Canadian Journal of Infectious Diseases and Medical Microbiology Impact Factor 2024-2025 - ResearchHelpDesk - Canadian Journal of Infectious Diseases and Medical Microbiology is a peer-reviewed, Open Access journal that publishes original research articles, review articles, and clinical studies related to infectious diseases of bacterial, viral and parasitic origin. The journal welcomes articles describing research on pathogenesis, epidemiology of infection, diagnosis and treatment, antibiotics and resistance, and immunology. Canadian Journal of Infectious Diseases and Medical Microbiology is archived in Portico, which provides permanent archiving for electronic scholarly journals, as well as via the LOCKSS initiative. It operates a fully open access publishing model which allows open global access to its published content. This model is supported through Article Processing Charges. Canadian Journal of Infectious Diseases and Medical Microbiology is included in many leading abstracting and indexing databases. Abstracting and Indexing The following is a list of the Abstracting and Indexing databases that cover Canadian Journal of Infectious Diseases and Medical Microbiology published by Hindawi. Abstracts on Hygiene and Communicable Diseases Agricultural Economics Database Agroforestry Abstracts Botanical Pesticides CAB Abstracts Directory of Open Access Journals (DOAJ) EMBASE Global Health Google Scholar Journal Citation Reports - Science Edition Open Access Journals Integrated Service System Project (GoOA) Primo Central Index PubMed PubMed Central Science Citation Index Expanded Scopus The Summon Service WorldCat Discovery Services All of Hindawi’s content is archived in Portico, which provides permanent archiving for electronic scholarly journals, as well as via the LOCKSS initiative.

International Journal of Contemporary Medical Research Impact Factor 2024-2025 - ResearchHelpDesk - International Journal of Contemporary Medical Research - IJCMR, an official publication of International Society for Contemporary Medical Research (Registered under Government of India, Society Registration Act No - 21, 1860), is a peer reviewed, international, print and online, open access journal with MONTHLY (since January, 2016) publication. It is a multidisciplinary journal to provide a forum for the presentation and criticism of original, innovative and thought provocative ideas in medical and allied specialties. IJCMR publishes new, challenging and radical ideas, so long as they are coherent and clearly expressed. The types of article accepted include original articles, review articles, case reports, and letters to the editor. Clinical microbiology relevant immunology, pathophysiology, genetics, epidemiological, and genomics studies are also welcome. International Journal of Contemporary Medical Research is an internationally targeted official publication. All articles have to be original articles that have not been published elsewhere or are being considered for publication in other journals. All articles submitted will be peer reviewed by experts. Receipt of the manuscript will be acknowledged by email. Every effort will be made to complete the review process within 2 weeks and communicated to the corresponding author. Papers should be submitted to ijcmr.journal@gmail.com. The Editorial board will strive for the quality of the journal and will also index the journal in various indexing bodies and the information will be updated on the journal website from time to time. We welcome all your submissions. I hope you will consider IJCMR for your next submission. Periodicity of the journal - Quarterly (Since inception to 2015 June (Volume 2; Issue 2) Bimonthly (Since 2015 July (Volume 2; Issue 3)) Monthly (Since January 2016 (Volume 3; Issue 1)) Scope of Journal The journal covers all aspects of medical sciences from genes to humans. Articles reporting clinical observations, experimental studies and theoretical concepts are all welcome, and especially welcome high quality review articles from distinguished authors, and original articles reporting new findings in medical and allied sciences. The journal covers technical and clinical studies related to health, ethical and social issues in the fields of Science and allied specialties. Articles with clinical interest and implications will be given preference. Journal editors, welcome thought provoking papers on areas listed above. Decisions about papers will be communicated to authors within 3 weeks of submission. IJCMR publishes original research work that contributes significantly to further the scientific knowledge and research in Medical, Dental, Pharmaceutical Sciences etc.. and aims to provide a platform to researchers to publish their articles. It comprises peer- reviewed articles as its core material which includes original research papers, case reports and review articles as well. We encourage the submission of manuscripts that cross disciplines and also studies that address universal problems of human health. Fields Anesthesiology, Anatomy, Animal Research, Ayurveda, Sidha & Unani (All Branches) Biochemistry, Biotechnology, Cardiology, Community, Dermatology, Dentistry (All Branches), Education, Emergency Medicine, Endocrinology, Ethics, Ear Nose and Throat, Forensic, Gastroenterology, Genetics, Haematology, Health Management and Policy, Homeopathy, Immunology and Infectious Diseases, Intensive Care, Internal Medicine, Microbiology, Health Management and Policy, Immunology and Infectious Diseases, Intensive Care, Internal Medicine, Microbiology, Nephrology / Renal, Neurology and Neuro-Surgery, Nutrition, Oncology, Orthopaedics, Ophthalmology, Obstetrics and Gynaecology, Paediatrics and Neonatology, Pharmacology, Pharmacy (All branches) Physiology, Pathology, Plastic Surgery, Psychiatry/Mental Health, Rehabilitation, Radiology, Statistics, Surgery, Yoga and alternative therapies.

