Indian Journal of Community Medicine最新文献

Background: Anaemia is a major public health problem among women, and it accounts for a high risk of morbidity and mortality. Community-based studies to identify the determinants and risk factors of anaemia in the local population will be critical in guiding timely and effective interventions. The objective of the study was to estimate the prevalence and contributing factors of anaemia among women in the reproductive age group in the rural Chengalpattu district.

Materials and methods: A cross-sectional study was conducted among 438 non-pregnant women of reproductive age in rural Chengalpattu district from 2022 to 2023. A multistage random sampling technique was used to select the study participants. Data collected using a pre-tested semi-structured questionnaire were analysed using bivariate and multivariate logistic regression analyses using the software Statistical Package for Social Sciences version 21.

Results: The prevalence of anaemia is 37.4%. Multivariate logistic regression analysis established a positive association between anaemia and unemployment [Adjusted B coefficient (AC) =1.758 (95% CI: 1.096-2.819)], lower socioeconomic status [AC = 2.301 (95% CI: 1.508-3.51)], inadequate dietary intake of iron [AC = 1.594 (95% CI: 1.038-2.45)], high perceived stress [AC = 3.948 (95% CI: 2.437-6.397)], irregular menstrual cycles [AC = 1.869 (95% CI: 1.199-2.914)] and heavy menstrual bleeding [AC = 2.814 (95% CI: 1.475-5.369)].

Conclusion: Health education on fortified foods and encouraging participation in village health nutrition day programme could enhance knowledge about locally available iron-rich foods. Moreover, integrating anaemia screening into routine non-communicable disease screening by multipurpose health workers at the community level can ensure early diagnosis and treatment.

Background: Maternal and neonatal health remains a public health priority, especially in marginalized tribal populations where maternal morbidity and mortality are disproportionately high due to the socio-cultural barriers and limited healthcare access. The Birth Preparedness and Complication Readiness (BPACR) index is used to assess the readiness of pregnant women and their families to handle complications, but its applicability in tribal regions needs further investigation. To assess knowledge, attitude, and practice (KAP) regarding BPACR among pregnant women in a tribal region of Maharashtra and to explore the relationships between KAP and BPACR scores using structural equation modelling (SEM).

Materials and methods: A cross-sectional survey was conducted among 384 pregnant women from tribal areas of Maharashtra. The BPACR questionnaire assessed observed and latent KAP variables. SEM with confirmatory factor analysis (CFA) explored associations between variables such as education, income, age at marriage, and KAP. Model fit was evaluated using χ², comparative fit index (CFI), Tucker-Lewis Index (TLI), root-mean-square error of approximation (RMSEA), and standardized root mean square residual (SRMR).

Results: The SEM model showed excellent fit (CFI = 0.996, RMSEA = 0.025, SRMR = 0.021). Knowledge and practice were significant predictors of BPACR scores, with higher knowledge of maternal health and antenatal care associated with better preparedness. Socio-demographic factors like education also significantly influenced BPACR scores.

Conclusion: Improving knowledge and practices around maternal health enhances birth preparedness among tribal women. Targeted education and health promotion interventions are essential to address the unique challenges faced by these communities, with a focus on overcoming socio-cultural barriers.

Background: Sustainable Development Goals (SDG) calls for the elimination of open-air defecation (OAD) by 2030. Despite of many interventions including the recent Swachh Bharat Mission of India, its prevalence is high. Hence, this study was planned to estimate the burden and factors involved in practice of OAD and to explore the perception of people about it.

Methods: Explanatory sequential mixed methods design was adopted. (Quan: Community-based cross-sectional survey; qual: Focus Group Discussion (FGD)). Randomly selected adults of any gender residing in the study villages participated. A structured questionnaire was used for the survey, and those who practiced OAD were purposively selected for FGD. Adjusted odds ratio was calculated and reported with its 95% confidence interval. Analysis was done in SPSS software.

Results: A total of 171 adults participated; of them, 56.7% were of the age group of 30-59 years; 69.6% were females. The prevalence of OAD was 58.5% (95% CI: 50.7-65.9). Multivariate binary logistic regression analysis showed that participants who either were illiterate or completed up to primary school, who lived in kutcha house and semi-pucca house, had 15.3 times (95% CI: 1.4-161), 9 (95% CI: 1.5-10.2) and 6.3 (95% CI: 1.8-22.2), higher odds of practicing OAD, respectively. The manual content analysis of the transcript resulted in emergence of two themes, namely, hindering and facilitating factors for OAD.

Conclusion: The prevalence of OAD was higher among the tribal predominant study population. Those who had lower education status and living in kutcha house were at higher risk. Interventions addressing the identified factors remain essential to achieve SDG.

Background: This descriptive cross-sectional study was undertaken to assess the quality of life (QOL) and to determine the factors affecting QOL in breast cancer patients.

Materials and methods: The data from 121 breast cancer patients attending the Tertiary Cancer Care Centre (TCCC) was gathered by interview technique using the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaires-Core-30 and Breast-23 (QLQ-C30 and QLQ-BR23) questionnaires.

