The investigation was a cross-sectional, descriptive study with an analytical perspective, featuring both quantitative and qualitative elements. Data collection occurred in March 2024.

The target population was comprised of residents of the commune of Kpomassè aged between 18 and 69 years.

The study included any individual who had been residing in the commune of Kpomassè for no less than 6 months and who had consented to participate in the survey.

Individuals excluded from the study included:

- those unable to communicate;

- pregnant women, to prevent the influence of pregnancy on anthropometric measurements and blood glucose levels.

Participants who withdrew their consent during the study were excluded.

We used a three-stage probabilistic cluster sampling method, adapted from WHO guidelines. The sample size was calculated based on Schwartz’s formula, considering the diabetes mellitus prevalence in the general population of Benin in 2015 (12.4%) [4] , a margin of error of 5%, and a cluster effect of 1.5. To account for potential refusals and missing data, the calculated sample size was increased by 10% and proportionally allocated according to the number of inmates.

First degree: selection of villages (utilizing 30 clusters);

Second degree: selection of households/concessions;

Third degree: selection of individuals (using the Kish method).

The sampling progressed systematically from step to step. This procedure was replicated until the predetermined sample size for each village was achieved.

The equipment utilized comprised OMRON® brand electronic arm blood pressure monitors, ACCU-CHEK Active® brand electronic glucose meters, mechanical bathroom scales, stadiometers (SATURE METER 2M) for height measurement, cotton, and professional measuring tapes for waist circumference measurement.

The research protocol for this study as well as the collection tools were validated by a jury which met on March 8, 2024 at the Regional Institute of Public Health (IRSP). The data collection sheet (Appendix 1) was drawn up taking into account the STEPS surveys carried out and the literature review we had carried out. The conceptual framework (Appendix 2) summarizes the data sought. After obtaining authorization from the municipal authorities of Kpomassè, we undertook a preliminary phase in one of the villages in this commune. The aim was to assess the local population’s understanding of the survey form used, to identify and correct any shortcomings, and to adjust our instruments accordingly. The pretest was carried out in the village of Missebo, which was not included in the study.

An invitation to apply was issued to form the data collection team. After a careful analysis of the applications received, the selected candidates were given the opportunity to undergo comprehensive training on notions relating to diabetes, the aim of the study and collection tools, culminating in a practical assessment. Only the first five candidates to pass this assessment were finally selected to join the data collection team.

With the required authorizations from the Ministry of Health and the local municipal authorities, data collection commenced in the designated villages. This data collection phase spanned from March 16 to March 30, 2024. To ensure accuracy and minimize information bias, each completed electronic form was systematically reviewed on a daily basis. Data were collected between 5:00 a.m. and 11:00 a.m., prior to any food intake by the subjects. We also inquired about the time of their last meal to confirm that at least eight hours had passed. Biometric and anthropometric data were gathered at the conclusion of the questionnaire. Weight was recorded using an electronic scale with an accuracy of 100 grams. Blood glucose levels were assessed with ACCU-CHEK Active® test strips for capillary blood glucose. A drop of capillary blood was collected from the fingertip and applied to the test strip inserted into the glucometer. The glucometer displayed blood glucose results, measured in mg/dL, within 12 seconds. Blood pressure was measured after a 15-minute rest period using an OMRON electronic sphygmomanometer, a device recommended for community surveys. Two readings were taken five minutes apart, and their average was computed. Height was measured using a standing stadiometer with a precision of 0.1 cm. Stress levels were assessed using the Hospital Anxiety and Depression (HAD) scale.

The dependent variable in this study was the presence of diabetes mellitus in adults, categorized as either diabetic or non-diabetic. A participant was classified as diabetic if they exhibited a fasting capillary blood glucose level of 1.26 g/L or higher, or if they had received diabetes treatment within the previous 12 months. Non-diabetic participants were further classified into normoglycemia or prediabetes. Prediabetes was defined by a blood glucose level ranging from 1.1 g/L to 1.25 g/L, whereas a blood glucose level of 1.1 g/L or below was considered as normoglycemia.

