Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana

Background The socioeconomic and sociodemographic situation are important components for the design and assessment of malaria control measures. In malaria endemic areas, however, valid classification of socioeconomic factors is difficult due to the lack of standardized tax and income data. The objec...
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Autor*in:	Krefis, Anne Caroline [verfasserIn] Schwarz, Norbert Georg Nkrumah, Bernard Acquah, Samuel Loag, Wibke Sarpong, Nimako Adu-Sarkodie, Yaw Ranft, Ulrich May, Jürgen

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2010

Schlagwörter:	Principal Component Analysis Malaria Malaria Case Malaria Risk Ashanti Region

Anmerkung:	© Krefis et al; licensee BioMed Central Ltd. 2010

Übergeordnetes Werk:	Enthalten in: Malaria journal - London : BioMed Central, 2002, 9(2010), 1 vom: 13. Juli
Übergeordnetes Werk:	volume:9 ; year:2010 ; number:1 ; day:13 ; month:07

Links:	Volltext

DOI / URN:	10.1186/1475-2875-9-201

Katalog-ID:	SPR02861030X

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520			\|a Background The socioeconomic and sociodemographic situation are important components for the design and assessment of malaria control measures. In malaria endemic areas, however, valid classification of socioeconomic factors is difficult due to the lack of standardized tax and income data. The objective of this study was to quantify household socioeconomic levels using principal component analyses (PCA) to a set of indicator variables and to use a classification scheme for the multivariate analysis of children < 15 years of age presented with and without malaria to an outpatient department of a rural hospital. Methods In total, 1,496 children presenting to the hospital were examined for malaria parasites and interviewed with a standardized questionnaire. The information of eleven indicators of the family's housing situation was reduced by PCA to a socioeconomic score, which was then classified into three socioeconomic status (poor, average and rich). Their influence on the malaria occurrence was analysed together with malaria risk co-factors, such as sex, parent's educational and ethnic background, number of children living in a household, applied malaria protection measures, place of residence and age of the child and the mother. Results The multivariate regression analysis demonstrated that the proportion of children with malaria decreased with increasing socioeconomic status as classified by PCA (p < 0.05). Other independent factors for malaria risk were the use of malaria protection measures (p < 0.05), the place of residence (p < 0.05), and the age of the child (p < 0.05). Conclusions The socioeconomic situation is significantly associated with malaria even in holoendemic rural areas where economic differences are not much pronounced. Valid classification of the socioeconomic level is crucial to be considered as confounder in intervention trials and in the planning of malaria control measures.
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700	1		\|a Schwarz, Norbert Georg \|4 aut
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700	1		\|a Adu-Sarkodie, Yaw \|4 aut
700	1		\|a Ranft, Ulrich \|4 aut
700	1		\|a May, Jürgen \|4 aut
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allfields	10.1186/1475-2875-9-201 doi (DE-627)SPR02861030X (SPR)1475-2875-9-201-e DE-627 ger DE-627 rakwb eng Krefis, Anne Caroline verfasserin aut Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Krefis et al; licensee BioMed Central Ltd. 2010 Background The socioeconomic and sociodemographic situation are important components for the design and assessment of malaria control measures. In malaria endemic areas, however, valid classification of socioeconomic factors is difficult due to the lack of standardized tax and income data. The objective of this study was to quantify household socioeconomic levels using principal component analyses (PCA) to a set of indicator variables and to use a classification scheme for the multivariate analysis of children < 15 years of age presented with and without malaria to an outpatient department of a rural hospital. Methods In total, 1,496 children presenting to the hospital were examined for malaria parasites and interviewed with a standardized questionnaire. The information of eleven indicators of the family's housing situation was reduced by PCA to a socioeconomic score, which was then classified into three socioeconomic status (poor, average and rich). Their influence on the malaria occurrence was analysed together with malaria risk co-factors, such as sex, parent's educational and ethnic background, number of children living in a household, applied malaria protection measures, place of residence and age of the child and the mother. Results The multivariate regression analysis demonstrated that the proportion of children with malaria decreased with increasing socioeconomic status as classified by PCA (p < 0.05). Other independent factors for malaria risk were the use of malaria protection measures (p < 0.05), the place of residence (p < 0.05), and the age of the child (p < 0.05). Conclusions The socioeconomic situation is significantly associated with malaria even in holoendemic rural areas where economic differences are not much pronounced. Valid classification of the socioeconomic level is crucial to be considered as confounder in intervention trials and in the planning of malaria control measures. Principal Component Analysis (dpeaa)DE-He213 Malaria (dpeaa)DE-He213 Malaria Case (dpeaa)DE-He213 Malaria Risk (dpeaa)DE-He213 Ashanti Region (dpeaa)DE-He213 Schwarz, Norbert Georg aut Nkrumah, Bernard aut Acquah, Samuel aut Loag, Wibke aut Sarpong, Nimako aut Adu-Sarkodie, Yaw aut Ranft, Ulrich aut May, Jürgen aut Enthalten in Malaria journal London : BioMed Central, 2002 9(2010), 1 vom: 13. Juli (DE-627)355986582 (DE-600)2091229-8 1475-2875 nnns volume:9 year:2010 number:1 day:13 month:07 https://dx.doi.org/10.1186/1475-2875-9-201 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2010 1 13 07