Results: The mean age at presentation was 51.10 ± 11.45 years, and 73% of breast cancer patients belonged to rural areas. The patients with an advanced stage of disease had the lowest scores on almost all functional scales, including physical, cognitive, emotional, and global. The young breast (20-34 years) cancer survivors showed significantly worse QOL outcomes compared with older age groups (50-64 years) on all other functional scales, except for future perspectives and upset by hair loss. Other factors that affected the quality of life of patients during treatment were the participants' education level, occupation, and place of residence.

Conclusion: Age, education status, occupation, stage of disease at presentation, and place of residence are a few factors that significantly affect QOL in Carcinoma breast patients. The study may provide insights into how to improve life conditions in breast cancer patients and, thus, their survival.

Human metapneumovirus (hMPV) is among the common sources of acute respiratory infection (ARI) that appears especially during the winter and spring season. The virus remains in circulation around the world and has been reported to contribute 5-25% of ARIs, particularly among the elderly, young children, and immunocompromised people. However, still a few gaps exist in its diagnostics, therapeutics, and many other research areas concerning hMPV, which need to be addressed to completely understand its exact impact and situation. In order to present much of the relevant information related to hMPV, a detailed literature review was conducted. A targeted search strategy was executed across relevant bibliographic databases, ensuring a broad and inclusive retrieval of pertinent studies. Phylogenetic analyses indicate a complex and dynamic hMPV epidemiology, with localized outbreaks. Studies demonstrate that hMPV infection is most prevalent in early childhood. Its symptoms may include from mild flu or cold-like symptoms to serious complications like bronchitis or pneumonia. Molecular diagnostics techniques including polymerase chain reaction (PCR), reverse-transcriptase PCR, multiplex assays, and array-based technologies are used for hMPV detection. Ongoing research aims to develop antiviral therapies as supportive care constitutes the current clinical standard for hMPV infection as specific antiviral treatments are unavailable. By clearly delineating critical research priorities, this article intends to inform and guide decision-makers in tackling the complex scientific and technological challenges associated with hMPV. Enhanced global surveillance is necessary to monitor hMPV epidemiology, especially in resource-constrained areas.

Background: Diabetes and hypertension pose significant public health challenges, especially among underprivileged urban populations. This study estimated the prevalence of these conditions and assessed associated cardiovascular disease (CVD) lifestyle risk factors among adults in an underprivileged urban community in Bangalore, India.

Materials and methods: A cross-sectional study was conducted from March to September 2022 in an underprivileged community in Bangalore, involving 1,298 participants. Data were collected through house-to-house surveys using a structured questionnaire and clinical measurements, including blood sugar, blood pressure, and anthropometric parameters. Logistic regression was used to identify associations between sociodemographic factors and health outcomes.

Results: The prevalence of diabetes and hypertension was 9.3% (95% CI: 7.8%-10.9%) and 19.1% (95% CI: 16.9%-21.2%), respectively, among the 1,298 participants. Diabetes prevalence was higher in females (13.1% CI: 10.6%-15.6%) than in males (4.9% CI: 3.1%-6.7%), while hypertension was common in older adults, especially those aged 60 and above (63.6% CI: 54.6%-72.6%). High body mass index (BMI > 30) showed significant associations with both conditions (OR: 1.7 for diabetes, OR: 1.4 for hypertension). Frequent consumption of tobacco, red meat, bakery items, aerated drinks, and central obesity were also linked to these conditions. A considerable proportion of diabetes (7.1% CI: 5.8%-8.4%) and hypertension (21.6% CI: 9.2%-23.9%) cases were undiagnosed before the study.

Conclusion: The study reveals a high prevalence of diabetes and hypertension among the urban poor, with many undiagnosed cases. Targeted screening and intervention programs are essential to address modifiable risk factors like diet and obesity, aiming to reduce the CVD burden in similar communities.

Background: Obesity poses an alarming threat for NCDs like cardiovascular disease, diabetes, etc., Weight circumference, Weight-Height-Ratio like indices assess obesity related disease. To study distribution of obesity in rural North-Indian population and efficiency of indices like WC, BMI for predicting obesity related health risk.

Materials and methods: The cross-sectional study was done among the rural population in two blocks of Dehradun districts of Uttarakhand. The study pretested questionnaire was used to obtain demographic information and calibrated equipment were used for Weight, height, BP, WC. Blood samples of all participants were taken in ICMR laboratory for blood sugar and lipid profiles. The institutional ethical clearance was taken for the study. After obtaining institutional ethical clearance, all data were trimmed and analyzed using SPSS. Age, weight, height, WC, WHtR were presented as Mean ± SD. Chi-square and t-test were used for categorical data. Regression analysis was used to assess better tools for health risk prediction.

Results: The mean age of 456 participants was 48.8 years. 31.8% of participant are obese (average BMI = 30.32 kg/m² and WC = 83.22 cm). Around 42% of obese belong to age 16-44 years. WC was significantly higher (P < 0.005) than BMI among obese females. Obesity possesses significant risk of Dyslipidemia, Hypertension, and Diabetes independently (P < 0.005). WC can be considered as proxy to predict health related risk (AUC = 0.973) compared to BMI (AUC = 0.767).

Conclusions: This study confirms the obesity related health risk increase irrespective of type of obesity. However, WC can better predict the health risk compared to BMI.

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.