Abstract
Aim: The Fukushima Daiichi Nuclear Power Plant accident caused lifestyle changes and psychological distress in residents living near the plant. This study clarified the associations between changes in residents’ lifestyles and psychological factors with the onset of metabolic syndrome (METs) after the accident.
Methods: This longitudinal study included 10,373 residents who underwent the Comprehensive Health Check and Mental Health and Lifestyle Survey in Fiscal Year (FY) 2013. Follow-up surveys were conducted between FY 2014 and FY 2017. Lifestyle changes and the METs incidence were evaluated using a logistic regression model.
Results: METs developed in 14.0% of subjects. In addition to metabolic factors, such as the body mass index, hypertension, dyslipidemia, and diabetes mellitus, there were differences in physical activity, fast walking, eating fast, eating habits before bedtime, skipping breakfast, current smoking, and alcohol intake between subjects with and without new-onset METs. Eating fast, current smoking, and drinking alcohol were positively associated with new-onset METs, whereas starting physical activity and fast walking were inversely associated with new-onset METs.
Conclusions: Disaster-related lifestyle changes, such as eating fast, starting to smoke, and continued alcohol intake, were risk factors for new-onset METs after the Fukushima Daiichi Nuclear Power Plant accident.
Keywords: Metabolic syndrome, Lifestyle, Great East Japan Earthquake
Introduction
Triple disasters in the Great East Japan Earthquake and the associated tsunami and accident at the Fukushima Daiichi Nuclear Power Plant occurred in March 2011 along the Pacific coast of northern Japan. These disasters dramatically changed the lifestyles of residents around the Fukushima Daiichi Nuclear Power Plant and affected the prevalence of many diseases 1) .
The Fukushima Health Management Survey (FHMS) continues to monitor the residents who lived near the plant immediately after the disaster 2 , 3) . The Mental Health and Lifestyle Survey in FHMS has collected residents’ information about their mental status, in addition to their ordinary lifestyle, since the disaster. Based on the FHMS, we previously reported an increase in metabolic syndrome (METs) after the disaster and associations between various factors, such as age, smoking, alcohol intake, physical activity, post-traumatic disorder, and METs, in a cross-sectional study 4 , 5) .
Changes in lifestyles after the disaster are thought to be associated with an increased onset of METs in residents around the Fukushima Daiichi Nuclear Power Plant. However, there have been no reports on the association between new-onset METs and lifestyle and psychological factors immediately after the accident and subsequent changes. Therefore, the present study assessed the associations between lifestyle changes after the Fukushima Daiichi Nuclear Power Plant accident and the onset of METs.
Methods
Study Population
The participants in this study were Japanese men and women living in designated evacuation areas near the Fukushima Daiichi Nuclear Power Plant during the disaster: Tamura City, Minamisoma City, Kawamata-machi, Hirono-machi, Naraha-machi, Tomioka-machi, Kawauchi-mura, Okuma-machi, Futaba-machi, Namie-machi, Katsurao-mura, Iitate-mura, and Date City. In fiscal year (FY) 2013, 17,587 people 40-90 years old participated in both the Comprehensive Health Check and Mental Health and Lifestyle Survey of the FHMS. Both surveys were followed up between FY 2014 and FY 2017, with a mean follow-up of 3.2 years. A total of 7,214 participants were excluded, as follows: 2,173 who had been diagnosed with METs in FY 2013, 3,750 with no data for the METs diagnosis in FY 2013, and 1,291 with missing follow-up data between FY 2014 and FY 2017. Ultimately, 10,373 participants (3,635 men and 6,738 women) were eligible for the analysis ( Fig.1 ) .
Fig.1.
Flow chart of participant selection for this study
The FHMS, including the Comprehensive Health Check and Mental Health and Lifestyle Survey, has been conducted once every year since 2013. Because Comprehensive Health Checks in FHMS have been performed as general medical examinations but not as occupational health checkups, there were approximately twice as many women as men in this study. Participants with new-onset METs completed the follow-up at the time of new-onset METs in this study, while the latest data from between FY 2014 and FY 2017 were used for participants without new-onset METs.
The ethics committee of Fukushima Medical University approved this study protocol (#1319, 2020-239, 29064), and all participants provided their written informed consent.
