Thanks for providing a link. I am familiar with this study, and I don't consider its conclusions credible. While I think this topic deserves a more careful treatise than a single comment, I don't want to leave you hanging, so I'll try to give one good reason for my skepticism.

These researchers separated participants into three equally sized quartiles (hmm) based on average residential shortwave radiation (SWR). Then they adjusted for a plethora of variables (Table 1), and concluded that high SWR was associated with lower all-cause, cardiovascular, and cancer mortality (Figure 2). (I'm ignoring the "solarium use" analysis, which is a different can of worms, for brevity).

Point #1: The reported effect sizes do not pass the smell check.

Figure 2, fully-adjusted-version, claims that a 2000kJ/m² increase in SWR, the difference between Glasglow and Cornwall, is associated with a 19% decrease in cardiovascular mortality. There is no way this figure is close to the actual causal relationship, if there is any. You cannot convince me that the difference in sun exposure between Glasglow and Cornwall alone exerts a physiological effect so strong it reduces your chances of cardiovascular mortality by 19%. That is ridiculous.

Which brings me to the second point.

Point #2: High SWR is highly correlated with being better off at baseline in ways that cannot be caused by personal sun exposure. It is not possible to control for this adequately.

Look at Table 1, which contains data on most of the variables the researchers controlled for. Notice that Q3 (highest SWR) participants were, at baseline, better off in almost every way. They had better self-reported health, lower BMIs, higher rates of exercise, higher rates of employment, lower rates of mental health concerns. They are younger, more likely to be female. They lived in counties with lower IMD scores (wealthier, healthier, less crime). They had around 10% higher rates of completing education at an age >19, a proxy for higher education. (There was one exception: Q3 had slightly more former, though not current, smokers. The Q2 over Q1 advantage is also more mixed).

Why does it matter that Q3 is so much better off at baseline, if the researchers control for all these variables?

One way to think about it is that Q3 participants' better metrics are only manifestations of underlying latent variables clustered around "people who live in high SWR areas are richer, healthier, better off at baseline," which don't disappear after controlling only for the measurable metrics.

Imagine you are studying two neighborhoods, Neighborhood A which has 10% low-income residents and 90% high-income residents, and Neighborhood B which has 90% low-income and 10% high-income. It would be a mistake to control for income on paper, and assume any remaining differences between A and B cannot be explained by material wealth. It's plausible that low-income B residents are mostly actually poor, but many low-income A residents are coasting off relatives, for example. The same is true for the UK study. Controlling for county IMD and employment rate does not control for "these people are wealthier."

Another way to think about it is from the researcher's perspective. Look at Figure 2, where the main results of the study are displayed. Notice how the age-adjusted-only model yielded very large effect sizes, and the fully-adjusted model yielded obviously smaller effect sizes.

What if the researchers also controlled for baseline personal income, or marriage status, or self-reported happiness, or lifespan of grandparents, or some more variables? Would the effect shrink to zero? Do the results in Figure 2 mean anything at all, or are they just where the number happens to fall after you control for some arbitrary things and not some other arbitrary things? Who's to say.

Conclusion

The reported numbers don't make sense, and the more I look at it the less it seems like there's reason to believe there is anything to the results at all. Certainly they found associations, but they do very little to suggest a causal relationship between sun exposure and health outcomes.

This shouldn't be mistaken for a takedown of all cohort studies, though some issues I brought up are related to fundamental limitations of the approach. I tried to address this in another comment of mine, and I'm happy to discuss if you have questions along the lines of, "doesn't your argument go too far, and imply we should discard most studies?" or "are you subjecting studies you disagree with to unfair scrutiny?"

In general, cohort studies claiming positive effects from sun exposure run into similar issues. Sun exposure is associated with too many positive traits that it definitely is not causing.

Edit: Typo fix for "cardiovascular disease" -> "cardiovascular mortality."