spelling	10.1186/1475-2875-9-201 doi (DE-627)SPR02861030X (SPR)1475-2875-9-201-e DE-627 ger DE-627 rakwb eng Krefis, Anne Caroline verfasserin aut Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Krefis et al; licensee BioMed Central Ltd. 2010 Background The socioeconomic and sociodemographic situation are important components for the design and assessment of malaria control measures. In malaria endemic areas, however, valid classification of socioeconomic factors is difficult due to the lack of standardized tax and income data. The objective of this study was to quantify household socioeconomic levels using principal component analyses (PCA) to a set of indicator variables and to use a classification scheme for the multivariate analysis of children < 15 years of age presented with and without malaria to an outpatient department of a rural hospital. Methods In total, 1,496 children presenting to the hospital were examined for malaria parasites and interviewed with a standardized questionnaire. The information of eleven indicators of the family's housing situation was reduced by PCA to a socioeconomic score, which was then classified into three socioeconomic status (poor, average and rich). Their influence on the malaria occurrence was analysed together with malaria risk co-factors, such as sex, parent's educational and ethnic background, number of children living in a household, applied malaria protection measures, place of residence and age of the child and the mother. Results The multivariate regression analysis demonstrated that the proportion of children with malaria decreased with increasing socioeconomic status as classified by PCA (p < 0.05). Other independent factors for malaria risk were the use of malaria protection measures (p < 0.05), the place of residence (p < 0.05), and the age of the child (p < 0.05). Conclusions The socioeconomic situation is significantly associated with malaria even in holoendemic rural areas where economic differences are not much pronounced. Valid classification of the socioeconomic level is crucial to be considered as confounder in intervention trials and in the planning of malaria control measures. Principal Component Analysis (dpeaa)DE-He213 Malaria (dpeaa)DE-He213 Malaria Case (dpeaa)DE-He213 Malaria Risk (dpeaa)DE-He213 Ashanti Region (dpeaa)DE-He213 Schwarz, Norbert Georg aut Nkrumah, Bernard aut Acquah, Samuel aut Loag, Wibke aut Sarpong, Nimako aut Adu-Sarkodie, Yaw aut Ranft, Ulrich aut May, Jürgen aut Enthalten in Malaria journal London : BioMed Central, 2002 9(2010), 1 vom: 13. Juli (DE-627)355986582 (DE-600)2091229-8 1475-2875 nnns volume:9 year:2010 number:1 day:13 month:07 https://dx.doi.org/10.1186/1475-2875-9-201 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2010 1 13 07
allfields_unstemmed	10.1186/1475-2875-9-201 doi (DE-627)SPR02861030X (SPR)1475-2875-9-201-e DE-627 ger DE-627 rakwb eng Krefis, Anne Caroline verfasserin aut Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Krefis et al; licensee BioMed Central Ltd. 2010 Background The socioeconomic and sociodemographic situation are important components for the design and assessment of malaria control measures. In malaria endemic areas, however, valid classification of socioeconomic factors is difficult due to the lack of standardized tax and income data. The objective of this study was to quantify household socioeconomic levels using principal component analyses (PCA) to a set of indicator variables and to use a classification scheme for the multivariate analysis of children < 15 years of age presented with and without malaria to an outpatient department of a rural hospital. Methods In total, 1,496 children presenting to the hospital were examined for malaria parasites and interviewed with a standardized questionnaire. The information of eleven indicators of the family's housing situation was reduced by PCA to a socioeconomic score, which was then classified into three socioeconomic status (poor, average and rich). Their influence on the malaria occurrence was analysed together with malaria risk co-factors, such as sex, parent's educational and ethnic background, number of children living in a household, applied malaria protection measures, place of residence and age of the child and the mother. Results The multivariate regression analysis demonstrated that the proportion of children with malaria decreased with increasing socioeconomic status as classified by PCA (p < 0.05). Other independent factors for malaria risk were the use of malaria protection measures (p < 0.05), the place of residence (p < 0.05), and the age of the child (p < 0.05). Conclusions The socioeconomic