Device-Measured 24-Hour Movement Behaviors and Blood Pressure: A 6-Part Compositional Individual Participant Data Analysis in the ProPASS Consortium.

BACKGROUND: Blood pressure (BP)-lowering effects of structured exercise are well-established. Effects of 24-hour movement behaviors captured in free-living settings have received less attention. This cross-sectional study investigated associations between a 24-hour behavior composition comprising 6 parts (sleeping, sedentary behavior, standing, slow walking, fast walking, and combined exercise-like activity [eg, running and cycling]) and systolic BP (SBP) and diastolic BP (DBP). METHODS: Data from thigh-worn accelerometers and BP measurements were collected from 6 cohorts in the Prospective Physical Activity, Sitting and Sleep consortium (ProPASS) (n=14 761; mean±SD, 54.2±9.6 years). Individual participant analysis using compositional data analysis was conducted with adjustments for relevant harmonized covariates. Based on the average sample composition, reallocation plots examined estimated BP reductions through behavioral replacement; the theoretical benefits of optimal (ie, clinically meaningful improvement in SBP [2 mm Hg] or DBP [1 mm Hg]) and minimal (ie, 5-minute reallocation) behavioral replacements were identified. RESULTS: The average 24-hour composition consisted of sleeping (7.13±1.19 hours), sedentary behavior (10.7±1.9 hours), standing (3.2±1.1 hours), slow walking (1.6±0.6 hours), fast walking (1.1±0.5 hours), and exercise-like activity (16.0±16.3 minutes). More time spent exercising or sleeping, relative to other behaviors, was associated with lower BP. An additional 5 minutes of exercise-like activity was associated with estimated reductions of -0.68 mm Hg (95% CI, -0.15, -1.21) SBP and -0.54 mm Hg (95% CI, -0.19, 0.89) DBP. Clinically meaningful improvements in SBP and DBP were estimated after 20 to 27 minutes and 10 to 15 minutes of reallocation of time in other behaviors into additional exercise. Although more time spent being sedentary was adversely associated with SBP and DBP, there was minimal impact of standing or walking. CONCLUSIONS: Study findings reiterate the importance of exercise for BP control, suggesting that small additional amounts of exercise are associated with lower BP in a free-living setting.

Device-measured physical activity and cardiometabolic health: the Prospective Physical Activity, Sitting, and Sleep (ProPASS) consortium.

BACKGROUND AND AIMS: Physical inactivity, sedentary behaviour (SB), and inadequate sleep are key behavioural risk factors of cardiometabolic diseases. Each behaviour is mainly considered in isolation, despite clear behavioural and biological interdependencies. The aim of this study was to investigate associations of five-part movement compositions with adiposity and cardiometabolic biomarkers. METHODS: Cross-sectional data from six studies (n = 15 253 participants; five countries) from the Prospective Physical Activity, Sitting and Sleep consortium were analysed. Device-measured time spent in sleep, SB, standing, light-intensity physical activity (LIPA), and moderate-vigorous physical activity (MVPA) made up the composition. Outcomes included body mass index (BMI), waist circumference, HDL cholesterol, total:HDL cholesterol ratio, triglycerides, and glycated haemoglobin (HbA1c). Compositional linear regression examined associations between compositions and outcomes, including modelling time reallocation between behaviours. RESULTS: The average daily composition of the sample (age: 53.7 ± 9.7 years; 54.7% female) was 7.7 h sleeping, 10.4 h sedentary, 3.1 h standing, 1.5 h LIPA, and 1.3 h MVPA. A greater MVPA proportion and smaller SB proportion were associated with better outcomes. Reallocating time from SB, standing, LIPA, or sleep into MVPA resulted in better scores across all outcomes. For example, replacing 30 min of SB, sleep, standing, or LIPA with MVPA was associated with -0.63 (95% confidence interval -0.48, -0.79), -0.43 (-0.25, -0.59), -0.40 (-0.25, -0.56), and -0.15 (0.05, -0.34) kg/m2 lower BMI, respectively. Greater relative standing time was beneficial, whereas sleep had a detrimental association when replacing LIPA/MVPA and positive association when replacing SB. The minimal displacement of any behaviour into MVPA for improved cardiometabolic health ranged from 3.8 (HbA1c) to 12.7 (triglycerides) min/day. CONCLUSIONS: Compositional data analyses revealed a distinct hierarchy of behaviours. Moderate-vigorous physical activity demonstrated the strongest, most time-efficient protective associations with cardiometabolic outcomes. Theoretical benefits from reallocating SB into sleep, standing, or LIPA required substantial changes in daily activity.

