Association of diabetes-related factors with life satisfaction and sleep disturbances among Indian ageing adults: Evidence from a large-scale study

Abstract

Countries across the world, including India, are witnessing an increase in the cases of diabetes, posing public health challenges. Although diabetes is a metabolic disease, psychosocial factors are crucial in its management. Hence, the present study tried to identify the association of diabetes-related factors with life satisfaction and sleep disturbances among ageing adults living with diabetes in India. The data of adults aged 45 years and older living with diabetes (N = 8272) were extracted from the Longitudinal Ageing Study in India Wave 1 (2017-18). We conducted weighted least squares regression, t-test, and descriptive analysis. The likelihood of life satisfaction reduced with insulin usage (β = −.73, 99% CI: −1.16 to −.29), special diet (β = −.92, 99% CI: −1.31 to −.54), smoking habit, involvement in physical activity, depressive symptoms, lack of involvement in social activities and with duration of diabetes. The insulin usage (β = −.25, 99% CI: −.44 to −.07), special diet (β = −.22, 99% CI: −.38 to −.06), and involvement in physical activities decreased the probability of sleep disturbances, while alcohol consumption, smoking habits, and depressive symptoms escalated the likelihood of it. The evidence from this study underlines the links between diabetes and psychosocial factors. It signifies the importance of addressing such factors to ensure better glycemic control and the well-being of people living with diabetes.

Keywords

diabetes life satisfaction sleep disturbances depression psychosocial aspects

Introduction

Globally, there has been a rise in diabetes cases from 422 million in 2014 to 537 million people in 2021, especially with an alarming increase in prevalence among low- and middle-income countries (International Diabetes Federation, 2021; World Health Organization [WHO], 2023). In general, diabetes results in comorbidities and can lead to a range of health complications if not well managed (Tomic et al., 2022). Diabetes impacts an individual’s physical health and social and psychological well-being (Kalra et al., 2018). The management includes medication adherence and lifestyle modification involving positive health behaviour (ElSayed et al., 2022; Garedow et al., 2023; Patel and Keyes, 2023). Positive health behaviour includes a healthy diet, involvement in physical activities, and avoidance of smoking and alcohol. Although it is a requirement in diabetes management (Ahmad and Joshi, 2023; ElSayed et al., 2022), not all are involved in healthy behaviours due to barriers at different levels (Adhikari et al., 2021; Padma Sri Lekha and Abdul Azeez, 2024; Rosiek et al., 2016). A range of bio-psycho-social factors influences involvement in these behaviours (Amsah et al., 2022; Świątoniowska-Lonc et al., 2021).

In addition, diabetes management could be exhausting physically and mentally as it requires persistent and long-term behavioural changes. Corbin and Strauss (1985) suggested that chronic illness management includes three lines of work: illness work, everyday life work, and biographical work. Coping with everyday struggles might require adaptation in physical, social and emotional dimensions (Moos and Holahan, 2007). Although individuals diagnosed with diabetes slowly adapt and try to lead productive lives over time, about one-third of them have witnessed distress, anxiety, depression, and eating disorders (Snoek, 2022). Further, studies have also evidenced the presence of diabetes distress (Rariden, 2019) and a three times higher risk of major depression among individuals living with diabetes compared to the general population (Kreider, 2017), which could hamper life satisfaction. A study conducted among diabetic outpatients in Nigeria pointed out the high risk of low self-esteem, poor mental health, and low life satisfaction among these patients, disturbing their quality of life (Okwaraji et al., 2017). A positive association exists between self-management and life satisfaction among individuals with diabetes (Özkan Tuncay and Avcı, 2020). However, the risk of depression increases with diabetes complications such as nephropathy (Zhang et al., 2023). The duration of illness was negatively associated with quality of life (Diriba et al., 2023), disrupting satisfaction and well-being as it increases disability (Tsai et al., 2021) among diabetic ageing adults.

