Abstract
Background
This study attempted to clarify the relationship between HL and starting and/or maintaining physical activity in the working generation through a one-year follow-up study of a large company’s employees.
Methods
Participants included 6060 employees aged 18–64 in a company in rural Japan. In 2019, health literacy was evaluated using the Japanese version of the HLS-EU-47. Data on leisure-time exercise habits and daily physical activity were obtained from the company’s 2019 and 2020 records. Based on combined responses from both years, participants were divided into four groups: remaining active, remaining inactive, changing from active to inactive, and changing from inactive to active. Multinomial logistic regression analysis assessed associations between health literacy and changes in leisure-time exercise and daily physical activity.
Results
At baseline, participants with physical exercise habits constituted 18.6%, and 39.9% engaged in physical activity daily for over an hour. Only 14.1% of all participants exercised in both 2019 and 2020, and 74.6% remained without exercise. The percentage remaining physically active daily was 29.1%, and 49.4% remained inactive. The proportion who remained active, doing leisure-time exercise and being physically active, was higher in the higher health literacy group than in the lower group. Compared to the lower health literacy group, the higher group tended to change physical activity status in both directions, from active to inactive and from inactive to active.
Conclusions
HL was associated with continuing and starting exercise and being active daily. Therefore, it was suggested that improving HL effectively improves physical activity among the working population.
Keywords: Employees, Epidemiology, Health literacy, Physical activity, Exercise
Background
Inactivity increases the risk of overall mortality and the incidence of cardiovascular disease, cancer, and diabetes mellitus [1–4]. In contrast, higher levels of total physical activity and less sedentary time reduced the risk of all-cause mortality [5]. Therefore, the World Health Organization (WHO) has published guidelines with goals of reducing the number of people classified inactive by 10% by 2025 and by 15% by 2030 [6] through the four strategies of creating active societies, environments, people, and systems.
However, nearly a third of adults globally do not meet the recommended level of physical activity [7]. Even so, the proportion of people engaging in physical activity has been reported as particularly high in high-income Asian countries. In Japan, for instance, Health Japan 21 (2nd phase) was launched in 2013, and improvement targets were set for the number of steps per day, the percentage of people with exercise habits, and awareness-raising and environmental improvements for local and workplace areas [8, 9]. The final assessment in 2023, however, showed no improvement and even some deterioration in most areas of physical activity. Furthermore, the situation is worsening, particularly for working people [10].
Many studies have reported factors determining physical activity. As for environmental factors, associations between social and physical environments (e.g., urban planning, transportation systems, parks and trails, physical activity) have been reported [11]. Sallis et al. [12] found that neighborhood walkability, assessed by residential density, intersection density, public transport density, and number of parks, were related to residents’ daily physical activity. In the work setting, occupational category, job strain, working hours, and overtime were associated with leisure-time physical activity [13].
The personal factors of age, gender, health status, self-efficacy, and motivation are also associated with physical activity [11]. A positive correlation between health literacy (HL)— “cognitive and social skills that determine an individual’s willingness and ability to access, understand, and use information to promote and maintain good health” [14] and physical activity has also been reported [15–20]. Having an observed association with health behavior [16, 21, 22], HL also has a positive association with readiness for exercise [23]. However, most studies have been cross-sectional, with few follow-up studies. To the best of our knowledge, no follow-up studies have been conducted on the relationship between HL and physical activity among working-age people.
Therefore, this study attempted to clarify the relationship between HL and starting and/or maintaining physical activity in the working generation.
Methods
Study design
In conducting a follow-up study for large company employees, we evaluated a one-year change in physical exercise and daily physical activity.
Target population and survey methods
The target population was all employees (n = 8,215) in a light metal product manufacturing company in Japan. The target company had an “average” ranking for occupational health and safety. In January 2020, we surveyed job characteristics, subjective health status (i.e., very good, good, fair, not good, bad), health habits, and HL using a self-administered questionnaire. HL was evaluated using the Japanese version of the HLS-EU-47 [24]. For data on leisure-time exercise and daily physical activity in 2019 and 2020, we used a self-administered questionnaire survey of life habits carried out in the annual health check-ups conducted by the company. A self-administered standard questionnaire developed by the Ministry of Health, Labor and Welfare was used for data on physical activity. It is used in health checkups conducted by law across Japan to achieve the goals of Health Japan 21. The questionnaire items are “Are you in a habit of doing exercise to sweat lightly for over 30 minutes a time, 2 times weekly, for over a year?” for leisure-time exercise and “In your daily life, do you walk or do any equivalent amount of physical activity for more than one hour a day?” for daily physical activity. These data were combined for analysis.