Relationship of device measured physical activity type and posture with cardiometabolic health markers: pooled dose-response associations from the Prospective Physical Activity, Sitting and Sleep Consortium.

AIMS/HYPOTHESIS: The aim of this study was to examine the dose-response associations of device-measured physical activity types and postures (sitting and standing time) with cardiometabolic health. METHODS: We conducted an individual participant harmonised meta-analysis of 12,095 adults (mean ± SD age 54.5±9.6 years; female participants 54.8%) from six cohorts with thigh-worn accelerometry data from the Prospective Physical Activity, Sitting and Sleep (ProPASS) Consortium. Associations of daily walking, stair climbing, running, standing and sitting time with a composite cardiometabolic health score (based on standardised z scores) and individual cardiometabolic markers (BMI, waist circumference, triglycerides, HDL-cholesterol, HbA1c and total cholesterol) were examined cross-sectionally using generalised linear modelling and cubic splines. RESULTS: We observed more favourable composite cardiometabolic health (i.e. z score <0) with approximately 64 min/day walking (z score [95% CI] -0.14 [-0.25, -0.02]) and 5 min/day stair climbing (-0.14 [-0.24, -0.03]). We observed an equivalent magnitude of association at 2.6 h/day standing. Any amount of running was associated with better composite cardiometabolic health. We did not observe an upper limit to the magnitude of the dose-response associations for any activity type or standing. There was an inverse dose-response association between sitting time and composite cardiometabolic health that became markedly less favourable when daily durations exceeded 12.1 h/day. Associations for sitting time were no longer significant after excluding participants with prevalent CVD or medication use. The dose-response pattern was generally consistent between activity and posture types and individual cardiometabolic health markers. CONCLUSIONS/INTERPRETATION: In this first activity type-specific analysis of device-based physical activity, ~64 min/day of walking and ~5.0 min/day of stair climbing were associated with a favourable cardiometabolic risk profile. The deleterious associations of sitting time were fully attenuated after exclusion of participants with prevalent CVD and medication use. Our findings on cardiometabolic health and durations of different activities of daily living and posture may guide future interventions involving lifestyle modification.

Secular trends in risk factors for adolescent anxiety and depression symptoms: the Young-HUNT studies 1995-2019, Norway.

In recent decades, increases in mental health problems in adolescents have been reported from several large population-based surveys. This raises questions about changes in underlying risk and protective factors that can inform future intervention strategies. Population data were collected from 1995 to 2019 in three waves of the Young-HUNT studies in Norway to map decennial trends in the prevalence of established risk factors for, and their associations with, adolescent mental health problems. All adolescents (aged 13-19 years) attending lower and upper secondary school in the county of Trøndelag were invited, representing three historical cohorts of 25,245 unique adolescents. Mental health problems (HSCL-5) and established mental health risk factors were self-reported. Using a generalized linear model and linear regression, we calculated changes in relative and absolute differences between risk factors and mental health problems. Overall, the prevalence of established risk factors for mental health problems in adolescence increased markedly between 1995 and 2019, especially in girls. Prominent increases were observed for fatigue, bullying, musculoskeletal pain and migraine, loneliness, and overweight. Furthermore, with the exception of excess alcohol use and family economy, associations between each risk factor and adolescent mental health problems strengthened over the same time span in girls, but less among boys. Our findings suggest that several modifiable risk factors for poor mental health in adolescence are increasing, especially among girls, and should be targeted in community, school, and in clinical settings.

