Duration and degree of weight change and risk of incident diabetes: Japan Epidemiology Collaboration on Occupational Health Study

Lifestyle behaviour patterns in the prevention of type 2 diabetes mellitus: the Fukushima Health Database 2015-2020

OBJECTIVES

Lifestyle behaviours associated with the incidence of type 2 diabetes mellitus (T2DM) need further clarification using health insurance data.

STUDY DESIGN

This is a cohort study.

METHODS

In 2015, 193,246 participants aged 40-74 years attended the specific health checkups and were observed up to 2020 in Fukushima, Japan. Using the principal component analysis, we identified two patterns from ten lifestyle behaviour questions, namely, the "diet-smoking" pattern (including smoking, alcohol drinking, skipping breakfast, eating fast, late dinner, and snacking) and the "physical activity-sleep" pattern (including physical exercise, walking equivalent activity, walking fast, and sufficient sleep). Then, individual pattern scores were calculated; the higher the scores, the healthier the behaviours.

RESULTS

The accumulative incidence rate of T2DM was 630.5 in men and 391.9 in women per 100,000 person-years in an average of 4 years of follow-up. Adjusted for the demographic and cardiometabolic factors at the baseline, the hazard ratio (95% confidence interval) of the highest versus lowest quartile scores of the "diet-smoking" pattern for T2DM risk was 0.82 (0.72, 0.92; P for trend = 0.002) in men and 0.87 (0.76, 1·00; P for trend = 0.034) in women; that of the "physical activity-sleep" pattern was 0.92 (0.82, 1·04; P for trend = 0.0996) in men and 0.92 (0.80, 1·06; P for trend = 0.372) in women. The "physical activity-sleep" pattern showed a significant inverse association in non-overweight men.

CONCLUSIONS

Lifestyle behaviour associated with a healthy diet and lack of smoking may significantly lower the risk of T2DM in middle-aged Japanese adults.

Incidence and temporal trends in type 2 diabetes by weight status: A systematic review and meta-analysis of prospective cohort studies

Background

Diabetes is more prevalent among overweight/obese individuals, but has become a significant public health challenge among normal weight populations. In this meta-analysis, we aimed to estimate diabetes/prediabetes incidence and its temporal trends by weight status.

Methods

PubMed, Embase, Web of Science, and Cochrane Library were searched until 8 December 2021. Prospective cohort studies reporting diabetes incidence by baseline body mass index (BMI) categories in adults were included. The median year of data collection was used to assess the temporal trends. Subgroup analyses and meta-regression were also performed.

Results

We included 94 studies involving 3.4 million adults from 22 countries. The pooled diabetes incidence in underweight, normal-weight, and overweight/obese adults was 4.5 (95% confidence interval (CI) = 2.8-7.3), 2.7 (95% CI = 2.2-3.3), and 10.5 (95% CI = 9.3-11.8) per 1000 person-years, respectively. The diabetes incidence in low- and middle-income countries (LMICs) was higher than in high-income countries among normal-weight (5.8 vs 2.0 per 1000 person-years) or overweight/obese (15.9 vs 8.9 per 1000 person-years) adults. European and American regions had a higher diabetes incidence than the non-Western areas, regardless of weight status. Underweight diabetes incidence decreased significantly from 1995-2000 to 2005-2010. Diabetes incidence in normal-weight populations has increased continuously since 1985 by an estimated 36% every five years. In overweight/obese adults, diabetes incidence increased between 1985-1990 and 1995-2000, stabilised between 2000 and 2010, and spiked suddenly after 2010.

Conclusions

Diabetes incidence and its temporal trends differed by weight status. The continuous upward trend of diabetes incidence among overweight/obese individuals requires urgent attention, particularly in LMICs. Furthermore, diabetes among normal-weight individuals is becoming a significant public health problem.

Registration

PROSPERO (CRD42020215957).

Abdominal volume index trajectories and risk of diabetes mellitus: Results from the China Health and Nutrition Survey

AIMS/INTRODUCTION

Abdominal obesity is a risk factor for developing diabetes mellitus, but trajectories of abdominal obesity over time and incident diabetes mellitus have not been considered. We derived trajectories of abdominal volume index (AVI) over 16 years of follow up, and examined the associations between AVI trajectories and risk of diabetes mellitus.

MATERIALS AND METHODS

Data were used from the China Health and Nutrition Survey, and 5,267 participants were enrolled to fit the trajectory of AVI by using latent class growth models. Multivariate logistic regression models explored the relationship between different AVI trajectories and risk of diabetes mellitus. In addition, we examined the slope of the AVI trajectories in relation to age to identify appropriate life course intervention opportunities for the prevention of diabetes mellitus.

