Elsevier

Health & Place

Volume 16, Issue 5, September 2010, Pages 893-902
Health & Place

Urban–rural health differences: primary care data and self reported data render different results

https://doi.org/10.1016/j.healthplace.2010.04.015Get rights and content

Abstract

Aim

Assessing the usefulness of GP electronic medical records for assessing the health of rural populations by comparing these data with data from health interview surveys.

Data

Data from electronic medical records routinely recorded in general practices in 2000–2002. Data on self-reported health problems were obtained through questionnaires in a subset of the same patient population.

Results

According to GP-records, acute somatic and chronic diseases were more frequently presented in rural areas. At the same time self reported health problems point to a better health in rural areas.

Conclusion

GP electronic medical records may be used to monitor the health of rural populations. These data can be obtained relatively quickly and easily and against acceptable cost. However, they do not give the same outcomes as health interview surveys. Reasons for this discrepancy may be; differences in the accessibility of specialist services and help seeking behaviour between urban and rural populations.

Introduction

In the developed (post-) industrialized world urbanicity is often found to be related to health status of the population. It is generally found that in modern industrialized societies (self reported) health status, and especially mental health status is worse in urban areas than in rural areas (Caldwell et al., 2004, Larson and Correa-de-Araujo, 2006, Maas et al., 2006, Verheij et al., 2008, Weich et al., 2006). Utilisation of all sorts of health services is usually found to be higher in urban areas too, though this may not only be a result of health differences but also of differences in access to health services in urban areas or help seeking behaviour. In line with the classic studies by Milgram (1970) and Wirth (1938) urbanicity is often found to be associated with deprivation, violence, concentrations of ethnic minorities and environmental health hazards, whereas the rural element is associated with salutogenic factors like ‘space’, fresh air and a green and healthy environment (Maas et al., 2006).

Studies on the health of farmers in the Netherlands and Finland showed that farmers had fewer health problems than the rest of the working population (Nielen et al., 2008, Stiernstrom et al., 2001, Thelin et al., 2009). The studies in Finland showed that the rural non-farming population was healthier compared to the urban population, except for musculoskeletal disorders (Thelin et al., 2009). This raised the question whether only farmers experienced fewer health problems than urban residents or whether this observation is valid for the rural areas population as a whole.

On the other hand, the health of rural populations is at risk. Increasing antibiotic resistance, outbreaks of foot-and-mouth disease, avian flu, Q-fever and swine flu impose serious physical as well as mental health threats to especially rural populations. Dutch rural areas are relatively densely populated compared to rural areas in other parts of the world. In combination with high concentrations of animals as a result of intensive livestock farming (poultry, pigs and goats) in these areas this may impose a significant and new threat to public health. The recent (autumn 2009) outbreak of Q-fever in a goat farming area in the Netherlands has made this all the more clear. Under these circumstances it is wise to keep a close watch on the health of especially rural populations.

Most studies dealing with urban–rural health differences in Western Europe are based on people's perceived general health and/or are limited to specific health problems or focus on specific subgroups in the population (see for instance: Iversen et al., 2005, Koskimaki et al., 1998, Lehtinen et al., 2003, Minelli et al., 2007, O’Reilly et al., 2007, Olowokure et al., 2006, Paykel et al., 2003). Very few studies on urban–rural health differences cover the whole population and the whole range of health problems. Besides, data are often collected on the basis of questionnaires or health interview surveys, which are time consuming and expensive. Also, real time health monitoring (necessary given the current health threats) is not a viable option using health interview surveys.

Routine data from GP electronic medical records may resolve this problem, especially in health care systems where virtually all inhabitants are listed with a GP, where GPs are usually the first to consult for all health problems and specifically in countries where GPs have a gatekeeping role for secondary care such as the Netherlands and the UK. Using GP electronic medical records for investigating geographic health differences has obvious advantages above other data sources such as health interviews (expensive) mortality or hospital data (only serious health problems).

The purpose of this paper is to identify rural–urban differences in the prevalence of specific (clusters of) diseases by using GP-based routine electronic medical records and thereby to assess the potential of such data for monitoring urban–rural health differences. The outcome of these analyses may be influenced by variations in the availability of health services and help seeking behaviour. On the other hand, EMR data may render more valid results because they are based on diagnoses made by doctors. Both types of data have their limitations. Therefore, we compare the results of this analysis data from health interview surveys in order to test the validity of the outcomes from EMR data.

Differences between EMR data and self reported health have been investigated before. Self reported prevalence of for example diabetes appeared to largely coincide with EMR data. With respect to asthma/COPD and heart failure the agreement was moderate compared to the medical records. For myocardial infarction the results varied across studies (Klungel et al., 1999; Mohangoo et al., 2006; Okura et al., 2004). It is unknown, however, to what extent this affects urban–rural differences. The second purpose of this paper is to investigate whether urban–rural differences are congruent between self-reported health measures and primary care EMRs.

