Introduction: Attention deficit hyperactivity disorder (ADHD) is a little-studied psychiatric pathology in our countries, and particularly here in Benin. Objectives: To calculate the prevalence and identify the factors associated with attention deficit hyperactivity disorder among adults in the commune of Parakou in 2022. Methods: Cross-sectional, descriptive, analytical study including subjects aged 18 and over. ADHD was assessed with the Adult ADHD Self Report Scale (ARSR-v1.1) and consequences with the Weiss functional impairment rating scale (WFIRS-S). Results: A total of 456 people were included in the study. The mean age of those surveyed was 25.9 ± 11.6 years. The prevalence of ADHD symptoms among the adults surveyed was 6.8%. The clinical form of ADHD with a predominance of inattention had a prevalence of 3.3%. After multivariate analysis, the factor associated with the presence of ADHD symptoms in adults in the commune of Parakou was: a poor relationship with the subject’s partner (p = 0 . 031, ORa = 6 . 5 [1 . 18-35 . 68]). Conclusion: ADHD is present in the community of Parakou and needs further attention.
Attention deficit hyperactivity disorder (ADHD) is a persistent (over the past 06 months) pattern of inattention and/or hyperactivity-impulsivity that interferes with functioning or development, characterized by inattention and/or hyperactivity and impulsivity [
Furthermore, adults with ADHD often present with concomitant psychiatric disorders, so much so that up to two-thirds of adults with ADHD present with at least one psychiatric comorbidity. Similarly, ADHD is present in around 15% of adults with other psychiatric disorders [
This syndrome affects all areas of life. One of the best studied concerns academic and professional success. For the same intellectual potential, these young adults do less well in school and interrupt their studies earlier. In addition, they do not stay in the same job for as long, and are more likely to be unemployed. For example, one study showed that 17% of young adults with ADHD had no high school diploma, 48% were unemployed at the time of the survey and had already changed jobs 5.4 times [
Njuwa et al. [
Therapeutically, ADHD can be treated with both medication and psychotherapy. Medication includes stimulants such as methylphenidate and D-amphetamine. Some 60%-70% of patients receiving stimulants showed moderate to marked improvement, compared with 20% of patients receiving placebo. Psychotherapeutic treatment involves education about the disorder and its manifestations in the subject’s life, as well as helping the patient to understand that the chronic nature of the disorder can lead to the development of maladaptive compensatory behavior that may require psychotherapeutic intervention such as supportive therapy or coaching [
The absence of statistical data on adult ADHD in Benin is the reason for the present study, which was initiated to take stock of the disorder.
The present study took place in the commune of Parakou, in the north-east of the Republic of Benin. It was a cross-sectional, descriptive, analytical study conducted from March 19 to December 07, 2022. A total of 456 major subjects were recruited during a general population survey in the commune of Parakou and clearly consented to participate during the collection period. A face-to-face interview was conducted. Sampling was probabilistic, using the WHO cluster sampling technique. The statistical unit was represented by all adults aged 18 and over meeting our inclusion criteria. The sampling frame consisted of a list of the 42 neighborhoods/villages in the commune of Parakou, with their respective populations. Thirty (30) clusters were selected according to WHO recommendations. The 30 clusters were distributed as follows: After listing the districts of the Parakou commune, the list was distributed in a random order chosen by a random number generator. Then, starting from the first district on the list, the cumulative number of inhabitants per district was calculated. A cluster sampling step (k) was then obtained by dividing the total number of neighborhoods (255,478) by the total number of clusters (30), i.e., 255,478. The cluster sampling step calculated was equal to 8515.93, i.e., 8516; every 8516 individuals on the cumulative list were then drawn into a cluster. A number between 1 and 8516 (1332) was drawn at random. To identify the start, a cluster was drawn in the neighborhood containing the 1332nd individual. A step was then added, incrementing each time to identify the next cluster, and so on until all 30 clusters were reached. In the field, the interviewer went to the center of the neighborhood and randomly chose a direction using the bottle method (turning the bottle on the ground), numbering all the houses along the direction and choosing a house by a simple random draw from this numbered list; this choice was made using a random number generator on a smartphone. Targets meeting the inclusion criteria were searched for in the house selected, and then one was selected by simple random draw. Targets from neighboring houses were then included. The same operation was repeated in the neighborhoods containing the clusters. In concessions containing more than one household and in family homes, households were numbered and then a single individual who had been surveyed was drawn at random. In the latter case, a target household meeting the inclusion criteria was selected at random. If no household target met the inclusion criteria, the household was dropped and the same household and target selection procedure repeated until a target meeting the inclusion criteria was found. The 30 clusters were made up of adults aged 18 and over who had consented to take part in the study, were able to answer the questions and were present at home when the interviewers visited. The dependent variable was the presence of ADHD symptoms (two modalities: yes/no) in adults, obtained by means of a self-report scale, the Adult ADHD Self Report Scale (ARSR-v1.1) [
Data analysis was performed using R software version 4.3.0. Quantitative data were expressed as mean and standard deviation. Qualitative data were expressed as numbers and percentages. The Chi² test and Fisher’s exact test were used to test the association between two categorical variables. Results were considered significant at the 5% confidence level (p < 0.05). Also, the logistic regression model was used to identify the independent variables explaining the presence of ADHD symptoms in adults. The diagnosis of ADHD had not been clinically confirmed.
