TTHealthWatch is a weekly podcast from Texas Tech. In it, Elizabeth Tracey, director of electronic media for Johns Hopkins Medicine, and Rick Lange, MD, president of the Texas Tech University Health Sciences Center in El Paso, look at the top medical stories of the week. A transcript of the podcast is below the summary.
0:40 Benefits of masking in reducing hospitalizations
1:40 99 counties in 14 states
2:40 Most older individuals wear masks already
3:30 Transmission of SARS-CoV-2 in daycare centers
4:35 Overall seroprevalence examined
5:35 Kids’ transmission would be rampant
6:30 Most kids got it from home
6:40 Misinformation and vaccine hesitancy
7:40 54% in U.K. said they would take it before
8:40 What is a free press?
9:41 Prediabetes in older folks
10:41 HbA1c and progression examined
11:41 Didn’t impact overall mortality
13:04 End
Elizabeth Tracey: Do kids really have anything to do with the spread of COVID-19?
Rick Lange, MD: Does misinformation affect vaccine acceptance?
Elizabeth: If you’re an older adult and you’ve been told you have prediabetes, should you worry about developing diabetes?
Rick: And do statewide mask mandates decrease COVID hospitalizations?
Elizabeth: That’s what we’re talking about this week on TT HealthWatch, your weekly look at the medical headlines from Texas Tech University Health Sciences Center in El Paso. I’m Elizabeth Tracey, a Baltimore-based medical journalist.
Rick: And I’m Rick Lange, president of Texas Tech University Health Sciences Center in El Paso, where I’m also dean of the Paul L. Foster School of Medicine.
Elizabeth: Rick, in light of the fact that we’ve been hearing an awful lot about these COVID variants that are emerging, why don’t we turn first to this issue of masks? That’s in Morbidity and Mortality Weekly Report — as we all know, a publication of the Centers for Disease Control and Prevention.
Rick: This was a study — they’re trying to assess whether statewide mask mandates actually decrease hospitalization rates. At the end of October of 2020, statewide mask mandates were in effect in 33 states and the District of Columbia. To look at whether this actually affected hospitalization, they went to the COVID-NET — that’s the COVID-19 Associated Hospital Surveillance Network.
This was in states that actually had the mask mandate and they looked at hospitalizations before masks were mandated, more than 4 weeks before, immediately before, immediately after, and then more than 4 weeks afterwards for people of various ages. That is between the ages of 18 and 40, and between 40 and 64, and over 64. Did, in fact, masks decrease hospitalization?
Ninety-nine counties in 14 different states. What they determined was that, in fact, hospitalizations did decrease by an average about 4% to 5% over that time period among those age groups, except for those over 68 years of age. They did not experience a decrease in hospitalizations. So they had to wear a mask anywhere outside their home, or in retail businesses and in restaurants. Something as simple as wearing a mask in public places, pretty effective.
Elizabeth: Let’s talk about why masks did not result in a reduction in hospitalizations among those who are in, admittedly, the highest-risk group for severe COVID-19 disease.
Rick: All right. Elizabeth, if I ask you if you just polled individuals over 65 and those who were young, let’s say 18 to 24, and what percentage of then wear a mask at baseline, for the over 65, what would you say?
Elizabeth: I’d say it’s really a large number.
Rick: Exactly right. It’s 70%, and so mask mandates didn’t matter very much. But in the younger group, it’s less than 45%. That’s where the biggest bang for the buck comes, is making sure that they wear a mask, because most of the older individuals are wearing masks already.
Elizabeth: Of course, we know that the federal government is poised to tug down a little bit more relative to mask-wearing and also there’s been the recent recommendation that one should don both a surgical mask with a cloth mask over the top of it.
Rick: We’ve talked before about there are various types of mask with various efficacy. Obviously, the most important thing is to wear a mask, but obviously the better the mask — or two masks, if necessary — the more protective it is. You’re not only protecting yourself, but more importantly, if you happen to have an infection, either presymptomatic or asymptomatic, you’re preventing another person from getting it. This is just one piece of a multi-pronged effort we need to decrease the COVID infection rate across the U.S.
Elizabeth: And particularly as these more infections variants are starting to gain the upper hand.
Rick: Good point.
