To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
This chapter explores the evolving and contested definitions of health, emphasizing its multidimensional and dynamic nature. In particular, it distinguishes between health conditions, health needs and health priorities. Health conditions are a broad set of situations, with both subjective and objective measures, related to present and future structures and functions of the human body, as well as the capacity to adapt to both the physical and social environment in which every human being lives. Health conditions occur on a gradient from an idealized state of perfect health to the total absence of health, which is death. Health needs are a subset of health conditions – they are the health conditions that require care. Using examples such as obesity, autism and fibromyalgia, the chapter shows how definitions can shift over time.
People with depressive disorder have increased premature mortality and higher rates of diabetes mellitus than general population. Evidence shows that diabetes may further increase their risk of premature death from diabetes-related complications, especially cardiovascular diseases (CVDs). Earlier studies examining depression-associated outcomes in diabetes patients have shown mixed results and were hindered by important limitations, especially the use of self-reported questionnaires to ascertain depression, causing misclassification bias by identifying subclinical symptoms or diabetes distress. Associations of depression with specific diabetes complications have not been systematically evaluated. This meta-analysis aimed to investigate the risk of mortality and complications among patients with depression and co-occurring diabetes (depression-diabetes group) relative to patients with diabetes-only (diabetes-only group), on their all-cause mortality rates, and if applicable cause-specific mortality rates, and occurrence of specific diabetes complications.
Methods
We systematically reviewed and quantitatively synthesized diabetes-related outcomes in patients with depression by searching Embase, MEDLINE, PsycInfo and Web-of-Science from inception to 20 December 2024, and included studies that examined mortality and complication outcomes in depression-diabetes group relative to diabetes-only group. Results were synthesized by random-effects meta-analytic models, with stratified-analyses (subgroup analyses and meta-regression) by study-level characteristics, including age, gender, study period, geographic region, follow-up duration and nature of diabetes sample. The study was registered with PROSPERO (CRD42024595145).
Results
Twenty-six studies were identified from nine geographic regions. Regarding mortality risk, depression-diabetes group exhibited increased risks of all-cause mortality (RR = 1.30 [95% CI: 1.21–1.39]) and CVD-specific mortality (1.15 [1.02–1.29]) relative to diabetes-only group. Regarding complication risk, depression-diabetes group showed increased risk of complications (1.28 [1.18–1.40]) relative to diabetes-only group, especially in incident-diabetes sample signifying advanced disease stage upon presentation, with stratified-analyses showing higher risk of metabolic complications (1.63 [1.33–1.99]) and cardiovascular complications (1.20 [1.11–1.29]), and lower likelihood of retinopathy (0.84 [0.76–0.94]), albeit comparable rates of cerebrovascular complications (1.36 [0.99–1.87]), nephropathy (1.09 [0.93–1.27]) and peripheral-vascular complications (0.97 [0.79–1.18]). Both overall mortality and complication risks were present in various regions and persisted over time. Heterogeneities were noted and could not be entirely explained by stratified analyses.
Conclusions
Our study demonstrated that patients with depression and co-occurring diabetes were associated with elevated overall mortality risk and complication risk (particularly metabolic and cardiovascular-complications) than non-depressed counterparts, suggesting an overall poorer glycemic control that might eventually drive their earlier death. Comprehensive and multipronged interventions are needed for individualized risk estimation of diabetes-related outcomes, with consequent early interventions to minimize the avoidable physical morbidity and premature mortality in this vulnerable population.
This chapter explores how elements of ‘sense of place’—place dependence, identity, and attachment—are essential for creating liveable, healthy communities. It discusses how community social interaction, cohesion (sense of community), and collective action enhance liveability. Addressing frequent shortcomings in defining and measuring ‘liveability’, the authors integrate recent geospatial population health research to establish connections between place, health, development, and policy. A framework linking community cognitions, attachment, and social action in response to environmental threats and disruptions is applied to brief case studies from Bulgaria and the United States illustrating varied community responses aimed at healthier, more liveable environments. Recommendations include leveraging liveability audits to evaluate local and regional impacts of disruptions, articulating threats to community identity and economic wellbeing, and embedding psychological conceptions of place into public-health and urban-planning assessments. This integrated, ecological approach aims to strengthen community responses and inform policy decisions supporting population health and wellbeing
Drawing on survey and interview evidence, this chapter explores the effect of coverage denials on patients’ health and economic security. Most Americans report an inability to pay an unexpected $1,000 bill, so, with notably expensive health care, denials can be devastating. Too often, when coverage is denied, patients abandon their treatments, a dynamic shown not only through physician surveys, but also through original survey evidence of patients, half of whom reported delaying or abandoning their prescribed care. Further, the people most likely to do so are typically Black or Hispanic or less affluent, and nearly half of patient respondents reported that their health condition declined. In fact, some patients may not survive at all. Marginalized patients are also more likely to postpone non-medical purchasing to accommodate unexpected health insurance barriers, suggesting the far-reaching consequences of prior authorization. The evidence shows not only that tools of managed care produce frequent coverage denials, but also that this practice shifts risk from insurers to patients, yielding new health and economic insecurities, especially for patients from marginalized backgrounds.
