Who Got Vaccinated for COVID-19? Evidence from Japan
Abstract
:1. Introduction
2. Materials and Methods
2.1. Sample and Setting
2.2. Data Collection
2.3. Measures
2.3.1. Vaccination
2.3.2. Socioeconomic Factors
2.3.3. Risk Attitude and Time Preference
2.3.4. Perceptions of COVID-19
2.3.5. Policy Stance and Mental Health during the COVID-19 Pandemic
2.4. Statistical Analysis
3. Results
3.1. Basic Statistics
3.2. Chi-Square Test Result
3.3. Estimation Results
3.4. Additional Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Variable | Explanation of Variable |
---|---|
Vaccinated | “Have you received the vaccine against COVID-19?” (1 = Received the second dose of vaccination between February and June; Received the second dose of vaccination from July to September; Received the first dose, but have not yet received the second one; Will receive the first dose in the future; 0 = Will not be vaccinated.) |
Socioeconomic Factors | |
Gender | “What is your gender?” |
Age | “What is your age?” |
Marital status | “Please indicate who you are currently living with.” We classified individuals as “married” if they answered “Spouse (including de facto marriage),” and “not married” if not. |
Education | “What is your last educational background (including current and correspondence courses)?” We classified individuals as “college educated” if they answered “university undergraduate,” “master’s program, professional graduate school,” or “postdoctoral program,” and “not college educated” if they answered others. |
Employment status | “What is your employment status?” We classified individuals as “regular” if they answered “employee (regular employee),” “non-regular” if they answered “employee (part-time worker, dispatched worker, contract employee, commissioned worker, and others),” “director” if they answered “director of a company, etc.," “self-employed” if they answered “self-employed (with employees),” “self-employed (with no employees),” or “self-employed helper,” and “others” if they answered “housewife/househusband,” “student,” “unemployed,” or “others.” |
Occupation | “What is your occupation?” |
Enterprise size | “Which of the following is the number of employees (including part-time workers and dispatched workers, etc.) in your company or business as a whole? If you work for a public office, please select “Public office.” |
Prefecture | “Please indicate the prefecture in which you live.” |
Income | “How much did you personally earn from your main job in 2020? Please indicate the amount before taxes and insurance premiums are deducted. If you are self-employed, please indicate the amount of operating income after subtracting necessary expenses from net sales.” |
Personal Preference | |
Risk preference | “Are you generally a person who is fully prepared to take risks or do you try to avoid taking risks?” (0 = “not at all willing to take risks” to 10 = “very willing to take risks.”) |
Time preference | “Instead of receiving 10,000 yen (approximately $88) after one month, how much would you be satisfied with receiving at least after 13 months?” (1 = “9500 yen (-5% annual interest rate),” 2 = “10,000 yen (0% annual interest rate),” 3 = “10,200 yen (2% annual interest rate),” 4 = “10,400 yen (4% annual interest rate),” 5 = “10,600 yen (6% annual interest rate),” 6 = “11,000 yen (10% annual interest rate),” 7 = “12,000 yen (20% annual interest rate),” 8 = “14,000 yen (40% annual interest rate).”) |
Perceptions of the COVID-19 | |
Perceived fear of COVID-19 infection | “In the past 30 days, how often did you feel fear of the COVID-19 infection?” (1 = Always to 5 = Not at all). |
COVID-19 preventive behaviors | “In the past 30 days, how often did you pay attention to keeping physical distance (social distance)?” (1 = Always to 5 = Not at all.) and “In the past 30 days, how often did you make a conscious effort to wear a mask outside the house?” (1 = Always to 5 = Not at all.) We measure the average perception of infection prevention by adding the results of the two item responses and dividing by two. |
Attitudes toward the policy | |
Agree with the restrictions on individual behavior by the government in crisis situations | “We would like to ask you a question in light of the spread of the COVID-19. Do you agree or disagree that the government should take the following measures for the entire nation, including the future?“—“Restrictions on individual behavior and control of goods and economy by the government in emergency situations.” (−2 =“Disagree,” −1 = “Somewhat disagree,” 0 = “Neither agree nor disagree/Don’t know,” 1 = “Somewhat agree,” 2 = “Agree.”) |
Agree with the policies that prioritize stimulating economic activity over deterring the spread of infection | Same question as above—“Promote policies that prioritize stimulating economic activity over deterring the spread of infection.” (−2 = “Disagree,” −1 = “Somewhat disagree,” 0 = “Neither agree nor disagree/Don’t know,” 1 = “Somewhat agree,” 2 = “Agree.”) |
Mental health | |
Kessler-6 Non-Specific Psychological Distress Scale (K6) | “In the past 30 days, how often did you feel: (1) so sad nothing could cheer you up?; (2) nervous?; (3) restless or fidgety?; (4) hopeless?; (5) that everything was an effort?; (6) worthless? ”(0 = Not at all to 4 = Always.) We added up the scores and created a dummy variable with 1 for those who scored 5 or more, indicating the possibility of having some depression/anxiety issues, and 0 for those who scored less than 5. |
References
- World Health Organization. General WHO Coronavirus Disease (COVID-19) Dashboard. Available online: https://covid19.who.int/ (accessed on 13 December 2021).