Good sleep is also an influential factor for well-being among individuals with diabetes. Moreover, the literature points to a higher prevalence of sleep disturbances among individuals with diabetes (Alamer et al., 2022; Birhanu et al., 2020). A study among diabetes patients evidenced poor sleep quality, which is associated with nocturia, restless leg syndrome, and emotional burden (Nasir et al., 2022). In addition, sleep problems are determined by depression and gender (Kia et al., 2023). Furthermore, the combined effect of poor sleep quality and depression elevated the risk of poor diabetes-related quality of life, with a higher risk among women (Zhang et al., 2016). Interestingly, life satisfaction and sleep quality are bi-directionally associated with glycemic control.

Although combating the rising cases of diabetes is a global public health challenge, it has a devastating impact on developing nations like India. Fuelled by socio-demographic shifts and lifestyle changes, India had 77 million individuals living with diabetes as of 2019, and a projection to grow to over 134 million by 2045 (Pradeepa and Mohan, 2021). As this will increase the disease burden of the nation and disability adjusted life years, it becomes essential to identify the determinants of life satisfaction and sleep quality among people living with diabetes. Further, with minuscule studies in this context in India, the present study tried to understand the role of diabetes-related factors, health behaviours, and socio-emotional factors on life satisfaction and sleep quality among middle-aged and older adults living with diabetes (refer to the conceptual framework of the study in Figure 1).

Figure 1.

Conceptual framework of the study. Note: unadjusted model (a) = diabetes-related factors + health behaviors + socio-emotional factors→ life satisfaction. Unadjusted model (b) = diabetes-related factors + health behaviours + socio-emotional factors→ sleep disturbances. Adjusted model (a) = unadjusted model (a) + covariates→ life satisfaction. Adjusted model (b) = unadjusted model (b) + covariates→ sleep disturbances.

Methods

Data

The data were extracted from the Longitudinal Ageing Study in India (LASI) Wave 1 (2017-2018). This survey assessed ageing associates such as health, psychosocial, socioeconomic, and psychiatric factors among ageing adults (45 years and above). The data was collected from all Indian states with a sample size of 73,396 ageing adults (International Institute for Population Sciences, 2020). The present study focused exclusively on adults with diabetes (type 1 or type 2) (N = 8746). Further, after removing the missing cases, this study had a sample size of 8272 adults living with diabetes aged 45 years and above (Refer to Figure 2 for the sample selection criteria).

Figure 2.

Sample selection criteria and process.

Outcome variables

Life satisfaction

The survey utilized ‘The Satisfaction with Life Scale' developed by Diener et al. (1985) to assess life satisfaction among the participants. The scale includes five questions with a seven-point Likert response (1 = strongly disagree; 7 = strongly agree). The score ranged from 5 to 35, with a higher score indicating the likelihood of good life satisfaction. The scale showed excellent reliability in this sample (Cronbach Alpha = .90).

Sleep disturbances

The survey used an adapted measure from the Jenkins Sleep Scale by Jenkins et al. (1988) to assess the sleep disturbances, which consisted of four items related to sleep problems, with four-point responses, where one indicates ‘Never’ and four indicates ‘Frequently (5 or more nights per week)’. The score ranged from 4 to 16, with a higher score indicating a greater likelihood of sleep disturbance. The scale has a good reliability for the sample with Cronbach Alpha = .88.

Predictor variables

This included three factors, namely, diabetes-related, health behaviours, and socio-emotional factors.

Diabetes-related factors

These consist of the intake of diabetes medicines, insulin use, and following a special diet to manage diabetes. Individuals taking diabetes medication were identified by the question, ‘In order to treat or control your diabetes or high blood sugar, are you currently taking medications that you swallow?’. Similarly, insulin usage and following a special diet were assessed with the questions ‘Are you currently using insulin shots/injections?’ and ‘In order to control your diabetes, are you following a special diet?’ respectively. These three questions had a response pattern of ‘yes’ or ‘no’.

Health-behaviour factors

These factors comprised health behaviours such as alcohol consumption, smoking habits, and involvement in physical activities. The alcohol consumption and smoking habits had a response pattern of ‘yes’ or ‘no’. At the same time, involvement in moderate physical activities was categorised as ‘yes’ (if the response was every day, more than once a week, and once a week) or ‘no’ (if the response was one to three times a month and hardly ever or never).

