Highlighting Unseen Activity Through 48-Hour Continuous Measurement in Subacute Stroke Rehabilitation: Preliminary Cohort Study.

BACKGROUND: Motor impairments not only lead to a significant reduction in patient activity levels but also trigger a further deterioration in motor function due to deconditioning, which is an issue that is particularly pronounced during hospitalization. This deconditioning can be countered by sustaining appropriate activity levels. Activities that occur outside of scheduled programs, often overlooked, are critical in this context. Wearable technology, such as smart clothing, provides a means to monitor these activities. OBJECTIVE: This study aimed to observe activity levels in patients who had strokes during the subacute phase, focusing on both scheduled training sessions and other nontraining times in an inpatient rehabilitation environment. A smart clothing system is used to simultaneously measure heart rate and acceleration, offering insights into both the amount and intensity of the physical activity. METHODS: In this preliminary cohort study, 11 individuals undergoing subacute stroke rehabilitation were enrolled. The 48-hour continuous measurement system, deployed at admission and reassessed 4 weeks later, monitored accelerometry data for physical activity (quantified with a moving SD of acceleration [MSDA]) and heart rate for intensity (quantified with percent heart rate reserve). The measurements were performed using a wearable activity monitoring system, the hitoe (NTT Corporation and Toray Industries, Inc) system comprising a measuring garment (wear or strap) with integrated electrodes, a data transmitter, and a smartphone. The Functional Independence Measure was used to assess the patients' daily activity levels. This study explored factors such as differences in activity during training and nontraining periods, correlations with activities of daily living (ADLs) and age, and changes observed after 4 weeks. RESULTS: A significant increase was found in the daily total MSDA after the 4-week program, with the average percent heart rate reserve remaining consistent. Physical activity during training positively correlated with ADL levels both at admission (ρ=0.86, P<.001) and 4 weeks post admission (ρ=0.96, P<.001), whereas the correlation between age and MSDA was not significant during training periods at admission (ρ=-0.41, P=.21) or 4 weeks post admission (ρ=-0.25, P=.45). Conversely, nontraining activity showed a negative correlation with age, with significant negative correlations with age at admission (ρ=-0.82, P=.002) and 4 weeks post admission (ρ=-0.73, P=.01). CONCLUSIONS: Inpatient rehabilitation activity levels were positively correlated with ADL levels. Further analysis revealed a strong positive correlation between scheduled training activities and ADL levels, whereas nontraining activities showed no such correlation. Instead, a negative correlation between nontraining activities and age was observed. These observations suggest the importance of providing activity opportunities for older patients, while it may also suggest the need for adjusting the activity amount to accommodate the potentially limited fitness levels of this demographic. Future studies with larger patient groups are warranted to validate and further elucidate these findings.

Blood pressure classification using the Japanese Society of Hypertension Guidelines for the Management of Hypertension and cardiovascular events among young to middle-aged working adults.

The Japanese Society of Hypertension updated guidelines for hypertension management (JSH2019), changing the blood pressure (BP) classification. However, evidence is sparse regarding the association of the classification with cardiovascular disease (CVD) events among young to middle-aged workers in Japan. We examined this issue using longitudinal data from Japan Epidemiology Collaboration on Occupational Health Study with a prospective cohort design. Participants were 81,876 workers (aged 20-64 years) without taking antihypertensive medication at baseline. BP in 2011 or 2010 was used as exposure. CVD events that occurred from 2012 to 2021 were retrieved from a within-study registry. Cox regression was used to calculate multivariable-adjusted hazard ratios of CVD events. During 0.5 million person-years of follow-up, 334 cardiovascular events, 75 cardiovascular deaths, and 322 all-cause deaths were documented. Compared with normal BP (systolic BP [SBP] < 120 mmHg and diastolic BP [DBP] < 80 mmHg), multivariable-adjusted hazard ratios (95% confidence intervals) of cardiovascular events were 1.98 (1.49-2.65), 2.10 (1.58-2.77), 3.48 (2.33-5.19), 4.12 (2.22-7.64), and 7.81 (3.99-15.30) for high normal BP (SBP120-129 mmHg and DBP < 80 mmHg), elevated BP (SBP130-139 mmHg and/or DBP80-89 mmHg), stage 1 hypertension (SBP140-159 mmHg and DBP90-99 mmHg), stage 2 hypertension (SBP160-179 mmHg and/or DBP100-109 mmHg), and stage 3 hypertension (SBP ≥ 180 mmHg and/or DBP ≥ 110 mmHg), respectively. The highest population attributable fraction was observed in elevated BP (17.8%), followed by stage 1 hypertension (14.1%). The present data suggest that JSH2019 may help identify Japanese workers at a higher cardiovascular risk.