BackgroundSince the global epidemic of the coronavirus disease 2019 (COVID-19), a large number of immunological studies related to COVID-19 have been published in various immunology journals. However, the results from these studies were discrete, and no study summarized the important immunological information about COVID-19 released by these immunology journals. This study aimed to comprehensively summarize the knowledge structure and research hotspots of COVID-19 published in major immunology journals through bibliometrics.MethodsPublications on COVID-19 in major immunology journals were obtained from the Web of Science Core Collection. CiteSpace, VOSviewer, and R-bibliometrix were comprehensively used for bibliometric and visual analysis.Results1,331 and 5,000 publications of 10 journals with high impact factors and 10 journals with the most papers were included, respectively. The USA, China, England, and Italy made the most significant contributions to these papers. University College London, National Institute of Allergy and Infectious Diseases, Harvard Medical School, University California San Diego, and University of Pennsylvania played a central role in international cooperation in the immunology research field of COVID-19. Yuen Kwok Yung was the most important author in terms of the number of publications and citations, and the H-index. CLINICAL INFECTIOUS DISEASES and FRONTIERS IN IMMUNOLOGY were the most essential immunology journals. These immunology journals mostly focused on the following topics: “Delta/Omicron variants”, “cytokine storm”, “neutralization/neutralizing antibody”, “T cell”, “BNT162b2”, “mRNA vaccine”, “vaccine effectiveness/safety”, and “long COVID”.ConclusionThis study systematically uncovered a holistic picture of the current research on COVID-19 published in major immunology journals from the perspective of bibliometrics, which will provide a reference for future research in this field.

Indian Journal of Comparative Microbiology Immunology and Infectious Diseases Abstract & Indexing - ResearchHelpDesk - Indian Journal of Comparative Microbiology, Immunology and Infectious Diseases (IJCMIID), an official organ of the Indian Association of Veterinary Microbiologists, Immunologists and Specialists in Infectious Diseases publishes the articles of original work pertaining to the Immunology, Microbiology and Infectious diseases of animals. Indexed/Abstract with - Indian Citation Index, NAAS Rating 2018 - 4.49, CAB Abstract, Scientific Journal Impact Factor (SJIF - 6.012), InfoBase Index(IB Factor - 3.1), I2OR, ESJI, DRJI, ISRA-JIF, EZB, IIJIF, Google Scholar CNKI Scholar, EBSCO Discovery, Summon(ProQuest), J-Gate, Primo and Primo Central, Indian Science and Cite Factor.