- Chung, H.; He, S.; Nasreen, S.; Sundaram, M.E.; Buchan, S.A.; Wilson, S.E.; Chen, B.; Calzavara, A.; Fell, D.B.; Austin, P.C.; et al. Effectiveness of BNT162b2 and mRNA-1273 covid-19 vaccines against symptomatic SARS-CoV-2 infection and severe covid-19 outcomes in Ontario, Canada: Test negative design study. BMJ 2021, 374, n1943. [Google Scholar] [CrossRef] [PubMed]
- Haas, E.J.; Angulo, F.J.; McLaughlin, J.M.; Anis, E.; Singer, S.R.; Khan, F.; Brooks, N.; Smaja, M.; Mircus, G.; Pan, K.; et al. Impact and effectiveness of mRNA BNT162b2 vaccine against SARS-CoV-2 infections and COVID-19 cases, hospitalisations, and deaths following a nationwide vaccination campaign in Israel: An observational study using national surveillance data. Lancet 2021, 397, 1819–1829. [Google Scholar] [CrossRef]
- Mathieu, E.; Ritchie, H.; Ortiz-Ospina, E.; Roser, M.; Hasell, J.; Appel, C.; Giattino, C. A global database of COVID-19 vaccinations. Nat. Hum. Behav. 2021, 5, 947–953. [Google Scholar] [CrossRef] [PubMed]
- Randolph, H.E.; Barreiro, L.B. Herd immunity: Understanding COVID-19. Immunity 2020, 52, 737–741. [Google Scholar] [CrossRef] [PubMed]
- Kwok, K.O.; Mcneil, E.B.; Tsoi, M.T.F.; Wei, V.W.I.; Wong, S.Y.S.; Tang, J.W.T. Will achieving herd immunity be a road to success to end the COVID-19 pandemic? J. Infect. 2021, 83, 381–412. [Google Scholar] [CrossRef]
- Wake, A.D. The willingness to receive COVID-19 Vaccine and its associated factors: “vaccination refusal could prolong the war of this pandemic”—A systematic review. Risk Manag. Health Policy 2021, 14, 2609–2623. [Google Scholar] [CrossRef]
- Nehal, K.R.; Steendam, L.M.; Campos Ponce, M.; van der Hoeven, M.; Smit, G.S.A. Worldwide Vaccination Willingness for COVID-19: A Systematic Review and Meta-Analysis. Vaccines 2021, 9, 1071. [Google Scholar] [CrossRef]
- Sallam, M. COVID-19 Vaccine Hesitancy Worldwide: A Concise Systematic Review of Vaccine Acceptance Rates. Vaccines 2021, 9, 160. [Google Scholar] [CrossRef]
- Lazarus, J.V.; Ratzan, S.; Palayew, A.; Billari, F.C.; Binagwaho, A.; Kimball, S.; Larson, H.J.; Melegaro, A.; Rabin, K.; White, T.M.; et al. COVID-SCORE: A global survey to assess public perceptions of government responses to COVID-19 (COVID-SCORE-10). PLoS ONE 2020, 15, e0240011. [Google Scholar] [CrossRef]
- Al-Amer, R.; Maneze, D.; Everett, B.; Montayre, J.; Villarosa, A.R.; Dwekat, E.; Salamonson, Y. COVID-19 vaccination intention in the first year of the pandemic: A systematic review. J. Clin. Nurs. 2021, 31, 62–86. [Google Scholar] [CrossRef]
- Bish, A.; Yardley, L.; Nicoll, A.; Michie, S. Factors associated with uptake of vaccination against pandemic influenza: A systematic review. Vaccine 2011, 29, 6472–6484. [Google Scholar] [CrossRef]
- Wang, J.; Jing, R.; Lai, X.; Zhang, H.; Lyu, Y.; Knoll, M.D.; Fang, H. Acceptance of COVID-19 Vaccination during the COVID-19 Pandemic in China. Vaccines 2020, 8, 482. [Google Scholar] [CrossRef] [PubMed]
- Wang, K.; Wong, E.L.Y.; Ho, K.-F.; Cheung, A.W.L.; Yau, P.S.Y.; Dong, D.; Wong, S.Y.S.; Yeoh, E.-K. Change of willingness to accept COVID-19 vaccine and reasons of vaccine hesitancy of working people at different waves of local epidemic in Hong Kong, China: Repeated cross-sectional surveys. Vaccines 2021, 9, 62. [Google Scholar] [CrossRef] [PubMed]
