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Brief Report

COVID-19 Vaccine Uptake among US Adults According to Standard Occupational Groups

by
Itunu Sokale
1,
Juan Alvarez
1,
Omar Rosales
1,
Eric Bakota
2,
Christopher I. Amos
1,3,
Hoda Badr
1,† and
Abiodun O. Oluyomi
1,*,†
1
Department of Medicine, Epidemiology and Population Sciences Section, Baylor College of Medicine, Houston, TX 77030, USA
2
Office of Science, Surveillance, and Technology, Harris County Public Health, Houston, TX 77030, USA
3
Institute of Clinical and Translational Research, Baylor College of Medicine, Houston, TX 77030, USA
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Vaccines 2022, 10(7), 1000; https://doi.org/10.3390/vaccines10071000
Submission received: 13 April 2022 / Revised: 3 June 2022 / Accepted: 21 June 2022 / Published: 23 June 2022
Versions Notes

Abstract

:
This cross-sectional ecological study examined the relationship between neighborhood-level standard occupational groups in the USA and COVID-19 vaccine uptake using 774 census tract data, each consisting of approximately 1600 housing units. The neighborhood-level COVID-19 vaccination uptake data were retrieved from Harris County Public Health, Harris County, Texas. The standard occupational group data were from the US Census Bureau. We calculated the incidence rate ratios (IRRs) for vaccine uptake using bivariate and multivariable Poisson regression models. In the adjusted models, we found that the healthcare practitioner/technician (IRR: 1.008; 95% CI: 1.003–1.014; p = 0.001), business/management/legal (IRR: 1.011; 95% CI: 1.008–1.013; p < 0.001), computer/engineering/life/physical/social science (IRR: 1.018; 95% CI: 1.013–1.023; p < 0.001), and arts/design/entertainment/sports/media (IRR: 1.031; 95% CI: 1.018–1.044; p < 0.001) occupational groups were more likely to have received the full regimen of a COVID-19 vaccine. On the contrary, the building/installation/maintenance/repair (IRR: 0.991; 95% CI: 0.987–0.995; p < 0.001), construction/extraction/production (IRR: 0.991; 95% CI: 0.988–0.995; p < 0.001), transportation/material moving (IRR: 0.992; 95% CI: 0.987–0.997; p = 0.002), food preparation/serving related (IRR: 0.995; 95% CI: 0.990–0.999; p = 0.023), and personal care/services (IRR: 0.991; 95% CI: 0.985–0.998; p = 0.017) groups were less likely to have received the complete dose of a COVID-19 vaccine. White-collar workers were more likely to be vaccinated than blue-collar workers. We adjusted for age, sex, and race/ethnicity in the multivariable analysis. The low vaccine uptake among certain occupational groups remains a barrier to pandemic control. Engaging labor-centered stakeholders in the development of vaccination interventions may increase uptake.

1. Introduction

The benefits of vaccination within public health interventions are widely recognized. Annually, immunizations prevent more than 2 million deaths from multiple preventable diseases [1]. Unfortunately, despite the current availability of safe and effective COVID-19 vaccines, the daily numbers of new cases and preventable deaths from COVID-19 in the United States (US) remain high. For example, in October 2021, the US average daily estimates for new COVID-19 cases and COVID-19-related deaths were 95,000 and 1400, respectively [2]. As a result, the US government and many non-governmental organizations have been making significant efforts to improve COVID-19 vaccine uptake among US workers across different occupational groups. This push is mainly because the low vaccine uptake puts individuals, coworkers, and clients at risk [3] and may prolong the pandemic.
Simultaneously, there is a growing body of literature on COVID-19 vaccination hesitancy, intention, and acceptability [3,4,5,6,7]. Vaccine hesitancy has been attributed primarily to concerns about vaccine safety and a mistrust of medical science [3,4]. While investigations into intention, acceptability, and hesitancy to participate in vaccination programs may serve as good predictors for vaccination behavior, the results could be too subjective and inadequate for elucidating actual vaccine uptake. Recently, healthcare workers across the globe have been in the spotlight, given their important role as frontline workers [4,5,8,9,10]. The findings of a state-wide study on nursing home and assisted living workers before the availability of the COVID-19 vaccines suggested that less than half of the workers were willing to participate in a vaccination program when one became available and that half of those uncertain workers would consider getting a COVID-19 vaccination in the future [5]. Additionally, a longitudinal study examined COVID-19 acceptability and uptake among frontline healthcare workers in California, USA. The results showed a progressive and significant increase in acceptability and vaccine uptake compared to the baseline data [4].
Although there has been a substantial focus on healthcare workers globally, including in the USA, there is limited information on the COVID-19 vaccination behavior among other occupational groups, specifically in the US. Nevertheless, a few recent works have addressed the influence of occupational groups on COVID-19 vaccine uptake in the US and other countries [11,12]. Occupation-based interventions have demonstrated efficacy in health promotion interventions, including tobacco control programs and influenza vaccine interventions [13,14]. Thus, occupation-based interventions may provide unique opportunities to strengthen COVID-19 vaccination uptake and help to control the pandemic. However, studies that have investigated the actual COVID-19 vaccination uptake among multiple occupational groups in the USA are scarce. In the current analysis, we assessed the associations between the neighborhood compositions of standard US occupational groups and neighborhood-level vaccine uptake in Harris County, Texas.

