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Physical Activity Patterns among Individuals with Prediabetes or Type 2 Diabetes across Two Years—A Longitudinal Latent Class Analysis

Author

Listed:
  • Jenny Rossen

    (Department of Health Promoting Science, Sophiahemmet University, Lindstedtsvägen 8, 114 86 Stockholm, Sweden)

  • Maria Hagströmer

    (Department of Health Promoting Science, Sophiahemmet University, Lindstedtsvägen 8, 114 86 Stockholm, Sweden
    Department of Neurobiology, Care Sciences and Society, Division of Physiotherapy, Karolinska Institutet, Alfred Nobels Allé 23, 141 52 Huddinge, Sweden
    Academic Primary Care Center, Region Stockholm, Solnavägen 1E, 104 31 Stockholm, Sweden)

  • Kristina Larsson

    (Department of Health Promoting Science, Sophiahemmet University, Lindstedtsvägen 8, 114 86 Stockholm, Sweden)

  • Unn-Britt Johansson

    (Department of Health Promoting Science, Sophiahemmet University, Lindstedtsvägen 8, 114 86 Stockholm, Sweden
    Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Sjukhusbacken 10, 118 83 Stockholm, Sweden)

  • Philip von Rosen

    (Department of Neurobiology, Care Sciences and Society, Division of Physiotherapy, Karolinska Institutet, Alfred Nobels Allé 23, 141 52 Huddinge, Sweden)

Abstract

Background: This study aimed to identify distinct profiles of physical activity (PA) patterns among individuals with prediabetes or type 2 diabetes participating in a two-year PA trial and to investigate predictors of the profiles. Methods: Data ( n = 168, collected 2013–2020) from the cohort of a randomized trial aimed at increasing PA in individuals with prediabetes and type 2 diabetes were used. PA and sedentary behaviours were assessed by waist-worn ActiGraph GT1M accelerometers at baseline and at 6, 12, 18 and 24 months. Fifteen PA and sedentary variables were entered into a latent class mixed model for multivariate longitudinal outcomes. Multinominal regression analysis modelled profile membership based on baseline activity level, age, gender, BMI, disease status and group randomisation. Results: Two profiles of PA patterns were identified: “Increased activity” ( n = 37, 22%) included participants increasing time in PA and decreasing sedentary time. “No change in activity” ( n = 131, 78%) included participants with no or minor changes. “Increased activity” were younger ( p = 0.003) and more active at baseline ( p = 0.011), compared to “No change in activity”. No other predictor was associated with profile membership. Conclusions: A majority of participants maintained PA and sedentary patterns over two years despite being part of a PA intervention. Individuals improving PA patterns were younger and more active at baseline.

Suggested Citation

  • Jenny Rossen & Maria Hagströmer & Kristina Larsson & Unn-Britt Johansson & Philip von Rosen, 2022. "Physical Activity Patterns among Individuals with Prediabetes or Type 2 Diabetes across Two Years—A Longitudinal Latent Class Analysis," IJERPH, MDPI, vol. 19(6), pages 1-10, March.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:6:p:3667-:d:775165
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    References listed on IDEAS

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    1. Jean-Philippe Chaput & Valerie Carson & Casey E. Gray & Mark S. Tremblay, 2014. "Importance of All Movement Behaviors in a 24 Hour Period for Overall Health," IJERPH, MDPI, vol. 11(12), pages 1-7, December.
    2. Proust-Lima, Cécile & Philipps, Viviane & Liquet, Benoit, 2017. "Estimation of Extended Mixed Models Using Latent Classes and Latent Processes: The R Package lcmm," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 78(i02).
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