How community ecology links natural mortality, growth, and production of fish populations

Size-spectrum theory is used to show that (i) predation mortality is a decreasing function of individual size and proportional to the consumption rate of predators; (ii) adult natural mortality M is proportional to the von Bertalanffy growth constant K; and (iii) productivity rate P/B is proportional to the asymptotic weight W8 -1/3. The constants of proportionality are specified using individual level parameters related to physiology or prey encounter. The derivations demonstrate how traditional fisheries theory can be connected to community ecology. Implications for the use of models for ecosystem-based fisheries management are discussed.

Malignancy and mortality in a population-based cohort of patients with coeliac disease or 'gluten sensitivity'

Aim: To determine the risk of malignancy and mortality in patients with a positive endomysial or anti-gliadin antibody test in Northern Ireland.

Methods: A population-based retrospective cohort study design was used. Laboratory test results used in the diagnosis of coeliac disease were obtained from the Regional Immunology Laboratory, cancer statistics from the Northern Ireland Cancer Registry and mortality statistics from the General Registrar Office, Northern Ireland. Age standardized incidence ratios of malignant neoplasms and standardized mortality ratios of all-cause and cause-specific mortality were calculated.

Results: A total of 13 338 people had an endomysial antibody and/or an anti-gliadin antibody test in Northern Ireland between 1993 and 1996. There were 490 patients who tested positive for endomysial antibodies and they were assumed to have coeliac disease. There were 1133 patients who tested positive for anti-gliadin anti-bodies and they were defined as gluten sensitive. Malignant neoplasms were not significantly associated with coeliac disease; however, all-cause mortality was significantly increased following diagnosis. The standardized incidence and mortality ratios for non-Hodgkin's lymphoma were increased in coeliac disease patients but did not reach statistical significance. Lung and breast cancer incidence were significantly lower and all-cause mortality, mortality from malignant neoplasms, non-Hodgkin's lymphoma and digestive system disorders were significantly higher in gluten sensitive patients compared to the Northern Ireland population.

Conclusion: Patients with coeliac disease or gluten sensitivity had higher mortality rates than the Northern Ireland population. This association persists more than one year after diagnosis in patients testing positive for anti-gliadin antibodies. Breast cancer is significantly reduced in the cohort of patients with gluten sensitivity. © 2007 The WJG Press. All rights reserved.

Habitat for Humanity: Calibrating Best Practice Against the MDGs

Poverty alleviation lies at the heart of contemporary international initiatives on development. The key to development is the creation of an environment in which people can develop their potential, leading productive, creative lives in accordance with their needs, interests and faith. This entails, on the one hand, protecting the vulnerable from things that threaten their survival, such as inadequate nutrition, disease, conflict, natural disasters and the impact of climate change, thereby enhancing the poor’s capabilities to develop resilience in difficult conditions. On the other hand, it also requires a means of empowering the poor to act on their own behalf, as individuals and communities, to secure access to resources and the basic necessities of life such as water, food, shelter, sanitation, health and education. ‘Development’, from this perspective, seeks to address the sources of human insecurity, working towards ‘freedom from want, freedom from fear’ in ways that empower the vulnerable as agents of development (not passive recipients of benefaction).

Recognition of the magnitude of the problems confronted by the poor and failure of past interventions to tackle basic issues of human security led the United Nations (UN) in September 2000 to set out a range of ambitious, but clearly defined, development goals to be achieved by 2015. These are known as the Millennium Development Goals (MDGs). The intention of the UN was to mobilise multilateral international organisations, non-governmental organisations and the wider international community to focus attention on fulfilling earlier promises to combat global poverty. This international framework for development prioritises: the eradication of extreme poverty and hunger; achieving universal primary education; promoting gender equality and empowering women; reducing child mortality; improving maternal health; combating HIV/AIDS, malaria and other diseases; ensuring environmental sustainability; and developing a global partnership for development. These goals have been mapped onto specific targets (18 in total) against which outcomes of associated development initiatives can be measured and the international community held to account. If the world achieves the MDGs, more than 500 million people will be lifted out of poverty. However, the challenges the goals represent are formidable. Interim reports on the initiative indicate a need to scale-up efforts and accelerate progress.
Only MDG 7, Target 11 explicitly identifies shelter as a priority, identifying the need to secure ‘by 2020 a significant improvement in the lives of at least 100 million slum dwellers’. This raises a question over how Habitat for Humanity’s commitment to tackling poverty housing fits within this broader international framework designed to allievate global poverty. From an analysis of HFH case studies, this report argues that the processes by which Habitat for Humanity tackles poverty housing directly engages with the agenda set by the MDGs. This should not be regarded as a beneficial by-product of the delivery of decent, affordable shelter, but rather understood in terms of the ways in which Habitat for Humanity has translated its mission and values into a participatory model that empowers individuals and communities to address the interdependencies between inadequate shelter and other sources of human insecurity. What housing can deliver is as important as what housing itself is.