The impact of selected methodological factors on data collection outcomes in observational studies of device-measured physical behaviour in adults: A systematic review.

BACKGROUND: Accelerometer measures of physical behaviours (physical activity, sedentary behaviour and sleep) in observational studies offer detailed insight into associations with health and disease. Maximising recruitment and accelerometer wear, and minimising data loss remain key challenges. How varying methods used to collect accelerometer data influence data collection outcomes is poorly understood. We examined the influence of accelerometer placement and other methodological factors on participant recruitment, adherence and data loss in observational studies of adult physical behaviours. METHODS: The review was in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA). Observational studies of adults including accelerometer measurement of physical behaviours were identified using database (MEDLINE (Ovid), Embase, PsychINFO, Health Management Information Consortium, Web of Science, SPORTDiscus and Cumulative Index to Nursing & Allied Health Literature) and supplementary searches to May 2022. Information regarding study design, accelerometer data collection methods and outcomes were extracted for each accelerometer measurement (study wave). Random effects meta-analyses and narrative syntheses were used to examine associations of methodological factors with participant recruitment, adherence and data loss. RESULTS: 123 accelerometer data collection waves were identified from 95 studies (92.5% from high-income countries). In-person distribution of accelerometers was associated with a greater proportion of invited participants consenting to wear an accelerometer (+ 30% [95% CI 18%, 42%] compared to postal distribution), and adhering to minimum wear criteria (+ 15% [4%, 25%]). The proportion of participants meeting minimum wear criteria was higher when accelerometers were worn at the wrist (+ 14% [ 5%, 23%]) compared to waist. Daily wear-time tended to be higher in studies using wrist-worn accelerometers compared to other wear locations. Reporting of information regarding data collection was inconsistent. CONCLUSION: Methodological decisions including accelerometer wear-location and method of distribution may influence important data collection outcomes including recruitment and accelerometer wear-time. Consistent and comprehensive reporting of accelerometer data collection methods and outcomes is needed to support development of future studies and international consortia. Review supported by the British Heart Foundation (SP/F/20/150002) and registered (Prospero CRD42020213465).

Patterns of physical activity over 34 years in a large sample of adults: The HUNT study, Norway.

AIMS: To examine physical activity patterns over 34 years in a representative adult population in Norway. METHODS: Longitudinal data were obtained from the Helseundersøkelsen i Trøndelag (HUNT) study, performed in 1984-1986 (HUNT1), 2006-2008 (HUNT3) and 2017-2019 (HUNT4). There were a total 123,005 participants across all four studies. Physical activity patterns over time are described, in relation to age, gender and body mass index (BMI). Multiple imputation was used to handle missing data. RESULTS: The proportion of adults estimated (using a proxy measure) as being physically active 1 h or more per week increased from 32% in 1984-1986 (HUNT1) to 64% in 2017-2019 (HUNT4). The most frequent pattern was being inactive at HUNT1, becoming active at HUNT3 and staying active (until HUNT4). From HUNT3 to HUNT4, the most frequent pattern was being active at both time points. The adults >50 years old had a similar physical activity pattern from HUNT3 to HUNT4 and were more active than those >50 years. During the period, men were more active than woman, but difference was reduced over time. Both for persons being underweight (BMI ⩽ 18.5) or obese (BMI > 30), the proportion being active at multiple time points was lower than for persons at normal weight. CONCLUSIONS: The data indicate a noticeable increase in being physically active for 1 h or more per week during the 34-year study period. Relatively stable patterns of physical activity were identified, with some variations according to age, gender and BMI.

Lower levels of physical activity volume are beneficial, and it's never too late to start: Results from the HUNT Study, Norway.

