This study has way too many problems to draw such a conclusion. It can only be taken as an indication that it may be worth further study, or may corroborate or contradict other, more carefully controlled, studies.
The main problem is simply that by the nature of the study, the authors are comparing two groups of people, at two different times and circumstances. They cant go back to the people in the second (2020/covid) group to check for individual data previously. Essentially they gamble that the profile of blood donors in Delhi did not change so that any change is likely due to mask-wearing.
But that's an assumption, not a fact. There have been other studies in other fields where it appeared two things were linked, and only more careful studies showed that the assumptions were incorrect or dubious. So we must tread very carefully.
A good paper will try to anticipate other factors ("confounds") that might have muddied the results, work around those it can, and at least highlight or try to estimate the effect of those it can't, so others are aware, and can either allow for it, form their own views, or design further experiments to address them. A bad paper will just conclude without such careful in-depth thought.
We don't know what factors might exist, or which factors might have had an effect (if any). Without reading the paper in-depth, I can guess at a few that I'd expect a gold-plated experiment would address. For example:
- We need to consider how representative blood donors are, of society at large, to draw such a conclusion from blood-donor-only data. If you study only blood donors, you will potentially exclude or under-represent huge swathes of society, with other characteristics. Anyone under 18. Anyone over (say) 65. Ages with above or below average representation among donors (maybe the population is older, but donors tend to be younger or whatever). People with a huge range of specific medical conditions. Rural dwellers (fewer local centres). Probably some ethnicities/genders/intersections are perceived to be socially suspicious or dissuaded by their cultural norms, and won't be as represented. Probably much more. Perhaps fitter people have lowered Hb but someone with already lowered Hb doesn't have as much of a reduction. We just don't know. The criteria and characteristics of blood donors as a group is very different from society overall. So all we can say is these results apply to the kinds of people who donate blood. Not to "people generally".
- The tests used for blood donor measurements are often designed to emphasise a pass/fail level, rather than an exact amount (which doesn't matter so much). As a result, how reliable and precise are the levels recorded?
- Do biases get introduced in the donation filtering process? For example, suppose women donors or people with certain clothing indicating religious beliefs, tend to have the measuring device placed slightly differently to avoid touching their religious clothing (or to go over it), or actual contact if that's taboo. Or women are seen as more fragile and borderline results more likely to be rounded down than up. Or Sikhs/Muslims seen as more suspicious, or whites/the poor (stereotype promiscuous/more likely infected) as more likely to have undetected HIV, and such bias tends to subtly impact how these donors are talked to/assessed/deterred. Or the questions asked are problematic for some groups. Or maybe some policy/criterion change had the effect of excluding some poor health people in the first group, but this had been removed prior to covid, so the excluded poor health people were prone to return in the 2nd group. Perhaps staff had more time to investigate borderline donors' health in a bit of depth before covid, so that borderline-pass cases were more often rejected after review, raising the average in the first group.
- As a variant on this, what if a more wary/cautious mindset existed in the medical services overall (including donor centre staff) due to the pandemic, and all measurements in 2020 were more likely to be rounded down than up, compared to normal where the staff are less looking for problems?
- Was the centre materially the same? Are we sure? People typically wait a while before a nurse measures them. Plenty of time that if the centre itself has some change, it could have had an effect. Suppose the AC is off or windows closed in the 2nd group to reduce spread, or patients are asked to wait in a more stuffy area, or the hospital waiting area was cleaned every hour by some cleaning product that lingered in the air and in high ongoing uses could affect a subset of patients breathing. Suppose by the time of the 2nd group, they called patients upstairs to a different room, and rushed their stats gathering (hospital pressures under covid) so patients were more likely to have run upstairs and been in slight oxygen debt. Suppose they used less experienced staff for taking patient stats, because of covid staff pressures, or they had budget pressures or a new supplier and their measuring devices were less well-calibrated or had systemic differences between the groups.
