World Population Research Articles

Designing AI for Partnership in Care

As the global population ages, promoting active aging and enabling older adults to age in place has become increasingly important. This paper explores the role of technology in this process, particularly in helping older adults identify and pursue meaningful activities and provide care for loved ones. Through two example projects -- the design of a social robot that supports older adults' experience of a sense of meaning and purpose (ikigai), and an exploration of how technology can assist with caregiving -- we demonstrate how technology can enhance the care for older adults. This short paper highlights how technology can create a more fulfilling and supportive active aging experience, empowering older adults to engage with what and who they care about and enhancing their caring relationships.

Assessing the long-term care (LTC) service needs of older adults based on time-driven activity-based costing (TDABC)–a cross-sectional survey in central China

BackgroundThe global population’s aging has led to an increasing demand for long-term care (LTC), especially in developing countries like China. Comprehensive assessment of LTC service demands by including the time and cost analysis is crucial to inform the planning and financing of LTC resources, yet such research is lacking in China. Our research team has developed a quantitative index system of the medical and nursing services needs of older adults (QISMNSNE) based on the framework of Time-Driven Activity-Based Costing (TDABC), providing a valuable tool for measuring LTC service needs. This study aimed to assess the LTC service needs of older adults in China and the factors associated with such needs.MethodsA cross-sectional study was conducted in Changsha City, Hunan Province, China, from June 2021 to December 2022. A stratified multistage cluster sampling method was used to recruit 1,270 older adults from five nursing homes and three communities/streets in three regions of Changsha City. The LTC service needs were assessed by calculating the service time required from caregivers, nurses, and doctors and the total service time (min/d) using the QISMNSNE. Participants’ disability, activities of daily living (ADLs), mental status and social involvement (MSSI), and sensory and communication (SC) were assessed using standard scales. Generalized linear regression models were used to analyze factors associated with LTC service needs.ResultsThe participants had an average age of 76.41 ± 8.38 years, with 43.7% being female. The median service time required from caregivers, nurses, and doctors was 53.34 min/d, 3.66 min/d, and 0.33 min/d, respectively, and the total service time was 83.31 min/d. The generalized linear regression model identified the following factors that were associated with higher total service time: aged 75–84 years, living in nursing homes, income over 5000 per month, ADLs, MSSI (9 ~ 40), SC, and having 3 ~ 4 kinds of geriatric comorbidity (P < 0.05).ConclusionsOlder adults have a high need for LTC services, especially those provided by caregivers, indicating an urgent need to expand and improve LTC systems. The LTC service time needed is associated with multilevel factors encompassing socio-demographic, functional, and psychological aspects. This study offers preliminary insights into the needs, demands, and costs of LTC services for older adults and provides essential guidance for future planning and financing of LTC resources.

Global burden and cross-country inequalities in diseases associated with high body mass index from 1990 to 2019: Result from the Global Burden of Disease Study 2019.

High body mass index (BMI) has gradually become an increased risk factor for the global burden of diseases (GBD). As the disease burden and the number of elders globally increase, it is crucial for policymakers to realise the associations between high BMI and disease burden worldwide in a timely manner and to develop effective interventions for different countries and ages. We used the GBD 2019 database to analyse the deaths and disability-adjusted life-years (DALYs) in the disease burden associated with high BMI and indicated the health inequality at the global, regional, and national levels. We applied the slope index of inequality and concentration index, two standard metrics of absolute and relative gradient inequality recommended by the World Health Organization (WHO), to quantify the distributive inequalities in the burden of diseases associated with high BMI. These rates were reported per 100 000 population as crude incidence rates, death rates, and DALYs rates. All the estimates were generated with a 95% uncertainty interval (UIs). Globally, we revealed that an estimated age-standardised mortality rate associated with high BMI is 6.26 million (95% UIs = 3.99, 8.91). The age-standardised DALYs rate is 19.32 million (95% UIs = 12.77, 26.40), and the global population attributable fraction was 9% (95% UIs = 5, 12) in 2019. The largest number of high-BMI-related deaths in women mainly concentrated in the age group of 65-79 years, whereas the largest number in men was in the age group of 60-69 years. The age-standardised DALYs rate of diseases associated with high BMI was larger in the high-middle and middle socio-demographic index (SDI) (population attributable fraction (PAF) = 11 and PAF = 9) regions than those with high SDI (PAF = 1) and low SDI (PAF = 5) regions. In this study, our results showed that the disease burden of global deaths and DALYs associated with high BMI has substantially increased between 1990-2019. Furthermore, we demonstrated that countries with higher SDI development levels shoulders higher burden of diseases associated with high BMI. Future policies to prevent and reduce the burden should be developed and implemented based on country-specific development status.