AIMS: We aimed to explore (a) how different patterns of physical activity (PA) over time (36 years) were associated with all-cause and cause-specific mortality, (b) if the association was similar for males and females and for different body mass levels and (c) how change in PA was associated with mortality for subjects who started out as physically inactive. METHODS: The study is based on the prospective population-based cohort Trøndelag Health Study (HUNT) from 1984 to 2020, across four study waves. Data were linked to the Norwegian Cause of Death Registry. There were 123,005 participants, divided into three groups: persistently active, persistently inactive and mixed, with two cut-offs for PA: 60 and 150 minutes per week. The results are reported as cumulative incidence and hazard ratios (HRs). RESULTS: At 60 minutes of PA per week, 8% of participants were persistently inactive, 15% were persistently active and 77% had a mixed pattern. At 150 minutes, the corresponding numbers were 32%, 2% and 65%. Compared to the persistently inactive group, for the 60-minute cut-off, the mixed group had an all-cause mortality HR of 0.83 (95% confidence interval (CI) 0.70-0.98), and the persistently active group had an HR of 0.51 (95% CI 0.40-0.65). For the 150-minute cut-off, the corresponding HRs were 0.84 (95% CI 0.75-0.94) and 0.48 (95% CI 0.26-0.88). The patterns were similar for males and females and across body mass index levels. Initially inactive participants had lower mortality if they ended up physically active, regardless of their activity level at an intermediate time point. CONCLUSIONS: At least 60 minutes of PA per week was associated with a marked reduction in mortality when this was a lasting habit over three decades. Given that six times as many people reach this less ambitious goal, it is vital to encourage all levels of PA in public health promotion. Any increase in PA during the lifespan is beneficial.

HUNT for better public health.

AIMS: The Trøndelag Health Study (HUNT) has collected population data through comprehensive decennial surveys over the last four decades and has so far collected data from 240,000 participants. The participants are identified with the unique Norwegian birth number, which enables them to be followed throughout different life stages, from survey to survey, and to endpoint measures in Norwegian national health registers without attrition bias. METHODS: The study design of HUNT offers several advantages: it provides an overview of the public health development in the population over decades, the data can be used in health services research, clinical epidemiology, studies of causation, trajectories, and consequences of diseases, and to study gene × environment interactions. RESULTS: HUNT data have shown major shifts in public health trends, such as decreasing mean blood pressure and resting heart rate among adults, increasing prevalence of obesity, geographical and socioeconomic inequalities in health, increasing mental health distress among adolescents and young adults with an opposite development among the elderly. Data from HUNT have been used in several major international research projects, where data harmonization with several other population cohorts internationally has been done. HUNT has placed great emphasis on safeguarding research ethics, privacy, and data security. The Norwegian authorities established national regulations for the surveys from the time General Data Protection Regulation was introduced in 2018. CONCLUSIONS: Researchers can apply for HUNT data access from HUNT Research Centre provided they have obtained project approval from the Regional Committee for Medical and Health Research Ethics. Researchers not affiliated to a Norwegian research institution must collaborate with and apply through a Norwegian principal investigator. Information on the application and conditions for data access is available at www.ntnu.edu/hunt/data.

Comparison of physical behavior estimates from three different thigh-worn accelerometers brands: a proof-of-concept for the Prospective Physical Activity, Sitting, and Sleep consortium (ProPASS).

BACKGROUND: Pooling data from thigh-worn accelerometers across multiple studies has great potential to advance evidence on the health benefits of physical activity. This requires harmonization of information on body postures, physical activity types, volumes and time patterns across different brands of devices. The aim of this study is to compare the physical behavior estimates provided by three different brands of thigh-worn accelerometers. METHODS: Twenty participants volunteered for a 7-day free-living measurement. Three accelerometers - ActiGraph GT3X+, Axivity AX3 and ActivPAL Micro4 - were randomly placed in a vertical line on the midsection of the right thigh. Raw data from each accelerometer was processed and classified into 8 physical activities and postures using the Acti4 software. Absolute differences between estimates and the respective coefficient of variation (CV) were calculated. RESULTS: We observed very minor differences between physical behavior estimates from three different accelerometer brands. When averaged over 24 h (1,440 min), the absolute difference (CV) between accelerometers were: 1.2 mins (0.001) for lying/sitting, 3.4 mins (0.02) for standing, 3.5 mins (0.06) for moving, 1.9 mins (0.03) for walking, 0.1 mins (0.19) for running, 1.2 mins (0.19) for stair climbing, 1.9 mins (0.07) for cycling. Moreover, there was an average absolute difference of 282 steps (0.03) per 24 h. CONCLUSIONS: Physical behaviors were classified with negligible difference between the accelerometer brands. These results support harmonization of data from different thigh-worn accelerometers across multiple cohorts when analyzed in an identical manner.

