Introduction
According to estimates by the United Nations Office on Drugs and Crime (UNODC), there were approximately 11.7 million people imprisoned worldwide in 2019, an increase of 21% since 2000 (9.3 million)1. According to the National Prisons Census of Peru, there are currently 76,180 inmates distributed in 66 prisons, of whom 3,001 (4%) are over 60 years of age2. The morbidity profile of this population is characterised by a range of diseases, the most prevalent being depression, anxiety, chronic lung disease, high blood pressure and diabetes2.
Diabetes is regarded as a non-communicable disease that has a major impact on global health3, and therefore efforts are being made to reduce its incidence and impact4. According to the World Health Organisation (WHO), diabetes was the direct cause of death for 1.5 million people 20195, and the incidence worldwide is increasing6. The disease has more of an impact on the elderly and is a risk factor for heart diseases and death7.
According to the Peruvian Family Health and Demographics Survey of 2020, diabetes is more common amongst the elderly (11%) than in other population groups8, which is the reason for the higher risk of mortality. There are studies that indicate that the most common co-morbidities in diabetes are high blood pressure and depression9,10.
It has also been reported that there is a two-way association between diabetes and depression, in other words, one can lead to the other9,11,12. Some studies indicate that depression presents twice as often amongst diabetics as it does in persons who do not have the disease13. They also state that both diabetes and depression can lead to disabilities in the elderly14-17that can have a negative impact on their quality of life and even restrict their participation in daily activities.
Persons with disabilities are those with physical, mental, intellectual or sensory deficiencies18that in the long term can restrict their activities and participation, as a result of the health conditions and the contextual factors that surround the process18. The prevalence of disability amongst the elderly has increased as a result of demographic transition and an increased prevalence of chronic diseases18.
According to the WHO World Report on Disability in 2011, the prevalence of disabilities worldwide is 38%19. In the case of Peru, the 2012 Report on Disabled Persons by the National Institute of Statistics and Information Technology states that the population of 60 to 69 years of age has a 20% prevalence of disability, while this figure increases to 24% amongst the 70 to 79 age group20.
As we mentioned, some studies have indicated that there is a risk of suffering from a disability as a result of the depression-diabetes co-morbidity14-16,21, but they have not been carried out with the six disabilities of a prison population in mind22. In this regard, any study that considers this issue would be particularly relevant given the major demographic and epidemiological transition. It is therefore necessary to establish healthcare policies for the elderly, especially for those living in overcrowded conditions in prisons, where there are many limitations on health services, which are meagre, do not cover all the medical specialities and do not offer the necessary medical treatment.
The aim of this study is to establish the strength of the association of the depression-diabetes co-morbidity with the presence of six types of disability amongst elderly prison inmates. The hypothesis that we seek to corroborate is whether elderly inmates with a depression-diabetes co-morbidity present a higher likelihood of suffering from a disability than elderly inmates without said co-morbidity.
Material and Method
Design
An analysis of the 2016 Peruvian National Prisons Census was used as the basis for a cross-sectional study. The population was made up of elderly prison inmates in the 66 penitentiary centres managed by the Peruvian National Prisons Institute.
The census participants consisted of inmates of both sexes of 60 years of age and over, who reported that they had (or did not have) diabetes or depression diagnosed by a health professional. Inmates who reported that they had diabetes or depression but were not diagnosed by a health professional were excluded.
The sample was made up of a census, consisting of 2,658 adults who met the criteria mentioned above.
Variables
Result variable
Disability, which was categorised into six sub-domains, taking into consideration the recommendations of the Washington group on disability22. It was categorised into: 1) reduced mobility; 2) visual disability; 3) hearing disability; 4) speaking disability; 5) difficulties in relating to others; and 6) difficulties in understanding.
Instruments
The national prison census certificate was used as an instrument for gathering data. As regards the outcome variable, information was gathered about disability in line with the recommendations of the Washington group, specifying six categories in this area al22. The same classification was used in Peru in the 12th National Population Census of 201723.
