06
MICRO-REGIONAL DISPARITIES AND DEMOGRAPHIC VARIABILITY IN
SINGRAULI DISTRICT (MADHYA PRADESH): A VILLAGE LEVEL STUDY
P. K. Sharma1 and K. R. Chouhan2
Associate Professor, Dept. of Geography, University of Allahabad, Prayagraj, India
2
Research Scholar, Department of General & Applied Geography,
Dr. H. S. Gour Central University, Sagar, India
Email: pawansharmageo@gmail.com, karanchouhan21@gmail.com

1

How to cite this paper:
Sharma P. K. and Chouhan
K. R. (2023) Micro-Regional
Disparities and Demographic
Variability in Singrauli District(Madhya Pradesh): A Village
Level Study, Journal of
Global Resources, Vol. 09
(02)
DOI:
10.46587/JGR.2023.v09i02.006

Received: 24 April 2023
Reviewed: 18 May 2023
Final Accepted: 25 June 2023

Abstract: Demographic variability and micro-regional
disparities are two important concepts in the study of
population and development. Demographic variability refers
to changes in the size, structure, and composition of a
population over time, which are influenced by birth and death
rates, migration patterns, and other factors. Micro-regional
disparities, on the other hand, refer to the unequal
distribution of economic, social, and environmental
resources within a small geographic area. These disparities
can lead to unequal outcomes for different population groups
and negatively impact their quality of life. Understanding theinterplay between demographic variability and microregional disparities is essential for developing effective
policies and programs aimed at promoting equitable andsustainable development. The purpose of this study toanalyse the micro-regional disparities and demographic
variability in the demographic development across 727
inhabited villages and 17 are un-inhabited/forest villages ofSingrauli district of Madhya Pradesh, 2011. The study ismainly based on secondary sources of data collected fromvarious sources like, the District Census Handbook, 2011
and official websites of the government of Madhya Pradesh.
To examine the status of demographic variability and thelevel of demographic development in the study area, havebeen applied the composite index (CI) method byconsidering 10 indicators at the village level. The study
reveals that the villages of Singrauli district have huge microregional disparity and demographic variability and it isclassified into various levels.
Keywords: Micro-Regional Disparities, Demographic
Development, Composite Index

46

Introduction
India is a country with a diverse and complex rural landscape, characterized by significant
variability in terms of geography, culture, language, religion, and socio-economic conditions.
The rural population in India is estimated to be around 800 million, which is roughly 70 percentof the total population. Despite the overall growth and development of the Indian economy inrecent decades, rural areas in India continue to face numerous challenges, such as poverty,
low levels of human development, limited access to basic services, and limited economic
opportunities (Census of India, 2011). Micro-regional disparities refer to the uneven distributionof economic, social, and environmental resources and opportunities within a small geographic
area. These disparities can result in unequal access to education, healthcare, employment,
and other essential services, leading to unequal outcomes and lower quality of life for certain
populations. These disparities are often caused by a combination of historical, economic, andpolitical factors, and can persist even in economically developed countries. Addressing microregional disparities is a complex issue that requires a multi-faceted approach, including
investment in infrastructure, education, and community development, as well as targeted
policies to address specific needs and challenges in affected areas (Baig & Salam, 2019;
Diwakar, 2009; Ghosh, 2011; Report, 2009; Sharma, 2021).
Demographic variability refers to the differences and variations in demographic
characteristics, such as age, gender, ethnicity, education, and income, within a population.
Demographic variability can have a significant impact on the development and well-being of a
population, as different demographic groups may have different needs, preferences, andopportunities. Understanding demographic variability is important for policymakers,organizations, and individuals to effectively address the needs of diverse populations andpromote sustainable development. The demographic variability in rural India is a result ofvarious historical, cultural, and economic factors, such as the caste system, ethnic diversity,and migration patterns. This variability has a significant impact on rural development, asdifferent groups within rural communities have varying levels of access to resources,
opportunities, and services. Additionally, demographic factors, such as age structure, gender,and migration patterns, also play a crucial role in shaping the socio-economic conditions anddevelopment prospects of rural areas in India (Sharma, 2020).
Demographic development refers to the changes in a population's characteristics suchas size, age structure, distribution, and composition over time. These changes are influenced
by birth and death rates, migration patterns, and other factors such as economic development,
educational attainment, and technological advancements (Behl & Singh, 2017). The level ofmaterial well-being, employment of household members, housing security, tightness, etc. areeconomic elements that shape the population's demographic behaviour. As a result, thedemographic development of the region is most directly influenced by these factors(reproductive, self-preservation, marital and migration) (Kabashova, 2021). Geographic,
economic, social, political, pure demographic, and other factors all have an impact on
demographic development, particularly the distribution of populations (Nejašmiæ, Ivo &Njegač, Dražen, 2001).
The level of development in each district of Assam is based on the best possiblecombination of 48 demographic development indicators that consider the industrial sector, theagricultural sector, and the availability of infrastructure. They discovered that the developmentof agriculture and the availability of infrastructure were both positively correlated with generalsocio-economic conditions. They went on to say that the level of literacy has not affected thestate of progress in the agricultural, industrial, or general socioeconomic sectors. In many state
districts, they noticed significant regional differences in the degree of development (Rai &47

