Estimating the stochastic uncertainty in sample-based estimates of infant mortality in Ghana

The Infant Mortality Rate (IMR) is an important population health statistic often used as one of the indicators of the health status of a nation. In many countries lacking adequate vital registration systems, sample methods are used to estimate IMRs. However, evaluations of this approach are rare and the literature contains no assessments of the stochastic uncertainty underlying these estimated IMRs. Stochastic uncertainty reflects the fact that even where the underlying IMR is constant in a small population over time, there is a likelihood of yearly fluctuation in its empirical observations even if it is measured from a complete count of the events of interest. In this study a method is presented that can be used to assess this stochastic uncertainty. We use the country of Ghana as a case study for this purpose. The method, a beta-binomial model, is described, tested for validity, and illustrated using 2014 sample-based estimates of IMR for 13 sample regions in Ghana. As such, the approach we described regarding the revision of sample-based IMR estimates is aimed at taking into account of the stochastic uncertainty while preserving the information concerning the uncertainty due to sampling. In applying the method to Ghana, we find that the sample-based IMR estimates perform well in accounting for stochastic uncertainty and could be applied elsewhere

Estimating the underlying infant mortality rates for small populations, including those reporting zero infant deaths: A case study of counties in California

Infant mortality is an important population health statistic that is often used to make health policy decisions. For a small population, an infant mortality rate is subject to high levels of uncertainty and may not indicate the “underlying” mortality regime affecting the population. This situation leads some agencies to either not report infant mortality for these populations or report infant mortality aggregated over space, time or both. A method is presented for estimating “underlying” infant mortality rates that reflect the intrinsic mortality regimes of small populations. The method is described and illustrated in a case study by estimating IMRs for the 15 counties in California where zero infant deaths are reported at the county level for the period 2009-2011. We know that among these 15 counties there are 50 infant deaths reported at the state level but not for the counties in which they occurred. The method’s validity is tested using a synthetic population in the form of a simulated data set generated from a model life table infant mortality rate, representing Level 23 of the West Family Model Life Table for both sexes. The test indicates that the method is capable of producing estimates that represent underlying rates. In this regard, the method described here may assist in the generation of information about the health status of small populations

Association of temporal factors and suicides in the United States, 2000–2004

The purpose of the study was to examine the association of temporal factors, in particular days of the week and seasons of the year and death from suicide in the United States. Data were pooled from the Multiple Cause of Death Files. Hierarchical logistic regression models were fitted to all deaths occurring in 2000 through 2004 by suicide. The incidence of suicide was significantly higher on Wednesdays, compared to Sunday. Specifically, individuals were 99% more likely to kill themselves on Wednesday than on Sunday. Suicides were more prevalent in the summer months, and they were less likely to occur in winter. The state suicide rate significantly elevated individual suicide risk. The results held even after controlling for the potentially confounding effects of socio-economic and demographic variables at both the individual and state levels. It was concluded that the observed association between seasonality and suicide cannot be discounted as a mere coincidence. Future research ought to focus on integrating individual level data and contextual variables when testing for seasonality effects

Economic factors and suicide rates: associations over time in four countries

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Characteristics of suicide attempters with family history of suicide attempt: a retrospective chart review

<p>Abstract</p> <p>Background</p> <p>Family history of suicide attempt is one of the risks of suicide. We aimed at exploring the characteristics of Japanese suicide attempters with and without a family history of suicide attempt.</p> <p>Methods</p> <p>Suicide attempters admitted to an urban emergency department from 2003 to 2008 were interviewed by two attending psychiatrists on items concerning family history of suicide attempt and other sociodemographic and clinical information. Subjects were divided into two groups based on the presence or absence of a family history of suicide attempt, and differences between the two groups were subsequently analyzed.</p> <p>Results</p> <p>Out of the 469 suicide attempters, 70 (14.9%) had a family history of suicide attempt. A significantly higher rate of suicide motive connected with family relations (odds ratio 2.21, confidence interval 1.18–4.17, <it>p </it>< .05) as well as a significantly higher rate of deliberate self-harm (odds ratio 2.51, confidence interval 1.38–4.57, <it>p </it>< .05) were observed in patients with a family history of suicide compared to those without such history. No significant differences were observed in other items investigated.</p> <p>Conclusion</p> <p>The present study has revealed the characteristics of suicide attempters with a family history of suicide attempt. Further understanding of the situation of such individuals is expected to lead to better treatment provision and outcomes, and family function might be a suitable focus in their treatment.</p