Socio-emotional factors

Under this domain, we considered depressive symptoms and involvement in social activities. The depressive symptoms were assessed using an adapted version of the Centre for Epidemiological Studies Depression Scale (CES-D) (Radloff, 1977), which comprises 10 items (of which 7 were about negative and 3 were positive feelings) with a four-point Likert scale response pattern (1 = rarely/never, less than 1 day; 4 = most or all of the time, 5–7 days). The composite score ranges from 10 to 40, with a higher score pointing to the presence of depressive symptoms. The measure had good reliability (Cronbach Alpha = .78) in this sample. Second, involvement in social activities was assessed through the frequency of involvement in 11 different types of activities (eating out, going to park/beach/entertainment, involvement in indoor and outdoor games, visiting relatives and friends, attending cultural performances, religious functions and political/community/organization group meetings, reading books/newspapers/magazines, watch television/ listen radio, using computer for email/net surfing) with response pattern ranging from 1 (Daily) to 7 (Never). The score ranges from 11 to 77, with a higher score indicating a lack of involvement in social activities. Further, the measure had suitable reliability (Cronbach Alpha = .65) for this sample.

Covariates

A range of socio-demographical variables were included in the model as age (in years), gender (male or female), educational status (yes/no), marital status (in a union or not in a union), Self-Rated Health (SRH) (Good or poor), Activities of Daily Living (ADL), Instrumental Activities of Daily Living (IADL), socioeconomic status (poorest, poorer, middle, richer and richest), duration of diabetes (in years) and location (rural or urban).

Statistical analysis

We used STATA version 16 to conduct all the analysis. A descriptive analysis was run to understand the characteristics of the population. Further, we employed t-tests to see the differences in outcome variables across the categories. In addition, we ran Weighted Least Square (WLS) regression models (adjusted and unadjusted) to identify the determinants of life satisfaction and sleep disturbances among individuals living with diabetes.

Results

The descriptive characteristics of the sample are presented in Table 1. The study included a sample size of 8272 ageing adults living with diabetes. The sample’s life satisfaction (M = 24.46; SD = 7.59) and sleep disturbances (M = 6.87; SD = 3.22) are moderate, as 38.57% of the adults in the sample scored lower than the mean, indicating poor life satisfaction. Similarly, 40% of the sample had scored above the mean, indicating moderate to severe sleep disturbances. Regarding diabetes-related factors, 81.53% were under medication, 17.15% of the participants were taking insulin, and 76.13% followed a special diet due to diabetes. Further, the majority reported having good health behaviour, as only 11.59% and 25.68% ever consumed alcohol and smoked, respectively. It is evident that 64.18% involved moderate physical activities. In addition, considering the mean as a cutoff, about 43% had moderate to severe levels of depressive symptoms (M = 19.58; SD = 4.01) and poor involvement in social activities (Mean = 63.59, SD = 8.97). The average age of individuals with diabetes was 61.84 years, with a higher proportion of females (54.18%). In the sample, 66.87% were educated, 74.77% were in a union, and 29.60% had poor self-rated health. Further, with the mean cutoff, about 19% and 25% of the sample had poor ADL (Mean = .44, SD = 1.15) and poor IADL (Mean = 1.30, SD = 1.96), respectively. In addition, 54.73% of adults living with diabetes were located in an urban setting. The mean duration of illness was 47.48 years (SD = 19.26) in this sample.

Table 1.

Descriptive characteristics of the sample (N = 8272).

Variables	Frequency/mean	w%/SD^a
Life satisfaction	24.46	7.59
Sleep disturbances	6.87	3.22
Diabetes-related factors
Diabetes medicine
No	1527	18.47
Yes	6745	81.53
Insulin use
No	6853	82.85
Yes	1419	17.15
Special diet
No	1975	23.87
Yes	6297	76.13
Health behaviour
Alcohol consumption
No	7313	88.41
Yes	959	11.59
Smoking
No	6148	74.32
Yes	2124	25.68
Physical activities
No	2963	35.82
Yes	5309	64.18
Socio-emotional factors
Depressive symptoms	19.58	4.01
Social activities	63.59	8.97
Covariates
Age (in years)	61.84	9.69
Gender
Male	3790	45.82
Female	4482	54.18
Educational status
No	2740	33.13
Yes	5532	66.87
Marital status
In a union	6185	74.77
Not in a union	2087	25.23
Self-rated health (SRH)
Good	5824	70.40
Poor	2448	29.60
ADL	.44	1.15
IADL	1.30	1.96
Socio-economic status
Poorest	1173	14.18
Poorer	1296	15.66
Middle	1515	18.31
Richer	1903	23.01
Richest	2385	28.84
Duration of illness (in years)	47.48	19.26
Location
Urban	4527	54.73
Rural	3745	45.27

