This study explored the association of a large array of comorbid health and functional measures with depressed mood as determined by the MHI-5. Complex issues of multi-morbidity occur within aging populations, and a range of health and functional measures appeared to identify older people at a high risk for depression. ‘Risk’ factors that appeared stronger than those, such as, diabetes and coronary heart disease that until recently prompted for screening in the UK due to the QOF, were identified.
Functional impairment explained some of the association of co-morbid health with depressed mood with odds ratios tending towards one but not all; being female, a previous doctor diagnosis of depression, and glaucoma, VFQ-poor vision, hearing difficulties, pain within the last 4 weeks, and fair or poor self-perceived general health remained significantly associated with depressed mood. Within the multivariable model, all of these factors remained significantly, and independently associated with depressed mood. Amongst the strongest ‘risk’ factors were a previous diagnosis of depression, glaucoma, and VFQ-poor vision, and amongst those without a previous diagnosis for depression, these were glaucoma and VFQ-poor vision. The association between sensory impairment and depression has been noted by other studies [28, 29]. Capella-McDonnall , noted significant associations of self-reported single sensory loss (vision loss or hearing loss) with depression, and that depression was more frequently associated in those with vision loss compared with hearing loss, which was also indicated in our study.
Approximately, half of those with glaucoma also had VFQ-poor vision. It may be that there were aspects to the visual difficulties within subjects with glaucoma that have not been captured by the current vision screen, or may have been remedied with current treatment and might reflect self-perception. Some aspects of visual function may be more associated with depressed mood than others . There are limited data from studies that investigate glaucoma and depression. However, a recent study indicated that its association did not remain significant after adjustment for self-reported general health . This was not observed within our population, and glaucoma remained significant after adjustment utilising baseline data. However, the association of glaucoma with depression was not confirmed utilising data from the control arms of this trial. This aspect potentially warrants further investigation due to the low number of cases within our study, paucity of data and conflicting findings. Retinal disease failed to reach significance on univariable analyses, and may, in part, be due to low numbers as this condition was associated with the lowest lifetime prevalence. However, the questionnaire framed this as doctor diagnosed ‘untreatable/irreversible’ retinal disease, and this may have excluded some respondents with diagnosed retinal disease. However, no further specific retinal disorder questions were asked within the questionnaire.
Both poor vision and poor hearing are common chronic conditions in later life and the potential impact of these conditions on mood are of concern as the population ages. Poor social support , or economic well-being and social and civic participation  may, in part, explain some of the association between self-reported visual impairment and depression. These factors were not investigated within our model, and potentially warrant further investigation.
Strengths and limitations of the study
This study used data from the HRA-O questionnaire, which is a comprehensive questionnaire that uses standardized and validated instruments. Rich data from a large community-dwelling non-disabled population of older adults in England were utilised, and comprehensive analyses adjusting for potential explanatory variables was undertaken. The MHI-5 screens for those with depressed mood, and although it is widely used to measure quality of life, it has received less attention within the mental health literature. However, it performs well in detecting a variety of psychiatric disorders, including mood disorders or major depression [21, 34], and has been recommended for use to measure psychological distress within a European framework . The findings are based on data from a limited geographical area, and participants could be considered to be the ‘healthy’ older population. Generalisability to wider areas beyond those of our London based sample and settings requires consideration.
The study uses survey data which were self-reported, and participants are those who self- completed and returned the health risk appraisal questionnaire, and is subject to bias. Responses to self-reported measures of vision, hearing, pain, and self-reported general health might be influenced by ‘mood’. Self-rating of general health reflects a global assessment of health incorporating physical, mental and social factors, albeit the strength of association may be greater for physical functioning . Whilst the study can investigate the strengths of associations, it cannot investigate the temporal association of health, functional, and demographic variables with depressed mood, and therefore, the directionality of association. However, there are potentially aspects of these variables that are distinct from one another as implied by their independence within the multivariable model.
The questionnaire determines self-reported lifetime prevalence of a condition, and whilst previously diagnosed conditions investigated in this study might be considered as chronic conditions, the possibility of diminishing symptomatology from the time of the last episode or correction of a condition, such as, surgery for cataracts, cannot be excluded, and might complicate comparisons with other data investigating the effects of co-morbidity. Multiple testing and therefore the risk of a significant result arising by chance within the current analyses also needs to be considered and interpretation through consideration to the p-values advisable. However, additional confirmatory analyses of the importance of the variables within the multivariable models identified utilising baseline data was undertaken using data from the control arms of this trial.