METHOD: A generalized linear model (GLM) estimates the relationships between different travel mode indicators (e.g., length of motorway per inhabitants, number of motorcycles per inhabitant, percentage of daily trips on foot and by bicycle, percentage of daily trips by public transport) and the number of passenger transport fatalities. Because this city-level model is developed using data sets from different cities all over the world, the impacts of gross domestic product (GDP) are also included in the model.
CONCLUSIONS: Overall, the results imply that the percentage of daily trips by public transport, the percentage of daily trips on foot and by bicycle, and the GDP per inhabitant have negative relationships with the number of passenger transport fatalities, whereas motorway length and the number of motorcycles have positive relationships with the number of passenger transport fatalities.
OBJECTIVE: The main objective of this study is to consolidate and analyse the dengue case dataset amassed by the e-Dengue web-based information system, developed by the Ministry of Health Malaysia, to improve our epidemiological understanding.
METHODS: We retrieved data from the e-Dengue system and integrated a total of 18,812 cases from 2012 to 2019 (8 years) with meteorological data, geoinformatics techniques, and socio-environmental observations to identify plausible factors that could have caused dengue outbreaks in Ipoh, a hyperendemic city in Malaysia.
RESULTS: The rainfall trend characterised by a linearity of R2 > 0.99, termed the "wet-dry steps", may be the unifying factor for triggering dengue outbreaks, though it is still a hypothesis that needs further validation. Successful mapping of the dengue "reservoir" contact zones and spill-over diffusion revealed socio-environmental factors that may be controlled through preventive measures. Age is another factor to consider, as the platelet and white blood cell counts in the "below 5" age group are much greater than in other age groups.
CONCLUSIONS: Our work demonstrates the novelty of the e-Dengue system, which can identify outbreak factors at high resolution when integrated with non-medical fields. Besides dengue, the techniques and insights laid out in this paper are valuable, at large, for advancing control strategies for other mosquito-borne diseases such as malaria, chikungunya, and zika in other hyperendemic cities elsewhere globally.
DESIGN: A quasi-experimental study comparing 2 groups: (1) integrated maternal health care (MHC) program (with preconception care) and (2) standard MHC program (without preconception care).
SETTING: Maternal health-care clinics in Alvand and Qazvin cities in Qazvin Province, Iran.
PARTICIPANTS: A total of 152 and 247 Iranian women aged 16 to 35 years were enrolled in the integrated MHC and standard MHC program, respectively.
MEASURES: The birth outcomes measured included low birth weight, preterm birth, maternal and neonatal complications, and mode of delivery (normal vaginal delivery and cesarean delivery).
ANALYSIS: Multiple logistic regression was performed to determine the impact of preconception care and risk of adverse birth outcomes with adjusted odds ratios (ORs) as effect sizes.
RESULTS: One hundred forty-seven women in integrated MHC and 218 women in standard MHC completed this study. Preconception care was associated with reduced risk of preterm birth (OR = 0.298; 95% confidence interval [CI] = 0.120-0.743; P = .009), low birth weight (OR = 0.406; 95% CI = 0.169-0.971; P = .043), maternal complication (OR = 0.399; 95% CI = 0.241-0.663; P < .001), and neonatal complications (OR = 0.460; 95% CI = 0.275-0.771; P = .003).
CONCLUSION: The findings of the present study revealed advantages of preconception care with reduced adverse birth outcomes.
Methods: People diagnosed with type 2 diabetes (n=218) were selected from three health care centers, located in different cities of Pakistan. Disease knowledge and self-care practices were assessed by Urdu versions of Diabetes Knowledge Questionnaire (DKQ) and Diabetes Self-Management Questionnaire (DSMQ), using a cross-sectional design. Chi-square and correlation analysis were applied to explore the relationship of disease knowledge with glycemic control and self-care practices. Linear regression was used to explore the predictors for disease knowledge.
Results: Majority of the sample was >45-60 years old (48.8%), suffering from type 2 diabetes mellitus for <5 years (49.5%) and had poor glycemic control (HbA1C≥7%; n=181 participants). Disease knowledge was significantly associated (p<0.05) with patient's gender, level of education, family history of diabetes, nature of euglycemic therapy, and glycemic control. Correlation matrix showed strongly inverse correlations of DKQ with glycated hemoglobin levels (r=-0.62; p<0.001) and strongly positive with DSMQ sum scale (r=0.63; p<0.001). PWD having university-level education (β=0.22; 95% Confidence Interval (CI) 0.189, 0.872; p<0.01), doing job (β=0.22; 95% CI 0.009, 0.908]; p=0.046), and use of oral hypoglycemic agents in combination with insulin (β=-0.16; 95% CI [-1.224, -0.071]; p=0.028) were the significant predictors for disease knowledge.
Conclusion: Disease knowledge significantly correlated with glycated hemoglobin levels and self-care activities of PWD. These findings will help in designing patient-tailored diabetes educational interventions for yielding a higher probability of achieving target glycemic control.