Risk factors for SARS-CoV-2 infection: a test-negative case-control study with additional population controls in Norway.

OBJECTIVES: This study aims to assess risk factors for SARS-CoV-2 infection by combined design; first comparing positive cases to negative controls as determined by PCR testing and then comparing these two groups to an additional prepandemic population control group. DESIGN AND SETTING: Test-negative design (TND), multicentre case-control study with additional population controls in South-Eastern Norway. PARTICIPANTS: Adults who underwent SARS-CoV-2 PCR testing between February and December 2020. PCR-positive cases, PCR-negative controls and additional age-matched population controls. PRIMARY OUTCOME MEASURES: The associations between various risk factors based on self- reported questionnaire and SARS-CoV-2 infection comparing PCR-positive cases and PCR-negative controls. Using subgroup analysis, the risk factors for both PCR-positive and PCR-negative participants were compared with a population control group. RESULTS: In total, 400 PCR-positive cases, 719 PCR-negative controls and 14 509 population controls were included. Male sex was associated with the risk of SARS-CoV-2 infection only in the TND study (OR 1.9, 95% CI 1.4 to 2.6), but not when PCR-positive cases were compared with population controls (OR 1.2, 95% CI 0.9. to 1.5). Some factors were positively (asthma, wood heating) or negatively (hypertension) associated with SARS-CoV-2 infection when PCR-positive cases were compared with population controls, but lacked convincing association in the TND study. Smoking was negatively associated with the risk of SARS-CoV-2 infection in both analyses (OR 0.5, 95% CI 0.3 to 0.8 and OR 0.6, 95% CI 0.4 to 0.8). CONCLUSIONS: Male sex was a possible risk factor for SARS-CoV-2 infection only in the TND study, whereas smoking was negatively associated with SARS-CoV-2 infection in both the TND study and when using population controls. Several factors were associated with SARS-CoV-2 infection when PCR-positive cases were compared with population controls, but not in the TND study, highlighting the strength of combining case-control study designs during the pandemic.

Loss to 5-year follow-up in the population-based Telemark Study: risk factors and potential for bias.

OBJECTIVES: This study aimed to characterise participants lost to follow-up and identify possible factors associated with non-participation in a prospective population-based study of respiratory health in Norway. We also aimed to analyse the impact of potentially biased risk estimates associated with a high proportion of non-responders. DESIGN: Prospective 5-year follow-up study. SETTING: Randomly selected inhabitants from the general population of Telemark County in south-eastern Norway were invited to fill in a postal questionnaire in 2013. Responders in 2013 were followed-up in 2018. PARTICIPANTS: 16 099 participants aged 16-50 years completed the baseline study. 7958 responded at the 5-year follow-up, while 7723 did not. MAIN OUTCOME MEASURES: χ2 test was performed to compare demographic and respiratory health-related characteristics between those who participated in 2018 and those who were lost to follow-up. Adjusted multivariable logistic regression models were used to assess the relationship between loss to follow-up, background variables, respiratory symptoms, occupational exposure and interactions, and to analyse whether loss to follow-up leads to biased risk estimates. RESULTS: 7723 (49%) participants were lost to follow-up. Loss to follow-up was significantly higher for male participants, those in the youngest age group (16-30 years), those in lowest education level category and among current smokers (all p<0.001). In multivariable logistic regression analysis, loss to follow-up was significantly associated with unemployment (OR 1.34, 95% CI 1.22 to 1.46), reduced work ability (1.48, 1.35 to 1.60), asthma (1.22, 1.10 to 1.35), being woken by chest tightness (1.22, 1.11 to 1.34) and chronic obstructive pulmonary disease (1.81, 1.30 to 2.52). Participants with more respiratory symptoms and exposure to vapour, gas, dust and fumes (VGDF) (1.07 to 1.00-1.15), low-molecular weight (LMW) agents (1.19, 1.00 to 1.41) and irritating agents (1.15, 1.05 to 1.26) were more likely to be lost to follow-up. We found no statistically significant association of wheezing and exposure to LMW agents for all participants at baseline (1.11, 0.90 to 1.36), responders in 2018 (1.12, 0.83 to 1.53) and those lost to follow-up (1.07, 0.81 to 1.42). CONCLUSION: The risk factors for loss to 5-year follow-up were comparable to those reported in other population-based studies and included younger age, male gender, current smoking, lower educational level and higher symptom prevalence and morbidity. We found that exposure to VGDF, irritating and LMW agents can be risk factors associated with loss to follow-up. Results suggest that loss to follow-up did not affect estimates of occupational exposure as a risk factor for respiratory symptoms.

Influence of lifestyle risk factors on work ability and sick leave in a general working population in Norway: a 5-year longitudinal study.

OBJECTIVES: The aim of this study is to assess (1) whether lifestyle risk factors are related to work ability and sick leave in a general working population over time, and (2) these associations within specific disease groups (ie, respiratory diseases, cardiovascular disease and diabetes, and mental illness). SETTING: Telemark county, in the south-eastern part of Norway. DESIGN: Longitudinal study with 5 years follow-up. PARTICIPANTS: The Telemark study is a longitudinal study of the general working population in Telemark county, Norway, aged 16 to 50 years at baseline in 2013 (n=7952) and after 5-year follow-up. OUTCOME MEASURE: Self-reported information on work ability (moderate and poor) and sick leave (short-term and long-term) was assessed at baseline, and during a 5-year follow-up. RESULTS: Obesity (OR=1.64, 95% CI: 1.32 to 2.05) and smoking (OR=1.62, 95% CI: 1.35 to 1.96) were associated with long-term sick leave and, less strongly, with short-term sick leave. An unhealthy diet (OR=1.57, 95% CI: 1.01 to 2.43), and smoking (OR=1.67, 95% CI: 1.24 to 2.25) were associated with poor work ability and, to a smaller extent, with moderate work ability. A higher lifestyle risk score was associated with both sick leave and reduced work ability. Only few associations were found between unhealthy lifestyle factors and sick leave or reduced work ability within disease groups. CONCLUSION: Lifestyle risk factors were associated with sick leave and reduced work ability. To evaluate these associations further, studies assessing the effect of lifestyle interventions on sick leave and work ability are needed.