BackgroundSince the global epidemic of the coronavirus disease 2019 (COVID-19), a large number of immunological studies related to COVID-19 have been published in various immunology journals. However, the results from these studies were discrete, and no study summarized the important immunological information about COVID-19 released by these immunology journals. This study aimed to comprehensively summarize the knowledge structure and research hotspots of COVID-19 published in major immunology journals through bibliometrics.MethodsPublications on COVID-19 in major immunology journals were obtained from the Web of Science Core Collection. CiteSpace, VOSviewer, and R-bibliometrix were comprehensively used for bibliometric and visual analysis.Results1,331 and 5,000 publications of 10 journals with high impact factors and 10 journals with the most papers were included, respectively. The USA, China, England, and Italy made the most significant contributions to these papers. University College London, National Institute of Allergy and Infectious Diseases, Harvard Medical School, University California San Diego, and University of Pennsylvania played a central role in international cooperation in the immunology research field of COVID-19. Yuen Kwok Yung was the most important author in terms of the number of publications and citations, and the H-index. CLINICAL INFECTIOUS DISEASES and FRONTIERS IN IMMUNOLOGY were the most essential immunology journals. These immunology journals mostly focused on the following topics: “Delta/Omicron variants”, “cytokine storm”, “neutralization/neutralizing antibody”, “T cell”, “BNT162b2”, “mRNA vaccine”, “vaccine effectiveness/safety”, and “long COVID”.ConclusionThis study systematically uncovered a holistic picture of the current research on COVID-19 published in major immunology journals from the perspective of bibliometrics, which will provide a reference for future research in this field.

Journal of Oral Microbiology Impact Factor 2024-2025 - ResearchHelpDesk - As the first Open Access journal in its field, the Journal of Oral Microbiology aims to be an influential source of knowledge on the aetiological agents behind oral infectious diseases. The journal is an international forum for original research on all aspects of 'oral health'. Articles which seek to understand 'oral health' through exploration of the pathogenesis, virulence, host-parasite interactions, and immunology of oral infections are of particular interest. However, the journal also welcomes work that addresses the global agenda of oral infectious diseases and articles that present new strategies for treatment and prevention or improvements to existing strategies. Topics: Oral health, Microbiome, Genomics, Host-pathogen interactions, Oral infections, Aetiologic agents, Pathogenesis, Molecular microbiology systemic diseases, Ecology/environmental microbiology, Treatment, Diagnostics, Epidemiology, Basic oral microbiology, and taxonomy/systematics. Article types: Original articles, Notes, Review articles, Mini-reviews and commentaries. The Journal of Oral Microbiology is indexed/tracked/covered by the following services: AgBiotechNet (CABI) BIOSIS Previews (Clarivate Analytics) CAB Abstracts (CABI) CAS Directory of Open Access Journals (DOAJ) EMBASE (Elsevier) Global Health (CABI) Health Research Premium Collection HINARI Hospital Premium Collection JournalSeek Open Access Journals Integrated Service System Project (GoOA) Ornamental Horticulture (CABI) Parasitology Database (CABI) Pig News and Information (CABI) Plant Genetics and Breeding Database (CABI) Plant Growth Regulator Abstracts (CABI) ProQuest Central ProQuest Natural Science Collection ProQuest SciTech Collection PubMed (NLM) PubMed Central (NLM) Science Citation Index Expanded (Clarivate Analytics) ScienceOpen SciTech Premium Collection Scopus (Elsevier) Ulrich's Periodicals Directory

The Late Quaternary extinctions of megafauna (defined as animal species > 44.5 kg) reduced the dispersal of seeds and nutrients, and likely also microbes and parasites. Here we use body-mass based scaling and range maps for extinct and extant mammal species to show that these extinctions led to an almost seven-fold reduction in the movement of gut-transported microbes, such as Escherichia coli (3.3–0.5 km 2 d − 1 ). Similarly, the extinctions led to a seven-fold reduction in the mean home ranges of vector-borne pathogens (7.8–1.1km 2 ). To understand the impact of this, we created an individualbased model where an order of magnitude decrease in home range increased maximum aggregated microbial mutations 4-fold after 20 000 yr. We hypothesize that pathogen speciation and hence endemism increased with isolation, as global dispersal distances decreased through a mechanism similar to the theory of island biogeography. To investigate if such an effect could be found, we analysed where 145 zoonotic diseases have emerged in human populations and found quantitative estimates of reduced dispersal of ectoparasites and fecal pathogens significantly improved our ability to predict the locations of outbreaks (increasing variance explained by 8%). There are limitations to this analysis which we discuss in detail, but if further studies support these results, they broadly suggest that reduced pathogen dispersal following megafauna extinctions may have increased the emergence of zoonotic pathogens moving into human populations.