Elizabeth: Yeah, so let’s turn to who isn’t responsible for transmission of a lot of these SARS-CoV-2 infections? This is in the Lancet Child and Adolescent Health and this is a study in France that takes a look at daycare centers. They looked at children and staff who attended one of 22 daycare centers during their nationwide lockdown in France between June 4th and July 3rd, so for about a month.
They enrolled 327 children with a mean age of 1.9 years but up to 4.4 years old, 197 daycare center staff whose mean age was 40 years, and 164 adults in a comparator group, which was folks who worked in hospitals but did not interact with children as part of their work duties.
They took a look at seroprevalence with blood tests in this group of people. They found that 3.7% of the children and 6.8% of the daycare center staff had positive serologic tests for SARS-CoV-2. In the comparator group, they had an overall seroprevalence of 5%. Interestingly, among the children, almost all of these cases were at different centers, so really just one case per center, and almost the majority, 43% — they guesstimate also — obtained this infection from an adult household member with laboratory-confirmed COVID-19.
So the upshot of this whole thing is it’s not the kids — and we’ve talked about that before — who seem to be transmitting this infection. The kids largely seem to get it from the adults in their households, and the authors argue that this could actually be used as evidence that it’s going to be okay to reopen schools.
Rick: France was the perfect place to study this. Because what happened, in March, April, and May they shut down daycare centers, but they had to leave them open for essential personnel and people working in the hospital setting. Well, those are high-risk groups. You’d think the kids would be high-risk as well. A kid could get it from a parent or parents and then bring it to school and transmit it among the school. It would be rampant.
What this study showed is when they looked at the kids in June and July — that is, months after they’ve been in the daycare center — and looked for antibodies, very few of the kids had ever been infected. As you said, they didn’t get it in the daycare center. They got it from their parents at home. This again shows that if you open schools properly, you can do so and do so safely.
Now, what do they do? Remember, they kept the kids in small groups, a single teacher. They did social distancing, even at lunch, for example. They wore a mask and used proper hygiene, all the things that we’re talking about, and even kids can do that. I think this was a terrific study, epidemiologic study, a natural history of what happens when you allow kids to stay at their care center with proper prevention measures.
Elizabeth: Since there’s so much energy right now behind opening schools, hopefully it will give those kinds of administrators some comfort that transmission, at least right now, seems to be reduced among kids.
Rick: Yeah. Since most of the kids got it from home, from one of their parents, what you do is you make sure if the child’s sick or has any symptoms, he doesn’t come to school.
Elizabeth: Let’s go to Nature Human Behavior. This was a study taking a look at, hmm, am I going to get a vaccine or not? What are the factors and how does misinformation play into this?
Rick: Elizabeth, I thought this was a really interesting study. As we’re aware, there are many individuals that are really reluctant to receive the vaccine, and some of it based upon some accurate information, but a lot because of misinformation. That misinformation comes from a lot of ways, sometimes social media, sometimes friends or relatives. What this study attempted to do was say does that misinformation actually influence someone’s decision to take the vaccine?
This was a study conducted in 8,000 individuals in the United Kingdom and the United States both. They took 6,000 of those individuals — 3,000 in each country — and they did a pretest. They said, “Would you be likely to take the vaccine or not?” And then they exposed them to five points of misinformation, some of which were scientific-sounding, some of which were not, and then they post-tested them, said, “Now would you take the vaccine?” The remaining 2,000 individuals — 1,000 in each country — they didn’t give any misinformation to see if anything’s changed or not.
Here’s what they discovered, is before misinformation was presented, 54% percent of the respondents in the United Kingdom and 43% in the U.S. reported they would definitely take the COVID vaccination. I would have thought it would have been a little bit higher. But having said that, after they spent time with these individuals providing misinformation, an additional 6% fell off the radar screen and said, “Oh, after hearing that I wouldn’t take the vaccination now. Maybe, but no, I’m not in the definite category any more.”
The other interesting thing is they ask them if you wouldn’t do it for yourself, would you do it for a family member? You know what? People said, yeah, they’d be more likely to take the vaccine. About 64% said they would for a family member other than themselves. Then when they got misinformation, they also fell off the radar screen as well. Again, about another 6% said, “Well, now that I’ve heard of that, I’m not going to take it.”