This chapter provides economic explanations of the level of total national health expenditures in the US and of population health outcomes. It helps managers explain the role of wage differences with other countries and the impact of income inequality and racism on spending and outcomes. Wages of healthcare workers are much higher in the US than abroad. The healthcare GDP share has stabilized after growing for many years, but beneficial yet costly new technology still matters for cost and health growth. Metrics of relative health spending are distorted by exchange rate mismeasurement. Evidence on the fraction of total spending that is wasteful is very uncertain because no managerial or policy actions as yet have been proven to reduce waste in ways that do more good than harm. Changes in insurance and pricing policy have the highest promise for improvement.
In this chapter, we discuss practical ways One Health approaches can be integrated into legal and policy action from the lens of the environment sector, to deliver improved human, animal, and ecosystem health outcomes. Relevance to specific processes are highlighted: (1) national implementation of global environmental conventions, including in laws and policy frameworks; (2) environmental and social impact assessment; and 3) local governance systems, including in and around protected areas. Examination of these topics is ground-truthed by national, regional, and subnational examples, including from Liberia, building on lessons from the country’s robust multi-sectoral One Health coordination platform that can guide One Health action at all levels. We also explore the relevance of One Health economics to guide law and policy decisions frameworks in reducing environmental degradation and other trade-offs and maximising societal co-benefits. Finally, we discuss how industry standards and voluntary frameworks, such as the IUCN Green List Standard and its accompanying One Health tools, can have a supporting role in advancing good governance and multi-sectoral management for conservation and health outcomes.
Matching available health resources to consumer needs is challenging. Governments and health bureaucracies with finite resources face increasing demands from their client populations, which often have complex health issues. No country prioritises resources to meet every single health need of every citizen; consequently, effective health service planning is critical to maximising population health outcomes and ensuring value for the available money. Due to the inherent contradictions existing between the high demand for and the limited responsive supply capacity by health services, health service planning is often characterised by negotiation, lobbying and compromise among various interest groups. A consensus can best be achieved if stakeholders agree upon a set of core values, and all involved in the process endorse principles and the procedures of planning. This chapter focuses on the practice of health service planning.
Epidemiological studies have reported an association between the planetary health diet (PHD), diet-related greenhouse gas emissions (GHGEs), and mortality. However, data from individuals from non-Western countries was limited. Therefore, we aimed to examine this association among Japanese individuals using a cross-sectional ecological study of all 47 prefectures in Japan. Prefecture-level data were obtained from government surveys. The dietary amount was estimated based on the weight of food purchased (211 items) from the 2021–2023 Family Income and Expenditure Survey. Adherence to PHD was scored using the EAT-Lancet index (range, 0 [worst] to 42 [best]) and categorised into four groups: ≤ 24 (n = 14, low), 25 (n = 17, medium-low), 26 (n = 10, medium-high), and 27 points (n = 6, high). Diet-related GHGEs were estimated using previously developed GHGE tables for each food item. Mortality data were obtained using the 2022 Vital Statistics. Mortality rate ratio (RR) was calculated using a multivariate Poisson regression model. After adjusting for confounders, compared to the prefecture in the medium-low group of adherence score, those in the low and high groups were associated with a higher mortality RR for all-cause (low group: RR = 1.03 [95% CI (confidence interval) = 1.01–1.05]; high group: RR = 1.03 [95% CI = 1.00–1.07]) and pneumonia. Moreover, although a higher adherence score was inversely associated with GHGE, it was linked to an increased mortality risk from heart disease and stroke. Our findings indicate a reverse J-shaped association between adherence to PHD and mortality.
