Background Wearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen substantially in recent years. However, there is a shortage of aggregated insights into how wearables have been used in health research. Objective In this review, we aim to broadly overview and categorize the current research conducted with affordable wearable devices for health research. Methods We performed a scoping review to understand the use of affordable, consumer-grade wearables for health research from a population health perspective using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. A total of 7499 articles were found in 4 medical databases (PubMed, Ovid, Web of Science, and CINAHL). Studies were eligible if they used noninvasive wearables: worn on the wrist, arm, hip, and chest; measured vital signs; and analyzed the collected data quantitatively. We excluded studies that did not use wearables for outcome assessment and prototype studies, devices that cost >€500 (US $570), or obtrusive smart clothing. Results We included 179 studies using 189 wearable devices covering 10,835,733 participants. Most studies were observational (128/179, 71.5%), conducted in 2020 (56/179, 31.3%) and in North America (94/179, 52.5%), and 93% (10,104,217/10,835,733) of the participants were part of global health studies. The most popular wearables were fitness trackers (86/189, 45.5%) and accelerometer wearables, which primarily measure movement (49/189, 25.9%). Typical measurements included steps (95/179, 53.1%), heart rate (HR; 55/179, 30.7%), and sleep duration (51/179, 28.5%). Other devices measured blood pressure (3/179, 1.7%), skin temperature (3/179, 1.7%), oximetry (3/179, 1.7%), or respiratory rate (2/179, 1.1%). The wearables were mostly worn on the wrist (138/189, 73%) and cost <€200 (US $228; 120/189, 63.5%). The aims and approaches of all 179 studies revealed six prominent uses for wearables, comprising correlations—wearable and other physiological data (40/179, 22.3%), method evaluations (with subgroups; 40/179, 22.3%), population-based research (31/179, 17.3%), experimental outcome assessment (30/179, 16.8%), prognostic forecasting (28/179, 15.6%), and explorative analysis of big data sets (10/179, 5.6%). The most frequent strengths of affordable wearables were validation, accuracy, and clinical certification (104/179, 58.1%). Conclusions Wearables showed an increasingly diverse field of application such as COVID-19 prediction, fertility tracking, heat-related illness, drug effects, and psychological interventions; they also included underrepresented populations, such as individuals with rare diseases. There is a lack of research on wearable devices in low-resource contexts. Fueled by the COVID-19 pandemic, we see a shift toward more large-sized, web-based studies where wearables increased insights into the developing pandemic, including forecasting models and the effects of the pandemic. Some studies have indicated that big data extracted from wearables may potentially transform the understanding of population health dynamics and the ability to forecast health trends.
Background Delays in care-seeking for childhood illness may lead to more severe outcomes. We evaluated whether community distance from a primary healthcare facility was associated with decreased healthcare utilization in a rural district of northwestern Burkina Faso. Methods We conducted passive surveillance of all government-run primary healthcare facilities in Nouna District, Burkina Faso from March 1 through May 31, 2020. All healthcare visits for children under 5 years of age were recorded on a standardized form for sick children. We recorded the age, sex, and community of residence of the child as well as any diagnoses and treatments administered. We calculated healthcare utilization per 100 child-months by linking the aggregate number of visits at the community level to the community’s population of children under 5 months per a census that was conducted from August 2019 through February 2020. We calculated the distance between each community and its corresponding healthcare facility and assessed the relationship between distance and the rate of healthcare utilization. Results In 226 study communities, 12,676 primary healthcare visits were recorded over the three-month period. The median distance between the community and primary healthcare facility was 5.0 km (IQR 2.6 to 6.9 km), and median number of healthcare visits per 100 child-months at the community level was 6.7 (IQR 3.7 to 12.3). The rate of primary healthcare visits declined with increasing distance from clinic (Spearman’s rho − 0.42, 95% CI − 0.54 to − 0.31, P < 0.0001). This relationship was similar for cause-specific clinic visits (including pneumonia, malaria, and diarrhea) and for antibiotic prescriptions. Conclusions We documented a distance decay effect between community distance from a primary healthcare facility and the rate of healthcare visits for children under 5. Decreasing distance-related barriers, for example by increasing the number of facilities or targeting outreach to more distant communities, may improve healthcare utilization for young children in similar settings.