Prolonged sitting may increase diabetes risk in physically inactive individuals: an 11 year follow-up of the HUNT Study, Norway.

AIMS/HYPOTHESIS: We examined the association between sitting time and diabetes incidence, overall and by strata of leisure-time physical activity and BMI. METHODS: We followed 28,051 adult participants of the Nord-Trøndelag Health Study (the HUNT Study), a population-based study, for diabetes incidence from 1995-1997 to 2006-2008 and estimated HRs of any diabetes by categories of self-reported total daily sitting time at baseline. RESULTS: Of 28,051 participants, 1253 (4.5%) developed diabetes during 11 years of follow-up. Overall, sitting ≥8 h/day was associated with a 17% (95% CI 2, 34) higher risk of developing diabetes compared with sitting ≤4 h/day, adjusted for age, sex and education. However, the association was attenuated to a non-significant 9% (95% CI -5, 26) increase in risk after adjustment for leisure-time physical activity and BMI. The association between sitting time and diabetes risk differed by leisure-time physical activity (p Interaction = 0.01). Among participants with low leisure-time physical activity (≤2 h light activity per week and no vigorous activity), sitting 5-7 h/day and ≥8 h/day were associated with a 26% (95% CI 2, 57) and 30% (95% CI 5, 61) higher risk of diabetes, respectively, compared with sitting ≤4 h/day. There was no corresponding association among participants with high leisure-time physical activity (≥3 h light activity or >0 h vigorous activity per week). There was no statistical evidence that the association between sitting time and diabetes risk differed by obesity (p Interaction = 0.65). CONCLUSIONS/INTERPRETATION: Our findings suggest that total sitting time has little association with diabetes risk in the population as a whole, but prolonged sitting may contribute to an increased diabetes risk among physically inactive people.

Patterns of sitting and mortality in the Nord-Trøndelag health study (HUNT).

BACKGROUND: Current evidence concerning sedentary behaviour and mortality risk has used single time point assessments of sitting. Little is known about how changes in sitting levels over time affect subsequent mortality risk. AIM: To examine the associations between patterns of sitting time assessed at two time points 11 years apart and risk of all-cause and cardio-metabolic disease mortality. METHODS: Participants were 25,651 adults aged > =20 years old from the Nord-Trøndelag Health Study with self-reported total sitting time in 1995-1997 (HUNT2) and 2006-2008 (HUNT3). Four categories characterised patterns of sitting: (1) low at HUNT2/ low at HUNT3, 'consistently low sitting'; (2) low at HUNT2/high at HUNT3, 'increased sitting'; (3) high at HUNT2/low at HUNT3, 'reduced sitting'; and (4) high at HUNT2 /high at HUNT3, 'consistently high sitting'. Associations of sitting pattern with all-cause and cardio-metabolic disease mortality were analysed using Cox regression adjusted for confounders. RESULTS: Mean follow-up was 6.2 years (158880 person-years); 1212 participants died. Compared to 'consistently low sitting', adjusted hazard ratios for all-cause mortality were 1.51 (95% CI: 1.28-2.78), 1.03 (95% CI: 0.88-1.20), and 1.26 (95% CI: 1.06-1.51) for 'increased sitting', 'reduced sitting' and 'consistently high sitting' respectively. CONCLUSIONS: Examining patterns of sitting over time augments single time-point analyses of risk exposures associated with high sitting time. Whilst sitting habits can be stable over a long period, life events (e.g., changing jobs, retiring or illness) may influence sitting trajectories and therefore sitting-attributable risk. Reducing sitting may yield mortality risks comparable to a stable low-sitting pattern.

Physical activity, obesity and mortality: does pattern of physical activity have stronger epidemiological associations?

