knitr::opts_chunk$set(echo = FALSE, message = FALSE, warning = FALSE)Depression is a significant growing health concern affecting millions of people worldwide and contributing to the global disease burden caused by several factors (WHO,2021). This mental illness can lead to self-harm or suicide and is characterized by high levels of sadness, apathy, guilt, low self-confidence, poor sleep, fatigue, and difficulty concentrating. These factors may be social and emotional factors such as sleeplessness, loneliness, sadness and unhappiness strongly correlating with the onset and severity of depression. Lack of sleep, loneliness and unhappiness increase the risk of depression by impacting emotional regulation and reducing social support (Baglioni et al.,2011). Understanding these predictors is important to improve mental health interventions and reduce the global disease burden. The justification for choosing this dependent variable lies in the rising prevalence of depression and the need to understand the social determinants that contribute to its onset and severity.
Prevalence and relationship between depression and social health determinants Social Health Determinants as Explanatory Variables: In Finland, the prevalence of depression remains a pressing issue, with approximately 5.9% of the population experiencing depressive symptoms annually (OECD, 2023). Recent studies highlight that social health determinants, such as gender, age, income, employment status, education level, and social support, play a crucial role in influencing mental health outcomes (WHO, 2022). In this study, we shall explore how social determinants such as happiness, lack of sleep, sadness and loneliness contribute to increasing levels of depression among the population of Finland.
Poor sleep patterns and disturbances are strong predictors of depression. Insufficient sleep exacerbates the relationship between lack of sleep and high depression rates, intensifying symptoms such as sadness, fatigue, and cognitive impairment (Lee et al., 2024). According to (Dong, L.et al., 2022) show that people who experience chronic sleep disturbances have 1.9 times higher to develop depression than those with healthy sleep patterns, Studies show that supportive social network helps mitigate the adverse effects of stress and reduces the risk of depression (Onyekachi et al., 2024).
Loneliness and social isolation Loneliness is a powerful social determinant of depression. Research indicates that loneliness increases the risk of depression by 26%, particularly among the elderly and individuals with limited social support (Cacioppo et al., 2015). Social isolation reduces opportunities for emotional validation and meaningful interactions, which are crucial for mental well-being.
Persistent sadness is a core symptom of depression, closely associated with chronic stress, loss, and emotional trauma. Studies highlight that sadness leads to prolonged depressive episodes, especially when compounded by poor coping mechanisms and inadequate social support (Kessler et al., 2010).
Happiness, while less studied in the context of depression, is known to be a buffer against mental illness(Seo, E. et al.,2018). Positive emotions and strong social connections foster resilience and promote better mental health outcomes. Individuals with higher happiness levels are more likely to engage in self-care behaviors and social activities, reducing the risk of depression(Luis.E.et al.,2021)
The study operationalized variables with depression status measured using the d20-d27 variables to create the CES-D8 depression scale. The independent variables were categorized on how frequently it happened in the past week i.e. sleeplessness, happiness, feelings of depression, sadness and loneliness. They were categorized as (none or almost none of the time, most of the time, all or almost all the time). Descriptive statistics summarized sample characteristics, while correlation analysis and multivariate regression analysis explored the relationship between social health determinants and depression. The data used was a subset of Finland.
Null hypothesis(H0): there is no relationship between the independent variables and depression Alternative hypothesis(H1): There is an association between the independent variables and depression H1: The more feeling of depression “fltdpr” is associated with higher levels of depression H1: Sleeplessness “slprl” is associated with high levels of depression H1: Sadness “fltsd” is associated to increase of depression levels H1: Loneliness “fltlnl” is associated to higher depression levels H1: Happiness “wrhpp” is associated to low levels of depression H1: Could not get going “cldgng” is related to an increase in depression H1: The feeling that everything did as effort “flteeff” is associated with an increase in depression.