Data Collection and Definition
Height (in stocking feet), weight (wearing light clothing), and blood pressure (BP) were measured for each participant by trained technicians, and the body mass index (BMI) was calculated as the body weight (kg) divided by the height in m2. Laboratory data were collected under overnight fasting conditions: aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyltransferase (γ-GT), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, triglycerides (TG), fasting plasma glucose (FPG), and hemoglobin A1c (HbA1c). METs was defined based on the Japanese diagnostic criteria for METs, as follows: visceral obesity (waist circumference ≥ 85 cm in men and ≥ 90 cm in women), in addition to the presence of at least 2 of the following risk factors: (1) dyslipidemia, TG ≥ 150 mg/dL and/or HDL-C ＜40 mg/dL, or treatment for dyslipidemia; (2) elevated BP, systolic BP ≥ 130 mmHg and/or diastolic BP ≥ 85 mmHg, or treatment with antihypertensive drugs; (3) hyperglycemia, FPG ≥ 110 mg/dL, or treatment for diabetes mellitus (if the participant was not fasting, HbA1c ＞5.6% was used instead). The status of participants’ mental health was evaluated using the Japanese versions of the Kessler 6-item scale (K6), and psychological distress was defined as corresponding to a K6 score ≥ 13 6) . In addition to the K6, participants’ various lifestyle factors, such as daily exercise, daily physical activity, eating fast, eating habits before bedtime, eating snacks after dinner, skipping breakfast, adequate sleep, current smoking, and alcohol intake, were assessed through self-report questionnaires. Each lifestyle factor was defined as follows: exercise, a habit of engaging in exercise with light perspiration for longer than 30 min per session, 2 times per week for more than 1 year; physical activity, walking or engaging in any equivalent amount of physical activity for more than 1 h per day; fast walking, a walking speed faster than the speed of other individuals of the same age and sex; eating fast, a quicker eating speed than the speed of others; eating habits before bedtime, eating dinner 2 h before bedtime more than three times per week; eating snacks after dinner, eating snacks after dinner more than three times per week, skipping breakfast more than three times per week, adequate sleep, sleeping well and enough, smoking status, current smoker, and alcohol intake, consuming any amount of alcohol compared to non-drinkers. Weight gain was defined as a weight gain of over 10 kg since reaching 20 years old.
Statistical Analyses
The characteristics of subjects who developed METs during the follow-up period (METs group) and those who did not (non-METs group) were compared using the unpaired t-test for continuous variables and the chi-squared test for categorical data. Odds ratios (ORs) and 95% confidence intervals (CIs) for METs onset after the accident were calculated with potential confounding factors using a logistic regression model. Based on previous studies, potential confounding factors were age, sex, weight gain, psychological distress, and lifestyle habits at baseline (daily exercise, daily physical activity, fast walking, eating fast, eating habits before bedtime, eating snacks after dinner, skipping breakfast, adequate sleep, current smoking, and alcohol intake). The statistical interactions of sex and body weight with lifestyle were also investigated for all participants using a multivariate-adjusted logistic regression analysis.
The SAS software program, version 9.4 (SAS Institute, Cary, NC, USA), was used for all analyses. All probability values for statistical tests were two-tailed, and p-values ＜0.05 were considered significant.
Results
Baseline Characteristics
Overall, 1,451 (14.0%) of 10,373 participants without METs in 2011-2013 developed METs during the 3.2-year follow-up period. METs developed more frequently in men (23.4%) than in women (8.9%). The mean BMI and BP were significantly higher in the METs group than in the non-METs group. In addition, there were significant differences in laboratory data, including FPG, HbA1c, HDL-C, and TG levels, between the METs and non-METs groups ( Table 1 ) .
Table 1. Baseline characteristics of participants.
| Number | All participants 10,373 | Incident METS 1,451 | Non-METS 8,922 | P value |
|---|---|---|---|---|
| Follow-up period (years) | 3.2 (1.1) | 2.1 (1.1) | 3.4 (1.0) | ＜0.01 |
| Sex, male/female | 3,635/6,738 | 853/598 | 2,782/6,140 | ＜0.01 |
| Age, years | 59.6 (7.9) | 60.4 (7.1) | 59.5 (8.0) | ＜0.01 |
| Body weight (Kg) | 57.3 (9.9) | 66.5 (9.1) | 55.8 (9.2) | ＜0.01 |
| Body mass index (kg/m2) | 23.2 (3.2) | 25.9 (2.9) | 22.7 (3.0) | ＜0.01 |
| SBP (mmHg) | 125.4 (15.1) | 130.1 (14.0) | 124.6 (15.1) | ＜0.01 |
| DBP (mmHg) | 75.3 (9.8) | 78.4 (9.4) | 74.7 (9.7) | ＜0.01 |
| TG (mg/dL) | 103.9 (60.6) | 129.7 (71.4) | 99.7 (57.6) | ＜0.01 |
| HDL-C (mg/dL) | 62.7 (15.2) | 55.7 (12.9) | 63.9 (15.3) | ＜0.01 |
| LDL-C (mg/dL) | 124.6 (30.5) | 124.6 (30.5) | 124.6 (30.5) | 0.998 |
| FPG (mg/dL) | 97.0 (14.4) | 104.1 (19.0) | 95.8 (13.2) | ＜0.01 |
| HbA1c (%) | 5.6 (0.5) | 5.8 (0.7) | 5.6 (0.5) | ＜0.01 |
| Hypertension (n, %) | 4,456 (43.1) | 929 (64.4) | 3,527 (39.7) | ＜0.01 |
| Dyslipidemia (n, %) | 5,728 (59.1) | 916 (67.8) | 4,812 (57.6) | ＜0.01 |
| Diabetes (n, %) | 786 (7.6) | 214 (14.8) | 572 (6.4) | ＜0.01 |
SBP; systolic blood pressure, DBP; diastolic blood pressure,TG; triglycerides, HDL-C; high-density lipoprotein cholesterol, LDL-C; low-density lipoprotein cholesterol, FPG; fasting plasma glucose, HbA1c; hemoglobin A1c
Changes in Lifestyle Characteristics
Table 2 shows a comparison of the changes in lifestyle characteristics. A total of 2,541 (24.7%) participants continued to gain body weight, and their frequency was significantly higher in participants with METs than in those without METs. There were significant differences in lifestyle changes, except daily exercise, eating snacks after dinner, and adequate sleep, between the METs and non-METs groups. There was no marked difference in changes in psychological distress between the groups.