RESULTS

Three trajectories were derived reflecting graded categories in the speed and slope of increase in AVI over time: slow, intermediate and fast increase group, respectively. After multivariate adjustment, the odds ratios for diabetes mellitus among those in the intermediate and fast increase groups were 1.81 (95% confidence interval 1.37-2.38, P < 0.001) and 2.80 (95% confidence interval 1.85-4.24, P < 0.001) respectively, relative to the slow increase group. The distribution of AVI slope in the slow increase group showed an inverted "U" shape, whereas the fast increase group presented a "U" shape.

CONCLUSIONS

AVI trajectory is associated with an increased risk of diabetes mellitus. These results provide new insights on the relationship between abdominal adiposity and diabetes mellitus, which in turn can help improve clinical and public health intervention for diabetes mellitus prevention.

Associations of anemia and hemoglobin with hemoglobin A1c among non-diabetic workers in Japan

AIMS/INTRODUCTION

We examined the association between hemoglobin A1c (HbA1c) and anemia, which was categorized into three groups according to mean corpuscular volume (MCV), as well as the association between hemoglobin in the non-anemic range and HbA1c.

MATERIALS AND METHODS

We used the 2016 health checkup data from 36,422 workers without diabetes. Anemic people were divided into three groups based on MCV: <80, 80-90 and >90 fL. Non-anemic people were divided into four groups based on their hemoglobin levels. We carried out multiple linear regression models to estimate the means and 95% confidence intervals (CIs) of HbA1c.

RESULTS

For men, 0.2% had anemia with MCV <80 fL, 0.5% had anemia with MCV 80-90 fL, 0.9% had anemia with MCV >90 fL and 98.4% had no anemia. For women, the corresponding values were 6.1, 6.4, 2.8 and 84.7%, respectively. The adjusted mean HbA1c (%) values for men with anemia with MCV <80, 80-90 and >90 fL were 5.67 (95% CI 5.60-5.74), 5.58 (95% CI 5.54-5.62) and 5.41 (95% CI 5.37-5.44), respectively. Among men without anemia, HbA1c (%) increased from 5.36 (95% CI 5.34-5.39) in those with hemoglobin ≥17.5 mg/dL to 5.45 (95% CI 5.45-5.46) in those with hemoglobin 13.0 to <14.5 mg/dL (P for trend <0.001). The HbA1c values were higher in men with anemia with MCV <80 fL or MCV 80-90 fL, but lower in men with MCV >90 fL, compared with non-anemic men with hemoglobin 13.0 to <14.5 mg/dL (All P < 0.001). Similar findings were observed in women.

CONCLUSIONS

We observed elevated HbA1c among anemic people with MCV <80 fL or MCV 80-90 fL, and decreased HbA1c among anemic people with MCV >90 fL, suggesting that different types of anemia might influence HbA1c differently. In addition, non-anemic people with lower hemoglobin levels had higher HbA1c levels, suggesting that hemoglobin levels are in need of consideration when interpreting HbA1c values among non-anemic people.

Beyond recent BMI: BMI exposure metrics and their relationship to health

Body mass index (BMI) is generally used to classify adiposity. Despite the fact that the consequences of adiposity for chronic health accumulate and manifest over time, most population health research exploring the implications of high BMI measures only its recent intensity. Some studies have used retrospective measures involving maximum weight, and even fewer have used BMI at multiple time points to estimate cumulative exposure to adiposity. The goal of this study was to compare BMI exposure metrics that captured different dimensions of body mass – intensity, history, and duration – in models of health indicators linked with adiposity. We used self-reported BMI of young adults (ages 18 – 33 years, n = 8,608) across 11 waves of data from the National Longitudinal Survey of Youth 1997 to evaluate eight BMI exposure metrics: most recent, maximum, mean, and median BMI, proportion of time with overweight/obesity, and excess BMI-years with overweight/obesity. We used these metrics in models of self-reported general health, chronic condition, and diabetes, and ascertained how most recent BMI performed when compared with other metrics that better capture the dynamics of BMI. The Akaike information criteria and Vuong tests were used for model comparison, and the strengths of associations were also compared. Most recent BMI was the best metric for explaining general health. Median BMI was best for explaining diabetes, with most recent BMI under-estimating the association by 13% relative to median BMI. For chronic condition, there was no clear best metric. We concluded that most recent BMI is useful for explaining health outcomes, though other metrics should also be given consideration, particularly for conditions that develop over time. Metrics that accounted for both intensity and history performed quite well, but the duration measures might be less useful.

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BMI is dynamic, so researchers need to consider beyond BMI at the time of survey.

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We calculated 8 BMI-based metrics accounting for intensity, history, and duration.

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Most recent BMI was the best metric, based on AIC, for explaining general health.

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Most recent BMI understated the association for diabetes, relative to median BMI.