The following text was prepared, which included a set of questions: “Now I am going to ask you some questions to see if you have some kind of permanent problem that stops you or impedes you from doing your daily activities. “Do you have any permanent problems with moving around, walking or using your arms and legs? ¿Seeing, do you use glasses? Taking or communicating, do you use sign language or another method? Hearing, do you use a hearing aid? Understanding or learning (concentrating and remembering)? Relating to others because of your thoughts, feelings, emotions or behaviour?”.
For the variables of suffering from diabetes and depression, the census certificate offers a two-level consultation, first it asks if the person suffers from these conditions, and if the answer is yes, there is a second question about whether the person has been diagnosed by a health professional, The questions for diabetes take the following form: “Do you suffer from diabetes, or rather, from high levels of blood sugar?”, with the following question: “Were you diagnosed by a health professional?”. The questions for depression have a similar format: “Do you suffer from depression?”, and then: “Were you diagnosed by a health professional?” In this regard, the reports of depression and diabetes made by the person surveyed were documented as valid24-27.
As regards the confounding variables, the following questions were used: gender, if the interviewee had participated in a sports activity in the previous beforehand and if they consumed drugs before entering prison. The last question could be under-reported28, but it was included for integration as a potential confounder.
Procedures
The procedures for obtaining the information as a primary source can be seen in the census technical document29. The following processes were followed for the study: the data bases were obtained from the website of the Peruvian National Institute of Statistics and Information Technology (available at: http://iinei.inei.gob.pe/microdatos/), the files were merged and the variables were re-codified for later analysis.
Statistical analysis
The Stata 14 (Stata Corp, Texas, USA) statistical program was used for the statistical analysis. Measurements of absolute frequency and percentages were used for the descriptive analysis. Associations were looked for in the bivariate analysis and potential confounders were identified with the chi-squared test or Fisher's exact test. After testing the scenarios required for multivariate analysis, logistical regression techniques were applied to calculate the crude and adjusted odds ratios; the adjustment variables were statistical and only those that were found to be associated with the specific disability were integrated into the model.
Secondary epidemiological analyses were carried out with the Openepi program, where the population aetiological fraction was calculated along with the aetiological fraction in exposed subjects.
Ethical considerations
The study made use of a secondary base available at the National Institute of Statistics and Information Technology website for unrestricted use in research, and so express permission was not required for downloading or processing.
The research project followed international parameters regarding bioethical practices in research, and complied with the Helsinki II Declaration and Peruvian regulations on research.
Prison inmates are regarded as a vulnerable population, and so a review of the literature was carried out, which showed that there were no complaints or reports about breaches of bioethics in preparing the census. The database is anonymous and does not allow the inmates to be identified.
Results
Characteristics of the population
The population studied was made up of 2,658 adults of over 60 years age or more who complied with the inclusion criteria. The frequency and percentage of the socio-demographic variables of health and disability can be seen in Table 1.
Characteristics | N = 2.658 | |||
---|---|---|---|---|
n | % | |||
Socio-demographic | Sex | Female | 137 | 5.2 |
Male | 2.521 | 94.9 | ||
Age group (years) | 60-69 | 2.147 | 80.8 | |
70-79 | 459 | 17.3 | ||
80-89 | 52 | 2.0 | ||
Physical activity (n = 2.643) | Yes | 932 | 36.3 | |
No | 1.711 | 64.7 | ||
Drug consumption (n = 2.648) | Yes | 205 | 7.7 | |
No | 2.443 | 92.3 | ||
Health | Depression | Yes | 222 | 8.4 |
No | 2.436 | 91.7 | ||
Diabetes | Yes | 299 | 11.3 | |
No | 2.359 | 88.8 | ||
Comorbidity | No depression or diabetes | 2.176 | 81.9 | |
Diabetes only | 260 | 9.8 | ||
Depression only | 183 | 6.9 | ||
Diabetes with depression | 139 | 1.5 | ||
Disability | Mobility disability | Sí | 752 | 28.3 |
No | 1.906 | 71.7 | ||
Speech disability | Sí | 83 | 3.1 | |
No | 2.575 | 96.9 | ||
Visual disability | Sí | 1.084 | 40.8 | |
No | 1.574 | 59.2 | ||
Hearing disability | Sí | 488 | 81.6 | |
No | 2.170 | 18.4 | ||
Difficulties in understanding | Sí | 322 | 12.1 | |
No | 2.336 | 87.9 | ||
Difficulties in relating to others | Sí | 92 | 3.5 | |
2.566 | 96.5 |
Factors associated with disability
A bivariate analysis was carried out on each socio-demographic variable (sex, age, sports activity, drug consumption before entering prison) and on health (co-morbidity) with each of the six types of disability (visual, hearing, understanding, mobility, relationships and speech). The chi-squared or Fisher's exact test were used to carry out the associations.