^aw% - weighted Percentage; SD- standard deviation.

Table 2 presents the t-test with binary categorical variables for life satisfaction and sleep quality. There existed a significant difference in life satisfaction among individuals concerning insulin usage (t = 2.67, p = .01), smoking habit (t = 2.50, p = .01), gender (t = 2.85, p = .00), educational status (t = −12.65, p = .00), marital status (t = 7.04, p = .00), SRH (t = 14.30, p = .00) and location (t = 5.06, p = .00). Further, in terms of sleep disturbances significant difference existed based on intake of diabetes medicine (t = 3.18, p = .00), insulin usage (t = −4.66, p = .00), special diet (t = 2.57, p = .01), alcohol consumption, involvement in moderate physical activities, gender, educational status, marital status, SRH and location.

Table 2.

t-test with binary categorical variables for life satisfaction and sleep disturbances.

Variables	N	Life satisfaction				Sleep disturbances
Variables	N	Mean	t	p	Mean	t	p
Diabetes medicine
No	1510	24.56	−1.20	.22	7.24	3.18	.00
Yes	6762	24.81			6.94
Insulin use
No	7217	24.84	2.67	.01	6.94	−4.66	.00
Yes	1055	24.22			7.44
Special diet
No	2006	24.87	.75	.45	7.16	2.57	.01
Yes	6266	24.73			6.95
Alcohol consumption
No	7058	24.74	−.76	.44	6.98	2.82	.00
Yes	1214	24.91			7.03
Smoking
No	6084	24.88	2.50	.01	6.98	−.55	.58
Yes	2188	24.44			7.03
Physical activities
No	3284	24.65	−1.18	.23	7.20	4.58	.00
Yes	4988	24.84			6.87
Gender
Male	3970	25.00	2.85	.00	6.65	−9.50	.00
Female	4302	24.55			7.73
Educational status
No	2516	23.28	−12.65	.00	7.54	10.11	.00
Yes	5756	25.41			6.76
Marital status
In a union	6328	25.07	7.04	.00	6.84	−8.04	.00
Not in a union	1944	23.77			7.52
SRH
Good	5900	25.46	14.30	.00	6.58	−18.87	.00
Poor	2372	23.02			8.05
Location
Urban	4655	25.11	5.06	.00	6.80	−6.25	.00
Rural	3617	24.32			7.25

A weighted OLS regression analysis was conducted to identify and understand the determinants of life satisfaction and sleep disturbances among individuals with diabetes (Table 3). Insulin usage and following a special diet reduced the likelihood of life satisfaction (β = −.73, 99% CI: −1.15 to −.29; β = −.86, 99% CI: −1.25 to −.47, respectively) compared to their counterparts. In addition, involvement in moderate physical activities (β = −.58, 99% CI: −.91 to −.25), presence of depressive symptoms (β = −.51, 99% CI: −.55 to −.47) and poor involvement in social activities (β = −.09, 99% CI: −.10 to −.07) reduced the likelihood of life satisfaction among individuals living with diabetes. These results were consistent with the adjusted model for life satisfaction. Considering the covariates, increase in age, being a female, being educated, and the presence of IADL increased the likelihood of life satisfaction. While not in a marital union (β = −1.20, 99% CI: −1.60 to −.79), poor ADL (β = −.17, 95% CI: −.33 to −.01), and longer duration of diabetes (β = −.016, 99% CI: −.02 to −.007) decreased the likelihood of life satisfaction among individuals living with diabetes.

Table 3.

