Correlation Between Symptoms of Depression and Obesity in Caregivers of Patients With Chronic Illness: A Gender Difference Analysis

Abstract

This study involved gender-stratified analysis and total-sample analysis to assess the extent to which symptoms of depression correlate with the body mass index (BMI) of a population of 112 people responsible for caring for others diagnosed with a chronic illness. The majority of the participants (caregivers) of this study were female (57.1%). All participants were recruited from an urban medical city hospital. The Patient Health Questionnaire-9 (PHQ-9) was employed to assess the extent to which caregivers exhibited symptoms of depression, and BMI was calculated by the researcher using the subject’s height and weight. Regressions were executed on the entire dataset spanning male and female participants to generate insights into demographic factors, after which the PHQ-9 was administered. After taking into account the possible confounding factors, the findings of the regression showed that there was a significant correlation between the BMI and PHQ-9 scores (β = .25, P = .042). The correlation between BMI and PHQ-9 persisted among females (β = .37, P = .023). Furthermore, there is a noteworthy correlation among the participants who were morbidly obese (BMI > 30 kg/m²). The correlation between BMI and PHQ-9 caregivers of patients with chronic illness remained after taking demographic factors into account. These findings could be utilized to enhance the outcomes for caregivers of patients with chronic illness. They may be particularly pertinent for caregivers who are experiencing depression or are overweight.

Keywords

gender obesity depressive symptoms body mass index

What do we already know about this topic?

Depression and obesity raise the risk of many diseases and mortality, and they also cause a variety of health problems.

How does your research contribute to the field?

The findings will help researchers develop a more in-depth comprehension of the intricate correlations between obesity, gender, and depression in the caregiver community.

What are your research’s implications toward theory, practice, or policy?

We hope to provide more detailed care for people who are responsible for providing care to people with chronic illnesses in Saudi Arabia.

Introduction

Depression remains a fundamental form of disability worldwide^1,2 and has significant economic consequences due to its impact on healthcare service resources and productivity.^3,4 According to the worldwide prevalence rates, depression has a 12-month prevalence of 4.9% and a lifetime prevalence of 3.6% in Saudi Arabia.⁵ This is in line with international prevalence rates. From the perspective of years of living with chronic illness, the impact of depression on the Saudi population increased by 4.3% between 1990 and 2019. Furthermore, depression remains among the 10 causes of chronic illness in Saudi Arabia,⁵ and the prevalence of the disability increased between 1990 and 2019. Caregiving for family members with chronic illness, which is common in Saudi Arabia, has been associated with depression rates ranging from 53% to 73%.^6
-8

Research has found that obesity is associated with a range of chronic illnesses, including musculoskeletal ailments and cardiac diseases.⁹ Obesity has been linked to a lower quality of life, including a shorter expected lifespan across caregiver samples.^10,11 Along with the higher expenditures associated with the increase in consumption of healthcare services, obesity has been linked to high levels of unemployment, poor work attendance, and low productivity. Consequently, it represents a significant burden on the economy.^12,13 In Saudi Arabia, 58.4% of the population is overweight or obese. This is among the most significant combined prevalences of obesity worldwide.¹⁴ Additionally, the prevalence rates of excessive weight are higher in a population of caregivers responsible for patients with chronic illnesses. This is markedly the case for caregivers of patients in nursing homes. An estimated 40% of caregivers assist adults who are classified as obese.¹⁵

Research has found a correlation between obesity and depression.¹⁶ Several authors have referred to the co-occurring conditions of obesity and depression as an epidemic.¹⁷ However, the conclusions presented in previous research are inconsistent. For example, some studies have indicated that obesity is related to higher levels of depressive symptoms,^18,19 while others have reported no correlation between obesity and depression,^20,21 and others still have reported that obesity is linked to a lower level of depressive symptoms.^22,23 One meta-analysis of numerous prior studies that were performed in the community found a significant correlation between obesity and depression, with a ratio of 1.18.²⁴ Most studies have determined a more significant connection between depression and obesity in women and those with lower educational attainment than in men with higher educational levels.^25,26 Gender-based research is essential because gender considerations may mitigate the correlation between depression and obesity. For instance, research has suggested that a stronger link exists between depression and obesity among white females than among non-white females.^27
-29 By contrast, alternative research has revealed a stronger correlation between obesity and depression among men.³⁰

Another set of researchers found no gender-specific variations in the correlation between obesity and depression.^31,32 These contradictory findings suggest the need for further research into the gender disparities evident within the correlation between depression and obesity among caregivers. Developing informed insights into gender differences—along with elucidating the possibility of prognostic distinctions in the correlation evident between symptoms of depression and obesity in a population of caregivers—may help to explain gender-based differences in prognosis and facilitate the identification of subgroups of caregivers who are at a higher of demonstrating adverse outcomes.

