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Fruit diseases brought on by fungus infestation leads to postharvest losses of fresh fruit. Approximately 30% of harvested fruits do not reach consumers’ plates due to postharvest losses. Fungal pathogens play a substantial part in those losses, as they cause the majority of fruit rots and consumer complaints. Understanding fungal pathogenic processes and control measures is crucial for developing disease prevention and treatment strategies. In this review, we covered the presented pathogen entry, environmental conditions for pathogenesis, fruit’s response to pathogen attack, molecular mechanisms by which fungi infect fruits in the postharvest phase, production of mycotoxin, virulence factors, fungal genes involved in pathogenesis, and recent strategies for protecting fruit from fungal attack. Then, in order to investigate new avenues for ensuring fruit production, existing fungal management strategies were then assessed based on their mechanisms for altering the infection process. The goal of this review is to bridge the knowledge gap between the mechanisms of fungal disease progression and numerous disease control strategies being developed for fruit farming.

A vital component of any country's economic growth is agricultural development. Food scarcity is one of the major concerns, owing to the negative consequences of environmental factors. By minimizing the adverse environmental impacts, enhancing food security and productivity, and fostering social and commercial equity, nanotechnology has the possibility to have a beneficial influence on the agrifood industries. This will increase input efficiency and decrease relevant losses. Through physical and chemical processes, the development of nanoparticles (NPs) has a detrimental effect on the ecosystem. Thus, in the past few decades, nanotechnology investigations have shifted toward green synthesis to support the growing use of NPs. Green synthesis using various microorganisms offers a more reliable and sustainable alternative to traditional synthetic techniques for producing NPs in biocompatible protocols. One of the most beneficial applications of the increased specific surface area of ‘nanomaterials’ is in the production of nanofertilizers. Additionally, as distinct agrochemical carriers, nanoparticles allow for the sitetargeted, regulated nutrition delivery with improved crop protection. The current review addresses the updated information on diverse use of greensynthesized metallic NPs for sustainable agriculture development.

Unmanned Aerial Vehicles have proven to be helpful in domains like defence and agriculture and will play a vital role in implementing smart cities in the upcoming years. Object detection is an essential feature in any such application. This work addresses the challenges of object detection in aerial images like improving the accuracy of small and dense object detection, handling the class-imbalance problem, and using contextual information to boost the performance. We have used a density map-based approach on the drone dataset VisDrone-2019 accompanied with increased receptive field architecture such that it can detect small objects properly. Further, to address the class imbalance problem, we have picked out the images with classes occurring fewer times and augmented them back into the dataset with rotations. Subsequently, we have used RetinaNet with adjusted anchor parameters instead of other conventional detectors to detect aerial imagery objects accurately and efficiently. The performance of the proposed three step pipeline of implementing object detection in aerial images is a significant improvement over the existing methods. Future work may include improvement in the computations of the proposed method, and minimising the effect of perspective distortions and occlusions.

Introduction Studies have shown that osteoporotic patients are more likely to have medical or surgical complications postoperatively. In this study, we determine the predictive value of various comorbidities on the likelihood of postoperative complications, mortality, and 30-day readmission following cement augmentation for osteoporotic vertebral compression fractures (OVCFs). Materials and Methods A retrospective analysis of the American College of Surgeons National Surgery Quality Improvement Project (ACS-NSQIP) database from 2007 to 2014 identified 1979 patients who met inclusion criteria. A multivariate logistic regression analysis was utilized to determine the relationship between various comorbidities and perioperative mortality, postoperative complications, and 30-day readmission rates. Results A history of cerebrovascular accident (CVA), coagulopathy, diminished preoperative functional status, and/or an American Society of Anesthesiologists (ASA) class > 2 were statistical predictors of postoperative complications. CVA generated the highest odds ratio among these comorbidities (OR = 5.36, p = 0.02 for minor complications; OR = 4.60 p = 0.05 for major complications). Among the 15 comorbidities considered, steroid use (OR =1.81; p = 0.03) and an ASA class > 2 (OR = 14.65; p = 0.01) were the only ones that were correlated with mortality; an ASA class > 2 had a particularly strong effect on the likelihood of mortality (OR = 14.65). Chronic obstructive pulmonary disorder (COPD), obesity, significant weight loss, and an ASA class > 2 were correlated with 30-day readmissions. Congestive heart failure (CHF), diabetes, dialysis, hypertension, or smoking was not correlated with adverse postoperative outcomes. Conclusion Of the 15 comorbidities considered in this study, four were statistically associated with increased rates of postoperative complications, two were associated with increased mortality, and four were associated with increased rates of readmission at 30 days. The presence of CHF, diabetes mellitus (DM), hypertension, ascites, renal failure, or smoking were not associated with the adverse outcomes studied. Level of Evidence III.

