WHAT IS ALREADY KNOWN ON THIS TOPIC

The unprecedented lifestyle changes during the COVID-19 pandemic have been consistently linked with poor cardiometabolic health such as worsened glycaemic control, blood pressure control and increased weight among individuals with pre-existing comorbidities.

However, it remains unclear whether the pandemic similarly affected the cardiometabolic health of individuals without pre-existing comorbid conditions.

WHAT THIS STUDY ADDS

By using comprehensive annual health check-up data, which captures both diagnosed and undiagnosed cardiometabolic events, this study provides robust evidence of an increased incidence of cardiometabolic risk factors among Japanese workers during the first year of the pandemic.

These risk factors returned to prepandemic levels in the second year, coinciding with the relaxation of restrictions and the widespread rollout of vaccines.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICYIntroduction

COVID-19, caused by the SARS-CoV-2, emerged as a significant global health hazard.1 To counter its rapid transmission, nations implemented various preventive measures such as lockdowns or restrictions on social gatherings, recommendations on infection prevention behaviours (ie, hand hygiene, wearing medical masks, practising social distancing) and vaccination campaigns. While these measures have been effective in reducing the incidence and mortality of COVID-19,2 3 some of them might have had negative consequences beyond the control of infectious disease. Changes in behaviour such as decreased physical activity, increased sedentary time, smoking, alcohol use and unhealthy diet have been observed during the pandemic.4 5 Studies have shown that the COVID-19 lockdown resulted in worsened glycaemic control, blood pressure control and increased weight among those with type 2 diabetes,6 hypertension7 and obesity.8 It would be of interest to examine whether the COVID-19 pandemic deteriorated the cardiometabolic profile of individuals without having relevant disease or condition.

Several studies9–18 have reported the incidence of cardiometabolic risk factors (ie, obesity,9 17 18 diabetes,9–15 hypertension,10–12 17 dyslipidaemia10 13 and metabolic syndrome (MetS)16) during the earlier COVID-19 pandemic period (ie, 2020 or 2020 to 2021) compared with those before the pandemic (2019 or 2017 to 2019), but their results were contradictory. For instance, studies in Belgium,9 USA,14 15 South Korea,16 Japan17 and Saudi Arabia18 have shown an increase in the incidence of obesity,9 17 diabetes,14 15 hypertension14 17 and MetS16 in 2020 compared with the prepandemic period. In contrast, studies in Finland,10 Wales11 and Spain12 13 have shown a decrease in the incidence of diabetes,10–13 hypertension10–12 and dyslipidaemia.10 13

Most of these studies analysed either healthcare-registered data9–13 or hospital-based data,14–16 18 which included only diagnosed cases. Under the pandemic, people might have hesitated to go to the hospital or clinic, leaving many cases undiagnosed. Thus, the real impact of the COVID-19 pandemic on cardiometabolic risk factors remains elusive. Further, the influence of the COVID-19 pandemic may differ across countries due to the differing levels of social restrictions imposed by their governments, but most previous studies on this issue were conducted in countries with strict lockdowns.9–15 In Japan, the government declared states of emergency and urged citizens to stay home and avoid social gatherings during specific periods—from 7 April to 25 May 2020, and from 8 January to 21 March 2021, but did not impose a strict lockdown. A Japanese study17 assessed and showed an increase in the incidence of cardiometabolic risk factors (overweight, hypertension) in the first year of the pandemic using health check-up data. It would be valuable to test whether the effect of the pandemic on cardiometabolic risk factors has continued after the vaccine rollout and the relaxation of the social restrictions.

The objective of the present study is to examine the incidence of obesity, diabetes, hypertension, dyslipidaemia and MetS among Japanese workers during the first 2 years of COVID-19 pandemic, relative to the incidence which was predicted from the data during the prepandemic period.

