Backpressure (BP) control was originally used for packet routing in communications networks. Since its first application to network traffic control, it has undergone different modifications to tailor it to traffic problems with promising results. Most of these BP variants are based on an assumption of perfect knowledge of traffic conditions throughout the network at all times, specifically the queue lengths (more accurately, the traffic volumes). However, it has been well established that accurate queue length information at signalized intersections is never available except in fully connected environments. Although connected vehicle technologies are developing quickly, a fully connected environment in the real world is still far. This paper tests the effectiveness of BP control when incomplete or imperfect knowledge about traffic conditions is available. BP control is combined with a speed/density field estimation module suitable for a partially connected environment. The proposed system is referred to as a BP with estimated queue lengths (BP-EQ). The robustness of BP-EQ is tested to varying levels of connected vehicle penetration, and BP-EQ is compared with the original BP (i.e. assuming accurate knowledge of traffic conditions), a real-world adaptive signal controller, and optimized fixed timing control using microscopic traffic simulation with field calibrated data. These results show that with a connected vehicle penetration rate as little as 10%, BP-EQ can outperform the adaptive controller and the fixed timing controller in terms of average delay, throughput, and maximum stopped queue lengths under high demand scenarios.
Background Like many countries in sub-Saharan Africa, Kenya has experienced rapid urbanization in recent years. Despite the distinct socioeconomic and environmental differences, few studies have examined the adherence to movement guidelines in urban and rural areas. This cross-sectional study aimed at examining compliance to the 24-hour movement guidelines and their correlates among children from urban and rural Kenya. Method Children (n = 539) aged 11.1 ± 0.8 years (52% female) were recruited from 8 urban and 8 rural private and public schools in Kenya. Physical activity (PA) and sleep duration were estimated using 24-h raw data from wrist-worn accelerometers. Screen time (ST) and potential correlates were self- reported. Multi-level logistic regression was applied to identify correlates of adherence to combined and individual movement guidelines. Results Compliance with the combined movement guidelines was low overall (7%), and higher among rural (10%) than urban (5%) children. Seventy-six percent of rural children met the individual PA guidelines compared to 60% urban children while more rural children also met sleep guidelines (27% vs 14%). The odds of meeting the combined movement guidelines reduced with age (OR = 0.55, 95% CI = 0.35–0.87, p = 0.01), was greater among those who could swim (OR = 3.27, 95% CI = 1.09–9.83, p = 0.04), and among those who did not engage in ST before school (OR = 4.40, 95% CI = 1.81–10.68, p<0.01). The odds of meeting PA guidelines increased with the number of weekly physical education sessions provided at school (OR = 2.1, 95% CI = 1.36–3.21, p<0.01) and was greater among children who spent their lunch break walking (OR = 2.52, 95% CI = 1.15–5.55, p = 0.02) or running relative to those who spent it sitting (OR = 2.33, 95% CI = 1.27–4.27, p = 0.01). Conclusions Prevalence of meeting movement guidelines among Kenyan children is low and of greatest concern in urban areas. Several correlates were identified, particularly influential were features of the school day, School is thus a significant setting to promote a healthy balance between sleep, sedentary time, and PA.
The prevalence of non-communicable diseases is increasing in lower-middle-income countries as these countries transition to unhealthy lifestyles. The transition is mostly predominant in urban areas. We assessed the association between wealth and obesity in two sub-counties in Nairobi City County, Kenya, in the context of family and poverty. This cross-sectional study was conducted among of 9–14 years old pre-adolescents and their guardians living in low- (Embakasi) and middle-income (Langata) sub-counties. The sociodemographic characteristics were collected using a validated questionnaire. Weight, height, mid-upper arm circumference, and waist circumference were measured using standard approved protocols. Socioeconomic characteristics of the residential sites were accessed using Wealth Index, created by using Principal Component Analysis. Statistical analyses were done by analysis of variance (continuous variables, comparison of areas) and with logistic and linear regression models.A total of 149 households, response rate of 93%, participated, 72 from Embakasi and 77 from Langata. Most of the participants residing in Embakasi belonged to the lower income and education groups whereas participants residing in Langata belonged to the higher income and education groups. About 30% of the pre-adolescent participants in Langata were overweight, compared to 6% in Embakasi (p<0.001). In contrast, the prevalence of adults (mostly mothers) with overweight and obesity was high (65%) in both study areas. Wealth (β = 0.01; SE 0.0; p = 0.003) and income (β = 0.29; SE 0.11; p = 0.009) predicted higher BMI z-score in pre-adolescents. In, pre-adolescent overweight was already highly prevalent in the middle-income area, while the proportion of women with overweight/obesity was high in the low-income area. These results suggest that a lifestyle promoting obesity is high regardless of socioeconomic status and wealth in Kenya. This provides a strong justification for promoting healthy lifestyles across all socio-economic classes.
BACKGROUND The prevalence of non-communicable diseases (NCDs) is increasing in the lower middle-income countries as these countries transition to unhealthy lifestyles which are mostly predominant in urban areas. OBJECTIVE The purpose of this paper is to describe the protocol; design, methods, and study population characteristics of a study explaining non-communicable disease-related behavior in Nairobi City County, Kenya, in the context of family and poverty. METHODS A cross-sectional study was conducted among 149 randomly selected pairs of 9-14 years old pre-adolescents and their guardians living in low- (Kayole) and middle-income (Langata) Sub-counties in Nairobi City County. This multidisciplinary study was conducted in two parts; the quantitative part involved the collection of dietary intake through a validated 12-food group (consisting of 174 foods) 7-day Food Frequency Questionnaire (FFQ) (for the pre-adolescents and their guardians) and two 24-hour recalls conducted on non-consecutive days (weekday and weekend) for the pre-adolescents. A photographic Food Atlas for Kenya Pre-adolescents specifically developed for this study and pilot tested for feasibility was used to estimate food portions. The sociodemographic characteristics were collected using a validated questionnaire. Weight, height, mid-upper arm circumference (MUAC), and waist circumference were measured using standard approved protocols. Physical activity was assessed objectively using waist-worn accelerometers for 24 hours over 8 days and self-reports using a validated questionnaire. Data were collected digitally using Android mobile devices and uploaded to the Open Data Kit (ODK) platform and stored on an online server. Data for the qualitative part of the study was collected through Key Informant Interviews (KIIs) and Focus Group Discussions (FGDs) on cultural and social beliefs related to obesity and physical activity. The data was to allow for triangulation with the quantitative data. The qualitative data were audio-recorded, transcribed, and imported to MAXQDA for analysis. Socioeconomic characteristics of the residential sites were accessed using the Wealth Index similar to the Demographic and Health Surveys (DHS) created using Principal Component Analysis. RESULTS A total of 149 households translating into a response rate of 93% participated in the study; 72 from Kayole and 77 from Langata. The majority of the participants residing in Kayole belonged to the lower income and education groups whereas participants residing in Langata belonged to the higher income and education groups. In Kayole, none of the participants belonged to the highest Wealth Index (highest fifth) whereas in Langata none of the participants belonged to the lowest Wealth Index (lowest fifth). CONCLUSIONS The findings of this research will provide novel and important new data on determinants of NCD-related lifestyles and risk factors in urban populations useful for setting priorities for NCD policy or programmes and further research on identified lifestyle changes in Kenya and other similar countries.
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