The prevalence of disability in elderly in India - Analysis of 2011 census data

BACKGROUND

Advancing age leads to physical and sensory impairment with varying degrees of disability. There is lack of publication focusing on disability of elderly in India with a countrywide state-based analysis of all types of disabilities.

OBJECTIVE

To measure the prevalence of disability and describe the types of disability in the elderly Indian population by gender, advancing age, states and geographical regions.

METHODS

The 2011 Census cross-sectional survey data restricted to elderly in India was analyzed. 'Elderly' is defined as a person who is of age 60 years or above. Disability rates per 100,000 elderly population and age-adjusted disability rates were calculated.

RESULTS

A total of 5,376,205 elderly individuals were disabled in India in 2011; disability rate of 5178 per 100,000 elderly population. Movement and seeing disabilities individually accounted for 25% of total disabilities and disability in hearing was 19%. Disability rates in 17 Indian States and Union Territories were above the national average. Disability rates increased as age advanced with the highest disability rate of 8409 per 100,000 among people aged 80 yrs or above. The disability rates were higher in males than females (5314 vs. 5045 per 100,000) and in rural compared to urban areas (5593 vs. 4181 per 100,000). Currently married and working populations had lower disability rates.

CONCLUSION

One in every twenty Indian citizens aged 60 yrs and above is either physically or mentally disabled. Identification of the underlying causes, employing effective and focused preventive strategies will help to reduce the prevalence of disability in the elderly.

Cholera outbreak linked with lack of safe water supply following a tropical cyclone in Pondicherry, India, 2012

In the aftermath of a severe cyclonic storm on 7 January 2012, a cluster of acute diarrhoea cases was reported from two localities in Pondicherry, Southern India. We investigated the outbreak to identify causes and recommend control measures. We defined a case as occurrence of diarrhoea of more than three loose stools per day with or without vomiting in a resident of affected areas during 6-18 January 2012. We used active (door-to-door survey) and stimulated passive (healthy facility-based) surveillance to identify cases. We described the outbreak by time, place, and person. We compared the case-patients with up to three controls without any apparent signs and symptoms of diarrhoea and matched for age, gender, and neighbourhood. We calculated matched odds ratio (MOR), 95% confidence intervals (CI), and population attributable fractions (PAF). We collected rectal swabs and water samples for laboratory diagnosis and tested water samples for microbiological quality. We identified 921 cases and one death among 8,367 residents (attack rate: 11%, case-fatality: 0.1%). The attack rate was the highest among persons of 50 years and above (14%) and females (12%). The outbreak started on 6 January and peaked on the 9th and lasted till 14 January. Cases were clustered around two major leakages in water supply system. Nine of the 16 stool samples yielded V. cholerae O1 Ogawa. We identified that consumption of water from the public distribution system (MOR=37, 95% CI 4.9-285, PAF: 97%), drinking unboiled water (MOR=35, 95% CI 4.5-269, PAF: 97%), and a common latrine used by two or more households (MOR=2.7, 95% CI 1.3-5.6) were independently associated with cholera. Epidemiological evidence suggested that this outbreak was due to ingestion of water contaminated by drainage following rains during cyclone. We recommended repair of the water supply lines, cleaning-up of the drains, handwashing, and drinking of boiled water.

Programmatic and beneficiary-related factors for low vaccination coverage in Papum Pare district, Arunachal Pradesh, India

Vaccination coverage in Papum Pare district, Arunachal Pradesh was observed to be low. We evaluated the universal immunization programme (UIP) through survey of health facilities in the district and collected data about inputs and processes for childhood vaccination, cold-chain maintenance, supervision and monitoring. Using cluster sampling methodology, we selected 697 children aged 12-23 months from 41 clusters and interviewed their mothers to collect information about vaccination status, socio-demographic factors, knowledge, attitude and practices. Only 50% health facilities in the district were conducting fixed-day immunizations. Of the children surveyed, 55% were fully vaccinated. Mothers who were informed about next due date by health workers, possessed immunization card, attended antenatal clinics, or who delivered in hospital were likely to complete the vaccination schedule of their children. In order to increase the vaccination coverage, all health facilities in the district need to be made functional for conducting immunization. Educating health workers to remind mothers about due date of vaccination will also help increasing the vaccination coverage.

