Cluster analysis dissecting cognitive deficits in older adults with major depressive disorder and the association with neurofilament light chain.

BACKGROUND: Cognitive impairment is a growing problem with increasing burden in global aging. Older adults with major depressive disorder (MDD) have higher risk of dementia. Neurofilament light chain (NfL) has been proven as a potential biomarker in neurodegenerative disease, including dementia. We aimed to investigate the association between cognitive deficits and NfL levels in older adults with MDD. METHODS: In this cross-sectional study, we enrolled 39 MDD patients and 15 individuals with mild neurocognitive disorder or major neurocognitive disorder, Alzheimer's type, as controls, from a tertiary psychiatric hospital. Both groups were over age 65 and with matched Mini-Mental State Examination (MMSE) score. Demographic data, clinical variables, and plasma NfL levels were obtained. We used cluster analysis according to their cognitive profile and estimated the correlation between plasma NfL levels and each cognitive domain. RESULTS: In the MDD group, participants had higher rate of family psychiatry history and current alcohol use habit compared with controls. Control group of neurocognitive disorders showed significantly lower score in total MMSE and higher plasma NfL levels. Part of the MDD patients presented cognitive deficits clustered with that of neurocognitive disorders (cluster A). In cluster A, the total MMSE score (r=-0.58277, p=0.0287) and the comprehension domain (r=-0.71717, p=0.0039) were negatively correlated to NfL levels after adjusting for age, while the associations had not been observed in the other cluster. CONCLUSIONS: We noted the negative correlation between NfL levels and cognition in MDD patients clustered with neurodegenerative disorder, Alzheimer's type. NfL could be a promising candidate as a biomarker to predict subtype of patients in MDD to develop cognitive decline. Further longitudinal studies and within MDD cluster analysis are required to validate our findings for clinical implications.

Estimating the health effects of COVID-19-related immunisation disruptions in 112 countries during 2020-30: a modelling study.

BACKGROUND: There have been declines in global immunisation coverage due to the COVID-19 pandemic. Recovery has begun but is geographically variable. This disruption has led to under-immunised cohorts and interrupted progress in reducing vaccine-preventable disease burden. There have, so far, been few studies of the effects of coverage disruption on vaccine effects. We aimed to quantify the effects of vaccine-coverage disruption on routine and campaign immunisation services, identify cohorts and regions that could particularly benefit from catch-up activities, and establish if losses in effect could be recovered. METHODS: For this modelling study, we used modelling groups from the Vaccine Impact Modelling Consortium from 112 low-income and middle-income countries to estimate vaccine effect for 14 pathogens. One set of modelling estimates used vaccine-coverage data from 1937 to 2021 for a subset of vaccine-preventable, outbreak-prone or priority diseases (ie, measles, rubella, hepatitis B, human papillomavirus [HPV], meningitis A, and yellow fever) to examine mitigation measures, hereafter referred to as recovery runs. The second set of estimates were conducted with vaccine-coverage data from 1937 to 2020, used to calculate effect ratios (ie, the burden averted per dose) for all 14 included vaccines and diseases, hereafter referred to as full runs. Both runs were modelled from Jan 1, 2000, to Dec 31, 2100. Countries were included if they were in the Gavi, the Vaccine Alliance portfolio; had notable burden; or had notable strategic vaccination activities. These countries represented the majority of global vaccine-preventable disease burden. Vaccine coverage was informed by historical estimates from WHO-UNICEF Estimates of National Immunization Coverage and the immunisation repository of WHO for data up to and including 2021. From 2022 onwards, we estimated coverage on the basis of guidance about campaign frequency, non-linear assumptions about the recovery of routine immunisation to pre-disruption magnitude, and 2030 endpoints informed by the WHO Immunization Agenda 2030 aims and expert consultation. We examined three main scenarios: no disruption, baseline recovery, and baseline recovery and catch-up. FINDINGS: We estimated that disruption to measles, rubella, HPV, hepatitis B, meningitis A, and yellow fever vaccination could lead to 49 119 additional deaths (95% credible interval [CrI] 17 248-134 941) during calendar years 2020-30, largely due to measles. For years of vaccination 2020-30 for all 14 pathogens, disruption could lead to a 2·66% (95% CrI 2·52-2·81) reduction in long-term effect from 37 378 194 deaths averted (34 450 249-40 241 202) to 36 410 559 deaths averted (33 515 397-39 241 799). We estimated that catch-up activities could avert 78·9% (40·4-151·4) of excess deaths between calendar years 2023 and 2030 (ie, 18 900 [7037-60 223] of 25 356 [9859-75 073]). INTERPRETATION: Our results highlight the importance of the timing of catch-up activities, considering estimated burden to improve vaccine coverage in affected cohorts. We estimated that mitigation measures for measles and yellow fever were particularly effective at reducing excess burden in the short term. Additionally, the high long-term effect of HPV vaccine as an important cervical-cancer prevention tool warrants continued immunisation efforts after disruption. FUNDING: The Vaccine Impact Modelling Consortium, funded by Gavi, the Vaccine Alliance and the Bill & Melinda Gates Foundation. TRANSLATIONS: For the Arabic, Chinese, French, Portguese and Spanish translations of the abstract see Supplementary Materials section.

