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Influence of grandchildren on COVID-19 vaccination uptake among older adults in China: a parallel-group, cluster-randomized controlled trial

Nature Aging (2024)Cite this article

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Abstract

The uptake of COVID-19 booster vaccination among older adults in China is suboptimal. Here, we report the results of a parallel-group cluster-randomized controlled trial evaluating the efficacy of promoting COVID-19 booster vaccination among grandparents (≥60 years) through a health education intervention delivered to their grandchildren (aged ≥16 years) in a Chinese cohort (Chinese Clinical Trial Registry: ChiCTR2200063240). The primary outcome was the uptake rate of COVID-19 booster dose among grandparents. Secondary outcomes include grandparents’ attitude and intention to get a COVID-19 booster dose. A total of 202 college students were randomized 1:1 to either the intervention arm of web-based health education and 14 daily reminders (n = 188 grandparents) or control arm (n = 187 grandparents) and reported their grandparents’ COVID-19 booster vaccination status at baseline and 21 days. Grandparents in the intervention arm were more likely to receive COVID-19 booster vaccination compared to control cohort (intervention, 30.6%; control, 16.9%; risk ratio = 2.00 (95% CI, 1.09 to 3.66)). Grandparents in the intervention arm also had greater attitude change (β = 0.28 (95% CI, 0.04 to 0.52)) and intention change (β = 0.32 (95% CI, 0.12 to 0.52)) to receive a COVID-19 booster dose. Our results show that an educational intervention targeting college students increased COVID-19 booster vaccination uptake among grandparents in China.

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Fig. 1: Trial profile.

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Data availability

According to our protocol, the individual deidentified data and documents are not publicly available due to institutional ethics committee regulations but can be made available upon reasonable scientific request to the corresponding author, H.Z., with each request subject to ethical and legislative review from the respective data sources. After internal review and approval, deidentified data and documents will be shared under agreements. The source data, study protocol and statistical analysis plan are provided with this paper. All other data supporting the findings of this study are available from the corresponding author upon reasonable request.

Code availability

The R code used in the analyses is available at Zenodo (10.5281/zenodo.10701551), but this study did not generate new or customized codes or software. The Poisson regression models were fitted using the glm function. The robust standard errors of Poisson models were computed using the glm.cluster function from the miceadds R package. The generalized estimation equation models were computed using the geeglm function from the geepack R package. The multiple imputation was performed using mice R package. The forest plots were created using the forestploter R package.

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Acknowledgments

We thank Prof. Zunyou Wu, late chief epidemiologist from the Chinese Center for Disease Control and Prevention, for his kind support and encouragement to our study. H.Z. is supported by the Natural Science Foundation of China Excellent Young Scientists Fund (82022064). The funder had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We thank our partners at Sun Yat-sen University and Bengbu University. We thank all participants who made this research possible.

Author information

Author notes

  1. These authors contributed equally: J. Bian, W. Zhang, Z. Guo, X. Li, L. Fu.

Authors and Affiliations

  1. School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China

    Junye Bian, Weijie Zhang, Zhihui Guo, Xinyi Li, Leiwen Fu, Zhen Lu, Yinghui Sun, Yanxiao Gao, Yuanyi Chen, Qi Liu & Caijun Sun

  2. School of Medicine, University of Washington, Seattle, WA, USA

    Thomas Fitzpatrick

  3. The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China

    Yinghui Sun

  4. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Yanxiao Gao

  5. Research Institute of Social Development, Southwestern University of Finance and Economics, Chengdu, China

    Longtao He

  6. School of Public Health, Fudan University, Shanghai, China

    Huachun Zou

  7. Shenzhen Campus of Sun Yat-sen University, Shenzhen, China

    Huachun Zou

  8. School of Public Health, Southwest Medical University, Luzhou, China

    Huachun Zou

  9. Kirby Institute, University of New South Wales, Sydney, New South Wales, Australia

    Huachun Zou

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Contributions

H.Z. and J.B. contributed to the study design. J.B., W.Z., Z.G., X.L. and L.F. contributed to data collection, data analysis and manuscript preparation. J.B. and L.F. optimized the statistical analysis method. Z.L., Y.S., Y.G., Y.C., Q.L., L.H., C.S., T.F. and H.Z. reviewed and verified the data in the study. J.B., W.Z., Z.G., X.L. and L.F. contributed equally to this paper. All authors have read and approved the final manuscript.

Corresponding authors

Correspondence to Longtao He, Caijun Sun or Huachun Zou.

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The authors declare no competing interests.

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Nature Aging thanks the anonymous reviewers for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 A subgroup per-protocol analysis of the primary outcome of COVID-19 booster dose uptake among grandparents.

RR = risk ratio. CI = confidence interval. In the forest plot, the points are represented as the point estimate of risk ratio, and the lines are represented as the range of the 95% confidence interval. Model 1 is a Poisson regression model. Model 2 is a Poisson regression model with robust standard error. In the two models, adjustment is made for grandparents’ sex, age, residence, education, history of cohabitation with the enrolled grandchild, living status, frequency of leaving the home, and presence of one or more chronic disease. P value is from interaction tests using Model 2. Analyses are two-sided at 5% significance level.

Source data

Extended Data Fig. 2 A subgroup intention-to-treat analysis of the primary outcome of COVID-19 booster dose uptake among grandparents.

RR = risk ratio. CI = confidence interval. In the forest plot, the points are represented as the point estimate of risk ratio, and the lines are represented as the range of the 95% confidence interval. Model 1 is a Poisson regression model. Model 2 is a Poisson regression model with robust standard error. In the two models, adjustment is made for grandparents’ sex, age, residence, education, history of cohabitation with the enrolled grandchild, living status, frequency of leaving the home, and presence of one or more chronic disease. P value is from interaction tests using Model 2. Analyses are two-sided at 5% significance level.

Source data

Extended Data Fig. 3 Secondary outcome of changes in grandparents’ attitude and intention to get a COVID-19 booster dose.

In the PP set, the number of participants is 147 in the intervention arm and 154 in the control arm. In the ITT set, the number of participants is 188 in the intervention arm and 187 in the control arm. Mean scores in the ITT set are estimated by multiple imputation.

Source data

Supplementary information

Supplementary Information

Supplementary materials of intervention, study protocol, statistical analysis plan and CONSORT 2010 checklist.

Reporting Summary

Supplementary Table 1

Inclusion and exclusion criteria.

Supplementary Table 2

Summary of enrollment.

Supplementary Table 3

Diagram of the study events.

Supplementary Table 4

Diagram of intervention for college students.

Supplementary Table 5

Completer analysis of the study.

Supplementary Table 6

Reliability analysis of the attitude and intention scores among grandparents.

Supplementary Table 7

Sensitivity analysis for the subgroup analysis using generalized estimating equation (GEE) model.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Extended Data Fig. 1

Statistical source data.

Source Data Extended Data Fig. 2

Statistical source data.

Source Data Extended Data Fig. 3

Statistical source data.

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Bian, J., Zhang, W., Guo, Z. et al. Influence of grandchildren on COVID-19 vaccination uptake among older adults in China: a parallel-group, cluster-randomized controlled trial. Nat Aging (2024). https://doi.org/10.1038/s43587-024-00625-z

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