Background Health Impact Assessment (HIA) is promoted as a decision-informing tool by public health and governmental agencies. HIA is beneficial when carried out as part of policy development but is also valuable as a methodology when a policy is being implemented to identify and understand the wider health and well-being impacts of policy decisions, particularly when a decision needs to be taken rapidly to protect the population. This paper focusses on a HIA of the ‘Staying at Home and Social Distancing Policy’ or ‘lockdown’ in response to the COVID-19 pandemic in Wales conducted by the Welsh national public health institute. It describes the process and findings, captures the learning and discusses how the process has been used to better understand the wider health and well-being impacts of policy decisions beyond direct health harm. It also examines the role of public health institutes in promoting and using HIA. Methods A HIA was conducted following a standard HIA five step process. A literature review was undertaken alongside 15 qualitative semi-structured interviews with key stakeholders, and relevant health and demographic data were collated. The results were triangulated and analysed to form a holistic assessment of the policy decision and its impacts. Results A wide range of major health and well-being impacts of the lockdown in Wales were identified across the determinants of health, which included positive and negative social, economic, environmental and mental well-being impacts beyond the impact on direct health. Populations affected included children and young people, those on low incomes and women as well as those whose health has been directly impacted by COVID-19 such as older people. The work highlighted the benefit that HIA can bring in emphasizing impacts which can inform policy and shared learning with others. Conclusion HIA is a largely underused tool to understand the impact of policy and political decisions, particularly when a decision has been taken at speed. This case study highlights how HIA provide evidence and information for advocacy and further work by public health institutes, health agencies and policy makers.
Health impact assessment (HIA) is a systematic and flexible tool, which is advocated by the World Health Organisation as a method through which to consider the impact of policies on the health and well-being of a population, and the inequalities that may arise because of it. In 2018, the HIA support unit in Wales carried out a comprehensive and unique HIA on the impact of Brexit in Wales. The aims were to understand the differential impacts that Brexit would have on the health and well-being of the population and to provide evidence to inform decision makers across a range of public bodies. It followed a five-step process for HIA and utilised a wide range of evidence sources and health intelligence including both quantitative and qualitative evidence. This paper reflects on the process of carrying out the HIA and the methods used. It discusses the stages of the HIA, and shares the findings and reflections of implementation which will be beneficial to other HIA practitioners and policy makers. It does not concentrate on the findings of the HIA in detail, but focusses on what worked and any challenges encountered. It has been used to progress the practice of HIA in Wales and demonstrates the value of HIA as a method to inform and influence complex decisions.
Background Homelessness is a complex societal and public health issue, with multiple causes and solutions. Efforts to reduce homelessness have tended to focus on crisis, with little attention paid to early intervention and primary prevention. Dealing with homelessness involves both supporting people at risk of homelessness and addressing personal and structural causes throughout the lifecourse, including adverse childhood experiences (ACEs). We examined the relationship between ACEs and homelessness in Wales.Methods We retrospectively analysed data from a 2017 cross-sectional national survey of adults aged 16-69 years, living in Wales (total respondents n=2497), using a stratified random probability sampling methodology. Outcome measures included number of ACEs (0, 1, 2-3, or ≥4) and lived experience of homelessness. The 11 categories of ACEs included childhood abuse (physical, sexual, and emotional); neglect (physical and emotional); parental separation or divorce; exposure to domestic violence; or living in a household affected by alcohol misuse, drug use, mental illness, or where someone is incarcerated. Bivariate analysis, adjusted for sociodemographic variables (age, deprivation, gender, and ethnicity), was used to assess the associations between homelessness and ACEs. FindingsWhen weighted to reflect the Welsh national population using mid-2015 population estimates for lower super output areas by sex, age group, and deprivation quintile, homelessness affected 141 (7•0%) of 2005 people in their lifetime. From the unweighted data (n=2497), of the 2333 participants without lived experience of homelessness, 1259 (54•0%) reported no ACEs, compared with 22 (13•4%) of the 164 with experience of homelessness. By contrast, the proportion of participants who reported four or more ACEs was lower among those without (n=253 [10•8%]) than in those with experience of homelessness (n=82 [50•0%]). Those with four or more ACEs were 16•0 times more likely to report lived experience of homelessness in their adult lives (95% CI 9•73-26•43, p<0•0001). Each ACE type was significantly associated with later homelessness, with the strongest associations seen for physical neglect (adjusted odds ratio 8•0 [95% CI 4•98-12•87], p<0•0001), physical abuse (7•0 [5•00-9•87], p<0•0001), sexual abuse (7•1 [4•69-10•78], p<0•0001), and emotional neglect (6•9 [4•63-10•19], p<0•0001).Interpretation This large study using national, representative data indicates that early intervention that prevents ACEs, combined with a trauma-informed approach that builds resilience in at-risk children and adults, is likely to contribute to reducing and preventing homelessness. Possible limitations include the potential recall bias from retrospective, self-reported data.
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