1. INTRODUCTION:

All over the world, eradicating poverty along with measuring in proper way is the most challenging issue; initially policy makers used to apply monetary parameters but recently they are using non monetary parameters like health, education and standard of living etc. India is a still developing country and trying to achieve sustainable development goals.

ll seventeen goals are qualitative and non monetary variables. Hence, the study focuses on the districts of marathwada region in Maharashtra state to calculate multidimentional deprivation index taking into account two parameters of education, four parameters of standard of living and twenty parameters of health. The study has used the data from National Family Health Survey 2019-20. The new deprivation index is calculated on the basis of twenty six parameters. These resources are more or less found in marathwada region.

Almost 193 Countries have adopted sustainable development goals in 2015. Sustainable development framework is aimed to reduce poverty in its all dimensions of men, women and children. Thus, calculating multidimensional poverty index is an important public policy tool which provides intensity and incidence of poverty of group and regional wise. The Oxford Poverty and Human Development Initiative (OPHI) and the United Nations Development Programme (UNDP) have developed MPI methodology which is globally accepted and it captures multiple deprivation of health, education and standard of living from the households.MPI can be calculated not only for the country and states but also for the districts. It will analyse the comparative and relative performance among the districts of the Maharashtra State. Since the concept of MPI development in 2010, Multidimentional Poverty index has identified the most vulnerable people among the poor and ratio of poverty regional wise and overtime. Thereby, policy makers will make proper policy and put target oriented resources for the development of the people. The MPI results are drawn based on the National Family Health Survey (NFHS) 2015-16.

2. REVIEW OF LITERATURE:

1) Sabina Alkire (June 2018) Multidimensional Poverty Measures as Relevant Policy Tools:

This paper highlighted on imperfection analysis of poverty measurement due to some limitations like, lack of quality data availability, coverage, cultural etc. This paper focuses on multidimensional poverty in terms of sustainable development goals. It has proved that a measure of multidimensional poverty is a relevant policy tools. It provides deprivations in each indicator headcount ratio, or poverty rate, and the intensity of poverty. Overall, it does nationally and for all groups of people by which the data set may be disaggregated. Furthermore, multiple poverty line are often made and recorded, bearing this above information in mind, This paper emphasis on many policy makers are using multidimensional poverty indices (MPIS) for its policy making. For instance, MPI methods often comprise participatory exercises and expert consultations and thus catalyzing a national conversation about poverty. MPI is employed to supervise any change and trend in a phenomenon society. Further, the MPI is described by group and across regional. The MPI also target to poverty areas/social groups and those households that are benefited from certain schemes. One of the most contribution role of MPI is to support policy (SDG) that may be more cost effective and impactful method to address deprivations. MPI gives transparency and accountability of statistics for many countries through sending the data tables or data sets.

2) Suman Seth and Sabina Alkire (2014) Did Poverty Reduction Reach the Poorest of the Poor? Assessment Methods in the Counting Approach:

In this paper, they proposed and justified the use of a separate decomposable inequality measurement to capture the distribution of multiple deprivations among poor and assed disparity using Demographic Health Survey (DHS) datasets for Haiti and India.

3) Sabina Alkire; Christoph Jindra, Gisela Robles Aguilar, and Ana vaz (July 2017) Multidimensional Poverty Reduction among countries in Sub-Saharan Africa. The study focuses on changes in MPI for global in Sub-Saharan Africa. The study has taken 35 countries as sample. It finds that changes in level of intensity and composition of MPI at the national level. It has found different pattern of poverty reduction within countries.

4) Yadira Diaz, Francisco Alejandro Espinoza, Yvomi Markaki, Lina maria Sanchez-Cespedas (2015) (Targeting Grenada’s Most Deprived Population: A multidimensional Living conditions Assessment) This study examines poverty reduction is rely on the identification of the most deprived households with using statistical techniques. This paper constructs a method for targeting deprivation household that is Grenadian living Condition Index in which analysed quality of living condition rather than merely income or expenditure.