Methods Materials and Methods

Impact of megafauna extinctions on microbial and blood parasite movement

We estimated current global ecto-parasite and fecal pathogen dispersal patterns using the IUCN mammal species range maps for all extant species (removing all bats because mass scaling of dispersal for bats is inaccurate) (N=5,487). To create maps of dispersal patters for a world without the Pleistocene megafauna extinctions, we added species range maps (N=274) of the now extinct megafauna (within 130,000 years) created in Faurby & Svenning (2015a) to the current IUCN based dispersal maps. These ranges estimate the natural range as the area that a given species would occupy under the present climate, without anthropogenic interference. In cases of evident anthropogenic range reductions for extant mammals, like the Asian elephant (Elephas maximus), the current ranges encompass only the IUCN defined ranges but the world without extinctions includes the ranges on these extant animals prior to anthropogenic range reductions. The taxonomy of recent species followed IUCN while the taxonomy of extinct species (which were included if there are dates records less than 130,000 years old) followed Faurby & Svenning (2015b). For each living and extinct animal species, we use body mass estimates (Faurby & Svenning, 2016), with the few species lacking data assigned masses based on the mass of their relatives. We used the following mass based (M: average body mass per species (kg)) scaling equations (recalculated from primary data in Figure S1) to estimate home range (Kelt and Van Vuren, 2001), day range (Carbone et al 2005), and gut retention time (Demment and Van Soest, 1985, Demment 1983):

Equation 1 - Home Range

HR (km2) = 0.04*M1.09

This dataset, originally compiled by Kelt and Van Vuren (2001) (N=113 mammalian herbivores), used the convex hull approach to calculate home range and found the mass-based scaling to be highly size dependent (with mass scaling exponent of >1)

Equation 2 –Mean home range for all mammals per pixel (MHR) or ectoparasite dispersal

MHR (km2) = Σ HRi / n

(i: per pixel species number; n: = number of mammal species per pixel)

We define the mean ectoparasite dispersal per pixel as the average distance a pathogen could travel across all mammals present in the pixel and assuming an equal change of colonizing any mammal species.

Next, we estimate fecal pathogen diffusivity with the following equations. We start with day range (daily distance travelled) originally from Carbone et al 2005 (N=171 mammalian herbivores) but recalculated from primary data in Figure S1.

Equation 3 - Day Range (DR)

DR (km/day) = 0.45*M0.37

Next, to estimate the minimum time a generalist microbe might stay in the body of a mammalian herbivore, we use passage time:

Equation 4 - Passage time (PT) from (Demment and Van Soest, 1985, Demment 1983)

PT (days) = 0.589*D*M0.28

Where D is digestibility, which we set to 0.5 as a parsimonious assumption because the actual value is unknown for many extant and extinct animals.

Distance between consumption and defecation or straight line fecal transmission distance is simply multiplying equation 3 by equation 4:

Equation 5 – Straight-line fecal transmission distance (FTD)

FTD (km) = DR * PT

However, animals rarely move in a straight line, and without any additional information, we can assume a random walk pattern with a probability density function governed by a random walk as:

Equation 6 – Random walk transmission (RWT) per species

RWT (km2/day) = (FTD)2/(2*PT)

Here we define the mean fecal diffusivity as the mean range in any pixel a generalist microbe could travel during its lifetime assuming an equal chance of colonizing any mammal species.

Equation 7 – Mean Fecal Diffusivity (FD)

FD (km2/day) = ∑RWTi/ n

(i: per pixel species number; n: = number of mammal species per pixel)

This equation represents the average distance a fecal pathogen would travel in an ecosystem if it had an equal chance of being picked up by any nearby species walking in a random walk.