The data-set used in this analysis is drawn from the ESS11 with a subset focusing on Finland. The sample consists of 1563 respondents. The variables considered were psycho social determinants related to depression CES-D8 scale i.e. sleeplessness, loneliness, sadness, happiness, motivation and effort that will help to understand the emotional and mental health status of the sample population. Below are the results obtained from the analysis methods used We had to first test the chosen variables ie fltlnl, slprl, fltsd, fltsd, wrhpp, cldgng, and flteeff from the database for reliability and the Cronbach’s alpha value was 0.714 which indicates acceptable internal consistency for the CES-D8 depression scale. The table below shows the descriptive statistics summarizing the distribution of the depression-dependent variable with its interpretation.
Min (Minimum) 7.00 The lowest depression score in the dataset is 7. 1st Quartile (Q1) 9.00 25% of the participants scored ≤ 9 on the depression scale. Median (Q2) 10.00 The middle value in the dataset (50% of participants scored ≤ 10). Mean (Average) 10.78 The average depression score is 10.78. 3rd Quartile (Q3) 12.00 75% of participants scored ≤ 12 on the depression scale. Max (Maximum) 28.00 The highest depression score in the dataset is 28. NA’s (Missing Values) 18 There are 18 missing values in the dataset.
| Item | None or almost none of the time | Some of the time | Most of the time | All or almost all of the time |
|---|---|---|---|---|
| fltdpr | 82.500000 | 15.00000 | 1.730769 | 0.7692308 |
| enjlf | 3.727506 | 21.97943 | 52.120823 | 22.1722365 |
| slprl | 42.233633 | 46.40565 | 7.894737 | 3.4659820 |
| wrhpp | 3.848621 | 23.28416 | 58.370750 | 14.4964721 |
| fltlnl | 78.745199 | 17.15749 | 2.816901 | 1.2804097 |
| fltsd | 69.186419 | 28.63549 | 1.729661 | 0.4484305 |
| flteeff | 59.858703 | 32.56262 | 5.587669 | 1.9910083 |
| cldgng | 50.965251 | 40.92664 | 6.177606 | 1.9305019 |
## fltdpr_num enjlf_num slprl_num wrhpp_num fltlnl_num fltsd_num
## fltdpr_num 1.0000000 0.3840703 0.2261975 0.3879171 0.4137524 0.4205361
## enjlf_num 0.3840703 1.0000000 0.1913690 0.6298359 0.3139027 0.2978691
## slprl_num 0.2261975 0.1913690 1.0000000 0.1606253 0.1263291 0.2053358
## wrhpp_num 0.3879171 0.6298359 0.1606253 1.0000000 0.3292103 0.2962833
## fltlnl_num 0.4137524 0.3139027 0.1263291 0.3292103 1.0000000 0.3075620
## fltsd_num 0.4205361 0.2978691 0.2053358 0.2962833 0.3075620 1.0000000
## flteeff_num 0.4505025 0.3237889 0.2560539 0.2848652 0.2879390 0.2866340
## cldgng_num 0.2839383 0.2462121 0.2043640 0.2336577 0.2025135 0.1718811
## flteeff_num cldgng_num
## fltdpr_num 0.4505025 0.2839383
## enjlf_num 0.3237889 0.2462121
## slprl_num 0.2560539 0.2043640
## wrhpp_num 0.2848652 0.2336577
## fltlnl_num 0.2879390 0.2025135
## fltsd_num 0.2866340 0.1718811
## flteeff_num 1.0000000 0.4093484
## cldgng_num 0.4093484 1.0000000##
## Call:
## lm(formula = DataFI$CES_D8 ~ fltdpr + enjlf + slprl + wrhpp +
## fltlnl + fltsd + cldgng + flteeff, data = DataFI)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.051e-12 -1.770e-15 3.200e-16 2.780e-15 3.815e-13
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.400e+01 7.580e-15 1.847e+15 <2e-16