Impact of COVID-19 national response on primary care utilisation in Singapore: an interrupted time-series analysis.

Since the start of the pandemic, many national responses, such as nationwide lockdowns, have been implemented to curb the spread of COVID-19. We aim to assess the impact of Singapore's national responses on primary care utilisation. We performed an interrupted time series using acute and chronic primary care data of 3 168 578 visits between 1 September 2019 and 31 August 2020 over four periods: before any measures were put in place, during Disease Outbreak Response System Condition (DORSCON) Orange, when Circuit Breaker was instituted, and when Circuit Breaker was lifted. We found significant mean reductions in acute and chronic primary care visits immediately following DORSCON Orange and Circuit Breaker. DORSCON Orange was associated with - 2020 mean daily visits (95% CI - 2890 to - 1150). Circuit Breaker was associated with a further - 2510 mean daily visits (95% CI - 3660 to - 1360). Primary care utilisation for acute visits remained below baseline levels even after the Circuit Breaker was lifted. These significant reductions were observed in both acute and chronic visits, with acute visits experiencing a steeper drop during DORSCON Orange. Understanding the impact of COVID-19 measures on primary care utilisation will be useful for future public health planning.

Hemodynamic regulation allows stable growth of microvascular networks.

How do vessels find optimal radii? Capillaries are known to adapt their radii to maintain the shear stress of blood flow at the vessel wall at a set point, yet models of adaptation purely based on average shear stress have not been able to produce complex loopy networks that resemble real microvascular systems. For narrow vessels where red blood cells travel in a single file, the shear stress on vessel endothelium peaks sharply when a red blood cell passes through. We show that stable shear-stress-based adaptation is possible if vessel shear stress set points are cued to the stress peaks. Model networks that respond to peak stresses alone can quantitatively reproduce the observed zebrafish trunk microcirculation, including its adaptive trajectory when hematocrit changes or parts of the network are amputated. Our work reveals the potential for mechanotransduction alone to generate stable hydraulically tuned microvascular networks.

AttentionViz: A Global View of Transformer Attention.

Transformer models are revolutionizing machine learning, but their inner workings remain mysterious. In this work, we present a new visualization technique designed to help researchers understand the self-attention mechanism in transformers that allows these models to learn rich, contextual relationships between elements of a sequence. The main idea behind our method is to visualize a joint embedding of the query and key vectors used by transformer models to compute attention. Unlike previous attention visualization techniques, our approach enables the analysis of global patterns across multiple input sequences. We create an interactive visualization tool, AttentionViz (demo: http://attentionviz.com), based on these joint query-key embeddings, and use it to study attention mechanisms in both language and vision transformers. We demonstrate the utility of our approach in improving model understanding and offering new insights about query-key interactions through several application scenarios and expert feedback.