A significant association in the socio-demographic co-variables was found for sex and the self-reported disability in understanding (p=0.047) and mobility (p=0.001), while no other associations were found with the other disabilities. A general association was found in the age groups where the older the group was, the greater the disability in hearing (p.<0.001), understanding (p=0.01) and mobility (p<0.001). Associations were found between sports activities and the visual (p=0.004), hearing (p<0.001), speaking (p=0.024) and mobility (p<0.001) disabilities. In the case of drug consumption before entering prison, no associations with any of the six types of disability were found (Tables 2 and 3).
Characteristics | Speech disability | Understanding disability | Visual disability | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Yes | No | P | Yes | No | Yes | No | P | |||||||||
n | % | n | % | n | % | n | % | P | n | % | n | % | ||||
Socio-demographic | ||||||||||||||||
Sex | Female | 6 | 4.4 | 131 | 95.6 | 0.320* | 24 | 17.5 | 113 | 82.5 | 0.047 | 64 | 46.5 | 73 | 53.3 | 0.147 |
Male | 77 | 3.1 | 2.444 | 96.9 | 298 | 11.8 | 2.223 | 88.2 | 1020 | 40.7 | 1.501 | 59.5 | ||||
Age group (years) | 60-69 | 65 | 3 | 2082 | 97 | 0.662 | 240 | 11.2 | 1.907 | 88.8 | 0.010 | 865 | 40.3 | 1.282 | 59.7 | 0.077 |
70-79 | 17 | 3.7 | 442 | 96.3 | 73 | 15.9 | 386 | 84.1 | 190 | 41.4 | 269 | 58.6 | ||||
80-89 | 1 | 1.9 | 51 | 98.1 | 9 | 17.3 | 43 | 82.7 | 29 | 55.8 | 23 | 44.2 | ||||
Physical activity (n=2.643) | Yes | 19 | 2 | 913 | 98 | 0.024 | 102 | 10.9 | 830 | 89.1 | 0.163 | 586 | 62.9 | 346 | 37.1 | 0.004 |
No | 62 | 3.6 | 1.649 | 96.4 | 219 | 12.8 | 1.492 | 87.2 | 978 | 57.2 | 733 | 42.8 | ||||
Drug consumption (n = 2.648) | Yes | 5 | 2.4 | 200 | 97.6 | 0.571 | 23 | 11.2 | 182 | 88.8 | 0.680 | 80 | 39 | 125 | 70 | 0.578 |
No | 77 | 3.2 | 2.366 | 96.8 | 298 | 12.2 | 2.415 | 87.8 | 1002 | 41 | 1.441 | 59 | ||||
Health | ||||||||||||||||
Comorbidity | No depression or diabetes | 62 | 2.9 | 2.114 | 97.1 | 0.001 | 239 | 11 | 1.937 | 89 | <0.001 | 833 | 38.3 | 1.343 | 61.7 | <0.001 |
Diabetes only | 9 | 3.5 | 251 | 69.5 | 29 | 11.2 | 231 | 88.9 | 122 | 46.9 | 138 | 53.1 | ||||
Depression only | 8 | 4.4 | 175 | 95.6 | 43 | 23.5 | 140 | 76.5 | 101 | 55.19 | 82 | 44.8 | ||||
Diabetes with depression | 4 | 10.3 | 35 | 89.7 | 11 | 28.2 | 28 | 71.8 | 28 | 71.8 | 11 | 28.2 |
Note.Pvalues obtained from chi square test, with the exception of the value marked with an asterisk (*), obtained from Fisher's exact test.
