The Household-Based Socio-Economic Index for Every District in Peninsular Malaysia
Deprivation indices are widely used in public health
study. These indices are also referred as the index of inequalities or
disadvantage. Even though, there are many indices that have been
built before, it is believed to be less appropriate to use the existing
indices to be applied in other countries or areas which had different
socio-economic conditions and different geographical characteristics.
The objective of this study is to construct the index based on the
geographical and socio-economic factors in Peninsular Malaysia
which is defined as the weighted household-based deprivation index.
This study has employed the variables based on household items,
household facilities, school attendance and education level obtained
from Malaysia 2000 census report. The factor analysis is used to
extract the latent variables from indicators, or reducing the
observable variable into smaller amount of components or factor.
Based on the factor analysis, two extracted factors were selected,
known as Basic Household Amenities and Middle-Class Household
Item factor. It is observed that the district with a lower index values
are located in the less developed states like Kelantan, Terengganu
and Kedah. Meanwhile, the areas with high index values are located
in developed states such as Pulau Pinang, W.P. Kuala Lumpur and
Selangor.
[1] A. Testi, E. Ivaldi, and A. Busi, An Index of Material Deprivation for
Geographical Areas. Working Paper No. 23, 2004, Giugno University:
Department of Economics.
[2] A. Niggebrugge, R. Haynes, A. Jones, A. Lovett, and I. Harvey, The
Index of Multiple Deprivation 2000 Access Domain: A Useful Indicator
for Public Health?. Social Science & Medicine, vol. 60, pp. 2743-2753,
Jan. 2005.
[3] O. Morgan and A. Baker, Measuring Deprivation in England and Wales
using 2001 Carstairs Scores. Health Statistics Quarterly 31, Autumn
2006, Office for National Statistics.
[4] M. Shaw, H. Tunstall, and D. Dorling, Increasing Inequalities in Risk of
Murder in Britain: Trends in the Demographic and Spatial Distribution
of Murder, 1981-2000. Health & Place, vol. 11, pp. 45-54, 2005.
[5] Y. A. Sanusi, Application of Human Development Index to
Measurement of Deprivation Among Urban Households in Minna,
Nigeria, Habitat International, vol. 32, pp. 384-398, 2008.
[6] J. B. Holt, and C.P. Lo, The Geography of Mortality in the Atlanta
Metropolitan. Computer, Environment & Urban System, vol. 32, pp.
149-164, 2008.
[7] G. Rey, E. Jougla, A. Fouillet and D. Hémon, Ecological Association
Between a Deprivation Index and Mortality in France over the Period
1997 - 2001: Variations with Spatial Scale, Degree of Urbanicity, Age,
Gender and Cause of Death. BMC Public Health, vol. 9, no. 33, Jan
2009, doi : 10.1186/1471-2458-9-33.
[8] Department of Statistics Malaysia. Taburan Penduduk dan Ciri-ciri Asas
Demografi: Banci Penduduk dan Perumahan Malaysia, 2000.
[9] Department of Statistics Malaysia. Laporan Am Banci Penduduk dan
Perumahan: Banci Penduduk dan Perumahan Malaysia, 2000.
[10] J.W. Grice, Computing and Evaluation Factor Scores. Psychological
Methods, vol. 6, no. 4, pp. 430-450, 2001.
[1] A. Testi, E. Ivaldi, and A. Busi, An Index of Material Deprivation for
Geographical Areas. Working Paper No. 23, 2004, Giugno University:
Department of Economics.
[2] A. Niggebrugge, R. Haynes, A. Jones, A. Lovett, and I. Harvey, The
Index of Multiple Deprivation 2000 Access Domain: A Useful Indicator
for Public Health?. Social Science & Medicine, vol. 60, pp. 2743-2753,
Jan. 2005.
[3] O. Morgan and A. Baker, Measuring Deprivation in England and Wales
using 2001 Carstairs Scores. Health Statistics Quarterly 31, Autumn
2006, Office for National Statistics.
[4] M. Shaw, H. Tunstall, and D. Dorling, Increasing Inequalities in Risk of
Murder in Britain: Trends in the Demographic and Spatial Distribution
of Murder, 1981-2000. Health & Place, vol. 11, pp. 45-54, 2005.
[5] Y. A. Sanusi, Application of Human Development Index to
Measurement of Deprivation Among Urban Households in Minna,
Nigeria, Habitat International, vol. 32, pp. 384-398, 2008.
[6] J. B. Holt, and C.P. Lo, The Geography of Mortality in the Atlanta
Metropolitan. Computer, Environment & Urban System, vol. 32, pp.
149-164, 2008.
[7] G. Rey, E. Jougla, A. Fouillet and D. Hémon, Ecological Association
Between a Deprivation Index and Mortality in France over the Period
1997 - 2001: Variations with Spatial Scale, Degree of Urbanicity, Age,
Gender and Cause of Death. BMC Public Health, vol. 9, no. 33, Jan
2009, doi : 10.1186/1471-2458-9-33.
[8] Department of Statistics Malaysia. Taburan Penduduk dan Ciri-ciri Asas
Demografi: Banci Penduduk dan Perumahan Malaysia, 2000.
[9] Department of Statistics Malaysia. Laporan Am Banci Penduduk dan
Perumahan: Banci Penduduk dan Perumahan Malaysia, 2000.
[10] J.W. Grice, Computing and Evaluation Factor Scores. Psychological
Methods, vol. 6, no. 4, pp. 430-450, 2001.
@article{"International Journal of Engineering, Mathematical and Physical Sciences:52081", author = "Nuzlinda Abdul Rahman and Syerrina Zakaria", title = "The Household-Based Socio-Economic Index for Every District in Peninsular Malaysia", abstract = "Deprivation indices are widely used in public health
study. These indices are also referred as the index of inequalities or
disadvantage. Even though, there are many indices that have been
built before, it is believed to be less appropriate to use the existing
indices to be applied in other countries or areas which had different
socio-economic conditions and different geographical characteristics.
The objective of this study is to construct the index based on the
geographical and socio-economic factors in Peninsular Malaysia
which is defined as the weighted household-based deprivation index.
This study has employed the variables based on household items,
household facilities, school attendance and education level obtained
from Malaysia 2000 census report. The factor analysis is used to
extract the latent variables from indicators, or reducing the
observable variable into smaller amount of components or factor.
Based on the factor analysis, two extracted factors were selected,
known as Basic Household Amenities and Middle-Class Household
Item factor. It is observed that the district with a lower index values
are located in the less developed states like Kelantan, Terengganu
and Kedah. Meanwhile, the areas with high index values are located
in developed states such as Pulau Pinang, W.P. Kuala Lumpur and
Selangor.", keywords = "Factor Analysis, Basic Household Amenities,
Middle-Class Household Item, Socio-economic Index", volume = "6", number = "10", pages = "1394-7", }