This really shows how important providing proper information is. Now, the unfortunate thing is once you provide misinformation it’s hard to get rid of it. Even a short period of misinformation can last for a long period of time.
Elizabeth: Clearly demonstrating the fact that most of us make decisions based on anecdotal information or our personal exposures to things. I think it’s also illustrative of what’s going on socially for many of us right now, which is this idea of, “Gosh, what is a free press? What is it okay to have out there?” This, clearly, is something that has public health implications.
Rick: It does, and you know they dove a little bit deeper and they said are there certain groups that are more likely to respond to misinformation? They discovered that females were less robust to misinformation than males, and surprisingly enough, the lower-income individuals were less likely to decline vaccination after misinformation than the higher-income individuals, which I found a little bit surprising. And the last thing is, “Did it relate to how long people spend on social media?” The answer was it didn’t have any relationship to that at all.
Elizabeth: It’s interesting, that last piece about higher-income individuals, and that’s supported by the general anti-vax movement.
Rick: Exactly, and so you might predict, well, lower-income people would be less educated perhaps, about this, or not have access to the information, but they’re really not swayed by the misinformation like the higher-income group.
Elizabeth: Very interesting. Let’s hope some of this is actionable. Finally, let’s turn to JAMA Internal Medicine. This is a look at this condition that’s called prediabetes, which gosh, we’ve been reporting for quite a long time about gloom and doom. “Oh my gosh, if you’ve got prediabetes, you’re on the path to frank diabetes and all the host of things that happen as a result of that.”
In this case, they’re taking a look at older individuals. They analyzed data for 3,412 participants without diabetes. Their mean age was 75.6 years. Slightly more percentage of them were women. At their analysis, they had 2,497 participants. In their 6.5 years of follow-up there were 156 incident total diabetes cases, 118 diagnosed, and 434 deaths.
They took a look at fasting glucose and hemoglobin A1c, and they said, “Gosh, how many of you all were in that prediabetes part, and then what happened to you?” Those who had hemoglobin A1C levels of 5.7% to 6.4% at baseline, 9% progressed to diabetes, 13% regressed to normoglycemia, and 207 died.
They also looked at this impaired fasting glucose number, and basically the upshot of the whole thing is it’s really interesting. It is not a solid line relationship, and maybe it says among older adults we don’t need to paint such a gloom-and-doom picture, although we should monitor.
Rick: Yep. Again, these were adults aged 70 to 91. Prediabetes meant that your sugar was a little bit high but not quite in the diabetic range, and your hemoglobin A1c was a little bit high but not in the diabetic range. That concern is that’s prediabetes. You’re going to progress to diabetes and it’s going to increase your mortality, but on the elderly group, it just doesn’t seem to be the case.
Now, keep in mind that progression oftentimes takes decades, by the way, so when you’re dealing with an elderly population, first of all, the progression of diabetes was rare, 8% to 9%, but even then it really didn’t affect overall mortality at all, and that because the mortality associated with diabetes takes decades to develop.
I’m not terribly surprised, but I do think that we don’t have to be quite so vigilant in this population. It’s already frail, by the way, and taking multiple medications could put another burden upon them thinking that, “Gosh, this is going to be a fatal or a near-fatal disease.”
Elizabeth: I think this points out two things that we’ve talked about many times. One is that we’ve looked at interventions among folks who are critically ill, and especially glucose levels, for example, and found out that, “Gosh, maybe there’s some compensatory aspect to that.” When we intervene, we actually end up with worse outcomes.
I think maybe what we don’t know is what happens to this number as we age in so-called normal aging. I think that we haven’t really looked at how these things change over time in somebody who is healthy otherwise, and we think it’s indicative of a potential problem when it really isn’t.
Rick: Right, and that’s the whole point of this study. It’s not really a major issue. Now, there are other issues that we do need to address, like sedentary lifestyles, or are they continuing to smoke cigarettes, or do they have uncontrolled hypertension, which was a much bigger problem in this patient population — but prediabetes, not really a significant risk factor in this age group.
Elizabeth: On that good news note, that’s a look at this week’s medical headlines from Texas Tech. I’m Elizabeth Tracey.
Rick: And I’m Rick Lange. Y’all listen up and make healthy choices.
Source: MedicalNewsToday.com