Weighted Least Square (WLS) regression with life satisfaction and sleep disturbances as dependent variables (N = 8272).

Variables	Unadjusted model		Adjusted model
	Life satisfaction	Sleep disturbances	Life satisfaction	Sleep disturbances
	β (95% CI)	β (95% CI)	β (95% CI)	β (95% CI)
Diabetes-related factors
Diabetes medicine (ref. no)
Yes	.39 (−.04 – .82)	.00 (−.17 –.18)	.38 (−.33 – .80)	−.02 (−.19 – .16)
Insulin use (ref. no)
Yes	−.73 ** (−1.15 to −.29)	−.24** (−.42 to −.06)	−.73** (−1.16 to −.29)	−.25** (−.44 to −.07)
Special diet (ref. no)
Yes	−.86** (−1.25 to −.47)	−.16 (−.32 – .01)	−.92** (−1.31 to −.54)	−.22** (−.38 to −.06)
Health behaviour
Alcohol consumption (ref. no)
Yes	−.13 (−.66 – .40)	.07 (−.15 – .29)	.23 (−.29 – .76)	.30** (.08 – .53)
Smoking (ref. no)
Yes	−.00 (−.39 – .39)	.21* (.05 – .38)	.47* (.07 – .87)	.31** (.15 – .48)
Physical activities (ref. no)
Yes	−.58** (−.91 to −.25)	−.33** (−.47 to −.19)	−.77** (−1.11 to −.44)	−.25** (−.39 to −1.03)
Socio-emotional factors
Depressive symptoms	−51** (−.55 to −.47)	.20** (.18 – .21)	−.42** (−.46 to −.38)	.17** (.14 – .18)
Social activities	−.09** (−.10 to −.07)	.04** (.03 – .05)	−.05** (−.07 to −.03)	.01 (−.00 – .01)
Covariates
Age (in years)			.07** (.05 – .09)	.01* (.002 – .02)
Gender (ref. male)
Female			1.58** (1.19 – 1.96)	.68** (.52 –.84)
Educational status (ref. #o)
Yes			2.26** (1.89 – 2.63)	.19* (−.04 -.35)
Marital status (ref. in a union)
Not in a union			−1.20** (−1.60 to −.79)	.10 (−.06 – .28)
SRH (ref. good)
Poor			−2.52** (−2.87 to −2.16)	.86** (.71 – 1.01)
ADL			−.17* (−.33 to −.01)	.31** (.24 −.38)
IADL			.11* (.01 – .22)	.07** (.03 −.11)
Socio-economic status (ref. poorest)
Poorer			−1.06** (−1.62 to −.51)	.04 (−.19 – .28)
Middle			−.61* (−1.15 to −.07)	.08 (−.14 – .32)
Richer			.09 (−.43 – .62)	−.06 (−.29 – .15)
Richest			−.83** (−1.35 to −.30)	−.36** (−.58 to −.14)
#Duration of diabetes (in years)			−.016** (−.02 to −.007)	.001 (−.002 – .005)
Location (ref. urban)
Rural			.28 (−.06 – .63)	.39** (.24 – .54)

*p < 0.05; **p < 0.01.

In the context of sleep disturbances as the outcome, insulin use (β = −.24, 99% CI: −.42 to −.06), involvement in physical activities (β = −.33, 99% CI: −.47 to −.19) and social activities reduced the likelihood of sleep disturbances. While the presence of smoking habit (β = .21, 95% CI: .05 −.38) and depressive symptoms (β = .20, 99% CI: .18 −.21) increased the possibility of sleep disturbances among individuals living with diabetes. These results were consistent with the adjusted model of sleep disturbances except for social activities that were not significant. In addition, following a special diet (β = −.22, 99% CI: −.38 to −.06) reduced the likelihood of sleep disturbances while consuming alcohol (β = 30, 99% CI: .08 −.53) increased it. The likelihood of sleep disturbances increased with age (β = .01, 95% CI: .002 −.02), female gender, and being educated. In addition, poor SRH (β = .86, 99% CI: .71- 1.01), ADL (β = .31, 99% CI: .24- .38), IADL (β = .07, 99% CI: .03- .11), and located in rural settings significantly increased the likelihood of sleep disturbances among individuals living with diabetes compared individuals residing in urban residence.

