, especially in Africa and Asia.
Other things can happen too. Global warming could precipitate viral mutations or new infectious diseases that don’t respond to antimicrobial treatments. Insecticide-resistant mosquitoes could evolve. Weather-related food insecurity could increase malnutrition and weaken people’s immune systems. And the impact of an epidemic will be worse if it co-occurs during a heatwave, flood, or drought, says Hess.
The devil is in the climate variables
Solid predictions about the future of climate and disease are not possible with so many uncertainties. Difficult-to-measure drivers must be added to the empirical model mix, such as land and water use, ecosystem changes or the public’s willingness to accept a vaccine or practice social distancing. Nor is there any precedent for calculating the effect of climate changes that are accelerating at a faster speed than ever before.
The most critical climate variables thought to influence disease spread are temperature, precipitation, humidity, sunshine and wind, according to Tezaur’s research. And then there are variables within variables. Influenza scientists, for example, found that warm winters were predictors of the most severe flu seasons in the following year.
The human factor may be the most challenging determinant. To what degree will people curtail greenhouse gas emissions, if at all? The swift development of effective COVID-19 vaccines was a game-changer, but will scientists be able to repeat it during the next pandemic? Plus, no model could predict the amount of internet-fueled COVID-19 misinformation, Fair noted. To tackle this issue, infectious disease teams are looking to include more sociologists and political scientists in their modeling.
Addressing the gaps
Currently, researchers are focusing on the near future, predicting for next year, says Fair. “When it comes to long-term, that’s where we have the most work to do.” While scientists cannot foresee how political influences and misinformation spread will affect models, they are positioned to make headway in collecting and assessing new data streams that have never been merged.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts at all spatial and temporal resolutions, Fair and her co-authors stated in their recent study. For example real-time data on mosquito prevalence and diversity in various settings and times is limited or non-existent. Fair also would like to see standards set in mosquito data collection in every country. “Standardizing across the US would be a huge accomplishment,” she says.
Understanding how climate change contributes to the spread of disease is critical for thwarting future calamities.
Jeanne Fair
Hess points to a dearth of data in local and regional datasets about how extreme weather events play out in different geographic locations. His research indicates that Africa and the Middle East experienced substantial climate shifts, for example, but are unrepresented in the evidentiary database, which limits conclusions. “A model for dengue may be good in Singapore but not necessarily in Port-au-Prince,” Hess explains. And, he adds, scientists need a way of evaluating models for how effective they are.
The hope, Rocklöv says, is that in the future we will have data-driven models rather than theoretical ones. In turn, sharper statistical analyses can inform resource allocation and intervention strategies to prevent outbreaks.
Most of all, experts emphasize that epidemiologists and climate scientists must stop working in silos. If scientists can successfully merge epidemiological data with climatic, biological, environmental, ecological and demographic data, they will make better predictions about complex disease patterns. Modeling “cross talk” and among disciplines and, in some cases, refusal to release data between countries is hindering discovery and advances.
It’s time for bold transdisciplinary action, says Hess. He points to initiatives that need funding in disease surveillance and control; developing and testing interventions; community education and social mobilization; decision-support analytics to predict when and where infections will emerge; advanced methodologies to improve modeling; training scientists in data management and integrated surveillance.
Establishing a new field of Outbreak Science to coordinate collaboration would accelerate progress. Investment in decision-support modeling tools for public health teams, policy makers, and other long-term planning stakeholders is imperative, too. We need to invest in programs that encourage people from climate modeling and epidemiology to work together in a cohesive fashion, says Tezaur. Joining forces is the only way to solve the formidable challenges ahead.
This article originally appeared in One Health/One Planet, a single-issue magazine that explores how climate change and other environmental shifts are increasing vulnerabilities to infectious diseases by land and by sea. The magazine probes how scientists are making progress with leaders in other fields toward solutions that embrace diverse perspectives and the interconnectedness of all lifeforms and the planet.
Scientists use AI to predict how hospital stays will go
The Friday Five covers five stories in research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
Here are the promising studies covered in this week's Friday Five:
- The problem with bedtime munching
- Scientists use AI to predict how stays in hospitals will go
- How to armor the shields of our livers against cancer
- One big step to save the world: turn one kind of plastic into another
- The perfect recipe for tiny brains
And an honorable mention this week: Bigger is better when it comes to super neurons in super agers