Edited by
Richard Pinder, Imperial College of Science, Technology and Medicine, London,Christopher-James Harvey, Imperial College of Science, Technology and Medicine, London,Ellen Fallows, British Society of Lifestyle Medicine
Group consultations are a form of community-integrated care that involve patients with similar health issues meeting with a clinician in a group setting. This approach enhances self-care and co-production, as patients learn from each other and participate in shared decision making. Group consultations have been shown to improve patient activation and evidence-based outcomes for long-term conditions such as diabetes and COPD, often at lower costs than individual consultations. Group consultations can be delivered in different ways, depending on the needs and preferences of the patients and the clinicians, including virtual sessions that allow for holistic care in the home environment. Case studies from various settings illustrate the effectiveness of group consultations in managing conditions like hypertension and diabetes. Group consultations are therefore a valuable method that combines the best of traditional care with the advantages of peer support and education, leading to better health outcomes in an efficient way.
Edited by
Richard Pinder, Imperial College of Science, Technology and Medicine, London,Christopher-James Harvey, Imperial College of Science, Technology and Medicine, London,Ellen Fallows, British Society of Lifestyle Medicine
Self-care is a broad concept that refers to the actions taken to preserve or improve health, which can vary depending on the academic literature. A useful framework to understand self-care is the Self-Care Matrix, which consists of four dimensions: activities, behaviours, context, and environment. Self-care activities are the specific practices that promote health, such as physical activity, healthy eating, hygiene, and rational use of health products. Self-care behaviours are the principles and actions that guide positive health behaviours and lifestyle choices. Self-care context is the degree of dependence or independence from external healthcare resources. Self-care environment is the external factor that influences self-care practices within the community. Self-care is closely related to Lifestyle Medicine, which supports individuals in adopting sustainable health practices and prioritises preventive strategies over reactive measures. Lifestyle Medicine and self-care play a crucial role in both primary and secondary prevention of diseases. The future of self-care envisions a healthcare landscape where technology and personalised approaches enhance self-care and Lifestyle Medicine. However, there are also challenges to address, such as potential inequalities and misconceptions that may arise as health systems pivot towards self-care.
Edited by
Richard Pinder, Imperial College of Science, Technology and Medicine, London,Christopher-James Harvey, Imperial College of Science, Technology and Medicine, London,Ellen Fallows, British Society of Lifestyle Medicine
Lifestyle Medicine is a practice grounded in evidence-based approaches, distinguishing it from unverified commercial wellness trends. It requires practitioners to critically interpret the evolving evidence base and communicate risks effectively to support shared decision making. While clinical trials for Lifestyle Medicine are less common than for pharmaceuticals, its interventions are nonetheless impactful and often preferred by patients. Epidemiology plays a crucial role in identifying associations between exposures and outcomes, although it cannot always establish causality. Understanding and communicating risk is vital, with absolute and relative risks offering different insights into the potential effects of interventions. The interpretation of evidence must consider both statistical and clinical significance, with confidence intervals providing a more nuanced understanding than p-values alone. Scepticism is necessary when interpreting clinical research to account for potential biases and confounding factors. Ultimately, consensus-driven approaches and trusted institutions guide practitioners in integrating Lifestyle Medicine into broader treatment guidelines.
For a case-control study to be a suitable design, we need a good idea about the outcome of interest (or condition) described by a strong case definition. But what if we know quite a bit about the exposures we are interested in, but we are a little hazy on the potential outcomes associated with those exposures? If we consider a scientific question like the one posed in this chapter – What happens if you eat pizza and chips every day?’ – we have specifically identified the exposures of interest, but can only guess what the outcomes might be. Okay, we could probably make fairly educated guesses about some of the potential outcomes (weight gain being foremost among these), but there remains a level of uncertainty about their timing, magnitude and variety. What is really needed to answer a question like this is a ‘cohort study’, a type of observational study in which ‘cohorts’ of people (population groups who share certain characteristics, such as being in the same work environment, or who are born in the same year) are sorted into groups on the basis of whether they have or have not been exposed to specific health-related factors.
Sex and gender have a significant relationship to health and health outcomes for women, men, and sexually and gender-diverse people. Sex relates to biological attributes, whether born female or male, while gender identity relates to how someone feels and experiences their gender, which may or may not be different to their physiology or sex at birth. Biological characteristics expose women and men to different health risks and health conditions. Gender also exposes people to different health risks, and gender inequity impacts on their potential to achieve health and well-being.
Sexual health nurses are employed to work in a range of practice settings and work with diverse population groups. Sexual and reproductive health care is considered a human right and is fundamental to positive well-being. The nurses role in sexual and reproductive health varies between settings within and across different jurisdictons. Work settings include dedicated sexual health clinics, family planning services, community health centres, women’s health services, correctional services, general practices and tertiary education settings. In some juristictions, nurses also provide care in publicly funded sexual health clinics aimed at providing services to specific priority population groups to increase their access to services and reduce the prevalence of adverse sexual and reproductive health outcomes including sexually transmitted infections and unplanned pregnancy.