As regards the variable of interest, the depression-diabetes co-morbidity was associated with the six disabilities (p≤0.001), with a greater prevalence of disability in the group that presented the co-morbidities (Tables 2 and 3).
Characteristics | Mobility disability | Relationship disability | Hearing disability | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Yes | No | P | Yes | No | P | Yes | No | P | ||||||||
n | % | n | % | n | % | n | % | n | % | n | % | |||||
Socio-demographic | ||||||||||||||||
Sex | Female | 56 | 40.9 | 81 | 59.1 | 0.001 | 4 | 3.5 | 133 | 97.1 | 0.722* | 17 | 12.4 | 120 | 87.6 | 0.065 |
Male | 696 | 27.6 | 1.826 | 72.4 | 88 | 2.9 | 2433 | 96.5 | 471 | 18.7 | 2.050 | 81.3 | ||||
Age group (years) | 60-69 | 570 | 26.6 | 1.577 | 73.5 | <0.001 | 69 | 3.2 | 2078 | 96.8 | 0.202 | 349 | 16.3 | 1.798 | 83.7 | <0.001 |
70-79 | 161 | 35.1 | 298 | 64.9 | 22 | 4.8 | 437 | 95.2 | 122 | 26.6 | 337 | 73.4 | ||||
80-89 | 21 | 40.4 | 31 | 59.6 | 1 | 1.9 | 51 | 98.1 | 17 | 32.7 | 35 | 67.3 | ||||
Physical activity (n=2.643) | Yes | 194 | 20.8 | 738 | 79.2 | <0.001 | 32 | 3.4 | 900 | 96.6 | 0.889 | 125 | 13.4 | 807 | 86.59 | <0.001 |
No | 555 | 32.4 | 1.156 | 67.6 | 57 | 3.3 | 1654 | 96.7 | 360 | 21 | 1.351 | 79 | ||||
Drug consumption (n = 2.648) | Yes | 70 | 34.2 | 135 | 65.9 | 0.051 | 6 | 2.9 | 199 | 97.1 | 0.656 | 37 | 18.1 | 168 | 81.9 | 0.895 |
No | 678 | 27.8 | 1.765 | 72.2 | 86 | 3.5 | 2357 | 96.5 | 450 | 18.4 | 1.993 | 81.6 | ||||
Health | ||||||||||||||||
Comorbidity | No depression or diabetes | 536 | 24.6 | 1.640 | 75.4 | <0.001 | 62 | 2.9 | 2114 | 97.2 | <0.001 | 363 | 16.7 | 1.813 | 83.3 | <0.001 |
Diabetes only | 104 | 40 | 156 | 60 | 6 | 2.3 | 254 | 97.7 | 59 | 22.7 | 201 | 77.3 | ||||
Depression only | 86 | 47 | 97 | 53 | 15 | 8.2 | 168 | 91.8 | 52 | 28.4 | 131 | 71.6 | ||||
Diabetes with depression | 26 | 66.7 | 13 | 33.3 | 9 | 23 | 30 | 76.9 | 14 | 35.9 | 25 | 64.1 |
Note.Pvalues obtained from chi square test, with the exception of the value marked with an asterisk (*), obtained from Fisher's exact test.
Strength of association of presenting disability in relation to co-morbidity
The magnitude or strength of association of presenting more or less probability of suffering from a disability, according to whether the subject is exposed solely to depression, to diabetes or with a depression-diabetes co-morbidity, or is not exposed to any event, was determined by calculating the crude and adjusted odds ratio of the socio-demographic variables that presented a significant association with disability (Tables 2 and 3).