- Troiano, G.; Nardi, A. Vaccine hesitancy in the era of COVID-19. Public Health 2021, 194, 245–251. [Google Scholar] [CrossRef] [PubMed]
- Trueblood, J.S.; Sussman, A.B.; O’Leary, D. The Role of Risk Preferences in Responses to Messaging About COVID-19 Vaccine Take-Up. Soc. Psychol. Personal. Sci. 2021, 1948550621999622. [Google Scholar] [CrossRef]
- Guo, N.; Wang, J.; Nicholas, S.; Maitland, E.; Zhu, D. Behavioral differences in the preference for hepatitis B virus vaccination: A discrete choice experiment. Vaccines 2020, 8, 527. [Google Scholar] [CrossRef]
- Detoc, M.; Bruel, S.; Frappe, P.; Tardy, B.; Botelho-Nevers, E.; Gagneux-Brunon, A. Intention to participate in a COVID-19 vaccine clinical trial and to get vaccinated against COVID-19 in France during the pandemic. Vaccine 2020, 38, 7002–7006. [Google Scholar] [CrossRef] [PubMed]
- Gagneux-Brunon, A.; Detoc, M.; Bruel, S.; Tardy, B.; Rozaire, O.; Frappe, P.; Botelho-Nevers, E. Intention to get vaccinations against COVID-19 in French healthcare workers during the first pandemic wave: A cross sectional survey. J. Hosp. Infect. 2020, 108, 168–173. [Google Scholar] [CrossRef]
- Kourlaba, G.; Kourkouni, E.; Maistreli, S.; Tsopela, C.-G.; Molocha, N.-M.; Triantafyllou, C.; Koniordou, M.; Kopsidas, I.; Chorianopoulou, E.; Maroudi-Manta, S.; et al. Willingness of Greek general population to get a COVID-19 vaccine. Glob. Health Res. Policy 2021, 6, 1–10. [Google Scholar] [CrossRef] [PubMed]
- Okubo, T.; Nippon Institute for Research Advancement. Report on the Results of a Fifth Questionnaire Survey Concerning the Impact of the Use of Telework to Respond to the Spread of COVID-19 on Working Styles, Lifestyles, and Awareness; Nippon Institute for Research Advancement: Tokyo, Japan, 2021. [Google Scholar]
- Okubo, T. Spread of COVID-19 and telework: Evidence from Japan. Covid Econ. 2020, 32, 1–25. [Google Scholar]
- Okubo, T.; Inoue, A.; Sekijima, K. Teleworker performance in the COVID-19 era in Japan. Asian Econ. Pap. 2021, 20, 175–192. [Google Scholar] [CrossRef]
- Government CIOs’ Portal, Japan. COVID-19 Vaccination in Japan. Available online: https://cio.go.jp/c19vaccine_dashboard (accessed on 12 November 2021).
- Ministry of Internal Affairs and Communications. Japan Standard Occupational Classification (Rev. 5th, December 2009). Available online: https://www.soumu.go.jp/english/dgpp_ss/seido/shokgyou/index09.htm#pTop (accessed on 12 November 2021).
- Kantar Public. SOEP-Core—2020: Individual (A-L3, M1-M2 + N-Q). SOEP Survey Papers 1069: Series A; DIW/SOEP: Berlin, Germany, 2021. [Google Scholar]
- Kessler, R.C.; Barker, P.R.; Colpe, L.J.; Epstein, J.F.; Gfroerer, J.C.; Hiripi, E.; Howes, M.J.; Normand, S.T.; Mandersheid, R.W.; Walters, E.E.; et al. Screening for Serious Mental Illness in the General Population. Arch. Gen. Psychiatry 2003, 60, 184–189. [Google Scholar] [CrossRef] [PubMed]
- Furukawa, T.A.; Kawakami, N.; Saitoh, M.; Ono, Y.; Nakane, Y.; Nakamura, Y.; Tachimori, H.; Iwata, N.; Uda, H.; Nakane, H.; et al. The performance of the Japanese version of the K6 and K10 in the World Mental Health Survey Japan. Int. J. Methods Psychiatr. Res. 2008, 17, 152–158. [Google Scholar] [CrossRef]