The sample consisted of 456 individuals surveyed in the commune of Parakou. ADHD was present in 31 individuals, representing a prevalence of 6.8% (IC95% [4.5%-9.1%]) in 2022. Among the clinical forms, the predominantly inattentive presentation of ADHD was the most objectified clinical form in the general population (
The average age of the participants was 30.4 ± 12 years, with extremes ranging from 18 to 82 years.
Among those with ADHD, the mean age was 25.90 years. Most were male (64.52%), with a gender ratio (M/F) of 1.81. The dominant age group was between 18 and 24 (64.54%). The following tables summarize these data.
Among the participants, 28.8% had a medical history. Approximately 11% of the participants had already had problems with the law. The surgical history sought was an accident (domestic or road traffic) with traumatic brain injury (TBI).
Among ADHD sufferers, 45.1% had a medical history. More than half used psychoactive substances (54.8%), and 35.30% had used them for more than 5 years.
Within the sample, people with living parents dominated (54.6%). Married people represented 47.1% of the study population. The majority had lived in a nuclear family during their childhood (58.6%). More than half had a father who did not attend school (51.4%), and around 7 out of 10 had a mother who did not attend school (69.9%). Most respondents had a partner (79.6%), and 75.7% had a good relationship with their partner.
In the case of ADHD sufferers, 67.7% had living parents, most of whom were married (58.0%). Most had lived in a nuclear family during childhood (48.39%). For the most part, the parents had not attended school (39.3% for the father and 53.6% for the mother). More than 8 out of ten had a partner (83.8%) with a good relationship (70.9%).
The present study shows that secondary education was dominant (49.1%) among those surveyed. More than 6 out of 10 had experienced failure during their school career (67.3%). Among those surveyed, 51.3% said they had never had a job.
Most of the respondents with ADHD (61.29%) had a secondary education.
Resumption of the school year was reported by 77.4%. It was found that 8 out of 10 people in this population were unable to find a job (80.0%).
The majority of respondents subscribe to a social network (74.0%). Of these, 71.1% spend up to 8 hours a day and 20.9% spend more than 8 hours a day on this social network.
Among people with ADHD, 8 out of 10 (80.6%) were subscribed to at least one social network. Most (84.0%) spent up to 8 hours on their favorite social networks, and 16.0% spent more than 8 hours.
| Sample (N = 456) | ADHD Positive (n = 31) | ADHD Negative (n = 425) | |
|---|---|---|---|
| Age (years) | |||
| [18-24[ | 175 (38.4%) | 20 (64.5%) | 155 (36.5%) |
| [25-34[ | 163 (35.7%) | 9 (29.0%) | 154 (36.2%) |
| [35-44[ | 62 (13.6%) | 1 (3.2%) | 61 (14.4%) |
| [45-54[ | 26 (5.7%) | 0 (0%) | 26 (6.1%) |
| [55-64[ | 15 (3.3%) | 0 (0%) | 15 (3.5%) |
| [65-74[ | 12 (2.6%) | 0 (0%) | 12 (2.8%) |
| [75 and over | 3 (0.7%) | 1 (3.2%) | 2 (0.5%) |