The following research questions will be addressed:

  • Which health problems presented to GPs can be identified as typical for urban or rural areas (as based on routine GP electronic medical records)?

  • To what extent do the results of these analyses correspond with similar analyses based on health interview surveys?

Section snippets

Study population

Data were derived from the Second Dutch National Survey of General Practice (DNSGP-2). The DNSGP-2 was conducted in 2000–2002 in 104 general practices consisting of 195 GPs and 385,461 listed patients (2.5% of the population of GPs and 2.5% of the total Dutch population (Westert et al., 2005)). Patients are representative for the Dutch population with respect to age, gender and type of health care insurance (Westert et al., 2005). GPs are representative for the Dutch population of GPs with

Rural–urban differences in broad disease clusters

For males, traumata, chronic diseases, acute somatic diseases, infections, family planning and neoplasms are more often recorded by GPs in rural areas (see Fig. 1 and Table 2). For females, the prevalence of chronic diseases, infections and traumata was higher in rural areas than in urban areas (see Fig. 2 and Table 2). These differences are to some extent gender specific: the urban–rural difference for traumata was larger for males (odds ratio 3.31) than for females (odds ratio 2.62). For

Discussion and conclusions

Morbidity presented in general practice and recorded in electronic medical records appeared to vary between urban and rural areas. Differences found were always to the disadvantage of the rural areas (traumata, chronic diseases and infections). For some health problems the difference was gender specific: for traumata, the urban–rural difference was much larger in men than in women. For acute somatic diseases, family planning issues (for males this is mainly sterilization) and neoplasms

Conclusion

We conclude that routine electronic medical records are a useful source of information on the health of rural (and urban) populations. It is possible to identify health problems that are specific for these two types of areas. The type of health problems in rural areas may relate to the agricultural environment (especially in the Netherlands, where most rural areas are agricultural areas), although, according to recent findings, those who work as farmers report a better health compared to the

Appendix A

The clustering of ICPC-codes is shown in Table A1 here.

Influenza vaccination in Dutch general practice

The family physicians that participated in this study invited all their high-risk patients for annual immunisation in accordance with the immunisation guidelines of the Dutch College of General Practitioners (Van Essen et al., 1993, Van Essen et al., 1997). Box 1 describes the Dutch influenza programme.

References (46)

  • A.H. Auchincloss et al.

    The health effects of rural–urban residence and concentrated poverty

    J. Rural Health

    (2002)
  • Biermans, M.C., De Bakker, D.H., Verheij, R.A., Gravestein, J.V., Van der Linden, M.W., Robbé, P.F., 2008. Development...
  • T.M. Caldwell et al.

    General practice encounters for psychological problems in rural, remote and metropolitan areas in Australia

    Aust. N Z J Psychiatry

    (2004)
  • H.M. Cooley et al.

    Symptomatic fracture incidence in southern Tasmania: does living in the country reduce your fracture risk?

    Osteoporos. Int.

    (2002)
  • D.H. De Bakker et al.

    Op één lijn. Toekomstverkenning eerstelijnszorg 2020 [Exploring the Future of Primary Health Care in 2020]

    (2005)
  • P. Dempsey et al.

    Self-reported patterns of health services utilisation: an urban–rural comparison in South Australia

    Aust. J. Rural Health

    (2003)
  • C.J. Den Dulk et al.

    Een nieuwe maatstaf voor stedelijkheid: de omgevingsadressendichtheid [A new measure for degree of urbanization: the address density of the surrounding area]

    Maandstatistiek van de Bevolking

    (1992)
  • D.P. Goldberg

    Detection of Psychiatric Illness by Questionnaire: a Technique for the Identification and Assessment of Non-Psychotic Psychiatric Illnesses

    (1972)
  • D.P. Goldberg et al.

    The validity of two versions of the GHQ in the WHO study of mental illness in general health care

    Psychol. Med.

    (1997)
  • E. Hak et al.

    Improving influenza vaccination coverage among high-risk patients: a role for computer-supported prevention strategy?

    Fam. Pract.

    (1998)
  • P. Hider et al.

    Doctors, practices, patients, and their problems during usual hours: a description of rural and non-rural primary care in New Zealand in 2001–2002

    N Z Med. J.

    (2007)
  • M.W.J. Koeter et al.

    General Health Questionnaire, Nederlandse Bewerking: Handleiding [General Health Questionnaire, Dutch version, Manual]

    (1991)
  • J. Koskimaki et al.

    Prevalence of lower urinary tract symptoms in Finnish men: a population-based study

    Br. J. Urol.

    (1998)
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