Identifying the sociodemographic and work-related factors related to workers' daily physical activity using a decision tree approach.

BACKGROUND: The social and behavioural factors related to physical activity among adults are well known. Despite the overlapping nature of these factors, few studies have examined how multiple predictors of physical activity interact. This study aimed to identify the relative importance of multiple interacting sociodemographic and work-related factors associated with the daily physical activity patterns of a population-based sample of workers. METHODS: Sociodemographic, work, screen time, and health variables were obtained from five, repeated cross-sectional cohorts of workers from the Canadian Health Measures Survey (2007 to 2017). Classification and Regression Tree (CART) modelling was used to identify the discriminators associated with six daily physical activity patterns. The performance of the CART approach was compared to a stepwise multinomial logistic regression model. RESULTS: Among the 8,909 workers analysed, the most important CART discriminators of daily physical activity patterns were age, job skill, and physical strength requirements of the job. Other important factors included participants' sex, educational attainment, fruit/vegetable intake, industry, work hours, marital status, having a child living at home, computer time, and household income. The CART tree had moderate classification accuracy and performed marginally better than the stepwise multinomial logistic regression model. CONCLUSION: Age and work-related factors-particularly job skill, and physical strength requirements at work-appeared as the most important factors related to physical activity attainment, and differed based on sex, work hours, and industry. Delineating the hierarchy of factors associated with daily physical activity may assist in targeting preventive strategies aimed at promoting physical activity in workers.

The societal cost of modifiable risk factors in Singapore.

BACKGROUND: Singapore is one of the most rapidly ageing populations in the world. Nearly half of all disease burdens in Singapore are attributable to modifiable risk factors. This indicates that many illnesses are preventable by modifying behaviours such as increasing physical activity levels or maintaining a healthy diet. Prior cost-of-illness studies have estimated the cost of selected modifiable risk factors. However, no local study has compared costs between groups of modifiable risks. This study aims to estimate the societal cost attributable to a comprehensive list of modifiable risks in Singapore. METHODS: Our study builds on the comparative risk assessment framework from the Global Burden of Disease (GBD) 2019 study. A top-down prevalence-based cost-of-illness approach was undertaken to estimate the societal cost of modifiable risks in 2019. These include healthcare costs from inpatient hospitalisation and productivity losses from absenteeism and premature mortality. RESULTS: Metabolic risks had the highest total cost of US$1.62 billion (95% uncertainty interval [UI] US$1.51-1.84 billion), followed by lifestyle risks of US$1.40 billion (95% UI US$1.36-1.66 billion) and substance risks of US$1.15 billion (95% UI US$1.10-1.24 billion). Across the risk factors, the costs were driven by productivity losses, heavily skewed towards the older working-age group and among males. Most of the costs were driven by cardiovascular diseases. CONCLUSION: This study provides evidence of the high societal cost of modifiable risks and highlights the importance of developing holistic public health promotion programmes. As modifiable risks often do not occur in isolation, implementing effective population-based programmes targeting multiple modifiable risks has a strong potential to manage the cost of the rising disease burden in Singapore.

The physical activity at work (PAW) study: a cluster randomised trial of a multicomponent short-break intervention to reduce sitting time and increase physical activity among office workers in Thailand.