The study identified and examined the independent variables that could elucidate the incidence of diabetes mellitus among adults in the commune of Kpomassè. These variables were categorized into four groups of factors:

To ensure data integrity, the completeness and consistency of the collected data were reviewed daily. The data processing and analysis utilized Stata 15 software, encompassing both descriptive and analytical phases.

Quantitative variables following a normal distribution were summarized by their mean and standard deviation. For variables with non-normal (asymmetric) distributions, the median and interquartile range (IQR) were reported. For qualitative variables, the analysis included calculating proportions or percentages.

Initially, univariate analyses were conducted through simple logistic regression and Pearson’s chi-squared tests, with a significance threshold set at 5%. For the multivariate analysis, a multiple logistic regression model was implemented to identify the determinants of diabetes mellitus in adults. Variables demonstrating a p-value below 20% in the bivariate analysis were included in the preliminary multiple logistic regression model. Subsequently, a stepwise backward elimination was applied. Variables with a p-value under 5% were maintained in the final model. The final model’s fit was evaluated using the Hosmer-Lemeshow test, and the reference categories were those associated with the lowest risk.

The study adhered to fundamental ethical principles concerning research involving human subjects. Necessary approvals were obtained, and a preliminary informational notice was distributed to inform residents. Authorization to conduct the study was granted by the Ministry of Health. On a local scale, consent from municipal authorities and health structures was secured prior to the initiation of data collection. Study participants were fully informed about the study’s nature and objectives, and informed consent was obtained from each respondent. Confidentiality was assured, and data collection was executed anonymously.

1) Biological characteristics of adults surveyed in the commune of Kpomassè in 2024

Out of 308 subjects surveyed, 156 were men, accounting for 50.65%, with a male to female ratio of 1.03. The median age of the study population was 43 years (Quartile 1: 36; Quartile 3: 55). The youngest participant was 19 years old, while the eldest was 69. Regarding diabetes history, 269 participants indicated no family history of diabetes. Among the 39 respondents who reported a family history of diabetes, 20 (51.28%) specified it as a first-degree relative. In terms of stress, approximately 123 (39.94%) subjects reported being stressed, and 127 (41.23%) were at least overweight. Table 1 summarizes the distribution of adults surveyed according to biological characteristics in the commune of Kpomassè in 2024 (n=308).

2) Behavioural and environmental characteristics of adults surveyed in the commune of Kpomassè in 2024

The majority of subjects (75.65%) were not physically active. The number of hours spent daily in sedentary activities was 2.93 hours (1.4). The proportion of individuals consuming alcohol in a harmful or excessive manner was zero. On the other hand, 181 subjects (58.76%) had at least low alcohol consumption, and only 6.17 of the subjects used tobacco. With regard to food consumption, only 12.34% of subjects consumed at least 05 fruits and vegetables a day, and 37.99% of subjects consumed sweet or fried foods at most once a week. Average sleep duration was 7.26 ± 1.72 and 48.7% of subjects had abnormal sleep duration (short or long). Regarding knowledge of diabetes, 71.10% of subjects had poor knowledge, and of these, 50.68% (111 subjects) had no knowledge of diabetes. Table 2 summarizes the distribution of adults surveyed according to behavioral characteristics in the commune of Kpomassè in 2024.

Regarding insecticide use, 70%, or 238 adults surveyed, did not use insecticides in their homes. Among farmers using pesticides, 34.78% mentioned using herbicides. Table 3 summarizes the distribution of adults surveyed according to environmental characteristics in the commune of Kpomassè in 2024.

The most predominant profession or occupation among the individuals surveyed was that of trader or dealer, encompassing a significant percentage of 37.26%. In second place were farmers, with a share of 20.45%. In terms of level of education, a majority of 223 subjects, that is 72.41% of the group studied, had attained primary level or less. In terms of income, 86.69% of those surveyed earned no more than the guaranteed minimum wage. In terms of marital status, a remarkable 82.14% of adults surveyed were either cohabiting or married. The Pedah ethnic group and its relatives were the most represented, accounting for 31.82%. Table 4 summarizes the distribution of adults surveyed by socio-demographic and socio-cultural characteristics in the commune of Kpomassè in 2024.