Predictive Modelling of Crop Rotation Using Data Mining Approaches

Agriculture is crucial for economic growth and food security, particularly in agro-based countries. As the global population grows, the demand for food increases, necessitating improvements in agricultural productivity. Traditional methods have often fallen short, and innovative approaches such as data mining and machine learning are needed. This research aims to develop a predictive model for crop rotation using machine learning techniques. A comprehensive dataset was collected and preprocessed to train various algorithms. The proposed model demonstrated that machine learning could effectively predict suitable crops for cultivation, thereby enhancing crop yield and sustainability. The evaluation results were promising, with the Random Forest model achieving a precision of 0.67 to 1.00, recall of 0.43 to 1.00, and F1-score of 0.60 to 1.00; the Decision Tree model had a precision of 0.50 to 1.00, recall of 0.43 to 1.00, and F1-score of 0.50 to 1.00; and the K-Neighbors Classifier model showed precision of 0.40 to 1.00, recall of 0.43 to 1.00, and F1-score of 0.50 to 1.00.

Elderly Citizenship Experience under Different Pension Policies: A Comparative Analysis of China and Japan

Abstract: As global population structures change rapidly, the social rights and welfare of the elderly have increasingly become a focal point of societal concern. Pension policies not only address economic issues but also encompass welfare levels, social equity, citizenship rights, and identity. This paper explores the impact of different pension policies on the citizenship experience of the elderly by comparing the pension systems of China and Japan. The study is based on pension policy documents and related data from both countries and employs a comparative social policy analysis. The comparison is conducted conceptually, focusing on the scope, content, and depth of the pension policies in China and Japan, in order to reflect on the elderly's citizenship experience in both nations. The research highlights that Chinas pension policy features a single-tier structure with limited autonomy and marked urban-rural disparities, which restrict the citizenship experience of the elderly. In contrast, Japans retirement policy is characterized by mandatory participation, clear responsibilities, and a multi-tiered structure, providing broader coverage and more comprehensive social rights and a sense of identity for the elderly. However, this system also brings about noticeable class divisions.

The cellular and molecular mechanisms mediating the protective effects of sodium-glucose linked transporter 2 inhibitors against metabolic dysfunction-associated fatty liver disease.

Metabolic dysfunction-associated fatty liver disease (MAFLD), formerly known as nonalcoholic fatty liver disease (NAFLD), is a common, highly heterogeneous condition that affects about a quarter of the world's population, with no approved drug therapy. Current evidence from preclinical research and a number of small clinical trials indicates that SGLT2 inhibitors could also be effective for MAFLD. MAFLD is associated with a higher risk of chronic liver disease and multiple extrahepatic events, especially cardiovascular disease (CVD) and chronic kidney disease (CKD). MAFLD is considered a more appropriate terminology than NAFLD because it captures the complex bidirectional interplay between fatty liver and metabolic dysfunctions associated with disease progression, such as obesity and type 2 diabetes mellitus (T2DM). SGLT2 inhibitors are antidiabetic drugs that block glucose reabsorption in the kidney proximal tubule. In this article, we reviewed current clinical evidence supporting the potential use of SGLT2 inhibitors as a drug therapy for MAFLD and discussed the possible cellular and molecular mechanisms involved. We also reviewed the clinical benefits of SGLT2 inhibitors against MAFLD-related comorbidities, especially CVD, CKD and cardiovascular-kidney-metabolic syndrome (CKM). The broad beneficial effects of SGLT2 inhibitors support their use, likely in combination with other drugs, as a therapy for MAFLD.

The herpes simplex virus alkaline nuclease is required to maintain replication fork progression.

Herpes simplex virus 1 (HSV-1) is a near-ubiquitous pathogen within the global population, causing a lifelong latent infection with sporadic reactivation throughout the life of the host. Within at-risk and immunocompromised communities, HSV-1 infection can cause serious morbidities including herpes keratitis and encephalitis. With the possibility of herpesviruses to evade established antiviral therapies and there being no approved HSV-1 vaccine, there comes a need to investigate potential targets for intervention against infection and subsequent disease. UL12 is the viral 5'-3' exonuclease, which is required for the production of infectious progeny. In this study, we show that in the absence of UL12, viral replication fork progression is abrogated. These data point to UL12 as an attractive target for intervention, which could lead to better clinical outcomes of HSV-1-associated disease in the future.