Table 2. Comparison of lifestyle changes between participants with and without new-onset metabolic syndrome (METs).
| Baseline | After |
All participants (n = 10,373) |
MTES (n = 1,451) |
Non-METS (n = 8,922) |
p | |
|---|---|---|---|---|---|---|
| Bodyweight gain %, n | No | No | 61.1 (6,272) | 26.9 (387) | 66.6 (5,885) | ＜0.01 |
| Yes | No | 7.4 (756) | 9.1 (131) | 7.1 (625) | ||
| No | Yes | 6.8 (703) | 9.9 (142) | 6.3 (561) | ||
| Yes | Yes | 24.7 (2,541) | 54.0 (776) | 20.0 (1,765) | ||
| Exercise | No | No | 51.6 (5,301) | 52.3 (751) | 51.5 (4,550) | 0.14 |
| Yes | No | 10.3 (1,062) | 11.3 (163) | 10.2 (899) | ||
| No | Yes | 14.5 (1,491) | 12.7 (183) | 14.8 (1,308) | ||
| Yes | Yes | 23.6 (2,423) | 23.7 (340) | 23.6 (2,083) | ||
| Physical activity | No | No | 54.1 (5,557) | 53.3 (765) | 54.2 (4,792) | ＜0.01 |
| Yes | No | 12.5 (1,282) | 14.6 (210) | 12.1 (1,072) | ||
| No | Yes | 13.2 (1,359) | 10.6 (152) | 13.7 (1,207) | ||
| Yes | Yes | 20.2 (2,078) | 21.5 (309) | 20.0 (1,769) | ||
| Fast walking | No | No | 47.4 (4,864) | 49.4 (709) | 47.1 (4,155) | ＜0.01 |
| Yes | No | 10.5 (1,083) | 12.1 (174) | 10.3 (909) | ||
| No | Yes | 11.4 (1,175) | 8.9 (128) | 11.9 (1,047) | ||
| Yes | Yes | 30.6 (3,145) | 29.6 (425) | 30.8 (2,720) | ||
| Eating Fast | No | No | 64.2 (6,579) | 57.5 (821) | 65.3 (5,758) | ＜0.01 |
| Yes | No | 9.0 (922) | 9.3 (133) | 9.0 (789) | ||
| No | Yes | 8.0 (824) | 9.0 (129) | 7.9 (695) | ||
| Yes | Yes | 18.7 (1,917) | 24.2 (346) | 17.8 (1,571) | ||
| Eating habits before bedtime | No | No | 76.3 (7,841) | 71.5 (1,027) | 77.0 (6,814) | ＜0.01 |
| Yes | No | 9.2 (948) | 10.6 (153) | 9.0 (795) | ||
| No | Yes | 7.6 (783) | 9.0 (129) | 7.4 (654) | ||
| Yes | Yes | 6.9 (709) | 8.9 (128) | 6.6 (581) | ||
| Eating snack after dinner | No | No | 85.9 (8,831) | 86.6 (1,244) | 85.8 (7,587) | 0.90 |
| Yes | No | 5.6 (578) | 5.4 (77) | 5.7 (501) | ||
| No | Yes | 4.7 (478) | 4.4 (63) | 4.7 (415) | ||
| Yes | Yes | 3.8 (391) | 3.7 (53) | 3.8 (338) | ||
| Skipping breakfast | No | No | 91.4 (9,393) | 88.9 (1,277) | 91.8 (8,116) | ＜0.01 |
| Yes | No | 3.7 (378) | 5.3 (76) | 3.4 (302) | ||
| No | Yes | 2.7 (273) | 3.3 (47) | 2.6 (226) | ||
| Yes | Yes | 2.3 (235) | 2.5 (36) | 2.3 (199) | ||
| Adequate sleep | No | No | 23.4 (2,402) | 22.4 (322) | 23.5 (2,080) | 0.18 |
| Yes | No | 13.7 (1,409) | 12.7 (182) | 13.9 (1,227) | ||
| No | Yes | 14.1 (1,449) | 13.5 (194) | 14.2 (1,255) | ||
| Yes | Yes | 48.8 (5,012) | 51.4 (739) | 48.4 (4,273) | ||
| Current smoking | No | No | 87.8 (8,664) | 82.2 (1,138) | 88.7 (7,526) | ＜0.01 |
| Yes | No | 1.9 (189) | 3.5 (48) | 1.7 (141) | ||
| No | Yes | 0.4 (43) | 0.9 (12) | 0.4 (31) | ||
| Yes | Yes | 9.9 (977) | 13.4 (186) | 9.3 (791) | ||
| Alcohol intake | No | No | 75.2 (7,751) | 64.3 (926) | 76.9 (6,825) | ＜0.01 |
| Yes | No | 3.3 (340) | 3.9 (56) | 3.2 (284) | ||
| No | Yes | 3.3 (336) | 3.3 (47) | 3.3 (289) | ||
| Yes | Yes | 18.3 (1,885) | 28.6 (412) | 16.6 (1,473) | ||
| Psychological distress | No | No | 90.0 (5,953) | 89.3 (879) | 90.1 (5,074) | 0.22 |
| Yes | No | 5.5 (362) | 5.0 (49) | 5.6 (313) | ||
| No | Yes | 2.1 (136) | 2.3 (23) | 2.0 (113) | ||
