Symptoms in the general Norwegian adult population - prevalence and associated factors

Abstract

Background: Patients´ own perceptions and evaluations of symptoms, functioning and other health-related factors, i.e. Patient Reported Outcomes (PROs), are important elements for providing good patient care. Symptoms are subjective and best elicited by the patient orally or by using PRO measures (PROMs), be it on paper, or as electronic assessment tools. Reference values on frequently used PROMs facilitate the interpretation of scores for use in clinics and research settings, by comparing patient data with relevant samples from the general population. Study objectives were to (1) present reference values for the M.D. Anderson Symptom Inventory (MDASI) (2) examine the occurrence and intensity of symptoms assessed by the MDASI in a general Norwegian adult population sample, and (3) examine factors associated with higher symptom burden defined as the sum score of all symptoms, and factors associated with symptoms` interference on functions.Methods: In 2015, MDASI was sent by mail as part of a larger survey, to a representative sample of the general Norwegian adult population (N = 6165). Medical comorbidities were assessed by the Self-Administered Comorbidity Questionnaire. Depression was self-reported on the Patient Health Questionnaire 9 (PHQ-9). Linear multivariable regression analysis was used to examine for factors associated with MDASI sum score and factors associated with symptoms’ interference on functions. Results: The response rate was 36%. More women (54%) than men (46%) responded. Mean age was 55 years (SD 14). The most frequent symptoms were fatigue (59.7%), drowsiness (56.2%) and pain (56.1%). Fatigue, pain and disturbed sleep had the highest mean scores. The presence of one or more comorbidities, increasing PHQ-9 score and lower level of education were associated with higher MDASI sum score (p<0.001). The MDASI sum score and the PHQ-9 score were positively associated with all interference items (p<0.001) except for walking (p=0.22). Conclusion: This study provides the first Norwegian reference values for MDASI. The presence of one or more comorbidities, higher level of depressive symptoms and lower level of education were significantly associated with higher MDASI sum score. These covariates must be controlled for when using the reference values.

Physical Distancing and Mental Health During the COVID-19 Pandemic: Factors Associated With Psychological Symptoms and Adherence to Pandemic Mitigation Strategies

“…In the obtained data from the same population in 2015 estimated by PHQ-9 (cutoff ≥ 10), the prevalence of depression was 10.24%. Consequently, the prevalence of depression in the present pandemic sample is 3 times higher than estimations from the obtained data of the same population (i.e., Norwegian adults) before the pandemic (30.78% vs. 10.24%) as well as approximately 3 times higher than similar representative samples from other countries in nonpandemic periods (8.20%–14.70%), all using the same instrument and cutoff value (Johansson et al, 2013; Kauffman et al, 2021; Krogstad et al, 2020; Maske et al, 2006). In addition, there was a significant difference ( p < .001) in depressive symptoms between participants who predominantly socially distanced themselves and participants who did not.…”

“…Although we did not employ a prospective design and could not directly assess changes in the same subjects, we were able to investigate differences in symptom levels by acquiring data from the same population as the population of the present study (i.e., Norwegian adults) from 2015. This prepandemic sample consists of 1,944 representative and randomly sampled Norwegian adults who had responded to the PHQ-9 before the COVID-19 pandemic (i.e., 2015), including 1,051 females and 893 males (Krogstad et al, 2020). In addition, using the same instruments and cutoff values, we compared the prevalence rates of depression and anxiety in the current pandemic sample with representative prepandemic samples from similar populations as well as more distinct cultures encompassing similar population characteristics.…”

The mental health impact of non-pharmacological interventions aimed at impeding viral transmission during the COVID-19 pandemic in a general adult population and the factors associated with adherence to these mitigation strategies

“…In the obtained data from the same population in 2015 estimated by PHQ-9 (cut-off => 10), the prevalence of depression was 10.24%. Consequently, the prevalence of depression in the present pandemic sample is three times higher than estimations from the obtained data of the same population (i.e., Norwegian adults) before the pandemic (30.78% versus 10.24%), as well as approximately three times higher than similar representative samples from other countries in non-pandemic periods (8.20-14.70%), all using the same instrument and cut-off value (Johansson, Carlbring, Heedman, Paxling, & Anderson, 2013;Kauffman et al, 2020;Krogstad et al, 2020;Maske et al, 2006). Additionally, there was a significant difference (p < .001) in depressive symptoms between those who predominantly socially distanced themselves and those who did not.…”

“…Although we did not employ a prospective design and could not directly assess changes in the same subjects, we were able to investigate differences in symptom levels by acquiring data from the same population as the population of the present study (i.e., Norwegian adults) from 2015. This pre-pandemic sample consists of 1944 representative and randomly sampled Norwegian adults who had responded to the PHQ-9 before the COVID-19 pandemic (i.e., 2015), including 1051 females and 893 males (Krogstad et al, 2020).…”

“…In recent calls for papers (e.g., Brooks et al, 2020;Galea et al, 2020;Holmes et al, 2020;Nature Human Behaviour, 2020;Nature Medicine, 2020;Pfefferbaum & North, 2020;Venkatesh & Edirappuli, 2020;Yao et al, 2020), numerous factors have been suggested to be associated with the potential increases in mental health problems, and other variables are hypothesized to be related to adherence difficulties. In non-pandemic settings, factors associated with increases in depressive and anxiety symptoms include female gender (Nolen-Hoeksema, 2001;McLean, Asnaani, Litz, & Hofmann, 2011), younger age (Molarius et al, 2009), being single (Scott et al, 2010), lower education (Bjelland et al, 2008), and involuntary job loss (Linn, Sandifer, & Stein, 1985). Furthermore, several other factors have been deemed important to investigate regarding depressive and anxiety symptoms in pandemic settings.…”