Regarding personal attributes, we asked about educational history (junior high school, high school, vocational school, junior college/technical college, university, or graduate school) and marital status (married, single, divorced, or widowed). Regarding occupational factors, we asked about job type (management, clerical work, sales, transport, and production) and working hours.
The European Health Literacy Survey (HLS-EU) adapted for Japanese administration (HLS-EU-47) [24] was used for evaluating HL. It comprises 47 items in three domains (i.e., health care, disease prevention, and health promotion) and four competencies (i.e., obtaining, understanding, evaluating, and using health information). Possible scores range from 0 to 50 points; the higher the score, the higher the HL.
We received survey responses from 6,962 individuals (response rate, 84.7%). Of these respondents, 6,880 were 18–64 years old. Among them, 414 lacked baseline characteristics (HL, marital status, education, job, working hours), and 406 lacked one or both types of physical activity data. Therefore, 6,060 workers (4,153 male; 1,907 female) were included in the final analysis (Fig. 1).
Fig. 1.
Flow diagram of the study
Analytical methods
The HL score was divided into four groups according to the European Health Literacy Project 2009–2012 [25]: 0–25 points = inadequate; 26–33 = problematic; 34–42 = sufficient; and 43–50 = excellent. Baseline sociodemographic characteristics were categorized as follows: educational attainment (lower than university education/university education or higher); marital status (married/single [single, divorced, widowed]); job (office work [management, clerical, sales]/industrial work [production process, transport]); working hours per week (≤ 48 h/>48 h); and health status (good [very good, good]/fair/poor [not good, bad]). HL was compared between groups of baseline characteristics using a t-test or analysis of variance. Distribution of leisure-time exercise and daily physical activity at the baseline was compared between groups of baseline characteristics using the χ2 test.
Based on a combination of responses about physical activity from both 2019 and 2020, participants were divided into four groups: maintaining active (yes/yes), maintaining inactive (no/no), changing from inactive to active (no/yes) and changing from active to inactive (yes/no). Using the χ2 test, the distribution of combinations of leisure-time exercise and daily physical activity status was compared between the two HL groups: “inadequate or problematic” and “sufficient or excellent.” To assess associations between HL and changes in physical activity, multinomial logistic regression analysis was employed because the dependent variables had four outcomes (yes/yes, no/yes, yes/no, and no/no). The base outcome was “no/no” group. The independent variables were age and sex in model 1 and age, sex, marital status, educational attainment, job, work hours, and subjective health status in model 2.
All statistical analyses were performed using the Statistical Package for the Social Sciences (version 27, IBM). The level of statistical significance was set at p = 0.05 with a two-sided or 95% confidence interval (CI) of odds ratio that did not cross 1.00.
Results
Participants’ demographic characteristics are summarized in Table 1. Their mean age was 40.9 [SD = 12.6] years. Of the 6,060 participants, 62.7% were married, 30.8% had a college degree or higher education, 51.9% were office workers, 14.0% worked more than 48 h per week, and 12.1% had “not good, bad” health status. In Table 2, the HL means were assigned according to groups of baseline characteristics. All participants’ mean HL was 26.4 (SD = 7.5). Participants 40–64 years old, married, working more than 48 h per week, and in poor health tended to have lower HL.
Table 1.
Baseline characteristics of study subjects
| Characteristics | n = 6060 | |
|---|---|---|
| Age, years, mean ± SD | 40.9 ± 12.6 | |
| Men, n (%) | 4,153 (68.5) | |
| Married, n (%) | 3,797 (62.7) | |
| College degree or higher, n (%) | 1,868 (30.8) | |
| Job, n (%) | Office work | 3,146 (51.9) |
| Industrial work | 2,914 (48.1) | |
| Working hours, n (%) | > 48 h/week | 847 (14.0) |
| Subjective health status, n (%) | Very good, good | 1,562 (25.8) |
| Fair | 3,763 (62.1) | |
| Poor, very poor | 735 (12.1) |
SD Standard deviation, n number
Table 2.