Background: Sedentary behaviour increases the risks of non-communicable diseases. The objective of this trial was to evaluate the effect of the Physical Activity at Work multicomponent intervention to reduce sedentary behaviour in Thai office workers. Methods: Offices under the Ministry of Public Health Thailand, were randomly allocated to the intervention and control group in a 1:1 ratio, stratified by office size. The intervention included individual (pedometer and lottery-based financial incentives), social (group movement breaks), environmental (posters), and organisational (leader encouragement) components. At baseline and 6-month follow-up, participants wore ActiGraphTM on the waist for ten days. The primary outcome was the between-group difference in sedentary time at 6-month, analysed using a linear mixed-effects model. Other outcomes were physical activity, biomarkers, productivity, and musculoskeletal health. Trial registration: The PAW study was registered at the Thai Clinical Trials Registry (ID TCTR20200604007) on 02 June 2020. Findings: 282 office workers were recruited and randomly allocated to the control group (142 participants, nine offices) and the intervention group (140 participants, nine offices). The mean age was 38.6 years (SD = 10.4), and 81% were women. There was no evidence of intervention effects on sedentary time during waking hours (-26.8; 95% CI = -69.2 to 15.7 min), physical activity levels, or biomarkers between groups at 6-month. In the adjusted analysis, increases in time spent in moderate-to-vigorous physical activity (5.45; 95% CI = -0.15 to 11.1 min) and step count (718; 95% CI = -45 to 1481 steps) during waking hours were observed, although there was no evidence of a difference between groups. Interpretation: The intervention did not significantly reduce sedentary time in Thai office workers. Suboptimal intervention uptake due to Covid-19 pandemic restrictions and loss of statistical power associated with recruitment constraints may explain this result. Further investigations are needed to evaluate the processes of the trial. Funding: The Thai Health Promotion Foundation and the International Decision Support Initiative (iDSI).

Geospatial divide in real-world EHR data: Analytical workflow to assess regional biases and potential impact on health equity.

Real-world data (RWD) like electronic health records (EHR) has great potential for secondary use by health systems and researchers. However, collected primarily for efficient health care, EHR data may not equitably represent local regions and populations, impacting the generalizability of insights learned from it. We assessed the geospatial representativeness of regions in a large health system EHR data using a spatial analysis workflow, which provides a data-driven way to quantify geospatial representation and identify adequately represented regions. We applied the workflow to investigate geospatial patterns of overweight/obesity and depression patients to find regional "hotspots" for potential targeted interventions. Our findings show the presence of geospatial bias in EHR and demonstrate the workflow to identify spatial clusters after adjusting for bias due to the geospatial representativeness. This work highlights the importance of evaluating geospatial representativeness in RWD to guide targeted deployment of limited healthcare resources and generate equitable real-world evidence.

Fukushima study for Engaging people with type 2 Diabetes in Behaviour Associated Change (FEEDBACK): study protocol for a cluster randomised controlled trial.

BACKGROUND: The growing burden of type 2 diabetes mellitus (T2DM) and the rising cost of healthcare worldwide make it imperative to identify interventions that can promote sustained self-management behaviour in T2DM populations while minimising costs for healthcare systems. The present FEEDBACK study (Fukushima study for Engaging people with type 2 Diabetes in Behaviour Associated Change) aims to evaluate the effects of a novel behaviour change intervention designed to be easily implemented and scaled across a wide range of primary care settings. METHODS: A cluster randomised controlled trial (RCT) with a 6-month follow-up will be conducted to evaluate the effects of the FEEDBACK intervention. FEEDBACK is a personalised, multi-component intervention intended to be delivered by general practitioners during a routine diabetes consultation. It consists of five steps aimed at enhancing doctor-patient partnership to motivate self-management behaviour: (1) communication of cardiovascular risks using a 'heart age' tool, (2) goal setting, (3) action planning, (4) behavioural contracting, and (5) feedback on behaviour. We aim to recruit 264 adults with T2DM and suboptimal glycaemic control from 20 primary care practices in Japan (cluster units) that will be randomly assigned to either the intervention or control group. The primary outcome measure will be the change in HbA1c levels at 6-month follow-up. Secondary outcome measures include the change in cardiovascular risk score, the probability to achieve the recommended glycaemic target (HbA1c <7.0% [53mmol/mol]) at 6-month follow-up, and a range of behavioural and psychosocial variables. The planned primary analyses will be carried out at the individual level, according to the intention-to-treat principle. Between-group comparisons for the primary outcome will be analysed using mixed-effects models. This study protocol received ethical approval from the research ethics committee of Kashima Hospital, Fukushima, Japan (reference number: 2022002). DISCUSSION: This article describes the design of a cluster RCT that will evaluate the effects of FEEDBACK, a personalised, multicomponent intervention aimed at enhancing doctor-patient partnership to engage adults with T2DM more effectively in self-management behaviour. TRIAL REGISTRATION: The study protocol was prospectively registered in the UMIN Clinical Trials Registry (UMIN-CTR ID UMIN000049643 assigned on 29/11/2022). On submission of this manuscript, recruitment of participants is ongoing.