Background: Alcohol use among adolescents is rising globally. This habit starts in adolescence and continues throughout their life. Alcohol addiction is associated with many other risky behaviors. Social environmental interventions will be an effective measure to control the problem of alcohol use. Objectives: The purpose of this study was to estimate the prevalence of alcohol use among adolescents and to investigate the associated risk and protective factors. Methods: A cross-sectional study was carried out among school going adolescents in the hilly state Himachal. A pre-validated, self-administered questionnaire was used for data collection. Results: The prevalence of alcohol use in adolescent was 6.1% (10.7% in males and 0.4% in females). Binary logistic regression model revealed that parent's and peer's drinking behavior significantly predicts an adolescent's drinking behavior. Conclusion: Our research supports the need for an adolescent health program involving school, peers, and family. Life skill education should be given to the adolescents to inculcate the resilience so that they learn to say no to peers who try to pull them into such habits.

Objectives We verified subnational (state/union territory (UT)/district) claims of achievements in reducing tuberculosis (TB) incidence in 2020 compared with 2015, in India.Design A community-based survey, analysis of programme data and anti-TB drug sales and utilisation data.Setting National TB Elimination Program and private TB treatment settings in 73 districts that had filed a claim to the Central TB Division of India for progress towards TB-free status.Participants Each district was divided into survey units (SU) and one village/ward was randomly selected from each SU. All household members in the selected village were interviewed. Sputum from participants with a history of anti-TB therapy (ATT), those currently experiencing chest symptoms or on ATT were tested using Xpert/Rif/TrueNat. The survey continued until 30 Mycobacterium tuberculosis cases were identified in a district.Outcome measures We calculated a direct estimate of TB incidence based on incident cases identified in the survey. We calculated an under-reporting factor by matching these cases within the TB notification system. The TB notification adjusted for this factor was the estimate by the indirect method. We also calculated TB incidence from drug sale data in the private sector and drug utilisation data in the public sector. We compared the three estimates of TB incidence in 2020 with TB incidence in 2015.Results The estimated direct incidence ranged from 19 (Purba Medinipur, West Bengal) to 1457 (Jaintia Hills, Meghalaya) per 100 000 population. Indirect estimates of incidence ranged between 19 (Diu, Dadra and Nagar Haveli) and 788 (Dumka, Jharkhand) per 100 000 population. The incidence using drug sale data ranged from 19 per 100 000 population in Diu, Dadra and Nagar Haveli to 651 per 100 000 population in Centenary, Maharashtra.Conclusion TB incidence in 1 state, 2 UTs and 35 districts had declined by at least 20% since 2015. Two districts in India were declared TB free in 2020.

Nowadays, effective cancer therapy is a global concern, and recent advances in nanomedicine are crucial. Cancer is one of the major fatal diseases and a leading cause of death globally. Nanotechnology provides rapidly evolving delivery systems in science for treating diseases in a site-specific manner using natural bioactive compounds, which are gaining widespread attention. Nanotechnology combined with bioactives is a very appealing and relatively new area in cancer treatment. Natural bioactive compounds have the potential to be employed as a chemotherapeutic agent in the treatment of cancer, in addition to their nutritional benefits. Alginate, pullulan, cellulose, polylactic acid, chitosan, and other biopolymers have been effectively used in the delivery of therapeutics to a specific site. Because of their biodegradability, biopolymeric nanoparticles (BNPs) have received a lot of attention in the development of new anticancer drug delivery systems. Biopolymer-based nanoparticle systems can be made in a variety of ways. These systems have developed as a cost-effective and environmentally friendly solution to boost treatment efficacy. Effective drug delivery systems with improved availability, increased selectivity, and lower toxicity are needed. Recent research findings and current knowledge on the use of BNPs in the administration of bioactive chemicals in cancer therapy are summarized in this review.