BackgroundWearable devices may generate valuable data for global health research for low- and middle-income countries (LMICs). However, wearable studies in LMICs are scarce. This study aims to investigate the use of consumer-grade wearables to generate individual-level data in vulnerable populations in LMICs, focusing on the acceptability (quality of the devices being accepted or even liked) and feasibility (the state of being workable, realizable, and practical, including aspects of data completeness and plausibility).MethodsWe utilized a mixed-methods approach within the health and demographic surveillance system (HDSS) to conduct a case study in Nouna, Burkina Faso (BF). All HDSS residents older than 6 years were eligible. N = 150 participants were randomly selected from the HDSS database to wear a wristband tracker (Withings Pulse HR) and n = 69 also a thermometer patch (Tucky thermometer) for 3 weeks. Every 4 days, a trained field worker conducted an acceptability questionnaire with participants, which included questions for the field workers as well. Descriptive and qualitative thematic analyses were used to analyze the responses of study participants and field workers.ResultsIn total, n = 148 participants were included (and n = 9 field workers). Participant's acceptability ranged from 94 to 100% throughout the questionnaire. In 95% of the cases (n = 140), participants reported no challenges with the wearable. Most participants were not affected by the wearable in their daily activities (n = 122, 83%) and even enjoyed wearing them (n = 30, 20%). Some were concerned about damage to the wearables (n = 7, 5%). Total data coverage (i.e., the proportion of the whole 3-week study duration covered by data) was 43% for accelerometer (activity), 3% for heart rate, and 4% for body shell temperature. Field workers reported technical issues like faulty synchronization (n = 6, 1%). On average, participants slept 7 h (SD 3.2 h) and walked 8,000 steps per day (SD 5573.6 steps). Acceptability and data completeness were comparable across sex, age, and study arms.ConclusionWearable devices were well-accepted and were able to produce continuous measurements, highlighting the potential for wearables to generate large datasets in LMICs. Challenges constituted data missingness mainly of technical nature. To our knowledge, this is the first study to use consumer-focused wearables to generate objective datasets in rural BF.
BackgroundBiannual, mass azithromycin distribution has previously been shown to reduce all-cause child mortality in sub-Saharan Africa. Subgroup analysis suggested that the strongest effects were in the youngest children, leading to the hypothesis that targeting younger age groups might be an effective strategy to prevent mortality. We present the methods of two randomized controlled trials designed to evaluate mass and targeted azithromycin distribution for the prevention of child mortality in Burkina Faso, West Africa.Methods/designThe Child Health with Azithromycin Treatment (CHAT) study consists of two nested, randomized controlled trials. In the first, communities are randomized in a 1:1 fashion to biannual, mass azithromycin distribution or placebo. The primary outcome is under-5 all-cause mortality measured at the community level. In the second, children attending primary healthcare facilities during the first 5–12 weeks of life for a healthy child visit (e.g., for vaccination) are randomized in a 1:1 fashion to a single orally administered dose of azithromycin or placebo. The primary outcome is all-cause mortality measured at 6 months of age. The trial commenced enrollment in August 2019.DiscussionThis study is expected to provide evidence on two health systems delivery approaches (mass and targeted treatment) for azithromycin to prevent all-cause child mortality. The results will inform global and national policies related to azithromycin for the prevention of child mortality.Trial registrationClinicalTrials.gov, ID: NCT03676764. Registered on 19 September 2018; prospectively registered pre results.
As the epidemiological transition progresses throughout sub-Saharan Africa, life lived with diseases is an increasingly important part of a population’s burden of disease. The burden of disease of climate-sensitive health outcomes is projected to increase considerably within the next decades. Objectively measured, reliable population health data is still limited and is primarily based on perceived illness from recall. Technological advances like non-invasive, consumer-grade wearable devices may play a vital role in alleviating this data gap and in obtaining insights on the disease burden in vulnerable populations, such as heat stress on human cardiovascular response. The overall goal of this study is to investigate whether consumer-grade wearable devices are an acceptable, feasible and valid means to generate data on the individual level in low-resource contexts. Three hundred individuals are recruited from the two study locations in the Nouna health and demographic surveillance system (HDSS), Burkina Faso, and the Siaya HDSS, Kenya. Participants complete a structured questionnaire that comprises question items on acceptability and feasibility under the supervision of trained data collectors. Validity will be evaluated by comparing consumer-grade wearable devices to research-grade devices. Furthermore, we will collect demographic data as well as the data generated by wearable devices. This study will provide insights into the usage of consumer-grade wearable devices to measure individual vital signs in low-resource contexts, such as Burkina Faso and Kenya. Vital signs comprising activity (steps), sleep (duration, quality) and heart rate (hr) are important measures to gain insights on individual behavior and activity patterns in low-resource contexts. These vital signs may be associated with weather variables—as we gather them from weather stations that we have setup as part of this study to cover the whole Nouna and Siaya HDSSs—in order to explore changes in behavior and other variables, such as activity, sleep, hr, during extreme weather events like heat stress exposure. Furthermore, wearable data could be linked to health outcomes and weather events. As a result, consumer-grade wearables may serve as a supporting technology for generating reliable measurements in low-resource contexts and investigating key links between weather occurrences and health outcomes. Thus, wearable devices may provide insights to better inform mitigation and adaptation interventions in these low-resource settings that are direly faced by climate change-induced changes, such as extreme weather events.