Impact of the value driven outcomes program among cataract surgery patients in Singapore: an interrupted time series analysis.

BACKGROUND: Healthcare cost is increasing rapidly in Singapore. Moving towards a value-based healthcare framework enables a sustainable health system. The National University Hospital (NUH) implemented the Value Driven Outcome (VDO) Program for cataract surgery due to its high volume and cost variability. We aimed to evaluate the association between VDO program implementation and costs and quality outcomes for cataract surgery in NUH. METHODS: We conducted an interrupted time-series analysis for cataract surgery episodes between January 2015 and December 2018. Using segmented linear regression models, we estimate the changes in levels and trends of cost and quality outcomes post-program implementation. We adjusted for autoregression and various confounders. RESULTS: Following VDO program implementation, the total cost of cataract surgery had a significantly decreased by $327.23 (95% CI: -$421.04 to -$233.43; p < 0.01) and the trend significantly decreased by $13.75 per month (95% CI: -$23.19 to -$4.30 per month; p < 0.01). There was a small improvement in the combined quality outcome score (0.028, 95% CI: 0.016 to 0.040; p < 0.01), but the trend remained unchanged. CONCLUSION: The VDO program was associated with a reduction in cost without compromising on quality outcomes. The program provides a structured methodology to measure performances, and through these data, initiatives were implemented to improve value. There are benefits to providing a data reporting system to physicians to understand actual care costs and quality outcomes achieved by individual patients with defined clinical conditions.

Indole-3-Propionic Acid, a Gut Microbiota Metabolite, Protects Against the Development of Postoperative Delirium.

OBJECTIVE: The aim was to determine preoperative gut microbiota metabolites that may be associated with postoperative delirium (POD) development in patients and further study in rodents. SUMMARY BACKGROUND DATA: POD occurs in 9% to 50% of older patients undergoing anesthesia/surgery but lacks effective treatments or prevention. High-throughput metabolomics using liquid chromatography with tandem mass spectrometry has accelerated disease-related biomarkers discovery. We performed metabolomic studies in humans to identify potential metabolite biomarkers linked to POD and examined potential mechanisms in rodents. METHODS: We performed a prospective observational cohort study to examine the metabolomic changes that were associated with the development of POD. Then the gut microbiota-related metabolomic changes were recapitulated by gut microbiota perturbation in rodents. POD was assessed in mice using a battery of behavioral tests including novel objective test, Y-maze test, open-field test, and buried food test. The mechanisms through which gut microbiota-related metabolomic changes influenced POD were examined using chemogenetics. RESULTS: Indole-3-propionic acid (IPA) is a gut microbiota metabolite that belongs to the indole family. Baseline plasma levels of IPA were significantly inversely correlated with the onset of POD in 103 (17 cases) human individuals. This relationship was validated in preclinical mouse models for POD: reducing IPA levels through gut microbiota perturbation promoted POD-like behavior. More importantly, IPA administration deterred POD-like behavior. Colonization of germ-free mice with mutant Clostridium sporogenes that did not produce IPA-promoted POD-like behavior. Chemogenetic studies revealed that the protective effect of IPA in mice was mediated, in part, by peroxisome proliferator-activated receptor gamma coactivator 1-alpha in hippocampal interneurons. CONCLUSIONS: Gut microbiota-derived IPA is an important molecule implicated in the pathogenesis of POD, which could potentially be harnessed for POD prevention.

HHV-6 Meningoencephalitis in a Healthy Adult Female.