2. Materials and Methods

This cross-sectional ecological study used neighborhood-level data for the COVID-19 vaccine uptake between 14 December 2020 and 10 August 2021 in Harris County, Texas. The estimated 2020 population of Harris County was 4.72 million people [15], making it the third most populous county in the USA. The county has a very diverse population and a high number of foreign-born residents (26% of the county population) [15]. We received the data on the COVID-19 vaccination uptake from the Office of Science, Surveillance, and Technology (OSST), Harris County Public Health, Harris County, TX, USA. The OSST provided the number of residents in each Harris County census tract that had received the full regimen of a COVID-19 vaccination, as of 10 August 2021.
A census tract (CT) is a small, homogenous, and relatively permanent statistical subdivision of a county, which usually consists of 4000 residents or 1600 housing units [16]. A CT is often used to represent neighborhood-level factors in health studies on the US population. Of the 786 CTs in Harris County, the OSST provided data for 782, of which 774 had occupational data; hence, 774 CTs were used for this analysis. We retrieved the occupational group data (explanatory variables) from the US Census Bureau’s 2014–2018 American Community Survey (ACS) 5-year estimates dataset [17]. A total of 22 occupational groups, as classified by the US Bureau of Labor Statistics, were reorganized into 15 groups (Table 1). The occupational groups were analyzed individually and the percentage of CT residents that were employed in each occupational group was entered into the analysis workflows as a continuous variable. A multivariable analysis was run for each occupational group by adjusting for % Hispanic, % Black or African American, % female, and % under 40 years old (covariates). The covariates were retrieved from the US Census 2015–2019 ACS.
For our statistical analysis, we used a Poisson-based modeling protocol. To address the over-dispersion that was observed in the vaccine uptake dataset, we utilized a negative binomial regression (NBR) technique [18]. Given the unequal CT populations, the natural logarithm of the population was used as an offset variable in all NBR models. For each CT, we used the estimated population of CT residents who were at least 15 years old. The was due to the fact that the US health authorities were yet to officially approve vaccines for children under 15 years of age at the time that our vaccine uptake data were compiled. The effect estimates were expressed as relative risk (incidence rate ratios, IRRs) by exponentiating the Poisson regression coefficient. The explanatory variables were presented as counts (%). For interpretation, the expected number of COVID-19 vaccine uptake within a CT increases or decreases by a factor of the effect measure (IRR) when the population percentage in an occupation increases by 1 unit. Due to the non-independent nature of the occupational groups inside a specific CT, our models did not evaluate the relative effects on each occupational group vis-à-vis the other groups. Instead, each occupational group was entered into a pair of Poisson models. In the first model, vaccine uptake was regressed on just the occupational group alone (bivariate analysis) while in the second model, vaccine uptake was regressed on the occupational group alongside four other independent variables (% Hispanic, % Black or African American, % female, and % less than 40 years old; i.e., the adjusted covariates).