Mapping the evolution of liver aging research: A bibliometric analysis.

With the increasing of the global aging population, healthy aging and prevention of age-related diseases have become increasingly important. The liver, a vital organ involved in metabolism, detoxification, digestion, and immunity, holds a pivotal role in the aging process of organisms. Although extensive research on liver aging has been carried out, no bibliometric analysis has been conducted to evaluate the scientific progress in this area. To analyze basic knowledge, development trends, and current research frontiers in the field via bibliometric methods. We conducted bibliometric analyses via a range of analytical tools including Python, the bibliometrix package in R, CiteSpace, and VOSviewer. We retrieved publication data on liver aging research from the Web of Science Core Collection Database. A scientific knowledge map was constructed to display the contributions from different authors, journals, countries, institutions, as well as patterns of co-occurrence keywords and co-cited references. Additionally, gene regulation pathways associated with liver aging were analyzed via the STRING database. We identified 4288 articles on liver aging, authored by 24034 contributors from 4092 institutions across 85 countries. Notably, the years 1991 and 2020 presented significant bursts in publication output. The United States led in terms of publications (n = 1008, 25.1%), citations (n = 55205), and international collaborations (multiple country publications = 214). Keywords such as "lipid metabolism", "fatty liver disease", "inflammation", "liver fibrosis" and "target" were prominent, highlighting the current research hotspots. Notably, the top 64 genes, each of which appeared in at least 8 articles, were involved in pathways essential for cell survival and aging, including the phosphatidylinositol 3-kinase/protein kinase B, Forkhead box O and p53 signaling pathways. This study highlights key areas of liver aging and offers a comprehensive overview of research trends, as well as insights into potential value for collaborative pursuits and clinical implementations.

Amino acid deletions at positions 893 and 894 of cytotoxin-associated gene A protein affect Helicobacter pylori gastric epithelial cell interactions.

Helicobacter pylori (H. pylori) persistently colonizes the human gastric mucosa in more than 50% of the global population, leading to various gastroduodenal diseases ranging from chronic gastritis to gastric carcinoma. Cytotoxin-associated gene A (CagA) protein, an important oncoprotein, has highly polymorphic Glu-Pro-Ile-Tyr-Ala segments at the carboxyl terminus, which play crucial roles in pathogenesis. Our previous study revealed a significant association between amino acid deletions at positions 893 and 894 and gastric cancer. To investigate the impact of amino acid deletions at positions 893 and 894 on CagA function. We selected a representative HZT strain from a gastric cancer patient with amino acid deletions at positions 893 and 894. The cagA gene was amplified and mutated into cagA-NT and cagA-NE (sequence characteristics of strains from nongastric cancer patients), cloned and inserted into pAdtrack-CMV, and then transfected into AGS cells. The expression of cagA and its mutants was examined using real-time polymerase chain reaction and Western blotting, cell elongation via cell counting, F-actin cytoskeleton visualization using fluorescence staining, and interleukin-8 (IL-8) secretion via enzyme-linked immunosorbent assay. The results revealed that pAdtrack/cagA induced a more pronounced hummingbird phenotype than pAdtrack/cagA-NT and pAdtrack/cagA-NE (40.88 ± 3.10 vs 32.50 ± 3.17, P < 0.001 and 40.88 ± 3.10 vs 32.17 ± 3.00, P < 0.001) at 12 hours after transfection. At 24 hours, pAdtrack/cagA-NE induced significantly fewer hummingbird phenotypes than pAdtrack/cagA and pAdtrack/cagA-NT (46.02 ± 2.12 vs 53.90 ± 2.10, P < 0.001 and 46.02 ± 2.12 vs 51.15 ± 3.74, P < 0.001). The total amount of F-actin caused by pAdtrack/cagA was significantly lower than that caused by pAdtrack/cagA-NT and pAdtrack/cagA-NE (27.54 ± 17.37 vs 41.51 ± 11.90, P < 0.001 and 27.54 ± 17.37 vs 41.39 ± 14.22, P < 0.001) at 12 hours after transfection. Additionally, pAdtrack/cagA induced higher IL-8 secretion than pAdtrack/cagA-NT and pAdtrack/cagA-NE at different times after transfection. Amino acid deletions at positions 893 and 894 enhance CagA pathogenicity, which is crucial for revealing the pathogenic mechanism of CagA and identifying biomarkers of highly pathogenic H. pylori.