Exposure solely to depression in the multivariate logistical regression models increases the likelihood of suffering from the following disabilities: understanding, with an adjusted OR of 2.37 (p<0.001); visual, with an adjusted OR of 2.01 (p<0.001); hearing, with an adjusted OR of 1.95 (p<0.001); mobility, with an adjusted OR of 2.70 (p<0.001), along with relationship difficulties, but only in the crude model, with a crude OR of 3.04 (p<0.001).
As regards diabetes, strong significant associations were found in visual disabilities, with an adjusted OR of 1.41 (p=0.01); hearing disabilities, with an adjusted OR of 1.45 (p=0.022); and mobility difficulties, with an adjusted OR of 1.98 (p<0.001) (Tables 4 and 5).
Speech disability* | Understanding disability* | Visual disability* | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
crude OR | CI95 | adjusted OR | CI95 | crude OR | CI95 | adjusted OR | CI95 | crude OR | CI95 | adjusted OR | CI95 | |
Comorbidity | ||||||||||||
No depression or diabetes | 1 | Ref. | 1 | Ref. | 1 | Ref. | 1 | Ref. | 1 | Ref. | 1 | Ref. |
Diabetes only | 1.22 | 0.60 to 2.49 | 1.23 | 0.60 to 2.51 | 1.02 | 0.68 to 1.153 | 1.01 | 0.67 to 1.52 | 1.43 | 1.10 to 1.85 | 1.41 | 1.09 to 1.83 |
p = 0.580 | p = 0.574 | p = 0.934 | p = 0.966 | p = 0.007‡ | p = 0.010‡ | |||||||
Depression only | 1.56 | 0.73 to 3.31 | 1.64 | 0.77 to 3.48 | 2.49 | 1.72 to 3.59 | 2.37 | 1.64 to 3.43 | 1.99 | 1.47 to 2.69 | 2.01 | 1.48 to 2.72 |
p = 0.248 | p = 0.201 | p <0.001‡ | p <0.001‡ | p <0.001‡ | p <0.001‡ | |||||||
Diabetes with depression | 3.90 | 1.34 to 11.30 | 3.98 | 1.37 to 11.58 | 3.18 | 1.56 to 6.48 | 2.97 | 1.45 to 6.11 | 4.10 | 2.03 to 8.29 | 4.09 | 2.03 to 8.27 |
p = 0.012‡ | p = 0.011‡ | p = 0.001‡ | p = 0.003‡ | p <0.001‡ | p <0.001‡ |
Note. *adjusted OR: OR adjusted to physical activity.
†adjusted OR: OR adjusted to sex and age.
‡Psignificant value ≤0,05.
CI95: confidence interval of 95%; OR: odds ratio; adjusted OR: adjusted odds ratio (obtained from logistic regression); crude OR: odds ratio crude; Ref: Reference.
Mobility disability* | Relationship disability* | Hearing disability* | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
crude OR | CI95 | adjusted OR | CI95 | crude OR | CI95 | adjusted OR | CI95 | crude OR | CI95 | adjusted OR | CI95 | |
Comorbid diabetes | ||||||||||||
No depression or diabetes | 1 | Ref. | 1 | Ref. | 1 | Ref. | 1 | Ref. | 1 | Ref. | 1 | Ref. |
Diabetes only | 2.04 | 1.56 to 2.66 | 1.98 | 1.51 to 2.60 | 0.81 | 0.34 to 1.88 | NA | NA | 1.47 | 1.07 to 2.00 | 1.45 | 1.05 to 1.99 |
p <0.001‡ | p <0.001‡ | p = 0.617 | p = 0.016‡ | p = 0.022‡ | ||||||||
Depression only | 2.71 | 2.00 to 3.68 | 2.70 | 1.98 to 3.69 | 3.04 | 1.70 to 5.47 | NA | NA | 1.98 | 1.41 to 2.79 | 1.95 | 1.38 to 2.76 |
p <0.001‡ | p <0.001‡ | p <0.001‡ | p <0.001‡ | p <0.001‡ | ||||||||
Diabetes with depression | 6.12 | 3.12 to 11.99 | 5.87 | 2.96 to 11.63 | 10.23 | 4.66 to 22.46 | NA | NA | 2.80 | 1.44 to 5.43 | 2.80 | 1.43 to 5.48 |
p <0.001‡ | p <0.001‡ | p <0.001‡ | p = 0.002‡ | p = 0.003‡ |
Note. * †adjusted OR: ajustado a sexo, grupo etario y actividad física deportiva.
