Health

 

Other analyses of health have similarly used information on long term limiting illness, examining how health varied geographically and by different types of living arrangement amongst elderly people. Migration, and particularly transitions to institutional residence, have also been linked to long term illness amongst the elderly.

• Geographic variations in morbidity
  Gould and Jones (1996) uses the 2% SAR to explore individual and geographical variations in morbidity through a multilevel modelling. They modelled the probability of being long-term ill, controlling for age, housing tenure, ethnicity, car ownership and class. They find that (1) for the youngest cohort, there is no difference between whites and non-whites, but differences become increasingly marked for older groups, which cannot be accounted for by socio-economic characteristics; (2) variations in morbidity are strongly related to individual socio-economic characteristics; (3) there are marked geographic differences in patterns of reported morbidity; and (4) the variations between SAR areas remain substantial even when socio-demographic variables at the individual level are taken into account.
  
  
• Health of elderly people
  Glaser et al (1997) examine the frequency of a limiting long-term illness among older people according to different types of living arrangements, including the population in institutions. Their results show that previous studies based only on the private household population have underestimated the prevalence of illness among older people. Long-term illness rates vary across family and household types, with higher frequencies found for those not living in families or in lone parent families, compared with those living as part of a couple. There is also a clustering of long-term illness among households. Those aged over 45 and suffering from long-term illness were more likely to live in households with other members also suffering from long-term illness. Thus health needs to be considered from a household, rather than just an individual, perspective; and institutional populations cannot be ignored. Sample surveys which are confined to private households may present misleading pictures. For instance, elderly people with poor health are more likely to be living in institutions than in their own home, particularly if they are single. Analysis of social surveys based on the non-institutional population therefore find the health of single elderly people better than elderly married people. However, if the institutional population is included this relationship is reversed (see also Grundy and Glaser, 1997; Murphy et al, 1997; Glaser and Grundy, 1998).