Reinforcement learning is an unsupervised learning algorithm, where learning is based upon feedback from the environment. Prior research has proposed cognitive (e.g., Instance-based Learning or IBL) and statistical (Q-learning) reinforcement learning algorithms. However, an evaluation of these algorithms in a single dynamic environment has not been explored. In this paper, a comparison between the statistical Q-learning algorithm and the cognitive IBL algorithm is presented. A well-known environment, “Frozen Lake,” is used to train, generalize, and scale Q-learning and IBL algorithms. For generalizing, the Q-learning and IBL agents were trained on one version of the Frozen Lake and tested on a permuted version of the same environment. For scaling, the two algorithms were tested on a larger version of the Frozen Lake environment. Results revealed that the IBL algorithm used less training time and generalized better to different environment variants. The IBL algorithm was also able to show scalability by retaining its superior performance in the larger environment. These results indicate that the IBL algorithm could be proposed as an alternative to the standard reinforcement learning algorithms based on dynamic programming such as Q-learning. The inclusion of human factors (such as memory) in the IBL algorithm makes it suitable for robust learning in complex and dynamic environments.

The agricultural sector is an important part of the Indian economy. The sector is challenged by various stresses, leading to huge loss in crop productivity globally and disturbs agricultural sustainability. Abiotic stresses (drought and salinity) are among the foremost ecological factors that hinder agricultural productivity globally. Several ecological stresses generate excess amounts of reactive oxygen species (ROS) either singly or in combination, leading to impaired redox homeostasis, causing oxidative stress thereby affecting the physiology of the plant. It further damages crop yields, affecting other bio-molecules, and hormones concerning development. Therefore, sustainable and climate-smart agriculture (CSA) that uses plant growth-promoting rhizobacteria (PGPR) is essential to fulfilling the demand. Various plant growth-promoting microbes (PGPM) have vast metabolic capabilities to alleviate the adverse effect of abiotic stresses. Herein we elaborate the effect of plant-microbe interaction on abiotic stress and several strategies adopted by PGPR to cope-up these stresses and help the crop to sustain its productivity thereby mitigating the loss. By highlighting plant-microbe interactions in this chapter, we provide a roadmap for the community to use beneficial microorganisms to improve crop productivity. Further, the relationship between abiotic stress, PGPR and plant productivity is also described and summarizes the responses of abiotic stress in plants concerning molecular and biochemical mechanisms thereby mediating the drought and saline stress.

Introduction: The most recent vaccine incorporated in the Universal Immunization Program of India is measles-rubella vaccine, introduced as a catch-up campaign to eliminate measles and control rubella by the year 2020. The success of any immunization campaign lies on its meticulous planning for areas such as trainings, cold chain management, advocacy, and social mobilizations. Rapid convenience monitoring (RCM) was done in nine health blocks of a hilly district of Himachal Pradesh, pertaining to various campaign activities, for determining vaccine coverage and side effects. Material and Methods: Standardized formats developed by the World Health Organization for RCM of the quality of activity at session sites which included information regarding vaccinating teams, immunization sites, logistics used, cold chain and aseptic condition management, waste disposal, and record maintenance were used. School and house-to-house visits were conducted randomly to check the indelible ink mark/vaccination cards to find out any missed child. Results: A total of 107 immunization sessions were observed for compliance. We assessed 1182 children between the age group of 9 months and 15 years for determining vaccine coverage during the measles–rubella campaign in September–October 2017. Compliance to various aspects of the campaign was found very good, exceeding 90% in almost all the domains. The total vaccination coverage was 98.1%. Schools and health-care providers were the major source of information for this campaign. No severe adverse events following immunization were reported during the survey. Conclusion: Activity compliance and vaccination coverage were found high. Adequate supply of indelible ink pens and functional hub cutters needs to be ensured. There should be revision of incentives to team members with increased involvement of accredited social health activist workers in such campaigns.