- Kadoya, Y.; Watanapongvanich, S.; Yuktadatta, P.; Putthinun, P. Willing or Hesitant? A Socioeconomic Study on the Potential Acceptance of COVID-19 Vaccine in Japan. Int. J. Environ. Res. Public Health 2021, 18, 4864. [Google Scholar] [CrossRef]
- Nomura, S.; Eguchi, A.; Yoneoka, D.; Kawashima, T.; Tanoue, Y.; Murakami, M.; Sakamoto, H.; Maruyama-Sakurai, K.; Gilmour, S.; Shi, S.; et al. Reasons for being unsure or unwilling regarding intention to take COVID-19 vaccine among Japanese people: A large cross-sectional national survey. Lancet Reg. Health-West. Pac. 2021, 14, 100223. [Google Scholar] [CrossRef]
- Machida, M.; Nakamura, I.; Kojima, T.; Saito, R.; Nakaya, T.; Hanibuchi, T.; Takamiya, T.; Odagiri, Y.; Fukushima, N.; Kikuchi, H.; et al. Acceptance of a COVID-19 Vaccine in Japan during the COVID-19 Pandemic. Vaccines 2021, 9, 210. [Google Scholar] [CrossRef] [PubMed]
- Yoda, T.; Katsuyama, H. Willingness to Receive COVID-19 Vaccination in Japan. Vaccines 2021, 9, 48. [Google Scholar] [CrossRef]
- Bell, S.; Clarke, R.; Mounier-Jack, S.; Walker, J.L.; Paterson, P. Parents’ and guardians’ views on the acceptability of a future COVID-19 vaccine: A multi-methods study in England. Vaccine 2020, 38, 7789–7798. [Google Scholar] [CrossRef]
- Shekhar, R.; Sheikh, A.; Upadhyay, S.; Singh, M.; Kottewar, S.; Mir, H.; Barrett, E.; Pal, S. COVID-19 Vaccine Acceptance among Health Care Workers in the United States. Vaccines 2021, 9, 119. [Google Scholar] [CrossRef] [PubMed]
Mean | SD | Min | Max | ||
---|---|---|---|---|---|
Vaccinated | 0.85 | 0.35 | 0 | 1 | |
Female | 0.44 | 0.50 | 0 | 1 | |
Age | |||||
15–29 | 0.15 | 0.36 | 0 | 1 | |
30–39 | 0.18 | 0.38 | 0 | 1 | |
40–49 | 0.24 | 0.43 | 0 | 1 | |
50–64 | 0.29 | 0.46 | 0 | 1 | |
>65 | 0.13 | 0.34 | 0 | 1 | |
Married | 0.51 | 0.50 | 0 | 1 | |
College educated | 0.51 | 0.50 | 0 | 1 | |
Employment Status | |||||
Regular | 0.55 | 0.50 | 0 | 1 | |
Non-regular | 0.31 | 0.46 | 0 | 1 | |
Directors | 0.02 | 0.15 | 0 | 1 | |
Self-employed | 0.11 | 0.31 | 0 | 1 | |
Others | 0.01 | 0.09 | 0 | 1 | |
Income (million yen) | 4.36 | 3.75 | 0.25 | 21.25 | |
Occupation | |||||
Administrative and managerial workers | 0.09 | 0.29 | 0 | 1 | |
Researchers | 0.01 | 0.11 | 0 | 1 | |
Agriculture, forestry, and fishery engineers | 0.00 | 0.06 | 0 | 1 | |
Manufacturing engineers | 0.04 | 0.20 | 0 | 1 | |
Architects, civil engineers and surveyor | 0.02 | 0.15 | 0 | 1 | |
Data processing and communication engineers | 0.04 | 0.19 | 0 | 1 | |
Doctors, dentists, veterinarians, and pharmacists | 0.01 | 0.12 | 0 | 1 | |
Public health nurses, midwives, and nurses | 0.02 | 0.13 | 0 | 1 | |
Medical technology and healthcare professionals | 0.02 | 0.13 | 0 | 1 | |
Professional social welfare workers | 0.02 | 0.12 | 0 | 1 | |
Legal professionals | 0.00 | 0.06 | 0 | 1 | |
Management, finance and insurance professionals | 0.01 | 0.08 | 0 | 1 | |
Management and business consultants | 0.00 | 0.06 | 0 | 1 | |
Teachers | 0.03 | 0.16 | 0 | 1 | |
Authors, journalists, editors | 0.00 | 0.06 | 0 | 1 | |
Artists, designers, photographers, film operators | 0.01 | 0.11 | 0 | 1 | |
Other specialist professionals | 0.01 | 0.11 | 0 | 1 | |
General clerical workers | 0.17 | 0.38 | 0 | 1 | |
Accountancy clerks | 0.03 | 0.17 | 0 | 1 | |
Production-related clerical workers | 0.01 | 0.10 | 0 | 1 | |
Sales clerks | 0.05 | 0.21 | 0 | 1 | |
Outdoor service workers | 0.00 | 0.03 | 0 | 1 | |