It is important to recognize that caregiving responsibilities encompass a range of activities involving individuals with serious medical conditions. These activities include tasks such as (a) assisting with acts of daily living and movement between a chair and bed; (b) transport, cooking meals, purchasing food and other supplies, cleaning, ensuring adherence to prescriptions, and coordinating external services; (c) making crucial treatment decisions for the individual; and (d) overseeing the financial aspects of their care.^33,34 Caregivers of individuals with chronic diseases shoulder a substantial emotional and financial responsibility that surpasses the general population’s experiences. Caregivers of individuals with chronic illnesses often experience higher levels of depression and exhibit elevated BMI scores compared to those who do not have caregiving responsibilities.^33,35

Furthermore, it’s important to note that unpaid caregivers are predominantly women who typically invest significantly more time, ranging from 2 to 10 times more, in unpaid care work compared to men.³⁶ In addition, caregiver depression serves as a critical indicator of various caregiving-related issues. A longitudinal study focusing on caregivers revealed a significant association between caregiver depression symptoms and unmet caregiving needs. These needs encompass a lack of adequate prescription management, failure to attend medical appointments, instances of abuse, and the failure to notice major declines in the care recipient’s condition that require immediate medical attention.³⁷ Consequently, caregivers experiencing depression may inadvertently induce similar adverse effects in the individuals under their care. Conversely, caregivers who are not affected by depression tend to provide more effective care.³⁷

To develop a more comprehensive understanding of the intricate relationships among obesity, gender, and depression in the caregiver population, we analyzed the entire sample—including analyses stratified by caregivers’ gender—to ascertain the extent to which depressive symptoms correlate with BMI. Our underlying hypothesis was that our findings would be aligned with those of previous studies that have found female caregivers of people with disabilities experience a higher frequency of depressive symptoms than men.^38,39 However, as we did not have any prior studies supporting gender variations in the correlation between BMI and depressive symptoms, we did not posit any a priori hypothesis in this regard.

Methods

Study Design and Participants

Before the completion of the questionnaire (online), each respondent provided their informed consent by signing an electronic consent form. The Institutional Review Board of King Saud University Medical City approved the research project (Ref. No. 21/01144/IRB). The participants in the study consisted of people who cared for family members who received treatment for kidney disease, eye disorders, cancer, or cardiovascular illnesses in the past or present.

A convenience sample of caregiver participants was selected by a nurse who reveiwed cases of chronically ill patients being treated at the Medical City. Caregivers whose assigned pateinet was diagnosded with chronic illnesses were invited to take part in the study by the nurse. Caregivers could consist of a partner, companion, or member of the family staying in the hospital with the patient. Caregivers who had any of the following conditions were excluded from the study: (1) cognitive problems that hindered their understanding of the consent form and questionnaire responses; (2) a major psychiatric condition, such as psychosis; and (3) medical contraindications that would affect their ability to participate in the study.

A cross-sectional survey was administered to Saudi caregivers (as defined above) between February and October 2022, during which the COVID-19 pandemic impacted the nation. As a result of the outbreak, the Google Forms online platform was employed to collect data instead of in-person interviews. Immediately after consenting and completing the survey a trained medical staff took the caregiver to the nursing station where the weight and height were recorded, after removing the shoes.

A minimum sample size of 97 was required for the multiple regressions based on the previously described effect size of 0.39.⁴⁰ Effect sizes of 0.15, 0.39, and 0.59 are conventionally considered small, medium, and large, respectively. To achieve the minimum level of statistical power of 0.8, the model included 6 variables and required a statistical significance of ≤0.05.