A qualitative analysis of derogatory labels used against persons with disabilities in Kashmir

ABSTRACT Approximately 15 per cent of the global population has disabilities, including 26 million people in India and 367,000 in Jammu and Kashmir. Persons with disabilities (PWD) face stigma worldwide, and derogatory labels in the Kashmiri language compound this problem. We applied stigma and labelling theories to analyse the effects of societal labels on PWD in Kashmir. Focusing on women participants, we explored the unique, gender-specific experiences of stigma they faced. We uncovered PWD’s experiences in the region through qualitative research and narrative analysis. We highlighted culturally specific labels deeply embedded in Kashmiri society, illustrating how these labels contribute to marginalisation. This approach offers a nuanced understanding of the social and emotional impacts of labelling on both men and women.

Multiple-wave admixture and adaptive evolution of the Pamirian Wakhi people.

While whole-genome sequencing has been applied extensively to investigate the genetic diversity of global populations, ethnic minority groups in Pakistan are generally underrepresented. In particular, little is known about the genetic origin and highland adaptation of the Pamirian Wakhi people. According to Chinese historical records, the geographical location and language usage of Wakhi may be closely related to Xinjiang Tajiks (XJT). In this study, based on high-coverage (∼30×) whole-genome sequencing of eight Wakhi and 25 XJT individuals, we performed data analyses together with worldwide populations to gain insights into their genetic composition, demography, and adaptive evolution to the highland environment. The Wakhi derived more than 85% of their ancestry from West Eurasian populations (European ∼44.5%, South Asian ∼42.2%) and 10% from East Eurasian populations (Siberian ∼6.0%, East Asian ∼4.3%). Modeling the admixture history of the Wakhi indicated that the early West-East admixture occurred approximately 3,875-2,250 years ago and that the recent admixture occurred 750-375 years ago. We identified selection signatures across EGLN3, in particular, a distinctive evolutionary signature was observed, and a certain underlying selected haplotype showed higher frequency (87.5%) in the Wakhi than in nearby XJT and other highlanders. Interestingly, we found high-frequency archaic sequences in the Wakhi genome, which overlapped with several genes related to cellular signaling transduction, including MAGI2, previously associated with high-altitude adaptation. Our analysis indicates that the Wakhi are distinct from the XJTs and Tajikistan Tajiks, and shed light on the Wakhi's ancestral origin and genetic basis of high-altitude adaptation.

Sequential multiple mediating effect of loneliness and family health on physical frailty and willingness to age at home in older adults: a national survey in China

BackgroundWith the rapid ageing of the global population, the number of older adults with physical frailty has been gradually increasing, making ageing at home a key strategy for coping with this demographic change. The opinions of older adults regarding their willingness to age at home deserve to be considered respectfully. As a result, this study aimed to investigate willingness to age at home and any associated underlying mechanisms involving physical frailty among older Chinese adults.MethodsThis study was a national cross-sectional survey. Stratified random and quota sampling were used before and after the individual level respectively. Willingness to age at home was compared between older adults with different characteristics using the Mann–Whitney U test and Kruskal–Wallis H test. A Spearman rank test was conducted to explore the correlations among physical frailty, loneliness, family health, and willingness to age at home. The path hypothesis that loneliness and family health influence the relationship between physical frailty and willingness to age at home among older adults was further tested through sequential multiple mediation analysis.ResultsA total of 3,837 older adults were included in this study. They returned a median score of 78 in terms of willingness to age at home. Physical frailty (β = − 0.044, P < 0.01) and loneliness (β = − 0.070, P < 0.001) were negatively associated, and family health (β = 0.275, P < 0.001) was positively associated with a willingness to age at home among older Chinese adults. Loneliness and family health played sequential multiple mediating role (β = − 0.018, Boot SE = 0.002, 95% CI = [–0.022, − 0.014]) between physical frailty and willingness to age at home.ConclusionsReducing physical frailty in older adults, reducing their sense of loneliness, and enhancing their family health is essential, as it can increase their levels of confidence with regard to ageing at home.

Diabetes knowledge and behaviour: a cross-sectional study of Jordanian adults.