3. Results

Table 2 presents the associations between vaccine uptake and the standard US occupational groups at the census tracts level. In the bivariate analysis, a high vaccine uptake was associated with healthcare practitioner/technician, business/management/legal, computer/engineering/life/physical/social science, arts/design/entertainment/sports/media, sales/sales related, and education/training/library workers. In contrast, we observed a low vaccine uptake among social service/protective services, healthcare support, office/administrative support, farming/fishing/forestry, building/installation/maintenance/repair, construction/extraction/production, transportation/material moving, food preparation/serving related, and personal care/services workers.
After adjusting for age, race/ethnicity, and sex, people who were in the healthcare practitioner/technician (IRR: 1.008; 95% CI: 1.003–1.014; p = 0.001), business/management/legal (IRR: 1.011; 95% CI: 1.008–1.013; p < 0.001), computer/engineering/life/physical/social science (IRR: 1.018; 95% CI: 1.013–1.023; p < 0.001), and arts/design/entertainment/sports/media (IRR: 1.031; 95% CI: 1.018–1.044; p < 0.001) occupational groups were more likely to have received a COVID-19 vaccine. On the contrary, building/installation/maintenance/repair (IRR: 0.991; 95% CI: 0.987–0.995; p < 0.001), construction/extraction/production (IRR: 0.991; 95% CI: 0.988–0.995; p < 0.001), transportation/material moving (IRR: 0.992; 95% CI: 0.987–0.997; p = 0.002), food preparation/serving related (IRR: 0.995; 95% CI: 0.990–0.999; p = 0.023), and personal care/services (IRR: 0.991; 95% CI: 0.985–0.998; p = 0.017) workers were less likely to have received a COVID-19 vaccine after adjusting for age, sex, and race/ethnicity (See Supplemental Materials, Table S1, for the covariates results).

4. Discussion

Workplace interventions present a valuable opportunity to increase COVID-19 vaccine uptake and further minimize the impacts of the COVID-19 pandemic. Our results suggested a discrepancy in COVID-19 vaccine uptake between white-collar jobs versus blue-collar jobs. Similar to our findings, a study on national COVID-19 vaccine coverage according to occupation in England observed higher vaccination uptake among highly skilled professionals and lower vaccination rates among blue-collar workers [11]. In addition, a US social media-based study examined self-reported COVID-19 vaccine uptake among the major occupational groups [12]. The researchers found that the highest and lowest vaccination rates were among college teachers and manual workers, respectively. However, the authors could not exclude the possibility of survey duplication within the sample.
As mentioned previously, vaccine hesitancy studies are more prevalent than COVID-19 vaccine uptake studies. Even so, the vaccine hesitancy or attitude studies involving occupational groups have generally reported findings that were similar to ours. A US study on COVID-19 vaccine hesitancy according to occupation and employment reported variations in vaccine hesitancy among the occupational groups, with the highest vaccine hesitancy observed among manual workers [19]. An Italian study on attitudes toward potential COVID-19 vaccines and influenza vaccines reported lower intentions to receive a potential COVID-19 vaccine among blue-collar workers and farmers. In contrast, managers, white-collar workers, and teachers were willing to accept a COVID-19 vaccine when one became available [20].
The disparity in the vaccine uptake that we observed could have resulted from the higher educational attainment among professional workers, resulting in a better understanding of the risks of COVID-19 infection, the benefits of vaccinations, and greater access to preventive measures, including vaccination services. Studies have shown that people with highly paying jobs are more likely to enjoy better health than those with low-paying jobs and that an increase in the years of education increases the impact of education on health [21]. This study highlighted the disparity in COVID-19 vaccine uptake between white-collar and blue-collar workers. The workplace is an ecosystem comprising interdependent actors who interact to achieve individual and collective goals [22]. A workplace becomes unsafe when disparities in vaccination uptake across job levels are not addressed. For example, an institution with high vaccination rates among the management-level staff but low vaccination rates among the maintenance staff may face challenges in controlling COVID-19 infection.
Our results indicated that highly skilled professionals were more likely to be vaccinated than lay workers and these results remained significant after adjusting for age, sex, and race/ethnicity. Another study investigated COVID-19 vaccine hesitancy and uptake according to race and ethnicity in the USA and the United Kingdom (UK) [23]. In both countries, the authors found significantly lower rates of vaccine hesitancy among participants of a racial minority, while this only persisted in vaccine uptake among US respondents [23]. Another study examined gender differences in COVID-19 vaccine acceptance among working adults in Japan [24]. Their results indicated that older men were more likely to be willing to receive a vaccine. Similarly, another US study on health care workers reported higher acceptance of vaccination among respondents who were male, older, and White or Asian [25].
We acknowledge that our study had strengths and limitations. We analyzed the associations between COVID-19 vaccine uptake and occupational groups using census tract data from actual vaccination records, unlike previous studies that have examined attitudes, acceptance or hesitancy at an individual level. Our data could also inform preparedness strategies for future pandemics in terms of work-based interventions. Our analysis used area-level vaccine uptake data and a cumulative count from January 2021 to August 2021. Therefore, we could not rule out the possibility of ecological fallacy. In addition, the variations in COVID-19 vaccine uptake among occupational groups might have since improved due to the additional public health interventions to reduce morbidity and mortality from the disease as a result of more transmissible variants, including the Delta and Omicron variants. Future studies analyzing more recent data should describe the temporal changes in vaccine uptake among the occupational groups.