EID modelling

We then tested whether these changes in pathogen dispersal distance could help explain the location of 145 new zoonotic diseases that emerged over the past 64 years (Jones et al., 2008). Jones et al 2008 searched the literature to find biological, temporal and spatial data on 335 human EID ‘events’ between 1940 and 2004 of which 145 were defined as zoonotic. We also divide our analysis into vector driven (Table S3), non-vector driven (Table S4) and all diseases (Table 2). To control for spatial reporting bias, they estimated the mean annual per country publication rate of the Journal of Infectious Disease (JID). However, this is not a perfect control for reporting bias as it may bias towards first world countries. In their paper, they used predictor variables of log(JID), log(human population density), human population growth rates, mean monthly rainfall, mammal biodiversity, and latitude. We repeat this study but add our six data layers shown in Figure 1 of animal function, as well as other variables such as rainfall seasonality, total biodiversity (species richness including the now extinct megafauna), biomass weighted species richness and the change in biomass weighted species richness. In total, we tested 16 variables against the EID outbreaks (explained in Table S1). In addition to the 145 known EID outbreaks, we randomly generated ~five times more random points (>600 points) to compare them (all results in the paper are the average of three separate runs where the control points vary randomly) (see Figure S2 as an example distribution).

We then used the Ordinary Least Squares (OLS) multiple regression models to predict the EID events. We used Akaike’s Information Criterion (AIC) for model inter-comparison, corrected for small sample size. Whenever spatial data are used there is a risk of autocorrelation because points closer to each other will have more similar signals than points far from each other. We therefore used Simultaneous Auto-Regressive (SARerr) models (Table 2) to account for spatial autocorrelation (Dormann et al., 2007) using the R library ‘spdep’ (Bivand, Hauke, & Kossowski, 2013). SAR-err reduces the sample size by assuming that all outbreaks within the same neighbourhood are the same. We examined possible neighbourhood sizes to determine how effective each was at removing residual autocorrelation from model predictions. We defined neighbourhoods by distance to the sample site. We tried distances from 5 km to 300 km and found that AIC was minimized at 200 km (Figure S3 – the average of 16 simulations). Following this reduction of our dataset, our correlogram (Figure S4) indicates vastly reduced spatial autocorrelation. We estimated the overall SAR model performance by calculating the square of the correlation between the predicted (only the predictor and not the spatial parts) and the raw values. We will refer to this as pseudo-R2 in the paper even though we are aware that several different estimates of model fit are frequently referred to as pseudo-R2. We also did a VIF analysis using the R package usdm (Naimi et al., 2014) to control for multicollinearity and all VIFs of the predictor variables are below 1.5 showing little multicollinearity.

Individual based model

To establish whether the loss of terrestrial megafauna increased microbe heterogeneity, we used Matlab (Mathworks) to create an individual based model (IBM) with two randomly distributed animal species carrying a generalist microbe. We varied our model assumptions (parentheses below) in sensitivity studies (Tables S7). The IBM consisted of a 500x500 cell grid (300x300 and 1000x1000 – in our sensitivity study, we tried big and small grids) with species A in 10% (5 and 20%) of randomly selected cells and species B also in 10% (5 and 20%) of cells. 10% (5 and 20%) of animals contained the generalist microbe. We then created a 9 by 9 grid around each of species A. This was considered the home range of the species and the group of animals would interact with all other groups of animals within that home range. We assumed the home range of species B to be one grid cell. We make a simple assumption that mutations in this generalist microbe increase linearly with time until two animals interact, at which point the

Comparison of journal self-citations in COVID-19 with other infectious diseases.

Standardized incidence ratios (p-values) were estimated using the multivariate regression model.*Factor excluded using stepwise analysis.†Significant factors (boldface).‡Non-significant factors kept using stepwise analysis.