Diabetes mellitus is a significant global health concern that is projected to affect 7.7% of the global population by 2030. Understanding factors that influence diabetes knowledge and management adherence is crucial for effective diabetes mellitus management and prevention. This study investigates the relationships between demographic and clinical factors and their impact on diabetes knowledge and behaviour, as well as the potential influence of diabetes knowledge on management behaviours. The study comprised a cross-sectional survey of 1050 adults, collecting data on age, sex, marital status, education, employment, hypertension, dyslipidaemia (any lipid imbalance, such as high cholesterol, high LDL-cholesterol or low HDL-cholesterol), smoking and diabetes status. Two multiple linear regression models were used to identify factors associated with diabetes knowledge and behaviour, and a simple linear regression model was used to assess the relationship between knowledge and behaviour. Significant associations were found between diabetes knowledge and the following factors: age (44.32 ± 9.53 for ≥50 years vs 39.73 ± 9.95 for 18 to <25 years; p<0.0001), sex (49.00 ± 12.35 for women vs 45.09 ± 13.27 for men; p<0.0001), marital status (50.92 ± 11.69 for married vs 45.39 ± 13.10 for single; p<0.0001), smoking status (45.78 ± 13.22 for smokers vs 48.22 ± 12.15 for non-smokers; p=0.003), hypertension (46.46 ± 13.11 for present vs 47.31 ± 12.87 for absent; p=0.007) and diabetes status (69.49 ± 17.35 for present vs 62.76 ± 16.88 for absent; p<0.001). Behaviour scores correlated similarly with these factors except for diabetes and smoking status. The adjusted simple linear regression model revealed that diabetes knowledge was significantly associated with better management behaviours (coefficient=0.0794, p<0.001) after adjusting for demographic and clinical factors. This study highlights the importance of demographic and clinical factors in the context of diabetes knowledge and behaviours, underscoring the need for targeted educational and preventive programmes to improve diabetes management, especially in vulnerable populations. Additionally, the strong association between diabetes knowledge and management behaviours supports a knowledge-attitude-behaviour (KAB) model of diabetes management.

Development cooperation facing the challenge of global aging: a critical analysis

World populations are changing rapidly in terms of their composition by age groups. Increased well-being has been instrumental in extending people's lives, giving rise to longer-living societies. Nevertheless, ageism persists in all areas in society; older people suffer discrimination in contexts of crisis according to their probability of survival, such as during the COVID-19 pandemic. How does international development cooperation face this new demographic reality, which is a growing concern in countries already receiving aid? Throughout this paper, we attempt to answer this question, and others, to ensure that international development cooperation is effective in building an inclusive society.

The Next 2 Billion: Can the World Support 10 Billion People?

AbstractThe UN projects that world population will peak at 10.3 billion in 2084, a 2.1 billion increase from 2024. Can the world provide food, water, and other resources to 10.3 billion people? How will additional population exacerbate resource challenges and worsen climate change? This paper analyzes these questions by looking at the last 60 years and by simulating the future impact of population growth and rising incomes on food, water, energy, and CO2 emissions. Looking back, food production has increased faster than the population in all regions, and we have not experienced significant shortages in nonrenewable resources. The history of water and CO2 emissions is less encouraging, however, with declining water levels in many aquifers and global warming threatening to undermine progress in all areas. Looking forward, population growth will be concentrated in poor countries, while rich countries, with higher consumption levels and emissions, will experience population decline. Population growth is projected to significantly increase demand for food and water in coming decades but is projected to have only modest impacts on energy and CO2, with population decline in high‐emission higher income countries more than offsetting the impact of population growth in low‐emission lower‐income countries.

Predictive modeling of COVID-19 mortality risk in chronic kidney disease patients using multiple machine learning algorithms

The coronavirus disease 2019 (COVID-19) has a significant impact on the global population, particularly on individuals with chronic kidney disease (CKD). COVID-19 patients with CKD will face a considerably higher risk of mortality than the general population. This study developed a predictive model for assessing mortality in COVID-19-affected CKD patients, providing personalized risk prediction to optimize clinical management and reduce mortality rates. We developed machine learning algorithms to analyze 219 patients’ clinical laboratory test data retrospectively. The performance of each model was assessed using a calibration curve, decision curve analysis, and receiver operating characteristic (ROC) curve. It was found that the LightGBM model showed the most satisfied performance, with an area under the ROC curve of 0.833, sensitivity of 0.952, and specificity of 0.714. Prealbumin, neutrophil percent, respiratory index in arterial blood, half-saturated pressure of oxygen, carbon dioxide in serum, glucose, neutrophil count, and uric acid were the top 8 significant variables in the prediction model. Validation by 46 patients demonstrated acceptable accuracy. This model can serve as a powerful tool for screening CKD patients at high risk of COVID-19-related mortality and providing decision support for clinical staff, enabling efficient allocation of resources, and facilitating timely and targeted management for those who need the relevant interference urgently.