Clinical impact of non-lying time on hospital-associated functional decline in older patients undergoing transcatheter aortic valve implantation.

The purposes of the present study were: (1) to investigate the relationship between hospital-associated functional decline (HAFD) and non-lying time and (2) to clarify the optimal cut-off value for non-lying time associated with HAFD in older patients undergoing transcatheter aortic valve implantation (TAVI). From January 2021 to December 2022, patients admitted to a university hospital who underwent trans-femoral TAVI were consecutively recruited. We measured short physical performance battery (SPPB) pre and post-TAVI, and non-lying time from post-operative days 3-5. HAFD was defined as at least 1 point decrease in SPPB during pre and post-TAVI. Among 75 patients (47 female, mean age of 84.5 years) enrolled, 14 patients were classified as having HAFD. Non-lying time was significantly shorter in the HAFD group than in the non-HAFD group (371 min vs. 539 min, P < 0.001). Receiver-operating characteristic analysis determined an optimal cut-off value of 477 min for differentiating the patients more likely to experience HAFD (sensitivity, 75%; specificity, 92%; area under the curve, 0.798). The non-lying time could be one of the associated factors of HAFD in older patients with TAVI. Non-lying time of about 480 min (8 h) during hospitalization may be an initial target for preventing HAFD.

Metabolic syndrome and the risk of severe cancer events: a longitudinal study in Japanese workers.

BACKGROUND: Metabolic syndrome (MetS) is associated with cancer risk; however, little is known regarding its relationship with the risk of cancer-related premature death and long-term sick leave (LTSL), which can lead to a substantial loss in working years. The present study aimed to quantify the all-site and site-specific associations between MetS and the risk of severe cancer events (a composite outcome of LTSL and mortality due to cancer) in a large working population in Japan. METHODS: We recruited 70,875 workers (59,950 men and 10,925 women), aged 20-59 years, who attended health check-ups in 2011 (10 companies) and 2014 (2 companies). All workers underwent follow up for severe cancer events until March 31, 2020. MetS was defined in accordance with the Joint Interim Statement. Cox regression models were used to quantify the association between baseline MetS and severe cancer events. RESULTS: During 427,379 person-years of follow-up, 523 participants experienced the outcome consisting of 493 LTSLs of which 124 eventually resulted in death, and 30 deaths without taking LTSL. The adjusted hazard ratios (HR) (95% confidence intervals [CI]) for composite severe events due to all-site, obesity-related, and non-obesity-related cancer among those with vs. without MetS were 1.26 (1.03, 1.55), 1.37 (1.04, 1.82), and 1.15 (0.84, 1.56), respectively. In cancer site-specific analyses, MetS was associated with an increased risk of severe events due to pancreatic cancer (HR, 2.06; 95% CI, 0.99-4.26). When mortality was treated solely as the endpoint, the association was significant for all-site (HR, 1.58; 95% CI, 1.10-2.26), and obesity-related (HR, 1.59; 95% CI, 1.00-2.54) cancer. Additionally, a greater number of MetS components was associated with a greater risk of both severe cancer events and cancer-related mortality (P trend < 0.05). CONCLUSION: Among Japanese workers, MetS was associated with an increased risk of severe cancer events, especially those due to obesity-linked cancer.

Ensemble averaging for categorical variables: Validation study of imputing lost data in 24-h recorded postures of inpatients.