Bhatia, 2004). Pana, V. and Pana, I. (2010) investigated several demographic indices in bothestablished and developing nations, including population distribution, density, growth, life
expectancy, literacy, and urbanisation. They concluded that while demographic concerns forsustainable development differ in developed countries with small populations and developing
countries with big populations, there are no predetermined solutions for addressing them.
Singh, R. (2015) evaluate based on four indicators—the percentage of people living above thepoverty line, the literacy rate for women, the proportion of non-agricultural workers in rural
areas, and urbanization—researchers examined regional differences in the levels of
demographic development in post-reform India and found that inter-state disparities had
widened while intra-state disparities had decreased. Borah, S. and Borah,M.(2017)investigated the demographic differences between two Assamese groups. They
discovered significant disparities amongst the districts in terms of demographic factors. They
noticed that the Muslim group had higher crude birth rates, total fertility rates, and child women
ratios than the Hindu society.
In recent years, the Indian government has launched several programs aimed atpromoting rural development, such as the Mahatma Gandhi National Rural Employment
Guarantee Act (MGNREGA), the Pradhan Mantri Gram Sadak Yojana (PMGSY), and theSwachh Bharat Abhiyan (Clean India Campaign). However, the impact of these programs isoften limited by the demographic variability and heterogeneity of rural areas in India.
Understanding the demographic variability in rural development in India is critical to designingand implementing effective and inclusive policies and programs that can address thechallenges and opportunities facing rural communities.
Study Area
The study area falls in the Singrauli district is situated in the northeastern part of Madhya
Pradesh extending between latitudes 23°49' and 24°42' North and longitudes 81°18' and82°48' East. The district is bounded in the North by Rewa and Sidhi districts, in the east by
Uttar Pradesh, in the south by Sarguja and West by Shahdol district. The district is also known
as the northeastern frontier of the state. The district is spread across a total geographical areaof 5675 sq. km2 and the area wise rank of the district is 28th in the state. The highest
topographic elevation in the district is 609 meters above sea level in Chitrangi. The Son River
traverses the district flowing from west to east. The watershed area lies in between the twoboundaries of Kaimour Hills and Son River. Singrauli is one of the districts of the Baghelkhand
region and one of the remotest districts in the state of Madhya Pradesh (Census of India, 2011;
Singh & Kharwar, 2019). There are 3 development blocks Deosar, Chitrangi and Waidhan, andAmong the 744 villages of the study region, 727 villages are inhabited and 17 villages areuninhabited (Census of India, 2011).
The total population of the district is 11,78,132 which constitutes 1.62 percent of thestate population. The population growth in Singrauli during the 2001-2011 period is about 28
percent. The total population of Singrauli district, living in rural areas is 951,487 (80.75 percent)of which males and females are 493,324 and 458,163 respectively. In rural areas of Singrauli
district, the sex ratio is 929 females per 1000 males. The district comprises 744 villages having
a population density of 208 persons per sq. km in 2011. Singrauli has an average literacy rateof 62.4 percent which is less than the national literacy rate of 74.04 percent whereas maleand female literacy rates are 73.8 percent and 49.9 percent respectively (Census of India,
2011).