| Gender | |||
| Female | 274 (60.1%) | 11 (35.4%) | 263 (61.9%) |
| Male | 182 (39.9%) | 20 (64.5%) | 162 (38.1%) |
| Religion | |||
| Muslim | 235 (51.5%) | 15 (48.3%) | 220 (51.8%) |
| Christian | 204 (44.7%) | 16 (51.6%) | 188 (44.2%) |
| Endogenous | 11 (2.4%) | 0 (0%) | 11 (2.6%) |
| No | 6 (1.3%) | 0 (0%) | 6 (1.4%) |
| Marital status | |||
| Married* | 154 (33.8%) | 6 (1.3%) | 148 (34.8%) |
| Single | 179 (39.3%) | 19 (76%) | 160 (37.6%) |
| Concubinage | 118 (25.9%) | 6 (24%) | 112 (26.4%) |
| Divorced | 5 (1.1%) | 0 (0.0%) | 5 (1.2%) |
| Occupation (n = 407) | |||
| Retailers | 114 (27.9%) | 4 (14.3%) | 110 (29.0%) |
| Pupils/students | 89 (21.8%) | 10 (35.7%) | 79 (20.8%) |
| Artisans | 62 (15.2%) | 4 (14.3%) | 58 (15.3%) |
| Workers | 45 (11.1%) | 5 (17.9%) | 40 (10.6%) |
| Civil servant | 33 (8.1%) | 1 (3.6%) | 32 (8.4%) |
| Housewife | 19 (4.7%) | 2 (7.1%) | 17 (4.5%) |
| Farmer/fishermen | 12 (2.9%) | 2 (7.1%) | 10 (2.6%) |
| Motorcycle/auto driver | 11 (2.7%) | 0 (0.0%) | 11 (2.9%) |
| Teachers | 5 (1.2%) | 0 (0.0%) | 5 (1.3%) |
| Economic operator | 5 (1.2%) | 0 (0.0%) | 5 (1.3%) |
| Animator | 4 (1.0%) | 0 (0.0%) | 4 (1.1%) |
| Hotel manager | 3 (0.7%) | 0 (0.0%) | 3 (0.8%) |
|---|---|---|---|
| Health agent | 2 (0.5%) | 0 (0.0%) | 2 (0.5%) |
| Footballer | 1 (0.2%) | 0 (0.0%) | 1 (0.2%) |
| Constable | 1 (0.2%) | 0 (0.0%) | 1 (0.2%) |
| Computer scientist | 1 (0.2%) | 0 (0.0%) | 1 (0.2%) |
| Pastor | 1 (0.2%) | 0 (0.0%) | 1 (0.2%) |
*Grooms were subjects in couples, whether in civil, religious or informal unions.
| Sample (N = 456) | ADHD Positive (n = 31) | ADHD Negative (n = 425) | |
|---|---|---|---|
| Medical history | |||
| Presence | 131 (28.8%) | 14 (45.1%) | 117 (27.5%) |
| Absence | 325 (71.2%) | 17 (54.8%) | 308 (72.5%) |
| History of traumatic brain injury | |||
| Presence | 62 (13.6%) | 5 (16.1%) | 57 (13.4%) |
| Absence | 394 (86.4%) | 26 (83.8%) | 368 (86.6%) |
| Neurosurgical intervention | |||
| Yes | 1 (1.5%) | 1 (3.2%) | 0 (0.0%) |
| No | 61 (98.5%) | 30 (96.7%) | 31 (7.3%) |
| Psychiatric history | |||
| Yes | 3 (0.7%) | 0 (0.0%) | 3 (0.7%) |
| No | 453 (99.3%) | 31 (100%) | 422 (99.3%) |
| Psychoactive substances (n = 187) | |||
| Yes | 187 (41%) | 17 (54.8%) | 170 (40.0%) |
| No | 269 (59%) | 14 (45.1%) | 255 (60.0%) |
| Consumption period (year) | |||
| <5 years | 21 (11.4%) | 11 (35.4%) | 10 (2.4%) |
| ≥5 years | 55 (29.6%) | 6 (19.3%) | 49 (11.5%) |
| Type of psychoactive substance | |||
| Alcohol | 26 (74.28%) | 1 (50.0%) | 25 (75.75%) |
| Tobacco | 7 (20.0%) | 1 (50.0%) | 6 (18.18%) |
| Tramadol | 1 (2.85%) | 0 (0%) | 1 (3.03%) |
| Cannabis | 1 (2.85%) | 0 (0%) | 1 (3.03%) |
| Criminal record | |||
| Yes | 50 (11.0%) | 25 (80%) | 25 (5.9%) |
| No | 406 (89.0%) | 6 (19.3%) | 400 (94.1%) |
| Sample (N = 456) | ADHD Positive (n = 31) | ADHD Negative (n = 425) | |
|---|---|---|---|
| Parents’ status | |||
| Living | 249 (54.6%) | 21 (67.7%) | 228 (53.6%) |
| Deceased | 207 (45.4%) | 105 (32.2%) | 197 (46.4%) |
| Parents’ marital status | |||
