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Additional file 1: Table S1. Original and modified categories of frequency of fish intake in the Tromsø Study. Table S2. Modifications of the frailtyphenotype in the Tromsø7 Study (2015–2016). Table S3. Characteristics of tracking sample in Tromsø4 and Tromsø6 (n=3229). Table S4. Odds ratios (ORs) and 95% confidence intervals (CIs) for fish intake and 8-year follow-up pre-frailty after exclusion of baseline frailty (n = 3219)a. Table S5. Characteristics of participants in Tromsø6 by Tromsø7 participation status (n = 6837)a. Table S6. Odds ratios (ORs) and 95% confidence intervals (CIs) for baseline fish intake and pre-frailty with inverse probability weightsa (n = 6183)b. Table S7. Characteristics of participants in Tromsø6 with complete and incomplete data on fish intake (n = 5750)a. Table S8. Odds ratios (ORs) and 95% confidence intervals (CIs) for patterns of fish intake and pre-frailty using multiple imputation (MI)a (n = 5750)b. Table S9. Onset of physical frailty characteristics in Tromsø7 (n = 4350)a. Table S10. Frailty prevalence in Tromsø7 stratified by age (n = 4350)a.

Epidemiological literature on the relationship between physical activity and chronic pain is scarce and inconsistent. Hence, our aim was to assess the relationship applying comprehensive methodology, including self-reported and accelerometer measures of physical activity and different severity levels of chronic pain. We used data from the Tromsø Study (2015-2016). All residents in the municipality, aged 40 years and older were invited to participate (n=32,591, 51% women). A total of 21,083 (53% women) reported on questionnaires. Additionally, 6,778 participants (54% women) were invited to wear accelerometers (6,125 with complete measurements). Our exposure measures were self-reported leisure time physical activity, exercise frequency, duration and intensity and two accelerometer-measures (steps per day and minutes of moderate to vigorous physical activity per day). Outcome measurements were chronic pain and moderate-to-severe chronic pain. We used Poisson regression to estimate chronic pain prevalence and prevalence ratios for each physical activity measure, with adjustments for sex, age, education level, smoking history, and occupational physical activity. Our main analyses showed an inverse dose-response relationships between all physical activity measures and both severity measures of chronic pain, except that the dose-response relationship with exercise duration was only found for moderate-to-severe pain. All findings were stronger for the moderate-to-severe pain outcomes than for chronic pain. Robustness analyses gave similar results as the main analyses. We conclude that an inverse dose-response association between physical activity and chronic pain is consistent across measures. To summarize, higher levels of physical activity is associated with less chronic pain and moderate-to-severe chronic pain.

BACKGROUND: Protein intake is suggested as an important dietary factor in the prevention of frailty, however, the infuence of lifelong intake remains unclear. OBJECTIVES: The present study investigated the relationship between daily protein intake and patterns of protein intake over 21 years and the risk of pre-frailty/frailty. DESIGN: Prospective cohort study. SETTING: The population-based Tromsø Study in Tromsø municipality, Norway. PARTICIPANTS: In total, 1,906 women and 1,820 men aged >45 years in 1994 who participated in both Tromsø4 (1994–95) and Tromsø7 (2015–16). MEASUREMENTS: Frailty status in Tromsø7 was measured according to Fried’s phenotype, classifying participants as “robust” (frailty components present: 0), “pre-frail” (1–2) or “frail” (>3). Daily intake of protein was estimated from self-reported habitual dietary intake using food frequency questionnaires and assessed as grams per kilogram bodyweight (g/kg BW) and per megajoule energy intake (g/MJ). The protein–frailty association was assessed via longitudinal and crosssectional multivariable logistic regression analyses. RESULTS: The prevalence of pre-frailty and frailty in this study was 27% and 1.0%, respectively. Longitudinal analysis showed that the odds of pre-frailty/frailty decreased by 57% (odds ratio (OR) = 0.43, 95% confdence interval (CI) = 0.31;0.58, pCONCLUSIONS: Intake of protein in g/kg BW both in mid-life and later in life was inversely associated with pre-frailty/frailty in older adults. This emphasizes the importance of an adequate protein intake to facilitate healthy ageing in Norwegian older adults.

Background A healthy diet can decrease the risk of several lifestyle diseases. From studying the health effects of single foods, research now focuses on examining complete diets and dietary patterns reflecting the combined intake of different foods. The main goals of the current study were to identify dietary patterns and then investigate how these differ in terms of sex, age, educational level and physical activity level (PAL) in a general Nordic population. Methods We used data from the seventh survey of the population-based Tromsø Study in Norway, conducted in 2015-2016. The study included 21,083 participants aged $$40-99$$ 40 - 99 years, of which $$72\%$$ 72 % completed a comprehensive food frequency questionnaire (FFQ). After exclusion, the study sample included 10,899 participants with valid FFQ data. First, to cluster food variables, the participants were partitioned in homogeneous cohorts according to sex, age, educational level and PAL. Non-overlapping diet groups were then identified using repeated hierarchical cluster analysis on the food variables. Second, average standardized diet intake scores were calculated for all individuals for each diet group. The individual diet (intake) scores were then modelled in terms of age, education and PAL using regression models. Differences in diet scores according to education and PAL were investigated by pairwise hypothesis tests, controlling the nominal significance level using Tukey’s method. Results The cluster analysis revealed three dietary patterns, here named the Meat and Sweets diet, the Traditional diet, and the Plant-based- and Tea diet. Women had a lower intake of the Traditional diet and a higher preference for the Plant-based- and Tea diet compared to men. Preference for the Meat and Sweets diet and Traditional diet showed significant negative and positive trends as function of age, respectively. Adjusting for age, the group having high education and high PAL compared favourably with the group having low education and low PAL, having a significant lower intake of the Meat and Sweets and the Traditional diets and a significant higher intake of the Plant-based- and Tea diet. Conclusions Three dietary patterns (Meat and Sweets, Traditional, and Plant-based- and Tea) were found by repeated clustering of randomly sampled homogeneous cohorts of individuals. Diet preferences depended significantly on sex, age, education and PAL, showing a more unhealthy dietary pattern with lower age, low education and low PAL.