5. Conclusions

Given the variations in vaccine uptake among the occupational groups, there is a need to involve labor-centered organizations/stakeholders in developing COVID-19 vaccination interventions. Additionally, we recommend the development of workplace-based and union-level interventions for both institution-based and self-employed workers. Interventions could use multiple evidence-based and theory-grounded strategies to address vaccine mistrust, the risks of COVID-19, the benefits of vaccination, and access to vaccinations, including the provision of vaccination clinics to encourage vaccination among workgroups with low uptake rates.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/vaccines10071000/s1, Table S1: The standard US occupational groups that were used for the current analysis.

Author Contributions

Conceptualization: A.O.O. and H.B.; methodology: A.O.O., H.B., O.R. and I.S.; formal analysis: A.O.O. and J.A.; resources: C.I.A. and H.B.; writing—original draft preparation: I.S. and J.A.; writing—review and editing: A.O.O., C.I.A., E.B., H.B. and O.R.; supervision, A.O.O. and H.B.; project administration, H.B.; funding acquisition, A.O.O., C.I.A. and H.B. All authors have read and agreed to the published version of the manuscript.

Funding

In this study, the efforts of A.O.O., H.B., and O.R. were supported by NHLBI RF 50087-2021-0309-S9 (PI: Badr). The efforts of C.I.A. and H.B. were supported by NHLBI 20-312-0217571-66102L. I.S. was supported by the research training award from the Cancer Prevention & Research Institute of Texas (CPRIT) for the Systems Epidemiology of Cancer Training (SECT) Program (RP210037; PI: A. Thrift). This study was also supported by the facilities and resources of the Dan L Duncan Comprehensive Cancer Center P30 CA125123 (PI: Heslop) and the facilities and resources of the Gulf Coast Center for Precision and Environmental Health P30ES030285 (PI: Walker). The funders had no role in the design of the study, the collection, analyses or interpretation of the data, the writing of the manuscript or the decision to publish the results.

Institutional Review Board Statement

This study leveraged publicly available data without engaging any individuals in the procedures. It was conducted with support of the CEAL Supplement Study. The CEAL Study was approved by the Institutional Review Board of the Baylor College of Medicine: H-47505.

Informed Consent Statement

Not applicable; data analyzed were publicly available aggregate data.

Data Availability Statement

The datasets used and/or analyzed in the current study are available upon reasonable request from the corresponding author.

Acknowledgments

We are grateful to several colleagues from the authors’ home departments and centers at the Baylor College of Medicine for their support during the ongoing COVID-19 pandemic season. We would also like to thank the COVID-19 Data Analytics team at the Harris County Health Department.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study, the collection, analyses or interpretation of the data, the writing of the manuscript or the decision to publish the results.