†adjusted OR: ajustado a grupo etario y actividad física deportiva.
‡p valor significativo ≤0,05.
CI95: intervalo de confianza del 95%; NA: adjusted OR calculation not applicable due to there being no potential statistical confounding variables in the bivariate analysis; OR: odds ratio (razón de posibilidades); adjusted OR: adjusted odds ratio (obtained from logistic regression); OR(c): odds ratio crudo; Ref: Reference.
In the case of depression-diabetes co-morbidity, there was an increased likelihood of suffering from speech disabilities, with an adjusted OR of 3.98 (p=0.012); from understanding difficulties, with an adjusted OR of 2.97 (p=0.003); visual disabilities, with an adjusted OR of 4.09 (p<0.001); hearing difficulties, with an adjusted OR of 2.8 (p=0.003); mobility issues, with an adjusted OR of 5.87 (p<0.001); and relationship difficulties, with a crude OR of 10.23 (p<0.001) (Tables 4 and 5).
Secondary epidemiological calculations
The secondary calculations consisted of determining the crude prevalence ratio, which indicates the ratio between the prevalence of the result (disability), if there is diabetes with depression as a denominator, and the prevalence of the result (disability) if there is no diabetes or depression.
The adjusted OR previously calculated in Tables 4 and 5 indicates the chance of presenting the result (disability) as a numerator if there is exposure to diabetes with depression and as a denominator when there is the likelihood of presenting disability when there is no depression or diabetes (not exposed). The aetiological fraction of the population as the contribution percentage in a given disability, where diabetes with depression is presented and the aetiological fraction of exposed subjects explain the reduction of the disability in percentages, in cases where the exposed subjects stop being so (Table 6).
Result | Exposure | crude PR | adjusted OR | AFp|OR | AFe|OR | ||
---|---|---|---|---|---|---|---|
(AFp|OR) | CI95 | (AFe|OR) | CI95 | ||||
Difficulties in relating to others | Diabetes with depression | 7.9 | 10.23* | 11.4% | 4.4 to 22.0 | 90.2% | 78.5 to 95.6 |
Mobility disability | 2.71 | 6.12 | 3.9 | 2.1 to 5.7 | 83.7% | 68 to 91.7 | |
Speech disability | 3.60 | 3.98 | 4.5 | 1.4 to 10.4 | 74.3% | 25.6 to 91.2 | |
Visual disability | 1.87 | 4.09 | 2.46% | 1.2 to 3.7 | 75.6% | 50.8 to 87.9 | |
Difficulties in understanding | 2.56 | 3.18 | 3.0% | 0.4 to 5.6 | 68.6 | 36.1 to 84.6 | |
Hearing disability | 2.1 | 2.80 | 2.4% | 0.4 to 4.4 | 64.3% | 30.6 to 81.6 |
Note. *crude OR.
AFe|OR: aetiological fraction in exposed subjects; AFp|OR: aetiological fraction in population; CI95: confidence interval of 95%; OR: odds ratio; adjusted OR: adjusted odds ratio; crude PR: crude prevalence ratio.
Calculations made using not having depression or diabetes as a reference.
Discussion
This study, carried out with data from the 2016 Peruvian National Prisons Census, found associations between the depression-diabetes co-morbidity and the six disabilities (hearing, visual, understanding, mobility, relationships and speech) established by the Washington group for disability. In other words, the hypothesis is accepted that elderly prison inmates with depression-diabetes co-morbidity are more likely to have a disability estimated at: 71.8% sight; 66.7% mobility; 23.0% relating to others; 35.9% hearing; 28.2% understanding; and 10.3% speech, in comparison to elderly inmates without co-morbidities. This relationship was also visible in the associations between disability and only diabetes or depression, but at lower proportions than when there was a co-morbidity.