Health literacy by baseline characteristics
| Number | HL | p | ||
|---|---|---|---|---|
| Overall | 6,060 | 26.4 ± 7.5 | ||
| Age | 18–39 years | 2,753 | 27.2 ± 7.7 | < 0.001 |
| 40–64 years | 3,307 | 25.6 ± 7.3 | ||
| Gender | Men | 4,153 | 26.4 ± 7.7 | 0.962 |
| Women | 1,907 | 26.4 ± 7.0 | ||
| Marital status | Single/bereaved | 2,263 | 26.6 ± 7.9 | 0.032 |
| Married | 3,797 | 26.2 ± 7.2 | ||
| Educational attainment | High school | 3,109 | 26.4 ± 7.6 | 0.639 |
| Vocational | 1,083 | 26.3 ± 7.4 | ||
| College degree or higher | 1,868 | 26.3 ± 7.4 | ||
| Job | Office work | 3,146 | 26.3 ± 7.2 | 0.253 |
| Industrial work | 2,914 | 26.5 ± 7.8 | ||
| Working hours/week | ≤ 48 h/week | 5,213 | 26.5 ± 7.5 | 0.012 |
| > 48 h/week | 847 | 25.8 ± 7.3 | ||
| Subjective health status | Very good, good | 1,562 | 28.7 ± 7.7 | < 0.001 |
| Fair | 3,763 | 25.9 ± 7.1 | ||
| Poor, Very poor | 735 | 23.0 ± 7.4 |
Values are presented with mean ± standard deviation
HL Health literacy
P values are presented using the t-test or one-way analysis of variance test
Table 3 shows the prevalence of baseline leisure-time exercise and daily physical activity by groups of baseline characteristics and HL. Of all participants, the prevalence of leisure-time exercise was 18.6%. Leisure-time exercise was more prevalent among younger participants, males, single people, those with college degrees and higher, industrial workers, those with fair health, and higher HL. A similar tendency was observed for daily physical exercise.
Table 3.
Status of physical activity in 2019 by baseline characteristics and HL groups
| Characteristics | N | Leisure time exercise | Daily physical activity | |||||
|---|---|---|---|---|---|---|---|---|
| Yes | No | p | Yes | No | p | |||
| Total | 6,060 | 1,125 (18.6) | 4,935 (81.4) | 2,419 (39.9) | 3,641 (60.1) | |||
| Age | 18–39 years | 2,753 | 607 (22.0) | 2,146 (78.0) | < 0.001 | 1,470 (53.4) | 1,283 (46.6) | < 0.001 |
| 40–64 years | 3,307 | 518 (15.7) | 2,789 (84.3) | 949 (28.7) | 2,358 (71.3) | |||
| Sex | Males | 4,153 | 914 (22.0) | 3,239 (78.0) | < 0.001 | 1,787 (43.0) | 2,366 (57.0) | < 0.001 |
| Females | 1,907 | 211 (11.1) | 1,696 (88.9) | 632 (33.1) | 1,275 (66.9) | |||
| Marital status | Single/bereaved | 2,263 | 529 (23.4) | 1,734 (76.6) | < 0.001 | 1,098 (48.5) | 1,165 (51.5) | < 0.001 |
| Married | 3,797 | 596 (15.7) | 3,201 (84.3) | 1,321 (34.8) | 2,476 (65.2) | |||
| Educational attainment | High school | 3,109 | 586 (18.8) | 2,523 (81.2) | 0.015 | 1,403 (45.1) | 1,706 (54.9) | < 0.001 |
| Vocational | 1,083 | 169 (15.6) | 914 (84.4) | 396 (36.6) | 687 (63.4) | |||
| University | 1,868 | 370 (19.8) | 1,498 (80.2) | 620 (33.2) | 1,248 (66.8) | |||
| Job | Office work | 3,146 | 537 (17.1) | 2,609 (82.9) | 0.002 | 816 (25.9) | 2,330 (74.1) | < 0.001 |
| Industrial work | 2,914 | 588 (20.2) | 2,326 (79.8) | 1,603 (55.0) | 1,311 (45.0) | |||
| Working hours | < 48 h/week | 5,213 | 973 (18.7) | 4,240 (81.3) | 0.618 | 2,148 (41.2) | 3,065 (58.8) | < 0.001 |
| ≥ 48 h/week | 847 | 152 (17.9) | 695 (82.1) | 271 (32.0) | 576 (68.0) | |||
