Indian Journal of Community Medicine最新文献

Mental and behavioral disorders impact over 25% of people worldwide, affecting quality of life and economic stability. In India, 14.9% of the population faces mental illness, with higher rates in rural areas. The elderly, especially in rural regions, face unique challenges like social isolation and abuse. This study evaluates awareness, attitudes, and practices regarding mental disorders among the rural elderly to aid stigma reduction and guide government policies. This qualitative study involved 10 focus group discussions (FGDs). Discussions were held at local health centers and schools. Ethical approval was obtained from the local ethics committee, and data collection was authorized by the Chief District Health Officer. Discussions were recorded, transcribed, and analyzed for key themes. Analysis revealed mixed information about mental illness. While some participants recognized symptoms like "sitting alone," they often confused them with physical issues or spiritual possession. Attributions for mental illness included stress, financial problems, family issues, and alcoholism, with misconceptions such as evil spirit possession. Attitudes varied; some favored compassionate treatment while others prioritized physical health or viewed mental illness as taboo. Traditional healers were preferred over medical treatments, though some supported allopathic approaches. Participants requested more mental health awareness, financial aid, and better guidance from health workers. The study highlights a mixed understanding of mental health among the elderly, with both accurate and erroneous beliefs. Recommendations include enhanced mental health awareness, integrated screenings, and training for health workers, alongside collaboration with traditional healers to correct misconceptions and promote appropriate care.

Background: Integrated and Enhanced Surveillance and Epidemiology (IESE) framework is a key surveillance tool for monitoring the level and trends of the human immunodeficiency virus (HIV) and related co-infections in the country.

Objectives: This paper describes the level and trends of the human immunodeficiency virus (HIV) epidemic in the country, along with the sero-prevalence of the related infections based on the various surveillance surveys and disease burden activities undertaken under the IESE framework.

Materials and methods: HIV sentinel surveillance (HSS) monitors the prevalence of HIV, Syphilis, hepatitis B, and hepatitis C in eight population groups through periodic facility-based surveys. The collected data is then used in estimating the HIV burden using a globally used modeling tool. Here, we present the results from the latest round of HSS and HIV disease burden estimation to highlight epidemic status by location and population.

Results: In 2023, adult HIV prevalence was 0.20% nationally, with a 44% drop in annual new infections and a 79% drop in acquired immune deficiency syndrome (AIDS)-related deaths since 2010. The incidence-prevalence ratio was 2.69, and the incidence-mortality ratio was 1.15 in 2023. The proportion of people living with HIV (PLHIV) aged 50+ among total PLHIV increased from 17% in 2000 to 37% in 2023. Two states and 29 districts had over 1% prevalence, with rising new infections in six states/union territories: Tripura, Arunachal Pradesh, Meghalaya, Punjab, Dadra and Nagar Haveli and Daman and Diu, and Assam. HIV prevalence ranged from 0.89% among migrants to 9.03% among people who inject drugs (PWID). Among HIV-positive individuals, syphilis sero-positivity was between 1% and 1.84%.

Conclusion: The HIV/acquired immune deficiency syndrome (AIDS) epidemic in India remains low nationally, with new infections and AIDS-related deaths declining faster than global averages. However, certain states and key populations are experiencing a rising epidemic, potentially due to injecting drug use and casual heterosexual risk behavior. The high prevalence of co-infections necessitates integrated care to reduce morbidity and mortality among those infected.

The unpredictable nature of cancer, along with the absence of noticeable symptoms, makes it essential to accurately predict patient survival in order to enhance treatment results. Conventional approaches often struggle with the complexity of cancer. As digitization continues to grow, advanced machine learning and deep learning models are increasingly used to improve survival predictions. This paper aims to identify the survival analysis models applied in cancer prediction, highlight recent advancements, and suggest directions for future research. A literature search was conducted using three databases: ScienceDirect, IEEE Xplore, and PubMed. Boolean search strategies were used to locate relevant studies published in the last 15 years. The PRISMA guidelines were followed to review and select articles based on predefined inclusion criteria. This review critically examines 51 articles, focusing on the transition from traditional statistical methods to more advanced machine learning techniques. The findings show a growing trend towards using clinical data, even when the data sets are limited, and an increasing interest in hybrid and deep learning models for survival prediction. While traditional machine learning methods still hold a majority, the potential of deep learning and integrated techniques is gaining wider recognition. The findings emphasize the need for improved machine learning approaches to achieve more accurate survival predictions and encourage further research into deep learning models. It offers valuable insights for researchers at all levels, providing an overview of current methods and potential areas for future exploration in cancer survival analysis.

Objectives: Premenstrual symptoms, commonly referred to as PMS symptoms, pose difficulties for women in the workforce, impacting their efficiency and overall health. This research sought to explore if a short, online integrated yoga module, customized for working women, could help reduce PMS symptoms.

Materials and methods: A group of 76 employed women (23 to 38 years) in Mumbai and Delhi, self-reporting premenstrual syndrome (PMS), were recruited through social media advertisements and split into two groups: The experimental group (n = 40) received yoga sessions for 12 weeks (five sessions per week), each lasting between 18 and 24 minutes; the other served as the control group (n = 36). The control group did not engage in any yoga activities. Both groups completed the Premenstrual Symptoms Screening Tool (PSST) questionnaire before and after the study. t-test statistics were used to evaluate the effects of the intervention on reported PMS symptoms.

