ABSTRACT
Background: Cancer is emerging as a major public health concern in many countries including India. Kerala state has the highest burden of cancer in the country. Objective of this study was to estimate the prevalence of diagnosed cancers, warning signs and selected risk factors of cancer in Kadapra Panchayath of Pathanamthitta district, Kerala.Methods: A total of 16,391 population was covered by door to door survey using a structured questionnaire. The questionnaire collected information on the sociodemographic variables of the residents, source of water supply, warning signs of cancer and details of diagnosed cancer cases.Results: The mean age of the population was 40.9+21 years. The prevalence of diagnosed cases of cancer in our study population was 776/100,000 population. Breast cancer was the most common cancer (43.5%) identified in the population. The prevalence of any warning sign among the study population was 220/100,000 population. Breast lump was the common warning sign identified. Increasing age and female gender were the factors found to be significantly associated with cancer.Conclusions: As prevalence of cancer was found to be high in this population, an active community based screening along with teaching self-breast examination to the women in the community are required. Improving community awareness could help in early diagnosis, treatment and prevention. Soil and water testing for carcinogens is recommended.
ABSTRACT
Background: Depression, the most common psychiatric disorder among the elderly, is not yet perceived as an important health problem in India, where few population-based studies have addressed this problem. Objectives: To estimate the prevalence of depression and identify the associated risk factors in the elderly population. Materials and Methods: 3038 consenting elderly (>60 years old) rural and urban residents of both sexes from the fi eld practice areas were interviewed and examined in a cross-sectional study. Physical impairment in the subjects was assessed with the Everyday Abilities Scale for India (EASI), depression by the 15-item Geriatric Depression Scale (GDS-15), and cognitive impairment by the Mini-Mental State Examination (MMSE). Data were analyzed using Epi Info version-6 software. Statistical analysis included proportions, χ2-test, odds ratio, and its 95% confi dence interval. Multiple logistic regression was done using SPSS version 21. Results: The prevalence of depression in the study population was 8.9%. It was signifi cantly higher in urban residents, females, older elderly, nuclear families, in those living alone, those not working, illiterates, poor, functionally impaired, and cognitively impaired. In the multivariate analysis, unmarried/widowed status, unemployment, and illiteracy did not emerge as risk factors. Conclusions: Urban residence, female gender, higher age, nuclear family, poverty, and functional and cognitive impairment were found to be associated with depression even after controlling for other factors.
ABSTRACT
Background: Cognitive impairment, an age-related condition, is often considered a precursor to more serious diseases such as depression/dementia/Alzheimer’s disease. Alzheimer’s disease, which is characterized by cognitive impairment, could have a devastating impact on low- and middle-income countries whose populations are ageing rapidly. The disease has, so far, largely remained neglected by researchers and national health services in India. In view of the growing elderly population and diverse sociocultural and geographical milieu of India, epidemiological data for the condition are desirable for different populations. Moreover, there is a dearth of population-based epidemiological studies on cognitive impairment in the Punjab state of India. Methods: Three thousand and thirty-eight consenting elderly adults aged over 60 years, of both sexes, residing in Ludhiana, Punjab state, India were examined for cognitive functioning, using a modified Hindi Mental State Examination, and a score of ≤25 was considered to be indicative of cognitive impairment. Data analysis included calculations of proportions; odds ratio and their 95% confidence intervals (CIs) were also calculated. The chi-square test and multiple logistic regression model were used to determine the association of cognitive impairment with various sociodemographic parameters. Results: The prevalence of cognitive impairment in the study population was 8.8% (95% CI = 8.06 to 9.54). Increasing age, unmarried/widowed status, illiteracy, unemployment and poverty were found to be independently associated with cognitive impairment. Conclusions: The prevalence of cognitive impairment in this north Indian population of elderly individuals is higher than that found in northern India. With emerging focus on geriatric health services, cognitive impairment, which is a precursor of Alzheimer’s disease/dementias, needs to be included in priority care within the national primary health-care framework.