situation is significantly associated with malaria even in holoendemic rural areas where economic differences are not much pronounced. Valid classification of the socioeconomic level is crucial to be considered as confounder in intervention trials and in the planning of malaria control measures. Principal Component Analysis (dpeaa)DE-He213 Malaria (dpeaa)DE-He213 Malaria Case (dpeaa)DE-He213 Malaria Risk (dpeaa)DE-He213 Ashanti Region (dpeaa)DE-He213 Schwarz, Norbert Georg aut Nkrumah, Bernard aut Acquah, Samuel aut Loag, Wibke aut Sarpong, Nimako aut Adu-Sarkodie, Yaw aut Ranft, Ulrich aut May, Jürgen aut Enthalten in Malaria journal London : BioMed Central, 2002 9(2010), 1 vom: 13. Juli (DE-627)355986582 (DE-600)2091229-8 1475-2875 nnns volume:9 year:2010 number:1 day:13 month:07 https://dx.doi.org/10.1186/1475-2875-9-201 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2010 1 13 07
allfieldsGer	10.1186/1475-2875-9-201 doi (DE-627)SPR02861030X (SPR)1475-2875-9-201-e DE-627 ger DE-627 rakwb eng Krefis, Anne Caroline verfasserin aut Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Krefis et al; licensee BioMed Central Ltd. 2010 Background The socioeconomic and sociodemographic situation are important components for the design and assessment of malaria control measures. In malaria endemic areas, however, valid classification of socioeconomic factors is difficult due to the lack of standardized tax and income data. The objective of this study was to quantify household socioeconomic levels using principal component analyses (PCA) to a set of indicator variables and to use a classification scheme for the multivariate analysis of children < 15 years of age presented with and without malaria to an outpatient department of a rural hospital. Methods In total, 1,496 children presenting to the hospital were examined for malaria parasites and interviewed with a standardized questionnaire. The information of eleven indicators of the family's housing situation was reduced by PCA to a socioeconomic score, which was then classified into three socioeconomic status (poor, average and rich). Their influence on the malaria occurrence was analysed together with malaria risk co-factors, such as sex, parent's educational and ethnic background, number of children living in a household, applied malaria protection measures, place of residence and age of the child and the mother. Results The multivariate regression analysis demonstrated that the proportion of children with malaria decreased with increasing socioeconomic status as classified by PCA (p < 0.05). Other independent factors for malaria risk were the use of malaria protection measures (p < 0.05), the place of residence (p < 0.05), and the age of the child (p < 0.05). Conclusions The socioeconomic situation is significantly associated with malaria even in holoendemic rural areas where economic differences are not much pronounced. Valid classification of the socioeconomic level is crucial to be considered as confounder in intervention trials and in the planning of malaria control measures. Principal Component Analysis (dpeaa)DE-He213 Malaria (dpeaa)DE-He213 Malaria Case (dpeaa)DE-He213 Malaria Risk (dpeaa)DE-He213 Ashanti Region (dpeaa)DE-He213 Schwarz, Norbert Georg aut Nkrumah, Bernard aut Acquah, Samuel aut Loag, Wibke aut Sarpong, Nimako aut Adu-Sarkodie, Yaw aut Ranft, Ulrich aut May, Jürgen aut Enthalten in Malaria journal London : BioMed Central, 2002 9(2010), 1 vom: 13. Juli (DE-627)355986582 (DE-600)2091229-8 1475-2875 nnns volume:9 year:2010 number:1 day:13 month:07 https://dx.doi.org/10.1186/1475-2875-9-201 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2010 1 13 07
allfieldsSound	10.1186/1475-2875-9-201 doi (DE-627)SPR02861030X (SPR)1475-2875-9-201-e DE-627 ger DE-627 rakwb eng Krefis, Anne Caroline verfasserin aut Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Krefis et al; licensee BioMed Central Ltd. 2010 Background The socioeconomic and sociodemographic situation are important components for the design and assessment of malaria control measures. In malaria endemic areas, however, valid classification of socioeconomic factors is difficult due to the lack of standardized tax and income data. The objective of this study was to quantify household socioeconomic levels using principal component analyses (PCA) to a set of indicator variables and to use a classification scheme for the multivariate analysis of children < 15 years of age presented with and without malaria to an outpatient department of a rural hospital. Methods In total, 1,496 children presenting to the hospital were examined for malaria parasites and interviewed with a standardized questionnaire. The information of eleven indicators of the family's housing situation was reduced by PCA to a socioeconomic score, which was then classified into three socioeconomic status (poor, average and rich). Their influence on the malaria occurrence was analysed together with malaria risk co-factors, such as sex, parent's educational and ethnic background, number of children living in a household, applied malaria protection measures, place of residence and age of the child and the mother. Results The multivariate regression analysis demonstrated that the proportion of children with malaria decreased with increasing socioeconomic status as classified by PCA (p < 0.05). Other independent factors