The role of occupational health nurses is to improve mental and physical health outcomes and the well-being of workers. These benefits can often extend to family and community. Workers’ health is impacted by several factors including fatigue, gender, culture, age, language, living conditions, access to nutritious food, level of physical activity, sleep patterns, personal health practices and coping strategies, levels of social support and inclusion, personal safety and freedom from violence.
There is a growing focus on understanding the complexity of dietary patterns and how they relate to health and other factors. Approaches that have not traditionally been applied to characterise dietary patterns, such as latent class analysis and machine learning algorithms, may offer opportunities to characterise dietary patterns in greater depth than previously considered. However, there has not been a formal examination of how this wide range of approaches has been applied to characterise dietary patterns. This scoping review synthesised literature from 2005 to 2022 applying methods not traditionally used to characterise dietary patterns, referred to as novel methods. MEDLINE, CINAHL and Scopus were searched using keywords including latent class analysis, machine learning and least absolute shrinkage and selection operator. Of 5274 records identified, 24 met the inclusion criteria. Twelve of twenty-four articles were published since 2020. Studies were conducted across seventeen countries. Nine studies used approaches with applications in machine learning, such as classification models, neural networks and probabilistic graphical models, to identify dietary patterns. The remaining studies applied methods such as latent class analysis, mutual information and treelet transform. Fourteen studies assessed associations between dietary patterns characterised using novel methods and health outcomes, including cancer, cardiovascular disease and asthma. There was wide variation in the methods applied to characterise dietary patterns and in how these methods were described. The extension of reporting guidelines and quality appraisal tools relevant to nutrition research to consider specific features of novel methods may facilitate consistent reporting and enable synthesis to inform policies and programs.
In Europe, organic food must comply with specific regulations which do not include nutritional criteria. The ability of organic food to meet the nutritional needs of children is not assessed. This narrative review discusses the nutritional composition (macronutrients, micronutrients) of organic food compared with conventional products and its clinical relevance with a paediatric focus, as well as the health impact of these differences and of contaminants which interfere with metabolism. Other potential differences, particularly regarding the direct/indirect exposure to other contaminants in conventional food, are not addressed in this review. The composition of some organic food may differ from conventional food. Protein content was lower in cereals and eggs. A lower n-6:n-3 polyunsaturated fat (PUFA) ratio was observed in milk, meat and eggs. Long-chain PUFA and vitamin E may be higher in milk, meat and fish, as well as some minerals and antioxidants (phenolic compounds, vitamin C) in fruits, vegetables and starchy food and carotenoids in fruits and vegetables. Epidemiological studies suggest an association between organic diets and lower prevalence of childhood obesity, type 2 diabetes and metabolic syndrome, whereas the protective effect on allergy and cancer is controversial. Some organic food may be of greater nutritional interest for children’s diet than conventional food. Standardised studies comparing food composition and diet in children are needed. Considering the lower toxicologic risk and the sustainability of organic food, the Committee on Nutrition encourages the use of organic food, provided that such food is affordable, alongside specific baby food which is subject to strict specific European Union regulations.
Health technology assessment (HTA) organizations generate guidelines to inform healthcare practices toward improved health outcomes. This review sought to identify and classify outcomes of guidelines from HTA organizations within published research.
Methodology
We performed a systematic mixed studies review of empirical studies that (a) referred to a published guideline from an HTA organization and (b) reported an outcome resulting from a guideline. We searched the published literature in English or French within seven databases. Outcome types were classified within five dimensions of an existing framework for online health information (e.g., relevance, cognitive/affective impact, and use). Subdimensions were inductively developed. A two-phase sequential data synthesis was performed. Phase 1: a hybrid deductive–inductive thematic analysis identified the types of outcomes and displayed their relationships on a concept map. Phase 2: descriptive statistics were tabulated by the type of outcome.
Results
A total of 6,719 records were retrieved through searches on 6 February 2023. After screening, we included 120 observational studies (twenty-one qualitative, ninety-four quantitative, and five mixed methods). Phase 1 identified twenty-nine types of outcomes. The most frequently reported outcomes were within the organizational dimension (reported in ninety-four studies). The most common subdimensions were “Referrals” (thirty-eight occurrences), the “Quality of Prescriptions” (fifteen occurrences), and the “Quality of Diagnosis” (eight occurrences). For Phase 2, we could only generate descriptive statistics on seventeen outcomes. These were almost equally distributed among positive, neutral, and negative effects. Our results contribute to knowledge about the outcomes of HTA guidelines and options for documenting and measuring them in future evaluations.