Acceleration sensors are widely used in consumer wearable devices and smartphones. Postures estimated from recorded accelerations are commonly used as features indicating the activities of patients in medical studies. However, recording for over 24 h is more likely to result in data losses than recording for a few hours, especially when consumer-grade wearable devices are used. Here, to impute postures over a period of 24 h, we propose an imputation method that uses ensemble averaging. This method outputs a time series of postures over 24 h with less lost data by calculating the ratios of postures taken at the same time of day during several measurement-session days. Whereas conventional imputation methods are based on approaches with groups of subjects having multiple variables, the proposed method imputes the lost data variables individually and does not require other variables except posture. We validated the method on 306 measurement data from 99 stroke inpatients in a hospital rehabilitation ward. First, to classify postures from acceleration data measured by a wearable sensor placed on the patient's trunk, we preliminary estimated possible thresholds for classifying postures as 'reclining' and 'sitting or standing' by investigating the valleys in the histogram of occurrences of trunk angles during a long-term recording. Next, the imputations of the proposed method were validated. The proposed method significantly reduced the missing data rate from 5.76% to 0.21%, outperforming a conventional method.

Metabolic Syndrome and the Increased Risk of Medically Certified Long-term Sickness Absence: A Prospective Analysis Among Japanese Workers.

BACKGROUND: Metabolic syndrome (MetS) has been associated with various chronic diseases that may lead to long-term sickness absence (LTSA), but there is lacking information on the direct association between MetS and LTSA. The present study aimed to investigate the all-cause and cause-specific associations between MetS and the risk of medically certified LTSA among Japanese workers. METHODS: We recruited 67,403 workers (57,276 men and 10,127 women), aged 20-59 years from 13 companies in Japan during their health check-ups in 2011 (11 companies) and 2014 (2 companies), and we followed them for LTSA events (≥30 consecutive days) until March 31, 2020. MetS was defined according to the Joint Interim Statement. A Cox proportional hazards regression model was used to estimate hazard ratios (HRs) and its 95% confidence intervals (CIs) for LTSA associated with MetS and its components. RESULTS: During 408,324 person-years of follow-up, 2,915 workers experienced LTSA. The adjusted HR for all-cause LTSA was 1.54 (95% CI, 1.41-1.68) among those with MetS compared to those without MetS. In cause-specific analysis, HRs associated with MetS significantly increased for LTSA due to overall physical disorders (1.76); cardiovascular diseases (3.16); diseases of the musculoskeletal system and connective tissue (2.01); cancers (1.24); obesity-related cancers (1.35); mental, behavioral, and neurodevelopmental disorders (1.28); reaction to severe stress and adjustment disorders (1.46); and external causes (1.46). The number of MetS components were also significantly associated with increased LTSA risk. CONCLUSION: MetS was associated with an increase in the risk of LTSA due to various diseases among Japanese workers.

Prediction of stroke patients' bedroom-stay duration: machine-learning approach using wearable sensor data.

Background: The importance of being physically active and avoiding staying in bed has been recognized in stroke rehabilitation. However, studies have pointed out that stroke patients admitted to rehabilitation units often spend most of their day immobile and inactive, with limited opportunities for activity outside their bedrooms. To address this issue, it is necessary to record the duration of stroke patients staying in their bedrooms, but it is impractical for medical providers to do this manually during their daily work of providing care. Although an automated approach using wearable devices and access points is more practical, implementing these access points into medical facilities is costly. However, when combined with machine learning, predicting the duration of stroke patients staying in their bedrooms is possible with reduced cost. We assessed using machine learning to estimate bedroom-stay duration using activity data recorded with wearable devices. Method: We recruited 99 stroke hemiparesis inpatients and conducted 343 measurements. Data on electrocardiograms and chest acceleration were measured using a wearable device, and the location name of the access point that detected the signal of the device was recorded. We first investigated the correlation between bedroom-stay duration measured from the access point as the objective variable and activity data measured with a wearable device and demographic information as explanatory variables. To evaluate the duration predictability, we then compared machine-learning models commonly used in medical studies. Results: We conducted 228 measurements that surpassed a 90% data-acquisition rate using Bluetooth Low Energy. Among the explanatory variables, the period spent reclining and sitting/standing were correlated with bedroom-stay duration (Spearman's rank correlation coefficient (R) of 0.56 and -0.52, p < 0.001). Interestingly, the sum of the motor and cognitive categories of the functional independence measure, clinical indicators of the abilities of stroke patients, lacked correlation. The correlation between the actual bedroom-stay duration and predicted one using machine-learning models resulted in an R of 0.72 and p < 0.001, suggesting the possibility of predicting bedroom-stay duration from activity data and demographics. Conclusion: Wearable devices, coupled with machine learning, can predict the duration of patients staying in their bedrooms. Once trained, the machine-learning model can predict without continuously tracking the actual location, enabling more cost-effective and privacy-centric future measurements.