Depression

The Arabic translation of the Patient Health Questionnaire-9 (PHQ-9), a tool that has been successfully utilized in previous studies involving the Saudi population,⁴¹ is a self-reported, single-construct, and reliable questionnaire employed to assess depression severity over the most recent 2 weeks.⁴² The PHQ-9 includes 9 questions designed to evaluate the following symptoms of depression: (1) anhedonia, (2) depressed mood, (3) sleep difficulties, (4) fatigue, (5) changes in appetite, (6) low self-esteem, (7) difficulties concentrating, (8) psychomotor retardation/agitation, and (9) suicidal ideation. The participants are required to rate the items as follows: 0 for never, 1 for more than 1 day a week, 2 for more than half the days in a week, and 3 for almost every day. The cumulative responses to the questions were employed as a continuous score to indicate depression symptom severity, with elevated scores indicating higher overall levels of depressive symptoms. The PHQ-9 has been proven to offer a high level of validity and reliability across all Saudi populations facing depression.^41,42 Additionally, a score of 5, 10, 15, or 20 corresponds to mild, moderate, fairly severe, and severe levels of depression symptoms.⁴²

Body Mass Index

The participants’ height and weight were measured by appropriately trained staff to determine their BMI. We categorized BMI according to the following weight categories: underweight (BMI 18.49) (excluded from regression analyses), normal weight (BMI = 18.5-24.9), overweight (BMI = 25-29.9), and obese (BMI > 30). These weight categories were calculated based on the thresholds established by the World Health Organization (WHO).⁴³

Covariates

Covariates comprised age (measured continuously), gender (0 = Women, 1 = Men), social status (0 = unmarried, 1 = married), educational attainment (0 =less than or equal to high school, 1 = at least some post-secondary education or higher), and employment status (0 = employed, 1 = not employed).

Statistical Analyses

Both continuous variables and categorical variables were examined in the current study. Differences in responses between male and female caregivers were compared. Independent t-tests were employed to assess continuous variables, while chi-square analysis was performed for the categorical variables. Multiple linear regression analyses were conducted on the entire sample and on men and women separately to investigate the relationships between depression symptoms and BMI. Each primary analysis used continuous BMI as the dependent variable throughout the process. First, participants provided demographic information, including age, social status, educational status, and work status. Subsequently, they completed the PHQ-9 questionnaire to assess their depression level. In the analysis, gender was treated as a covariate in Step 1. If continuous BMI was found to be related to depressive symptoms in a gender-stratified regression model, an ANCOVA was used to assess the level of depressive symptoms across BMI categories for each gender. The same confounding factors were controlled as those employed for the regression models. IBM SPSS Version 28.0 (IBM Corporation) was used to perform all analyses. P-values exceeding 0.05 were deemed to be of statistical significance.

Results

Gender-Based Variations in Demographic and Medical Factors

Table 1 indicates that approximately 34.8% of the sample were of a healthy weight, while 65.2% were either overweight or obese. In terms of patient diagnoses, 48.2% of chronic patients receiving care from a caregiver are suffering from eye disorders, 22.3% suffer from kidney disease, 17% suffer from cardiovascular, and 12.5% suffer from cancer. The chi-square analysis (χ²) revealed no variation in the proportion of people in each BMI group based on gender; the value for χ² (2, N = 112) was 2.51, and the significance level was .285. Therefore, the likelihood of a person being classified as having normal weight, overweight, or obese was comparable among men and women. Consistent with prior studies’ findings, the current study found no significant gender differences in continuous BMI (P = .115). In terms of the severity of depression symptoms, the depressive symptom levels of the full sample fell below the subclinical range (a PHQ-9 score of 5 or lower).⁴¹ In the independent t-tests, women exhibited elevated PHQ-9 scores (t[110] =2.58, P = .011), indicating that they were exhibiting mild depressive symptoms (PHQ-9 score < 5), than men, who exhibited minimum depression (PHQ-9 score < 3). Women also exhibited a lower likelihood of being employed than men (χ²[1, N = 112] =18.58, P < .001). No significant differences were found between the genders concerning age (P = .760), social status (P = .587), or educational attainment (P = .321).

Table 1.

Characteristics of Participants.

	Total sample (N = 112)	Males (N = 48)	Females (N = 64)
Demographic factors
Age	36.9 ± 10.3	36.5 ± 10.3	37.1 ± 10.3
Female	64 (57.1)	-	-
Married	80 (71.4)	33 (68.8)	47 (73.4)
less or equal to high school	36 (32.1)	13 (27.1)	23 (35.9)
Employed	65 (58)	39 (91.3)	26 (40.6)^a
BMI category
Normal Weight (BMI 18.5-24.9 kg/m²)	39 (34.8)	19 (39.6)	20 (31.3)
Overweight (BMI 25.0-29.9 kg/m²)	41 (36.6)	19 (39.6)	22 (34.4)
Obese (BMI ≥ 30 kg/m²)	32 (28.6)	20.8 (20.8)	22 (34.4)
BMI (kg/m²)	27.6 ± 4.7	26.8 ± 4.2	28.2 ± 4.9
PHQ-9	3.9 ± 3.7	2.9 ± 3.3	4.6 ± 3.8^a

Note. Continuous variables represented with mean ± SD. Categorical variables represented with N (%).

BMI = body mass index; PHQ-9 = Patient Health Questionnaire-9.

P < .05 for independent t-test or chi-square test, indicating differences between males and females.

Correlation Between Symptoms of Depression and BMI

Total sample: After controlling for potential confounding factors, the regression analysis results for the entire sample indicated a significant positive correlation between PHQ-9 scores and BMI (β = .25, P = .042). Specifically, for every one-unit increase in PHQ-9 score, the BMI increased by 0.25 units on average (Table 2). Beyond age, gender, social status, educational background, and employment status, the inclusion of PHQ-9 scores contributed an extra 3% to the variability in BMI. The overall model elucidated 12% of the BMI variation. Importantly, this rise in variability was both statistically significant and distinct from the influence of age, gender, social status, and employment status. In Step 2, none of the variables (including age, gender, social position, education level, or work status) were significantly associated with BMI (all ps > 0.05).

Table 2.

Regressions of PHQ-9 Depression Scale Predicting Body Mass Index.

	Total sample (N = 112)				Males (N = 48)				Females (N = 64)
	β	R ²	ΔR²	ΔF	β	R ²	ΔR²	ΔF	β	R ²	ΔR²	ΔF
Step 1	-	.09	-	2.18	-	.09	-	1.10	-	.09	-	1.47
Gender	−.61				-				-
Age	.02				.01				.01
Social status	2.2				1.15				3.04^*
Education	−1.1				−2.52				.07
Employment	1.51				1.03				2.01
Step 2	-	.12	.03	4.25^*	-	.10	.01	.24	-	.17	.08	5.45
PHQ-9	.25^*				.10				.37^*

PHQ-9 = Patient Health Questionnaire-9.

P < .05.

Men: The regression analysis on the male members of the population revealed the correlation between BMI and PHQ-9 continued to be insignificant, with a value of β = .10 and a P-value of .621 (Table 2). The inclusion of PHQ-9 in the model accounted for an additional 1% of the variance in BMI, and none of the other factors had a significant relationship with BMI when PHQ-9 was included in the model (all P values were above .156). The overall model explained 10% of the variance in BMI.

An ANCOVA was performed across all BMI categories for men to assess the correlation between PHQ-9 and BMI. As the omnibus test did not provide statistically significant results (F[2, 41] =0.527, P = .594, η² =.02), pairwise comparisons were not reported.

Women: The regressions revealed that the link between the BMI and PHQ-9 remained the same among women, with a value of β = .37 and a significance level of P = .023 (Table 2), and the PHQ-9 was responsible for 8% of the variation in BMI. When PHQ-9 was included in the framework, social status was connected with BMI (β = 3.04, P = .030), whereas none of the other variables were related to BMI (all P values were greater than.267). The model explained 17% of the overall variation in BMI when considered as a whole.

As the PHQ-9 exhibited a correlation with BMI among members of the female population, an ANCOVA was performed to ascertain the extent to which the average levels of depression symptoms varied according to the BMI category. The ANCOVA omnibus test did not indicate any significance after adjusting for the same variables as the regression models (F[2, 57] =2.86, P = .065, η² = 0.091), so we did not perform any pairwise comparisons.

Discussion

The objective of the current was to investigate the correlation between depressive symptoms and obesity among a population of caregivers of patients with chronic illnesses. After considering demographic factors, we found a correlation between the severity of depressive symptoms and BMI across the entire sample. Women scored 45% higher on the PHQ-9 than men, which supported our hypothesis that female caregivers of disabled patients would report more severe depression symptoms than male caregivers. After performing a gender-specific analysis, we discovered that an elevated PHQ-9 score correlated with a higher BMI among members of the female population.

The findings of prior studies of the association between obesity and depression in caregivers of patients with dementia support our finding that obese caregivers exhibit a higher severity of depressive symptoms than their counterparts with a lower BMI.⁴⁴ Notably, the overall mean depressive symptoms for the entire population was in the subclinical range (score of or lower). However, our findings support the hypothesis that female caregivers experience a higher severity of depressive symptoms than male caregivers.^44,45 Additionally, the obesity rates observed in our sample were similar to those reported in previous estimates of obesity among caregiver populations.¹⁵

This study contributes to the existing body of research by presenting analyses not performed in previous studies. Specifically, we analyzed gender-based variations in the correlation between obesity and depression among caregivers of patients with chronic illnesses. We found that the level of depressive symptoms in women is correlated with their BMI and that morbidly obese carers are more likely to experience depression than their counterparts of a healthy weight. Therefore, the severity of an obese condition may serve to moderate the link between obesity and depression in women, with higher classes indicating the most serious cases of depression.

The reported findings have consequences for both clinical practice and scientific research. First, these findings are particularly significant because they imply that obesity is connected with relatively serious cases of depression. Second, our findings suggest that caregivers of inpatients and outpatients should be screened and monitored for signs of depression, particularly if the caregivers are overweight. Medical professionals should perform this monitoring process. Those falling in a higher BMI class (eg, those who are obese and have a BMI of more than 30) may experience the most emotional discomfort and benefit from early-stage depression screening and intervention. Even moderate depression symptoms (eg, a PHQ score of 5-9) without a formal diagnosis of severe depression require tracking and possible intervention.⁴² This aligns with the recommendations resulting from previous studies. Third, researchers could conduct studies elucidating how obesity affects depression treatment in caregivers or vice versa, in addition to how these characteristics function together to affect caregivers’ ability to self-manage their caregiving responsibilities. In conclusion, investigating whether a third component contributes to the worsening of both obesity and depression in the caregiving population is crucial. For instance, a predisposing genotype or a gene-by-environment dynamic may precipitate the correlation between obesity and depression. The hypothalamic–pituitary–adrenal axis’ dysregulation, which increases cortisol release, may also influence the association.^46,47 The likelihood that a single component is responsible for causing this observed association is low; nevertheless, strong pathways that substantially interact to precipitate a correlation between obesity and depression may exist. These pathways may reflect physiological, genetic, or behavioral processes.

The current study has some limitations that are worth exploring. The study’s cross-sectional nature entailed that it was not possible to assess the directionality of the association between obesity and depression among caregivers of patients with disabilities. As obesity and depression have been found to have bidirectional interactions,³¹ future research should investigate whether excessive adiposity in caregivers is a predictor or a consequence of depression in both men and women. In addition, there is a need for further research to explore the legitimacy of the “obesity paradox”⁴⁸ and provide further insight into how obesity can affect consequences such as healthcare utilization and mortality among caregivers. In our study, we focused on depression but did not explore other forms of psychopathology. For instance, we did not investigate whether BMI is associated with other disorders that are linked with both depression and obesity.⁴⁶ Additionally, it’s worth noting that certain characteristics of our sample may restrict the generalizability of our findings. For instance, our sample primarily consisted of Saudi caregivers who were predominantly married and possessed at least some post-secondary education or higher qualifications. To establish the broader applicability of our results, future studies should encompass more diverse samples, including caregivers residing outside of Saudi Arabia and individuals with varying levels of education. This would help confirm whether our findings hold across different populations.

Conclusion

This study contributes to the existing research by examining the correlation between BMI and depression symptoms in people responsible for caring for patients with chronic illness, even after accounting for demographic factors. Moreover, it explores gender differences in this association and finds that depression is correlated with BMI among women, particularly among those who are morbidly obese. Understanding the factors related to depressive symptoms in caregivers has important implications for clinical treatment; for example, early intervention can prevent negative health outcomes. Further research is needed to investigate 2 specific areas: 1) The directionality of the correlation between obesity and depression in caregivers and 2) outcomes such as hospitalization and mortality. By improving our understanding of the relationships among depression, obesity, and caregiving, we may be able to improve the quality of life of caregivers and reduce hospitalizations and mortality rates.

Footnotes

Acknowledgements

The author of this study extends his appreciation to the Researchers Supporting Project Number (RSPD2023R880), King Saud University, Riyadh, Saudi Arabia.

Declaration of Conflicting Interests

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

Funding

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

Ethics Approval

The Institutional Review Board of King Saud Medical City approved the research project (Ref. No. 21/01144/IRB).

Consent

Informed consent was obtained from all individual participants included in the study.

ORCID iD

Salman M. Alreshidi

Data Sharing

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

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