Salinity-induced ethylene production and reactive oxygen species (ROS) inhibit agricultural productivity. The plant synthesizes ethylene directly from aminocyclopropane-1-carboxylic acid (ACC). By using ACC as a nitrogen source, bacteria with ACC deaminase (ACCD) inhibit the overproduction of ethylene, thereby maintaining the ROS. The present study investigated the ACCD activity of previously identified rhizobacterial strains in Dworkin and Foster (DF) minimal salt media supplemented with 5 mM ACC (as N-source). Bacterial isolates GKP KS2_7 (Pseudomonas aeruginosa) and MBD 133 (Bacillus subtilis) could degrade ACC into α-ketobutyrate, exhibiting ACCD activity producing more than ~257 nmol of α-ketobutyrate mg protein−1 h−1, and were evaluated for other plant growth-promoting (PGP) traits including indole acetic acid production (>63 µg/mL), phosphate solubilization (>86 µg mL−1), siderophore (>20%) ammonia and exopolysaccharide production. Furthermore, Fourier Transform Infrared analysis also demonstrated α-ketobutyrate liberation from ACC deamination in DF minimal salt media, thereby confirming the ACCD activity. These isolates also showed enhanced tolerance to salinity stress of 3% w/v NaCl in vitro, in addition to facilitating multifarious PGP activities. Seed bacterization by these ACCD-producing bacterial isolates (GKP KS2_7 and MBD 133) revealed a significant decline in stress-stimulated ethylene levels and its associated growth inhibition during seedling germination. They also mitigated the negative effects of salt stress and increased the root-shoot length, fresh and dry weight of root and shoot, root-shoot biomass, total sugar, protein, reducing sugar, chlorophyll content, and antioxidants enzymes in Pisum sativum. As a result, these strains (GKP KS2_7 and MBD 133) might be applied as biofertilizers to counteract the negative effects of soil salinity.

Arsenic contamination in water and soil is becoming a severe problem. It is toxic to the environment and human health. It is usually found in small quantities in rock, soil, air, and water which increase due to natural and anthropogenic activities. Arsenic exposure leads to several diseases such as vascular disease, including stroke, ischemic heart disease, and peripheral vascular disease, and also increases the risk of liver, lungs, kidneys, and bladder tumors. Arsenic leads to oxidative stress that causes an imbalance in the redox system. Mycoremediation approaches can potentially reduce the As level near the contaminated sites and are procuring popularity as being eco-friendly and cost-effective. Many fungi have specific metal-binding metallothionein proteins, which are used for immobilizing the As concentration from the soil, thereby removing the accumulated As in crops. Some fungi also have other mechanisms to reduce the As contamination, such as biosynthesis of glutathione, cell surface precipitation, bioaugmentation, biostimulation, biosorption, bioaccumulation, biovolatilization, methylation, and chelation of As. Arsenic-resistant fungi and recombinant yeast have a significant potential for better elimination of As from contaminated areas. This review discusses the relationship between As exposure, oxidative stress, and signaling pathways. We also explain how to overcome the detrimental effects of As contamination through mycoremediation, unraveling the mechanism of As-induced toxicity.

Climate change has devastating effects on plant growth and yield. During ontogenesis, plants are subjected to a variety of abiotic stresses, including drought and salinity, affecting the crop loss (20–50%) and making them vulnerable in terms of survival. These stresses lead to the excessive production of reactive oxygen species (ROS) that damage nucleic acid, proteins, and lipids. Plant growth-promoting bacteria (PGPB) have remarkable capabilities in combating drought and salinity stress and improving plant growth, which enhances the crop productivity and contributes to food security. PGPB inoculation under abiotic stresses promotes plant growth through several modes of actions, such as the production of phytohormones, 1-aminocyclopropane-1-carboxylic acid deaminase, exopolysaccharide, siderophore, hydrogen cyanide, extracellular polymeric substances, volatile organic compounds, modulate antioxidants defense machinery, and abscisic acid, thereby preventing oxidative stress. These bacteria also provide osmotic balance; maintain ion homeostasis; and induce drought and salt-responsive genes, metabolic reprogramming, provide transcriptional changes in ion transporter genes, etc. Therefore, in this review, we summarize the effects of PGPB on drought and salinity stress to mitigate its detrimental effects. Furthermore, we also discuss the mechanistic insights of PGPB towards drought and salinity stress tolerance for sustainable agriculture.

