Impact of applying a diabetes risk score in primary care on change in physical activity: a pragmatic cluster randomised trial

Esther Seidel-Jacobs, Fiona Kohl, Miguel Tamayo, Joachim Rosenbauer, Matthias B Schulze, Oliver Kuss, Wolfgang Rathmann, Esther Seidel-Jacobs, Fiona Kohl, Miguel Tamayo, Joachim Rosenbauer, Matthias B Schulze, Oliver Kuss, Wolfgang Rathmann

Abstract

Aim: There is little evidence of the impact of diabetes risk scores on individual diabetes risk factors, motivation for behaviour changes and mental health. The aim of this study was to investigate the effect of applying a noninvasive diabetes risk score in primary care as component of routine health checks on physical activity and secondary outcomes.

Methods: Cluster randomised trial, in which primary care physicians (PCPs), randomised (1:1) by minimisation, enrolled participants with statutory health insurance without known diabetes, ≥ 35 years of age with a body mass index ≥ 27.0 kg/m2. The German Diabetes Risk Score was applied as add-on to the standard routine health check, conducted in the controls. Primary outcome was the difference in participants' physical activity (International Physical Activity Questionnaire) after 12 months. Secondary outcomes included body mass index, perceived health, anxiety, depression, and motivation for lifestyle change. Analysis was by intention-to-treat principle using mixed models.

Results: 36 PCPs were randomised; remaining 30 PCPs (intervention: n = 16; control: n = 14) recruited 315 participants (intervention: n = 153; controls: n = 162). A slight increase in physical activity was observed in the intervention group with an adjusted mean change of 388 (95% confidence interval: - 235; 1011) metabolic equivalents minutes per week. There were no relevant changes in secondary outcomes.

Conclusions: The application of a noninvasive diabetes risk score alone is not effective in promoting physical activity in primary care.

Clinical trial registration: ClinicalTrials.gov (NCT03234322, registration date: July 31, 2017).

Keywords: Physical activity; Prevention; Primary care; Risk prediction model; Risk score; Type 2 diabetes.

Conflict of interest statement

WR reported having received consulting fees for attending educational sessions or advisory boards from AstraZeneca, Boehringer Ingelheim and NovoNordisk and institutional research grants from AstraZeneca and NovoNordisk. ES-J, FK, MT, JR, MBS and OK have no financial disclosures.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
Flow-chart
Fig. 2
Fig. 2
Odds ratio (OR) on reachability of stages action or maintenance at 12 months follow-up. Results labelled with MI refer to results after multiple across-cluster imputation of missing values