| Married | 215 (47.1%) | 18 (58.0%) | 197 (46.4%) |
| Divorced | 28 (6.1%) | 2 (6.4%) | 26 (6.1%) |
| Physically separated | 213 (46.7%) | 11 (35.4%) | 202 (47.5%) |
| Family during childhood | |||
| Nuclear family | 267 (58.6%) | 15 (48.39%) | 252 (59.3%) |
| Extended family | 136 (29.8%) | 12 (38.7%) | 124 (22.2%) |
| Single-parent family | 24 (5.3%) | 3 (9.6%) | 21 (4.9%) |
| Polygamous family | 24 (5.3%) | 1 (3.22%) | 23 (5.4%) |
| Blended family | 5 (1.1%) | 0 (0.0%) | 5 (1.2%) |
| Father’s level of education (401) | |||
| Out of school | 206 (51.4%) | 11 (39.3%) | 195 (52.3%) |
| Primary | 59 (14.7%) | 5 (17.9%) | 54 (14.5%) |
| Secondary | 92 (22.9%) | 9 (32.1%) | 83 (22.3%) |
| Higher | 44 (11.0%) | 3 (10.7%) | 41 (11.0%) |
| Mother’s level of education (418) | |||
| Out of school | 292 (69.9%) | 15 (53.6%) | 277 (71.0%) |
| Primary | 52 (12.4%) | 6 (21.4%) | 46 (11.8%) |
| Secondary | 62 (14.8%) | 5 (17.9%) | 57 (14.6%) |
| Higher | 12 (2.9%) | 2 (7.1%) | 10 (2.6%) |
| Relationship with father (n = 456) | |||
| Good | 429 (94.1%) | 29 (93.5%) | 400 (94.1%) |
| Wrong | 27 (6.0%) | 2 (6.4%) | 25 (5.9%) |
| Relationship with mother (n = 456) | |||
| Good | 440 (95.5%) | 30 (96.8%) | 410 (96.5%) |
| Wrong | 16 (3.5%) | 1 (3.2%) | 15 (3.6%) |
| Presence of a partner (n = 456) | |||
| Yes | 363 (79.6%) | 26 (83.8%) | 337 (79.3%) |
| No | 93 (20.4%) | 5 (16.1%) | 88 (20.7%) |
| Relationship with partner (n = 363) | |||
| Good | 275 (75.7%) | 22 (70.9%) | 253 (96.2%) |
| Bad* | 14 (3.9%) | 4 (12.8%) | 10 (3.8%) |
|---|---|---|---|
| Number of descendants (n = 456) | |||
| 0 | 210 (46.1%) | 20 (64.5%) | 190 (44.7%) |
| ≥à 1 | 246 (53.9%) | 11 (35.4%) | 235 (55.3%) |
| Type of relationship with descendants (n = 246) | |||
| Good | 245 (99.6%) | 11 (100.0%) | 234 (99.6%) |
| Wrong | 1 (0.4%) | 0 (0.0%) | 1 (0.4%) |
*A bad relationship is defined by the presence of conflict, a toxic or even abusive relationship; a relationship in which the subject is not fulfilled.
| Sample (N = 456) | ADHD Positive (n = 31) | ADHD Negative (n = 425) | |
|---|---|---|---|
| Study level | |||
| Higher | 130 (28.5%) | 9 (29.0%) | 121 (28.5%) |
| Secondary | 224 (49.1%) | 19 (61.2%) | 205 (48.2%) |
| Primary | 55 (12.1%) | 2 (6.4%) | 53 (12.5%) |
| Out of school | 47 (10.3%) | 1 (3.2%) | 46 (10.8%) |
| School failure | |||
| Yes | 307 (67.3%) | 24 (77.4%) | 283 (66.6%) |
| No | 149 (32.7%) | 7 (22.5%) | 142 (33.4%) |
| Frequency of school failure | |||
| Once | 149 (48.5%) | 3 (9.6%) | 146 (57.0%) |
| More than once | 111 (36.1%) | 1 (3.2%) | 110 (43.0%) |
| Number of jobs obtained | |||
| 0 | 234 (51.3%) | 4 (80.0%) | 230 (51.0%) |
| 1 | 164 (36.0%) | 1 (20.0%) | 163 (36.1%) |
| 2 | 38 (8.3%) | 0 (0.0%) | 38 (8.4%) |
| 3 | 8 (1.8%) | 0 (0.0%) | 8 (1.8%) |
| 4 | 6 (1.3%) | 0 (0.0%) | 6 (1.3%) |
| 5 | 5 (1.1%) | 0 (0.0%) | 5 (1.1%) |
| 10 | 1 (0.2%) | 0 (0.0%) | 1 (0.2%) |
| Redundancies | |||
| Yes | 15 (3.3%) | 2 (6.4%) | 13 (3.1%) |
| No | 441 (96.7%) | 29 (93.6%) | 412 (96.9%) |
| Frequency of layoffs | |||