Mice deficient in glucose-6-phosphate dehydrogenase (G6PD) cannot replenish the cellular antioxidant glutathione, which detoxifies neurodegenerative reactive oxygen species (ROS). To determine the functional consequences of G6PD deficiency, young and aging G6PD-deficient mice were evaluated for brain G6PD activity, DNA damage (comets, γH2AX), Purkinje cell loss, brain function (electrophysiology, behaviour) and lifespan. DNA comet formation was increased and Purkinje cell counts were decreased in a G6pd gene dose-dependent fashion. γH2AX formation varied by age, sex and brain region, with increased levels in G6PD-deficient young and aging females, and in aging males. Aging male G6PD-deficient mice exhibited synaptic dysfunction in hippocampal slices. G6PD-deficient young and aging females exhibited deficits in executive function, and young deficient mice exhibited deficits in social dominance. Conversely, median lifespan in G6PD-deficient females and males was enhanced. Enhanced ROS-initiated brain damage in G6PD deficiency has functional consequences, suggesting that G6PD protects against ROS-mediated neurodegenerative disorders. Keywords: Aging, Glucose-6-phosphate dehydrogenase (G6PD), Reactive oxygen species (ROS), DNA damage, 8-Oxo-2′-deoxyguanine (8-oxodG), Comet, Gamma-H2AX (γH2AX), Neurodegeneration, Behavioural disorders, Electrophysiology, Lifespan

Introduction: Recently, an increasing trend in the prevalence of pediatric metabolic syndrome (PMS) among school-age children has been documented in different parts of India. There is lack of data on the prevalence of PMS and its associated risk factors among school-age children living in district Shimla, Himachal Pradesh. Hence, to fill in the gap in the existing knowledge, the present study was conducted. Methodology: A cross-sectional study was conducted during 2015–2016. Thirty clusters (schools) were identified from a list of all schools using population proportionate to size sampling methodology. From each school, 70 children in the age group of 10–16 years were selected. Data was collected on the sociodemographic characteristics, anthropometry, waist circumference, blood pressure, and physical activity. Fasting venous blood samples were collected for estimation of blood glucose, triglycerides, and high-density lipoprotein levels. Results: The prevalence of PMS using International Diabetes Federation classification was 3.3% and using modified-adult treatment panel classification criteria was 3.5%. Risk factors identified to be associated with PMS among school-age children were (i) male gender, (ii) high family monthly income, (iii) sedentary lifestyle, (iv) consumption of evening snack, (v) television/computer viewing, and (vi) motorized transportation for commuting to school. Conclusion: The PMS prevalence was 3.3% in school-age children residing in District Shimla. There is a need to formulate interventions to prevent and correct metabolic syndrome among them for reducing early onset of cardiovascular disease during adulthood.

Vegetable cultivation is a promising economic activity, and vegetable consumption is important for human health due to the high nutritional content of vegetables. Vegetables are rich in vitamins, minerals, dietary fiber, and several phytochemical compounds. However, the production of vegetables is insufficient to meet the demand of the ever-increasing population. Plant-growth-promoting rhizobacteria (PGPR) facilitate the growth and production of vegetable crops by acquiring nutrients, producing phytohormones, and protecting them from various detrimental effects. In this review, we highlight well-developed and cutting-edge findings focusing on the role of a PGPR-based bioinoculant formulation in enhancing vegetable crop production. We also discuss the role of PGPR in promoting vegetable crop growth and resisting the adverse effects arising from various abiotic (drought, salinity, heat, heavy metals) and biotic (fungi, bacteria, nematodes, and insect pests) stresses.

Cognitive workload is a crucial factor in tasks involving dynamic decision-making and other real-time and high-risk situations. Neuroimaging techniques have long been used for estimating cognitive workload. Given the portability, cost-effectiveness and high time-resolution of EEG as compared to fMRI and other neuroimaging modalities, an efficient method of estimating an individual’s workload using EEG is of paramount importance. Multiple cognitive, psychiatric and behavioral phenotypes have already been known to be linked with “functional connectivity”, i.e., correlations between different brain regions. In this work, we explored the possibility of using different model-free functional connectivity metrics along with deep learning in order to efficiently classify the cognitive workload of the participants. To this end, 64-channel EEG data of 19 participants were collected while they were doing the traditional n-back task. These data (after pre-processing) were used to extract the functional connectivity features, namely Phase Transfer Entropy (PTE), Mutual Information (MI) and Phase Locking Value (PLV). These three were chosen to do a comprehensive comparison of directed and non-directed model-free functional connectivity metrics (allows faster computations). Using these features, three deep learning classifiers, namely CNN, LSTM and Conv-LSTM were used for classifying the cognitive workload as low (1-back), medium (2-back) or high (3-back). With the high inter-subject variability in EEG and cognitive workload and recent research highlighting that EEG-based functional connectivity metrics are subject-specific, subject-specific classifiers were used. Results show the state-of-the-art multi-class classification accuracy with the combination of MI with CNN at 80.87%, followed by the combination of PLV with CNN (at 75.88%) and MI with LSTM (at 71.87%). The highest subject specific performance was achieved by the combinations of PLV with Conv-LSTM, and PLV with CNN with an accuracy of 97.92%, followed by the combination of MI with CNN (at 95.83%) and MI with Conv-LSTM (at 93.75%). The results highlight the efficacy of the combination of EEG-based model-free functional connectivity metrics and deep learning in order to classify cognitive workload. The work can further be extended to explore the possibility of classifying cognitive workload in real-time, dynamic and complex real-world scenarios.