References

  1. Centers for Disease Control and Prevention. Ten great public health achievements–United States, 2001–2010. MMWR Morb. Mortal Wkly Rep. 2011, 60, 619. [Google Scholar]
  2. Centers for Disease Control and Prevention. COVID Data Tracker Weekly Review. Available online: https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/index.html (accessed on 12 October 2021).
  3. Coustasse, A.; Kimble, C.; Maxik, K. COVID-19 and Vaccine Hesitancy: A Challenge the United States Must Overcome. J. Ambul. Care Manag. 2021, 44, 71–75. [Google Scholar] [CrossRef] [PubMed]
  4. Paterson, P.; Meurice, F.; Stanberry, L.R.; Glismann, S.; Rosenthal, S.L.; Larson, H.J. Vaccine hesitancy and healthcare providers. Vaccine 2016, 34, 6700–6706. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Pacella-LaBarbara, M.L.; Park, Y.L.; Patterson, P.D.; Doshi, A.; Guyette, M.K.; Wong, A.H.; Chang, B.P.; Suffoletto, B.P. COVID-19 Vaccine Uptake and Intent Among Emergency Healthcare Workers: A Cross-Sectional Survey. J. Occup. Environ. Med. 2021, 63, 852–856. [Google Scholar] [CrossRef] [PubMed]
  6. Marzo, R.R.; Sami, W.; Alam, M.Z.; Acharya, S.; Jermsittiparsert, K.; Songwathana, K.; Pham, N.T.; Respati, T.; Faller, E.M.; Baldonado, A.M.; et al. Hesitancy in COVID-19 vaccine uptake and its associated factors among the general adult population: A cross-sectional study in six Southeast Asian countries. Trop. Med. Health 2022, 50, 4. [Google Scholar] [CrossRef]
  7. Sherman, S.M.; Smith, L.E.; Sim, J.; Amlôt, R.; Cutts, M.; Dasch, H.; Rubin, G.J.; Sevdalis, N. COVID-19 vaccination intention in the UK: Results from the COVID-19 vaccination acceptability study (CoVAccS), a nationally representative cross-sectional survey. Hum. Vaccin. Immunother. 2021, 17, 1612–1621. [Google Scholar] [CrossRef] [PubMed]
  8. Halbrook, M.; Gadoth, A.; Martin-Blais, R.; Gray, A.N.; Kashani, S.; Kazan, C.; Kane, B.; Tobin, N.H.; Ferbas, K.G.; Aldrovandi, G.M.; et al. Longitudinal assessment of COVID-19 vaccine acceptance and uptake among frontline medical workers in Los Angeles, California. Clin. Infect. Dis. 2021, 74, ciab614. [Google Scholar] [CrossRef]
  9. Unroe, K.T.; Evans, R.; Weaver, L.; Rusyniak, D.; Blackburn, J. Willingness of Long-Term Care Staff to Receive a COVID-19 Vaccine: A Single State Survey. J. Am. Geriatr. Soc. 2021, 69, 593–599. [Google Scholar] [CrossRef] [PubMed]
  10. Sun, Y.; Li, B.; Li, N.; Li, B.; Chen, P.; Hao, F.; Sun, C. Acceptance of COVID-19 Vaccine Among High-Risk Occupations in a Port City of China and Multifaceted Strategies for Increasing Vaccination Coverage: A Cross-Sectional Study. Risk Manag. Healthc. Policy 2022, 15, 643–655. [Google Scholar] [CrossRef] [PubMed]
  11. Nafilyan, V.; Dolby, T.; Finning, K.; Morgan, J.; Edge, R.; Glickman, M.; Pearce, N.; van Tongeren, M. Differences in COVID-19 vaccination coverage by occupation in England: A national linked data study. medRxiv 2021, preprint. [Google Scholar] [CrossRef]
  12. Henneberger, P.K.; Cox-Ganser, J.M.; Guthrie, G.M.; Groth, C.P. Estimates of COVID-19 vaccine uptake in major occupational groups and detailed occupational categories in the United States, April–May 2021. Am. J. Ind. Med. 2022, 65, 525–536. [Google Scholar] [CrossRef] [PubMed]
  13. Nowalk, M.P.; Lin, C.J.; Toback, S.L.; Rousculp, M.D.; Eby, C.; Raymund, M.; Zimmerman, R.K. Improving influenza vaccination rates in the workplace: A randomized trial. Am. J. Prev. Med. 2010, 38, 237–246. [Google Scholar] [CrossRef] [PubMed]
  14. Moher, M.; Hey, K.; Lancaster, T. Workplace interventions for smoking cessation. Cochrane Database Syst. Rev. 2003, 2, CD003440, Erratum in Cochrane Database Syst. Rev. 2005, 2, CD003440. [Google Scholar] [CrossRef]
  15. U.S. Census Bureau. State & County Quick Facts: Harris County, Texas 2021. Available online: https://www.census.gov/quickfacts/fact/table/harrisoncountytexas,US/PST045221 (accessed on 7 April 2022).
  16. Census Bureau. Geographic Areas Reference Manual, Chapter 10: Census Tracts and Block Numbering Areas; Census Bureau: Suitland, MD, USA, 1994.
  17. Census. American Community Survey Information Guide. 2017. Available online: https://www.census.gov/content/dam/Census/programs-surveys/acs/about/ACS_Information_Guide.pdf (accessed on 20 April 2019).
  18. Cameron, A.C.; Trivedi, P.K. Regression Analysis of Count Data; Cambridge University Press: Cambridge, UK, 2013; Volume 53. [Google Scholar]
  19. King, W.C.; Rubinstein, M.; Reinhart, A.; Mejia, R. COVID-19 vaccine hesitancy January-May 2021 among 18–64 year old US adults by employment and occupation. Prev. Med. Rep. 2021, 24, 101569. [Google Scholar] [CrossRef] [PubMed]
  20. La Vecchia, C.; Negri, E.; Alicandro, G.; Scarpino, V. Attitudes towards influenza vaccine and a potential COVID-19 vaccine in Italy and differences across occupational groups, September 2020. Med. Lav. 2020, 111, 445–448. [Google Scholar] [CrossRef] [PubMed]