Introduction: We describe the case of a 47-year-old female who presented to an academic tertiary emergency department with two to three days of worsening fever, headache, malaise, and rigors. A broad infectious workup revealed a diagnosis of Human Herpesvirus 6 (HHV-6) meningoencephalitis without any additional identifiable causes. HHV-6, the virus responsible for the childhood disease roseola, is a common cause of fever, seizures, diarrhea, and a characteristic faint-pink rash in children. Symptomatic HHV-6 infection in adults is far less common. We believe this represents one of only a few reported cases of HHV-6 meningoencephalitis in an immunocompetent host. Case Report. A 47-year-old female presented to the emergency department with two to three days of fever, headache, malaise, and rigors. She had a noncontributory medical, surgical, and family history but had traveled extensively in northeast Africa six months prior. A physical exam was notable for a wide based gait, photophobia, mild nuchal rigidity, and pain with active range of motion of the neck. A broad infectious workup was pursued; however, given headache, fever, and subjective nuchal rigidity, the highest concern was for meningoencephalitis. A lumbar puncture was positive for HHV-6 without any other diagnostic findings to otherwise explain the patient's symptoms. The patient was discharged on hospital day 3 with improving symptoms. Conclusion: HHV-6 meningoencephalitis has previously been described as a pathogen associated with individuals with immunosuppressive conditions. There have been several prior case reports of symptomatic meningoencephalitis in immune-competent individuals, and we believe this case adds to a growing body of evidence that HHV-6 meningoencephalitis can cause symptomatic infection in a broader patient population.

Multiple models for outbreak decision support in the face of uncertainty.

Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020.

Societal Adaptation to Aging and Prevalence of Depression Among Older Adults: Evidence From 20 Countries.

Policy Points Countries have adopted different strategies to support aging populations, which are broadly reflected in social, economic, and contextual environments. Referred to as "societal adaptation to aging," these factors affect countries' capacity to support older adults. Results from our study show that countries with more robust societal adaptation to aging had lower depression prevalence. Reductions in depression prevalence occurred among every investigated sociodemographic group and were most pronounced among the old-old. Findings suggest that societal factors have an underacknowledged role in shaping depression risk. Policies that improve societal approaches to aging may reduce depression prevalence among older adults. CONTEXT: Countries have adopted various formal and informal approaches to support older adults, which are broadly reflected in different policies, programs, and social environments. These contextual environments, broadly referred to as "societal adaptation to aging," may affect population health. METHODS: We used a new theory-based measure that captured societal adaptation to aging, the Aging Society Index (ASI), which we linked with harmonized individual-level data from 89,111 older adults from 20 countries. Using multi-levels models that accounted for differences in the population composition across countries, we estimated the association between country-level ASI scores and depression prevalence. We also tested if associations were stronger among the old-old and among sociodemographic groups that experience more disadvantage (i.e., women, those with lower educational attainment, unmarried adults). FINDINGS: We found that countries with higher ASI scores, indicating more comprehensive approaches to supporting older adults, had lower depression prevalence. We found especially strong reductions in depression prevalence among the oldest adults in our sample. However, we did not find stronger reductions among sociodemographic groups who may experience more disadvantage. CONCLUSIONS: Country-level strategies to support older adults may affect depression prevalence. Such strategies may become increasingly important as adults grow older. These results offer promising evidence that improvements in societal adaptation to aging-such as through adoption of more comprehensive policies and programs targeting older adults-may be one avenue to improve population mental health. Future research could investigate observed associations using longitudinal and quasi-experimental study designs, offering additional information regarding a potential causal relationship.

Daily accelerometer-measured physical activity patterns and associations with cardiometabolic health among Canadian working adults.

