Kuppuswamy’s Socio-economic Status Scale: Updating Income Ranges for the Year 2015

Community and hospital based studies require assessment of socio-economic status of an individual/family. Socioeconomic status (SES) is an important determinant of the health, nutritional status, mortality, and morbidity of an individual. SES also influences the accessibility, affordability, acceptability, and actual utilization of available health facilities. (1) There are many different scales to measure the SES of a family: Rahudkar scale 1960, Udai Parikh scale 1964, Jalota Scale 1970, Kulshrestha scale 1972, Kuppuswamy scale 1976, Shrivastava scale 1978, Bharadwaj scale 2001. (2,3,4,5,6,7,8) However, social transition and fast growing economy have reduced these scales effectiveness in measuring the SES over the years. Kuppuswamy’s socio-economic status scale is an important tool to measure socioeconomic status of families in urban areas. It was first proposed by Kuppuswamy in the in the year 1976. (6) (Table-1) This scale takes into account education, occupation of the head of the family and total income of the family per month from all the sources to categorise families into 5 groups; namely upper, upper middle, lower middle, upper lower and lower socioeconomic status. It is used by students and researchers in India for hospital and community based research. Mishra D and Singh HP (9) in their article on revision of Kuppuswamy’s Socio-economic status scale have pointed that an income scale usually has relevance only for the period under study. They further clarified that due to the steady inflation and consequent fall in the value of the rupee, the income criteria in the scale lose their relevance. There is an unprecedented demand from researchers for the updated version of this because changes in inflation rate change the monetary values of the monthly income range scores. Attempts to revise the original scale to bring the income subscale up to date are done by various authors. The year wise reference indices are shown in Table -2. It tell us how index and base year have seen changes for reference index and has been used to calculate inflation based conversion factor. Mishra D therefore worked on this issue of revision of family’s monthly income in rupees for the year 1976, when the price index was 296 according to base year 1960=100. Then he revised it for the year 1998 using base year 1982=100.The base year has been changed from 2001. Kumar N et al. (10) took into account the new base year 2001= 100 for revision of family’s monthly income in rupees for the year 2007. Conversion factor for 1982, base year has changed with considering 2001 as base year. To get the updated conversion factor the following exercise is adopted as follows For calculating the conversion factor for the year 2007, the All India Average Consumer Price Index for Industrial Workers (CPI-IW) has to be divided by 88.428. All India Average Consumer Price Index Numbers for Industrial Workers (Base 2001=100) shows general index as 128 on April 2007 (http : // labourbureau.nic.in/indexes.htm – Labour Bureau Government of India, as per survey done in 1999-2000). The conversion factor for year 2007= 128/88.428=1.45. The income ranges for the year 2007 was obtained by multiplying 1998 income ranges by the conversion factor 1.45 to get the revised Kuppuswamy Socioeconomic status scale for the year 2007. Kumar N et al. (11) again revised the socioeconomic status in the year 2012 taking the base year 2001= 100 for revision of monthly income in rupees for the year 2012

Five insights from the Global Burden of Disease Study 2019

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3.5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers.Peer reviewe

Effect of Diabetes and Pre-Diabetes and its associated risk factors on treatment outcome of TB patients attending Government Hospitals in Haldwani of District Nainital, Uttarakhand

Background: Diabetes mellitus has the potential to fuel the epidemic of tuberculosis (TB). The world seems to face a looming co-epidemic of TB-diabetes, and that this is a serious public health issue we need to address urgently. DM may have a negative impact on the outcome of TB treatment: higher failure rates, higher rates of all-cause mortality, and death specifically related to TB. Methods: This study is a hospital based prospective study carried out in Government Medical College & Dr. Sushila Tiwari Government Hospital and S.S.J Base hospital, Haldwani, District Nainital of Uttarakhand. 400 tuberculosis patients who were registered to DOTS center of Government Medical College, Haldwani and S. S. J. Base Hospital, Haldwani in the third quarter (July to September) of the year 2015 were included in the study by Systematic random sampling. Results: The mean age of the study participants was 37.8±15.9 years. Hypertension and smoking were associated with unsuccessful treatment outcome. It was seen that Diabetic patients were significantly associated with unsuccessful treatment outcome (38.2% vs 21.3%).There was no effect of Pre-Diabetes on TB treatment outcome. Conclusion: This converging of two epidemics should be a wakeup call for all clinicians and researchers to gearup to meet the challenge of patients afflicted by tuberculosis as well as diabetes.It is time that the “unhealthy partnership” of tuberculosis and diabetes receives the attention it deserve