  21. Cutler, D.M.; Lleras-Muney, A. Education and Health: Evaluating Theories and Evidence; National Bureau of Economic Research Working Paper; National Bureau of Economic Research: Cambridge, MA, USA, 2006; p. 12352. [Google Scholar] [CrossRef]
  22. Altman, E.J.; Kiron, D.; Schwartz, J.; Jones, R. The Future of Work is through Workforce Ecosystem; MIT Sloan Management Review: Cambridge, MA, USA, January 2021; ISBN 53863MIT62315. Available online: https://sloanreview.mit.edu/article/the-future-of-work-is-through-workforce-ecosystems/ (accessed on 10 January 2022).
  23. Nguyen, L.H.; Joshi, A.D.; Drew, D.A.; Merino, J.; Ma, W.; Lo, C.H.; Kwon, S.; Wang, K.; Graham, M.S.; Polidori, L.; et al. Self-reported COVID-19 vaccine hesitancy and uptake among participants from different racial and ethnic groups in the United States and United Kingdom. Nat. Commun. 2022, 13, 636, Erratum in Nat. Commun. 2022, 13, 1715. [Google Scholar] [CrossRef] [PubMed]
  24. Ishimaru, T.; Okawara, M.; Ando, H.; Hino, A.; Nagata, T.; Tateishi, S.; Tsuji, M.; Matsuda, S.; Fujino, Y.; CORoNaWork Project. Gender differences in the determinants of willingness to get the COVID-19 vaccine among the working-age population in Japan. Hum. Vaccin. Immunother. 2021, 17, 3975–3981. [Google Scholar] [CrossRef]
  25. Farah, W.; Breeher, L.; Shah, V.; Hainy, C.; Tommaso, C.P.; Swift, M.D. Disparities in COVID-19 vaccine uptake among health care workers. Vaccine 2022, 40, 2749–2754. [Google Scholar] [CrossRef]
Table
Table 1. The US Bureau of Labor Statistics classification of the standard occupational groups and our reclassification for the statistical analysis.
Table 1. The US Bureau of Labor Statistics classification of the standard occupational groups and our reclassification for the statistical analysis.
Original US Standard Occupational GroupsReclassification for Statistical Analysis
1Community/Social Service 1Social Service/Protective Services
2Protective Service
3Healthcare Practitioner/Technician 2Healthcare Practitioner/Technician
4Healthcare Support 3Healthcare Support
5Management 4Business/Management/Legal
6Business/Financial
7Legal
8Computer/Mathematical 5Computer/Engineering/Life/Physical/Social Science
9Architecture/Engineering
10Life/Physical/Social Science
11Arts/Design/Entertainment/Sports/Media 6Arts/Design/Entertainment/Sports/Media
12Office/Administrative Support 7Office/Administrative Support
13Farming/Fishing/Forestry 8Farming/Fishing/Forestry
14Building/Grounds Cleaning/Maintenance 9Building/Installation/Maintenance/Repair
15Installation/Maintenance/Repair
16Construction/Extraction 10Construction/Extraction/Production
17Production
18Transportation/Material Moving 11Transportation/Material Moving
19Food Preparation/Serving Related 12Food Preparation/Serving Related
20Personal Care/Services 13Personal Care/Service
21Sales/Sales Related 14Sales/Sales Related
22Education/Training/Library 15Education/Training/Library
Table
Table 2. The associations between COVID-19 vaccine uptake in Harris County and the percentage of census tract residents that were employed in each of the US standard occupational groups (n = 774 census tracts) up to August 2021.
Table 2. The associations between COVID-19 vaccine uptake in Harris County and the percentage of census tract residents that were employed in each of the US standard occupational groups (n = 774 census tracts) up to August 2021.
Occupational GroupsBivariate Analysis aMultivariable Analysis a
IRR95% CI p-ValueIRR b95% CIp-Value
Social Service/Protective Services0.990.97–0.99< 0.0010.9960.988–1.0050.399
Healthcare Practitioner/Technician1.031.02–1.03< 0.0011.0081.003–1.0140.001
Healthcare Support0.960.96–0.97< 0.0010.9980.989–1.0070.693
Business/Management/Legal1.021.01–1.02< 0.0011.0111.008–1.013< 0.001
Computer/Engineering/Life/Physical/Social Science1.031.02–1.03< 0.0011.0181.013–1.023< 0.001
Arts/Design/Entertainment/Sports/Media1.081.06–1.09< 0.0011.0311.018–1.044< 0.001
Office/Administrative Support 0.990.98–0.99< 0.0010.9970.993–1.0010.089
Farming/Fishing/Forestry 0.930.90–0.96< 0.0010.9890.958–1.0210.485
Building/Installation/Maintenance/Repair0.980.97–0.98< 0.0010.9910.987–0.995< 0.001
Construction/Extraction/Production0.990.98–0.99< 0.0010.9910.988–0.995< 0.001
Transportation/Material Moving0.970.97–0.98< 0.0010.9920.987–0.997 0.002
Food Preparation/Serving Related0.980.97–0.98< 0.0010.9950.990–0.9990.023
Personal Care/Services0.980.97–0.98< 0.0010.9910.985–0.9980.017
Sales/Sales Related1.011.01–0.02< 0.0010.9990.994–1.0040.658
Education/Training/Library1.031.02–1.04< 0.0011.0020.995–1.0080.628
a Each occupational group was entered into a pair of Poisson regression models: in the first model, the vaccine uptake was regressed on just the occupational group alone (bivariate analysis); in the second model, vaccine uptake was regressed on the occupational group alongside four other independent variables (adjusted covariates). b The IRR under multivariable analysis was adjusted for % Hispanic, % Black or African American, % female, and % less than 40 years old.
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MDPI and ACS Style

