JMIR Publications

ABSTRACT

Background:

Cardiovascular diseases, cancers, chronic respiratory diseases, and diabetes are the main noncommunicable diseases (NCDs). These NCDs share four modifiable risk factors (tobacco use, harmful use of alcohol, physical inactivity, and unhealthy diet), and are referred to as NCD4 hereafter. An important part of United Nations Sustainable Development Goal target 3.4 is to reduce premature mortality from NCD4 by 33% by 2030, relative to 2015 levels. Surveillance of the NCD4 risk factors is crucial to prevent premature death from NCD4. In Norway, there has been a lack of annual, data on these four modifiable risk factors from a nationally, representative sample.

Objective:

Our main objective was to develop a smartphone-based Information Communication Technology (ICT) solution with functionalities for collecting data annually, on the four modifiable risk factors. The secondary objective was to collect nationally, representative data.

Methods:

During a two-year period, The Norwegian Centre for E-health Research, UiT The Arctic University of Norway, and Healthcom, a private enterprise, designed a feasibility study. We piloted the “Health and Disease” study, which included a smartphone-based solution, a website, and two smartphone surveys, during fall 2019. We developed an ICT solution with functionalities for capturing sensitive data from smartphones, receiving, and handling data in accordance with the general data protection regulations. The main survey comprised 26 questions: eight on socio-economic factors, 17 concerning the four risk factors and one regarding current/previous NCDs. For answers to the continuous and categorical variables, a keyboard for filling in numbers and pull-down menus, were displayed, respectively. The non-responder survey comprised nine statements that could be answered with (yes, no). We used short message service (SMS) as means of contact. For the main survey, we invited 11000 men and women, aged 16-69 years, selected randomly from the Norwegian National Population Registry, 1000 from each of the eleven counties. For the non-responder survey, we invited a random sample of 100 non-responders from each of the counties, altogether 1100 persons. All data, except county of residence, were self-reported. We calculated the distribution for the selected variables overall and by sex. We used means, with standard deviations (± SD), medians with range and percentages.

Results:

The response rate was 21.9% (n=2303/11000) of which 61.7% (1397/2263) were women. The median age (range) for men was 52 (16-69) years and for women 48 (16-69) years. The main reported reason for non-participation was that the sender of the initial SMS was unknown.

Conclusions:

We successfully developed and piloted a smartphone-based ICT solution for collecting data, annually, on the four modifiable risk factors for the NCD4s from a random sample of the population. One in five responded, thus our secondary objective to collect nationally, representative data may not have been achieved.