ELife Impact Factor 2024-2025 - ResearchHelpDesk - eLife welcomes the submission of Research Articles, Short Reports, Tools and Resources articles, Research Advances, Scientific Correspondence and Review Articles in the subject areas below. Biochemistry and Chemical Biology; Cancer Biology; Cell Biology; Chromosomes and Gene Expression; Computational and Systems Biology; Developmental Biology; Ecology; Epidemiology and Global Health; Evolutionary Biology; Genetics and Genomics; Human Biology and Medicine; Immunology and Inflammation; Microbiology and Infectious Disease; Neuroscience; Physics of Living Systems; Plant Biology; Stem Cells and Regenerative Medicine; Structural Biology and Molecular Biophysics eLife is a selective, not for profit peer-reviewed open access scientific journal for the biomedical and life sciences. It was established at the end of 2012 by the Howard Hughes Medical Institute, Max Planck Society, and Wellcome Trust, following a workshop held in 2010 at the Janelia Farm Research Campus. Together, these organizations provided the initial funding to support the business and publishing operations. In 2016, the organization committed US$26 million to continue the publication of the journal.

BackgroundTuberculosis (TB) is an infectious disease with a significant impact on public health, with the pulmonary form being the most critical. The disease poses numerous risks to the elderly population, as it often manifests concomitantly with other age-related illnesses, thereby complicating its diagnosis and management. Several causal and associated factors contribute to the disease.ObjectiveThe objective of this manuscript is to present a scoping review protocol aimed at mapping the available literature on factors associated with and contributing to the incidence of Pulmonary Tuberculosis (PTB) in the elderly.Methods and analysisThe scoping review protocol was developed following the guidelines of the Joanna Briggs Institute (JBI) and the PRISMA-ScR checklist, and it has been registered on the Open Science Framework (DOI: 10.17605/OSF.IO/DHQVP). The databases to be searched include Medline via PubMed, Lilacs, Web of Science, Scopus, Embase, as well as gray literature through Google Scholar and the Brazilian Coordination for the Improvement of Higher Education Personnel (CAPES) Thesis and Dissertation Catalog. The search strategy is grounded on a research question formulated using the PCC acronym (P–Population; C–Concept; C–Context). Peer-reviewed journal articles, scientific books, editorials, conference proceedings, and theses/dissertations published in Portuguese, English, or Spanish between 2014 and 2024 will be included.DiscussionElderly individuals are more susceptible to diseases due to the natural decline in immune response to Mycobacterium tuberculosis, the causative agent of tuberculosis. In this age group, symptoms are often difficult to detect. Understanding the causal and associated factors of the disease contributes to favorable outcomes and helps reduce the transmission chain to the rest of the population.

Sensitivity index of each variable to .

Intrapersonal factors.

IntroductionJournal self-citation contributes to the overall citation count of a journal and to some metrics like the impact factor. However, little is known about the extent of journal self-citations in COVID-19 research. This study aimed to determine the journal self-citations in COVID-19 research and to compare them according to the type of publication and publisher.MethodsData in COVID-19 research extracted from the Web of Science Core Collection 2020–2023 was collected and further analyzed with InCites. The journals with the highest self-citation rates and self-citation per publication were identified. Statistical comparisons were made according to the type of publication and publishers, as well as with other major infectious diseases.ResultsThe median self-citation rate was 4.0% (IQR 0–11.7%), and the median journal self-citation rate was 5.9% (IQR 0–12.5%). 1,859 journals (13% of total coverage) had self-citation rates at or above 20%, meaning that more than one in five references are journal self-citations. There was a positive and statistically significant correlation of self-citations with the other indicators, including number of publications, citations, and self-citations per publication (p