Lightweight heartbeat detection algorithm for consumer grade wearable ECG measurement devices and its implementation.

We have developed a lightweight heartbeat detection algorithm for electrocardiogram (ECG) measurement in consumer-grade wearable devices. Based on a principle of calculating the clearance height in the inverted time differential of an ECG, the algorithm has a sensitivity specific to the QRS complex in an ECG. Because this algorithm is simple and lightweight, an efficient implementation form has been established for porting the algorithm to consumer-grade devices. We experimentally confirmed that the algorithm runs in an actual commercialized wearable device and provides improvement of heart rate measurement with noise caused by body motion.

Validity of trunk acceleration measurement with a chest-worn monitor for assessment of physical activity intensity.

BACKGROUND: Recent advancements in wearable technology have enabled easy measurement of daily activities, potentially applicable in rehabilitation practice for various purposes such as maintaining and increasing patients' activity levels. In this study, we aimed to examine the validity of trunk acceleration measurement using a chest monitor embedded in a smart clothing system ('hitoe' system), an emerging wearable system, in assessing the physical activity in an experimental setting with healthy subjects (Study 1) and in a clinical setting with post-stroke patients (Study 2). METHODS: Study 1 involved the participation of 14 healthy individuals. The trunk acceleration, heart rate (HR), and oxygen consumption were simultaneously measured during treadmill testing with a Bruce protocol. Trunk acceleration and HR were measured using the "hitoe" system, a smart clothing system with embedded chest sensors. Expiratory gas analysis was performed to measure oxygen consumption. Three parameters, moving average (MA), moving standard deviation (MSD), and moving root mean square (RMS), were calculated from the norm of the trunk acceleration. The relationships between these accelerometer-based parameters and oxygen consumption-based physical activity intensity measured with the percent VO2 reserve (%VO2R) were examined. In Study 2, 48 h of simultaneous measurement of trunk acceleration and heart rate-based physical activity intensity in terms of percent heart rate reserve (%HRR) was conducted with the "hitoe" system in 136 post-stroke patients. RESULTS: The values of MA, MSD, RMS, and %VO2R were significantly different between levels 1, 2, 3, and 4 in the Bruce protocol (P < 0.01). The average coefficients of determination for individual regression for %VO2R versus MA, %VO2R versus MSD, and %VO2R versus RMS were 0.89 ± 0.05, 0.96 ± 0.03, and 0.91 ± 0.05, respectively. Among the parameters examined, MSD showed the best correlation with %VO2R, indicating high validity of the parameter for assessing physical activity intensity. The 48-h measurement of MSD and %HRR in post-stroke patients showed significant within-individual correlation (P < 0.05) in 131 out of 136 patients (correlation coefficient: 0.60 ± 0.16). CONCLUSIONS: The results support the validity of the MSD calculated from the trunk acceleration measured with a smart clothing system in assessing the physical activity intensity. TRIAL REGISTRATION: UMIN000034967. Registered 21 November 2018 (retrospectively registered).

Diagnosis-specific Cumulative Incidence of Return-to-work, Resignation, and Death Among Long-term Sick-listed Employees: Findings From the Japan Epidemiology Collaboration on Occupational Health Study.