Sokale, I.; Alvarez, J.; Rosales, O.; Bakota, E.; Amos, C.I.; Badr, H.; Oluyomi, A.O. COVID-19 Vaccine Uptake among US Adults According to Standard Occupational Groups. Vaccines 2022, 10, 1000. https://doi.org/10.3390/vaccines10071000

AMA Style

Sokale I, Alvarez J, Rosales O, Bakota E, Amos CI, Badr H, Oluyomi AO. COVID-19 Vaccine Uptake among US Adults According to Standard Occupational Groups. Vaccines. 2022; 10(7):1000. https://doi.org/10.3390/vaccines10071000

Chicago/Turabian Style

Sokale, Itunu, Juan Alvarez, Omar Rosales, Eric Bakota, Christopher I. Amos, Hoda Badr, and Abiodun O. Oluyomi. 2022. "COVID-19 Vaccine Uptake among US Adults According to Standard Occupational Groups" Vaccines 10, no. 7: 1000. https://doi.org/10.3390/vaccines10071000

APA Style

Sokale, I., Alvarez, J., Rosales, O., Bakota, E., Amos, C. I., Badr, H., & Oluyomi, A. O. (2022). COVID-19 Vaccine Uptake among US Adults According to Standard Occupational Groups. Vaccines, 10(7), 1000. https://doi.org/10.3390/vaccines10071000

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