Page 109 - IJPS-10-3

International Journal of
Population Studies Gender differences in mental health outcomes

health-related dependent variables; the ENTER method Table 1. Demographic characteristics and gender
was applied to come up with the appropriate model with distribution
proper assumptions. This method allowed for a MANCOVA Characteristics Males Females p‑value
(multivariate analysis of covariance) analysis and the N=238 N=265
calculation of the estimated marginal means for mental (100%) (100%)
health measures among men and women and among Marital status 0.114
subjects with and without declared domestic violence, Single 92 (38.8%) 97 (36.6%)
after adjustment over potential confounders, such as age, Married 139 (58.6%) 151 (57.0%)
marital status, education level, health coverage, chronic Widowed/Divorced 6 (2.5%) 17 (6.4%)
disease, having a family member with a chronic disease, Level of education 0.018
worrying for a family member with a chronic disease, Less than university 19 (8.0%) 39 (14.7%)
fear of not having access to chronic disease treatment, University degree 219 (92.0%) 226 (85.3%)
domestic violence, professional status, socioeconomic Dwelling region 0.671
status, APGAR family index, financial wellness scale, Beirut (capital) 39 (16.4%) 45 (17.0%)
and fear of COVID-19 scale. As for comparing groups Lebanon 110 (46.2%) 112 (42.3%)
35 (14.7%)
34 (12.8%)
South Lebanon
with or without declared domestic violence, the following Beqaa 19 (8.0%) 29 (10.9%)
potential confounders were used for adjustment: gender, North Lebanon 35 (14.7%) 45 (17.0%)
age, marital status, education level, health coverage, Household size 0.973
chronic disease, having a family member with a chronic <4 persons 77 (32.5%) 84 (31.8%)
disease, worrying for a family member with a chronic 4 persons 66 (27.8%) 70 (26.5%)
disease, fear of not having access to chronic disease 5 persons 56 (23.6%) 66 (25.0%)
treatment, professional status, socioeconomic status, 6 and more 38 (16.0%) 44 (16.7%)
APGAR family index, financial wellness scale, and fear of Number of dependent 0.357
COVID-19 scale. children
None 101 (42.6%) 105 (39.8%)
3. Results 1 child 16 (6.8%) 29 (11.0%)
2 children 66 (27.8%) 66 (25.0%)
3.1. Sociodemographic characteristics and gender 3 children or more 54 (22.8%) 64 (24.2%)
distribution Number of rooms 0.611
A total of 503 participants were included in our study, <5 rooms 79 (33.2%) 88 (33.3%)
5 rooms
70 (29.4%)
69 (26.1%)
with slightly more females (52.68%) than males (average 6 rooms 53 (22.3%) 56 (21.2%)
age 42.47 ± 14.06). The majority had a university degree. 7 rooms or more 36 (15.1%) 51 (19.3%)
However, males were significantly more educated (92% Alcohol consumption <0.001
vs. 85% university degree; p = 0.018); they reported more Previous 11 (4.6%) 3 (1.1%) 0.001
domestic violence than females (8.4% vs. 3.8%; p = 0.038). None 70 (29.4%) 127 (48.1%) Ref
Higher percentages of previous, occasional, and regular Occasional 30 (12.6%) 14 (5.3%) 0.001
cigarette and waterpipe smokers were found. Moreover, Regular 127 (53.4%) 120 (45.5%) <0.001
significantly more women (17%; p < 0.001) had never Cigarette smoking 0.059
worked, as compared to men (2.9%) (Table 1). Previous 11 (4.6%) 10 (3.8%)
None 145 (61.2%) 189 (71.1%)
3.2. Economic characteristics and gender Occasional 37 (15.6%) 23 (8.6%)
distribution Regular 44 (18.6%) 44 (16.5%)
Waterpipe smoking <0.001
The subjective assessment before COVID-19 did not Previous 22 (9.3%) 5 (1.9%) <0.001
significantly differ between males and females; however, None 153 (64.6%) 210 (79.2%) Ref
regarding the post-COVID-19 evaluation, more males Occasional 22 (9.3%) 11 (4.2%) 0.168
classified themselves in poorer classes than females. Regular 40 (16.9%) 39 (14.7%) 0.007
A further economic impact on males was thus noticed, Self-reported 0.031
although more males initially belonged to households domestic violence
Ref
with higher revenues. Overall, socioeconomic quartiles No violence reported 215 (90.7%) 247 (93.6%) 0.038
10 (3.8%)
20 (8.4%)
Violence reported
were equally distributed between males and females. There No answer given 2 (0.8%) 7 (2.7%) 0.188
were significantly more males with no health coverage
(Table 2). (Cont’d...)

Volume 10 Issue 3 (2024) 103 https://doi.org/10.36922/ijps.1985