BACKGROUND: While it is essential to understand how long is sufficient for return-to-work when designing paid sick-leave systems, little attempt has been done to collect cause-specific information on when and how many of sickness absentees returned to work, became unemployed, or passed away. METHODS: We studied the first sick-leave episode of ≥30 consecutive days in those ≤55 years of age during 2012-2013 among employees of 11 Japanese private companies (n = 1,209), which were followed until 2017. Overall and disease-specific cumulative incidences of return-to-work, resignations, and deaths were estimated using competing risk analysis. RESULTS: During the 3.5-year period (follow-up rate: 99.9%), 1,014 returned to work, 167 became unemployed, and 27 died. Overall, return-to-work occurred within 1 year in 74.9% of all absentees and in 89.3% of those who successfully returned to work. Resignation occurred within 1 year in 8.7% of all absentees and in 62.9% of all subjects who resigned. According to ICD-10 chapters, the cumulative incidence of return-to-work ranged from 82.1% for mental disorders (F00-F99) to 95.3% for circulatory diseases (I00-I99). The cumulative incidence of return-to-work due to mental disorders ranged from 66.7% in schizophrenia (F20) to 95.8% in bipolar affective disorders (F31). Death was rarely observed except for cases of neoplasms (C00-D48), of which the cumulative incidence of death reached 14.2% by 1.5 years. CONCLUSION: Return-to-work and resignations occurred commonly within 1 year of sick leave among long-term sickness absentees in the Japanese private companies. Our findings may assist occupational physicians and employers in developing effective social protection schemes.

Non-High-Density Lipoprotein Cholesterol and Risk of Cardiovascular Disease: The Japan Epidemiology Collaboration on Occupational Health Study.

AIMS: We aimed to investigate the association between non-high-density lipoprotein cholesterol (non-HDL-C) levels and the risk of cardiovascular disease (CVD) and its subtypes. METHODS: In this contemporary cohort study, we analyzed the data of 63,814 Japanese employees aged ≥ 30 years, without known CVD in 2012 and who were followed up for up to 8 years. The non-HDL-C level was divided into 5 groups: ＜110, 110-129, 130-149, 150-169, and ≥ 170 mg/dL. The Cox proportional hazards model was used to calculate the hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs) for CVD and its subtypes associated with each non-HDL-C group, considering 130-149 mg/dL as the reference group. RESULTS: During the study period, 271 participants developed CVD, including 78 myocardial infarctions and 193 strokes (102 ischemic strokes, 89 hemorrhagic strokes, and 2 unknowns). A U-shaped association between non-HDL-C and stroke was observed. In the analysis of stroke subtypes, the multivariable-adjusted HR (95% CI) for hemorrhagic stroke was 2.61 (1.19-5.72), 2.02 (0.95-4.29), 2.10 (1.01-4.36), and 1.98 (0.96-4.08), while that for ischemic stroke was 1.54 (0.77-3.07), 0.91 (0.46-1.80), 0.73 (0.38-1.41), and 1.50 (0.87-2.56) in the ＜110, 110-129, 150-169, and ≥ 170 mg/dL groups, respectively. Individuals with elevated non-HDL-C levels had a higher risk of myocardial infarction. CONCLUSIONS: High non-HDL-C levels were associated with an increased risk of myocardial infarction. Moreover, high and low non-HDL-C levels were associated with a high risk of stroke and its subtypes among Japanese workers.

Visit-to-visit variability of blood pressure and cardiovascular events among the working-age population in Japan: findings from the Japan Epidemiology Collaboration on Occupational Health Study.

Increased visit-to-visit variability (VVV) of blood pressure, which is calculated based on several readings, has been suggested to be a significant predictor of cardiovascular events and mortality, independent of mean blood pressure. This study examined associations between the VVV of systolic blood pressure (SBP) measured annually and cardiovascular disease (CVD) events among 72,617 Japanese subjects. Data were obtained from the Japan Epidemiology Collaboration on Occupational Health Study, which is an ongoing epidemiological survey of workers in Japan. VVV was calculated as the coefficient of variation of SBP readings from 2008 to 2011; information on fatal and nonfatal CVD events was collected from registries of specific outcomes between April 2012 and March 2019. A Cox proportional hazards model was applied to investigate associations after adjusting for mean SBP between 2008 and 2011 and covariates. During the 7-year follow-up period, there were 63 CVD fatalities and 314 CVD events (combining fatal and nonfatal events). The results showed that a one-standard deviation increase in VVV was associated with a significant increase in the risk of CVD mortality (hazard ratio [HR] = 1.42; 95% confidence interval [CI] = 1.32-1.54); those in the highest tertile had a 3.20 times (95% CI = 1.26-8.17) higher risk of CVD mortality than those in the lowest tertile. We found less pronounced associations regarding CVD events (HR = 1.08, 95% CI = 1.02-1.15). In conclusion, VVV was significantly associated with CVD mortality in our Japanese working population.

