To evaluate the incidence and progression of myopia and factors associated with progression of myopia in school going children in Delhi. Prospective longitudinal study of 10,000 school children aged 5 to 15 years screened after an interval of 1 year to identify new myopes (Spherical Equivalent≤ -0.5D) and progression of myopia in previously diagnosed myopic children. Association between risk factors and progression was analyzed using adjusted odds ratio. Of the 9,616 children re-screened (97.3% coverage), annual incidence of myopia was 3.4%with mean dioptric change of -1.09 ± 0.55. There was a significant higher incidence of myopia in younger children compared to older children (P = 0.012) and among girls compared to boys (P = 0.002). Progression was observed in 49.2%children with mean dioptric change of -0.27 ± 0.42 diopters. The demographic and behavioral risk factors were analyzed for children with progression (n = 629) and adjusted odds ratio values were estimated. Hours of reading-writing/week (p<0.001), use of computers/ video games (P 2 hours in a day were protective with an inverse association with progression of myopia (P< 0.001). Myopia is an important health issue in India and is associated with long hours of reading and screen time with use of computers and video games. An annual eye vision screening should be conducted, and outdoor activities be promoted to prevent the increase of myopia among school children.

A review appropriateness of the current definition of blindness under National Programme for Control of Blindness (NPCB), Government of India. Online search of peer-reviewed scientific published literature and guidelines using PubMed, the World Health Organization (WHO) IRIS, and Google Scholar with keywords, namely blindness and visual impairment, along with offline examination of reports of national and international organizations, as well as their cross-references was done until December 2016, to identify relevant documents on the definition of blindness. The evidence for the historical and currently adopted definition of blindness under the NPCB, the WHO, and other countries was reviewed. Differences in the NPCB and WHO definitions were analyzed to assess the impact on the epidemiological status of blindness and visual impairment in India. The differences in the criteria for blindness under the NPCB and the WHO definitions cause an overestimation of the prevalence of blindness in India. These variations are also associated with an over-representation of refractive errors as a cause of blindness and an under-representation of other causes under the NPCB definition. The targets for achieving elimination of blindness also become much more difficult to achieve under the NPCB definition. Ignoring differences in definitions when comparing the global and Indian prevalence of blindness will cause erroneous interpretations. We recommend that the appropriate modifications should be made in the NPCB definition of blindness to make it consistent with the WHO definition.

Background: The Comprehensive Rural Health Services Project Ballabgarh, run by All India Institute of Medical Sciences (AIIMS), New Delhi has a computerized Health Management Information System (HMIS) since 1988. The HMIS at Ballabgarh has undergone evolution and is currently in its third version which uses generic and open source software. This study was conducted to evaluate the effectiveness of a computerized Health Management Information System in rural health system in India.Methods: The data for evaluation were collected by in-depth interviews of the stakeholders i.e. program managers (authors) and health workers. Health Workers from AIIMS and Non-AIIMS Primary Health Centers were interviewed to compare the manual with computerized HMIS. A cost comparison between the two methods was carried out based on market costs. The resource utilization for both manual and computerized HMIS was identified based on workers' interviews.Results: There have been no major hardware problems in use of computerized HMIS. More than 95% of data was found to be accurate. Health workers acknowledge the usefulness of HMIS in service delivery, data storage, generation of workplans and reports. For program managers, it provides a better tool for monitoring and supervision and data management. The initial cost incurred in computerization of two Primary Health Centers was estimated to be Indian National Rupee (INR) 1674,217 (USD 35,622). Equivalent annual incremental cost of capital items was estimated as INR 198,017 (USD 4213). The annual savings is around INR 894,283 (USD 11,924).Conclusion: The major advantage of computerization has been in saving of time of health workers in record keeping and report generation. The initial capital costs of computerization can be recovered within two years of implementation if the system is fully operational. Computerization has enabled implementation of a good system for service delivery, monitoring and supervision.

Background: Tobacco is the leading cause of mortality globally and in India. The magnitude and the pattern of tobacco consumption are likely to be influenced by the geographical setting and with rapid urbanization in India there is a need to study this differential pattern. Aim: The aim was to study the rural, urban, and urban-slum differences in patterns of tobacco use. Settings: The study was conducted in Ballabgarh block, Faridabad district, Haryana, and was a community-based cross-sectional study. Materials and Methods: The study was conducted in years 2003-2004 using the WHO STEPS approach with 7891 participants, approximately equal number of males and females, selected using multistage sampling from urban, urban-slum, and rural strata. Statistical Analysis: The analysis was done using the SPSS 12.0 statistical package (SPSS Inc., Chicago, IL, USA). Direct standardization to the WHO world standard population was done to and chi-square and ANOVA tests were used for comparison across three study settings. Results: Self-reported tobacco use among males was as follows: urban 35.2%; urban-slums 48.3%; and rural 52.6% (P value <0.05). Self-reported tobacco use among females was as follows: Urban 3.5%; urban-slums 11.9%; and rural 17.7% (P value <0.05). More males reported daily bidi (tobacco wrapped in temburini leaf) smoking (urban 17.8%, urban-slums 36.7%, rural 44.6%) than cigarette use (urban 9.6%, urban-slums 6.3%, rural 2.9%). Females using smoked tobacco were almost exclusively using bidis (urban 1.7%, 7.9%, 11% in rural). Daily chewed tobacco use had urban, urban-slum, and rural gradients of 12%, 10.5%, and 6.8% in males respectively. Its use was low in females. Conclusion: The antitobacco policies of India need to focus on bidis in antitobacco campaigns. The program activities must find ways to reach the rural and urban-slum populations.