| Subjective health status | Good | 1,562 | 421 (9.9) | 1,141 (73.0) | < 0.001 | 802 (51.3) | 760 (48.7) | < 0.001 |
| Fair | 3,763 | 626 (16.6) | 3,137 (83.4) | 1,390 (36.9) | 2,373 (63.1) | |||
| Poor | 735 | 78 (10.6) | 657 (89.4) | 227 (30.9) | 508 (69.1) | |||
| HL category | Inadequate | 2,673 | 376 (14.1) | 2,297 (85.9) | < 0.001 | 904 (33.8) | 1,769 (66.2) | < 0.001 |
| Problematic | 2,444 | 512 (20.9) | 1,932 (79.1) | 1,026 (42.0) | 1,418 (58.0) | |||
| Sufficient | 745 | 175 (23.5) | 570 (76.5) | 383 (51.4) | 362 (48.6) | |||
| Excellent | 198 | 62 (31.3) | 136 (68.7) | 106 (53.5) | 92 (46.5) | |||
Leisure time exercise, yes: doing exercise to sweat lightly for over 30 min at a time, 2 times weekly, for over a year
Daily physical activity, yes: walk or do any equivalent amount of physical activity for more than one hour a day
HL Health literacy, Values are presented as a number (%)—p values presented using a chi-squared test
Table 4. displays the prevalence of a combination of leisure-time exercise and daily physical activity in 2019/2020 by groups of baseline characteristics and HL. The four HL groups were combined into “inadequate and problematic” and “sufficient and excellent.” Regarding leisure-time exercise, 14.1% of all participants were “yes/yes,” 4.4% were “yes/no,” 6.8% were “no/yes,” and 74.6% were “no/no.” The two groups showed significant difference. Regarding daily physical activity, of all participants, 29.1% were “yes/yes,” 10.8% were “yes/no,” 10.7% were “no/yes,” and 49.4% were “no/no.” Again, the two groups showed significant difference.
Table 4.
Status of physical exercise of 2019 and 2020 by HL groups
| Health literacy | N | 2019/2020 | p | ||||
|---|---|---|---|---|---|---|---|
| Yes/Yes | Yes/No | No/Yes | No/No | ||||
| Leisure time exercise | Overall | 6,060 | 857 (14.1) | 268 (4.4) | 412 (6.8) | 4,523 (74.6) | |
| Inadequate or Problematic | 5,117 | 678 (13.2) | 210 (4.1) | 320 (6.3) | 3,909 (76.4) | <0.001 | |
| Sufficient or Excellent | 943 | 179 (19.0) | 58 (6.2) | 92 (9.8) | 614 (65.1) | ||
| Daily physical activity | Overall | 6,060 | 1,763 (29.1) | 656 (10.8) | 650 (10.7) | 2,991 (49.4) | |
| Inadequate or Problematic | 5,117 | 1,389 (27.1) | 541 (10.6) | 542 (10.6) | 2,645 (51.7) | <0.001 | |
| Sufficient or Excellent | 943 | 374 (39.7) | 115 (12.2) | 108 (11.5) | 346 (36.7) | ||
HL Health literacy, Values are presented number (%)
P values presented using chi-squared test
Table 5 shows the results of the multivariable multinominal logistic regression model for identifying the relationship between HL and change in leisure-time exercise, with the “no/no” group serving as the reference. Compared with those who were “inadequate or problematic,” the age- and gender-adjusted odds ratios of the “sufficient and excellent” group in model 1 were for “Yes/Yes” 1.87 (95% CI, 1.68–2.13); for “Yes/No,” 1.88 (95% CI, 1.59–2.35); and for “No/Yes” 1.81 (95% CI, 1.59–2.14). In model 2, the adjusted odds ratios were for “Yes/Yes,” 2.00 (95% CI, 1.78–2.32); for “Yes/No” 1.96 (95% CI, 1.64–2.50); and for “No/Yes” 1.88 (95% CI, 1.63–2.25).