## fltdprSome of the time 1.000e+00 3.514e-15 2.846e+14 <2e-16
## fltdprMost of the time 2.000e+00 9.907e-15 2.019e+14 <2e-16
## fltdprAll or almost all of the time 3.000e+00 1.345e-14 2.231e+14 <2e-16
## enjlfSome of the time -1.000e+00 7.121e-15 -1.404e+14 <2e-16
## enjlfMost of the time -2.000e+00 7.376e-15 -2.711e+14 <2e-16
## enjlfAll or almost all of the time -3.000e+00 7.762e-15 -3.865e+14 <2e-16
## slprlSome of the time 1.000e+00 2.312e-15 4.325e+14 <2e-16
## slprlMost of the time 2.000e+00 4.272e-15 4.682e+14 <2e-16
## slprlAll or almost all of the time 3.000e+00 6.466e-15 4.639e+14 <2e-16
## wrhppSome of the time -1.000e+00 6.935e-15 -1.442e+14 <2e-16
## wrhppMost of the time -2.000e+00 7.219e-15 -2.771e+14 <2e-16
## wrhppAll or almost all of the time -3.000e+00 7.825e-15 -3.834e+14 <2e-16
## fltlnlSome of the time 1.000e+00 3.063e-15 3.265e+14 <2e-16
## fltlnlMost of the time 2.000e+00 7.297e-15 2.741e+14 <2e-16
## fltlnlAll or almost all of the time 3.000e+00 1.044e-14 2.874e+14 <2e-16
## fltsdSome of the time 1.000e+00 2.626e-15 3.808e+14 <2e-16
## fltsdMost of the time 2.000e+00 9.099e-15 2.198e+14 <2e-16
## fltsdAll or almost all of the time 3.000e+00 1.642e-14 1.827e+14 <2e-16
## cldgngSome of the time 1.000e+00 2.337e-15 4.279e+14 <2e-16
## cldgngMost of the time 2.000e+00 5.012e-15 3.990e+14 <2e-16
## cldgngAll or almost all of the time 3.000e+00 8.705e-15 3.446e+14 <2e-16
## flteeffSome of the time 1.000e+00 2.529e-15 3.954e+14 <2e-16
## flteeffMost of the time 2.000e+00 5.432e-15 3.682e+14 <2e-16
## flteeffAll or almost all of the time 3.000e+00 8.967e-15 3.346e+14 <2e-16
##
## (Intercept) ***
## fltdprSome of the time ***
## fltdprMost of the time ***
## fltdprAll or almost all of the time ***
## enjlfSome of the time ***
## enjlfMost of the time ***
## enjlfAll or almost all of the time ***
## slprlSome of the time ***
## slprlMost of the time ***
## slprlAll or almost all of the time ***
## wrhppSome of the time ***
## wrhppMost of the time ***
## wrhppAll or almost all of the time ***
## fltlnlSome of the time ***
## fltlnlMost of the time ***
## fltlnlAll or almost all of the time ***
## fltsdSome of the time ***
## fltsdMost of the time ***
## fltsdAll or almost all of the time ***
## cldgngSome of the time ***
## cldgngMost of the time ***
## cldgngAll or almost all of the time ***
## flteeffSome of the time ***
## flteeffMost of the time ***
## flteeffAll or almost all of the time ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4.174e-14 on 1516 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 1, Adjusted R-squared: 1
## F-statistic: 3.807e+29 on 24 and 1516 DF, p-value: < 2.2e-16##
## Call:
## lm(formula = CES_D8 ~ fltdpr_num + enjlf_num + slprl_num + fltsd_num +
## fltlnl_num + cldgng_num + flteeff_num, data = DataFI)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.13736 -0.25381 -0.02128 0.38952 2.08524
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.63189 0.05549 11.39 <2e-16 ***
## fltdpr_num 1.15642 0.03488 33.15 <2e-16 ***
## enjlf_num 1.49457 0.02027 73.73 <2e-16 ***
## slprl_num 1.00177 0.01935 51.76 <2e-16 ***
## fltsd_num 1.07435 0.02914 36.87 <2e-16 ***
## fltlnl_num 1.11412 0.02748 40.53 <2e-16 ***
## cldgng_num 1.04317 0.02202 47.37 <2e-16 ***
## flteeff_num 1.00433 0.02401 41.83 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5357 on 1533 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.9724, Adjusted R-squared: 0.9722
## F-statistic: 7709 on 7 and 1533 DF, p-value: < 2.2e-16