48

Figure 01: Location Map of Singrauli District, Madhya Pradesh

Objectives
The main objectives of the study are:
• To analyses the demographic variability in villages of study area based on demographic
indicators.
• To identify the cause and sources of demographic disparity and classify into various
categories.
• To examine the level of micro-regional disparities in the level of demographic
development of Singrauli district.
Database and Methodology
The present study is mainly based on secondary sources of data which collected from theprimary census abstract and census of Madhya Pradesh, 2011 and The Socio Economic andCaste Census 2011. Some other data collected from sources like directorate of Economics
and Statistics, department of Agriculture, and other government official websites of Madhya
Pradesh. To measure the micro-regional disparities in the demographic development invillages of Singrauli District, Madhya Pradesh, 10 indicators are considered to evaluate thedemographic development by the composite index method of each village of the district. For
the analysis of level of demographic development, we merged the demographic andeducational indicators. The indicators are adopted from the census of India, 2011 thatmentioned in Table 01.

49

Table 01: Indicators Used to Measure Levels of Demographic Development
Variables Demographic and Educational Indicators
X1
Literacy Rate
X2
Female Literacy Rate
Sex Ratio
X3
X4
Sex Ratio for the Age group of 0-6 Year
X5
Percentage of Non-SC / ST Population
Percentage of Total Workers to the Total Population
X6
X7
No. of Integrated Child Development Service (Nutritional Centres)
X8
No. of Anganwadi Centre (Nutritional Centres)
X9
No. Educational facilities (Primary and secondary school)
X10
No. Educational facilities (Higher secondary school)
Source: Computed by author

These statistics may not be all-inclusive, but they do represent the main interacting
factors in the demographic growth of the research area. The indicators of all the different
demographic development indices have been combined to create a composite index thatmeasures the demographic development of the districts. The methodology used in the present
study is illustrated as follows:• The first step is to select the indicators (X1……. Xn) that you want to include in thecomposite index.
• The next step is to standardize the indicators by converting them into a standard
scale, such as Z-scores. This allows for the comparison of indicators acrossdifferent areas or time periods.
• The formula for calculating the Z-score for a particular indicator is:•••

Zij = Xi - X̅ / σ
Where,
Zij = standard score of the ith observation
Xi = original value of the observationX̅ = mean of all the values of x
σ = standard deviation
calculate the composite index by combining the standardized indicators into asingle index by dividing (X- X̅) by Standard Deviation (SD). i.e. (X- X̅ /SD).
In next step the Gross Value have been calculated by the formula:
Gross value = Mean + (Z-score * SD)and the composite index scores are computed by dividing the gross value by the
total number of the development indicators.

After the analysis the value noted here that higher the value of composite score will
indicate the high level of demographic development whereas smaller value of composite scoreindicates the low level of demographic development. Based on composite score all the
inhabited villages of the study area categorised into the different levels of development that
ranged from (< -0.50) to (> +0.50) values shown in Table 2.
Table 02: Levels of Demographic Development
Composite index(CI)
Above 0.50
0.00 to 0.50
-0.50 to 0.00
Below -0.50-

Level of Accessibility

Relatively high developed
Moderately high developed
Low developed
Very low developed
Uninhabited/forest villages
Total
Source: Computed by author

Block wise No. of Village
Singrauli
Chitrangi
Deosar
24
23
8
115
108
107
132
84
79
29
8
10
5
2
10
305
225
214

