ReviewHealth services insights2023
Covid-19 and Pre-Morbid Lifestyle-Related Risk Factors-A Review.
Review in Health services insights, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Machine learning models for the prediction of COVID-19 prognosis in the primary health care setting.BMC primary care · 2025Article
- Association of Vitamin D Supplementation with Glutathione Peroxidase (GPx) Activity, Interleukine-6 (IL-6) Levels, and Anxiety and Depression Scores in Patients with Post-COVID-19 Condition.International journal of molecular sciences · 2025Article
- Review
- Association of COVID-19 with thyroid dysfunction and autoimmune thyroid disease: A retrospective cohort study.Journal of translational autoimmunity · 2024Article
- Association Between Rhesus and ABO Blood Group Types and Their Impact on Clinical Outcomes in Critically Ill Patients with COVID-19: A Multi-Center Investigation [Letter].Infection and drug resistance · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Since its outbreak in December 2019 in China, COVID-19 has spread like wild fire to affect many communities of the world. The high infectivity and case fatality rates of the disease among the general population and the severely ill patients respectively drew the attention of the global community. Our review showed that socio-demographic and lifestyle-related risk factors and underlying comorbid diseases were directly and indirectly associated with increased susceptibility and severity of COVID-19. These factors included older age (⩾60 years), male gender, and ethnic minority groups (especially blacks), smoking, low serum level of vitamin D, unhealthy diet, physical inactivity (with poor exposure to sunlight), overweight/obesity, high blood pressure/hypertension, high blood cholesterol, cardiovascular diseases (like stroke and coronary heart disease), diabetes mellitus, chronic obstructive pulmonary disease, chronic kidney disease, chronic liver disease, and some cancers (like leukemia, lymphoma, or myeloma). The literature further revealed that the clinical progression of the majority of these associated risk factors can be modified through effective and comprehensive risk reduction through healthy living and lifestyle modification. COVID-19 preventive and treatment guidelines that give adequate attention to risk reduction and healthy lifestyle among people-either in the pre-, peri-, or post-COVID-19 stage, should be developed by public health policymakers and clinicians. This will play a significant role in the global effort to combat the pandemic, and reduce its negative impact on the life expectancy and socio-economic development of the world particularly in low- and middle-income countries (LMICs).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.