Discussion

The current study tried to understand the predicting factors of life satisfaction and sleep disturbances among middle-aged and older adults living with diabetes (Figure 3). This study’s results indicated poor life satisfaction among individuals taking insulin and following a special diet. Similarly, earlier studies suggested poor life satisfaction, happiness (Agrawal, 2015), and quality of life among insulin users compared to their counterparts (Davis et al., 2001). However, compared to oral medication users, insulin users had better health-related quality of life, treatment adherence, and health outcomes (Gillani et al., 2019). In terms of diet and life satisfaction, minuscule studies have addressed this to our knowledge. Since food is associated with pleasure and happiness, diet restrictions could hamper life satisfaction. In addition, a study conducted among women with diabetes evidenced a correlation between life satisfaction and the type of food consumption (Gacek and Wojtowicz, 2019). In terms of health behaviours, contradictory to earlier evidence, the present study results point to the positive role of smoking on life satisfaction. This could be mainly due to the subjective pleasure people derive from smoking. However, literature points to the ill effects of smoking in the form of higher cardiovascular events among people with diabetes (Pan et al., 2015), and smoking frequency was negatively associated with life satisfaction and partially mediated by SRH (Kang, 2022). Contrary to an earlier study by Soleimani Tapehsari et al. (2020), this study’s results showed that involvement in moderate physical activities is associated with poor life satisfaction among individuals with diabetes.

Figure 3.

Schematic representation of adjusted regression model results. Note. ‘+’ indicates increase in the outcome; ‘−’ a decrease.

The role of socio-emotional factors, such as depressive symptoms and social activities, on life satisfaction among individuals with diabetes is evident, as the presence of depressive symptoms and poor involvement in social activities reduced the likelihood of life satisfaction. These results were congruent with previous studies suggesting the negative role of depression on quality of life (Accinelli et al., 2021; Schram et al., 2009). Further, only a few studies have addressed the involvement of social activities among individuals with diabetes. Nonetheless, studies have pointed to the detrimental effects of social exclusion and isolation (Ida and Murata, 2022; Prell et al., 2023), indirectly suggesting the usefulness of involvement in social activities.

In terms of covariates, an increase in age, being a female, educated, in a marital union, lower ADL, higher IADL, and lower duration of diabetes increased the likelihood of good life satisfaction, while life satisfaction has reduced irrespective of socioeconomic status. These results were consistent with the literature (Diriba et al., 2023; Imayama et al., 2011), except for life satisfaction among females and IADL. However, a study among women living with diabetes indicated higher mental health and health perception despite their impaired roles (Gillani et al., 2018). This could be attributed to the prevailing cultural factors that create a gendered diabetes management experience among adults. In addition, the present study evidenced contrasting results in terms of IADL, as difficulties in IADL increased the likelihood of life satisfaction. To our knowledge, there is no earlier work on the association between IADL and life satisfaction among individuals with diabetes. In general, it is established that the presence of diabetes accelerated the detrimental aspect of morbidity and functionality (Tsai et al., 2021), in turn reducing life satisfaction. However, involvement in positive health behaviours could reduce negative outcomes associated with poor IADL, increasing the possibility of life satisfaction.

Considering sleep disturbances, this study showed that following insulin usage and special diet reduced the likelihood of sleep disturbances. To our knowledge, there is no earlier work on these factors’ role in sleep disturbances among individuals living with diabetes. However, a complex and cyclic association exists between sleep and diabetes and its management (Barone and Menna-Barreto, 2011). In contrast to the present results, there is evidence of an association between nocturnal hypoglycemia and sleep disruption (Surani et al., 2015), while there is a possibility of improvement in sleep with insulin usage as it regulates homeostasis in the body. We suggest future studies ponder these factors more deeply to test the results. In terms of diet, the results were consistent with earlier works as a review pointed at the association between diet, nocturnal changes, and glucose regulation (Mantantzis et al., 2022), and in general, high-calorie intake as carbohydrates and fat was associated with short duration of sleep (Alruwaili et al., 2023).