Background: Previous studies examining the cardiometabolic risks associated with physical activity (PA) in workers have predominantly used self-reported measures. Little is known about workers' distinct daily PA patterns and whether these are linked with cardiometabolic risks. This study examined associations between patterns of workers' accelerometer-measured daily PA and four markers of cardiometabolic health. Data and methods: Working adults (N=8,229; 47% women; average age: 42 years; standard deviation = 0.3) were sampled from the Canadian Health Measures Survey (five cycles: 2007 to 2017). Accelerometer devices measured daily PA, and hierarchical cluster analysis identified distinct activity patterns. Multiple linear regression analyses examined associations between activity patterns and cardiometabolic risk markers (waist circumference, systolic and diastolic blood pressure, and non-high-density lipoprotein [HDL] cholesterol). Results: Workers were classified into six distinct activity patterns. On average, compared with workers classified in the "lowest activity" pattern, workers with the "moderate consistent activity," "fluctuating moderate activity," "high daytime activity" and "highest activity" patterns were associated with lower waist circumferences; workers with the "fluctuating moderate activity" and "highest activity" patterns were associated with lower systolic blood pressure; the "moderate evening activity" pattern was associated with lower diastolic blood pressure; and workers with the "fluctuating moderate activity," "high daytime activity" and "highest activity" patterns were associated with lower non-HDL cholesterol. "High daytime activity" was associated with lower waist circumference in women, compared with men, and the "moderate consistent activity" and "fluctuating moderate activity" patterns were associated with lower diastolic blood pressure in younger workers (40 years or younger). Interpretation: Workers with high daily PA levels tended to have the most optimal cardiometabolic health. Some evidence suggested that there are benefits to moderate levels of PA, particularly for lowering waist circumference and non-HDL cholesterol. Findings may assist in identifying workers for PA initiatives to promote cardiometabolic health benefits.

The association between health costs and physical inactivity; analysis from the Physical Activity at Work study in Thailand.

Introduction: Physical inactivity increases the risks of several common yet serious non-communicable diseases, costing a tremendous amount of health expenditure globally. This study aimed to estimate the association between health costs and physical inactivity in Thailand. Methods: Data from the Physical Activity at Work cluster randomized controlled trial participants with valid objective physical activity data were extracted. Health costs were collected using the Health and Welfare Survey and the Work Productivity and Activity Impairment Questionnaire and were categorized into past-month outpatient illness, past-year inpatient illness, and past-week presenteeism and absenteeism. Time spent in moderate-to-vigorous physical activity was used to determine the activity level according to the current guideline (i.e., ≥150 minutes moderate-intensity or ≥75 minutes vigorous-intensity equivalent physical activity per week). The primary analysis evaluated the association between direct cost (treatment and travel costs) and societal cost (direct cost plus absenteeism due to the illness) of past-month outpatient illness and physical inactivity using a two-part model. Results: In total, 277 participants with a mean age of 38.7 were included. Average direct and societal cost due to past-month outpatient illness were 146 THB (3.99 USD) (SD = 647 THB) and 457 THB (12.5 USD) (SD = 1390 THB), respectively. Compared to active participants, direct and societal cost of past-month outpatient illness were 153 THB (4.18 USD) (95%CI: -54.7 to 360 THB) and 426 THB (11.7 USD) (95%CI: 23.3 to 829 THB) higher in physically inactive individuals, respectively, adjusted for covariates. The additional societal cost of past-month outpatient illness was 145% higher in physically inactive participants compared to active participants. On the other hand, there was no significant association in direct and societal cost of past-year inpatient illness nor past-week indirect costs between physically active and non-active participants. Discussion: Results were similar to recent findings in different countries. However, the findings should be generalized with caution due to the small sample size and potential bias from reverse causation. Future research is crucial for clarifying the health costs of physical inactivity in Thailand and other countries.

How Does Job Insecurity and Workplace Activity Limitations Relate to Rheumatic Disease Symptom Trajectories in Young Adulthood? A Longitudinal Study.