5) Nicolai Suppa (Jan 2017) Transitions in Poverty and Deprivations: An Analysis of Multidimensional Poverty Dynamics: This paper explored adjusted headcount ratio to analysis poverty that is proposed by Alkire and Foster. Some advanced analysis done like a decomposition of changes of multidimentional poverty and a framework to figure out the relationship between dashboard approach, dimensional contributions and multidimentional poverty by using German panel data. Apart that, this paper examined the method that illuminate the process of the accumulation of deprivations. Cross –sectional data are also discussed for implication for monitoring, policy evaluation and strategies for analysis.

6) Sabina Alkire, James E. Foster, Suman Seth, maria Emma Santos, Jose M. Roche and Paola Ballon (Jan 2015) (Multidimensional Poverty Measurement and analysis Chapter 5- The Alkire-Foster Counting Methodology) This study provides the general modeling framework for analyzing the determinants of poverty measures of both micro and macro levels of analysis. At the micro level, we present a model where the focal variable is a person’s poverty status. At the macro level, we present a model where the focal variable is an overall poverty measure like the poverty head count ratio or the adjusted head count ratio. This study presents these regression models within the structure of Generalized Linear Models.

7) Maria Emma Santos, Pablo Villatorao, Xavier Mancero and Pascal Gerstenfeld (2015) A Multidimensional Poverty Index for Latin America: This paper stated a new multidimensional poverty index for Latin America (MPI-LA) taking into account the unsatisfied basic needs (UBN) approach, poverty line approach and recently developed multidimensional poverty index. This index contains monetary and non-monetary indicators in which some new indicators are included and traditional are omitted for aiming the regional comparability within 17 countries in two points in time- one around 2005 and the other around 2012. Though huge hetergenity across countries, The study estimated about 28% of people are multidimentional poor in 2012 n the region. The Data provides statistical significance in terms of incidence and intensity over the period. Important disparities found between rural and urban areas.

3. OBJECTIVES OF THE STUDY:

1) To measure multidimensional deprivation index of marathwada region in Maharashtra state

2) To compare and analysis district wise differences in terms of living standard, education and health

3) To identify the factors that may change deprivation level of districts in marathwada region.

4. METHODOLOGY:

Multidimensional deprivation index is calculated taking into account the three parameters that are: living standard, education and health. Each parameter has some sub parameters which are associated with main parameter. Education parameter has considered how many women’s are literate and women with 10 or more years of schooling; living standard involves four sub parameter; households are living with electricity, drinking water, sanitation facility and clean fuel for cooking. Besides, health has twenty parameter considered.

5. RESULTS AND DISCUSSION:

Human Development Report 2020 clearly published that Marathwada region is the backward region to other regions in Maharashtra State. Hence the study reflects that which district is more backward than other districts in Marathwada. Backwardness is measured on certain parameters of health, education and living standard. Standard of living is basically depends on available electricity, good drinking water, sanitation facility and clean fuel for cooking. Aurangabad, latur and Osmanabad districts having good standard of living rather than Beed, Jalna and Parbhani. The data shows Hingoli district is identified 54.4 per cent household use clean fuel for cooking and rest of the households must be use cow-dung, wood, etc for cooking. Similarly, fifty per cent household use unclean fuel for cooking in beed, jalna and parbhani districts. Education is the most crucial factor of Human development. It is proverb that “one women educates to whole family” hence woman education is impacted on other members of the family. Womens’ education percentage is low in the Hingoli, Jalna, Nanded and Parbhani districts wheareas Aurangabad, Latur and osmanabad have high.

Health factor is one of the crucial factors of the development. The study has considered almost 20 sub factors which are related to health. Parbhani, Osmanabad, Nanded, Latur and Hingoli are the deprived districts of the Marathwada region in terms of health parameters. Overall, taken into account all three parameters in deprivation level of marathwada region. Following districts are classified as follows.