Johne's disease (JD), a persistent and slow progressing infection of ruminants such as cows and sheep, is caused by slow replicating bacilli Mycobacterium avium subspecies paratuberculosis (MAP) infecting macrophages in the gut. Infected animals initially mount a cell-mediated CD4 T cell response against MAP which is characterized by the production of interferon (Th1 response). Over time, Th1 response diminishes in most animals and antibody response to MAP antigens becomes dominant (Th2 response). The switch from Th1 to Th2 response occurs concomitantly with disease progression and shedding of the bacteria in feces. Mechanisms controlling this Th1/Th2 switch remain poorly understood. Because Th1 and Th2 responses are known to cross-inhibit each other, it is unclear why initially strong Th1 response is lost over time. Using a novel mathematical model of the immune response to MAP infection we show that the ability of extracellular bacteria to persist outside of macrophages naturally leads to switch of the cellular response to antibody production. Several additional mechanisms may also contribute to the timing of the Th1/Th2 switch including the rate of proliferation of Th1/Th2 responses at the site of infection, efficiency at which immune responses cross-inhibit each other, and the rate at which Th1 response becomes exhausted over time. Our basic model reasonably well explains four different kinetic patterns of the Th1/Th2 responses in MAP-infected sheep by variability in the initial bacterial dose and the efficiency of the MAP-specific T cell responses. Taken together, our novel mathematical model identifies factors of bacterial and host origin that drive kinetics of the immune response to MAP and provides the basis for testing the impact of vaccination or early treatment on the duration of infection.

Index system of influenza influencing factors in Hubei Province.

Poisson multiple regression models of the impact of the coronavirus disease pandemic on hospital admissions for chronic non-communicable diseases (NCDs) in Brazil according to the type of NCDs.

We investigated the social, emotional, and cognitive predictors of adherence to four health behaviors (handwashing, mask wearing, social contact limitations, and physical distancing) during one critical phase of the COVID-19 pandemic. We collected data (N = 5803, mean age = 53; 57% women) in Belgium at five time points between April and July 2021, a time during which infections evolved from high (third wave of the pandemic) to low numbers of COVID-19 cases. The results show that the social, emotional, and cognitive predictors achieved high levels of explained variance (R2 > .60). In particular, the central components of behavioral change (attitudes, intentions, control, habits, norms, and risk) were the strongest and most consistent predictors of health behaviors over time. Likewise, autonomous motivation and empathetic emotions (e.g., attentive, compassionate) had a positive impact on health behavior adherence, whereas it was the opposite for lively emotions (e.g., active, enthusiastic). These results offer policymakers actionable insights into the most potent and stable factors associated with health behaviors, equipping them with effective strategies to curtail the spread of future infectious diseases.

BackgroundIn India, the prevalence of overweight and obesity has increased rapidly in recent decades. Given the association between overweight and obesity with many non-communicable diseases, forecasts of the future prevalence of overweight and obesity can help inform policy in a country where around one sixth of the world’s population resides.MethodsWe used a system of multi-state life tables to forecast overweight and obesity prevalence among Indians aged 20–69 years by age, sex and urban/rural residence to 2040. We estimated the incidence and initial prevalence of overweight using nationally representative data from the National Family Health Surveys 3 and 4, and the Study on global AGEing and adult health, waves 0 and 1. We forecasted future mortality, using the Lee-Carter model fitted life tables reported by the Sample Registration System, and adjusted the mortality rates for Body Mass Index using relative risks from the literature.ResultsThe prevalence of overweight will more than double among Indian adults aged 20–69 years between 2010 and 2040, while the prevalence of obesity will triple. Specifically, the prevalence of overweight and obesity will reach 30.5% (27.4%-34.4%) and 9.5% (5.4%-13.3%) among men, and 27.4% (24.5%-30.6%) and 13.9% (10.1%-16.9%) among women, respectively, by 2040. The largest increases in the prevalence of overweight and obesity between 2010 and 2040 is expected to be in older ages, and we found a larger relative increase in overweight and obesity in rural areas compared to urban areas. The largest relative increase in overweight and obesity prevalence was forecast to occur at older age groups.ConclusionThe overall prevalence of overweight and obesity is expected to increase considerably in India by 2040, with substantial increases particularly among rural residents and older Indians. Detailed predictions of excess weight are crucial in estimating future non-communicable disease burdens and their economic impact.

Impact of vital signs, age and laboratory parameters on mortality following COVID-19 infection.