Examples of the ways in which Habitat for Humanity projects engage with the MDG framework include the incorporation of sustainable livelihoods strategies, up-grading of basic infrastructure and promotion of models of good governance. This includes housing projects that have also offered training to young people in skills used in the construction industry, microfinanced loans for women to start up their own home-based businesses, and the provision of food gardens. These play an important role in lifting families out of poverty and ensuring the sustainability of HFH projects. Studies of the impact of improved shelter and security of livelihood upon family life and the welfare of children evidence higher rates of participation in education, more time dedicated to study and greater individual achievement. Habitat for Humanity projects also typically incorporate measures to up-grade the provision of basic sanitation facilities and supplies of safe, potable drinking water. These measures not only directly help reduce mortality rates (e.g. diarrheal diseases account for around 2 million deaths annually in children under 5), but also, when delivered through HFH project-related ‘community funds’, empower the poor to mobilise community resources, develop local leadership capacities and even secure de facto security of tenure from government authorities.

In the process of translating its mission and values into practical measures, HFH has developed a range of innovative practices that deliver much more than housing alone. The organisation’s participatory model enables both direct beneficiaries and the wider community to tackle the insecurities they face, unlocking latent skills and enterprise, building sustainable livelihood capabilities. HFH plays an important role as a catalyst for change, delivering through the vehicle of housing the means to address the primary causes of poverty itself. Its contribution to wider development priorities deserves better recognition. In calibrating the success of HFH projects in terms of units completed or renovated alone, the significance of the process by which HFH realises these outcomes is often not sufficiently acknowledged, both within the organisation and externally. As the case studies developed in the report illustrate, the methodologies Habitat for Humanity employs to address the issue of poverty housing within the developing world, place the organisation at the centre of a global strategic agenda to address the root causes of poverty through community empowerment and the transformation of structures of governance.

Given this, the global network of HFH affiliates constitutes a unique organisational framework to faciliate sharing resources, ideas and practical experience across a diverse range of cultural, political and institutional environments. This said, it is apparent that work needs to be done to better to faciliate the pooling of experience and lessons learnt from across its affiliates. Much is to be gained from learning from less successful projects, sharing innovative practices, identifying strategic partnerships with donors, other NGOs and CBOs, and engaging with the international development community on how housing fits within a broader agenda to alleviate poverty and promote good governance.

House value as an indicator of cumulative wealth is strongly related to morbidity and mortality risk in older people: a census-based cross-sectional and longitudinal study

Background: There has been relatively little research into health inequalities in older populations. This may be partly explained by the difficulty in identifying appropriate indicators of socio-economic status for older people. Ideally, indicators of socio-economic status to be used in studies of health inequalities in older populations should incorporate some measure of life-time socio-economic standing, and house value may fill this role. This study examined whether an indicator of accumulated wealth based on a combination of housing tenure and house value was a strong predictor of ill-health in older populations.
Methods: A total of 191 848 people aged =65 years and not living in communal establishments were identified from the 2001 Northern Ireland Census and followed for 5 years. Self-reported health and mortality risk by housing tenure/house value groupings were examined while controlling for a range of other demographic and socio-economic characteristics.
Results: Housing tenure/house value was highly correlated with other indicators of socio-economic status. Public-sector renters had worse self-reported health and higher mortality rates than owner occupiers but significant gradients were also found between those living in the highest-and lowest-valued owner-occupier properties. The relationship between housing tenure and value was unchanged by adjustment for indicators of social support and quality of the physical environment. Adjustment for limiting long-term illness and self-reported health at baseline narrowed but did not eliminate the health gains associated with living in more expensive housing.
Conclusions: House value of residence is an accessible and powerful indicator of accumulated wealth that is highly correlated with current health status and predictive of future mortality risk in older populations.

Impact of PSA testing and prostatic biopsy on cancer incidence and mortality: comparative study between the Republic of Ireland and Northern Ireland

Objectives: To investigate the impact of different PSA testing policies and health-care systems on prostate cancer incidence and mortality in two countries with similar populations, the Republic of Ireland (RoI) and Northern Ireland (NI).

