Important consideration when combining data is independence. If the cohorts can be considered independent, that is, properties of one cohort do not affect the others, then you can combine them. If cohorts influence each other, then considering them as one sample is problematic. Important document is attached below:

If population characteristics are different, one may mix but it needs to be analyzed against relevant characteristics or independent variables.

I agree with Suraj Kapoor's answer'

Thank you sir

Yes, they may be combined if the populations are independent, but with this anticipated bias at design level, y not avoid it, should u be pushed to the wall, combine but consider clustering at time variable

This study design would introduce more bias and would obscure the true causal association.

I agree with Mr. Han. Care should be taken to analyze separately even after merging to avoid bias if time-line is different to assess its effect on outcome of the study if any

Analyzing data from two cohorts studies (retrospectively & prospectively) for different populations spearately and then combine the results using a meta-analysis approach may be more appropriate.

I would like to extend my sincere gratitude to you all and all the members of the ResearchGate community for sharing your valuable input and assistance in helping me to finaliz my below paper using retrospectively & prospectively study design.

Impact of vaccination and risk factors on COVID-19 mortality amid delta wave in Libya: A single center cohort study.

https://www.researchgate.net/publication/372913621_Impact_of_vaccination_and_risk_factors_on_COVID-19_mortality_amid_delta_wave_in_Libya_A_single_center_cohort_study?_tp=eyJjb250ZXh0Ijp7ImZpcnN0UGFnZSI6Il9kaXJlY3QiLCJwYWdlIjoicHJvZmlsZSJ9fQ

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