MethodsStudy design

We used data of the Japan Epidemiology Collaboration on Occupational Health (J-ECOH) study, which is an ongoing multicentre epidemiological study among predominantly full-time workers of more than 10 companies (eg, electric machinery and apparatus manufacturing, chemical, gas, steel, automobile, and instrument manufacturing, non-ferrous metal manufacturing and plastic product manufacturing) in Japan.19 We invited companies headquartered in the Kanto and Tokai regions of Japan via an occupational physician network; the J-ECOH study mainly involves large-scale companies in Japan. The workers underwent annual health check-ups, comprising anthropometric measurements, physical examinations, laboratory examinations and a self-administered questionnaire about medical history and health-related lifestyle factors. Almost all workers underwent the annual health check-up, as employers in Japan must organise general health check-ups for their employees at least once per year according to the Industrial Safety and Health Act in Japan. Participants did not provide verbal or written informed consent, but they were allowed to refuse and withdraw participation. This procedure conforms to the Japan Ethical Guideline for Epidemiological Research, which suggests that informed consent from each participant is not necessarily required for observational studies using existing data.

Participants

To calculate the annual incidence of health conditions among workers, we used annual health check-up data from fiscal year (FY) 2015 to 2021 (from 1 April 2015 to 31 March 2022). We then created six cohorts: cohort 1 (2015 to 2016, n=72 046); cohort 2 (2016 to 2017, n=72 013); cohort 3 (2017 to 2018, n=71 500); cohort 4 (2018 to 2019, n=71 394); cohort 5 (2019 to 2020, n=71 012); and cohort 6 (2020 to 2021, n=68 190).

For the analysis for each outcome in each cohort, we excluded individuals who lacked data on the targeted outcome, self-reported a history of cardiovascular diseases or cancer, or already had the targeted outcome at baseline. This led to varying population sizes for each analysis, as depicted in figure 1.

Figure 1

Study design. B, baseline; CVD, cardiovascular disease; E, endline; J-ECOH, Japan Epidemiology Collaboration on Occupational Health; MetS, metabolic syndrome.

General health examination

The body height and weight were measured according to a standard protocol of each company. Body mass index was calculated as the weight in kilograms divided by the squared height in metres. Blood pressure was measured as a part of the mandatory health check-up, with different protocols used at each worksite; treatment status for diabetes, hypertension and dyslipidaemia was self-reported using a questionnaire. Biochemical measurements included plasma glucose, haemoglobin A1c (HbA1c), low-density lipoprotein-cholesterol (LDL-C), high-density lipoprotein-cholesterol (HDL-C) and triglycerides (TG). Plasma blood glucose was measured using an enzymatic or a glucose oxidase peroxidative electrode method. HbA1c was measured using a latex agglutination immunoassay method, high-performance liquid chromatography method or enzymatic method. TG, LDL-C and HDL-C levels were measured by the enzymatic method. All laboratories involved in the health check-up in the participating companies have received satisfactory scores (rank A or a score >95 out of 100) from external quality control agencies, including the National Federation of Industrial Health Organization, the Japan Medical Association and the Japanese Association of Laboratory Medical Technologists.

Diagnosis of cardiometabolic risk factors

According to Asia-Pacific anthropometric cut-offs, obesity was defined as ≥25 kg/m2.20 Following the ADA criteria, we defined diabetes as HbA1c≥6.5%, fasting plasma glucose (FPG) level ≥126 mg/dL or current use of antidiabetic medication.21 Hypertension was defined as systolic blood pressure ≥140 mm Hg, diastolic blood pressure ≥90 mm Hg or as receiving medical treatment for hypertension.22 Dyslipidaemia was defined as TG ≥150 mg/dL, LDL-C ≥140 mg/dL, HDL-C <40 mg/dL or as receiving medical treatment for dyslipidaemia, based on the criteria for the Japan Atherosclerosis Society.23 According to the Joint Interim Statement,24 we defined MetS as the presence of three or more of the following components: (1) high waist circumferences: a waist circumference ≥90 cm in men and ≥80 cm in women; (2) high TG: serum TG levels ≥150 mg/dL; (3) low HDL-C: HDL-C <40 mg/dL in men and <50 mg/dL in women; (4) high blood pressure: systolic blood pressure ≥130 mm Hg or diastolic blood pressure ≥85 mm Hg; and (5) high FPG: an FPG level ≥100 mg/dL. Participants with a history of diabetes, hyperlipidaemia medication and antihypertensive medication were considered to meet the criteria for high FPG, high TG and high blood pressure, respectively.

