Background Antimicrobial misuse is common in low-income and middle-income countries (LMICs), and this practice is a driver of antibiotic resistance. We compared community-based antibiotic access and use practices across communities in LMICs to identify contextually specific targets for interventions to improve antibiotic use practices. Methods We did quantitative and qualitative assessments of antibiotic access and use in six LMICs across Africa (Mozambique, Ghana, and South Africa) and Asia (Bangladesh, Vietnam, and Thailand) over a 2•5-year study period (July 1, 2016-Dec 31, 2018). We did quantitative assessments of community antibiotic access and use through supplier mapping, customer exit interviews, and household surveys. These quantitative assessments were triangulated with qualitative drug supplier and consumer interviews and discussions. Findings Vietnam and Bangladesh had the largest proportions of non-licensed antibiotic dispensing points. For mild illness, drug stores were the most common point of contact when seeking antibiotics in most countries, except South Africa and Mozambique, where public facilities were most common. Self-medication with antibiotics was found to be widespread in Vietnam (55•2% of antibiotics dispensed without prescription), Bangladesh (45•7%), and Ghana (36•1%), but less so in Mozambique (8•0%), South Africa (1•2%), and Thailand (3•9%). Self-medication was considered to be less time consuming, cheaper, and overall, more convenient than accessing them through healthcare facilities. Factors determining where treatment was sought often involved relevant policies, trust in the supplier and the drug, disease severity, and whether the antibiotic was intended for a child. Confusion regarding how to identify oral antibiotics was revealed in both Africa and Asia. Interpretation Contextual complexities and differences between countries with different incomes, policy frameworks, and cultural norms were revealed. These contextual differences render a single strategy inadequate and instead necessitate context-tailored, integrated intervention packages to improve antibiotic use in LMICs as part of global efforts to combat antibiotic resistance. Funding Wellcome Trust and Volkswagen Foundation.

ObjectivesTo explore the levels and trends of household need for caregivers of older people and to explore the impact of potential determinants of psychological burden among caregivers of older people in Thailand.MethodsThe secondary data analysis was performed using the Survey of Older Persons in Thailand 2007, 2011, and 2014 datasets which conducted by the National Statistical Office of Thailand. The household need for caregivers of older persons refers to having at least one older person in the household who needs a caregiver for assistance with activities of daily living. Caregiver mental health, which is confined to the available 2011 data, is defined as a state of psychological burden. Ordinal logistic regression models were used to explore the impact of potential determinants of psychological caregiver burden.ResultsThe household need for caregivers in Thailand tends to be increasing, from 5.0% in 2007 to 6.6% in 2014. The levels of the household need for caregivers were significantly higher in urban areas, Bangkok, and high socioeconomic households. In terms of psychological caregiver burden, the Thai Mental Health Indicators in 2011 produced, on average, a fair level of mental health, but one-fourth of caregivers had poor mental health. Duration of care for older people, household wealth, and functional dependency significantly predict total caregiver burden. Household characteristics are vital in predicting psychological caregiver burden, and the adjusted effect of the fifth quintile of household wealth was high (odds ratio = 2.34; 95% confidence interval = 1.47–3.73).ConclusionThe increasing need for caregiving in households with an older person can lead to a higher caregiver burden, particularly among those caregivers who care for dependent older people in poor households. Longer duration of caregiving is a factor that mitigates this burden.

Background ‘Yaa Chud’ is a non-prescribed poly-pharmaceutical pack containing several types of drugs, including antibiotics and steroids, which can be purchased over the counter in Thailand for self-medication. Although it is illegal, it is still available at some community outlets. This study aimed to understand access to and use of Yaa Chud at the community level in order to raise awareness on its usage and to provide policy recommendations to address the problem. Methods This study employed qualitative methods, including in-depth interviews with 18 drug suppliers and 16 community members, and six focus group discussions. It included inventories from 17 drug suppliers. Data were collected in selected communities of the Kanchanaburi Demographic Surveillance System, located in the western region of Thailand.Thematic analysis was based upon the Health Services Utilization Model and conducted using the Open Code qualitative software program. Results Overcrowding, long waiting times, and a perceived unwelcoming environment at public health-care service outlets were identified as factors that drive people into the private sector, where loose regulation of drug laws facilitates access and use of Yaa Chud. Migrants and older people were most likely to seek and use Yaa Chud, especially for mild illness. Availability, easy access through a user’s network, low cost, and perceived effectiveness were identified as factors that enable access and use of Yaa Chud. Conclusions Though illegal in Thailand, Yaa Chud is likely to remain available for self-medication by community members, due to the persisting demand by the elderly and migrant workers. There is an urgent need to replace these mixed medications with better choices. Safer Yaa Chud may be a preferred, first-line health-care option, which could help reduce congestion in the formal health-care setting. At the same time, enforcement of regulatory compliance needs to be continued in order to stop the supply of unsafe Yaa Chud. Electronic supplementary material The online version of this article (10.1186/s12889-019-7300-5) contains supplementary material, which is available to authorized users.

Background Like many developing countries, Thailand has experienced a rapid rise in obesity, accompanied by a rapid change in occupational structure. It is plausible that these two trends are related, with movement into sedentary occupations leading to increases in obesity. National health examination survey data contains information on obesity and socioeconomic conditions that can help untangle the relationship, but analysis is challenging because of small sample sizes. Methods This paper explores the relationship between occupation and obesity using data on 10,127 respondents aged 20–59 from the 2009 National Health Examination Survey. Obesity is measured using waist circumference. Modelling is carried out using an approach known as Multiple Regression with Post-Stratification (MRP). We use Bayesian hierarchical models to construct prevalence estimates disaggregated by age, sex, education, urban-rural residence, region, and occupation, and use census population weights to aggregate up. The Bayesian hierarchical model is designed to protect against overfitting and false discovery, which is particularly important in an exploratory study such as this one. Results There is no clear relationship between the overall sedentary nature of occupations and obesity. Instead, obesity appears to vary occupation by occupation. For instance, women in professional occupations, and men who are agricultural or fishery workers, have relatively low rates of obesity. Conclusion Bayesian hierarchical models plus post-stratification offers new possibilities for using surveys to learn about complex health issues.

Objectives: To examine the impacts of changes in social determinants of health (SDH) toward changes in cognition. Methods: Longitudinal data came from the Kanchanaburi Demographic Surveillance System (KDSS) collected in 2007 and 2011. Cognitive impairment was measured by category fluency and delayed recall. Generalized estimating equation (GEE) was used to investigate changes in cognition by taking SDH and other variables including age, gender, marital status, education, and depression into the model. Results: GEE revealed longitudinal effects of wealth index and working status against cognition. Older Thais living with richest wealth index (odds ratio [OR] = 0.54; 95% confidence interval [CI] = 0.31-0.94) and still being employed (OR = 0.65; 95% CI = 0.47-0.89) were less likely to have cognitive impairment. Discussion: Poorer wealth index and being unemployed were served as a risk factor for cognitive impairment over time. Increasing age was still the major risk for cognitive impairment.