| Yes | Yes | 2.5 (165) | 3.4 (33) | 2.3 (132) |
Risk Factors for METs Onset
Table 3 shows the age-, sex-, and multivariable-adjusted ORs and 95% CIs for METs onset. Weight gain was positively associated with METs onset in both men and women, and its continuation had the highest OR for METs onset (OR 6.70; 95% CI, 5.82-7.70). Although exercise was not associated with METs onset, starting physical activity (OR 0.79; 95% CI, 0.64-0.97) and fast walking (OR 0.68; 95% CI, 0.55-0.85) were inversely associated with METs onset. Conversely, continuation of eating fast (OR 1.28; 95% CI, 1.10-1.49) and alcohol intake (OR 1.18; 95% CI, 1.00-1.38) were positively associated with METs onset. Interestingly, quitting and starting smoking were both positively associated with METs onset in men (OR 1.58; 95% CI, 1.05-2.36) as well as women (OR 7.62; 95% CI, 2.17-26.72). In particular, starting to smoke in women showed the highest OR for METs onset. It was also confirmed that the OR of starting smoking for METs onset was slightly higher in non-smokers at baseline than in ex-smokers at baseline (9.4 vs. 7.2) ( Supplementary Table 1 ) . Starting to skip breakfast was associated with METs onset in men (OR 1.68; 95% CI, 1.08-2.62). Continued psychological distress had a relatively high OR (OR 1.36; 95% CI, 0.88-2.08) for METs onset, but it was not significant. Sex differences were significant in the analyses using the interaction terms (sex×body weight gain, sex×exercise, sex×physical activities, sex×skipping breakfast). Regarding the association between lifestyle changes and each component of METs, continued body weight gain and smoking were positively associated with dyslipidemia ( Supplementary Table 2 ) , whereas continued or starting exercise was inversely associated with dyslipidemia. Starting to eat fast and continued psychological distress were positively associated with hyperglycemia. While continued body weight gain, inadequate sleep and alcohol intake were positively associated with hypertension, continued smoking was inversely associated with it.
Table 3. Multivariable-adjusted odds ratios and 95% confidence intervals of new-onset METs for changes in lifestyle factors among participants without METs at baseline.
| Baseline | After |
All participants (n = 10,373) |
Men (n = 3,635) |
Women (n = 6,738) |
P for interaction of sex | |
|---|---|---|---|---|---|---|
| age | 1.02 (1.02-1.03) ＊ | 1.01 (1.00-1.03)＊ | 1.03 (1.02-1.04)＊ | - | ||
| Sex (men) | 2.69 (2.34-3.10) ＊ | - | - | - | ||
| Bodyweight gain | ＜0.01 | |||||
| No | No | Ref | ||||
| Yes | No | 2.89 (2.32-3.60)＊ | 2.57 (1.94-3.40)＊ | 3.38 (2.33-4.89)＊ | ||
| No | Yes | 3.72 (2.99-4.62)＊ | 3.20 (2.39-4.27)＊ | 4.65 (3.31-6.54)＊ | ||
| Yes | Yes | 6.70 (5.82-7.70)＊ | 4.45 (3.69-5.38)＊ | 10.82 (8.71-13.45)＊ | ||
| Exercise | 0.02 | |||||
| No | No | Ref | ||||
| Yes | No | 1.06 (0.86-1.30) | 1.17 (0.88-1.55) | 0.94 (0.69-1.28) | ||
| No | Yes | 0.90 (0.74-1.10) | 1.02 (0.78-1.33) | 0.78 (0.59-1.05) | ||
| Yes | Yes | 0.96 (0.80-1.15) | 1.04 (0.81-1.32) | 0.86 (0.66-1.13) | ||
| Physical activity | ＜0.01 | |||||
| No | No | Ref | ||||
| Yes | No | 1.10(0.91-1.34) | 1.04 (0.80-1.35) | 1.20 (0.91-1.59) | ||