Transport and post clerical workers | 0.01 | 0.10 | 0 | 1 | |
Office appliance operators | 0.00 | 0.05 | 0 | 1 | |
Sales workers | 0.07 | 0.26 | 0 | 1 | |
Workers in family life support and care service | 0.01 | 0.12 | 0 | 1 | |
Occupational health and hygiene service workers | 0.01 | 0.09 | 0 | 1 | |
Food and drink cooking, staff serving customers | 0.03 | 0.18 | 0 | 1 | |
Manager of residential facilities and buildings | 0.01 | 0.09 | 0 | 1 | |
Other service workers | 0.06 | 0.24 | 0 | 1 | |
Security workers | 0.01 | 0.10 | 0 | 1 | |
Agriculture, forestry and fishery workers | 0.00 | 0.07 | 0 | 1 | |
Manufacturing process workers | 0.04 | 0.19 | 0 | 1 | |
Transport and machine operation workers | 0.01 | 0.09 | 0 | 1 | |
Construction and mining workers | 0.01 | 0.08 | 0 | 1 | |
Carrying, cleaning, packaging, and related workers | 0.02 | 0.15 | 0 | 1 | |
Other | 0.09 | 0.29 | 0 | 1 | |
Enterprise size | |||||
1–4 | 0.14 | 0.35 | 0 | 1 | |
5–29 | 0.17 | 0.37 | 0 | 1 | |
30–99 | 0.17 | 0.37 | 0 | 1 | |
100–499 | 0.19 | 0.39 | 0 | 1 | |
More than 500 | 0.28 | 0.45 | 0 | 1 | |
Government offices | 0.05 | 0.22 | 0 | 1 | |
Risk aversion | 3.93 | 2.25 | 0 | 10 | |
Time preference | 6.17 | 2.03 | 1 | 8 | |
Perceived fear of COVID-19 infection | 2.56 | 1.27 | 1 | 5 | |
COVID-19 preventive behaviors | 3.32 | 1.33 | 1 | 5 | |
Agree with the restrictions on individual behavior by the government in emergency situations | 0.44 | 0.94 | −2 | 2 | |
Agree with the policies that prioritize stimulating economic activity over deterring the spread of infection | 0.22 | 0.96 | −2 | 2 | |
K6 over 5 (possibility of having some depression/anxiety issues) | 0.39 | 0.49 | 0 | 1 |
Vaccination | ||||||
---|---|---|---|---|---|---|
Vaccinated | Non-Vaccinated | |||||
n | % | n | % | p-Value | ||
Gender | 0.249 | |||||
Female | 3479 | 43.81 | 620 | 45.49 | ||
Male | 4462 | 56.19 | 743 | 54.51 | ||
Age | <0.001 | |||||
15–29 | 1076 | 13.55 | 316 | 23.18 | ||
30–39 | 1341 | 16.89 | 334 | 24.50 | ||
40–49 | 1919 | 24.17 | 359 | 26.34 | ||
50–64 | 2433 | 30.64 | 292 | 21.42 | ||
>65 | 1172 | 14.76 | 62 | 4.55 | ||
Marital status | <0.001 | |||||
Unmarried | 3745 | 47.16 | 851 | 62.44 | ||
Married | 4196 | 52.84 | 512 | 37.56 | ||
Education | <0.001 | |||||
Not college educated | 3777 | 47.56 | 752 | 55.17 | ||
College educated | 4164 | 52.44 | 611 | 44.83 | ||
Employment Status | <0.001 | |||||
Regular | 4374 | 55.08 | 723 | 53.04 | ||
Non-regular | 2491 | 31.37 | 421 | 30.89 | ||
Directors | 204 | 2.57 | 22 | 1.61 | ||
Self-employed | 809 | 10.19 | 176 | 12.91 | ||
Others | 63 | 0.79 | 21 | 1.54 | ||
Occupation | <0.001 | |||||
Administrative and managerial workers | 780 | 9.82 | 91 | 6.68 | ||
Researchers | 91 | 1.15 | 14 | 1.03 | ||
Agriculture, forestry, and fishery engineers | 25 | 0.31 | 5 | 0.37 | ||
Manufacturing engineers | 312 | 3.93 | 58 | 4.26 | ||
Architects, civil engineers and surveyor | 197 | 2.48 | 27 | 1.98 | ||
Data processing and communication engineers | 318 | 4.00 | 47 | 3.45 | ||
Doctors, dentists, veterinarians, and pharmacists | 115 | 1.45 | 14 | 1.03 | ||
Public health nurses, midwives, and nurses | 136 | 1.71 | 12 | 0.88 | ||
Medical technology and healthcare professionals | 155 | 1.95 | 10 | 0.73 | ||
Professional social welfare workers | 128 | 1.61 | 13 | 0.95 | ||