A Bayesian approach to study the space time variation of leprosy in an endemic area of Tamil Nadu, South India

BACKGROUND

In leprosy endemic areas, patients are usually spatially clustered and not randomly distributed. Classical statistical techniques fail to address the problem of spatial clustering in the regression model. Bayesian method is one which allows itself to incorporate spatial dependence in the model. However little is explored in the field of leprosy. The Bayesian approach may improve our understanding about the variation of the disease prevalence of leprosy over space and time.

METHODS

Data from an endemic area of leprosy, covering 148 panchayats from two taluks in South India for four time points between January 1991 and March 2003 was used. Four Bayesian models, namely, space-cohort and space-period models with and without interactions were compared using the Deviance Information Criterion. Cohort effect, period effect over four time points and spatial effect (smoothed) were obtained using WinBUGS. The spatial or panchayat effect thus estimated was compared with the raw standardized morbidity (leprosy prevalence) rate (SMR) using a choropleth map. The possible factors that might have influenced the variations of prevalence of leprosy were explored.

RESULTS

Bayesian models with the interaction term were found to be the best fitted model. Leprosy prevalence was higher than average in the older cohorts. The last two cohorts 1987-1996 and 1992-2001 showed a notable decline in leprosy prevalence. Period effect over 4 time points varied from a high of 3.2% to a low of 1.8%. Spatial effect varied between 0.59 and 2. Twenty-six panchayats showed significantly higher prevalence of leprosy than the average when Bayesian method was used and it was 40 panchayats with the raw SMR.

CONCLUSION

Reduction of prevalence of leprosy was 92% for persons born after 1996, which could be attributed to various intervention and treatment programmes like vaccine trial and MDT. The estimated period effects showed a gradual decline in the risk of leprosy which could be due to better nutrition, hygiene and increased awareness about the disease. Comparison of the maps of the relative risk using the Bayesian smoothing and the raw SMR showed the variation of the geographical distribution of the leprosy prevalence in the study area. Panchayat or spatial effects using Bayesian showed clustersing of leprosy cases towards the northeastern end of the study area which was overcrowded and population belonging to poor economic status.

Magnitude of recall bias in the estimation of immunization coverage and its determinants

OBJECTIVE

To study the magnitude of recall bias in the estimation of immunization coverage and to identify its determinants.

DESIGN

A follow-up study of cohort of children for one year; followed by a cross-sectional recall survey.

SUBJECTS

All live births in two contiguous PHC areas in Villupuram district, Tamil Nadu.

METHODS

The prospective data collected from mothers of 774 children was considered as 'Gold Standard' and the retrospective recall data from them was compared with it. This was carried out for individual immunization schedules, namely, DPT, OPV, BCG and measles and for the combined immunization status. Measures such as sensitivity, specificity, positive and negative predictive values were computed. Logistic Regression technique was employed for evaluating the determinants of agreement.

RESULTS

Less than 50% of mothers has immunization cards with them and more than 70% of the cards did not have complete information. The sensitivity of the recall method was 41.3% and the specificity was 79.5% when the complete immunization status was considered. For individual immunization schedules, the sensitivity ranged from 95% for BCG to 53% for measles vaccination and the specificity ranged from 30% for BCG to 68% for measles vaccination. Mother's age emerged out as a significant determinant in the agreement of two methods. Maintenance of immunization cards were very poor.

CONCLUSIONS

Method of obtaining immunization status through recall survey is not sensitive. Proper maintenance of immunization cards and ensuring the availability of them with mothers for inspection are recommended for obtaining accurate estimation of vaccine coverages.