| No | Yes | 0.79 (0.64-0.97)＊ | 0.84 (0.64-1.10) | 0.75 (0.54-1.02) | ||
| Yes | Yes | 1.04 (0.87-1.26) | 1.16 (0.91-1.48) | 0.84 (0.62-1.13) | ||
| Fast walking | 0.22 | |||||
| No | No | Ref | ||||
| Yes | No | 0.99 (0.81-1.21) | 0.95 (0.73-1.23) | 1.06 (0.79-1.42) | ||
| No | Yes | 0.68 (0.55-0.85)＊ | 0.65 (0.48-0.87)＊ | 0.75 (0.55-1.03) | ||
| Yes | Yes | 0.86 (0.74-1.00) | 0.90 (0.74-1.10) | 0.84 (0.67-1.06) | ||
| Eating fast | 0.23 | |||||
| No | No | Ref | ||||
| Yes | No | 1.02 (0.83-1.27) | 0.93 (0.69-1.25) | 1.13 (0.83-1.55) | ||
| No | Yes | 1.11 (0.89-1.38) | 1.06 (0.79-1.43) | 1.16 (0.84-1.61) | ||
| Yes | Yes | 1.28 (1.10-1.49)＊ | 1.22 (0.99-1.50) | 1.34 (1.06-1.67)＊ | ||
| Eating habits before bedtime | 0.13 | |||||
| No | No | Ref | ||||
| Yes | No | 0.99 (0.81-1.21) | 0.96 (0.74-1.24) | 1.05 (0.76-1.45) | ||
| No | Yes | 1.02 (0.82-1.27) | 1.00 (0.74-1.33) | 1.00 (0.72-1.38) | ||
| Yes | Yes | 0.96 (0.77-1.21) | 0.85 (0.65-1.12) | 1.31 (0.90-1.92) | ||
| skipping breakfast | 0.048 | |||||
| No | No | Ref | ||||
| Yes | No | 1.25 (0.94-1.66) | 1.40 (0.97-2.03) | 1.16 (0.74-1.83) | ||
| No | Yes | 1.22 (0.86-1.72) | 1.68 (1.08-2.62)＊ | 0.68 (0.38-1.23) | ||
| Yes | Yes | 0.95 (0.64-1.41) | 1.14 (0.70-1.84) | 0.60 (0.29-1.23) | ||
| adequate sleep | 0.23 | |||||
| No | No | Ref | ||||
| Yes | No | 0.85 (0.69-1.05) | 0.87 (0.65-1.17) | 0.87 (0.64-1.17) | ||
| No | Yes | 1.01 (0.82-1.25) | 1.21 (0.90-1.62) | 0.85 (0.63-1.15) | ||
| Yes | Yes | 1.06 (0.90-1.24) | 1.13 (0.90-1.41) | 1.01 (0.80-1.26) | ||
| current smoking | 0.12 | |||||
| No | No | Ref | ||||
| Yes | No | 1.57 (1.08-2.26)＊ | 1.58 (1.05-2.36)＊ | 1.10 (0.44-2.72) | ||
| No | Yes | 2.20 (1.04-4.67)＊ | 1.35 (0.54-3.38) | 7.62 (2.17-26.72)＊ | ||
| Yes | Yes | 1.09 (0.89-1.32) | 0.97 (0.78-1.20) | 1.56 (0.99-2.45) | ||
| alcohol intake | 0.23 | |||||
| No | No | Ref | ||||
| Yes | No | 0.88 (0.64-1.22) | 0.94 (0.66-1.35) | 0.77 (0.37-1.58) | ||
| No | Yes | 0.89 (0.63-1.25) | 0.98 (0.65-1.46) | 0.69 (0.36-1.35) | ||
| Yes | Yes | 1.18 (1.00-1.38)＊ | 1.25 (1.05-1.49)＊ | 0.96 (0.63-1.45) | ||
| psychological distress | 0.98 | |||||
| No | No | Ref | ||||
| Yes | No | 0.89 (0.63-1.24) | 1.03 (0.64-1.66) | 0.77 (0.47-1.24) | ||
| No | Yes | 1.20 (0.73-1.98) | 1.12 (0.55-2.27) | 1.24 (0.61-2.50) | ||
| Yes | Yes | 1.36 (0.88-2.08) | 1.40 (0.78-2.49) | 1.26 (0.66-2.39) |
＊p＜0.05 METs, metabolic syndrome; [please define all abbreviations used]
Supplementary Table 1. Multivariable-adjusted odds ratios and 95% confidence intervals of new-onset METs for changes in lifestyle factors among participants without METS at baseline (sensitivity analysis using detail smoking status).
| Baseline | After |
All participants (n = 10,373) |
Men (n = 3,635) |
Women (n = 6,738) |
|
|---|---|---|---|---|---|
| age | 1.02 (1.02-1.03)＊ | 1.01 (1.00-1.03)＊ | 1.03 (1.02-1.04)＊ | ||
| Sex (men) | 2.50 (2.12-2.94)＊ | - | - | ||
| Bodyweight gain | |||||
| No | No | Ref | |||
| Yes | No | 2.88 (2.31-3.59)＊ | 2.56 (1.93-3.39)＊ | 3.36 (2.32-4.87)＊ | |
| No | Yes | 3.70 (2.97-4.60)＊ | 3.16 (2.37-4.23)＊ | 4.65 (3.31-6.54)＊ | |
