Objectives: This study aims to assess sample selection bias in mobile phone survey estimates of fertility and under-5 mortality.
Design: With data from the Demographic and Health Surveys, we use logistic regressions to identify sociodemographic correlates of mobile phone ownership and access, and Poisson regressions to estimate the association between mobile phone ownership (or access) and fertility and under-5 mortality estimates. We evaluate the potential reasons why estimates by mobile phone ownership differ using a set of behavioural characteristics.
Setting: 34 low-income and middle-income countries, mostly in sub-Saharan Africa.
Participants: 534 536 women between the ages of 15 and 49.
Outcome Measures: Under-5 mortality rate (U5MR) and total fertility rate (TFR).
Results: Mobile phone ownership ranges from 23.6% in Burundi to 96.7% in Armenia. The median TFR ratio and U5MR ratio between the non-owners and the owners of a mobile phone are 1.48 and 1.29, respectively. Fertility and mortality rates would be biased downwards if estimates are only based on women who own or have access to mobile phones. Estimates of U5MR can be adjusted through poststratification using age, educational level, area of residence, wealth and marital status as weights. However, estimates of TFR remain biased even after adjusting for these covariates. This difference is associated with behavioural factors (eg, contraceptive use) that are not captured by the poststratification variables, but for which there are also differences between mobile phone owners and non-owners.
Conclusions: Mobile phone surveys need to collect data on sociodemographic background characteristics to be able to weight and adjust mortality estimates ex post facto. Fertility estimates from mobile phone surveys will be biased unless further research uncovers the mechanisms driving the bias.
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http://dx.doi.org/10.1136/bmjopen-2023-071791 | DOI Listing |
Nutrients
January 2025
Department of Community Medicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400349 Cluj-Napoca, Romania.
Background/objectives: This study aimed to investigate the lifestyle and the behavioral factors that influence the nutritional status of adolescents from Transylvania, Romania.
Methods: The Global School-Based Student Health Survey (GSHS) was used to collect data from 900 adolescents between 11 and 18 years old from the Transylvania region, Romania. This study assessed nutritional status by calculating BMI indicators adjusted to Z-Score, cut-off points according to the World Health Organization (WHO), using self-reported weight and height; perceived health status; food vulnerability; physical activity; addictive behaviors (cigarette, alcohol and drug consumption); number of hours spent in front of the computer/phone; hand and oral hygiene; sitting time/day; and sleep.
Polymers (Basel)
January 2025
State Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China.
Vibration sensors are integral to a multitude of engineering applications, yet the development of low-cost, easily assembled devices remains a formidable challenge. This study presents a highly sensitive flexible vibration sensor, based on the piezoresistive effect, tailored for the detection of high-dynamic-range vibrations and accelerations. The sensor's design incorporates a polylactic acid (PLA) housing with cavities and spherical recesses, a polydimethylsiloxane (PDMS) membrane, and electrodes that are positioned above.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Computer Engineering, Dongseo University, Busan 47011, Republic of Korea.
Choosing nutritious foods is essential for daily health, but finding recipes that match available ingredients and dietary preferences can be challenging. Traditional recommendation methods often lack personalization and accurate ingredient recognition. Personalized systems address this by integrating user preferences, dietary needs, and ingredient availability.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Artifcial Intelligence, Chung-Ang University, Heukseok-dong, Dongjak-gu, Seoul 06974, Republic of Korea.
Sensor-based gesture recognition on mobile devices is critical to human-computer interaction, enabling intuitive user input for various applications. However, current approaches often rely on server-based retraining whenever new gestures are introduced, incurring substantial energy consumption and latency due to frequent data transmission. To address these limitations, we present the first on-device continual learning framework for gesture recognition.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Institute of Sport Science, University of Applied Sciences Wiener Neustadt, 2700 Wiener Neustadt, Austria.
Striking velocity is a key performance indicator in striking-based combat sports, such as boxing, Karate, and Taekwondo. This study aims to develop a low-cost, accelerometer-based system to measure kick and punch velocities in combat athletes. Utilizing a low-cost mobile phone in conjunction with the PhyPhox app, acceleration data was collected and analyzed using a custom algorithm.
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