References

    1. Dunkley AJ, Bodicoat DH, Greaves CJ, et al. Diabetes prevention in the real world: effectiveness of pragmatic lifestyle interventions for the prevention of type 2 diabetes and of the impact of adherence to guideline recommendations: a systematic review and meta-analysis. Diabetes Care. 2014;37(4):922–933. doi: 10.2337/dc13-2195.
    1. Hoebel J, Starker A, Jordan S, Richter M, Lampert T. Determinants of health check attendance in adults: findings from the cross-sectional German Health Update (GEDA) study. BMC Public Health. 2014;14(1):913. doi: 10.1186/1471-2458-14-913.
    1. Paulweber B, Valensi P, Lindstrom J, et al. A European evidence-based guideline for the prevention of type 2 diabetes. Horm Metab Res. 2010;42(Suppl 1):S3–36. doi: 10.1055/s-0029-1240928.
    1. Mühlenbruch K, Ludwig T, Jeppesen C, et al. Update of the German Diabetes Risk Score and external validation in the German MONICA/KORA study. Diabetes Res Clin Pract. 2014;104(3):459–466. doi: 10.1016/j.diabres.2014.03.013.
    1. Noble D, Mathur R, Dent T, Meads C, Greenhalgh T. Risk models and scores for type 2 diabetes: systematic review. BMJ. 2011;343:d7163. doi: 10.1136/bmj.d7163.
    1. Lucaroni F, Cicciarella Modica D, Macino M, et al. Can risk be predicted? An umbrella systematic review of current risk prediction models for cardiovascular diseases, diabetes and hypertension. BMJ Open. 2019;9(12):e030234. doi: 10.1136/bmjopen-2019-030234.
    1. Nowak C, Ingelsson E, Fall T. Use of type 2 diabetes risk scores in clinical practice: a call for action. Lancet Diabetes Endocrinol. 2015;3(3):166–167. doi: 10.1016/S2213-8587(14)70261-X.
    1. Dhippayom T, Chaiyakunapruk N, Krass I. How diabetes risk assessment tools are implemented in practice: a systematic review. Diabetes Res Clin Pract. 2014;104(3):329–342. doi: 10.1016/j.diabres.2014.01.008.
    1. American Diabetes Association Classification and diagnosis of diabetes: standards of medical care in diabetes. Diabetes Care. 2021;44(Suppl 1):S15–S33. doi: 10.2337/dc21-S002.
    1. National Institute for Health and Care Excellence (2012, reviewed 2017) Preventing type 2 diabetes: risk identification and interventions for individuals at high risk. London: NICE
    1. Studziński K, Tomasik T, Krzysztoń J, Jóźwiak J, Windak A. Effect of using cardiovascular risk scoring in routine risk assessment in primary prevention of cardiovascular disease: an overview of systematic reviews. BMC Cardiovasc Disord. 2019;19(1):11. doi: 10.1186/s12872-018-0990-2.
    1. Usher-Smith JA, Silarova B, Schuit E, Moons KG, Griffin SJ. Impact of provision of cardiovascular disease risk estimates to healthcare professionals and patients: a systematic review. BMJ Open. 2015;5(10):e008717. doi: 10.1136/bmjopen-2015-008717.
    1. Jacobs E, Tamayo M, Rosenbauer J, Schulze MB, Kuss O, Rathmann W. Protocol of a cluster randomized trial to investigate the impact of a type 2 diabetes risk prediction model on change in physical activity in primary care. BMC Endocr Disord. 2018;18(1):72. doi: 10.1186/s12902-018-0299-2.
    1. Saghaei M, Saghaei S. Implementation of an open-source customizable minimization program for allocation of patients to parallel groups in clinical trials. J Biomed Sci Eng. 2011;4:734–739. doi: 10.4236/jbise.2011.411090.
    1. Paprott R, Muhlenbruch K, Mensink GB, et al. Validation of the German Diabetes Risk Score among the general adult population: findings from the German Health Interview and Examination Surveys. BMJ Open Diabetes Res Care. 2016;4(1):e000280. doi: 10.1136/bmjdrc-2016-000280.
    1. International Physical Activity Questionnaire (IPAQ) group (2005) Guidelines for data processing and analysis of the international physical activity questionnaire (IPAQ)—short and long forms. . Accessed 13 April 2022
    1. De Bruin A, Picavet H, Nossikov A (1996) Health interview survey. Towards harmonization of methods and instruments. WHO Regional Publications, European Series, Copenhagen
    1. Hinz A, Brahler E. Normative values for the hospital anxiety and depression scale (HADS) in the general German population. J Psychosom Res. 2011;71(2):74–78. doi: 10.1016/j.jpsychores.2011.01.005.
    1. Prochaska JO, Velicer WF, Rossi JS, et al. Stages of change and decisional balance for 12 problem behaviors. Health Psychol. 1994;13(1):39–46. doi: 10.1037/0278-6133.13.1.39.
    1. Steptoe A, Kerry S, Rink E, Hilton S. The impact of behavioral counseling on stage of change in fat intake, physical activity, and cigarette smoking in adults at increased risk of coronary heart disease. Am J Public Health. 2001;91(2):265–269. doi: 10.2105/AJPH.91.2.265.
    1. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)–a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–381. doi: 10.1016/j.jbi.2008.08.010.
    1. Godino JG, van Sluijs EM, Marteau TM, Sutton S, Sharp SJ, Griffin SJ. Lifestyle advice combined with personalized estimates of genetic or phenotypic risk of type 2 diabetes, and objectively measured physical activity: a randomized controlled trial. PLoS Med. 2016;13(11):e1002185. doi: 10.1371/journal.pmed.1002185.
    1. Palladino R, Vamos EP, Chang KC-M, Khunti K, Majeed A, Millett C. Evaluation of the diabetes screening component of a national cardiovascular risk assessment programme in England: a retrospective cohort study. Sci Rep. 2020;10(1):1231. doi: 10.1038/s41598-020-58033-3.
    1. Sanchez A, Bully P, Martinez C, Grandes G. Effectiveness of physical activity promotion interventions in primary care: a review of reviews. Prev Med. 2015;76(Suppl):S56–67. doi: 10.1016/j.ypmed.2014.09.012.
    1. Lee PH, Macfarlane DJ, Lam TH, Stewart SM. Validity of the International Physical Activity Questionnaire Short Form (IPAQ-SF): a systematic review. Int J Behav Nutr Phys Act. 2011;8:115. doi: 10.1186/1479-5868-8-115.
    1. Zaccagni L, Toselli S, Barbieri D. Physical activity during COVID-19 lockdown in Italy: a systematic review. Int J Environ Res Public Health. 2021;18(12):6416. doi: 10.3390/ijerph18126416.
    1. Stockwell S, Trott M, Tully M, et al. Changes in physical activity and sedentary behaviours from before to during the COVID-19 pandemic lockdown: a systematic review. BMJ Open Sport Exerc Med. 2021;7(1):e000960. doi: 10.1136/bmjsem-2020-000960.

Source: PubMed

3
Abonnieren