Sr. No.	Districts	Deprivation Parameter
1	Aurangabad (0.32+0.32+0.224=0.864/3 =0.28)	----------------
2	Beed (0.0+0.16+0.128=0.368/3 =0.12	Living standard.
3	Jalna (0.0+0.0+0.192 = 0.192/3 =0.064	Living standard and Education
4	Latur (0.32+0.32+0.16 =0.80/3 0.26	Health
5	Nanded (0.24+0.0+0.096) = 0.336/3 =0.12	Education and Health
6	Hingoli (0.24+0.0+0.176 =0.416/3 0.13	Living standard, Education and Health
7	Osmanabad (0.32+0.32+0.16=0.80/3 = 0.26	Health
8	Parbhani (0.0+0.0+0.17=0.17/3 =0.058	Living standard, Education and Health

Parameter

Marathwada Region

Living Standard

Aurangabad

Beed

Hingoli

Jalna

Latur

Nanded

Osmanabad

Parbhani

Average

Population living in households with electricity (%)

97.0

(1)

94.8

(0)

98.1

(1)

95.7

(0)

97.2

(1)

96.4

(0)

96.8

(1)

96.8

(1)

96.6

1/12

0.08

Population living in households with an improved drinking water source (%)

91.7

(1)

85.4

(0)

92.4

(1)

82.8

(0)

94.6

(1)

94.8

(1)

96.4

(1)

89.0

(0)

90.88

1/12

0.08

Population living in households that use an improved sanitation facility (%)

69.1

(1)

66.4

(0)

69.0

(1)

63.6

(0)

72.5

(1)

68.0

(1)

71.2

(1)

60.1

(0)

67.48

1/12

Households using clean fuel for cooking

78.4

(1)

54.4

(0)

53.1

(0)

56.4

(0)

78.5

(1)

64.5

(1)

69.7

(1)

54.8

(0)

63.72

1/12

0.32

0.24

0.32

.24

0.32

Education

Women who are literate (%)

83.1

(1)

76.3

(0)

76.5

(0)

71.8

(0)

83.3

(1)

71.9

(0)

83.7

(1)

73.4

(0)

77.5

1/6

0.16

Women with 10 or more years of schooling (%)

48.4

(1)

38.6

(1)

33.2

(0)

34.3

(0)

40.7

(1)

31.6

(0)

41.5

(1)

28.8

(0)

37.13

1/6

0.32

0.16

00.0

0.32

00.00

0.32

00.0

Health

Women age 15-24 years who use hygienic methods of protection during their menstrual period

77.3

(1)

70.7

(0)

77.2

(1)

71.8

(0)

81.0

(1)

76.8

(0)

86.5

(1)

75.3

(0)

77.07

1/60

0.016

Mothers who consumed iron folic acid for 180 days or more when they were pregnant

6.9

(0)

21.8

(1)

10.9

(0)

20.8

(1)

38.00

(1)

8.8

(0)

44.4

(1)

11.2

(0)

20.35

Average out-of pocket expenditure per delivery in a public health facility

4039

(1)

3988

(1)

3114

(0)

4178

(1)

2483

(0)

2964

(0)

2654

(0)

2779

(0)

3274

Home births that were conducted by skilled health personnel

3.1

(1)

2.5

(0)

1.6

(0)

3.4

(1)

2.4

(0)

0.9

(0)

1.6

(0)

7.3

(1)

2.85

Children age 12-23 months who received most of their vaccinations in a public health facility

98.4

(1)

97.8

(1)

94.8

(1)

96.1

(1)

91.00

(0)

93.0

(1)

92.0

(0)

93.1

(1)

94.52

Children age 12-23 months who received most of their vaccinations in a private health facility

1.6

(0)

2.2

(0)

5.2

(1)

2.6

(0)

9.00

(1)

7.0

(1)

8.0

(1)

5.5

(1)

5.13

Total children age 6-23 months receiving an adequate diet

11.7

(1)

3.2

(0)

11.5

(1)

5.2

(0)

14.0

(1)

3.8

(0)

12.8

(1)

1.9

(0)

8.01

Children under 5 years who are stunted (height-for-age)

34.2

(0)

40.8

(1)

37.4

(0)

38.0

(1)

43.2

(1)

36.0

(0)

37.2

(0)

37.6

(0)

38.02

Children under 5 years who are wasted (weight-for-height)

26.4

(1)

28.4

(1)

25.8

(1)

22.2

(1)

18.0

(0)

19.0

(0)

16.1

(0)

22.8

(1)

22.33

Children under 5 years who are severely wasted (weight-for-height)

11.8

(1)

11.9

(1)

10.5

(1)

8.2

(0)

8.0

(0)

8.7

(0)

5.5

(0)

7.6

(0)