Statistical analysis

Data are shown as mean (SD) for continuous variables and percentages for categorical variables. A Poisson regression model was used to estimate the incidence rate and 95% CI per 100 person-years for obesity, diabetes, hypertension, dyslipidaemia and MetS in each year from 2016 to 2021 FYs considering the previous FY as baseline. In this study, the incidence rate from FY 2016 to 2019 was considered as the prepandemic period to establish a long-term trend and predict changes in each outcome during the pandemic period (FYs 2020 and 2021). The rationale for selecting this extended time span was to provide a comprehensive and stable prepandemic trend, thereby minimising the influence of short-term fluctuations and natural ageing effects on our analysis. To analyse deviations of the respective outcome during the COVID-19 pandemic (FYs 2020 and 2021) compared with predicted levels based on the prepandemic years (FYs 2016 to 2019), we applied multivariable linear trend regression models from 2016 to 2019 for each outcome and used the resulting regression coefficients to predict the incidence rate of targeted outcome for 2020 and 2021. We then compared the observed incidence rate in 2020 and 2021 with the predicted incidence rate by calculating the difference with corresponding 95% CIs and applying a Z test based on standard normal distribution. The model was adjusted for age (<35, 35 to 44, 45 to 54, 55 to 64 or ≥65 years), sex (male or female) and company. Statistical significance was set at p<0.05 for the trend. All analyses were performed using the statistical software Stata V.18.0 (StataCorp, College Station, Texas, USA).

Results

Table 1 shows the participant’s background characteristics in each cohort across the targeted outcome. In cohort 5 (FYs 2019–2020), the proportion of men was around 80% and mean age was 41–45 years. These figures were similar across all six cohorts.

Table 1

Characteristics of the study population according to each cohort

As shown in figure 2, an increasing incidence of obesity, diabetes, hypertension, dyslipidaemia, and MetS was evident over the time period from 2016 through 2021. There was a significant increase in the incidence of all the outcomes in 2020 compared with the prepandemic period, followed by a decrease in 2021. The average of age, sex and company-adjusted annual incidence per 100 person-years for obesity, diabetes, hypertension, dyslipidaemia and MetS between FY 2016 and 2019 was 5.0%, 1.4%, 5.3%, 17.4% and 7.6%, which was increased to 6.0%, 1.8%, 6.6%, 19.3% and 8.5% in FY 2020 and then again decreased to 5.1%, 1.5%, 6.1%, 18.0% and 8.3% in FY 2021 (figure 2 and online supplemental table 1).

Figure 2

Age, sex and company-adjusted observed and predicted incidence per 100 person-years for (A) obesity, (B) diabetes, (C) hypertension, (D) dyslipidaemia and (E) metabolic syndrome from fiscal year (FY) 2016 to 2021 among the workers in Japan. Circles with vertical bars (in red) represent the observed incidence rates with 95% CI, and a solid line with bands (in blue) represents the predicted incidence rates with 95% CI estimated from linear trend regression models from 2016 to 2019.

As shown in table 2, the age, sex and company-adjusted observed incidence in 2020 was significantly higher than the predicted incidence; the difference in observed and predicted incidence rates (95% CI) was 0.79 (0.45 to 1.12) for obesity, 0.30 (0.11 to 0.48) for diabetes, 0.60 (0.27 to 0.93) for hypertension, and 0.45 (0.12 to 0.88) for MetS, respectively. Similarly, the observed incidence for dyslipidaemia in 2020 was higher, although marginally significant, than the predicted incidence; the difference in observed and predicted incidence rates (95% CI) was 0.72 (−0.02 to 1.46).

Table 2

Difference between the age, sex and worksites-adjusted observed incidence of health outcomes in 2020 and 2021, and the predicted incidence based on the data from 2016 to 2019

In 2021, the observed incidence for obesity, diabetes and hypertension was slightly lower than the predicted incidence; the difference in observed and predicted incidence rates (95% CI) was −0.23 (−0.63 to 0.17) for obesity, −0.08 (−0.30 to 0.14) for diabetes, and −0.25 (−0.66 to 0.16) for hypertension, respectively. For dyslipidaemia, the observed incidence was significantly lower than the predicted incidence (−1.06 (−1.97 to –0.14)). As for MetS, the observed incidence in 2021 was slightly higher than the predicted incidence in 2021 (0.09 (−0.45 to 0.63)).

Discussion

In a large occupational cohort in Japan, there was an excess in the incidence of cardiometabolic risk factors in the first year of the COVID-19 pandemic (2020), relative to the prepandemic period (FYs 2016 to 2019); the excess was diminished in 2021.

The present finding of an increased incidence of cardiometabolic risk factors in 2020 agrees with those of previous studies in Belgium (obesity),9 USA (diabetes, hypertension),14 California (diabetes)15 and South Korea (MetS),16 showing an increased incidence in 2020 compared with the prepandemic period (2019,9 2017 to 2019,14 2016 to 201915 16). In contrast, studies from Finland,10 Wales,11 Barcelona, Spain12 and Aragon, Spain13 reported a decrease in the incidence of diabetes,10–13 hypertension10–12 and dyslipidaemia10 13 in 2020 compared with 2019,10 13 2015 to 201911 and 2017 to 2019.12 The mixed results in previous studies may be due, at least in part, to the use of disease registries or hospital data, which reflect both real changes in disease incidence and use of healthcare services. The investigators who reported a reduction in cardiometabolic risk factors10–13 ascribed their findings to diagnostic delays resulting from limited access to healthcare services. In our study, we used data of periodic health check-ups which employees must receive under the Industrial Safety and Health Act in Japan; we thus were able to capture both diagnosed and undiagnosed cases. Most importantly, our study used health check-up data covering the entire Japanese FY (1 April 2020 to 31 March 2021), rather than just the initial few months of the pandemic, which helps to address concerns related to the short timeframe between the onset of the COVID-19 pandemic and the observed changes in cardiometabolic risk factors in 2020. Our results are also consistent with a Japanese study based on health check-ups for office workers17 showing an increase in the incidence of overweight and hypertension in 2020 compared with the prepandemic year (2019). With the use of health check-up data during the 4 years of the prepandemic period (2016 to 2019) to predict the incidence during the pandemic, the present study provides strong evidence supporting the worsening of cardiometabolic risk profile in the first year of the pandemic.

The increase in the incidence of obesity, diabetes, hypertension, and MetS in 2020 may reflect the deteriorated lifestyles due to COVID-19 pandemic and its associated restrictions on social activities. While Japan’s measures against infection prevention were not so strict as those in other countries, a state of emergency, which was initially declared from 7 April to 25 May 2020,25 promoted ‘The New Lifestyle’ for infection prevention, including promoting remote work, limiting gatherings and events, refraining from non-essential outings and encouraging social distancing in public spaces.26 27 Studies conducted in the early phase of the pandemic among the general28–30 and working population in Japan17 reported a decrease in physical activity and an increase in sedentary time, intake of sweets or snacks and eating between meals, all of which might have contributed to the increase in weight and visceral fat17 29 30—underlying condition for cardiometabolic abnormality. Therefore, we assumed that the pandemic conditions, characterised by substantial societal disruptions and uncertainties, may have exacerbated pre-existing vulnerabilities related to the onset of cardiometabolic risk factors, rather than the pandemic itself being the sole cause of the increased incidence.

In the second year of the epidemic (FY 2021), the incidence of cardiometabolic risk factors has returned to the prepandemic level. Some studies in the USA (diabetes,11 15 hypertension11) also showed a decline in the incidence of diabetes and hypertension during 2021, after showing a temporal increase of these diseases in 2020. Our finding of a lower incidence of obesity in 2021 (5.1%) than in 2020 (6.0%) is supported by a nationwide online survey in Japan, which reported a slight reduction in the prevalence of obesity from 2020 to 2021 (4.5% to 4.0% in male and 2.4% to 2.0% in female).31 However, our findings on dyslipidaemia (declined in 2021) contrast with a study based on the clinical database in Spain,13 showing an increase in the incidence from 11.0 per 100 000 population in 2020 to 18.3 per 100 000 population in 2021. The authors ascribed their findings to the large number of individuals with undiagnosed dyslipidaemia during the early period of the pandemic.13

Among the reasons for the return of the incidence of cardiometabolic risk factors in 2021 to the prepandemic level, the start of vaccine rollout is the most plausible. While large epidemic waves continued to attack Japan in 2021, mass vaccination combined with the relaxation of behavioural restrictions might have prompted people to return to normal daily life. Supporting this, a recent prospective study reported significantly increased physical activity, reduced smoking and alcohol intake, and increased fruit intake in 2021 compared with 2020 among white UK adults.32 Also, a study in Korea, which implemented a restriction policy similar to those in Japan,33 showed an increase in physical activity levels among younger adults (aged 19–39 years) in 2021 compared with 2020. This favourable change in lifestyle might have contributed to the improvement of the cardiometabolic risk profile in 2021 FY.

The strengths of the present study include prospective design, large sample size and the use of periodic check-up data from multiple companies. The present study also has several limitations that warrant mention. First, while we observed a temporal worsening of the cardiometabolic risk profile during the earlier period of the COVID-19 pandemic, this association may not be causal due to the observational nature of the study. Second, the assumption that the incidence trends of the outcomes we assessed from 2016 to 2019 would have persisted thereafter if COVID-19 had not occurred could not be tested. Third, our study lacked data on who contracted COVID-19, which could increase the risk of diabetes, hypertension and dyslipidaemia.34 35 Given that only 0.4% of Japan’s population had been infected as of 31 March 2021 (the end of the FY 2020) (https://www.mhlw.go.jp/stf/COVID-19/open-data.html), however, the effect of contracting COVID-19 on the present results is negligible. Fourth, we defined outcomes based on data measured at single time point, which is subject to random variation. The calculated incidence of each outcome might thus have overestimated the true incidence. Fifth, we were not able to estimate which lifestyle behaviours have influenced the onset of the outcome. Sixth, due to the lack of data on educational background, we were unable to assess the influence of this factor. Finally, since the study participants were predominantly male, full-time workers of large manufacturing companies, the present finding might not be applied to those in small and medium companies, those in other large companies with different backgrounds or non-working populations.

Conclusion

The incidence of cardiometabolic risk factors significantly increased in FY 2020 compared with the preceding 4 years, subsequently returning to prepandemic levels in 2021 FY. This study suggests that the initial phase of the COVID-19 pandemic, characterised by substantial societal disruptions and uncertainties, may have a negative impact on the incidence of cardiometabolic risk factors during the first year of the pandemic. However, the return to prepandemic levels in 2021 indicates that this impact may have been temporary or mitigated by adaptations over time. More research with extended monitoring is necessary to clarify the long-term effect of COVID-19 on cardiometabolic risk factors and to understand the dynamics of these changes over time.

Data availability statement

Data are available upon reasonable request. The data underlying this article will be shared on reasonable request to the corresponding author.

Ethics statementsPatient consent for publication

Not applicable.

Ethics approval

This study involves human participants and was approved by the Ethics Committee of the National Center for Global Health and Medicine, Japan (NCGM-S-001140). Participants gave informed consent to participate in the study before taking part.

Acknowledgments

The authors thank Toshiteru Okubo (Chairperson, Industrial Health Foundation) for scientific advice on conducting the J-ECOH study and Rika Osawa (National Center for Global Health and Medicine) for administrative support.