Methods: Population-level data on PSA tests, prostate biopsies and prostate cancer cases 1993–2005 and prostate cancer deaths 1979–2006 were compiled. Annual percentage change (APC) was estimated by joinpoint regression.

Results: Prostate cancer rates were similar in both areas in 1994 but increased rapidly in RoI compared to NI. The PSA testing rate increased sharply in RoI (APC = +23.3%), and to a lesser degree in NI (APC = +9.7%) to reach 412 and 177 tests per 1,000 men in 2004, respectively. Prostatic biopsy rates rose in both countries, but were twofold higher in RoI. Cancer incidence rates rose significantly, mirroring biopsy trends, in both countries reaching 440 per 100,000 men in RoI in 2004 compared to 294 in NI. Median age at diagnosis was lower in RoI (71 years) compared to NI (73 years) (p < 0.01) and decreased significantly over time in both countries. Mortality rates declined from 1995 in both countries (APC = -1.5% in RoI, -1.3% in NI) at a time when PSA testing was not widespread.

Conclusions: Prostatic biopsy rates, rather than PSA testing per se, were the main driver of prostate cancer incidence. Because mortality decreases started before screening became widespread in RoI, and mortality remained low in NI, PSA testing is unlikely to be the explanation for declining mortality.

Mortality from cerebrovascular disease in a cohort of 23 000 patients with insulin-treated diabetes

Background and Purpose-Disease of the cardiovascular system is the main cause of long-term complications and mortality in patients with type I (insulin-dependent) and type 11 (non-insulin-dependent) diabetes. Cerebrovascular mortality rates have been shown to be raised in patients with type 11 diabetes but have not previously been reported by age and sex in patients with type I diabetes.

Breast cancer mortality in neighbouring European countries with different level of breast screening but similar access to treatment: An analysis of WHO mortality database

Objective: To compare trends in breast cancer mortality within three pairs of neighbouring European countries in relation to implementation of screening. Design: Retrospective trend analysis.
Setting: Three country pairs (Northern Ireland (United Kingdom) v Republic of Ireland, the Netherlands v Belgium and Flanders (Belgian region south of the Netherlands), and Sweden v Norway).
Data sources: WHO mortality database on cause of death and data sources on mammography screening, cancer treatment, and risk factors for breast cancer mortality.
Main outcome measures: Changes in breast cancer mortality calculated from linear regressions of log transformed, age adjusted death rates. Joinpoint analysis was used to identify the year when trends in mortality for all ages began to change.
Results: From 1989 to 2006, deaths from breast cancer decreased by 29% in Northern Ireland and by 26% in the Republic of Ireland; by 25% in the Netherlands and by 20% in Belgium and 25% in Flanders; and by 16% in Sweden and by 24% in Norway. The time trend and year of downward inflexion were similar between Northern Ireland and the Republic of Ireland and between the Netherlands and Flanders. In Sweden, mortality rates have steadily decreased since 1972, with no downward inflexion until 2006. Countries of each pair had similar healthcare services and prevalence of risk factors for breast cancer mortality but differing implementation of mammography screening, with a gap of about 10-15 years.
Conclusions: The contrast between the time differences in implementation of mammography screening and the similarity in reductions in mortality between the country pairs suggest that screening did not play a direct part in the reductions in breast cancer mortality.

Explaining young mortality

Stochastic modeling of mortality rates focuses on fitting linear models to logarithmically adjusted mortality data from the middle or late ages. Whilst this modeling enables insurers to project mortality rates and hence price mortality products it does not provide good fit for younger aged mortality. Mortality rates below the early 20's are important to model as they give an insight into estimates of the cohort effect for more recent years of birth. It is also important given the cumulative nature of life expectancy to be able to forecast mortality improvements at all ages. When we attempt to fit existing models to a wider age range, 5-89, rather than 20-89 or 50-89, their weaknesses are revealed as the results are not satisfactory. The linear innovations in existing models are not flexible enough to capture the non-linear profile of mortality rates that we see at the lower ages. In this paper we modify an existing 4 factor model of mortality to enable better fitting to a wider age range, and using data from seven developed countries our empirical results show that the proposed model has a better fit to the actual data, is robust, and has good forecasting ability.