Prediabetes, Diabetes, and the Risk of All-Cause and Cause-Specific Mortality in a Japanese Working Population: Japan Epidemiology Collaboration on Occupational Health Study.

OBJECTIVE: Prediabetes has been suggested to increase risk for death; however, the definitions of prediabetes that can predict death remain elusive. We prospectively investigated the association of multiple definitions of prediabetes with the risk of death from all causes, cardiovascular disease (CVD), and cancer in Japanese workers. RESEARCH DESIGN AND METHODS: The study included 62,785 workers who underwent a health checkup in 2010 or 2011 and were followed up for death from 2012 to March 2019. Prediabetes was defined according to fasting plasma glucose (FPG) or glycated hemoglobin (HbA1c) values or a combination of both using the American Diabetes Association (ADA) or World Health Organization (WHO)/International Expert Committee (IEC) criteria. The Cox proportional hazards regression model was used to investigate the associations. RESULTS: Over a 7-year follow-up, 229 deaths were documented. Compared with normoglycemia, prediabetes defined according to ADA criteria was associated with a higher risk of all-cause mortality (hazard ratio [HR] 1.53; 95% CI 1.12-2.09) and death due to cancer (HR 2.37; 95% CI 1.45-3.89) but not with death due to CVD. The results were materially unchanged when prediabetes was defined according to ADA FPG, ADA HbA1c, WHO FPG, or combined WHO/IEC criteria. Diabetes was associated with the risk of all-cause, CVD, and cancer deaths. CONCLUSIONS: In a cohort of Japanese workers, FPG- and HbA1c-defined prediabetes, according to ADA or WHO/IEC, were associated with a significantly increased risk of death from all causes and cancer but not CVD.

Smoking and Long-Term Sick Leave in a Japanese Working Population: Findings of the Japan Epidemiology Collaboration on Occupational Health Study.

BACKGROUND: Few studies have investigated the association between tobacco smoking and sick leave (SL) in Japan. METHODS: We followed 70 896 workers aged 20-59 years (60 133 males, 10 763 females) between April 2012 and March 2017. A Cox proportional hazards model was used to investigate the associations between smoking (smoking status and intensity) and long-term SL (ie, SL lasting ≥30 consecutive days). Cause-specific analyses were also conducted. RESULTS: A total of 1777 people took long-term SL during a follow-up of 307 749 person years. Compared with never-smokers, current smokers were at a higher risk of long-term SL (hazard ratio [HR] = 1.32; 95% confidence interval [CI] = 1.19 to 1.48). Cause-specific analyses revealed that current smoking was associated with a higher risk of SL due to all physical disorders (HR = 1.44, 95% CI = 1.22 to 1.69), cancer (HR = 1.49, 95% CI = 1.10 to 2.01), cardiovascular disease (CVD; HR = 2.16, 95% CI = 1.31 to 3.55), and injuries/external causes (HR = 1.83, 95% CI = 1.31 to 2.58). Former smokers were at a higher risk of SL due to cancer at a borderline significance level (HR = 1.38, 95% CI = 0.99 to 1.92). Low-intensity smoking (ie, 1-10 cigarettes smoked per day) was associated with all-cause SL, SL due to CVD, and SL due to injuries/external causes compared with never-smokers. CONCLUSION: In a large cohort of working-age Japanese, smoking was associated with a greater risk of long-term SL. Greater effort is needed to mitigate disease burden associated with smoking at workplace in Japan. IMPLICATIONS: Our study contributes to the literature on the association between smoking and SL in several ways. First, the study was conducted among a Japanese working population. While the association has been extensively studied in Western setting, few attempts have been made elsewhere. Second, cause-specific analyses were undertaken in our study. Third, we paid attention to the effect of low-intensity smoking on SL given that there is growing evidence of an elevated health risk associated with low-intensity smoking.