Five-year cumulative incidence of overweight and obesity, and longitudinal change in body mass index in Japanese workers: The Japan Epidemiology Collaboration on Occupational Health Study

OBJECTIVE

The present study aimed to estimate cumulative incidence of overweight and obesity and describe 5-year longitudinal changes in body mass index (BMI) in a large occupational cohort in Japan.

METHODS

Participants were 55 229 Japanese employees, who were aged 20-59 years and attended at all subsequent annual health check-ups between 2009 and 2014. Mixed model analysis was performed to examine the effects of age and cohort by gender on BMI change, with age as a random variable. Cumulative incidence of overweight (23.0≤ BMI <27.5 kg/m2 ) and obesity (BMI ≥27.5 kg/m2 ) was calculated. Logistic regression analysis was used to estimate odds ratios for the incidence of overweight and obesity according to age group.

RESULTS

The incidence of overweight and obesity was approximately double in men (28.3% and 6.7%, respectively) compared to women (14.3% and 3.9%, respectively).The incidence of obesity decreased with age in men, but did not differ according to age in women (P for trend: .02 and .89, respectively). Among overweight participants, the incidence of obesity was higher in women (18.9%) than men (14.5%) and decreased with advancing age (P for trend: <.001 in men and .003 in women). Mean BMI was higher in men than women in all age groups throughout the period. Younger cohorts tended to have a higher BMI change compared with older cohorts.

CONCLUSIONS

In this Japanese occupational cohort, transition from overweight to obesity is higher in women than men, and the more recent cohorts had a higher change in mean BMI than the older cohorts.

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.

Low serum creatinine and risk of diabetes: The Japan Epidemiology Collaboration on Occupational Health Study

AIMS/INTRODUCTION

We examined a prospective association between serum creatinine levels and diabetes.

MATERIALS AND METHODS

The present study included 31,343 male workers without diabetes, and aged between 20 and 64 years at baseline. We calculated the cumulative average of their serum creatinine over the study period. We defined diabetes as either glycated hemoglobin levels ≥6.5%, random glucose levels ≥200 mg/dL, fasting glucose levels ≥126 mg/dL or receiving antidiabetic treatment. Cox proportional hazards regression analysis was carried out to estimate the hazard ratio (HR) and 95% confidence interval (CI).

RESULTS

With a median observation of 7.7 years, 2,509 participants developed diabetes. After adjusting for age, smoking, body mass index, hypertension and dyslipidemia, lower cumulative average serum creatinine levels were related to a greater diabetes risk: HRs were 1.56 (95% CI 1.35-1.82), 1.22 (1.09-1.35) and 1.06 (0.96-1.17) for the participants with serum creatinine <0.70, 0.70-0.79 and 0.80-0.89 mg/dL, respectively, compared with those with 0.90-1.20 mg/dL (P for trend <0.001). The serum creatinine-diabetes association was more pronounced among older adults (serum creatinine <0.70 vs 0.90-1.20 mg/dL, HR 1.66, 95% CI 1.37-2.00) than younger adults (HR 1.32, 95% CI 1.02-1.71; P for interaction by age group = 0.001).

CONCLUSIONS

Low serum creatinine is associated with an increased risk of diabetes. Screening serum creatinine levels can be used to identify those who are at high risk of diabetes.

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.

Cumulative Risk of Type 2 Diabetes in a Working Population: The Japan Epidemiology Collaboration on Occupational Health Study

BACKGROUND

We estimated the cumulative risk of type 2 diabetes from age 30 to 65 years in a large working population in Japan.

METHODS

We used data from the Japan Epidemiology Collaboration on Occupational Health Study. Participants (46,065 men and 7,763 women) were aged 30-59 years, free of diabetes at baseline, and followed up for a maximum of 7 years. Incident type 2 diabetes was defined based on fasting and casual glucose, glycated hemoglobin, and current medical treatment for type 2 diabetes. We calculated the sex-specific cumulative risk of type 2 diabetes using the Practical Incidence Estimator macro, which was created to produce several estimates of disease incidence for prospective cohort studies based on a modified Kaplan-Meier method.

RESULTS

During 274,349 person-years of follow-up, 3,587 individuals (3,339 men and 248 women) developed type 2 diabetes. The cumulative risk was 34.7% (95% confidence interval, 33.1-36.3%) for men and 18.6% (95% confidence interval, 15.5-21.7%) for women. In BMI-stratified analysis, obese (BMI ≥30 kg/m2) and overweight (BMI 25-29.9 kg/m2) men and women had a much higher cumulative risk of type 2 diabetes (obese: 77.3% for men and 64.8% for women; overweight: 49.1% and 35.7%, respectively) than those with BMI <25 kg/m2 (26.2% and 13.4% for men and women, respectively).

