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The origins of ischaemic heart disease are obscure. The article discusses the influence of environment, heredity and diet (especially for consumption). It is then proposed that dietary deficiencies of copper may be a factor that enhances risk of the disease. The evidence for this is discussed.

There is growing evidence to suggest that childhood deprivation is linked to social inequalities and has important consequences for health in later life. Past studies tend to focus on the influence of cumulative deprivation on the risk of developing a particular disease. This study adds to the literature by exploring how deprivation in childhood may be linked to how people (who already have a disease) self-manage their condition in later life. Questionnaires and focus groups were analysed to explore this relationship (n=91) among coronary heart disease patients living in a deprived urban area of Northern England. The results suggest that childhood deprivation may influence health behaviours and lifestyle in later life especially with regard to diet, health locus of control and doctor visits.

The world is shifting towards the fourth industrial revolution (Industry 4.0), symbolising the move to digital, fully automated habitats and cyber-physical systems. Industry 4.0 consists of innovative ideas and techniques in almost all sectors, including Smart health care, which recommends technologies and mechanisms for early prediction of life-threatening diseases. Cardiovascular disease (CVD), which includes stroke, is one of the world’s leading causes of sickness and deaths. As per the American Heart Association, CVDs are a leading cause of death globally, and it is believed that COVID-19 also influenced the health of cardiovascular and the number of patients increases as a result. Early detection of such diseases is one of the solutions for a lower mortality rate. In this work, early prediction models for CVDs are developed with the help of machine learning (ML), a form of artificial intelligence that allows computers to learn and improve on their own without requiring to be explicitly programmed.

The proposed CVD prediction models are implemented with the help of ML techniques, namely, decision tree, random forest, k-nearest neighbours, support vector machine, logistic regression, AdaBoost and gradient boosting. To mitigate the effect of over-fitting and under-fitting problems, hyperparameter optimisation techniques are used to develop efficient disease prediction models. Furthermore, the ensemble technique using soft voting is also used to gain more insight into the data set and accurate prediction models.

The models were developed to help the health-care providers with the early diagnosis and prediction of heart disease patients, reducing the risk of developing severe diseases. The created heart disease risk evaluation model is built on the Jupyter Notebook Web application, and its performance is calculated using unbiased indicators such as true positive rate, true negative rate, accuracy, precision, misclassification rate, area under the ROC curve and cross-validation approach. The results revealed that the ensemble heart disease model outperforms the other proposed and implemented models.

The proposed and developed CVD prediction models aims at predicting CVDs at an early stage, thereby taking prevention and precautionary measures at a very early stage of the disease to abate the predictive maintenance as recommended in Industry 4.0. Prediction models are developed on algorithms’ default values, hyperparameter optimisations and ensemble techniques.

African American men and women suffer from health problems such as hypertension, cardiovascular disease, diabetes, AIDS, sickle cell anemia, and various forms of cancer, often at a higher rate than the rest of the population. There is a need for information about these and other health problems affecting this particular community. This annotated bibliography includes recent articles, books, Internet resources, and Web sites. The audience for this essay includes the layperson, health‐care professionals, and information specialists who wish to provide information to patrons on these important health issues.

The purpose of this article is to clarify the social burden of Japan’s three major diseases including Long-term Care (LTC) burden.

A modification of the Cost of Illness (COI)—the Comprehensive-COI (C-COI) was utilized to estimate three major diseases: cancer, heart disease, and cerebrovascular diseases (CVD). The C-COI consists of five parts: medical direct cost, morbidity cost, mortality cost, formal LTC cost and informal LTC cost. The latter was calculated by two approaches: opportunity cost approach (OC) and replacement approach (RA), which assumed that informal caregivers were substituted by paid caregivers.

The C-COI of cancer, heart disease and CVD in 2017 amounted to 10.5 trillion JPY, 5.2 trillion JPY, and 6.7 trillion JPY, respectively (110 JPY= 1 US$). The mortality cost was preponderant for cancer (61 percent) and heart disease (47.9 percent); while the informal LTC cost was preponderant for CVD (27.5 percent). The informal LTC cost of the CVD in OC amounted to 1.8 trillion JPY; while the RA amounted to 3.0 trillion JPY.

The LTC burden accounted for a significant proportion of the social burden of chronic diseases. The informal care was maintained by unsustainable structures such as the elderly providing care for the elderly. This result can affect health policy decisions.

The C-COI is more appropriate for estimating the social burden of chronic diseases including the LTC burden and can be calculated using governmental statistics.

The question is: should women be encouraged to reduce dietary fats – especially saturated fats – as a measure to prevent cardiovascular disease (i.e. heart disease plus stroke)? Presents evidence to support the conclusion that enhanced levels of blood cholesterol do not indicate enhanced risk of cardiovascular disease in women. Similar evidence supports the conclusion that enhanced blood cholesterol levels do not indicate enhanced risk of all‐cause death, i.e. they do not indicate reduced life expectancy. Hence there is no rational basis for adopting a diet designed to reduce cholesterol, e.g. one based on reduced consumption of saturated fat. These conclusions illustrate the undesirability of pursuing measures to reduce a single disease – in this case coronary heart disease – in isolation from consideration of risk relations for other ailments and for overall health.

The purpose of this paper is to examine if facets of workaholism are associated with a family history of metabolic diseases.

Data on workaholism and family history of health issues were collected, through administration of an online survey, from 194 employees.

Workaholism significantly related to a family history of metabolic diseases.

Future researchers should collect objective disease data, examine work-related moderators as well as potential mediators, and implement longitudinal designs with much larger samples. That said, the data reveal a correlation between workaholism and family history of metabolic disease.

The results provide valuable information to help promote a healthy workforce and to improve employees’ health by reducing workaholic tendencies. They could also help to minimize health-related costs associated with metabolic diseases that could develop in parallel with workaholism, as well as costs in terms of a loss in productivity due absenteeism.

It is, the authors believe, the first study to investigate the relationship between facets of workaholism and family history of health issues that have often been associated with metabolic diseases.

Although much is known about inequalities in the prevalence of CHD, less is known about the barriers experienced in self-managing it. Questionnaires, focus groups, and Internet forums were analyzed to explore obstacles in self-managing CHD. Most people found it difficult and costly to maintain a healthy lifestyle. Gender inequalities included women being more likely to live on their own and with a lower income. Marital status was an issue as several were either caring for an ill spouse or were coping with their recent death. Socio-demographic factors played a key role in influencing people's ability to manage their CHD.

Coronary heart disease, which is sometimes called ischaemic heart disease, is the major cause of death in the United Kingdom. Much more is known, and even more talked about, the relationship between coronary heart disease (CHD) and diet than any other type of medical disorders except for the deficiency diseases.