Axshya SAMVAD is an active tuberculosis (TB) case finding (ACF) strategy under project Axshya (Axshya meaning ‘free of TB’ and SAMVAD meaning ‘conversation’) among marginalized and vulnerable populations in 285 districts of India. To compare patient characteristics, health seeking, delays in diagnosis and treatment initiation among new sputum smear positive TB patients detected through ACF and passive case finding (PCF) under the national TB programme in marginalized and vulnerable populations between March 2016 and February 2017. This observational analytic study was conducted in 18 randomly sampled Axshya districts. We enrolled all TB patients detected through ACF and an equal number of randomly selected patients detected through PCF in the same settings. Data on patient characteristics, health seeking and delays were collected through record review and patient interviews (at their residence). Delays included patient level delay (from eligibility for sputum examination to first contact with any health care provider (HCP)), health system level diagnosis delay (from contact with first HCP to TB diagnosis) and treatment initiation delays (from diagnosis to treatment initiation). Total delay was the sum of patient level, health system level diagnosis delay and treatment initiation delays. We included 234 ACF-diagnosed and 231 PCF-diagnosed patients. When compared to PCF, ACF patients were relatively older (≥65 years, 14% versus 8%, p = 0.041), had no formal education (57% versus 36%, p<0.001), had lower monthly income per capita (median 13.1 versus 15.7 USD, p = 0.014), were more likely from rural areas (92% versus 81%, p<0.002) and residing far away from the sputum microscopy centres (more than 15 km, 24% versus 18%, p = 0.126). Fewer patients had history of significant loss of weight (68% versus 78%, p = 0.011) and sputum grade of 3+ (15% versus 21%, p = 0.060). Compared to PCF, HCP visits among ACF patients was significantly lower (median one versus two HCPs, p<0.001). ACF patients had significantly lower health system level diagnosis delay (median five versus 19 days, p = 0.008) and the association remained significant after adjusting for potential confounders. Patient level and total delays were not significantly different. Axshya SAMVAD linked the most impoverished communities to TB care and resulted in reduction of health system level diagnosis delay.

Background: There is limited evidence on whether active case finding (ACF) among marginalised and vulnerable populations mitigates the financial burden during tuberculosis (TB) diagnosis. Objectives: To determine the effect of ACF among marginalised and vulnerable populations on prevalence and inequity of catastrophic costs due to TB diagnosis among TB-affected households when compared with passive case finding (PCF). Methods: In 18 randomly sampled ACF districts in India, during March 2016 to February 2017, we enrolled all new sputum-smear-positive TB patients detected through ACF and an equal number of randomly selected patients detected through PCF. Direct (medical and non-medical) and indirect costs due to TB diagnosis were collected through patient interviews at their residence. We defined costs due to TB diagnosis as ‘catastrophic’ if the total costs (direct and indirect) due to TB diagnosis exceeded 20% of annual pre-TB household income. We used concentration curves and indices to assess the extent of inequity. Results: When compared with patients detected through PCF (n = 231), ACF patients (n = 234) incurred lower median total costs (US$ 4.6 and 20.4, p < 0.001). The prevalence of catastrophic costs in ACF and PCF was 10.3 and 11.5% respectively. Adjusted analysis showed that patients detected through ACF had a 32% lower prevalence of catastrophic costs relative to PCF [adjusted prevalence ratio (95% CI): 0.68 (0.69, 0.97)]. The concentration indices (95% CI) for total costs in both ACF [−0.15 (−0.32, 0.11)] and PCF [−0.06 (−0.20, 0.08)] were not significantly different from the line of equality and each other. The concentration indices (95% CI) for catastrophic costs in both ACF [−0.60 (−0.81, –0.39)] and PCF [−0.58 (−0.78, –0.38)] were not significantly different from each other: however, both the curves had a significant distribution among the poorest quintiles. Conclusion: ACF among marginalised and vulnerable populations reduced total costs and prevalence of catastrophic costs due to TB diagnosis, but could not address inequity.