Non-small cell lung cancer detection through knowledge distillation approach with teaching assistant.

Non-small cell lung cancer (NSCLC) exhibits a comparatively slower rate of metastasis in contrast to small cell lung cancer, contributing to approximately 85% of the global patient population. In this work, leveraging CT scan images, we deploy a knowledge distillation technique within teaching assistant (TA) and student frameworks for NSCLC classification. We employed various deep learning models, CNN, VGG19, ResNet152v2, Swin, CCT, and ViT, and assigned roles as teacher, teaching assistant and student. Evaluation underscores exceptional model performance in performance metrics achieved via cost-sensitive learning and precise hyperparameter (alpha and temperature) fine-tuning, highlighting the model's efficiency in lung cancer tumor prediction and classification. The applied TA (ResNet152) and student (CNN) models achieved 90.99% and 94.53% test accuracies, respectively, with optimal hyperparameters (alpha = 0.7 and temperature = 7). The implementation of the TA framework improves the overall performance of the student model. After obtaining Shapley values, explainable AI is applied with a partition explainer to check each class's contribution, further enhancing the transparency of the implemented deep learning techniques. Finally, a web application designed to make it user-friendly and classify lung types in recently captured images. The execution of the three-stage knowledge distillation technique proved efficient with significantly reduced trainable parameters and training time applicable for memory-constrained edge devices.

Revisiting North-South Disparities in Naming Practices: An Extension and Update

This research note presents evidence of persistent disparities in naming practices in social science research between the global North and South from 1960 to the present. The analysis relied on bibliometric records of 11.9 million articles sourced from the OpenAlex collection. By covering the 1960–2024 period and including six social science and humanities subdisciplines—Economic, Geography, History, Political Sciences, Psychology, and Sociology—this study replicates and expands an existing study that used Scopus data (0.5 million articles). Results show that scientific articles about global North countries and populations are systematically less likely to mention the country name in their titles compared to global South. For example, compared to the US, articles about China are between 1.8 and 2.7 times more likely to include the country name in the title. Significant variations across subdisciplines are observed, with Psychology displaying the lowest localization rates and greatest geographical gaps, and History showing seemingly converging trends over time across geographies. Continued research is needed to warrant diversity and inclusivity in social science research. A country-year dataset with country-mention counts in titles and abstracts is made available.

Diseases Caused by and Behaviors Associated with Toxoplasma gondii Infection

Toxoplasma gondii is an Apicomplexan parasite that is estimated to infect at least one-third of the global human population. T. gondii infection may be transmitted horizontally or vertically. The main risk factors for transmission to humans are related to diet, especially the consumption of undercooked meat, along with soil contact. In immunocompetent persons, the acute infection may go undetected as it typically produces minor, non-specific symptoms that are self-limited. After infection is established, recurrent retinochoroiditis is the most common clinical disease. In contrast, severe systemic or cerebral toxoplasmosis may be life-threatening for immunocompromised individuals. Furthermore, congenital toxoplasmosis acquired in utero may have devastating consequences if not recognized and promptly treated. A growing body of research has identified associations between latent T. gondii infection, and personality traits and risk-taking behaviors. Other studies have documented associations between latent infection and psychiatric conditions that include schizophrenia and bipolar affective disorder. With no current treatment regimens being curative of T. gondii infection, effective prevention measures at both the public health and individual levels are vitally important.

Factors Associated with Heart Disease in Japan: Multivariate Analysis Based on Specific Health Checkups

The global population affected by heart failure is projected to reach 30 million. The number of deaths due to heart disease has surged, rising from 2 million in 2000 to 8.9 million in 2019. In Japan, the prevalence of heart failure is rapidly increasing, with the number expected to reach 1.3 million by 2030. Primary prevention is crucial to prevent heart disease. We explored the associations of heart disease incidence with findings from checkups performed a decade ago. A multivariate logistic regression analysis revealed that individuals who reported a history of stroke, history of chronic renal failure, or weight gain ≥ 10 kg since age 20 in the questionnaire-based health checkup are at high risk for developing heart disease. Additionally, those with biochemical test results from 10 years ago indicating the use of antihypertensive drugs, use of insulin injections or hypoglycemic medications, systolic hypertension, and abnormal creatinine levels also exhibited a significantly higher risk of heart disease. Conversely, individuals who identified as female, walked faster than people of the same age, drank alcohol daily, and felt refreshed upon awakening in the questionnaire-based health checkup were protected from heart disease.