CONCLUSIONS

The present data highlight the public health burden of type 2 diabetes in the working population. There is a need for effective programs for weight management and type 2 diabetes screening, especially for young obese employees, to prevent or delay the development of type 2 diabetes.

Prediabetes and cardiovascular disease risk: A nested case-control study

BACKGROUND AND AIMS

We aimed to examine the risk of cardiovascular disease (CVD) with persistent prediabetes during the last four years prior to a CVD event in a large occupational cohort in Japan.

METHODS

We performed a nested case-control study using data from the Japan Epidemiology Collaboration on Occupational Health Study. A total of 197 registered cases of CVD were identified and matched individually with 985 controls according to age, sex, and worksite. Prediabetes was defined as fasting plasma glucose 100-125 mg/dL and/or HbA1c 5.7-6.4%. Persistent prediabetes was defined as having prediabetes at years one and four prior to the onset/index date; persistent normoglycemia was similarly defined. Associations between prediabetes and CVD risk were assessed using conditional logistic regression models.

RESULTS

Compared with people with persistent normoglycemia over the four years prior to the onset/index date, the unadjusted odds ratio (95% confidence interval) for CVD was 2.88 (1.56, 5.32) for people with persistent prediabetes. After adjusting for BMI, smoking, hypertension, and dyslipidemia assessed four years before the onset/index date, the association was slightly attenuated to an OR (95% confidence interval) of 2.62 (1.31, 5.25). Prediabetes assessed at single time points was also associated with an elevated risk of CVD, with multivariable-adjusted odds ratio (95% confidence interval) of 1.72 (1.12, 2.64) and 2.13 (1.32, 3.43) for prediabetes at one and four years prior to the onset/index date, respectively.

CONCLUSIONS

Prediabetes is associated with an increased risk of CVD. Identification and management of prediabetes are important for the prevention of CVD.

Development and validation of risk models to predict the 7-year risk of type 2 diabetes: The Japan Epidemiology Collaboration on Occupational Health Study

AIMS/INTRODUCTION

We previously developed a 3-year diabetes risk score in the working population. The objective of the present study was to develop and validate flexible risk models that can predict the risk of diabetes for any arbitrary time-point during 7 years.

MATERIALS AND METHODS

The participants were 46,198 Japanese employees aged 30-59 years, without diabetes at baseline and with a maximum follow-up period of 8 years. Incident diabetes was defined according to the American Diabetes Association criteria. With routine health checkup data (age, sex, abdominal obesity, body mass index, smoking status, hypertension status, dyslipidemia, glycated hemoglobin and fasting plasma glucose), we developed non-invasive and invasive risk models based on the Cox proportional hazards regression model among a random two-thirds of the participants, and used another one-third for validation.

RESULTS

The range of the area under the receiver operating characteristic curve increased from 0.73 (95% confidence interval 0.72-0.74) for the non-invasive prediction model to 0.89 (95% confidence interval 0.89-0.90) for the invasive prediction model containing dyslipidemia, glycated hemoglobin and fasting plasma glucose. The invasive models showed improved integrated discrimination and reclassification performance, as compared with the non-invasive model. Calibration appeared good between the predicted and observed risks. These models performed well in the validation cohort.

CONCLUSIONS

The present non-invasive and invasive models for the prediction of diabetes risk up to 7 years showed fair and excellent performance, respectively. The invasive models can be used to identify high-risk individuals, who would benefit greatly from lifestyle modification for the prevention or delay of diabetes.

Metabolic Syndrome Over 4 Years Before the Onset of Cardiovascular Disease - Nested Case-Control Study

BACKGROUND

We investigated the risk of cardiovascular disease (CVD) with duration of metabolic syndrome (MetS) for the past 4 years before the CVD event.Methods and Results:We performed a nested case-control study within the Japan Epidemiology Collaboration on Occupational Health Study. A total of 139 registered cases of CVD and 561 self-reported cases of CVD were identified and matched individually on age, sex, and worksite with 695 and 2,803 controls, respectively. MetS was defined by the Joint Interim Statement definition. The odds ratio (95% confidence interval) for registered CVD was 4.7 (2.9, 7.5) for people with persistent MetS (positive for MetS for ≥3 assessments) and 1.9 (1.1, 3.3) for those with intermittent MetS (positive for MetS for 1-2 assessments), compared with people without MetS during the past 4 years before the event/index date (P for trend <0.001). The corresponding odds ratio for self-reported CVD was 2.7 (2.2, 3.5) and 1.8 (1.4, 2.3) (P for trend <0.001). The association with MetS duration was stronger for myocardial infarction than for other CVD subtypes. Similar results were obtained when using the Japanese MetS criteria.

CONCLUSIONS

The risk of CVD increases with increasing MetS duration. These findings contribute to risk stratification and encourage lifestyle modification for people with MetS to minimize their health risk.