I mean it's good enough for Harvard, so what's wrong with the methodology?

FYI:

>The metabolic syndrome (MetS) is a cluster of cardiovascular risk factors that includes atherogenic dyslipidemia, abdominal obesity, high blood pressure, as well as high blood glucose.

Link to the paper

>Caffeine is considered the most popular psychoactive drug used by the majority of the general population in the world. Due to its ergogenic effect, it is widely used by athletes of many sports disciplines.
>
>Interestingly, between 1984 and 2004 caffeine was banned in sports competitions, although only in extremely high doses (i.e., representing a concentration of caffeine greater than 12 μg/mL in urine). However, on 1 January 2004, the World Anti-Doping Agency (WADA) decided to remove caffeine from the list of banned substances. Since then, athletes can freely use this substance during competitions. Nevertheless, caffeine has been moved to the Monitoring Program to control the consumption of high doses of caffeine by athletes (i.e., over 6 μg/mL in urine) as they can be harmful to them.
>
>Interestingly, a urinary caffeine concentration greater than 15 µg/mL is still prohibited by the National Collegiate Athletic Association (NCAA). However, since the ban was lifted for almost all associations, caffeine-containing supplements have been hugely popular in the sports world. It has been shown that up to 75–90% of athletes use caffeine before or during competition. The recommended doses of caffeine intake by athletes are 3–6 mg/kg body mass (BM). This is due to the fact that higher doses of caffeine (9–13 mg/kg BM) do not result in additional benefits, and also increase the risk of side effects.

Methods:

>A retrospective cohort study of Kaiser Permanente Southern California
adult patients who had a positive COVID-19 diagnosis between January 1,
2020 and May 31, 2021 was created. The exposure was the median of at
least 3 physical activity self-reports before diagnosis. Patients were
categorized as follows: always inactive, all assessments at 10
minutes/week or less; mostly inactive, median of 0–60 minutes per week;
some activity, median of 60–150 minutes per week; consistently active,
median>150 minutes per week; and always active, all
assessments>150 minutes per week. Outcomes were hospitalization,
deterioration event, or death 90 days after a COVID-19 diagnosis. Data
were analyzed in 2022.

Interpretation:

>This early warning system is the first to identify temporal associations
for PE, AMI, DIC, and ITP following BNT162b2 vaccination in the
elderly. Because an early warning system does not prove that the
vaccines cause these outcomes, more robust epidemiologic studies with
adjustment for confounding, including age and nursing home residency,
are underway to further evaluate these signals. FDA strongly believes
the potential benefits of COVID-19 vaccination outweigh the potential
risks of COVID-19 infection.

>In this study, the results showed that the low efficacy of preventive measures for preventing infection in unvaccinated people does not necessarily mean that they are completely ineffective. As an example, our results show that protective measures on non vaccinated individuals were statistically significant in reducing the need to receive anti-COVID-19 treatments (OR: 0.447, 95% CI = 0.321–0.623; p < 0.0001). These agree with the systematic review of Talic et al., who found a reduction in the incidence of COVID-19 associated with mask-wearing, handwashing, and physical distancing.

Method:

>This study follows a quantitative design to analyse anti-vaccination
tweets posted from the UK. An exploratory content analysis, a strong and commonly used social research method for communication was employed.