Background: Depression in elderly is a public health problem. Aims and Objectives: To determine the prevalence of depression and its correlates among the elderly population. Materials and Methods: This cross-sectional study was conducted among elderly aged 60 years and above using two-stage cluster sampling technique among elderly residing in the rural and urban areas of Shimla district of Himachal Pradesh, India. A written consent was taken from each participant after explaining the purpose of the study. Results: Of the 800 subjects, 76 (9.5%) were found to be suffering from depression. The logistic regression analysis revealed that elderly having lower income, consuming tobacco, experiencing stressful life event in the past 1 year, having 3 or more chronic diseases, and lacking positive approach toward life and were found to be more depressed. Conclusion: The study conducted in Shimla district shows that one-tenth of the elderly residing in the study area suffering from depression. Elderly having lower income, residing in the urban area, experiencing significant life event, suffering from multimorbidity, and lacking positive approach toward life increase should be identified by screening. They should be focused on so as to reduce the probability of occurrence of depression.

Context: Unprecedented low coverage (63%) of fully vaccinated (FV) children in the recent round of national survey district level household (HH) and facility survey 4 (DLHS-4) propelled health system of Himachal Pradesh for an independent rapid assessment of FV coverage. Aim: The aim of the study was to assess the FV coverage among 12–23-month old children in the state. Settings and Design: A community-based survey with an interviewer-administered questionnaire was carried out in all 12 districts of Himachal Pradesh from September 2015 to January 2016. Subject and Methods: WHO 30 × 7 cluster technique was used. Statistical Analysis Used: Chi-square and unpaired Student's t-test along with 95% confidence intervals. Results: A total of 2492 children across 35,551 HHs (2.4% of state share) were surveyed with FV coverage of 98.1% (95% confidence interval [CI]: 97.5–98.6) and 86% (95% CI: 84.6–87.3) based on history and card, respectively. Conclusions: The reported FV coverage in the current study was observed too high in the state as reported in earlier round of the national surveys (except DLHS-4).

Background: Adolescent suicide is an important public health issue. Suicidal ideations are often the precursor of suicide and can be targeted by appropriate and timely interventions. Aims and Objectives: To determine the prevalence of suicide ideation and to study its predictive factors among school going adolescents. Materials and Methods: This cross-sectional study was carried out in selected senior secondary schools in Shimla district of Himachal Pradesh, India. A pre-validated, self-administered questionnaire was used for data collection. Both descriptive and inferential statistics were applied using Epi info software for windows (CDC Atlanta) software for windows. Results: A total of 218 study subjects (30.9%; confidence interval = 27.6–34.5%) had suicide ideation. Discussing problems with parents (adjusted odds ratio [AOR] =0.5), having good relations with school teachers (AOR = 0.6) and helpful classmates (AOR = 0.6) lowered the odds of having suicidal ideations. On the contrary, adolescents having worrying issues in family (AOR = 2.5), verbally or physically abused (AOR = 2.8) and body image conscious (AOR = 1.8) had increased odds of suicidal ideations. Conclusions: Suicidal ideation is a common experience among adolescents residing in Shimla district of North India. The supportive environment at home and in school decrease its vulnerability.

In Himachal Pradesh, cancer cervix is a major public health problem since it ranks as the number one female cancer. A case-control study of 226 newly diagnosed, histopathologically confirmed cases of cancer cervix and equal number of matched controls was conducted at Regional Cancer Center, Himachal Pradesh during the period from July 2008 to October 2009 with the objective to study the common factors associated with cancer cervix. Univariate analysis identified 10 risk factors associated significantly with the disease. On multiple logistic regression, however, only seven risk factors were found to be associated significantly with the disease. These were: Age at birth of first child, spacing between two children, age at marriage, literacy, socioeconomic status, multiparity, and poor genital hygiene. Risk factors such as poor genital hygiene, age at birth of first child