| Once | 13 (86.7%) | 1 (50.0%) | 12 (92.3%) |
| More than once | 2 (13.3%) | 1 (50.0%) | 1 (7.7%) |
| Sample (N = 456) Workforce | ADHD Positive (n = 31) Workforce | ADHD Negative (n = 425) Workforce | |
|---|---|---|---|
| Time spent online (n = 333) | |||
| ≤8 hours | 240 (72.1%) | 19 (73.1%) | 221 (72.0%) |
| >8 hours | 93 (27.9%) | 7 (26.9%) | 86 (28.0%) |
| Social network subscription (n = 456) | |||
| Yes | 340 (74.0%) | 25 (80.6%) | 315 (74.1%) |
| No | 116 (25.4%) | 6 (19.3%) | 110 (25.9%) |
| Time spent on social networks (n = 329) | |||
| ≤8 hours | 260 (79.1%) | 21 (84.0%) | 239 (78.61%) |
| >8 hours | 69 (20.9%) | 4 (16.0%) | 65 (21.38%) |
| Workforce | Percentage | |
|---|---|---|
| Self-esteem | 6 | 1.3 |
| Social functioning | 2 | 0.4 |
| Family | 1 | 0.2 |
| Work | 1 | 0.2 |
| School | 0 | 0 |
| Life skills | 0 | 0 |
| Risky behavior | 0 | 0 |
ADHD caused different types of impact. Among these, self-esteem was predominant (1.3%).
The presence or absence of ADHD repercussions is shown in
1) Bivariate analysis
Bivariate analysis showed that there was a statistically significant difference between ADHD and age (p = 0.013), presence of medical history (p = 0.002), use (p = 0.002) and duration of use of a psychoactive substance (p = 0.000), relationship with life partner (p = 0.040) and number of offspring (p = 0.033).
2) Multivariate analysis
The multivariate model of potential predictors of attention deficit disorder with or without hyperactivity in the commune of Parakou in 2022 shows that among people aged over 18, only the nature of the relationship with the life partner explains the presence of ADHD symptoms (p = 0.031, Ora = 6.5 [1.18-35.68]. Couples with a poor relationship were 6.5 times more likely to have
| Existence of ADHD (N = 456) | p | ||
|---|---|---|---|
| Yes | No | ||
| Gender | |||
| Male | 20 (4.4%) | 254 (55.7%) | 0.602 |
| Female | 11 (2.4%) | 171 (37.5%) | |
| Age | |||
| [18-24] | 20 (4.4%) | 155 (34.0%) | |
| [25-34] | 9 (2%) | 154 (33.8%) | |
| [35-44] | 1 (0.2%) | 61 (13.4%) | |
| [45-54] | 0 (0.0%) | 26 (5.7%) | 0.013 |
| [55-64] | 0 (0.0%) | 15 (3.3%) | |
| [65-74] | 0 (0.0%) | 12 (2.6%) | |
| [75 and over | 1 (0.2%) | 2 (0.4%) | |
| Religion | |||
| No | 0 (0.0%) | 6 (1.3%) | |
| Christian | 16 (3.5%) | 188 (41.2%) | 0.647 |
| Endogenous | 0 (0.0%) | 11 (2.4%) | |
| Muslim | 15 (3.3%) | 220 (48.2%) | |
| Widowed/not widowed | |||
| Widowed | 2 (0.4%) | 24 (5.3%) | 0.149 |
| Not widowed | 4 (0.9%) | 124 (27.2%) | |
| Marital status | |||
| Married | 6 (1.3%) | 148 (32.5%) | 0.079 |
| Unmarried | 25 (60.7%) | 277 (60.7%) | |
| Single | 19 (4.2%) | 160 (35.1%) | |
| Concubinage | 6 (1.3%) | 112 (24.6%) | 0.07 |
| Divorced | 0 (0.0%) | 5 (1.1%) | |
| Number of weddings/remarriages | |||
| Once | 4 (2.7%) | 125 (84.5%) | 0.626 |
| More than once | 1 (0.2%) | 18 (12.2%) | |
| Study level | |||
| Out of school | 0 (0.0%) | 38 (8.3%) | |
| Literate | 1 (0.2%) | 8 (1.8%) | |
| Primary | 2 (0.4%) | 53 (11.6%) | |
| Secondary | 19 (4.2%) | 205 (45.0%) | 0.297 |