BACKGROUND: Most studies of physical activity (PA) epidemiology use behaviour measured at a single time-point. We examined whether 'PA patterns' (consistently low, consistently high or inconsistent PA levels over time) showed different epidemiological relationships for anthropometric and mortality outcomes, compared to single time-point measure of PA. METHODS: Data were the Danish MONICA (MONItoring Trends and Determinants in CArdiovascular Disease) study over three waves 1982-3 (time 1), 1987-8 (time 2) and 1993-4 (time 3). Associations between leisure time single time-point PA levels at time 1 and time 3, and sport and active travel at times 1 and 2 with BMI, waist, hip circumference and mortality (death from coronary heart disease (CHD) and cardiovascular disease (CVD)) were compared to 'PA patterns' spanning multiple time points. PA pattern classified participants' PA as either 1) inactive or low PA at both time points; 2) moderate level PA at time 1 and high activity at time 3; or 3) a 'mixed PA pattern' indicating a varying levels of activity over time. Similarly, sport and active travel were also classified as indicating stable low, stable high and mixed patterns. RESULTS: The moderately and highly active groups for PA at times 1 and 3 had up to 1.7 cm lower increase in waist circumference compared with the inactive/low active group. Across 'PA patterns', 'active maintainers' had a 2.0 cm lower waist circumference than 'inactive/low maintainers'. Waist circumference was inversely related to sport but not active travel. CHD risk did not vary by activity levels at time 1, but was reduced significantly by 43% for high PA at time 3 (vs 'inactive' group) and among 'active maintainers' (vs 'inactive/low maintainers') by 62%. 'Sport pattern' showed stronger reductions in mortality for cardiovascular disease and CHD deaths among sport maintainers, than the single time point measures. CONCLUSIONS: PA patterns demonstrated a stronger association with a number of anthropometric and mortality outcomes than the single time-point measures. Operationalising PA as a sustained behavioural pattern may address some of the known under-estimation of risk for poor health in PA self-report measurements and better reflect exposure for epidemiological analysis of risk of health outcomes.

Multiple lifestyle behaviours and mortality, findings from a large population-based Norwegian cohort study - The HUNT Study.

BACKGROUND: Lifestyle risk behaviours are responsible for a large proportion of disease burden and premature mortality worldwide. Risk behaviours tend to cluster in populations. We developed a new lifestyle risk index by including emerging risk factors (sleep, sitting time, and social participation) and examine unique risk combinations and their associations with all-cause and cardio-metabolic mortality. METHODS: Data are from a large population-based cohort study in a Norway, the Nord-Trøndelag Health Study (HUNT), with an average follow-up time of 14.1 years. Baseline data from 1995-97 were linked to the Norwegian Causes of Death Registry. The analytic sample comprised 36 911 adults aged 20-69 years. Cox regression models were first fitted for seven risk factors (poor diet, excessive alcohol consumption, current smoking, physical inactivity, excessive sitting, too much/too little sleep, and poor social participation) separately and then adjusted for socio-demographic covariates. Based on these results, a lifestyle risk index was developed. Finally, we explored common combinations of the risk factors in relation to all-cause and cardio-metabolic mortality outcomes. RESULTS: All single risk factors, except for diet, were significantly associated with both mortality outcomes, and were therefore selected to form a lifestyle risk index. Risk of mortality increased as the index score increased. The hazard ratio for all-cause mortality increased from 1.37 (1.15-1.62) to 6.15 (3.56-10.63) as the number of index risk factors increased from one to six respectively. Among the most common risk factor combinations the association with mortality was particularly strong when smoking and/or social participation were included. CONCLUSIONS: This study adds to previous research on multiple risk behaviours by incorporating emerging risk factors. Findings regarding social participation and prolonged sitting suggest new components of healthy lifestyles and potential new directions for population health interventions.

The effect of a music-based caregiving intervention on pain intensity in nursing home patients with dementia: a cluster-randomized controlled study.