Loss of Working Life Years Due to Mortality, Sickness Absence, or Ill-health Retirement: A Comprehensive Approach to Estimating Disease Burden in the Workplace.

BACKGROUND: While much effort has focused on quantifying disease burden in occupational health, no study has simultaneously assessed disease burden in terms of mortality and morbidity. We aimed to propose a new comprehensive method of quantifying the disease burden in the workplace. METHODS: The data were obtained from the Japan Epidemiology Collaboration on Occupational Health (J-ECOH) Study, a large-scale prospective study of approximately 80,000 workers. We defined disease burden in the workplace as the number of working years lost among the working population during a 6-year period (April 2012 to March 2018). We calculated the disease burden according to consequences of health problems (ie, mortality, sickness absence [SA], and ill-health retirement) and disease category. We also calculated the age-group- (20-39 and 40-59 years old) and sex-specific disease burden. RESULTS: The largest contributors to disease burden in the workplace were mental and behavioural disorders (47.0 person-years lost per 10,000 person-years of working years; ie, per myriad [proportion]), followed by neoplasms (10.8 per myriad) and diseases of the circulatory system (7.1 per myriad). While mental and behavioural disorders made a greater contribution to SA and ill-health retirement compared to mortality, the latter two disorders were the largest contributors to the disease burden in the workplace due to mortality. The number of working years lost was greater among younger versus older female participants, whereas the opposite trend was observed in males. CONCLUSIONS: Our approach is in contrast to those in previous studies that focused exclusively on mortality or morbidity.

Diabetes, prediabetes, and suicide deaths in a Japanese working population.

OBJECTIVE: To examine the association of diabetes and prediabetes with suicide deaths in a Japanese working population. METHODS: A nested case-control study was conducted using data from the Japan Epidemiology Collaboration on Occupational Health Study. During 8 years of follow-up, we identified 56 registered cases of suicide death that had information on fasting plasma glucose or glycated hemoglobin A1c at any health check-up during the past 3 years prior to suicide. For each case, we randomly selected five controls matched for age, sex, and worksite. We used the latest health check-up data for analysis. We defined diabetes status based on the American Diabetes Association criteria and used a conditional logistic regression model to investigate the association. RESULTS: Adjusted odds ratios and 95% confidence intervals for suicide death were 0.67 (0.32-1.41) and 3.53 (1.05-11.91) for prediabetes and diabetes, respectively, compared to normoglycemia. Similar results were obtained when diabetes status was exclusively defined by the fasting plasma glucose or glycated hemoglobin A1c level. CONCLUSION: Diabetes, but not prediabetes, was associated with a higher risk of suicide death, compared with normoglycemia, among a Japanese working population.

BMI and Medically Certified Long-Term Sickness Absence Among Japanese Employees.

OBJECTIVE: In contrast to the association between excess weight and sickness absence (SA), the association in relation to underweight has been under-researched. This study aimed to examine the effects of BMI at both extremes of its distribution on SA. METHODS: Data came from the Japan Epidemiology Collaboration on Occupational Health study of 77,760 workers aged 20 to 59 years (66,166 males, 11,594 females). Information was collected on medically certified long-term SA (LTSA) (i.e., SA lasting ≥ 30 consecutive days) from April 2012 to March 2017. A sex-specific Cox proportional hazards model was used to investigate the associations. RESULTS: Among males, both obesity (hazard ratio [HR] = 1.81, 95% CI: 1.50-2.17) and underweight (HR = 1.56, 95% CI: 1.23-1.96) were significantly associated with LTSA compared with normal weight. This U-shaped association between BMI categories and LTSA was observed both for mental and physical disorders. Among females, an elevated risk was observed among those with overweight (HR = 1.54, 95% CI: 1.16-2.05). CONCLUSIONS: In a cohort of the Japanese working-age population, both obesity and underweight were associated with a greater risk of LTSA in males. Future research should not overlook the excess risk of LTSA associated with underweight.

Trajectories of body mass index and waist circumference before the onset of diabetes among people with prediabetes.