- Could time of year, pollen/asthma, air humidity (wetter or drier air), or other seasonal changes have had any effect? People may also pant if hot and the windows are closed, and CO2 could be higher, oxygen absorption may differ with moisture in some ways, or people may experience other changes to metabolism/physiology related to the time of year/weather.
- Did they match records of those donors who were in both groups, and analyse statistically the variation between Hb levels for individuals who appeared in both groups, or only compare the overall distribution of results at a group level?
- Did they compare also, say, a third or fourth group, taken at the same time of year as the 2020 (covid era) group but from say 2017 or 2018, to check if two or three groups before the covid era group, were comparable? In which case that would help emphasise if there was something truly different with the 2020 (covid) group. They didn't, and this seems a crucial control, to me.
- Was the profile of blood donors affected by other events (causation not correlation)? For example, we might speculate that (1) a lot of people had low-grade health conditions due to say, asymptomatic covid, (2) vaccine reactions, (3) changes to daily life affecting stress levels hence low-level changes to usual heart rate, breathing or other autonomous functions, for many people, (4) changes to diet and exercise, (5) reduction in health and respiratory/heart/blood system efficiency due to lockdowns or lack of work, (6) changes resulting from changing behaviours/commerce/travel, affecting polluters such as vehicles and industry, affecting the air in Delhi which is hugely polluted, or (7) changing how people breathed, if your work and life change due to lockdown then you might breathe deeper or lighter, (8) or be more/less exposed to the air if you have to change between walking/bus/tuktuk.......
- Also we can imagine what kind of people are more or less likely to donate blood during a lockdown or pandemic. Blood donation is unpaid in India, but we might speculate that people in less than excellent health or economic circumstances (which correlates strongly with poorer health and other conditions) are disproportionately deterred from donating normally, because there is not so huge pressure or reward, they work longer hours, or are less able to take time and travel to do so, and during a pandemic, they may have more time and opportunity, see news that hospitals need support, and see it as their duty to help others since they can now do so and it's urgently needed. So perhaps the health profile of those giving, will become poorer anyway. Or maybe it's the other way around. We can speculate that more affluent, economically secure, healthy, and educated, were more prone to stay at home and * not * go out for non-essential matters during the pandemic, because they were used to avoiding risks and watching their health, whereas poorer and less secure donors (on average having poorer health) were more likely to be fatalistic and carried on as normal.
In addition, there are other relevant studies to guide us, already. Did they use those or refer to them?
- Some countries like Japan have long social histories of mask-wearing before covid. Are there studies of such groups? Do Japanese long term maskers, vs. new (2020) maskers vs non-maskers (pre-covid) vs. non-maskers (2020) show a consistent difference in oxygen levels?
- Masks are also worn in many other contexts. Are there studies showing changes to blood Hb in Japan or elsewhere, when a mask is worn for a long time, or does a person's average mask-wearing times changes? For example, many jobs needed masks even before covid - forensic and lab technicians, "clean room" computer and technology workers, people working with hazardous chemicals or cement dust (construction).....
- And in any case is it medically important or not, that's another issue. Are there studies showing actual effects? Like assessment tests of mental performance/ability, or long term vs short term effect, or effect of a few hours a day vs continual vs none, or recovery curves if any needed?
And so on.
The point is, without better comparisons and controls, we don't know what happened, literally, all we know is oxygen, as marked by Hb, is down among donors, but why? Could be any of these, or something else, or indeed, yes, could be masks.
Fortunately, other credible studies do exist. This one for example studies the impact of mask-wearing for doctors during surgery. This one is in progress for exercisers. This one studies the effects of N95 masks during pregnancy.
The overall conclusion of these seems to be that there is a moderate reduction in blood oxygen, and a slight elevation of demands on the body as a result. But not really enough to be a danger to health. More a level to be aware of and manage how hard you push yourself and your body while wearing a mask.
That's paraphrased. You can read the originals, or google for others - I stopped at 3.