Middle-aged smokers are much more likely to report having memory loss and confusion than nonsmokers, and the likelihood of cognitive decline is lower for those who have quit, even recently, according to a new study appearing in the Journal of Alzheimer’s Disease.
The study is the first to examine the relationship between smoking and cognitive decline using a one-question self-assessment asking people if they’ve experienced worsening or more frequent memory loss and/or confusion.
The findings build on previous research that established relationships between smoking and Alzheimer’s Disease and other forms of dementia, and could point to an opportunity to identify signs of trouble earlier in life, said Jenna Rajczyk, lead author of the study.
It’s also one more piece of evidence that quitting smoking is good not just for respiratory and cardiovascular reasons, but to preserve neurological health, said Rajczyk, a PhD student in Ohio State’s College of Public Health, and senior author Jeffrey Wing, assistant professor of epidemiology.
“The association we saw was most significant in the 45–59 age group, suggesting that quitting at that stage of life may have a benefit for cognitive health,” Wing said. A similar difference wasn’t found in the oldest group in the study, which could mean that quitting earlier affords people greater benefits, he said.
Researchers used data from the 2019 Behavioral Risk Factor Surveillance System Survey to compare subjective cognitive decline (SCD) measures for current smokers, recent former smokers, and those who had quit years earlier. The analysis included 136 018 people 45 and older, and about 11% reported SCD.
The prevalence of SCD among smokers in the study was almost 1.9 times that of nonsmokers. The prevalence among those who had quit less than 10 years ago was 1.5 times that of nonsmokers. Those who quit more than a decade before the survey had an SCD prevalence just slightly above the nonsmoking group.
“These findings could imply that the time since smoking cessation does matter, and may be linked to cognitive outcomes,” Rajczyk said.
The simplicity of SCD, a relatively new measure, could lend itself to wider applications, she said.
“This is a simple assessment that could be easily done routinely, and at younger ages than we typically start to see cognitive declines that rise to the level of a diagnosis of Alzheimer’s Disease or dementia,” Rajczyk said. “It’s not an intensive battery of questions. It’s more a personal reflection of your cognitive status to determine if you’re feeling like you’re not as sharp as you once were.”
Many people don’t have access to more in-depth screenings, or to specialists, making the potential applications for measuring SCD even greater, she said.
Wing said it’s important to note that these self-reported experiences don’t amount to a diagnosis, nor do they confirm independently that a person is experiencing decline out of the normal ageing process. But, he said, they could be a low-cost, simple tool to consider employing more broadly.
Following established guidelines about prescription drugs would seem an obvious choice, especially for the professionals that do the prescribing. Yet doctors – and their family members – are less likely than other people to comply with those guidelines, according to a large-scale study published in the American Economic Review: Insights.
This result could be surprising or else prompt a knowing nod. In any case, the finding flies in the face of past scholarly hypotheses. Previously, it was assumed that greater knowledge and easier communication with medical providers leads patients to follow instructions more closely.
The new study is based on over a decade of population-wide data from Sweden and includes suggestive evidence about why doctors and their families may ignore medical advice. Overall, the research shows that the rest of the population adheres to general medication guidelines 54.4% of the time, while doctors and their families lag 3.8% behind that.
“There’s a lot of concern that people don’t understand guidelines, that they’re too complex to follow, that people don’t trust their doctors,” says Amy Finkelstein, a professor in MIT’s Department of Economics. “If that’s the case, you should see the most adherence when you look at patients who are physicians or their close relatives. We were struck to find that the opposite holds, that physicians and their close relatives are less likely to adhere to their own medication guidelines.”
The paper, “A Taste of Their Own Medicine: Guideline Adherence and Access to Expertise,” is The authors are Finkelstein, the John and Jennie S. MacDonald Professor of Economics at MIT; Petra Persson, an assistant professor of economics at Stanford University; Maria Polyakova PhD ’14, an assistant professor of health policy at the Stanford University School of Medicine; and Jesse M. Shapiro, the George Gund Professor of Economics and Business Administration at Harvard University.
Millions of data points
To conduct the study, the scholars examined Swedish administrative data from 2005 through 2016, for 63 prescription drug guidelines. Doctors and their close relatives were selected. All told, the research involved 5 887 471 people to whom at least one of the medication guidelines applied. Of these people, 149 399 were doctors or their close family members.