| Higher | 9 (1.0%) | 121 (26.5%) | |
| Existence of ADHD (N = 456) | p | ||
|---|---|---|---|
| Yes | No | ||
| Time spent online | |||
| ≥ 8 hours | 19 (5.7%) | 221 (66.4%) | 0.905 |
| < 8 hours | 7 (2.1%) | 86 (25.8%) | |
| Social network subscription | |||
| Yes | 25 (5.5%) | 315 (69.1%) | 0.42 |
| No | 6 (1.3%) | 110 (24.1%) | |
| Social network subscription | |||
| ≥8 hours | 26 (5.8%) | 353 (78.8%) | 0.745 |
| <8 hours | 4 (0.9%) | 65 (14.5%) | |
| Medical history | |||
| Presence | 14 (3.1%) | 88 (19.3%) | 0.002 |
| Absence | 0 (0.0%) | 337 (73.9%) | |
| Psychiatric history | |||
| Yes | 0 (0.0%) | 3 (0.7%) | 0.639 |
| No | 31 (6.8%) | 422 (92.5%) | |
| Criminal record | |||
| Yes | 25 (80.6%) | 50 (11.0%) | 0.121 |
| No | 6 (19.4%) | 406 (89.0%) | |
| History of Cranio-Encephalic Trauma | |||
| Presence | 5 (1.1%) | 57 (12.5%) | 0.670 |
| Absence | 26 (5.7%) | 368 (80.7%) | |
| Neurosurgical intervention | |||
| Yes | 1 (0.2%) | 6 (1.3%) | 0.428 |
| No | 30 (6.6%) | 419 (91.9%) | |
| Parents’ status | |||
| Alive | 21 (4.6%) | 228 (50.0%) | 0.128 |
| Died | 10 (2.2%) | 197 (43.2%) | |
| Family during childhood | |||
| Extended family | 12 (2.6%) | 124 (27.2%) | 0.505 |
| Single-parent family | 3 (0.7%) | 21 (4.6%) | |
| Nuclear family | 15 (3.3%) | 252 (55.3%) | |
| Blended family | 0 (0.0%) | 5 (1.1%) | |
| Polygamous | 1 (0.2%) | 23 (5.0%) | |
|---|---|---|---|
| Psychoactive substances | |||
| Yes | 17 (3.7%) | 170 (37.3% | 0.002 |
| No | 14 (3.1%) | 255 (55.9%) | |
| Consumption period (year) | |||
| <05 | 11 (5.9%) | 41 (21.9%) | <0.000 |
| ≥05 | 6 (3.2%) | 129 (69.0%) | |
| Relationship with father (n = 456) | |||
| Good | 29 (6.4%) | 400 (87.7%) | 0.711 |
| Conflict | 1 (0.2%) | 13 (2.9%) | |
| Wrong | 1 (0.2%) | 12 (2.6%) | |
| Relationship with mother (n = 456) | |||
| Good | 30 (6.6%) | 410 (89.9%) | |
| Conflict | 1 (0.2%) | 5 (1.1%) | 0.559 |
| Wrong | 0 (0.0%) | 10 (2.2%) | |
| Presence of a partner | |||
| Yes | 26 (5.7%) | 337 (73.9%) | 0.643 |
| No | 5 (1.1%) | 78 (17.1%) | |
| Relationship with the partner | |||
| Good | 22 (4.8%) | 323 (70.8%) | 0.040 |
| Conflict | 1 (0.2%) | 6 (1.3%) | |
| Wrong | 3 (0.7%) | 8 (1.8%) | |
| Number of children | |||
| 0 | 20 (4.4%) | 190 (41.7%) | 0.033 |
| ≥1 | 11 (2.4%) | 235 (51.5%) | |
| Relationship with children | |||
| Good | 11 (2.4%) | 234 (51.3%) | 0.100 |
| Wrong | 0 (0.0%) | 1 (0.2%) | |
| School failure | |||
| Yes | 24 (5.3%) | 283 (62.1%) | 0.215 |
| No | 7 (1.5%) | 142 (31.1%) | |
| Number of failures | |||
| 0 | 7 (1.5%) | 142 (31.1%) | 0.215 |
| ≥1 | 24 (5.3%) | 283 (62.1%) | |
| Currently employed | |||
| Yes | 12 (2.6%) | 237 (52.0%) | 0.066 |
| No | 19 (4.2%) | 188 (41.2%) | |
|---|---|---|---|
| Number of jobs already held | |||
| 0 | 19 (4.2%) | 215 (47.1%) | 0.250 |
| ≥1 | 12 (2.6%) | 210 (46.1%) | |
| One-time dismissal | |||
| Yes | 2 (0.4%) | 13 (2.9%) | 0.307 |
| No | 29 (6.4%) | 412 (90.4%) | |
| Number of dismissals | |||
| 1 | 1 (6.7%) | 12 (80.0%) | 0.101 |
| ≥1 | 1 (6.7%) | 1 (6.7%) | |