9.02

Children under 5 years who are underweight (weight-for-age)

42.9

(1)

36.8

(0)

38.9

(1)

39.0

33.9

(0)

35.2

(0)

32.5

(0)

41.8

37.62

Children under 5 years who are overweight (weight-for-height)

2.8

(1)

3.5

(1)

1.0

(0)

1.3

(0)

5.3

(1)

3.5

(1)

1.8

(0)

3.0

(1)

2.77

Women whose Body Mass Index (BMI) is below normal (BMI, 18.5 kg/m2

20.3

(0)

20.8

(0)

24.9

(1)

23.3

(1)

24.2

(1)

22.9

(1)

19.1

(0)

20.4

(0)

21.98

Women who are overweight or obese

24.4

(1)

21.9

(1)

16.6

(0)

20.6

(0)

17.6

(0)

19.2

(0)

25.1

(1)

23.7

(1)

21.13

Women who have high risk waist-to-hip ratio

24.7

(0)

30.4

(0)

24.7

(0)

21.4

(0)

51.2

(1)

37.0

(1)

44.5

(1)

27.1

(0)

32.62

All women age 15-49 years who are anaemic

52.4

(1)

50.8

(1)

51.3

(1)

58.2

(1)

50.7

(1)

57.3

(1)

49.1

(1)

58.8

(1)

46.22

Bood sugar level-high or very high or taking medicine to control blood sugar level (Blood sugar level among adults (age 15 years and above (women)

13.1

(1)

10.5

(1)

10.5

(1)

11.0

(1)

10.2

(1)

9.1

(0)

9.5

(0)

11.6

(1)

10.68

Elevated bold pressure or taking medicine to control blood pressure (Hypertension among adults (age 15 years and above) (Women)

20.8

26.4

17.4

(0)

21.8

18.6

(0)

16.7

(0)

23.5

21.0

20.77

Women age 15 years and above who use any kind of tobacco

7.9

6.0

7.8

7.0

3.7

(0)

5.7

(0)

8.0

7.0

6.63

Women age 15 years and above who consume alcohol

0.2

(0)

0.5

0.2

(0)

0.2

(0)

0.2

(0)

0.2

(0)

0.3

0.1

(0)

0.224

0.208

0.176

0.192

0.16

0.096

0.16

0.176

Source of Data: National Family Health Survey -5 District Fact Sheet (2019-20)

6. FINDINGS:

1. Jalna and Parbhani are the most backward districts rather than in terms of living standard, education and health, followed by Nanded and Hingoli.

2. Aurangabad is the most progressed district in the marathwada region

3. According to the data of National Family Health Survey, Latur and Osmanabad districts have problem of health issues and beed district is the backward in living standard.

4. Low proportion of electricity, drinking water source, sanitation facility and clean fuel for cooking found in Beed District.

5. Less percentage of women, who are literate and completed more years of schooling, existed in Nanded and Parbhani district.

6. Osmanabad district have more women whose age 15-24 years use hygienic method of protection during their menstrual period.

7. Iron folic acid more consumed women found in Osmanbad and Latur, followed by Jalna and beed when they were pregnant.

8. Large number of home births that were conducted by skilled health personnel in Parbhani district.

9. Children whose age 6-23 months received low adequate diet in Parbhani, Nanded and Beed district.

10. More Stunted children found in Latur and Beed.

11. Almost 40 percent children sare an underweight in all districts of marathwada region

12. Over weighted children and who men who have high risk waist-to-hip ratio are found more in Latur district.

13. Fifty percentage women age 15-49 years who are suffering by anemic in almost all districts of marathwada region.

7. CONCLUSION:

Multidimensional deprivation index is calculated on the basis of major three key components; health, education and standard of living in which two sub factors from education, four factors from living standard and twenty sub factors from health are considered. Overall, health and education and standard of living parameter is good for Aurangabad district, followed by Latur and Osmanabad. In this connection, the study finds that hingoli and parbhani districts are worst in comparison with other districts in marathwada in terms of health, education and living standard; followed by Jalna and Nanded.

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Received on 08.11.2023 Modified on 01.01.2024

Res. J. Humanities and Social Sciences. 2024;15(1)7-11.

DOI: 10.52711/2321-5828.2024.00002