In terms of health behaviours, similar to earlier studies (Barakat et al., 2019; Birhanu et al., 2020), this study’s results suggested that unhealthy behaviours like alcohol consumption and smoking led to sleep disturbances among ageing adults living with diabetes. Also, this study showed that involvement in moderate physical activities had reduced sleep disturbances, as supported by an earlier study where individuals involved in less physical activities had a higher prevalence of insomnia (Vézina-Im et al., 2021). Further, considering the socio-emotional factors, this study’s results revealed that depressive symptoms and not being involved in social activities increased the likelihood of sleep disturbances. The studies by Birhanu et al. (2020) and Zewdu et al. (2022) identified depression as a significant predictor of sleep quality among people living with diabetes. In addition, an earlier work suggested a positive association between neighbourhood social cohesion and sleep quality (Ma et al., 2023) which could promote involvement in social activities. To our knowledge, no study exists on the association between social activities and sleep quality among individuals with diabetes.

Further, the results of this study suggested that an increase in age, being female, being educated, having poor SRH, higher ADL and IADL, and residing in rural areas are associated with sleep disturbances. These results were supported by literature, although not specific to diabetes (Kia et al., 2023; Park et al., 2013; Xiao et al., 2022; Zhang et al., 2020), except for educational status. In contrast, an earlier work suggested a decrease in the likelihood of poor sleep quality with levels of education among individuals living with diabetes (Riahi et al., 2024). However, there is also a possibility that increased education would create more responsibility and many more things to manage that could influence sleep quality among individuals with diabetes.

Limitations

As limitations are inevitable in any empirical investigation, the present study also holds certain limitations. First, due to its cross-sectional nature, the study does not give the causal relationship between the variables. Second, biological tests were not conducted among the sample to get their exact blood glucose levels and HbA1C. Third, the study included a few self-reported measures, which may pertain to reporting bias, although the reliability is well-established. Fourth, the study did not include data related to the type of diabetes and frequency of diabetes medication, insulin usage, and special diet, as they were unavailable. Finally, we have considered the response to health behaviours as binary and did not include the frequency of these behaviours. Future research should consider these limitations while designing studies. Also, studies can comprehensively explore the subject matter under this study through a longitudinal design and using biomarkers.

Conclusions

The present study tried to identify the role of diabetes-related and socio-emotional factors on life satisfaction and sleep disturbances among ageing adults living with diabetes. The study results evidenced that insulin usage, following a special diet, involvement in physical activities, higher depressive symptoms, less involvement in social activities, poor SRH, higher ADL and not being in a marital union, and longer duration of diabetes were associated with lower life satisfaction among adults with diabetes. On the other hand, smoking, an increase in age, being female, being educated, and higher IADL resulted in better life satisfaction. Regarding sleep disturbances, we identified that using insulin, special diets, and involvement in physical and social activities reduced the likelihood of sleep disturbances. The possibility of sleep disturbances is increased by unhealthy behaviours (alcohol consumption and smoking), depressive symptoms, age, being female, being educated, having poor SRH, having higher ADL, IADL, and residing in rural settings.

The results highlight the importance of psychosocial interventions for enhancing life satisfaction and sleep among adults with diabetes. It is crucial to promote involvement in physical and social activities among individuals living with diabetes. Promoting peer education and awareness on diabetes and its management with community involvement is crucial. Further, the results highlight the need for multidimensional and integrated healthcare services and policies for ageing adults with diabetes to improve their glycemic control and well-being. In addition, healthcare provisions should focus on retaining and improving functionality among ageing adults with diabetes during their illness, which could improve their well-being.

Footnotes

ORCID iD

E. P. Abdul Azeez

Ethical approval

Ethical approval for conducting the Longitudinal Ageing Study in India (LASI) was guided by the Indian Council of Medical Research. The secondary data used for this study is freely available in the public domain. Hence, no third-party ethical clearance was sought for this study.

Author contributions

The authors contributed equally to the study’s design, development, and write-up.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data used for this study is available through the following website. https://www.iipsindia.ac.in/content/lasi-wave-i or through .

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