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Household food security in Vietnam remains tenuous. We surveyed 552 households to investigate household food insecurity (HFI) in rural districts in the Vietnamese Mekong Delta. HFI prevalence was 34.4% and 48.4% in the last month and last year respectively. Khmer households were twice as likely to experience HFI compared to their Kinh counterparts. The primary factors associated with HFI were weak livelihood assets including lower natural, financial and human assets (being landless, low incomes), physical and social assets (poor market access, social networks), lower kitchen utensil scores, belonging to a minority and experiencing financial, agricultural and extreme weather shocks.

INTRODUCTION: Household food insecurity and inadequate water, sanitation, and hygiene (WASH) contribute to ill health. However, the interactions between household food insecurity, WASH and health have been rarely assessed concurrently. This study investigated compounded impacts of household food insecurity and WASH on self-reported physical and mental health of adults in the Vietnamese Mekong Delta. MATERIALS AND METHODS: This cross-sectional survey interviewed 552 households in one northern and one southern province of the Vietnamese Mekong Delta. The survey incorporated previously validated tools such as the Short Form 12-item Health Survey, Household Food Insecurity Assessment Scale, and the Access and Behavioural Outcome Indicators for Water, Sanitation, and Hygiene. Physical and mental health were quantified using the physical health composite score (PCS) and mental health composite score (MCS), respectively. These measures were the dependent variables of interest for this study. RESULTS: Statistical analysis revealed that household food insecurity and using <50 litres of water per person per day (pppd) were independently associated with lower PCS (p<0.05), after adjusting for socio-economic confounders. Household food insecurity and lack of food availability, using <50 litres of water pppd, and the use of untreated drinking water were associated with lower MCS (p<0.05), with water usage being an effect modifier of the relationship between household food insecurity and MCS. The results indicate that being food insecure and having limited potable quality water had a compounding effect on MCS, compared to being individually either food insecure or having limited water. CONCLUSION: This study is one of only a few that have established a link between potable water availability, food insecurity and poorer physical and mental health. The results also indicate a need to validate national data with fine-scale investigations in less populous regions to evaluate natio

The populations in the vicinity of surface coal mining activities have a higher risk of morbidity due to diseases, such as cardiovascular, respiratory and hypertensive diseases, as well as cancer and diabetes mellitus. Despite the large and historical volume of coal production in Queensland, the main Australian coal mining state, there is little research on the association of coal mining exposures with morbidity in non-occupational populations in this region. This study explored the association of coal production (Gross Raw Output—GRO) with hospitalisations due to six disease groups in Queensland using a Bayesian spatial hierarchical analysis and considering the spatial distribution of the Local Government Areas (LGAs). There is a positive association of GRO with hospitalisations due to circulatory diseases (1.022, 99% CI: 1.002–1.043) and respiratory diseases (1.031, 95% CI: 1.001–1.062) for the whole of Queensland. A higher risk of circulatory, respiratory and chronic lower respiratory diseases is found in LGAs in northwest and central Queensland; and a higher risk of hypertensive diseases, diabetes mellitus and lung cancer is found in LGAs in north, west, and north and southeast Queensland, respectively. These findings can be used to support public health strategies to protect communities at risk. Further research is needed to identify the causal links between coal mining and morbidity in non-occupational populations in Queensland.

The potential impacts of coal mining on health have been addressed by the application of impact assessment methodologies that use the results of qualitative and quantitative analyses to support their conclusions and recommendations. Although human epidemiological analyses can provide the most relevant measures of risk of health outcomes in populations exposed to coal mining by-products, this kind of studies are seldom implemented as part of the impact assessment methods. To review the use of human epidemiological analyses in the methods used to assess the impacts of coal mining, a systematic search in the peer review literature was implemented following the PRISMA protocol. A synthesis analysis identified the methods and the measures used in the selected publications to develop a thematic review and discussion. The major methodological approaches to assess the impacts of coal mining are environmental impact assessment (EIA), health impact assessment (HIA), social impact assessment (SIA) and environmental health impact assessment (EHIA). The measures used to assess the impacts of coal mining on health were classified as the estimates from non-human-based studies such as health risk assessment (HRA) and the measures of risk from human epidemiological analyses. The inclusion of human epidemiological estimates of the populations exposed, especially the general populations in the vicinity of the mining activities, is seldom found in impact assessment applications for coal mining. These methods rather incorporate HRA measures or other sources of evidence such as qualitative analyses and surveys. The implementation of impact assessment methods without estimates of the risk of health outcomes relevant to the potentially exposed populations affects their reliability to address the environmental and health impacts of coal mining. This is particularly important for EIA applications because these are incorporated in regulatory frameworks globally. The effective characterizat

The 17 United Nations’ Sustainable Development Goals (SDGs) form an internationally-agreed agenda for development, and include a dedicated goal for water and sanitation (SDG 6). Yet, the presentation of the SDGs potentially invites appraisal and response ‘goal-by-goal’- to the possible neglect of the mutual influences between them.We applied a systems approach to understand the interrelationships in an Australian context. While there are multiple potential ‘readings’ of these interrelationships, our approach is intended to initiate debate around the SDG commitments. We found the SDGs for global partnerships (SDG 17) and climate action (SDG 13) are enabling influences for the other goals, and the SDG for health (SDG 3) is influenced by all the other goals. Within SDG 6, we found that integrated water resources management target (SDG 6.5) is key to achieving the other targets. Inter-sectoral collaboration by government agencies will be essential to progress achievement of the SDGs. KEYWORDS: Sustainable Development Goals, water and sanitation, systems approach, Australia

Background/Aim: Over the last three decades studies of the effects of coal mining on the health of populations living in the vicinity of coal mining have found substantial associations which could suggest public health impacts. However the expression of the outcomes in these studies do not always clearly align with the International Classification of Diseases (ICD). Health outcomes categorised according to the ICD can be used to identify and assess more specific health impacts. This review aimed to identify the ICD codes of morbidity and mortality in studies of general populations living in the vicinity of coal mining. Methods: Systematic searches of three databases were conducted by two independent researchers to identify studies according to selection criteria (e.g. health outcomes that can be categorised in the ICD). The analysis conducted identified health outcomes and research methods, and the quality of the studies was evaluated. Health outcomes not presented as ICD codes were classified by a medical doctor according to the ICD. Results: Twenty eight studies were selected and reviewed. The majority of studies (93%) found significant association between coal mining and one or more causes of morbidity or mortality. Of those studies, 50% presented health outcomes as ICD codes, and 50% had health outcomes which could be classified according to the ICD. Sixty two codes were identified in 10 ICD chapters. Codes in the chapters: external causes, neoplasms, circulatory, respiratory, and genitourinary systems were identified in studies of mortality. Codes in the chapters: neoplasms, metabolic, eye and skin diseases; congenital abnormalities, circulatory, respiratory, and genitourinary systems and perinatal conditions were identified in studies of morbidity. Conclusions: Our review provided a clear framework of ICD codes to use when scrutinising health-based data sets for the prevalence of morbidity and/or mortality in populations residing in the vicinity of coal mining