50

Total No.
of Villages
55
330
295
47
17
744

Results and Discussion
The Demographic development of any region depends on changes in population's
characteristics such as size, age structure, distribution, and composition over time. Thesechanges are influenced by birth and death rates, migration patterns, and other factors such as
economic development, educational attainment, and technological advancements. Here thedemographic indicators like literacy rate, female literacy rate, sex ratio, sex ratio for the agegroup of 0–6-year, non-SC and ST population ratio, nutritional centres, and educational
facilities on the village level of Singrauli district. And that indicators are directly associated withthe level of demographic development at village level in the district based on NITI Aayog’s
Aspirational district program Singrauli district comes under the backward region in Madhya
Pradesh. In this study, we have considered villages of Singrauli district of Madhya Pradesh
and there are 744 villages in which 727 villages are inhabited and 17 are forest/uninhabitedvillages. The outcome of analysis that obtained for 727 villages of Singrauli district to examine
the level of demographic development and here we are classified into four categories of levelof development.
Relatively High Demographic Development (CI = >0.50)
The relatively high developed category is the highest level of demographic development in the
study and ranges from 0.50 to 1.81 composite score value (Fig 2). In this category ofdevelopment level having 55 villages (Table 2) among 727 villages of 3 blocks of Singrauli
district in which Chitrangi block (24) has many relatively high developed villages than the
Deosar (23) and Singrauli block (8) shows in Table 4. Development indicators are well
performed in this category of the village but indicators like women’s literacy rate and literacy
rate are not performing well according to educational facilities available in the area. The sizeof the settlements in this category is large and some villages are nearly the property of towns
and are situated near the large towns and development blocks that is why available of all thenecessary facilities are to the people of the villages and they are performing well than the othervillages.
Moderately High Demographic Development (CI = 0.00 to 0.50)
Moderately high developed category is second highest level of demographic development it
varies from 0.00 to 0.50 composite score value (Table 2). There are 330 villages that comeunder this category (Fig 2). It shows that there are nearly half villages come under the category
among the total villages in the district. The nutritional centres and the educational facilities are
not performing well that is why the literacy rate is affected and low. The education is mostvaluable indicator to associate the demographic development. In this category, the Deosar
block has the highest number of villages followed by the Chitrangi and Singrauli block of thestudy area. the highest CI score was secured by Daga village (0.49) and the lowest by Khaira(0.00) and some other villages of the district in this category.
Low Demographic Development (CI = -0.50 to 0.00)
In this category the level of demographic development is low and it is third highest level it varies
from -0.50 to 0.00 composite score value (Fig 2). There are 295 village comes under thiscategory (Table 2) and Chitrangi block (132) having large number of villages in this category
followed by Deosar (84) and Singrauli (79) block. It shows that the backwardness and low levelof development in more than half villages the area due to lack of awareness and unavailabilityof facilities the condition of villages is miserable. In this category many villages having morethan 50 percent population are workers and in education facilities secondary and higher
secondary school facilities are very low. Many villages are needed better facilities to enhance
the level and living standard of the people.
51

Figure 02: Level of Demographic Development in Singrauli District, Madhya Pradesh