ABSTRACT: Treatment of chronic pain in patients with dementia is challenging because they have reduced ability to report pain and are particularly vulnerable to side effects of analgesics. Different types of music-based therapy have been recommended and are used as an alternative to analgesics, but the evidence is lacking. Therefore, we performed a cluster-randomized controlled study (RCT) to reduce pain intensity using music-based caregiving (MBC) over 8 weeks in nursing home patients with dementia and chronic pain. We also investigated if the amount of MBC and different chronic pain syndromes would impact on the effect. Of the 645 patients, 498 patients from 36 wards in 12 nursing homes were screened for dementia and pain. Using the Clinical Dementia Rating Scale and the Mobilization-Observation-Behavior-Intensity-Dementia Pain Scale (range 0-10), 279 (71% females, 42% severe dementia) nursing home patients were randomized to intervention group (n = 134, 18 wards) or control group (n = 145, 18 wards). The main outcome was change in pain intensity before and after the intervention. The study did not reveal any effect of MBC on pain intensity when compared with the control group (B = -0.15, 95% CI [-0.72 to 0.43]). No significant difference was found within the intervention group analyzing the impact of intervention time (B = 0.73, 95% CI [-0.55 to 2.02]) or chronic primary vs secondary pain syndromes (B = 0.45, 95% CI [-0.05 to 0.96]). Our data from this first RCT on music and pain intensity in patients with dementia and chronic pain did not find an effect of MBC on pain.

Association between engagement in cultural activities and use of general practitioner consultations: 7-year follow-up of adults from the HUNT study, Norway.

OBJECTIVE: Assess whether engagement in a range of cultural activities, both 'passive' and 'active' (ie, receptive and creative) participation, is associated with later demand for general practitioner (GP) consultations. DESIGN: Longitudinal prospective cohort study. SETTING: Data from the population-based the third Survey of Trøndelag Health Study (2006-2008) in Norway was linked to an administrative register including service information from all GP offices nationwide. PARTICIPANTS: This study included 17 396 (54.6%) women and 14 451 (45.4%) men aged 30-79 years. MAIN OUTCOME MEASURES: Multilevel negative binomial regression models assessed the relationship between cultural engagement and GP consultations, and reported as rate ratios. RESULTS: A mean of 3.57 GP visits per patient was recorded during the 7 years of follow-up. Participation in creative activities and a combination of both receptive and creative activities was associated with lower number of GP consultation. Gender-specific analyses suggest that these effects were attributable to men. The rate ratio of GP consultations among men taking part in creative activities less than once, twice and more than twice (<9 times) per week is 0.90, 0.89 and 0.87 times lower, respectively, compared with non-participants. Whereas weekly frequency of receptive and creative activity engagement showed a 0.92, 0.87 and 0.83 times lower rate ratio among engaged men. The variety of activities shows a similar pattern and participation in creative activities lowers the rate ratio among men. Engagement in a wide range/variety of activities, compared with non-engagement, was associated with lower numbers of GP consultations in men, but not women. CONCLUSIONS: Engagement in creative or combined receptive and creative cultural activities was associated with lower numbers of GP consultations among men. Thus, facilitating and promoting a culturally engaged lifestyle, particularly in men, may affect primary healthcare use. However, this study design gives no evidence of a causal relationship between cultural engagement and use of GP consultations.

Feasibility of a Postpartum Web- and Phone-Based Lifestyle Program for Women with a History of Preeclampsia or Gestational Diabetes: A Pilot Intervention Study.

