METHODS: 12-year observational study of a UK Fracture Liaison Service (outpatient secondary care setting). Database analyses of the records of adult outpatients aged 50 years and older with fragility fractures. Weather data were obtained from the UK's national Meteorological Office. In the seasonality analyses, we tested for the association between months and seasons (determinants), respectively, and outpatient attendances, by analysis of variance (ANOVA) and Tukey's test. In the meteorological analyses, the determinants were mean temperature, mean daily maximum and minimum temperature, number of days of rain, total rainfall and number of days of frost, per month, respectively. We explored the association of each meteorological variable with outpatient attendances, by regression models.

RESULTS: The Fracture Liaison Service recorded 25,454 fragility fractures. We found significant monthly and seasonal variation in attendances for fractures of the: radius or ulna; humerus; ankle, foot, tibia or fibula (ANOVA, all p-values <0.05). Fractures of the radius or ulna and humerus peaked in December and winter. Fractures of the ankle, foot, tibia or fibula peaked in July, August and summer. U-shaped associations were showed between each temperature parameter and fractures. Days of frost were directly associated with fractures of the radius or ulna (p-value <0.001) and humerus (p-value 0.002).

RESEARCH AIMS: To (1) describe exploratory estimates of greenhouse gas emission factors for all infant and young child milk formula products and (2) estimate national greenhouse gas emission association with commercial milk formulas sold in selected countries in the Asia Pacific region.

METHOD: We used a secondary data analysis descriptive design incorporating a Life Cycle Assessment (LCA) concepts and methodology to estimate kg CO2 eq. emissions per kg of milk formula, using greenhouse gas emission factors for milk powder, vegetable oils, and sugars identified from a literature review. Proportions of ingredients were calculated using FAO Codex Alimentarius guidance on milk formula products. Estimates were calculated for production and processing of individual ingredients from cradle to factory gate. Annual retail sales data for 2012-2017 was sourced from Euromonitor International for six purposively selected countries; Australia, South Korea, China, Malaysia, India, Philippines.

RESULTS: Annual emissions for milk formula products ranged from 3.95-4.04 kg CO2 eq. Milk formula sold in the six countries in 2012 contributed 2,893,030 tons CO2 eq. to global greenhouse gas emissions. Aggregate emissions were highest for products (e.g., toddler formula), which dominated sales growth. Projected 2017 emissions for milk formula retailed in China alone were 4,219,052 tons CO2 eq.

METHODS: The most important climatic factors that contribute to dengue outbreaks were identified in the current work. Correlation analyses were performed in order to determine these factors and these factors were used as input parameters for machine learning models. Top five machine learning classification models (Bayes network (BN) models, support vector machine (SVM), RBF tree, decision table and naive Bayes) were chosen based on past research. The models were then tested and evaluated on the basis of 4-year data (January 2010 to December 2013) collected in Malaysia.

RESULTS: This research has two major contributions. A new risk factor, called the TempeRain factor (TRF), was identified and used as an input parameter for the model of dengue outbreak prediction. Moreover, TRF was applied to demonstrate its strong impact on dengue outbreaks. Experimental results showed that the Bayes Network model with the new meteorological risk factor identified in this study increased accuracy to 92.35% for predicting dengue outbreaks.