Legal professionals | 29 | 0.37 | 7 | 0.51 | ||
Management, finance and insurance professionals | 54 | 0.68 | 7 | 0.51 | ||
Management and business consultants | 33 | 0.42 | 3 | 0.22 | ||
Teachers | 224 | 2.82 | 25 | 1.83 | ||
Authors, journalists, editors | 28 | 0.35 | 5 | 0.37 | ||
Artists, designers, photographers, film operators | 95 | 1.20 | 23 | 1.69 | ||
Other specialist professionals | 107 | 1.35 | 15 | 1.10 | ||
General clerical workers | 1412 | 17.78 | 208.00 | 15.26 | ||
Accountancy clerks | 246 | 3.10 | 31 | 2.27 | ||
Production-related clerical workers | 90 | 1.13 | 9 | 0.66 | ||
Sales clerks | 383 | 4.82 | 68 | 4.99 | ||
Outdoor service workers | 8 | 0.10 | 1 | 0.07 | ||
Transport and post clerical workers | 68 | 0.86 | 23 | 1.69 | ||
Office appliance operators | 20 | 0.25 | 6 | 0.44 | ||
Sales workers | 552 | 6.95 | 118 | 8.66 | ||
Workers in family life support and care service | 119 | 1.50 | 9 | 0.66 | ||
Occupational health and hygiene service workers | 68 | 0.86 | 12 | 0.88 | ||
Food and drink cooking, staff serving customers | 263 | 3.31 | 51 | 3.74 | ||
Manager of residential facilities and buildings | 65 | 0.82 | 3 | 0.22 | ||
Other service workers | 474 | 5.97 | 92 | 6.75 | ||
Security workers | 80 | 1.01 | 12 | 0.88 | ||
Agriculture, forestry and fishery workers | 38 | 0.48 | 5 | 0.37 | ||
Manufacturing process workers | 277 | 3.49 | 70 | 5.14 | ||
Transport and machine operation workers | 63 | 0.79 | 16 | 1.17 | ||
Construction and mining workers | 42 | 0.53 | 11 | 0.81 | ||
Carrying, cleaning, packaging, and related workers | 184 | 2.32 | 39 | 2.86 | ||
Other | 662 | 8.34 | 203 | 14.89 | ||
Enterprise size | 0.008 | |||||
1–4 | 1095 | 13.79 | 224 | 16.4 | ||
5–29 | 1303 | 16.41 | 246 | 18.1 | ||
30–99 | 1322 | 16.65 | 230 | 16.9 | ||
100–499 | 1503 | 18.93 | 262 | 19.2 | ||
More than 500 | 2301 | 28.98 | 339 | 24.9 | ||
Government offices | 417 | 5.25 | 62 | 4.6 | ||
K6 | <0.001 | |||||
Less than 5 | 4900 | 61.71 | 772 | 56.64 | ||
Over 5 (possibility of having some depression/anxiety issues) | 3041 | 38.29 | 591 | 43.36 | ||
Mean | SD | Mean | SD | |||
Income (million yen) | 4.39 | 0.04 | 4.16 | 0.11 | 0.033 | |
Risk aversion | 3.92 | 0.03 | 3.94 | 0.06 | 0.760 | |
Time preference | 6.18 | 0.02 | 6.14 | 0.06 | 0.498 | |
Perceived fear of COVID-19 infection | 2.60 | 0.01 | 2.29 | 0.04 | <0.001 | |
COVID-19 preventive behaviors | 3.40 | 0.01 | 2.90 | 0.04 | <0.001 | |
Agree with the restrictions on individual behavior by the government in emergency situations | 0.48 | 0.01 | 0.22 | 0.03 | <0.001 | |
Agree with the policies that prioritize stimulating economic activity over deterring the spread of infection | 0.22 | 0.01 | 0.22 | 0.02 | 0.819 |
OR | 95% CI | p-Value | |||
---|---|---|---|---|---|
Female | 0.89 | 0.77 | 1.02 | 0.086 | |
Age | 15–29 | 0.75 | 0.65 | 0.86 | <0.001 |
30–39 | 0.76 | 0.63 | 0.90 | 0.002 | |
40–49 | Ref | ||||
50–64 | 1.62 | 1.32 | 1.97 | <0.001 | |
>65 | 3.98 | 2.75 | 5.77 | <0.001 | |
Married | 1.36 | 1.15 | 1.61 | <0.001 | |
College educated | 1.30 | 1.11 | 1.53 | 0.001 | |
Employment Status | Regular | Ref | |||
Non-regular | 0.89 | 0.76 | 1.05 | 0.181 | |
Directors | 1.07 | 0.69 | 1.68 | 0.753 | |
Self-employed | 0.65 | 0.49 | 0.87 | 0.004 | |
Others | 0.67 | 0.41 | 1.10 | 0.113 | |
