Asthma remains a leading cause of illness, where primary care can assist to reduce hospitalisations through prevention, controlling acute episodes, and overall management of asthma. In Victoria, Asthma hospitalisations were as high as 3.1 hospitalisations per 1000 population in 1993–94. The primary aims of this study are to: determine if changes in asthma hospitalisations have occurred between 2010 and 2015; determine the key factors that impact asthma hospitalisation over time; and verify whether rural and urban asthma hospitalisations are disparate. A secondary aim of the study is to compare 2010–2015 results with asthma data prior to 2010. Hospital separation data from 1 July 2010 to 30 June 2015 were obtained through the Victorian Admitted Episodes Dataset and other agencies. Data included sex, age, Local Government Area, private or public patient, length of stay, and type of discharge. Asthma and predictor variables were analysed according to hospital separation rates after adjusting for smoking and sex. Hierarchical multiple regression examined the association between asthma and predictor variables. During the study period, 49,529 asthma hospital separations occurred, of which 77.5% were in metropolitan hospitals, 55.4% hospital separations were aged 0–14 years, and 21.7% were privately funded. State-wide hospital separations were 1.85 per 1000 population and were consistently higher in metropolitan compared to rural areas (1.93 vs 1.64 per 1000 population). When data among metropolitan adults aged 15 and over were analysed, an increase in the proportion of smokers in the population was reflected by an increase in the number of hospital separations (Adj OR 1.035). Further, among rural and metropolitan children aged 0–14 the only predictor of asthma hospital separations was sex, where metropolitan male children had higher odds of separation than metropolitan females of the same age (Adj OR 4.297). There was no statistically meaningful difference for separation rates between males and females in rural areas. We demonstrated a higher overall hospital separation rate in metropolitan Victoria. For children in metropolitan areas, males were hospitalised at higher rates than females, while the inverse was demonstrated for children residing in rural areas. Therefore, optimising asthma management requires consideration of the patient’s age, gender and residential context. Primary health care may play a leading role in increasing health literacy for patients in order to improve self-management and health-seeking behaviour.

Data is scarce on early life exposure to arsenic and its association with malnutrition during infancy. This study followed the nutritional status of a cohort of 120 infants from birth to 9 months of age in an arsenic contaminated area in Bangladesh. Anthropometric data was collected at 3, 6 and 9 months of the infant’s age for nutritional assessment whereas arsenic exposure level was assessed via tube well drinking water arsenic concentration at the initiation of the study. Weight and height measurements were converted to Z-scores of weight for age (WAZ-underweight), height for age (HAZ-stunting), weight for height (WHZ-wasting) for children by comparing with WHO growth standard. Arsenic exposure levels were categorized as <50 μg/L and ≥50 μg/L. Stunting rates (<−2 SD) were 10% at 3 months and 44% at both 6 and 9 months. Wasting rates (<−2 SD) were 23.3% at 3 months and underweight rates (<−2 SD) were 25% and 10% at 3 and 6 months of age, respectively. There was a significant association of stunting with household drinking water arsenic exposure ≥50 μg/L at age of 9 months (p = 0.009). Except for stunting at 9 months of age, we did not find any significant changes in other nutritional indices over time or with levels of household arsenic exposure in this study. Our study suggests no association between household arsenic exposure and under-nutrition during infancy; with limiting factors being small sample size and short follow-up. Difference in stunting at 9 months by arsenic exposure at ≥50 μg/L might be a statistical incongruity. Further longitudinal studies are warranted to establish any association.