ObjectivesThe aim of this study was to investigate time trends in known and undiagnosed diabetes, glycated haemoglobin (HbA1c) levels and other cardiometabolic risk factors in the general population as well as treatment target achievement among those with diabetes.Design and settingRepeated cross-sectional surveys in the population-based Tromsø Study.MethodsWe used age-adjusted generalised estimating equation models to study trends in self-reported and undiagnosed (HbA1c ≥6.5%) diabetes, cardiometabolic risk factors and the metabolic syndrome in 27 281 women and men aged 40–84 years examined in up to four surveys of the Tromsø Study between 1994 and 2016. Further, we analysed trends in diabetes treatment target achievement.ResultsDuring 1994–2016, diabetes prevalence increased in women (2.3% to 4.6%) and men (2.4% to 5.8%) and in all age groups, while the proportion of undiagnosed diabetes in women (32% to 17%) and men (37% to 24%) decreased. Blood pressure and total cholesterol decreased, while waist circumference increased in participants with and without diabetes, leading to a relatively stable prevalence of the metabolic syndrome throughout the study period. There was a marginal increase in HbA1c levels among participants without diabetes. Only half of those with diabetes achieved the treatment target of HbA1c ≤7.0%.ConclusionIn the last two decades, diabetes prevalence increased, while the proportion of undiagnosed diabetes declined. The prevalence of the metabolic syndrome remained stable throughout, driven by opposing trends with an increase in obesity and a decrease in other cardiometabolic risk factors. HbA1c treatment target achievement did not improve.

Supplemental material, sj-docx-1-sjp-10.1177_14034948211011796 for Trends in Disability-Free Life Expectancy (DFLE) from 1995 to 2017 in the older Norwegian population by sex and education: The HUNT Study by Siri H. Storeng, Simon Øverland, Vegard Skirbekk ERSTATT, Laila Arnesdatter Hopstock, Erik R. Sund, Steinar Krokstad and Bjørn H. Strand in Scandinavian Journal of Public Health

Additional File 3 Supplementary Table 3. Hazard ratio for all-cause death between combinations of categories of hard and light physical activity levels ores as time-dependent covariates.

Additional file 1: Supplementary Table 1. Physical activity level according to age and sex. Supplementary figure 1. Activity level according to age and sex.

Additional file 1. Participant Flow Chart. All inhabitants in Tromsø municipality aged 40 years and older (N = 32,591) were invited to the basic examination. A sub-sample (N = 13,028) was pre-marked for invitation to participate in the extended examination conducted approximately 2 weeks later. This sub-sample consisted of a) a randomized sample (N = 9925), and b) Tromsø 6 (2007–2008) participants who attended body composition, echocardiogram and eye examinations (n = 3103). A total of 21,083 women and men aged 40–99 years attended the basic examination (65%). A total of 8346 attended the extended examination (64% of the original pre-marked sub-sample and 90% of the sub-sample who also attended the basic examination). In the present study we included participants aged 40–84 years with complete data from physical function and body composition measurements (n = 3498).

Additional file 2: Supplementary Table 2. Results from the random coefficient proportional odds model with estimates for the sex-specific associations of subject-specific factors with self-reported health.

Source at https://digitalcommons.wku.edu/ijes/vol13/iss4/9/. Collecting objective physical activity data from research participants are increasingly done using consumer-based activity trackers. Several validation studies of Polar devices are conducted to date, but no systematic review of the current level of accuracy for these devices exist. The aim of this study is therefore to investigate the accuracy of current wrist-worn Polar devices that equips a triaxial accelerometer to measure physical activity. We conducted a systematic review by searching six databases for validation studies on modern Polar activity trackers. Studies were grouped and examined by tested outcome, i.e. energy expenditure, physical activity intensity, and steps. We summarized and reported relevant metrics from each study. The initial search resulted in 157 studies, out of which fourteen studies were included in the final review. Energy expenditure was reviewed in seven studies, physical activity intensity was reviewed in four studies, and steps was reviewed in 11 studies. There is a large difference in study protocols with conflicting results between the identified studies. However, for energy expenditure there is some indication that Polar devices perform better in free-living, compared to lab-based studies. In addition, step counting seems to have less average error compared to energy expenditure and physical activity intensity. There is large heterogeneity between the identified studies, both in terms of study protocols and results, and the accuracy of Polar devices remains unclear. More studies are needed for more recently developed devices, and future studies should take care to follow guidelines for assessment of wearable sensors designed for physical activity monitoring.

Additional file 2. Comparison of study sample to larger sample with only physical function measures.