| Yes | Yes | 6.67 (5.80-7.67)＊ | 4.41 (3.65-5.33)＊ | 10.80 (8.69-13.42)＊ | |
| Exercise | |||||
| No | No | Ref | |||
| Yes | No | 1.06 (0.86-1.30) | 1.17 (0.88-1.56) | 0.94 (0.69-1.29) | |
| No | Yes | 0.90 (0.74-1.09) | 1.02 (0.78-1.33) | 0.78 (0.58-1.04) | |
| Yes | Yes | 0.96 (0.80-1.15) | 1.04 (0.81-1.32) | 0.86 (0.65-1.12) | |
| Physical activity | |||||
| No | No | Ref | |||
| Yes | No | 1.11 (0.92-1.34) | 1.05 (0.81-1.36) | 1.21 (0.92-1.61) | |
| No | Yes | 0.79 (0.64-0.97)＊ | 0.84 (0.63-1.10) | 0.75 (0.54-1.03) | |
| Yes | Yes | 1.05 (0.87-1.26) | 1.17 (0.92-1.48) | 0.84 (0.62-1.14) | |
| Fast walking | |||||
| No | No | Ref | |||
| Yes | No | 0.99 (0.81-1.21) | 0.95 (0.73-1.24) | 1.06 (0.78-1.42) | |
| No | Yes | 0.68 (0.55-0.85)＊ | 0.65 (0.48-0.87)＊ | 0.75 (0.54-1.03) | |
| Yes | Yes | 0.86 (0.74-1.00) | 0.90 (0.74-1.10) | 0.84 (0.67-1.06) | |
| Eating fast | |||||
| No | No | Ref | |||
| Yes | No | 1.02 (0.82-1.26) | 0.94 (0.70-1.26) | 1.13 (0.83-1.54) | |
| No | Yes | 1.11 (0.89-1.38) | 1.05 (0.78-1.42) | 1.17 (0.85-1.61) | |
| Yes | Yes | 1.28 (1.09-1.49)＊ | 1.23 (1.00-1.51) | 1.33 (1.06-1.67)＊ | |
| Eating habits before bedtime | |||||
| No | No | Ref | |||
| Yes | No | 0.99 (0.81-1.22) | 0.96 (0.74-1.25) | 1.04 (0.75-1.44) | |
| No | Yes | 1.02 (0.82-1.26) | 0.99 (0.74-1.33) | 0.99 (0.72-1.38) | |
| Yes | Yes | 0.97 (0.77-1.21) | 0.85 (0.65-1.12) | 1.31 (0.90-1.92) | |
| skipping breakfast | |||||
| No | No | Ref | |||
| Yes | No | 1.24 (0.93-1.65) | 1.39 (0.96-2.02) | 1.15 (0.73-1.81) | |
| No | Yes | 1.20 (0.85-1.70) | 1.67 (1.07-2.60)＊ | 0.68 (0.37-1.22) | |
| Yes | Yes | 0.94 (0.64-1.40) | 1.13 (0.69-1.83) | 0.60 (0.29-1.22) | |
| adequate sleep | |||||
| No | No | Ref | |||
| Yes | No | 0.85 (0.69-1.05) | 0.86 (0.64-1.16) | 0.87 (0.64-1.17) | |
| No | Yes | 1.02 (0.83-1.25) | 1.21 (0.90-1.62) | 0.85 (0.63-1.15) | |
| Yes | Yes | 1.06 (0.90-1.24) | 1.12 (0.90-1.41) | 1.01 (0.80-1.26) | |
| current smoking | |||||
| No | No | Ref | |||
| non-smokers | non-smokers | ||||
| No | No | ||||
| ex-smokers | ex-smokers | 1.18 (0.99-1.42) | 1.19 (0.96-1.46) | 1.29 (0.82-2.01) | |
| Yes | No | 1.74 (1.17-2.57)＊ | 1.83 (1.19-2.81)＊ | 0.91 (0.31-2.72) | |
| No | Yes | 4.64 (0.69-31.13) | 2.87 (0.17-49.89) | 9.44 (0.92-96.76) | |
| non-smokers | |||||
| No | Yes | ||||
| ex-smokers | 2.15 (0.95-4.86) | 1.42 (0.53-3.82) | 7.19 (1.66-31.12)＊ | ||
| Yes | Yes | 1.19 (0.96-1.49) | 1.10 (0.85-1.42) | 1.58 (1.00-2.49)＊ | |
| alcohol intake | |||||
| No | No | Ref | |||
| Yes | No | 0.87 (0.63-1.20) | 0.92 (0.64-1.32) | 0.74 (0.36-1.53) | |
| No | Yes | 0.88 (0.62-1.24) | 0.97 (0.65-1.45) | 0.69 (0.36-1.36) | |
| Yes | Yes | 1.15 (0.98-1.35) | 1.22 (1.02-1.45)＊ | 0.94 (0.62-1.42) | |
| psychological distress | |||||
| No | No | Ref | |||
| Yes | No | 0.89 (0.64-1.24) | 1.03 (0.64-1.66) | 0.77 (0.47-1.25) | |
| No | Yes | 1.20 (0.73-1.97) | 1.12 (0.55-2.26) | 1.24 (0.61-2.51) | |
| Yes | Yes | 1.36 (0.89-2.08) | 1.40 (0.79-2.51) | 1.26 (0.66-2.39) | |
＊p＜0.05 METs, metabolic syndrome; [please define all abbreviations used]
Supplementary Table 2. Associations between lifestyle changes and each component of METs among participants (n = 10,373) at baseline .