A Dynamic Factor Approach to Mortality Modelling

Longevity risk has become one of the major risks facing the insurance and pensions markets globally. The trade in longevity risk is underpinned by accurate forecasting of mortality rates. Using techniques from macroeconomic forecasting, we propose a dynamic factor model of mortality that fits and forecasts mortality rates parsimoniously.We compare the forecasting quality of this model and of existing models and find that the dynamic factor model generally provides superior forecasts when applied to international mortality data. We also show that existing multifactorial models have superior fit but their forecasting performance worsens as more factors are added. The dynamic factor approach used here can potentially be further improved upon by applying an appropriate stopping rule for the number of static and dynamic factors. 

Mortality in Barrett's oesophagus:Results from a population based study

Background: Patients with Barrett's oesophagus have an increased risk of oesophageal adenocarcinoma but this cancer only accounts for a small proportion of deaths in these patients. Other causes of death are reportedly raised in this group. We examined cause specific mortality among individuals in a population based Barrett's oesophagus register. Methods: We constructed a register of all patients diagnosed with columnar mucosa (including specialised intestinal metaplasia) of the oesophagus within Northern Ireland between 1993 and 1999. Deaths occurring within this cohort until 31 December 2000 were identified and mortality rates were compared with the general population. Results: Overall mortality was not raised in Barrett's patients. During 7413 person years of follow up in 2373 patients there were 253 deaths (standardised mortality ratio (SMR) 96 (95% confidence interval (CI) 84-107)). Mortality from oesophageal cancer was raised in patients with specialised intestinal metaplasia (SMR 774 (95% CI 317-1231 )) but only 4.7% of patients died from this cancer. Mortality from stroke (SMR 65 (95% CI 37-93)) was significantly lower than the general population while mortality from non-cancerous digestive system diseases was significantly higher (SMR 211 (95% CI 111-311)). Mortality rates from all other causes were similar to those of the general population. Conclusions: This study demonstrates that the overall mortality rate in patients with Barrett's oesophagus is closely similar to that of the general population. Oesophageal cancer mortality was raised but is an uncommon cause of death in these patients who also appear to have a reduced risk of death from stroke.

Comparing the decline in coronary heart disease and stroke mortality in neighbouring countries with different healthcare systems

Objective
To examine age and gender specific trends in coronary heart disease (CHD) and stroke mortality in two neighbouring countries, the Republic of Ireland (ROI) and Northern Ireland (NI). Design Epidemiological study of time trends in CHD and stroke mortality.

Setting/patients
The populations of the ROI and NI, 1985–2010.

Interventions
None.

Main outcome measures
Directly age standardised CHD and stroke mortality rates were calculated and analysed using joinpoint regression to identify years where the slope of the linear trend changed significantly. This was performed separately for specific age groups (25–54, 55–64, 65–74 and 75–84 years) and by gender. Annual percentage change (APC) and 95% CIs are presented.

Results
There was a striking similarity between the two countries, with percentage change between 1985 and 1989 and between 2006 and 2010 of 67% and 69% in
CHD mortality, and 64% and 62% in stroke mortality for the ROI and NI, respectively. However, joinpoint analysis identified differences in the pace of change between the two countries. There was an accelerated pace of decline (negative APC) in mortality for both CHD and stroke in both countries from the mid-1990s (APC ROI −8% (95% CI −9.5 to 6.5) and NI −6.6% (−6.9 to −6.3)), but the accelerated decrease started later for CHD mortality in the ROI. In recent years, a levelling off in CHD mortality was observed in the 25–54 year age group in NI and in stroke mortality for men and women in the ROI.

Conclusions
While differences in the pace of change in mortality were observed at different time points, similar, substantial decreases in CHD and stroke mortality were achieved between 1985 and 1989 and between 2006 and 2010 in the ROI and NI despite important differences in health service structures. There is evidence of a levelling in mortality rates in some groups in recent years.

Is Mortality Spatial or Social?

Mortality modelling for the purposes of demographic forecasting and actuarial pricing is generally done at an aggregate level using national data. Modelling at this level fails to capture the variation in mortality within country and potentially leads to a mis-specification of mortality forecasts for a subset of the population. This can have detrimental effects for pricing and reserving in the actuarial context. In this paper we consider mortality rates at a regional level and analyse the variation in those rates. We consider whether variation in mortality rates within a country can be explained using local economic and social variables. Using Northern Ireland data on mortality and measures of deprivation we identify the variables explaining mortality variation. We create a population polarisation variable and find that this variable is significant in explaining some of the variation in mortality rates. Further, we consider whether spatial and non-spatial models have a part to play in explaining mortality differentials.