BACKGROUND & AIMS: To investigate trajectories of body mass index (BMI) and waist circumference (WC) among prediabetic people who progressed to diabetes, people who remained with prediabetes, and those who returned to normoglycemia. METHODS: We used data from 22,945 prediabetic people who received an annual health checkup for up to eight years. The development of diabetes was defined using the American Diabetes Association criteria. People who did not progress to diabetes during the observation period were classified as 'remained with prediabetes' or 'returned to normoglycemia', based on their last health checkup data. Trajectories of BMI and WC were evaluated using linear mixed models for repeated measures, with adjustment for a wide range of covariates. RESULTS: During the study period, 2972 people progressed to diabetes, 4706 returned to normoglycemia, and 15,267 remained with prediabetes. People who progressed to diabetes had a larger increase in mean BMI from 7 years to 1 year prior to diagnosis, which was about three times that of people who remained with prediabetes (annual change rate, 0.20 [95% confidence interval; 0.15 to 0.24] vs 0.06 [0.04 to 0.08] kg/m2 per year, P < 0.001), regardless of their BMI levels at the initial health checkup. Among people who returned to normoglycemia, mean BMI remained almost the same over time (-0.04 [-0.09 to 0.002] kg/m2 per year), except for those with obesity (-0.16 [-0.28 to -0.05] kg/m2 per year). As for WC, the annual change rate among people who developed diabetes was about 7 times that of people who remained with prediabetes (0.38 [0.32 to 0.45] vs 0.05 [0.03 to 0.08] cm per year, P < 0.001). We also observed a constant mean WC over time among people who had no central obesity and later returned to normoglycemia (-0.02 [-0.06 to 0.03] cm per year), and an annual decrease in mean WC among those who had central obesity and later returned to normoglycemia (-0.40 [-0.47 to -0.32] cm per year). CONCLUSIONS: Our study provides strong evidence that avoiding weight gain could help prediabetic people minimize the risk of developing diabetes, regardless of whether they are obese. Losing weight could help obese people restore normoglycemia from a prediabetic state, whereas maintaining current weight may help nonobese people return to normoglycemia.

Obesity and risk of hearing loss: A prospective cohort study.

BACKGROUND & AIMS: The existing yet limited prospective studies reported conflicting results about obesity and hearing loss. We investigated the prospective association between obesity and hearing loss in a large-scale Japanese working population, as well as the association between metabolic phenotype and hearing loss. METHODS: The study included 48,549 employees aged 20-64 years and free of hearing loss at baseline. Pure-tone audiometric testing was performed annually to identify hearing loss at 1 and 4 kHz. Cox proportional hazards regression was used to investigate the risk of hearing loss associated with body mass index (BMI) and metabolic phenotype (based on a BMI of ≥25.0/<25.0 kg/m2 and presence/absence of ≥2 components of metabolic syndrome, except waist circumference). Baseline and updated information were obtained from annual health checkups. RESULTS: With a median follow-up of 7 years, 1595 and 3625 individuals developed unilateral hearing loss at 1 and 4 kHz, respectively. The adjusted hazard ratios (HR) for hearing loss at 1 kHz were 1.21 (1.08, 1.36) and 1.66 (1.33, 2.08) for those with BMI 25.0-29.9 kg/m2 and BMI ≥30.0 kg/m2, respectively, compared to individuals with BMI <25.0 kg/m2. For hearing loss at 4 kHz, the corresponding HRs were 1.14 (1.05, 1.23) and 1.29 (1.09, 1.52). Compared with metabolically healthy non-obese individuals, the adjusted HRs for hearing loss at 1 kHz were 1.19 (1.03, 1.39), 1.27 (1.01, 1.61), and 1.48 (1.25, 1.76) for unhealthy non-obese, healthy obese, and unhealthy obese individuals, respectively. For hearing loss at 4 kHz, the corresponding HRs were 1.13 (1.04, 1.25), 1.21 (1.04, 1.41), and 1.26 (1.12, 1.41). CONCLUSIONS: Overweight and obesity are associated with an increased risk of hearing loss, and metabolically unhealthy obesity may confer additional risk.