Risk factors for suicide in Hungary: a case-control study

<p>Abstract</p> <p>Background</p> <p>Hungary previously had one of the highest suicide rates in the world, but experienced major social and economic changes from 1990 onwards. We aimed to investigate the antecedents of suicide in Hungary. We hypothesised that suicide in Hungary would be associated with both risk factors for suicide as identified in Western studies, and experiences related to social and economic restructuring.</p> <p>Methods</p> <p>We carried out a controlled psychological autopsy study. Informants for 194 cases (suicide deaths in Budapest and Pest County 2002–2004) and 194 controls were interviewed by clinicians using a detailed schedule.</p> <p>Results</p> <p>Many of the demographic and clinical risk factors associated with suicide in other settings were also associated with suicide in Hungary; for example, being unmarried or having no current relationship, lack of other social contacts, low educational attainment, history of self-harm, current diagnosis of affective disorder (including bipolar disorder) or personality disorder, and experiencing a recent major adverse life event. A number of variables reflecting experiences since economic restructuring were also associated with suicide; for example, unemployment, concern over work propects, changes in living standards, practising religion. Just 20% of cases with evidence of depression at the time of death had received antidepressants.</p> <p>Conclusion</p> <p>Suicide rates in Hungary are falling. Our study identified a number of risk factors related to individual-level demographic and clinical characteristics, and possibly recent societal change. Improved management of psychiatric disorder and self-harm may result in further reductions in suicide rates.</p

Suicide among adults aged 30–49: A psychological autopsy study in Hong Kong

<p>Abstract</p> <p>Background</p> <p>A surge in suicide rates in middle age people in Hong Kong and many Asian countries was recently observed. However, there is a paucity of suicide research on this subgroup of people in Asia.</p> <p>Methods</p> <p>The next-of-kin of 85 suicide cases and 85 community subjects aged 30–49 years were interviewed by a psychological autopsy approach. Information was triangulated by interview notes, coroner's court files, and police investigation reports.</p> <p>Results</p> <p>A multiple logistic regression analysis identified the following risk factors for suicide among the middle age people in Hong Kong: the presence of at least one psychiatric disorder (OR = 37.5, 95% CI 11.5–121.9, p < 0.001), indebtedness (OR = 9.4, 95% CI 2.2–40.8, p < 0.01), unemployment (OR = 4.8, 95% CI 1.3–17.5, p < 0.05), never married (OR = 4.2, 95% CI 1.1–16.3, p < 0.05), and lived alone (OR = 3.9, 95% CI 1.2–13.4, p < 0.05).</p> <p>Conclusion</p> <p>The data show that socio-economical factors had a strong impact on suicide in the target group. Further research is needed to explore any positive qualities that protect the middle-aged from suicide. The prevention of suicide in the middle-aged requires multiple strategies.</p

The interplay between structure and agency in shaping the mental health consequences of job loss

Main themes that emerged from the qualitative exploration of the psychological distress of job loss included stress, changes to perceived control, loss of self-esteem, shame and loss of status, experiencing a grieving process, and financial strain. Drawing on two models of agency we identified the different ways workers employed their agency, and how their agency was enabled, but mainly constrained, when dealing with job loss consequences. Respondents’ accounts support the literature on the moderating effects of economic resources such as redundancy packages. The results suggest the need for policies to put more focus on social, emotional and financial investment to mediate the structural constraints of job loss. Our study also suggests that human agency must be understood within an individual’s whole of life circumstances, including structural and material constraints, and the personal or interior factors that shape these circumstances.The authors acknowledge support from the National Health and Medical Research Council Capacity Building Grant (324724). The research was supported by the SA Department of Health and the SA Department of Families and Communities through the Human Services Research and Innovation Program (HSRIP), and the Australian Research Council Linkage Program (LP0562288), with the Department of Health (DOH) serving as Industry Partner. Professor Fran Baum was supported by an ARC Federation Fellowship and Drs Newman and Ziersch by the SA Premier’s Science and Research Fund

Ancillary human health benefits of improved air quality resulting from climate change mitigation

<p>Abstract</p> <p>Background</p> <p>Greenhouse gas (GHG) mitigation policies can provide ancillary benefits in terms of short-term improvements in air quality and associated health benefits. Several studies have analyzed the ancillary impacts of GHG policies for a variety of locations, pollutants, and policies. In this paper we review the existing evidence on ancillary health benefits relating to air pollution from various GHG strategies and provide a framework for such analysis.</p> <p>Methods</p> <p>We evaluate techniques used in different stages of such research for estimation of: (1) changes in air pollutant concentrations; (2) avoided adverse health endpoints; and (3) economic valuation of health consequences. The limitations and merits of various methods are examined. Finally, we conclude with recommendations for ancillary benefits analysis and related research gaps in the relevant disciplines.</p> <p>Results</p> <p>We found that to date most assessments have focused their analysis more heavily on one aspect of the framework (e.g., economic analysis). While a wide range of methods was applied to various policies and regions, results from multiple studies provide strong evidence that the short-term public health and economic benefits of ancillary benefits related to GHG mitigation strategies are substantial. Further, results of these analyses are likely to be underestimates because there are a number of important unquantified health and economic endpoints.</p> <p>Conclusion</p> <p>Remaining challenges include integrating the understanding of the relative toxicity of particulate matter by components or sources, developing better estimates of public health and environmental impacts on selected sub-populations, and devising new methods for evaluating heretofore unquantified and non-monetized benefits.</p