| Baseline | After | Hyperglycemia | Hypertension | Dyslipidemia | |
|---|---|---|---|---|---|
| age | 1.04 (1.03-1.05)＊ | 1.07 (1.07-1.08)＊ | 1.01 (1.00-1.01) | ||
| Sex (men) | 1.64 (1.44-1.86)＊ | 1.20 (1.08-1.33)＊ | 1.80 (1.60-2.03)＊ | ||
| Bodyweight gain | No | No | Ref | ||
| Yes | No | 1.27 (1.04-1.55)＊ | 1.51 (1.28-1.78)＊ | 1.69 (1.40-2.04)＊ | |
| No | Yes | 1.20 (0.97-1.48) | 1.53 (1.28-1.81)＊ | 1.81 (1.49-2.19)＊ | |
| Yes | Yes | 1.46 (1.29-1.66) | 2.46 (2.20-2.74)＊ | 2.67 (2.38-2.99)＊ | |
| Exercise | No | No | Ref | ||
| Yes | No | 1.13 (0.94-1.35) | 1.03 (0.88-1.20) | 0.98 (0.82-1.17) | |
| No | Yes | 1.00 (0.85-1.19) | 0.92 (0.81-1.05) | 0.82 (0.70-0.96) ＊ | |
| Yes | Yes | 1.13 (0.97-1.32) | 1.03 (0.91-1.17) | 0.84 (0.72-0.97) ＊ | |
| Physical activity | No | No | Ref | ||
| Yes | No | 1.10 (0.93-1.31) | 0.99 (0.86-1.13) | 1.05 (0.90-1.24) | |
| No | Yes | 0.99 (0.84-1.18) | 0.94 (0.82-1.08) | 0.94 (0.80-1.11) | |
| Yes | Yes | 1.07 (0.91-1.26) | 1.05 (0.92-1.19) | 1.01 (0.86-1.18) | |
| Fast walking | No | No | Ref | ||
| Yes | No | 1.06 (0.89-1.26) | 1.02 (0.88-1.18) | 0.85 (0.72-1.02) | |
| No | Yes | 0.88 (0.73-1.05) | 0.94 (0.82-1.08) | 0.90 (0.76-1.07) | |
| Yes | Yes | 0.90 (0.79-1.03) | 0.90 (0.81-1.00) | 0.96 (0.85-1.09) | |
| Eating fast | No | No | Ref | ||
| Yes | No | 1.09 (0.90-1.32) | 0.91 (0.78-1.06) | 1.10 (0.92-1.31) | |
| No | Yes | 1.26 (1.04-1.52)＊ | 1.07 (0.91-1.26) | 1.14 (0.95-1.37) | |
| Yes | Yes | 1.14 (0.99-1.32) | 1.11 (0.99-1.25) | 1.03 (0.90-1.18) | |
| Eating habits before bedtime | No | No | Ref | ||
| Yes | No | 0.92 (0.76-1.11) | 1.23 (1.05-1.43)＊ | 1.08 (0.91-1.28) | |
| No | Yes | 1.16 (0.96-1.40) | 1.15 (0.98-1.36) | 0.97 (0.80-1.17) | |
| Yes | Yes | 1.06 (0.87-1.30) | 1.16 (0.97-1.39) | 0.99 (0.82-1.21) | |
| skipping breakfast | No | No | Ref | ||
| Yes | No | 0.95 (0.71-1.27) | 0.83 (0.66-1.04) | 1.23 (0.97-1.58) | |
| No | Yes | 1.02 (0.73-1.42) | 0.87 (0.67-1.14) | 0.87 (0.64-1.20) | |
| Yes | Yes | 0.95 (0.65-1.38) | 1.04 (0.78-1.39) | 0.97 (0.70-1.34) | |
| adequate sleep | No | No | Ref | ||
| Yes | No | 0.99 (0.82-1.19) | 0.93 (0.81-1.07) | 1.00 (0.84-1.19) | |
| No | Yes | 0.95 (0.79-1.14) | 1.13 (0.98-1.30) | 0.98 (0.83-1.17) | |
| Yes | Yes | 1.13 (0.98-1.31) | 1.13 (1.02-1.26)＊ | 1.00 (0.88-1.14) | |
| current smoking | No | No | Ref | ||
| Yes | No | 1.40 (0.99-1.99) | 1.17 (0.84-1.63) | 1.62 (1.17-2.24)＊ | |
| No | Yes | 1.46 (0.70-3.03) | 0.97 (0.50-1.90) | 1.36 (0.67-2.78) | |
| Yes | Yes | 0.98 (0.81-1.18) | 0.79 (0.68-0.92) ＊ | 1.54 (1.31-1.82)＊ | |
| alcohol intake | No | No | Ref | ||
| Yes | No | 0.88 (0.65-1.19) | 1.02 (0.80-1.29) | 0.73 (0.55-0.98)＊ | |
| No | Yes | 0.97 (0.72-1.32) | 1.22 (0.96-1.55) | 0.55 (0.40-0.76)＊ | |
| Yes | Yes | 0.95 (0.82-1.10) | 1.54 (1.35-1.76) ＊ | 0.90 (0.78-1.03) | |
| psychological distress | No | No | Ref | ||
| Yes | No | 0.98 (0.73-1.32) | 0.98 (0.78-1.24) | 0.94 (0.71-1.24) | |
| No | Yes | 0.95 (0.59-1.53) | 1.19 (0.81-1.74) | 0.98 (0.63-1.52) | |
| Yes | Yes | 1.61 (1.10-2.36)＊ | 0.84 (0.60-1.18) | 1.30 (0.90-1.88) |
＊p＜0.05
METs, metabolic syndrome
Discussion
Disaster-related factors were associated with METs after the Fukushima Daiichi Nuclear Power Plant accident 4) . A previous report focused on METs near the time after the disaster, and long-term associations between new-onset METs and lifestyle changes following the disaster were examined in the present study. Participants with new-onset METs had different lifestyles until METs onset from those without new-onset METs, and continuation or changes in lifestyle, such as physical activity, fast walking, eating fast, eating habits before bedtime, skipping breakfast, current smoking, and alcohol intake, in addition to weight gain, were associated with METs onset. This longitudinal study is the first to identify lifestyle risk factors for new-onset METs after the Fukushima Daiichi Nuclear Power Plant accident.
