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Interrelations between three proxies of health care need at the small area level: an urban/rural comparison

Interrelations between three proxies of health care need at the small area level: an urban/rural comparison
Interrelations between three proxies of health care need at the small area level: an urban/rural comparison
STUDY OBJECTIVE: To examine the relations between geographical variations in mortality, morbidity, and deprivation at the small area level in the south west of England and to assess whether these relations vary between urban and rural areas.
DESIGN: A geographically based cross sectional study using 1991 census data on premature limiting long term illness (LLTI) and socioeconomic characteristics, and 1991-1996 data on all cause premature mortality. The interrelations between the three widely used proxies of health care need are examined using correlation coefficients and scatterplots. The distribution of standardised LLTI residuals from a regression analysis on mortality are mapped and compared with the distribution of urban and rural areas. Multilevel Poisson modelling investigates whether customised deprivation profiles improve upon a generic deprivation index in explaining the spatial variation in morbidity and mortality after controlling for age and sex. These relations are examined separately for urban, fringe, and rural areas.
SETTING: Nine counties in the south west of England.
PARTICIPANTS: Those aged between 0-64 who reported having a LLTI in the 1991 census, and those who died during 1991-1996 aged 0-74.
MAIN RESULTS: Relations between both health outcomes and generic deprivation indices are stronger in urban than rural areas. The replacement of generic with customised indices is an improvement in all area types, especially for LLTI in rural areas. The relation between mortality and morbidity is stronger in urban than rural areas, with levels of LLTI appearing to be greater in rural areas than would be predicted from mortality rates. Despite the weak direct relations between mortality and morbidity, there are strong relations between the customised deprivation indices computed to predict these outcomes in all area types.
CONCLUSIONS: The improvement of the customised deprivation indices over the generic indices, and the similarity between the mortality and morbidity customised indices within area types highlights the importance of modelling urban and rural areas separately. Stronger relations between mortality and morbidity have been revealed at the local authority level in previous research providing empirical evidence that the inadequacy of mortality as a proxy for morbidity becomes more marked at lower levels of aggregation, especially in rural areas. Higher levels of LLTI than expected in rural areas may reflect different perceptions or differing patterns of illness. The stronger relations between the three proxies in urban than rural areas suggests that the choice of indicator will have less impact in urban than rural areas and strengthens the argument to develop better measures of health care need in rural areas.
adult, health, poisson distribution, infant, chronic disease, preschool, epidemiology, newborn, male, comparative study, poverty areas, analysis, cause of death, survival rate, rural health, adolescent, humans, child, female, research, non-u.s.gov't, urban health, regression analysis, research support, cross-sectional studies, design, health services needs and demand, England, middle aged, small-area analysis, mortality, geography, morbidity, perception, statistics, sex, aged, needs assessment, socioeconomic factors
0143-005X
754-761
Barnett, S.
7df2590b-e4ed-4bae-87ea-236ba0a875c2
Roderick, P.
dbb3cd11-4c51-4844-982b-0eb30ad5085a
Martin, D.
8abf0647-d3f7-4fcf-ac10-ebaad80e0482
Diamond, I.
21cc1457-695f-4063-9503-2e43d6bb8809
Wrigley, H.
b454a099-ea4b-4e4a-b5a9-723241418dd5
Barnett, S.
7df2590b-e4ed-4bae-87ea-236ba0a875c2
Roderick, P.
dbb3cd11-4c51-4844-982b-0eb30ad5085a
Martin, D.
8abf0647-d3f7-4fcf-ac10-ebaad80e0482
Diamond, I.
21cc1457-695f-4063-9503-2e43d6bb8809
Wrigley, H.
b454a099-ea4b-4e4a-b5a9-723241418dd5

Barnett, S., Roderick, P., Martin, D., Diamond, I. and Wrigley, H. (2002) Interrelations between three proxies of health care need at the small area level: an urban/rural comparison. Journal of Epidemiology & Community Health, 56 (10), 754-761.

Record type: Article

Abstract

STUDY OBJECTIVE: To examine the relations between geographical variations in mortality, morbidity, and deprivation at the small area level in the south west of England and to assess whether these relations vary between urban and rural areas.
DESIGN: A geographically based cross sectional study using 1991 census data on premature limiting long term illness (LLTI) and socioeconomic characteristics, and 1991-1996 data on all cause premature mortality. The interrelations between the three widely used proxies of health care need are examined using correlation coefficients and scatterplots. The distribution of standardised LLTI residuals from a regression analysis on mortality are mapped and compared with the distribution of urban and rural areas. Multilevel Poisson modelling investigates whether customised deprivation profiles improve upon a generic deprivation index in explaining the spatial variation in morbidity and mortality after controlling for age and sex. These relations are examined separately for urban, fringe, and rural areas.
SETTING: Nine counties in the south west of England.
PARTICIPANTS: Those aged between 0-64 who reported having a LLTI in the 1991 census, and those who died during 1991-1996 aged 0-74.
MAIN RESULTS: Relations between both health outcomes and generic deprivation indices are stronger in urban than rural areas. The replacement of generic with customised indices is an improvement in all area types, especially for LLTI in rural areas. The relation between mortality and morbidity is stronger in urban than rural areas, with levels of LLTI appearing to be greater in rural areas than would be predicted from mortality rates. Despite the weak direct relations between mortality and morbidity, there are strong relations between the customised deprivation indices computed to predict these outcomes in all area types.
CONCLUSIONS: The improvement of the customised deprivation indices over the generic indices, and the similarity between the mortality and morbidity customised indices within area types highlights the importance of modelling urban and rural areas separately. Stronger relations between mortality and morbidity have been revealed at the local authority level in previous research providing empirical evidence that the inadequacy of mortality as a proxy for morbidity becomes more marked at lower levels of aggregation, especially in rural areas. Higher levels of LLTI than expected in rural areas may reflect different perceptions or differing patterns of illness. The stronger relations between the three proxies in urban than rural areas suggests that the choice of indicator will have less impact in urban than rural areas and strengthens the argument to develop better measures of health care need in rural areas.

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More information

Published date: 2002
Keywords: adult, health, poisson distribution, infant, chronic disease, preschool, epidemiology, newborn, male, comparative study, poverty areas, analysis, cause of death, survival rate, rural health, adolescent, humans, child, female, research, non-u.s.gov't, urban health, regression analysis, research support, cross-sectional studies, design, health services needs and demand, England, middle aged, small-area analysis, mortality, geography, morbidity, perception, statistics, sex, aged, needs assessment, socioeconomic factors
Organisations: Community Clinical Sciences

Identifiers

Local EPrints ID: 61656
URI: http://eprints.soton.ac.uk/id/eprint/61656
ISSN: 0143-005X
PURE UUID: a577b615-bef6-4565-8ea1-201170d57afd
ORCID for P. Roderick: ORCID iD orcid.org/0000-0001-9475-6850

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Date deposited: 04 Sep 2008
Last modified: 05 Nov 2019 02:03

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Contributors

Author: S. Barnett
Author: P. Roderick ORCID iD
Author: D. Martin
Author: I. Diamond
Author: H. Wrigley

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