| Father’s level of education | |||
| Literate | 1 (0.2%) | 9 (2.0%) | |
| Higher | 3 (0.6%) | 41 (9.0%) | |
| Unknown | 3 (0.6%) | 52 (11.4%) | 0.736 |
| Primary | 5 (1.1%) | 54 (11.8%) | |
| Secondary | 9 (2.0%) | 83 (18.2%) | |
| Out of school | 10 (2.2%) | 186 (40.8%) | |
| Mother’s level of education | |||
| Literate | 1 (0.2%) | 6 (1.3%) | |
| Higher | 2 (0.4%) | 10 (2.2%) | |
| Unknown | 3 (0.6%) | 35 (7.67%) | 0.293 |
| Primary | 6 (3.2%) | 46 (10.1%) | |
| Secondary | 5 (1.1%) | 57 (12.5%) | |
| Out of school | 14 (3.1%) | 271 (59.4%) | |
| ADHD | Multivariate analysis | ||||
|---|---|---|---|---|---|
| Yes | No | Adjusted OR | IC95% | p | |
| Relationship with the partner | |||||
| Good | 22 (6.1%) | 323 (89.0%) | 1 | ||
| Wrong | 4 (1.1%) | 14 (3.9%) | 6.5 | [1.18 - 35.68] | 0.031 |
| Age | |||||
| ≤24 | 20 (4.4%) | 155 (34.0%) | 1 | ||
| >24 | 11 (2.4%) | 270 (59.2%) | 0.6 | [3.720 - 0.097] | 0.583 |
| Marital status | |||||
|---|---|---|---|---|---|
| Married | 6 (1.3%) | 148 (32.5%) | 1 | ||
| Unmarried | 25 (5.5%) | 277 (60.7%) | 1.091 | [0.270 - 4.410] | 0.903 |
| Parents’ status | |||||
| No | 30 (6.6%) | 197 (43.2%) | 1 | ||
| Yes | 21 (4.6%) | 228 (50.0%) | 1.169 | [0.266 - 5.136] | 0.836 |
| Relationship with father | |||||
| Good | 29 (6.6%) | 382 (87.2%) | 1 | ||
| Wrong | 1 (0.2%) | 12 (2.6%) | 1.093 | [0.093 - 12.789] | 0.943 |
| Relationship with mother | |||||
| Good | 29 (6.5%) | 403 (90.0%) | 1 | ||
| Wrong | 1 (0.2%) | 15 (3.3%) | 4.322 | [0.381 - 49.022] | 0.237 |
| Relationship with children | |||||
| Good | 11 (4.5%) | 234 (95.1%) | 1 | 0 | 1 |
| Wrong | 1 (0.4%) | 0 (0.0%) | 0 | ||
| Number of children | 1.042 | [0.832-1.305] | 0.722 | ||
| School failure | |||||
| No | 7 (1.5%) | 142 (31.1%) | 1 | ||
| Yes | 24 (5.3%) | 283 (62.1%) | 1.058 | [0.244 - 4.597] | 0.94 |
| Redundancies | |||||
| No | 29 (6.4%) | 412 (90.4%) | 1 | 0 | |
| Yes | 2 (0.4%) | 13 (2.9%) | 0 | 0.999 | |
| Frequency of layoffs | |||||
| Never | 29 (6.4%) | 412 (90.4%) | 1 | ||
| At least once | 2 (0.4%) | 13 (3.0%) | 0.909 | [0.228 - 3.625] | 0.892 |
ADHD symptoms than couples with a good relationship.
To achieve the objectives of this study, a cross-sectional, descriptive and analytical study was carried out. It enabled us to identify subjects with ADHD [
The procedure used was probability sampling using the WHO cluster sampling technique. The statistical unit was represented by all adults aged 18 and over meeting the inclusion criteria. The sampling frame consisted of the list of 42 neighborhoods/villages in the commune of Parakou, with their respective populations. 30 clusters were selected according to WHO recommendations. Determined using the Schwartz formula based on the prevalence of ADHD found in Nigeria in 2014, which was 12.5%, the sample size initially planned for 371 subjects was increased to a size of 456 surveyed subjects in order to obtain greater reliability of the results. By deduction, the methodology used was reliable, reinforcing the quality of the results obtained.
