Study design and sample size:
A prospective cohort study with 1-year follow-up will be performed in collaboration with the municipality of Hjørring, Denmark. A total sample size of 500 participants is expected. This was chosen due to economical and administrative reasons of the municipality contributing with personnel to include participants and collect data on predictors. Data for the development and internal validation of the model will originate from the same cohort.
Study setting, participants, data collectors, process of recruitment and data collection:
According to Danish legislation on health and social services, Danish municipalities are responsible for developing and initiating prophylactic and health-promoting initiatives for their senior citizens. This is done through different authorities in the municipality (e.g. preventive-home-visits, senior activity centres). Also, the municipality of Hjørring administers a local hall for citizens together with general- and patient associations. Therefore, data collection will be performed in participants' own homes through preventive-home-visits, at senior activity centres and at the local hall in the municipality of Hjørring, Denmark.
Predictors:
Data collection of predictors will be performed at baseline. The following predictors were chosen by an expert panel. Reasons are stated at each predictor. First, a brief summary on the process of how predictors were selected will be given followed by a short description of each predictor.
\- Predictor selection process: A feasibility study. This model is intended for health care professionals in a non-clinical setting, in this case the municipality of Hjørring with a setting consisting of homes and activity centres. Therefore, it needs to be time-efficient, low-cost and practicable. In order to ease implementation if the model is successful in accuracy, the predictors for data collection was chosen by an expert panel on the basis of scientific value and experiences from a feasibility study performed as a precursor for this study.
The feasibility study investigated the feasibility of measuring a set of predictors, selected by the expert panel, with regards to time-consumption and user experiences both from participants and data collectors in order to ensure participant and public involvement. These predictors constituted the basis from which final selection for the prospective cohort study was performed.
In order to collect data on predictors in a time-efficient way. It was decided to collect these both by tests performed by data collectors and questionnaires filled out by study participants. All results from tests and questionnaire will be typed into REDCap (Research Electronic Data Capture, Vanderbilt University, Nashville, USA) electronic data capture tool hosted at Region Nordjylland, Denmark.
Tests:
• Arrhythmias: The investigator's study will be the first to investigate the prevalence of arrhythmias in a Danish population of older adults (+75 years old) by performing data collection in participants' own environments (i.e. own homes and activity centres). All participants will receive 5 days of 2-lead continuous heart rhythm monitoring (E-patch system, BioTelemetry Inc, Denmark).
• Lower limb reaction time: This was chosen since a slow reaction time was found in earlier studies to increase the risk of falling.12 Measurements will be performed using a Nintendo Wii Balance Board with appropriate software Fysiometer (Bronderslev, Denmark).
• Unilateral lower extremity strength: This was chosen since a poor lower strength in lower extremities was found in earlier studies to increase the risk of falling. Measurements will be performed using a Nintendo Wii Balance Board with appropriate software Fysiometer (Bronderslev, Denmark).
• Grip strength: This was chosen since a poor grip strength was found in earlier studies to increase the risk of frailty, which is associated to increased fall risk. Measurements will be performed using a Nintendo Wii Balance Board with appropriate software Fysiometer (Bronderslev, Denmark).
• Balance with dual-tasking: This was chosen since a poor dual-tasking ability was found in earlier studies to an increased fall risk. Measurements will be performed using a Nintendo Wii Balance Board with appropriate software Fysiometer (Bronderslev, Denmark).31 Simultaneously, participants will be instructed mention as many things one can buy in a supermarket, while attempting to stand still on the board.
• Walking speed: This was chosen since a poor gait speed was found in earlier studies to an increased fall risk. Participants will be instructed to do a 4-meter walk at regular speed. Time spent will be noted using a stop watch. The fastest of the two measurements will be selected for further analysis.
• Physical activity: This will be measured using an accelerometer incorporated in the hearth rhythm monitoring device.
Questionnaire:
The following list specifies predictors of falls and participant characteristics that will be included in the questionnaire.
* Age.
* Gender.
* Comorbidities.
* Medication.
* Educational level.
* Status of living.
* Prior falls.
* Walking aids.
* Alcohol consumption.
* Using multifocal lenses.
* Having dogs or cats in the household.
* Health-related quality of life using EQ-5D-3L by the EuroQol group
* Nutrition status.
* Symptoms of urinary incontinence, pain when walking and dizziness.
* Patient self-assessment as a measure of self-awareness of fall risk: Do you think that you could fall during the next year?
* Fear of falling using Short FES-I 7 item.
* Depression using Geriatric Depression Scale 4 item.
* Frailty using Tilburg Frailty Indicator.
* Activities of Daily Living using Vulnerable Elders Survey
* Orientation-Memory-Concentration test performed over the telephone
Blinding: Due to nature of the study design, all assessments of predictors for the outcome to be predicted, future falls, will be blinded.