for malaria risk were the use of malaria protection measures (p < 0.05), the place of residence (p < 0.05), and the age of the child (p < 0.05). Conclusions The socioeconomic situation is significantly associated with malaria even in holoendemic rural areas where economic differences are not much pronounced. Valid classification of the socioeconomic level is crucial to be considered as confounder in intervention trials and in the planning of malaria control measures. Principal Component Analysis (dpeaa)DE-He213 Malaria (dpeaa)DE-He213 Malaria Case (dpeaa)DE-He213 Malaria Risk (dpeaa)DE-He213 Ashanti Region (dpeaa)DE-He213 Schwarz, Norbert Georg aut Nkrumah, Bernard aut Acquah, Samuel aut Loag, Wibke aut Sarpong, Nimako aut Adu-Sarkodie, Yaw aut Ranft, Ulrich aut May, Jürgen aut Enthalten in Malaria journal London : BioMed Central, 2002 9(2010), 1 vom: 13. Juli (DE-627)355986582 (DE-600)2091229-8 1475-2875 nnns volume:9 year:2010 number:1 day:13 month:07 https://dx.doi.org/10.1186/1475-2875-9-201 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2010 1 13 07
language	English
source	Enthalten in Malaria journal 9(2010), 1 vom: 13. Juli volume:9 year:2010 number:1 day:13 month:07
sourceStr	Enthalten in Malaria journal 9(2010), 1 vom: 13. Juli volume:9 year:2010 number:1 day:13 month:07
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Principal Component Analysis Malaria Malaria Case Malaria Risk Ashanti Region
isfreeaccess_bool	true
container_title	Malaria journal
authorswithroles_txt_mv	Krefis, Anne Caroline @@aut@@ Schwarz, Norbert Georg @@aut@@ Nkrumah, Bernard @@aut@@ Acquah, Samuel @@aut@@ Loag, Wibke @@aut@@ Sarpong, Nimako @@aut@@ Adu-Sarkodie, Yaw @@aut@@ Ranft, Ulrich @@aut@@ May, Jürgen @@aut@@
publishDateDaySort_date	2010-07-13T00:00:00Z
hierarchy_top_id	355986582
id	SPR02861030X
language_de	englisch
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Their influence on the malaria occurrence was analysed together with malaria risk co-factors, such as sex, parent's educational and ethnic background, number of children living in a household, applied malaria protection measures, place of residence and age of the child and the mother. Results The multivariate regression analysis demonstrated that the proportion of children with malaria decreased with increasing socioeconomic status as classified by PCA (p < 0.05). Other independent factors for malaria risk were the use of malaria protection measures (p < 0.05), the place of residence (p < 0.05), and the age of the child (p < 0.05). Conclusions The socioeconomic situation is significantly associated with malaria even in holoendemic rural areas where economic differences are not much pronounced. 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author	Krefis, Anne Caroline
spellingShingle	Krefis, Anne Caroline misc Principal Component Analysis misc Malaria misc Malaria Case misc Malaria Risk misc Ashanti Region Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana
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topic_title	Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana Principal Component Analysis (dpeaa)DE-He213 Malaria (dpeaa)DE-He213 Malaria Case (dpeaa)DE-He213 Malaria Risk (dpeaa)DE-He213 Ashanti Region (dpeaa)DE-He213
topic	misc Principal Component Analysis misc Malaria misc Malaria Case misc Malaria Risk misc Ashanti Region
topic_unstemmed	misc Principal Component Analysis misc Malaria misc Malaria Case misc Malaria Risk misc Ashanti Region
topic_browse	misc Principal Component Analysis misc Malaria misc Malaria Case misc Malaria Risk misc Ashanti Region
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title	Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana
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title_full	Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana
author_sort	Krefis, Anne Caroline
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author_browse	Krefis, Anne Caroline Schwarz, Norbert Georg Nkrumah, Bernard Acquah, Samuel Loag, Wibke Sarpong, Nimako Adu-Sarkodie, Yaw Ranft, Ulrich May, Jürgen
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title_sort	principal component analysis of socioeconomic factors and their association with malaria in children from the ashanti region, ghana
title_auth	Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana
abstract	Background The socioeconomic and sociodemographic situation are important components for the design and assessment of malaria control measures. In malaria endemic areas, however, valid classification of socioeconomic factors is difficult due to the lack of standardized tax and income data. The objective of this study was to quantify household socioeconomic levels using principal component analyses (PCA) to a set of indicator variables and to use a classification scheme for the multivariate analysis of children < 15 years of age presented with and without malaria to an outpatient department of a rural hospital. Methods In total, 1,496 children presenting to the hospital were examined for malaria parasites and interviewed with a standardized questionnaire. The information of eleven indicators of the family's housing situation was reduced by PCA to a socioeconomic score, which was then classified into three socioeconomic status (poor, average and rich). Their influence on the malaria occurrence was analysed together with malaria