Background: Women with a history of preeclampsia (PE) or gestational diabetes mellitus (GDM) are at increased risk of diabetes and cardiovascular disease (CVD) later in life. Increased awareness of pregnancy complications as early warning signs for CVD has called for postpartum primordial prevention strategies. The aim of this study was to evaluate the feasibility of a postpartum web- and phone-based lifestyle program promoting healthy lifestyle behaviors to women after a pregnancy complicated by PE or GDM. Materials and Methods: Women with a validated history of PE or GDM were invited to participate in a nonrandomized pilot intervention study 3-12 months after delivery. The intervention was delivered over 6 months. All participants received tailored lifestyle counseling by a registered dietitian and access to information material on healthy lifestyle behaviors on the study's website. After inclusion, participants were invited to three study visits at baseline, 3 months, and 6 months. Feasibility outcomes included assessment of recruitment, retention, and acceptability. Secondary outcomes were changes in lifestyle behaviors and cardiovascular risk factors. Results: Of the 207 women invited, 44 were enrolled in the feasibility study and 40 women completed the intervention, corresponding to a recruitment rate of 21% and a retention rate of 91%. At the 3-month study visit, 94.6% of participants reported they had used the website. A total of 41.7% of the participants reported that they had achieved their personal goals during the intervention period. Conclusions: This study suggested the feasibility and potential acceptability of a web- and phone-based lifestyle intervention for mothers with recent PE or GDM. Clinical Trial Registration: clinicaltrials.gov, www.clinicaltrials.gov, no. NCT03993145.

Postpartum Lifestyle Behaviors among Women with Hypertensive Disorders of Pregnancy: Data from the HUNT Study.

Hypertensive disorders of pregnancy (HDP) are associated with an increased risk of cardiovascular disease later in life. Clinical guidelines for postpartum follow-up after HDP often recommend lifestyle counseling to reduce this risk. However, knowledge about lifestyle behaviors and perceptions among women with a history of HDP is limited. We linked data from the fourth survey of the population-based Trøndelag Health Study (HUNT4) with data from the Medical Birth Registry of Norway. The associations between HDP and postpartum lifestyle behaviors and perceptions were examined using multivariable logistic regression. In a secondary analysis, HUNT4 participants with a recent history of pre-eclampsia were compared with women with a recent history of pre-eclampsia participating in a postpartum pilot intervention study. Lifestyle behaviors and perceptions were self-reported and included diet (intake frequency of fruits, vegetables, meat, fish, and sugar-sweetened beverages), alcohol intake, physical activity, sleep, smoking, lifestyle satisfaction, and the importance of a healthy lifestyle. Among 7551 parous HUNT4 participants, 610 had a history of HDP. We found no differences in lifestyle behaviors between women with and without a history of HDP. However, women with HDP had higher odds of being unsatisfied with their lifestyle. Women with pre-eclampsia participating in a postpartum lifestyle intervention study tended to have a healthier lifestyle at baseline than women participating in HUNT4. Future studies should explore how lifestyle intervention programs could be adapted to the needs of women who have experienced HDP or other pregnancy complications that are associated with an increased risk of CVD.

Postpartum lifestyle behaviour among women with prior gestational diabetes mellitus: evidence from the HUNT study.

Introduction: Women with a history of gestational diabetes mellitus (GDM) are at increased risk of type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD). Recommendations for postpartum follow-up include targeted lifestyle advice to lower the risk.The aim of this study was to compare postpartum lifestyle behaviours and perceptions among women with and without a history of GDM. In addition, we examined whether lifestyle behaviours of women with a history of GDM participating in a lifestyle intervention study differed from lifestyle behaviours of women with a history of GDM in the general population. Research design and methods: We linked data from the fourth survey of the population-based Trøndelag Health Study (HUNT4) to information from the Medical Birth Registry of Norway for women with registered births between 2000 and 2019. Using logistic regression, we compared lifestyle behaviours in women with and without GDM. In secondary analyses, lifestyle behaviours in women with GDM participating in a postpartum lifestyle intervention study were compared with HUNT participants with GDM using Fisher's exact tests/t-tests. Results: A high proportion of the women in our population, regardless of GDM history, reported several unhealthy lifestyle behaviours. We found no significant association between history of GDM and lifestyle behaviours. The lifestyle intervention study for women with a history of GDM appeared to recruit women with more favourable lifestyle behaviours. Conclusions: Women, regardless of GDM history, could potentially benefit from further support for lifestyle improvement, but it may be especially important in women with a history of GDM given their increased risk of T2DM and CVD. Interventions targeting women with GDM might not reach the women with the unhealthiest lifestyle behaviours, and measures to reach out to all women should be further investigated.