Smoking increases the risk of METs owing to increased insulin resistance and central fat accumulation 7) . This risk was confirmed in women in the present study. In contrast, smoking cessation was positively associated with new-onset METs in men. This can be explained by the evidence that nicotine increases energy expenditure and reduces appetite 8) . METs was more prevalent in ex-smokers than in smokers in a three-year follow-up study 9) . However, a longer smoking cessation period reduced the risk of METs onset 10) . Therefore, maintaining smoking cessation and not smoking to begin with are essential for preventing METs onset after a disaster.
In addition to increasing physical activity, starting fast walking is a preventive factor against the onset of MET. Interestingly, fast walking is also a preventive factor against new-onset diabetes mellitus 11) . A faster walking pace was associated with participation in high-intensity physical activity, higher exercise frequency, and total walking volume 12) . These findings support the association between fast walking and METs onset in the present study.
Continuation of eating fast and skipping breakfast was positively associated with METs onset in the present study. These associations between each habit and METs are in accordance with previous studies 13 - 15) . Furthermore, intensive health guidance focusing on eating quickly was effective for improving METs 16) . Therefore, improvements in these eating habits may be promising for preventing METs onset. Moreover, continued alcohol intake was positively associated with the onset of MET. Heavy but not light alcohol consumption is known to increase the risk of METs 17) . Although alcohol consumption was not evaluated in the present study, the amount of alcohol intake should be considered for prevention of METs onset after a disaster.
There were sex differences in lifestyle factors associated with METs onset in this study. Among the risk factors evaluated in the present study, there were significant interactions between sex and body weight gain, exercise, physical activity, and skipping breakfast. This finding suggests that lifestyle interventions to prevent the onset of METs should consider sex differences. However, skipping breakfast was associated with an unexpectedly low OR for METs onset in women. Detailed meal data are required to determine the reasons for this.
The association between depressive status and METs onset was inconsistent in previous studies 18) . We previously showed the association between post-traumatic distress and METs after a disaster in a cross-sectional study 4) . Continuation of psychological distress had a higher OR for METs onset, but this association was not significant, possibly due to the gradual decrease in the frequency of psychological distress after the disaster 19) . Conversely, we previously reported the causal association of new-onset diabetes after a disaster and psychological burden 20) . In addition, the K6 score after a disaster has been shown to be associated with dietary pattern and activities of daily living 19 , 21) . Although the association between psychological distress and METs onset remains uncertain, care for psychological distress after a disaster is important to prevent new-onset METs.
The present study showed that continuation (“yes to yes”) of unhealthy factors, such as body weight gain, eating fast, and alcohol intake, are positively associated with the onset of METs. As described above, these three factors are risk factors for METs but not disaster-specific factors. However, previous studies 4 , 22) in the relatively short term after the disaster showed that disaster-related factors, such as evacuation or post-traumatic distress were positively associated with METs. The results of this study may indicate that general risk factors for METs are more influential for METs onset in long-term observation after a disaster than disaster-specific factors. However, we previously confirmed that the increase in the BMI and new alcohol consumption after the disaster were affected by disaster-specific factors, such as evaluation or psychological distress 23 , 24) . Therefore, general risk factors for METs are expected to also be disaster-related factors in evacuees from a broad perspective.
Limitations
The strengths of this study include its large sample size and longitudinal design. Furthermore, the onset of METs was evaluated with a focus on lifestyle changes. However, this study had some limitations. First, the underlying mechanism of METs onset could not be evaluated because the daily food intake and calorie consumption were uncertain. Second, factors other than the disaster that affected lifestyle and psychological burden could not be evaluated in detail. Some participants may have received lifestyle interventions after the disaster. In fact, ‘the mental health support team’ in FHMS provides efficient intervention for people at a high risk of psychological burden and lifestyle-related diseases 19) . A multifaceted evaluation of lifestyle after a disaster may help prevent METs onset. Third, psychological distress was selected as a potential confounding factor. However, one cannot deny the possibility that psychological distress causes METs through undesirable changes in lifestyle habits, such as alcohol intake, smoking, and lack of sleep. However, a previous study found a positive association between METs and psychological distress after adjusting for smoking and alcohol intake 25) . Whether or not psychological distress after a disaster causes METs is a critical issue that needs to be examined further in future studies.
Conclusions
Changes in lifestyle, such as physical activity, fast walking, eating fast, eating habits before bedtime, skipping breakfast, current smoking, and alcohol intake, were associated with new-onset METs after a disaster. Regular lifestyle monitoring and adequate interventions are important to prevent METs onset.
Acknowledgements
The authors thank the staff of the Fukushima Health Management Survey for their cooperation. The findings and conclusions of this article are solely the responsibility of the authors and do not represent the official views of the Fukushima Prefectural Government. All the authors participated in the conception and design of the study. A. Takahashi, T. Ohira, F. Hayashi, and S. Sato performed statistical analysis of the data and wrote the manuscript. All authors participated in the interpretation of the results and drafting of the manuscript, and approved the final version.
Conflict of Interest
All authors have no financial disclosures.
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