Background Although climate change is one of the biggest global health threats, individual-level and short-term data on direct exposure and health impacts are still scarce. Wearable electronic devices (wearables) present a potential solution to this research gap. Wearables have become widely accepted in various areas of health research for ecological momentary assessment, and some studies have used wearables in the field of climate change and health. However, these studies vary in study design, demographics, and outcome variables, and existing research has not been mapped. Objective In this review, we aimed to map existing research on wearables used to detect direct health impacts and individual exposure during climate change–induced weather extremes, such as heat waves or wildfires. Methods We conducted a scoping review according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework and systematically searched 6 databases (PubMed [MEDLINE], IEEE Xplore, CINAHL [EBSCOhost], WoS, Scopus, Ovid [MEDLINE], and Google Scholar). The search yielded 1871 results. Abstracts and full texts were screened by 2 reviewers (MK and IM) independently using the inclusion and exclusion criteria. The inclusion criteria comprised studies published since 2010 that used off-the-shelf wearables that were neither invasive nor obtrusive to the user in the setting of climate change–related weather extremes. Data were charted using a structured form, and the study outcomes were narratively synthesized. Results The review included 55,284 study participants using wearables in 53 studies. Most studies were conducted in upper–middle-income and high-income countries (50/53, 94%) in urban environments (25/53, 47%) or in a climatic chamber (19/53, 36%) and assessed the health effects of heat exposure (52/53, 98%). The majority reported adverse health effects of heat exposure on sleep, physical activity, and heart rate. The remaining studies assessed occupational heat stress or compared individual- and area-level heat exposure. In total, 26% (14/53) of studies determined that all examined wearables were valid and reliable for measuring health parameters during heat exposure when compared with standard methods. Conclusions Wearables have been used successfully in large-scale research to measure the health implications of climate change–related weather extremes. More research is needed in low-income countries and vulnerable populations with pre-existing conditions. In addition, further research could focus on the health impacts of other climate change–related conditions and the effectiveness of adaptation measures at the individual level to such weather extremes.
Background The current COVID-19 pandemic affects the entire world population and has serious health, economic and social consequences. Assessing the prevalence of COVID-19 through population-based serological surveys is essential to monitor the progression of the epidemic, especially in African countries where the extent of SARS-CoV-2 spread remains unclear. Methods A two-stage cluster population-based SARS-CoV-2 seroprevalence survey was conducted in Bobo-Dioulasso and in Ouagadougou, Burkina Faso, Fianarantsoa, Madagascar and Kumasi, Ghana between February and June 2021. IgG seropositivity was determined in 2,163 households with a specificity improved SARS-CoV-2 Enzyme-linked Immunosorbent Assay. Population seroprevalence was evaluated using a Bayesian logistic regression model that accounted for test performance and age, sex and neighbourhood of the participants. Results Seroprevalence adjusted for test performance and population characteristics were 55.7% [95% Credible Interval (CrI) 49·0; 62·8] in Bobo-Dioulasso, 37·4% [95% CrI 31·3; 43·5] in Ouagadougou, 41·5% [95% CrI 36·5; 47·2] in Fianarantsoa, and 41·2% [95% CrI 34·5; 49·0] in Kumasi. Within the study population, less than 6% of participants performed a test for acute SARS-CoV-2 infection since the onset of the pandemic. Conclusions High exposure to SARS-CoV-2 was found in the surveyed regions albeit below the herd immunity threshold and with a low rate of previous testing for acute infections. Despite the high seroprevalence in our study population, the duration of protection from naturally acquired immunity remains unclear and new virus variants continue to emerge. This highlights the importance of vaccine deployment and continued preventive measures to protect the population at risk.
Background Given the high risk of infectious mortality among children with severe acute malnutrition (SAM), the World Health Organization recommends routine administration of a broad-spectrum antibiotic like amoxicillin as part of the management of uncomplicated SAM. However, evidence for the efficacy of amoxicillin to improve nutritional recovery or reduce mortality has been mixed. With a long half-life and evidence of efficacy to reduce mortality in high-risk populations, azithromycin is a potential alternative to amoxicillin in the management of SAM. In this pilot study, we aim to compare the efficacy of azithromycin to amoxicillin to improve nutritional outcomes in children with uncomplicated SAM. Methods This pilot randomized controlled trial will enroll 300 children with uncomplicated SAM from 6 Centre de Santé et de Promotion Sociale in the Boromo health district in Burkina Faso. Eligible children are randomized to receive a single directly observed dose of oral azithromycin or a 7-day course of oral amoxicillin in addition to the standard package of care for uncomplicated SAM. Enrolled children are followed weekly until nutritional recovery, and all children return for a final study visit at 8 weeks after enrollment. Anthropometric indicators, vital status, and clinical outcomes are monitored at each visit and compared by arm. Primary feasibility outcomes include enrollment potential, refusals, loss to follow-up, and completeness of data collection. The primary clinical outcome is weight gain (g/kg/day) over the 8-week study period. Discussion This pilot trial will establish the feasibility of conducting a full-scale randomized controlled trial to evaluate alternative antibiotics in this setting and provide preliminary evidence for the efficacy of azithromycin compared to amoxicillin to improve outcomes for children with SAM. Trial registration This trial was first registered on clinicaltrials.gov on 26 June 2018 (NCT03568643).
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