Results: The yoga group showed improvements in 11 of the 14 (Emotional, Behavioral, and Physical) PMS symptoms (P < 0.05) and four out of five functional impairment symptoms (P < 0.05) of the PSST after the intervention. Paired t-tests within the control group did not reveal any changes before and after the intervention.

Conclusion: Results highlight that the tailored 5 days a week online, integrated yoga module for working women significantly relieves most of the PMS symptoms and can be prescribed for the treatment of PMS for working women.

Introduction: Diarrheal diseases along with dysentery, remain a significant cause of illness and death among children under five in developing regions. This study aimed to determine the 1-year cumulative incidence of dysentery and examine its association with socio-environmental factors among underprivileged urban populations in Bhopal.

Methods: We conducted a prospective cohort study involving 620 children under five recruited from both slum areas and Basic Services for Urban Poor (BSUP) colonies in Bhopal. Monthly follow-ups were carried out for 1 year to document incident dysentery cases (acute diarrhea with visible blood in stool) and gather socio-environmental data. Cumulative incidence of dysentery was calculated. Logistic regression analyses were performed to assess associations between these socio-environmental variables and dysentery incidence.

Results: Overall, 15.4% of children experienced dysentery over 1 year. Children in slum areas showed a significantly higher cumulative incidence (19.0%) compared with those residing in BSUP colonies (11.7%). Multivariable logistic regression confirmed that living in a slum was associated with an elevated risk (adjusted OR = 1.85; 95% CI: 1.13-3.02; P = 0.015). Other variables-such as age, sex, socioeconomic status, water source, sanitation, and in-home hygiene indicators-were not statistically significant.

Conclusion: The findings reveal a substantial burden of dysentery among underprivileged children in urban Bhopal, particularly within slum environments. These results highlight the potential health benefits of improved housing and sanitation, as evidenced by lower dysentery incidence in BSUP areas. Targeted public health interventions are warranted to alleviate the impact of dysentery in vulnerable communities.

India's medical device sector is experiencing growth and technological advancements, driven by increased interest and government support in research and development. To promote innovation, significant amount of time and resources are spent on research and development before realization of a final product. To optimize the judicious allocation of these limited resources, the implementation of Health Technology Assessment (HTA) during the early phases of product development and testing should be adopted. Conducting early HTA enables an innovator to make well-informed decisions, demonstrate value to stakeholders, and improve market access by determining an appropriate price for the device which represents its value. The health economic models can be used throughout the life cycle of the innovation to inform decision making; however, the challenge lies in the lack of awareness regarding early HTA. It is thus imperative to increase knowledge and build capacity of the researchers, and foster collaboration between innovators and government organizations to realize the true potential of early HTA.

Background: There is an increased incidence of patients coming to a hospital in the post-COVID-19 clinic for symptoms related to the musculoskeletal (MSK) system. The aim of our study is to know the MSK symptoms and post-COVID functional status in COVID-19 patients at 1-year postrecovery and identify any factors associated with the increased incidence and severity of the MSK symptoms.

Methodology: A single-center prospective observational study was undertaken among 1954 in-patients diagnosed with COVID-19 from March 1, 2020 to December 31, 2020. Informed verbal consent was taken from the patients; they were followed up, and data were collected telephonically using a questionnaire and analyzed.

Results: Among 1954 patients, 1087 had MSK symptoms, the most common being fatigue (50.71%), followed by myalgia, backache, and joint pain. Symptomatic COVID-19 patients had significantly higher incidence of MSK symptoms. The post-COVID-19 functional limitation was more in the MSK group (88.78%) as compared to the non-MSK group (55.02%). The presence of symptoms during COVID-19 had 3.37 times higher risk for developing joint pain. Patients with ≥2 comorbidities had 2.27 times higher risk to develop joint pain.

Conclusion: The majority of patients reported to have achieved their previous physical status after COVID-19 within a 1 month. Fatigue (50.71%) was noted to be the most common MSK symptom among COVD-19 survivors. The functional limitation was more after symptomatic COVID-19. Risk of having long-term joint pain was elevated if the patient had COVID-19 symptoms and ≥2 comorbidities. To evaluate MSK symptoms over a longer period of time and determine whether they result in hospital visits, more research is needed.

Snakebite is a neglected tropical disease that requires attention. The mortality due to snakebite is highest in India as compared to other countries. This review aims to investigate underlying factors influencing the treatment seeking behaviour and its impact on snakebite related mortality. Articles were reviewed rigorously on online databases PubMed, Medline, Web of Science, and Google Scholar. The search strings used were "snake bite" [MeSH Terms] AND "treatment seeking behavior" [MeSH Terms]. A total of 22 articles were retrieved, and 12 articles were considered relevant for the final review. Primarily, the delay in obtaining care, attributed to a lack of understanding regarding various snake species, biting behaviors, and their venomous properties attributes to the snakebite fatality. Overreliance on conventional treatments and religious beliefs significantly influences treatment-seeking behavior. The choice of treatment for snakebite directly influences snakebite mortality. Delays in seeking treatment increase mortality and the chance of long-term consequences (amputations, kidney failure, etc.). The treatment-seeking behavior impacts snakebite mortality. The main cause of delay in snakebite treatment is largely dependent on snakebite victim's beliefs regarding snakebite management.