Income | 1.00 | 0.98 | 1.02 | 0.676 | |
Occupation | Administrative and managerial workers | Ref | |||
Researchers | 1.03 | 0.58 | 1.82 | 0.916 | |
Agriculture, forestry, and fishery engineers | 1.44 | 0.51 | 4.03 | 0.493 | |
Manufacturing engineers | 0.98 | 0.72 | 1.32 | 0.867 | |
Architects, civil engineers and surveyor | 1.28 | 0.84 | 1.94 | 0.254 | |
Data processing and communication engineers | 1.25 | 0.91 | 1.73 | 0.166 | |
Doctors, dentists, veterinarians, and pharmacists | 1.13 | 0.67 | 1.92 | 0.652 | |
Public health nurses, midwives, and nurses | 2.36 | 1.44 | 3.88 | 0.001 | |
Medical technology and healthcare professionals | 3.11 | 1.62 | 5.99 | 0.001 | |
Professional social welfare workers | 1.90 | 1.02 | 3.54 | 0.044 | |
Legal professionals | 0.80 | 0.41 | 1.53 | 0.495 | |
Management, finance and insurance professionals | 1.27 | 0.51 | 3.18 | 0.613 | |
Management and business consultants | 1.81 | 0.50 | 6.49 | 0.366 | |
Teachers | 1.27 | 0.87 | 1.86 | 0.220 | |
Authors, journalists, editors | 0.89 | 0.39 | 2.04 | 0.775 | |
Artists, designers, photographers, film operators | 0.96 | 0.66 | 1.40 | 0.833 | |
Other specialist professionals | 1.21 | 0.60 | 2.46 | 0.592 | |
General clerical workers | 1.25 | 1.01 | 1.53 | 0.037 | |
Accountancy clerks | 1.30 | 0.87 | 1.93 | 0.198 | |
Production-related clerical workers | 1.69 | 0.91 | 3.13 | 0.099 | |
Sales clerks | 0.90 | 0.61 | 1.32 | 0.583 | |
Outdoor service workers | 1.66 | 0.20 | 13.61 | 0.636 | |
Transport and post clerical workers | 0.53 | 0.35 | 0.81 | 0.003 | |
Office appliance operators | 0.42 | 0.20 | 0.88 | 0.022 | |
Sales workers | 0.88 | 0.67 | 1.16 | 0.373 | |
Workers in family life support and care service | 2.10 | 0.95 | 4.65 | 0.068 | |
Occupational health and hygiene service workers | 1.07 | 0.56 | 2.05 | 0.830 | |
Food and drink cooking, staff serving customers | 1.12 | 0.76 | 1.66 | 0.563 | |
Manager of residential facilities and buildings | 2.07 | 0.67 | 6.41 | 0.206 | |
Other service workers | 0.97 | 0.68 | 1.38 | 0.849 | |
Security workers | 1.01 | 0.45 | 2.24 | 0.984 | |
Agriculture, forestry and fishery workers | 1.52 | 0.57 | 4.09 | 0.406 | |
Manufacturing process workers | 0.76 | 0.51 | 1.12 | 0.168 | |
Transport and machine operation workers | 0.81 | 0.42 | 1.57 | 0.533 | |
Construction and mining workers | 0.72 | 0.30 | 1.71 | 0.452 | |
Carrying, cleaning, packaging, and related workers | 0.93 | 0.58 | 1.47 | 0.747 | |
Other | 0.72 | 0.53 | 0.97 | 0.031 | |
Enterprise size | 1–4 | Ref | |||
5–29 | 1.22 | 0.95 | 1.56 | 0.124 | |
30–99 | 1.33 | 1.04 | 1.70 | 0.024 | |
100–499 | 1.33 | 0.98 | 1.81 | 0.064 | |
More than 500 | 1.46 | 1.13 | 1.88 | 0.004 | |
Government offices | 1.42 | 1.02 | 1.96 | 0.036 | |
Risk aversion | 1.01 | 0.98 | 1.04 | 0.519 | |
Time preference | 0.99 | 0.96 | 1.02 | 0.412 | |
Perceived fear of COVID-19 infection | 1.16 | 1.09 | 1.23 | <0.001 | |
COVID-19 preventive behaviors | 1.22 | 1.14 | 1.30 | <0.001 | |
Agree with the restrictions on individual behavior by the government in emergency situations | 1.25 | 1.17 | 1.34 | <0.001 | |
Agree with the policies that prioritize stimulating economic activity over deterring the spread of infection | 0.96 | 0.89 | 1.04 | 0.315 | |
K6 over 5 (possibility of having some depression/anxiety issues) | 0.73 | 0.63 | 0.85 | <0.001 | |