There are a number of factors that may play a part in the co-morbidity. The direction The direction can be two-way: persons with diabetes may be more likely to get depressed and depressed persons may be more at risk of suffering from diabetes11,16,30.
On the other hand, co-morbidity increases the probability of multiple disabilities, which can be seen in the results of this study. Although this has not been seen in similar studies on elderly prison inmates, the results do match those in a research project carried out in Singapore16, where a 15 year long longitudinal monitoring study on a Hispanic population in the USA showed that depression accelerated the disability process over time14.
Depression affects the capacity to relate to others, and this can explain the disability in relating to others and in mobility10,11. The effect on the disability in mobility, vision and hearing, may be explained by the deterioration provoked by diabetes31-33, while the disability in speech and understanding are related to the cognitive deterioration common to both conditions34,35. These results match the ones obtained in this study.
Furthermore, the factors that may explain the differences in the association are related to the socio-demographic characteristics of older adults. This study showed that physical and sports activities are an important factor in visual, hearing (besides age), mobility and speech disabilities, while sex and age are relevant factors in mobility disabilities. These results match those from a longitudinal study carried out in China, which showed that the association of depression and disability are different according to gender, and so should be treated differently17,36. Only in the case of understanding disabilities was there an association with sex and the age group.
The multivariable models adjusted by the variables of physical activity, sex and age group, maintained the probability of having the six types of disability in older adults with depression-disability co-morbidity in comparison to those who do not have both co-morbidities.
There are studies that show other relevant factors, such as differentiated health services and socio-emotional support, which can mitigate this strength of association. This was shown in a Canadian study on adults with depression-diabetes co-morbidity, the results of which showed greater functional disability, while indicating that this process can be mitigated with social support15.
This evidence highlights the need to strengthen and amplify the national prison census, in order to gather information that can help to more effectively define the interventions, strategies and guidelines for promotion, prevention and care for the prison population, especially elderly inmates, given that the health services are limited and not all the medical specialisations are available.
One of the main limitations of this study is the design, which does not permit the direction of the variables to be clearly established. However, the estimates match other studies that show that disability is greater amongst women, the elderly and when both co-morbidities are present. A selection bias was identified in depression diagnosed by a health professional, therefore there may be a high level of under-reporting, but the base of the census presented enough power for analysis of this variable.
There may also be a memory bias, although a reduced one, given that the questions about the main variables refer to the present time (diabetes, depression, disability, sex, age) or an event that took place no more than a month ago (participation in sports activities over the last month). The question about drug use before entering prison may have a greater memory bias, since it depends on the time each participant has spent in prison. It may also be subject to under-reporting28.
The strengths of this study include its representative nature at national level and the opportunity to present estimates with different strengths of association for each co-morbidity, which enables disability to be better understood, helps in making timely decisions and prioritising the services that should be implemented in prisons.
Conclusions
The main finding of this study is that the hypothesis about the increased likelihood of presenting the six disabilities due to the presence of co-morbid diabetes and depression (p <0.001) has been confirmed.
The most powerful measurement of association is in the disability in relating to others, with an adjusted OR of 6.99; followed by mobility disabilities, with an adjusted OR of 5.52, while the lowest strength of association found was for hearing disabilities, with an adjusted OR of 1.75.
The largest aetiological fraction in the population (with co-morbid diabetes and without diabetes or depression) was in the disability in relating to others, where the modification of the exposure (co-morbid) diminished by 16%. The largest fraction of exposed subjects also corresponds to the disability in relating to others, where 86% of this disability can be attributed to exposure.
These findings may be used for establishing approaches for management of depression-diabetes in prison, so as to reduce their impact on the disability load. In terms of research, primary studies that set out to clarify other variables not included in this study are recommended, such as the characteristics of these diseases, medical management, nutritional and psychological treatment and treatment adherence as factors associated with disability in older adults.