Using information on prescription drug purchases, hospital visits, and diagnoses, the researchers could see if people were adhering to medication guidelines by examining whether prescription drug decisions matched these patients’ medical circumstances. In the study, six guidelines pertained to antibiotics; 20 involved medication use by the elderly; 20 focused on medication attached to particular diagnoses; and 17 were about prescription drug use during pregnancy.
Some guidelines recommended use of a particular prescription drug, like a preference of narrow-spectrum antibiotics for an infection; other guidelines were about not taking certain medications, such as the recommendation that pregnant women avoid antidepressants.
Out of the 63 guidelines used in the study, doctors and their families followed the standards less often in 41 cases, with the difference being statistically significant 20 times. Doctors and their families followed the guidelines more often in 22 cases, with the difference being statistically significant only three times.
“What we found, which is quite surprising, is that they [physicians] are on average less adherent to guidelines,” says study author Maria Polyakova PhD, an assistant professor of health policy at the Stanford University School of Medicine. “So, in this paper we are also trying to figure out what experts do differently.”
Ruling out other answers
Since doctors and their close relatives adhere to medical guidelines less often than the rest of the population, what exactly explains this phenomenon? While homing in on an answer, the research team examined and rejected several hypotheses.
First, the lower compliance by those with greater access to expertise is unrelated to socioeconomic status. In society overall, there is a link between income and adherence levels, but physicians and their families are an exception to this pattern. As the researchers wrote, special “access to doctors is associated with lower adherence despite, rather than because of, the high socioeconomic status” of those families.
Additionally, the researchers did not find any link between existing health status and adherence. They also studied whether a greater comfort with prescription medication – due to being a doctor or related to one – makes people more likely to take prescription drugs than guidelines recommend. This does not appear to be the case. The lower adherence rates for doctors and their relatives were similar in magnitude whether the guidelines pertained to taking medication or, alternately, not taking medication.
“There are a number of first-order alternative explanations that we could rule out,” Polyakova says.
Resolving a medical mystery
Instead, the researchers believe the answer is that doctors possess “superior information about guidelines” for prescription drugs – and then deploy that information for themselves. In the study, the largest difference in adherence to guidelines is for antibiotics: Doctors and their families are 5.2% less in compliance than everyone else.
Most guidelines in this area recommend starting patients off with “narrow-spectrum” antibiotics, which are more targeted, rather than “broader-spectrum” antibiotics. The latter might be more likely to eradicate an infection, but greater use of them also increases the chances that bacteria will develop resistance to these valuable medications, which can reduce efficacy for other patients. Thus for things like a respiratory tract infection, guidelines call for a more targeted antibiotic first.
The issue, however, is that what is good for the public in the long run – trying more targeted drugs first – may not work well for an individual patient. For this reason, doctors could be more likely to prescribe broader-spectrum antibiotics for themselves and their families.
“From a public-health perspective, what you want to do is kill it [the infection] off with the narrow-spectrum antibiotic,” Finkelstein observes. “But obviously any given patient would want to knock that infection out as quickly as possible.” Therefore, she adds, “You can imagine the reason doctors are less likely to follow the guidelines than other patients is because they … know there’s this wedge between what’s good for them as a patients and what’s good for society.”
Another suggestive piece of data comes from different types of prescription drugs that are typically avoided during pregnancies. For so-called C-Class drugs, where empirical evidence about the dangers of the drugs is slightly weaker, doctors and their families have an adherence rate 2.3 percentage points below other people (meaning, in this case, that they are more likely to take these medications during pregnancy). For so-called D-Class drugs with slightly stronger evidence of side effects, that dropoff is only 1.2 percentage points. Here too, doctors’ expert knowledge may be influencing their actions.
“The results imply that probably what’s going on is that experts have a more nuanced understanding of what is the right course of action for themselves, and how that might be different than what the guidelines suggest,” Polyakova says.
Still, the findings suggest some unresolved tensions in action. It could be, as Polyakova suggests, that guidelines about antibiotics should be more explicit about the public and private tradeoffs involved, providing more transparency for patients. “Maybe it’s better for the guidelines to be transparent and say they recommend this not because it is [always] the best course of action for you, but because it is the best for society,” she says.
Additional research could also aim to identify areas where lower expert adherence with guidelines may be associated with better health outcomes –to see how often doctors have a point, as it were. Or, as the researchers write in the paper, “An important avenue for further research is to identify whether and when nonadherence is in the patient’s best interest.”
Over the festive season, the South African measles outbreak has now extended to five provinces, including Gauteng as of epidemiological week (epiweek) 51, the National Institute for Communicable Diseases (NICD) has reported.