Table 5.
Relationship between HL and status of leisure time exercise in 2019 and 2020 by a multinomial logistic analysis
| Base outcome (No/No) | ||||
|---|---|---|---|---|
| Yes/Yes | Yes/No | No/Yes | ||
| OR (95% CI) | OR (95% CI) | OR (95% CI) | ||
| Model 1 | Inadequate or Problematic | 1 | 1 | 1 |
| Sufficient or Excellent | 1.87 (1.68, 2.13) | 1.88 (1.59, 2.35) | 1.81 (1.59, 2.14) | |
| Model 2 | Inadequate or Problematic | 1 | 1 | 1 |
| Sufficient or Excellent | 2.00 (1.78, 2.32) | 1.96 (1.64, 2.50) | 1.88 (1.63, 2.25) | |
HL Health literacy
Model 1: adjusted for age (linear) and sex
Model 2: adjusted for age, sex, marital status (married/single), educational attainment (college degree or more/under college degree), job type (office work/industrial work), work hours (≤ 48 h/week/>48 h/week) and subjective health status (good/fair/poor)
Table 6 shows results of the multivariable multinomial logistic regression model for identifying the relationship between HL and the change in daily physical activity, with the “no/no” group serving as the reference. Compared with those who were “inadequate or problematic” in HL, the age- and gender-adjusted odds ratios of the “sufficient and excellent” group in model 1 were for “Yes/Yes” 1.74 (95% CI, 1.60–1.93); for “Yes/No” 1.94 (95% CI, 1.69–2.31); and for “No/Yes” 2.04 (95% CI, 1.75–2.46). In model 2, the adjusted odds ratios were for “Yes/Yes” 1.80 (95% CI, 1.64–2.02); for “Yes/No” 1.99 (95% CI, 1.72–2.40); and for “No/Yes” 2.09 (95% CI,1.78–2.57).
Table 6.
Relationship between HL and status of daily physical activity in 2019 and 2020 by a multinomial logistic analysis
| Base outcome (No/No) | ||||
|---|---|---|---|---|
| Yes/Yes | Yes/No | No/Yes | ||
| OR (95% CI) | OR (95% CI) | OR (95% CI) | ||
| Model 1 | Inadequate or Problematic | 1 | 1 | 1 |
| Sufficient or Excellent | 1.74 (1.60, 1.93) | 1.94 (1.69, 2.31) | 2.04 (1.75, 2.46) | |
| Model 2 | Inadequate or Problematic | 1 | 1 | 1 |
| Sufficient or Excellent | 1.80 (1.64, 2.02) | 1.99 (1.72, 2.40) | 2.09 (1.78, 2.57) | |
Model 1: adjusted for age (linear) and sex
Model 2: adjusted for age, sex, marital status (married/single), educational attainment (college degree or more/under college degree), job type (office work/industrial work), work hours (≤ 48 h/week/>48 h/week), and subjective health status (good/fair/poor)
HL Health literacy
Discussion
In this study, the percentage of participants with physical exercise habits was under 20%, and only about 40% of people walked or engaged in physical activity for more than an hour a day. These data were almost identical to those of Japan’s National Health and Nutrition Survey: 23.5% of men and 16.9% of women aged 20–64 [10]. After one year, 80% of the study participants lacked regular physical exercise, and 60% remained inactive daily.
Cross-sectionally, those with high HL had more participants with leisure-time exercise habits and daily physical activity. Longitudinally, the proportion who continued to exercise and stay active daily was higher in the high HL group than in the low group. Of participants with sufficient or excellent HL, however, 65% lacked leisure-time exercise and were inactive daily. The Japanese government has been promoting health policies through Health Japan 21, which involves companies. The target company also took a population approach, for instance, providing information to all employees about the physical activity and its health benefits. However, these approaches have seemed unable to produce sufficient results.