Prior to the start of data collection, authorization was obtained from the Mayor of the commune of Parakou (N˚50/155/MPKOU).
The data collection technique was a guided face-to-face interview using a digitized survey form with the aid of Kobocollect software, which included sociodemographic data, history, biography, clinical data, lifestyle data, intellectual and professional development data and the ARSR-v1. 1 (Adult ADHD Self-Re- port Scale) to screen for ADHD and the WFIRS-S (Weiss functional impairment rating scale) to assess the consequences of ADHD.
The one-on-one interview is a rapid and appropriate data collection technique. It allowed for follow-up and rephrasing to help the participant express his or her point of view, and to deepen and complete the information in addition to the questions asked. Anonymity ensured more honest responses. This technique ensured that the information collected was as reliable as possible. As with any self-reporting study, there are always biases associated with the source of the information, which may minimize or exaggerate certain aspects of the statements. As the questionnaire used was in French, not having been validated in local languages, an intervention bias may have arisen during the interviews. To limit information bias due to misunderstanding of the questions, the interview guide was written in precise French, using simple themes with suggested answers and respecting anonymity, which made the task easier for the subjects in the study population. Similarly, each interviewing team included at least one interviewer fluent in a local language. Consequently, the results obtained are valid and can be the subject of etiological hypotheses that could lead to an analytical study to identify the factors associated with ADHD in order to undertake corrective actions.
Age
Among the 31 individuals with ADHD symptoms, the average age was 25.90 ± 11.6 years. This is close to that reported by Jenkins et al. [
There was a statistically significant difference between age and ADHD (p = 0.013). The average age of subjects with ADHD was 25.90 years. As age increases, ADHD symptoms decrease, as was the case in the study by Vňuková et al. [
Gender
In this work male subjects predominated in the ADHD population with a proportion of 64.52%. The same finding was made by Vňuková et al. in 2021 (Czech Republic) [
Marital status
Unmarried subjects (66.2%) were dominant in the present study, in contrast to the data from De Ridder et al. [
Most (60.7%) of the ADHD subjects were also unmarried, since unmarried subjects were dominant in this work, which could justify this result. It should be pointed out that in the present work, the respondents were classified as “married (civil, religious or cultural marriage)” and “unmarried (single, cohabiting, divorced)”.
The prevalence of ADHD was 6.8%, measured using the Adult ADHD Self Report Scale (ARSRv1.1) that is a screening scale. This prevalence is higher than those found by Kessler et al. in 2006 in the United States (4.4%) [
The prevalence found in the present study was lower than that found (13.1%) by Jenkins et al. [
The predominantly inattentive form of ADHD was represented by 3.3%. In the work of various authors (Okhakhume and Oluwafemi in Nigeria in 2014 [
The combined form of ADHD accounted for 2.4%. It is the second most represented clinical form in this survey. However, other authors have reported much higher proportions: Bassiony et al. [
ADHD in its clinical form with predominant hyperactivity/impulsivity was 1.1% in the present work. Okhakume and Oluwafemi [
In our multivariate regression model, only the poor relationship with the life partner explains the presence of ADHD symptoms (p = 0.040; OR = 7.035). A poor relationship within the couple can therefore generate attention disorders in adults. This result raises the issue of reduced academic and professional performance in a conflict-ridden couple relationship. This work allows us to confirm the need to resolve conflicts within the couple in order to optimize the subject’s productivity. A day spent serenely as a couple preserves and improves the subject’s performance, enabling him to concentrate on his work.
Attention deficit hyperactivity disorder (ADHD) is a disorder for which study data are scarce in our country. The results reveal that it is present in six (6) out of every hundred adults in the commune of Parakou. The associated factor was a poor relationship with a life partner. Taking into account the many aspects of life that can be affected by its presence, ADHD requires in-depth interest to assess all its contours, following clinical confirmation of subjects presenting these symptoms.
The authors declare no conflicts of interest regarding the publication of this paper.
Elie, A.I.N., Kémo, S., Kévin, K.K.C., Ignace, T.C.N., Elvire, D.S.E., Sinet, K.D., Djibrilla, M., Francis, T.T. and Prosper, G. (2023) Attention Deficit Hyperactivity Disorder in the General Adult Population in Benin (Parakou 2022). Open Journal of Psychiatry, 13, 324-344. https://doi.org/10.4236/ojpsych.2023.134025