OBJECTIVE: Workplace and labor market conditions are associated with the health of the working population. A longitudinal study was conducted among young adults with rheumatic disease to examine workplace activity limitations and job insecurity and their relationship with disease symptom trajectories. METHODS: Three online surveys were administered to young adults with rheumatic disease over 27 months. Self-reported data on pain, fatigue, and disease activity were collected. Workplace activity limitations and job insecurity were measured. Group-based discrete mixture models determined pain, fatigue, and disease activity trajectory groups. Robust Poisson regression models were fitted to examine the relationship among workplace activity limitations, job insecurity, and trajectory group membership. RESULTS: In total, 124 participants (mean ± SD age 29 ± 4.5 years) with rheumatic disease were recruited. At baseline, participants reported considerable workplace activity limitations (10.35 ± 5.8), and 36% of participants indicated experiencing job insecurity. We identified 2 latent rheumatic disease symptom trajectory groups. The first group had high persistent pain, fatigue, or disease activity; the second group had low persistent disease symptoms over time. Greater workplace activity limitations were associated with an increased relative risk (RR) of being in the high persistent severe pain (RR 1.02 [95% confidence interval (95% CI) 1.01, 1.03]), fatigue (RR 1.02 [95% CI 1.01, 1.03]), and disease activity trajectory groups (RR 1.02 [95% CI 1.01, 1.03]). Job insecurity was associated with an increased RR of membership in the high persistent pain (RR 1.14 [95% CI 1.04, 1.25]) and disease activity trajectory groups (RR 1.11 [95% CI 1.00, 1.22]). CONCLUSION: Workplace activity limitations and job insecurity represent working conditions that are associated with the health of young adults with rheumatic disease and should be examined as potential targets for intervention.

Evaluation of the gap in delivery of opioid agonist therapy among individuals with opioid-related health problems: a population-based retrospective cohort study.

AIMS: Although opioid-related harms have reached new heights across North America, the size of the gap in opioid agonist therapy (OAT) delivery for opioid-related health problems is unknown in most jurisdictions. This study sought to characterize the gap in OAT treatment using a cascade of care framework, and determine factors associated with engagement and retention in treatment. DESIGN: A population-based retrospective cohort study. SETTING: Ontario, Canada. PARTICIPANTS: Individuals who sought medical care for opioid-related health problems or died from an opioid-related cause between 2005 and 2019. MEASUREMENTS: Monthly treatment status for buprenorphine/naloxone or methadone OAT between 2013 and 2019 (i.e. 'off OAT', 'retained on OAT < 6 months', 'retained on OAT ≥ 6 months'). FINDINGS: Of 122 811 individuals in the cohort, 97 516 (79.4%) received OAT at least once during the study period. There was decreasing 6-month treatment retention over time. Model results indicated that males had higher odds of being on OAT each month [odds ratio (OR) = 1.26, 95% confidence interval (CI) = 1.23-1.28] but lower odds of OAT retention (OR = 0.90, 95% CI = 0.88-0.92), while the reverse was observed for older individuals (monthly: OR = 0.76 per 10-year increase, 95% CI = 0.76-0.77; retention: OR = 1.36 per 10-year increase, 95% CI = 1.34-1.38) and individuals with higher neighbourhood income (e.g. highest income quintile, monthly: OR = 0.79, 95% CI = 0.77-0.82; highest income quintile, retention: OR = 1.15, 95% CI = 1.11-1.20). Individuals residing in rural areas and with a history of mental health diagnoses had poorer outcomes overall, including lower odds of being on OAT each month (rural: OR = 0.75, 95% CI = 0.73-0.78; mental health: OR = 0.89, 95% CI = 0.87-0.92) and OAT retention (rural: OR = 0.79, 95% CI = 0.77-0.82; mental health: OR = 0.81, 95% CI = 0.78-0.83), as well as higher risk of starting/stopping OAT [rural, starting OAT: hazard ratio (HR) = 1.07, 95% CI = 1.05-1.10; mental health, starting OAT: HR = 1.20, 95% CI: 1.18-1.23; rural, stopping OAT: HR = 1.24, 95% CI: = 1.22-1.26; mental health, stopping OAT: HR = 1.11, 95% CI = 1.09-1.13]. Individuals with a history of mental health diagnoses also had a higher risk of death, regardless of OAT status (off OAT death: HR = 1.49, 95% CI = 1.33-1.66; on OAT death: HR = 1.20, 95% CI = 1.09-1.31). CONCLUSIONS: Factors influencing engagement and declining retention in treatment with opioid agonist therapy in Ontario's health system include age, sex and neighbourhood income, as well as mental health diagnoses or residing in rural regions.