risk co-factors, such as sex, parent's educational and ethnic background, number of children living in a household, applied malaria protection measures, place of residence and age of the child and the mother. Results The multivariate regression analysis demonstrated that the proportion of children with malaria decreased with increasing socioeconomic status as classified by PCA (p < 0.05). Other independent factors for malaria risk were the use of malaria protection measures (p < 0.05), the place of residence (p < 0.05), and the age of the child (p < 0.05). Conclusions The socioeconomic situation is significantly associated with malaria even in holoendemic rural areas where economic differences are not much pronounced. Valid classification of the socioeconomic level is crucial to be considered as confounder in intervention trials and in the planning of malaria control measures. © Krefis et al; licensee BioMed Central Ltd. 2010
abstractGer	Background The socioeconomic and sociodemographic situation are important components for the design and assessment of malaria control measures. In malaria endemic areas, however, valid classification of socioeconomic factors is difficult due to the lack of standardized tax and income data. The objective of this study was to quantify household socioeconomic levels using principal component analyses (PCA) to a set of indicator variables and to use a classification scheme for the multivariate analysis of children < 15 years of age presented with and without malaria to an outpatient department of a rural hospital. Methods In total, 1,496 children presenting to the hospital were examined for malaria parasites and interviewed with a standardized questionnaire. The information of eleven indicators of the family's housing situation was reduced by PCA to a socioeconomic score, which was then classified into three socioeconomic status (poor, average and rich). Their influence on the malaria occurrence was analysed together with malaria risk co-factors, such as sex, parent's educational and ethnic background, number of children living in a household, applied malaria protection measures, place of residence and age of the child and the mother. Results The multivariate regression analysis demonstrated that the proportion of children with malaria decreased with increasing socioeconomic status as classified by PCA (p < 0.05). Other independent factors for malaria risk were the use of malaria protection measures (p < 0.05), the place of residence (p < 0.05), and the age of the child (p < 0.05). Conclusions The socioeconomic situation is significantly associated with malaria even in holoendemic rural areas where economic differences are not much pronounced. Valid classification of the socioeconomic level is crucial to be considered as confounder in intervention trials and in the planning of malaria control measures. © Krefis et al; licensee BioMed Central Ltd. 2010
abstract_unstemmed	Background The socioeconomic and sociodemographic situation are important components for the design and assessment of malaria control measures. In malaria endemic areas, however, valid classification of socioeconomic factors is difficult due to the lack of standardized tax and income data. The objective of this study was to quantify household socioeconomic levels using principal component analyses (PCA) to a set of indicator variables and to use a classification scheme for the multivariate analysis of children < 15 years of age presented with and without malaria to an outpatient department of a rural hospital. Methods In total, 1,496 children presenting to the hospital were examined for malaria parasites and interviewed with a standardized questionnaire. The information of eleven indicators of the family's housing situation was reduced by PCA to a socioeconomic score, which was then classified into three socioeconomic status (poor, average and rich). Their influence on the malaria occurrence was analysed together with malaria risk co-factors, such as sex, parent's educational and ethnic background, number of children living in a household, applied malaria protection measures, place of residence and age of the child and the mother. Results The multivariate regression analysis demonstrated that the proportion of children with malaria decreased with increasing socioeconomic status as classified by PCA (p < 0.05). Other independent factors for malaria risk were the use of malaria protection measures (p < 0.05), the place of residence (p < 0.05), and the age of the child (p < 0.05). Conclusions The socioeconomic situation is significantly associated with malaria even in holoendemic rural areas where economic differences are not much pronounced. Valid classification of the socioeconomic level is crucial to be considered as confounder in intervention trials and in the planning of malaria control measures. © Krefis et al; licensee BioMed Central Ltd. 2010
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title_short	Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana
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author2	Schwarz, Norbert Georg Nkrumah, Bernard Acquah, Samuel Loag, Wibke Sarpong, Nimako Adu-Sarkodie, Yaw Ranft, Ulrich May, Jürgen
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Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana

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