From samples collected in epiweek 40 (end 8 Oct 2022) to epiweek 51 (end 24 Dec 2022), a total of 297 cases of laboratory-confirmed measles cases have been reported in South Africa. From epiweek 40 to mid-week 51, 2022, a total of 285 laboratory-confirmed cases were reported from five provinces with declared measles outbreaks in Limpopo (128 cases), Mpumalanga (68), North West (69), Gauteng (13), and Free State (7). The NICD classifies a measles outbreak as three or more confirmed laboratory measles cases reported within 30 days of disease onset, within a district.
The number of cases continues to increase daily as blood and throat swabs are submitted to the NICD for measles serology and PCR testing.
The age of laboratory-confirmed cases across the five provinces ranges from two months to 42 years. Of these, 41% were ages 5–9, followed by 28% for ages 1–4 and 15% for ages 10–14 . Vaccination status of 84 cases (29%) was known, of whom 33 (39%) were vaccinated.
Data on hospital admission rates and measles mortality rates are not yet known. Whilst cases that are seen at hospitals may not necessarily be admitted, this figure gives us an indication of the severity of illness, as patients consulted tertiary care facilities. The number of admitted patients will be a subset of these cases.
An explanatory model presented in a thesis from University of Gothenburg may make simplify the understanding of autism development. It provides new insights into how various risk factors give rise to autism and why there is such great variability between individuals.
Autism, a neurodevelopmental condition, affects how people perceive the world around them and how they interact and communicate with others. Among individuals with autism, there are major differences in terms of personal traits and manifestations alike. The disorder is therefore usually described as a spectrum, with numerous subtle variations.
While theoretical, the new explanatory model is also practical in application, since its various components are quantifiable through testing. The model describes various contributing factors and how they combine to prompt an autism diagnosis and cause other neurodevelopmental conditions.
Three contributing factors
The model links three contributing factors. Together, these result in a pattern of behaviour that meets the criteria for an autism diagnosis:
Autistic personality – hereditary common genetic variants that give rise to an autistic personality.
Cognitive compensation – intelligence and executive functions, such as the capacity to learn, understand others, and adapt to social interactions.
Exposure to risk factors – for example, harmful genetic variants, infections, and other random events during gestation and early childhood that adversely affect cognitive ability.
“The autistic personality is associated with both strengths and difficulties in cognition but does not, as such, mean that diagnostic criteria are fulfilled. Still, exposure to risk factors that inhibit people’s cognitive ability may affect their capacity to tackle difficulties, which contributes to individuals being diagnosed with autism,” says Darko Sarovic, physician and postdoctoral researcher at Sahlgrenska Academy, University of Gothenburg, who wrote the thesis.
The model makes it clear that it is the many different risk factors combined that bring about the major differences among individuals on the spectrum. The various components of the model are supported by results from previous research.
Adaptive ability
High executive functioning skills may let people cover up their impairment, reducing their risk of meeting the diagnostic criteria for autism. This may explain why a lower degree of intelligence is observed among people diagnosed with autism, as well as other neurodevelopmental conditions. It also affords an understanding of why intellectual disability is more common among these groups. Thus, the model indicates that low cognitive ability is not part of the autistic personality but, rather, a risk factor that leads to diagnostic criteria being met.
“The autistic personality is associated with various strengths. For example, parents of children with autism are overrepresented among engineers and mathematicians. The parents themselves have probably been able to compensate for their own autistic personality traits and thus not met the criteria for an autism diagnosis. The impact of the disorder has then become more noticeable in their children owing, for instance, to an exposure to risk factors and relatively low cognitive ability,” Sarovic says.
Gender differences affect diagnosis
The diagnosis of autism is more common among boys than girls, and girls often get their diagnosis later in life. Some girls reach adulthood before being diagnosed, after many years of diffuse personal difficulties.
“Girls’ symptoms are often less evident to other people. It’s well known that girls generally have more advanced social skills, which probably means that they’re better at compensating for their own difficulties. Girls also tend to have fewer autistic traits and be less susceptible to the effects of risk factors. Accordingly, the model can help to answer questions about the gender gap,” Sarovic says.
Research and diagnostics
The model also proposes ways of estimating and measuring the three factors, enabling use of the model in research studies. Diagnostics is another conceivable area of use. In a pilot study in which 24 participants had been diagnosed with autism and 22 controls had not, measuring the three factors of the model enabled more than 93% to be correctly assigned to the right category. The model can also be used to explain the inception of other neurodevelopmental disorders, such as schizophrenia.