Several observational studies have shown a positive association between HL and the prevalence of leisure-time exercise habits among adults [15–19, 26]. Suka et al. [16] reported that those with higher HL were significantly more likely to obtain sufficient health information from multiple sources, less likely to lack exercise, and, in turn, more likely to report good self-rated health. Friis et al. [17] found that HL mediates the association between educational attainment and health behavior, including inactivity. Matsushita et al. [18] found that high-level HL was significantly related to total, travel-related, and recreational physical activity, but not to work activity. However, longitudinal studies are few. Kobayashi et al. [27] reported that higher HL was associated with continued exercise, although that study’s participants were older than ours.
Compared to the group with “inadequate or problematic” HL, the group with “sufficient and excellent” HL tended to start and quit physical exercise more. The same was true for daily activities. These results suggest that people with relatively high HL are interested in becoming more active but find it difficult to continue. In a systematic review and meta-analysis of behavioral interventions’ effectiveness with motivational interviewing, Zhu et al. [28] found that although interventions increased physical activity and reduced sedentary time, the effects did not persist beyond the intervention period.
Several articles have shown that in working populations, work factors were associated with leisure-time physical activity. Workers who put in long hours were at risk of inactivity [12, 29]. In a cross-sectional analysis, the Individual-Participant-Data Meta-Analysis in Working Populations Consortium of the European cohort study reported that employees with high-strain jobs (low control/high demands) and passive jobs (low control/low demands) were more inactive than employees in low-strain (high control/low demands) jobs. They also reported that employees under high strain became more inactive in the prospective analysis [29]. From the Netherlands Working Conditions Survey, Van As et al. [30] found negative associations between job demands and leisure-time physical activity via fatigue among selected participants engaged in sedentary work. However, we could not evaluate the work environment other than working hours.
This study’s interpretation has several limitations. First, participants were employees of a large-scale business in rural Japan, and most employees commuted by car. However, when we examined rates of exercise habits and those engaging in a certain level of physical activity, they were almost identical to the National Health and Nutrition Survey results, indicating that this group is not particularly skewed. Second, although the study was a follow-up, it examined changes over only one year. Third, data on HL and physical activity were self-assessed. Fourth, we could not evaluate other factors such as work environment and home environment, which might affect physical activity.
Despite these limitations and due to the few longitudinal studies on the relationship between physical activity and HL, we believe this study is worthwhile. In this study, we found that although HL was related to staying physically active, more people with sufficient and excellent HL remained inactive.
Conclusions
In this study, the group with sufficient and excellent HL tended to remain active compared to those with insufficient and problematic HL. Additionally, we found that the high HL group tended to try to practice exercise and engage in active daily living, even though they were unable to continue. These results suggested that HL was associated with starting and maintaining exercise and being active daily. Therefore, it was suggested that improving HL effectively enhances physical activity.
Acknowledgements
The authors thank Yuchi Naruse, Chiaki Okamoto, and Yuki Nakashima (Health Care Center, YKK Corporation) for their scientific advice and for performing the questionnaire survey.
Abbreviations
- HL
Health literacy
- CI
Confidence interval
Authors’ contributions
YM conceived the ideas, YM, KT, MS, MI, TK, and HN designed the study. YM, MS, and MI collected the data. YM, KT, TK, and MS analyzed the data. YM and MS wrote the paper. YM, KT, MS, MI, TK, and HN reviewed the manuscript and accepted the final version for publication.
Funding
This work was supported by a grant (18K10093) from the Japan Society for the Promotion of Science.
Data availability
The datasets generated and/or analyzed during the current study are not publicly available due to the target company’s information management rules. However, they are available from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participate
We conducted this study in accordance with the Declaration of Helsinki. This study was approved by the Kanazawa Medical University Medical Research Ethics Board (approval number: I431). A committee representing the target company also approved it. All participants provided written informed consent after receiving a document describing the entire study. During data processing, a company employee in charge converted participants’ identification into pseudonyms, with the researchers then receiving only de-identified data for analysis.
Consent for publication
Not applicable
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and/or analyzed during the current study are not publicly available due to the target company’s information management rules. However, they are available from the corresponding author upon reasonable request.