Assessment of village health sanitation and nutrition committee under NRHM in Nainital district of Uttarakhand

Background: The Village Health Sanitation and Nutrition Committee (VHSNC) is one of the major initiatives under National Rural Health Mission (NRHM) to decentralize and empower local people to achieve NRHM goal. Limited studies have been conducted to assess the VHSNC in India. Objective: To assess the composition of VHSNC and find out the deviations, if any, from the prescribed framework of guidelines, awareness of VHSNC members about their roles and to assess the functioning of VHSNC. Methodology: The cross-sectional study was carried out from July 2012 to June 2013 in two selected blocks (out of eight) in Nainital district of Uttarakhand. A total of 18 VHSNCs were studied, nine from Haldwani and nine from Bhimtal covering 48 revenue villages, 31 in Haldwani and 17 in Bhimtal block respectively. Out of 139 members in 18 VHSNC, 110 members were interviewed. Results: Mean age of the study subjects was 39.01 ± 8.5 years. Out of the 110 members studied maximum 73 (66.4 %) were female and 37 (33.6%) were males. Maximum subjects, 35 (32.8%) were qualified up to intermediate followed by 29 (26.4%) graduates. Maximum 78 (70.9%) participants belonged to Others (General) category, 30 (27.3%) belonged to scheduled caste and only two (1.8%) belonged to OBC category. There were no subjects belonging to scheduled tribe. Out of the 110 members interviewed there were 18 (16.4%) Gram Pradhans, 10 (9.1%) Female Health Workers, 20 (18.2%) ASHAs and 15(13.6%) Anganwadi Workers. There was very low awareness among the members about role of the committee. Maximum, 93 responses were for cleaning village environment which were given by all 18 Gram Pradhans, 16 ASHAs and ward members

Assessment of community - based monitoring under NRHM in Nainital district of Uttarakhand

Background: The government of India started the Community-Based Monitoring (CBM) under National Rural Health Mission (NRHM) which allow the community and its representatives to directly give feedback about the functioning of public health services. Uttarakhand was the 10th state where CBM system under NRHM implemented in 2010 in all 13 districts as pilot project. Objective: To assess the composition and training of Community Monitoring Groups (CMGs) at sub-centre and block level, the capability of the CMG to prepare the report card at sub-centre and facility score card at PHC and to study the improvement in quantitative aspects of health services in study areas. Methodology: This community based prospective study was carried out in two selected Haldwani and Bhimtal blocks of Nainital district. The period of study was from July 2011 to June 2013. Multi-stage random sample design was adopted to select 54 CMG members.  Results: About 91% CMG members belong to General Category. Out of 54 CMG members, majority 45(83.3%) had received training and among them 80% did not have clarity about training guideline. The activities of preparing Report cards, Facility score cards and conducting Jan-Sunwais were done once in a year. Concurrent reductions in yellow (partially satisfactory) and red (bad) rating of series were not seen in 2011-12 to 2012-13 at all centres. Conclusion: The composition and training of the CMGs at all sub-centres and at PHCs were not as per guidelines of NRHM. The activities of preparing the Report card, the Facility score card and conducting Jan-sunwais were not done as per guidelines by NRHM. Majority of sub-centre indicators scored yellow colour and only few scored green

Five insights from the Global Burden of Disease Study 2019

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3·5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers