Depression, anxiety and job dissatisfaction: consequences of economic hardship in a lower middle-income country

Abstract

Background

Mental health disorders remain underexplored among civil servants in Nigeria, a group exposed to economic hardship and family responsibilities. This study examined the association between socioeconomic, demographic, and lifestyle factors with anxiety, depression, and job satisfaction.

Methods

A cross-sectional online survey of 538 civil servants collected data on demographics, income, health status, dependents, and exercise frequency. Anxiety, depression and job satisfaction were assessed using GAD-7, PHQ-9, and MSQ, respectively. Multinomial regression models estimated adjusted odds ratios (aOR) with 95% confidence intervals (CI).

Results

Respondents had a mean age of 39 years and were predominantly male (72.7%) and married (79.6%). Hypertension prevalence was 15.0%. Anxiety was significantly reduced among those engaging in daily (aOR = 0.37; 95% CI:0.18–0.75; p = 0.006), weekly (aOR = 0.39; 95% CI:0.19–0.78; p = 0.008), or monthly exercise (aOR = 0.22; 95% CI:0.10–0.48; p < 0.001). Higher income was protective (>₦200,000/month: aOR = 0.11; 95% CI:0.04–0.34; p < 0.001), while large family burdens increased anxiety (6–10 dependents: aOR = 4.45; 95% CI:1.55–12.81; p = 0.006; >10 dependents: aOR = 7.43; 95% CI:2.28–24.24; p < 0.001). 

Depression was more likely among younger respondents (<30 years: aOR=4.15; 95% CI:1.24–13.90; p=0.021), those with hypertension (aOR=3.12; 95% CI:1.57–6.19; p=0.001), and low-income earners (<₦20,000: aOR=9.03; 95% CI:2.87–28.40; p<0.001).

Job dissatisfaction was associated with older age (31–40 years: aOR=2.01; 95% CI:1.14–3.57; p=0.017; >50 years: aOR=3.26; 95% CI:1.44–7.39; p=0.005), low income, and lack of regular exercise. Anxiety and depression showed strong comorbidity, with moderate depression (aOR=5.23; 95% CI:3.23–8.46; p<0.001) and severe depression (aOR=24.39; 95% CI:4.71–126.32; p<0.001) significantly elevating anxiety risk.

Conclusion

Mental health outcomes among Nigerian civil servants could be shaped by economic hardship, family burden, and lifestyle factors. Physical activity and higher income were protective, while low income, caregiving responsibilities, and hypertension increased risk. Integrated workplace and policy interventions are needed to address financial insecurity, support families, and promote healthy lifestyles.

Introduction

Mental health is an essential aspect of human health that impacts overall well-being, quality of life, productivity, and social connections. Mental health conditions include disorders, psychosocial disabilities, and other mental states marked by significant distress, functional impairment, or self-harm risk. Common conditions include depression, anxiety, bipolar disorder, and post-traumatic stress disorder (PTSD). According to the World Health Organization (WHO), adverse social, economic, geopolitical, and environmental factors—such as poverty, violence, inequality, and environmental degradation—can increase the risk of developing mental health conditions [1]. The global prevalence of mental disorders is increasing, leading to significant impacts on both society and healthcare systems [2]. Mental disorders significantly contribute to the global disease burden and are a major cause of disability around the world, representing a substantial share of years lived with disability. They rank among the top ten most prevalent diseases globally [3]; therefore, mental health is a significant global public health issue that has received considerable attention in developed countries. However, in many low- and middle-income countries, including Nigeria, mental health receives comparatively less attention, partly due to limited resources and competing health priorities. Studies have shown that economic hardship has been consistently linked to an increased risk of poor mental health [4]. However, the intersection of economic hardship, job satisfaction, and mental health remains underexplored. This may be partly due to the perception that these issues pose a comparatively lower public health burden than infectious diseases and maternal/child health conditions, which are associated with substantial morbidity and mortality [5, 6].

Economic hardship adversely affects mental health and encompasses various dimensions, including unemployment, low income, and financial stress [7]. Studies in the United States have demonstrated that financial stress is closely linked to higher levels of psychological distress, which aligns with social stress theory and suggests that socioeconomic disadvantages increase vulnerability to stressors and mental health issues [4]. A systematic review by Ryu and Fan (2022) further emphasized that financial stress could lead to negative mental health outcomes, including depression and anxiety [7]. During the COVID-19 pandemic, Velthorst (2020) reported that economic hardships significantly increased the prevalence of mental health complaints, with those facing financial difficulties reporting increased levels of anxiety, depression, and other mental health problems [8].

While economic hardship is a global phenomenon, its consequences are especially pronounced in low- and middle-income countries (LMICs), where fragile economies and limited social safety nets exacerbate the effects on individuals and households. To promote fiscal stability, the International Monetary Fund (IMF) has encouraged LMICs to adopt reforms aimed at strengthening revenue mobilization and improving economic resilience. In Nigeria, a lower-middle-income country, such reforms—including the partial removal of petrol subsidies and multiple currency devaluations—have inadvertently intensified poverty and food insecurity [9, 10]. These policies have fueled the continuous depreciation of the Naira, contributing to rising living costs. Inflation surged from 22.2% in 2023 to 34.2% in June 2024, while the official exchange rate averaged ₦1,652.50/US$ [11].

Despite a recent increase in the national minimum wage from ₦30,000.00 to ₦70,000.00, civil servants—whose livelihoods depend largely on fixed salaries—remain particularly vulnerable to these economic shocks [12]. The World Bank estimates that approximately 87 million Nigerians live below the international poverty line, placing the country among those with the largest populations in extreme poverty [13]. Wage stagnation, coupled with escalating commodity prices, has deepened poverty and heightened food insecurity. These socioeconomic adversities are not only eroding household welfare but are also likely to impose significant psychological burdens, with adverse implications for the mental health and job satisfaction of Nigerian civil servants.

Economic challenges not only affect mental health but may also influence how individuals perceive and engage with their work. Zhang et al. (2022) reported a strong correlation between mental health and job satisfaction, and its significant effect on workers’ performance and the overall efficiency of an organization [14]. Job satisfaction is commonly defined as an individual’s evaluative judgment about their job, encompassing both affective responses (positive or negative feelings) and cognitive assessments of various aspects of employment [15, 16]. Optimal psychological well-being has been shown to promote positive affective states and greater job satisfaction, whereas compromised mental health is associated with negative emotional experiences and reduced satisfaction in the workplace [17]. In light of the persistent economic challenges in Nigeria and their potential implications for mental health outcomes, including depression and anxiety disorders, this study aimed to assess the risk of depression, anxiety, and job dissatisfaction among civil servants in Nigeria. The findings are expected to contribute to a deeper understanding of the mental well-being of this workforce and to inform the development of targeted interventions and policies designed to mitigate the burden of depression, anxiety, and job dissatisfaction.

Materials and methods

Questionnaire design

A structured questionnaire was employed, comprising two validated health measurement instruments for depression (PHQ-9) and anxiety (GAD-7), in addition to the Minnesota Job Satisfaction Questionnaire [18–20]. The PHQ-9 and GAD-7 are widely recognized and validated tools for the assessment of depression and anxiety, respectively, and have demonstrated strong psychometric properties across clinical and non-clinical populations, including patients, community health workers, and the general public [21, 22].

The study questionnaire was organized into three sections. Section 1 elicited sociodemographic characteristics, including age, sex, marital status, employment status, monthly income, and number of dependents. Section 2 included the PHQ-9 and GAD-7 instruments. The PHQ-9 consists of nine items with ordinal categorical responses (0 = not at all, 1 = several days, 2 = more than half the days, 3 = nearly every day). Total scores are used to classify depression severity as minimal (1–4), mild (5–9), moderate (10–14), moderately severe (15–19), and severe (20–27). The GAD-7 consists of seven items with response options identical to the PHQ-9. Anxiety severity is categorized as minimal (0–4), mild (5–9), moderate (10–14), and severe (15–21). Both tools are widely utilized in research and clinical practice to evaluate mental health status and symptom severity [18, 19].

Section 3 incorporated the Minnesota Job Satisfaction Questionnaire (MSQ), which has been extensively validated across occupational and cultural contexts, supporting its robustness as a measure of job satisfaction [20, 23, 24]. The MSQ comprises 20 items rated on a 5-point Likert scale (1 = very dissatisfied to 5 = very satisfied). The mean score for each participant was computed to determine overall job satisfaction.

Study design and data collection

The cross-sectional study was conducted between March and September 2024. Data collection extended over six months, largely due to a low initial response rate, which required the use of periodic reminders and repeated circulation of the survey link. The questionnaire was designed using Google Forms and disseminated through multiple online platforms, including email, WhatsApp, and Telegram. The choice of online distribution was guided by considerations of efficiency, cost-effectiveness, and the need to reach a geographically dispersed population within a limited timeframe.

Participation was restricted to civil servants employed at the federal, state, or local government levels. A purposive sampling strategy was employed, with distribution facilitated primarily through the authors’ professional networks. While this approach enhanced access to the target population, it may have introduced selection bias and constrained the generalizability of the findings. To maximize coverage, respondents were encouraged to further share the survey link within their networks.

A minimum sample size of 385 participants was targeted, based on the calculation for an infinite population at a 95% confidence level and a 5% margin of error [25]. This sample size is also considered adequate for populations exceeding one million [26].

Data analysis

The data obtained from the Google Form–based questionnaire were exported into Microsoft Excel for initial cleaning and subsequently imported into RStudio for statistical analysis. Participant responses were processed to derive measures of anxiety, depression, and job satisfaction. Demographic characteristics and survey responses were summarized using descriptive statistics and presented as frequencies and percentages. Associations between demographic variables and the outcome variables (anxiety, depression, and job satisfaction) were first assessed using univariable multinomial regression. Variables with a p-value < 0.25 were retained for inclusion in the multivariable multinomial regression model [27]. For each analysis, participants with missing data on the variable of interest were excluded; therefore, the analytic sample size varied across variables. All statistical analyses were conducted using R software (version 4.2.3), with statistical significance defined at the 5% level and 95% confidence intervals reported.

Results

Descriptive statistics of the respondents

A total of 538 Nigerian civil servants completed the survey. The mean age was 39 years (SD = 9.15), with 20.1% under 30 years, 38.2% aged 31–40 years, 29.5% aged 41–50 years, and 12.2% over 50 years. The sample was predominantly male (72.7%), and most participants were married (79.6%), with singles comprising 17.7%, divorced 2.3%, and widowed 0.4%. In terms of health status, 80.9% reported no chronic disease, 15.0% had hypertension, 1.1% had diabetes, and 3.0% reported both conditions.

Regarding lifestyle factors, 29.2% engaged in daily exercise, 36.3% weekly, 20.6% monthly, and 13.9% reported no exercise. Income distribution revealed that 34.2% earned above ₦200,000 ($121.03) monthly, 34.2% earned ₦101,000–200,000 ($61.12 - $121.03), 19.2% earned ₦51,000–100,000 ($30.86 - $61.12), 6.0% earned ₦20,000–50,000 ($12.10 - $30.26), and 6.4% earned less than ₦20,000 ($12.10). The number of dependents varied: 36.8% had 6–10 dependents, 34.6% had 3–5, 11.7% fewer than 3, 11.7% more than 10, and 5.3% had none (Table 1).

Table 1.

Sociodemographic characteristics of the respondents

Variable	Mean (SD)	Frequency	Percentage (%)
Age	39.1 (9.15)
Age group
Less than 30		102	20.1
31 to 40		194	38.2
41 to 50		150	29.5
Above 50		62	12.2
Gender
Female		144	27.3
Male		384	72.7
Marital status
Single		94	17.7
Married		422	79.6
Divorced		12	2.3
Widow/widower		2	0.4
Underlying health condition
None		432	80.9
High blood pressure		80	15
Diabetes		6	1.1
Both		16	3
Workout session
Never		74	13.9
Daily		156	29.2
Weekly		194	36.3
Monthly		110	20.6
Monthly Income
Less than N 20,000		34	6.4
N 20,000 - 50,000		32	6
N 51,000 - 100,000		102	19.2
N 101,000 - 200,000		182	34.2
Above N200,000		182	34.2
Number of dependants
None		28	5.3
Less than 3		62	11.7
3–5		184	34.6
6 to 10		196	36.8
Over 10		62	11.7

Mental health outcomes indicated that 51.3% experienced minimal to mild anxiety, 41.6% moderate anxiety, and 7.1% severe anxiety. Depression levels were minimal to mild in 66.5% of respondents, moderate in 20.1%, and severe in 13.4%. Regarding job satisfaction, 49.3% were undecided, 31.8% dissatisfied, and 19.0% satisfied (Table 2).

Table 2.

Distribution of the respondents based on different levels of anxiety, depression, and job satisfaction

Variable			Frequency		Percentage (%)
Anxiety (PHQ-9)
Minimum to Mild			276		51.3
Moderate			224		41.6
Severe			38		7.1
Depression (GAD-7)
Minimum to mild			358		66.5
Moderate			108		20.1
Severe			72		13.4
Job Satisfaction
Cannot decide			265		49.3
Dissatisfied			171		31.8
Satisfied			102		19

Multivariable regression analysis: anxiety

The model revealed a significant relationship between anxiety and the frequency of workout sessions, monthly income, and the number of dependents. The overall model was statistically significant, demonstrating that the predictors significantly improved model fit compared with the null model (χ² (42) = 113, p < 0.001; deviance = 753, AIC = 841, BIC = 1025; pseudo-R² = 0.131), explaining approximately 13.1% of the variation in the levels of anxiety (Table 3).

Table 3.

Multivariable regression analysis of the relationships between the demographic variables of the respondents with moderate versus minimum to mild anxiety

Predictor	Moderate (n)	Minimum to Mild (n)	p-value	aOR	95% CI
					Lower	Upper
Age category:
<=30 years	44	50	REF	1.0	NA	NA
31 to 40 years	92	96	0.752	1.127	0.536-	2.369
41 to 50 years	58	78	0.563	0.779	0.334	1.817
above 50 years	22	32	0.309	0.588	0.211	1.636
Gender:
Female	66	70	REF	1.0	NA	NA
Male	156	200	0.569	0.864	0.522	1.429
Marital status:
Single	42	46	REF	1.0	NA	NA
Divorced	6	6	0.296	2.260	0.490	10.433
Married	174	216	0.627	0.827	0.385	1.776
*Widow/widower	0	2
Underlying health condition:
None	174	230	REF	1.0	NA	NA
Both	8	8	0.979	1.018	0.280	3.700
Diabetes	4	2	0.160	3.643	0.600	22.123
High blood pressure	36	34	0.121	1.624	0.880	2.998
Workout session:
Never	38	26	REF	1.0	NA	NA
Daily	60	86	0.006	0.365	0.179	0.745
Monthly	38	68	< 0.001	0.222	0.104	0.476
Weekly	86	94	0.008	0.385	0.191	0.777
Monthly income:
Less than 20,000	22	8	REF	1.0	NA	NA
Above 200,000	62	112	< 0.001	0.109	0.035	0.339
100,000–200,000	72	98	0.003	0.189	0.064	0.564
20,000–50,000	16	14	0.089	0.339	0.098	1.178
51,000–100,000	50	40	0.095	0.391	0.130	1.177
Number of dependents:
Over 10	22	32	REF	1.0	NA	NA
6 to 10	92	88	0.044	1.982	1.018	3.858
3 to 5	74	98	0.397	0.740	0.368	1.487
Less than 3	22	38	0.034	0.363	0.142	0.929
None	8	20	0.008	0.175	0.048	0.628

Model fit measures: Deviance = 753, AIC = 841, BIC = 1025, R² = 0.131 (χ² (42) = 113, p < 0.001)

REF Reference Category, NA Not Applicable, aOR Adjusted Odds Ratio, n number

*Predictor category removed from the model owing to zero count in one level of the outcome variable

Daily exercisers had 64% lower odds of moderate anxiety compared to non-exercisers (aOR = 0.365; 95% CI: 0.179–0.745; p = 0.006). Weekly exercisers also had reduced odds of moderate anxiety (aOR = 0.385; 95% CI: 0.191–0.777; p = 0.008), indicating roughly 62% lower odds, while monthly exercisers showed the largest protective effect against moderate anxiety (aOR = 0.222; 95% CI: 0.104–0.476; p < 0.001), suggesting nearly 78% lower odds.

Income showed a protective effect, with respondents earning more than ₦200,000 having 89% lower odds of moderate anxiety (aOR = 0.109; 95% CI: 0.035–0.339; p < 0.001), and those earning ₦101,000 – ₦200,000 demonstrating 81% lower odds (aOR = 0.189; 95% CI: 0.064–0.564; p = 0.003). However, the levels of anxiety amongst participants earning ₦20,000 - ₦50,000 (aOR = 0.339; 95% CI: 0.098–1.178; p = 0.089) and ₦51,000 - ₦100,000 (aOR = 0.391; 95% CI: 0.130–1.177; p = 0.095) were not statistically different from the lowest earners.

The number of dependents was positively associated with anxiety; participants with more than 10 dependents had over sevenfold higher odds (aOR = 7.43; 95% CI: 2.28–24.24; p < 0.001), while those with 6 to 10 dependents had over fourfold higher odds (aOR = 4.45; 95% CI: 1.55–12.81; p = 0.006). The anxiety levels were not significantly different among participants with no dependents (aOR = 2.09; 95% CI: 0.67–6.56; p = 0.205) and those with between 3 and 5 dependents (aOR = 1.97; 95% CI: 0.73–5.28; p = 0.178). Age, sex, marital status, and underlying health conditions were not significantly associated with anxiety (Table 3).

Multivariable analysis: depression

The depression model was statistically significant (χ² (42) = 158, p < 0.001; deviance 694, AIC = 782, BIC = 966; pseudo-R² = 0.185), explaining approximately 18.5% of the variance in depression levels (Table 4).

Table 4.

Multivariable regression analysis of the relationships between the demographic variables of the respondents with moderate versus minimum to mild depression

Predictor	Moderate	Minimum to mild	p-value	aOR	95% CI
					Lower	Upper
Age category:
31 to 40 years	32	134	0.448	1.469	0.544	3.969
41 to 50 years	26	102	0.361	1.578	0.593	4.198
Less than 30 years	40	52	0.021	4.147	1.237	13.904
Above 50 years	10	42	REF	NA	NA	NA
Gender:
Male	78	256	0.798	1.085	0.580	2.028
Female	30	94	REF	NA	NA	NA
Marital status:
Divorced	2	10	0.715	1.424	0.214	9.499
Single	30	52	0.633	1.256	0.492	3.207
*Widow/widower	0	0
Married	74	290	REF	NA	NA	NA
Underlying health condition:
Both	4	12	0.237	2.500	0.548	11.402
Diabetes	0	6
High blood pressure	24	42	0.001	3.116	1.568	6.191
None	78	296	REF	NA	NA	NA
Workout session:
Daily	40	102	0.801	1.117	0.472	2.646
Monthly	20	78	0.311	0.608	0.232	1.592
Weekly	36	136	0.182	0.545	0.224	1.328
Never	12	38	REF	NA	NA	NA
Monthly income:
100,000–200,000	36	128	0.007	2.680	1.308	5.491
20,000–50,000	14	16	0.014	4.403	1.350	14.364
51,000–100,000	26	52	< 0.001	5.338	2.265	12.581
less than 20,000	14	18	< 0.001	9.026	2.868	28.404
Above 200,000	16	140	REF	NA	NA	NA
Number of dependents:
Less than 3	12	46	REF	NA	NA	NA
3 to 5	32	132	0.178	1.969	0.735	5.275
6 to 10	32	124	0.006	4.454	1.549	12.812
None	12	16	0.205	2.093	0.668	6.556
Over 10	16	38	< 0 0.001	7.432	2.279	24.240

Model fit measures: Deviance = 694, AIC = 782, BIC = 966, R² = 0.185 (χ² (42) = 158, p < 0.001)

REF Reference Category, NA Not Applicable, aOR Adjusted Odds Ratio

*Predictor category removed from the model owing to zero count in one level of the outcome variable

Participants under 30 years had over four times higher odds of moderate depression compared with those over 50 years (aOR = 4.15; 95% CI: 1.24–13.90; p = 0.021). However, the depression levels among other age groups (31–40 years: aOR = 1.47, 95% CI: 0.54–3.97; 41–50 years: aOR = 1.58, 95% CI: 0.59–4.20) were not significantly different.

Hypertension was also significantly associated with depression (aOR = 3.12; 95% CI: 1.57–6.19; p = 0.001), whereas diabetes combined with hypertension showed elevated but non-significant odds (aOR = 2.50; 95% CI: 0.55–11.40; p = 0.237).

Income remained a strong predictor; respondents earning less than ₦20,000 per month had the highest odds of moderate depression (aOR = 9.03; 95% CI: 2.87–28.40; p < 0.001), followed by those earning ₦51,000–100,000 (aOR = 5.34; 95% CI: 2.26–12.58; p < 0.001), ₦20,000–₦50,000 (aOR = 4.40; 95% CI: 1.35–14.36; p = 0.014), and ₦100,000 – ₦200,000 (aOR = 2.68; 95% CI: 1.31–5.49; p = 0.007).

The number of dependents also increases the risk of depression. Those with 6–10 dependents had over four times higher odds of moderate depression (aOR = 4.45; 95% CI: 1.55–12.81; p = 0.006), while participants with more than 10 dependents had the highest risk, with over seven times higher odds (aOR = 7.43; 95% CI: 2.28–24.24; p < 0.001). In contrast, the risk was not significantly different among participants with either three to five, fewer than three, or no dependents at all. Other demographic variables, including gender, marital status, and workouts, had no significant relationship with the level of depression among the respondents (Table 4).

Multivariable analysis: job satisfaction

The model for job satisfaction was significant (χ² (42) = 100, p < 0.001; deviance = 884; AIC = 972; BIC = 1156; pseudo-R² = 0.102), explaining approximately 10.2% of the variation in job satisfaction levels (Table 5). Age, income, and exercise frequency were significantly associated with dissatisfaction. Respondents aged 31–40 (aOR = 2.01; 95% CI: 1.14–3.57; p = 0.017) and those above 50 years (aOR = 3.26; 95% CI: 1.44–7.39; p = 0.005) were more likely to report dissatisfaction compared with those aged 41–50 years.

Table 5.

Multivariable regression analysis of the relationships between the demographic variables of the respondents with dissatisfied versus ‘can’t decide’ levels of job satisfaction

Predictor	Dissatisfied	Cannot decide	p-value	aOR	95%CI
					Lower	Upper
Age category
Less than 30	32	50	0.110	2.074	0.847	5.080
31 to 40	71	83	0.017	2.014	1.136	3.570
41 to 50	32	98	REF	NA	NA	NA
above 50	22	24	0.005	3.261	1.439	7.388
Gender
Male	122	194	0.749	1.093	0.634	1.884
Female	43	67	REF	NA	NA	NA
Marital status:
Married	134	210	0.681	1.483	0.227	9.674
Single	28	46	0.881	1.167	0.155	8.799
Widow/widower	2	0
Divorced	2	8	REF	NA	NA	NA
Underlying health condition:
Diabetes	2	2	0.475	2.808	0.166	47.611
High blood pressure	21	45	0.784	0.747	0.093	6.020
None	148	212	0.730	1.437	0.184	11.242
Both	4	4	REF	NA	NA	NA
Workout session:
Never	42	24	< 0 0.001	2.016	0.988	4.116
Monthly	30	54	0.054	5.479	2.599	11.550
Weekly	69	97	0.002	2.699	1.460	4.992
Daily	28	88	REF	NA	NA	NA
Monthly income:
Less than 20,000	9	17	0.699	1.259	0.392	4.047
20,000–50,000	10	16	0.145	2.370	0.743	7.554
51,000–100,000	36	56	0.253	1.502	0.748	3.017
100,000–200,000	66	82	0.045	1.798	1.012	3.195
Above 200,000	46	94	REF	NA	NA	NA
Number of dependents:
None	8	12	0.973	0.978	0.259	3.689
Less than 3	16	36	0.232	0.551	0.207	1.465
3 to 5	57	85	0.756	0.887	0.416	1.892
6 to 10	68	98	0.963	1.017	0.498	2.078
Over 10	20	32	REF	NA	NA	NA

Model fit measures: Deviance = 884, AIC = 972, BIC = 1156, R² = 0.102 (χ² (42) = 100, p < 0.001)

REF Reference Category, NA Not Applicable, aOR Adjusted Odds Ratio

*Predictor category removed from the model owing to zero count in one level of the outcome variable

Income of ₦101,000 – ₦200,000 was associated with higher dissatisfaction than greater than ₦200,000 (aOR = 1.80; 95% CI: 1.01–3.20; p = 0.045). Physical inactivity was strongly linked to dissatisfaction, with never-exercisers (aOR = 2.02, 95% CI: 0.99–4.12, p < 0.001), weekly exercisers (aOR = 2.70, 95% CI: 1.46–4.99, p = 0.002), and monthly exercisers (aOR = 5.48, 95% CI: 2.60–11.55, p = 0.054) showing higher odds. Sex, marital status, and number of dependents were not significantly associated with job satisfaction (Table 5).

Association between anxiety and depression

A strong relationship was observed between depression and anxiety (χ² = 210, df = 4, p < 0.001; deviance = 752; AIC = 764; BIC = 790; pseudo-R² = 0.219), indicating that approximately 21.9% of the variability in levels of anxiety is explained by depression. The pseudo-R² value is within the 0.2 and 0.4 range, generally regarded excellent fit [28, 29]. Respondents with moderate depression had over fivefold higher odds of moderate anxiety (aOR = 5.23; 95% CI: 3.23–8.46; p < 0.001), while severe depression was associated with more than twentyfold higher odds (aOR = 24.39; 95% CI: 4.71–126.32; p < 0.001) (Table 6).

Table 6.

Univariable regression analysis of the relationship between levels of depression and anxiety

Depression (GAD-7)	Predictor	p-value	OR	95%CI
				Lower	Upper
Moderate - Minimum to Mild	Anxiety (PHQ-9):
	Minimum to mild	Ref	NA	NA	NA
	Moderate	< 0.001	5.229	3.232	8.459
	Severe	< 0.001	24.394	4.711	126.320

Model fit measures: Deviance = 752, AIC = 764, BIC = 790, pseudo-R² = 0.219 (χ² = 210, df = 4, p < 0.001)

REF Reference Category, NA Not Applicable, OR Odds Ratio

Discussion

This study examined the determinants of anxiety, depression, and job satisfaction among Nigerian civil servants, with a focus on sociodemographic, health, and lifestyle factors. The levels of explained variance in the multivariable regression models are modest and consistent with values typically observed in social and behavioral phenomena, as earlier described [30].

The mean age of 39 years indicates a relatively mature workforce, with the largest proportion of respondents in the 31–40 age bracket (38.2%). The gender distribution, dominated by males (72.7%), is consistent with patterns frequently reported in Nigerian workforce surveys and may also reflect broader structural employment trends in the civil service, where male predominance has been documented [31]. Marital status was similarly aligned with national cultural norms, as the majority of respondents were married (79.6%). Regarding health status, most respondents (80.9%) reported no history of diabetes or hypertension, suggesting a generally healthy cohort. Nevertheless, 15% of participants reported high blood pressure, which may indicate the influence of psychosocial and economic stressors. Previous research in Nigeria has similarly demonstrated associations between socioeconomic adversity and hypertension prevalence [32].

The findings highlight a significant relationship between anxiety and both physical activity and economic status. Compared with inactive individuals, those engaging in daily or weekly exercise had substantially lower odds of experiencing moderate anxiety (64% and 62% reductions, respectively), with even irregular activity conferring notable benefits. These findings corroborate earlier Nigerian studies showing that physical activity enhances psychological well-being and reduces anxiety symptoms [33, 34]. The protective role of exercise may be mediated through physiological pathways, including modulation of the hypothalamic–pituitary–adrenal (HPA) axis, improved sleep, and greater social engagement, which collectively buffer against anxiety [35].

Economic hardship emerged as a critical determinant of both anxiety and depression. Respondents earning less than ₦200,000 per month exhibited higher susceptibility to moderate-to-severe symptoms, reflecting the well-documented association between financial stress, economic insecurity, and poor mental health outcomes [36–39]. Moreover, individuals with large family responsibilities were disproportionately affected: respondents with more than 10 dependents were more likely to report both anxiety and depression compared with those supporting fewer than three dependents. This finding aligns with prior Nigerian research, which has identified family size as a predictor of psychological distress, likely through pathways of financial strain and caregiving demands [40]. These observations underscore the intersection of economic burden, family structure, and mental health within the sociocultural context of Nigeria, where extended family obligations are common.

Age also influenced mental health outcomes, but in distinct ways. Unlike anxiety, depression was more prevalent among younger respondents (< 30 years), suggesting greater vulnerability among early-career individuals facing job insecurity, financial instability, and high social expectations [41]. Conversely, individuals over 50 years reported lower prevalence of moderate depression, possibly due to greater financial stability or career consolidation. Hypertension was positively associated with depression, reinforcing existing evidence on the bidirectional relationship between chronic illness and mental health [42]. This highlights the importance of integrated approaches to managing both physical and mental health conditions in populations at risk.

Job satisfaction patterns further reflected the interplay between socioeconomic and psychological factors. Nearly half of respondents (49.3%) were undecided about their job satisfaction, while only 19% reported satisfaction and 31.8% reported dissatisfaction. This ambivalence may reflect systemic occupational challenges in Nigeria, such as limited career progression, stagnant wages, and unsatisfactory working conditions. Multivariable analyses revealed that job satisfaction was significantly associated with age, income, exercise frequency, and family size. Respondents aged 31–40 years and those over 50 years were more likely to report dissatisfaction, mirroring the U-shaped distribution of job satisfaction across the life course documented in previous studies [43–45]. Financial strain—particularly among those earning below ₦200,000 per month or with extensive dependent responsibilities—was strongly associated with dissatisfaction, consistent with economic theories linking material deprivation to occupational well-being [46]. Additionally, physical inactivity was linked to lower job satisfaction, suggesting that exercise may not only buffer mental health challenges but also enhance occupational fulfillment and work–life balance [47].

Finally, the comorbidity between anxiety and depression was pronounced, with evidence of a dose–response relationship. Increasing severity of depression was strongly associated with the likelihood of concurrent anxiety, and the magnitude of these associations emphasizes the clinical and public health importance of addressing these conditions together. This observation is consistent with a large body of international literature on the high prevalence and burden of anxiety–depression comorbidity [48–50].

Overall, the findings underscore the multidimensional nature of mental health challenges among Nigerian civil servants. Economic hardship, family obligations, and occupational stressors intersect with individual lifestyle and health factors to shape psychological outcomes. Interventions aimed at improving financial security, promoting physical activity, and addressing both chronic physical and mental health conditions are therefore essential for fostering a healthier and more productive workforce.

Conclusion

This study demonstrates that mental health outcomes among Nigerian civil servants are strongly influenced by socioeconomic and lifestyle factors. Low income, economic hardship, and large family responsibilities were key predictors of anxiety, depression, and job dissatisfaction, while physical inactivity further exacerbated these outcomes. Younger respondents were more vulnerable to depression, whereas older individuals reported greater dissatisfaction, reflecting distinct age-related challenges. Hypertension was also associated with depression, underscoring the close link between physical and mental health. The strong comorbidity observed between anxiety and depression highlights the need for integrated approaches to mental health support. Overall, policies and strategies that enhance financial stability, promote regular physical activity, and address occupational challenges may play a critical role in improving well-being and productivity in this workforce.

Future research should employ longitudinal designs to clarify causal pathways between economic hardship, family obligations, and mental health. Comparative studies across sectors and regions could provide broader insights into occupational differences in mental health risks. Further, examining gender-specific vulnerabilities and incorporating physiological measures of stress would strengthen the evidence base. Finally, intervention studies testing workplace wellness programs, financial education, and family support initiatives could inform policy responses aimed at reducing the burden of anxiety and depression among Nigerian civil servants.

Limitation

This study is subject to some limitations. First, the use of a cross-sectional design restricts the ability to establish causal inferences between variables. Second, reliance on an online survey platform may have introduced selection bias, as participation was limited to individuals with internet access and adequate digital literacy, thereby potentially reducing the representativeness of the sample. Third, as responses to individual items were not mandatory, certain variables had incomplete responses, which could introduce response bias and limit the completeness of some analyses. Furthermore, the relatively high proportion of respondents (80.9%) who reported not having diabetes or hypertension may not accurately reflect the true prevalence of these conditions. This is particularly important given that hypertension often remains undiagnosed, especially among men and rural populations, until clinical symptoms emerge or the condition is detected during routine health checks [51, 52].

However, these limitations are unlikely to significantly influence the study’s results. The cross-sectional approach is appropriate for detecting associations, and the large, diverse sample helps mitigate potential selection bias from online recruitment. Missing responses were minimal and did not impact key variables, maintaining analytical validity. Lastly, while self-reported rates of hypertension and diabetes may be underestimated, focusing on associations rather than exact prevalence lessens the effect of this limitation.

Abbreviations

PTSD

Post-traumatic stress disorder

PHQ

Patient health questionnaire

GAD

Generalized anxiety disorder

MSQ

Minnesota Job Satisfaction Questionnaire

Authors’ contributions

Y.Y. conceptualized the study, analyzed the data, and wrote the first manuscript draft.M.D.M. collated the data and reviewed the draft manuscript.A.A.O., E.A.A., and V.F.O. cleaned the data and conducted preliminary data analysis.I.I. contributed to the literature review and part of the manuscript writing.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability

The dataset collected during this study is available in the Zenodo repository at DOI [10.5281/zenodo.17177576](https:/doi.org/10.5281/zenodo.17177576).

Declarations

Ethics approval and consent to participate

Informed consent was obtained from all participants, and the study adhered to the principles outlined in the Declaration of Helsinki for human and animal research. Ethical approval was granted by the Faculty Research Ethics Committee (FAREC) of Usmanu Danfodiyo University, Sokoto-Nigeria (UDUS/FAREC/2023/QS003/032).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.