The association of body mass index with quality of life and working ability:a Finnish population-based study

Abstract Purpose: The impact of obesity on quality of life (QoL) and working ability vary in different dimensions. This study investigated the association of obesity with QoL and working ability in Finnish adults. Comorbidities as associative factors were also characterised. Methods: This cross-sectional study included 4956 randomly selected adults. QoL (EUROHIS-QOL 8 total score and individual components), perceived physical and psychological working ability, and sick leave days were analysed in different body mass index (BMI) groups. Regression models were used to study the role of comorbidities as associative factors. Results: EUROHIS-QOL 8 total score was significantly lower in BMI group 25.0–29.9 kg/m² (4.01; 95% confidence interval 3.97–4.05), BMI 30.0–34.9 kg/m² (3.85; 3.79–3.91), BMI 35.0–39.9 kg/m² (3.75; 3.66–3.85), and BMI ≥ 40.0 kg/m² (3.73; 3.46–4.00) compared to individuals with normal (18.5–24.9 kg/m²) BMI (4.08; 4.04–4.12). Individuals with obesity (BMI ≥ 30.0 kg/m²) rated their QoL lower than individuals with normal BMI in seven of the eight EUROHIS-QOL 8 components. A lesser proportion of individuals (53–73%) with obesity rated their physical working ability as very or fairly good compared to individuals with normal BMI (90%, p values < 0.001). The psychological working ability was rated as very or fairly good by 71–75% of individuals with obesity compared to 85% of individuals with normal BMI (p = 0.008 and p = 0.001 in individuals with BMI 30.0–34.9 and BMI 35.0–39.9 kg/m², respectively). Conclusions: Obesity was negatively associated with both physical and psychological components of QoL, even after accounting for obesity-related comorbidities. Obesity treatment can benefit from a holistic approach that considers these multifaceted associations

Field measurement for antenna configuration comparison in challenging NLOS locations

Abstract This paper has two main objectives. First, it describes the practical challenges of field trials and proposes a developed test method. Second, the test method is used to compare the uplink (UL) performance with different antenna technologies when user equipment (UE) does not have a line of sight (LOS) to the evolved node B. Both passive and active antenna configurations were used in the performance evaluation. Modern cellular networks have high demands for capacity, reliability, and availability. The verification of a network’s configuration and technological features is essential to guarantee network performance, and the performance of a network must be verified by the laboratory testing or field trials; such trials produce the experimental knowledge of technology features and configurations. Technological and environmental factors must also be considered before performing mobile network field testing. This paper showed that moving UE produces more reliable and repeatable results than measurements with stationary UE. Our antenna configuration comparison study revealed that in the UL direction, active antenna system beam control could significantly increase the UL capacity in non-LOS conditions