Control | Prefecture | ✓ | |||
N | 9304 | ||||
Log likelihood | −3507.0 |
Male | Female | ||||||||
---|---|---|---|---|---|---|---|---|---|
(1) | (2) | ||||||||
OR | 96% CI | p-Value | OR | 97% CI | p-Value | ||||
Age | 15–29 | 0.878 | 0.691 | 1.116 | 0.288 | 0.578 | 0.438 | 0.762 | <0.001 |
30–39 | 0.914 | 0.680 | 1.229 | 0.553 | 0.576 | 0.443 | 0.749 | <0.001 | |
40–49 | Ref | Ref | |||||||
50–64 | 1.669 | 1.266 | 2.200 | <0.001 | 1.499 | 1.188 | 1.893 | 0.001 | |
>65 | 4.816 | 2.997 | 7.739 | <0.001 | 3.139 | 1.967 | 5.010 | <0.001 | |
Married | 1.463 | 1.143 | 1.871 | 0.002 | 1.253 | 1.033 | 1.521 | 0.022 | |
College educated | 1.301 | 1.055 | 1.604 | 0.014 | 1.348 | 1.069 | 1.699 | 0.012 | |
Employment Status | Regular | Ref | Ref | ||||||
Non-regular | 0.888 | 0.710 | 1.110 | 0.297 | 0.847 | 0.666 | 1.077 | 0.175 | |
Directors | 1.477 | 0.782 | 2.788 | 0.229 | 0.575 | 0.254 | 1.299 | 0.183 | |
Self-employed | 0.688 | 0.413 | 1.148 | 0.152 | 0.569 | 0.379 | 0.856 | 0.007 | |
Others | 0.621 | 0.308 | 1.252 | 0.183 | 0.714 | 0.381 | 1.339 | 0.294 | |
Income | 0.985 | 0.953 | 1.018 | 0.365 | 1.008 | 0.970 | 1.047 | 0.688 | |
Enterprise size | 1–4 | Ref | Ref | ||||||
5–29 | 1.140 | 0.735 | 1.770 | 0.558 | 1.259 | 0.839 | 1.888 | 0.266 | |
30–99 | 1.259 | 0.806 | 1.966 | 0.312 | 1.425 | 0.941 | 2.156 | 0.094 | |
100–499 | 1.256 | 0.781 | 2.021 | 0.347 | 1.435 | 0.997 | 2.064 | 0.052 | |
More than 500 | 1.382 | 0.899 | 2.123 | 0.140 | 1.572 | 1.095 | 2.258 | 0.014 | |
Government offices | 1.460 | 0.883 | 2.414 | 0.140 | 1.351 | 0.827 | 2.208 | 0.230 | |
Risk aversion | 1.005 | 0.976 | 1.035 | 0.724 | 1.016 | 0.976 | 1.058 | 0.438 | |
Time preference | 1.005 | 0.971 | 1.041 | 0.771 | 0.970 | 0.926 | 1.016 | 0.199 | |
Perceived fear of COVID-19 infection | 1.133 | 1.044 | 1.230 | 0.003 | 1.195 | 1.060 | 1.347 | 0.004 | |
COVID-19 preventive behaviors | 1.271 | 1.165 | 1.386 | <0.001 | 1.151 | 1.048 | 1.265 | 0.003 | |
Agree with the restrictions on individual behavior by the government in emergency situations | 1.293 | 1.191 | 1.402 | <0.001 | 1.177 | 1.065 | 1.301 | 0.001 | |
Agree with the policies that prioritize stimulating economic activity over deterring the spread of infection | 0.944 | 0.849 | 1.050 | 0.291 | 0.972 | 0.872 | 1.085 | 0.616 | |
K6 over 5 (possibility of having some depression/anxiety issues) | 0.671 | 0.529 | 0.851 | 0.001 | 0.795 | 0.639 | 0.990 | 0.041 | |
Control | Occupation | ✓ | ✓ | ||||||
Prefecture | ✓ | ✓ | |||||||
N | 5197 | 4095 | |||||||
Log likelihood | −1881.5 | −1573.3 |
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Okubo, T.; Inoue, A.; Sekijima, K. Who Got Vaccinated for COVID-19? Evidence from Japan. Vaccines 2021, 9, 1505. https://doi.org/10.3390/vaccines9121505
Okubo T, Inoue A, Sekijima K. Who Got Vaccinated for COVID-19? Evidence from Japan. Vaccines. 2021; 9(12):1505. https://doi.org/10.3390/vaccines9121505
Chicago/Turabian StyleOkubo, Toshihiro, Atsushi Inoue, and Kozue Sekijima. 2021. "Who Got Vaccinated for COVID-19? Evidence from Japan" Vaccines 9, no. 12: 1505. https://doi.org/10.3390/vaccines9121505
APA StyleOkubo, T., Inoue, A., & Sekijima, K. (2021). Who Got Vaccinated for COVID-19? Evidence from Japan. Vaccines, 9(12), 1505. https://doi.org/10.3390/vaccines9121505