Very Low Demographic Development (CI = < -0.50)
It is the lowest category and level of demographic development in this study. It varies frombelow to -0.50 composite score value (Fig 2). In this category, there are only 47 villages havingvery low development levels (Table 2). The Kharkhauli village (-1.62) of the Chitrangi blocksecured the lowest composite score value. The level of demographic development reveals thecondition of villages and how indicators are performing in this category. It shows that the microregional disparities are very high in the villages of this category. Somehow in this category
having a smaller number of villages that means the resources and facilities are needed less in
the region. In this level of demographic development, the worst condition is found in the villagesof this category. Many indicators are not performing well in these villages. Due to lack ofinfrastructure and unavailability of basic facilities like education and health care facilities. It is
the major concern to focus on these villages to better rural development and better facilities
provide to local people.
Conclusion
The different levels of demographic development of Singrauli district, Madhya Pradesh showed
in Fig. 2. It represents the huge micro-regional disparities in the level of development.
Relatively developed villages are scattered in the study area and have small population sizes
and situated nearly to towns and cities. Many relatively developed villages are large villages
52like a small town. The study reveals that the large numbers of villages are very backward andthe condition is miserable in terms of facilities and standard of living of people of the area. Dueto physical imbalances, there is a lack of connectivity in the study area. The villages of the son
river basin have a level of development are high due to farming condition and the availabilityof favourable resources. The key findings and trends related to demographic variability and its
impact on rural development highlight the importance of understanding the demographic
characteristics of rural areas and the need for inclusive and effective policies that respond to
the unique needs and challenges faced by different demographic groups. These findings andtrends can inform the design and implementation of policies aimed at promoting ruraldevelopment in India.
In order to reduce regional inequities and imbalances, coordinated efforts should bemade to enhance the sectors of education, health care, transportation, and communication,
particularly in the district's extensive rural areas. Our findings have strong policy implications.
the villages whose development has trailed substantially behind that of comparatively highdeveloped villages should receive special attention if the government seeks a fair distributionof development facilities (Chauhan, 2011). Future research and policy development in the areaof demographic variability and rural development in India should prioritize a comprehensive
and interdisciplinary approach that addresses the unique challenges and opportunities facedby different demographic groups in rural areas. By doing so, research and policy can promote
the development of effective policies and programs that address the complex and evolving
needs of rural populations in India.
References
1. Baig, I. A., & Salam, A. (2019) Regional disparities in agricultural development: An analysis of microlevel. 6(1), 1154–1160.
2. Behl, A., & Singh, R. (2017) Regional Disparities in the Levels of Demographic Development in
Punjab: A Block Level Study. In International Journal of Applied Business and Economic Research(Vol. 293). www.serialsjournals.com
3. Borah, S. and Borah, M. (2017) Statistical Evaluation of Demographic Disparities of Two
Communities in Assam. International Journal of Applied Mathematics & Statistical Sciences. 6 (4):99-106.
4. Chauhan, A. (2021) Hill Geographer Regional Disparities in the levels of demographic developmentin Rajasthan: A District level analysis. https://www.researchgate.net/publication/357625571
5. Diwakar, D. M. (2009) Intra-regional disparities, inequality and poverty in Uttar Pradesh. Economic
and Political Weekly, 44(26–27), 264–273.
6. Ghosh, M. (2011). Regional Disparities in Education, Health and Human Development in India. 5(1),5–28. https://doi.org/10.1177/0973703020110101
7. Kabashova, E. (2021) Standard of living of the population and demographic development of theregion. The Eurasian Scientific Journal, 13(6). https://doi.org/10.15862/12ecvn621
8. Kumar Sharma, P. (2020) Demographic Diversities In Madhya Pradesh: An Inter District Analysis.
https://www.researchgate.net/publication/363294500
9. India, C. of. (2011). Madhya Pradesh District Census Handbook Census of India 2011 Series-24
Part XII-A Village and Town Directory 2011, Directorate of Census Operations Madhya Pradesh
Singrauli.
10. Pana, V. and Pana, I. (2010) Sustainable Development and Demography. Scientific BulletinEconomic Sciences. 9 (15): 51-58.
11. Rai, S. C. and Bhatia, V.K. (2004) Dimensions of Regional Disparities in Socio-Economic
Development of Assam. Journal of the Indian Society of Agricultural Statistics. Vol. 57.
12. Report, W. (2009) Importance of Micro-Level Planning in Rural Development. July.
13. Sharma, P. K. (2021) Infrastructural development in Bundelkhand region: a micro- level analysis.
Punjab Geographer, 16 (October 2020).
14. Singh, R. (2015) Regional disparities in the post reform India. Modern Geografia. II pp. 41
15. Nejašmiæ, Ivo & Njegač, Dražen. (2001) Spatial (Regional) Differences of Demographic
Development of the Republic of Croatia. European Regional Science Association, ERSA conference
papers.

53