*: Tradipratician (01), Driver (07), Mechanic (02), Cook (03), Pupil/student (03), Housekeeper (03), Photographer (01), Plumber (02); **: Adja (07), Goun (03), Kotafon (01), Kotokoli (01), Mina (01), Nagot (01), Yoruba (01).

All subjects surveyed said they had never received nutritional education, awareness-raising about non-communicable diseases, or systematic screening for diabetes risk.

Of the 308 subjects surveyed, 62 individuals, representing 20.13% of the sample, exhibited fasting hyperglycemia. Within this group, 46 were diagnosed with diabetes, and 16 were identified as prediabetic. Therefore, the prevalence rates of diabetes and prediabetes among adults in the Kpomassè commune were 14.94% and 5.19%, respectively. Table 5 details the distribution of the surveyed adults based on their glycemic levels.

Thirteen variables in univariate analysis had modalities with p-values below 20%. These were age, gender, blood pressure, waist circumference, family history of diabetes, body mass index (BMI), stress, level of knowledge, sleep duration, salt consumption, fried food consumption, ethnic origin and marital status. Table 6 presents the associations between a few variables and diabetes mellitus in adults in the commune of Kpomassè in 2024.

The aim of the bivariate analysis was to find associations between the different independent variables. We present the dependent variables that were statistically significantly related to each other.

Sedentary lifestyle and age are statistically associated. Adults over 40 are more sedentary than those under 40 ( Table 7 ).

There was a statistically significant relationship between age and waist circumference (p = 0.011). Among subjects with abdominal obesity, 66.40% were over 40 years of age ( Table 8 ).

There was a statistically significant relationship between age and BMI (p = 0.001). Among overweight subjects, 70.51% were over 40 years of age. Similarly, among obese subjects, 69.39% were aged over 40 ( Table 9 ).

There is a statistically significant association between gender and physical activity (p = 0.017). Among the individuals engaging in physical activity, 62.67% are male ( Table 10 ).

There is a statistically significant association between gender and alcohol consumption (p = 0.000). Among those who consume at least small amounts of alcohol, 64.64% are male ( Table 11 ).

There is a statistically significant association between income and stress (p = 0.005). Among individuals suffering from stress, 94.31% have an income below 52,000 FCFA ( Table 12 ).

Thirteen variables were integrated into the initial multivariate model, including age, sex, blood pressure, waist circumference, family history of diabetes, body mass index (BMI), stress, knowledge level, sleep duration, salt intake, fried food consumption, ethnicity, and marital status. Following a stepwise backward elimination of non-significant variables, five were identified as being associated with diabetes mellitus among adults residing in Kpomassè in 2024. Analysis of the final model enabled us to conclude that diabetes mellitus in adults in the municipality of Kpomassè is influenced by the interaction between sex, age, sleep duration, fried food consumption, and stress. Table 13 shows the final multivariate model of determinants associated with diabetes mellitus among adults in the municipality of Kpomassè in 2024.

The present study aimed to investigate the determinants of diabetes mellitus in adults within the municipality of Kpomassè in 2024. The process of collecting and analyzing data enabled us to achieve our research objectives.

The study followed a mixed cross-sectional approach, encompassing both qualitative and quantitative methods, with a focus on analytical outcomes. The chosen methodology was fully aligned with the purpose of the study. Sampling was conducted using a probabilistic approach, adhering to the cluster sampling technique recommended by the World Health Organization (WHO), which is known for its reliability. An exhaustive list of villages in the commune was drawn up in order to effectively implement the cluster technique, selecting 30 clusters (Villages). Data were collected from adults of all sexes, aged 18 to 69, using a questionnaire administered by specially trained interviewers. Biological and anthropometric measurements were taken using appropriate instruments. For univariate and multivariate analysis, simple and multiple logistic regression were used. However, as with any study, ours may be subject to information bias, notably due to memory defects. In order to control this bias, the interviewers, local health workers, were accompanied by community relays to establish a relationship of trust with the respondents and guarantee the anonymity of the survey. Sensitive questions were formulated progressively to facilitate the respondent’s response, and certain questions were repeated to elicit the respondent’s memory. To limit interviewer bias, data collection was carried out by qualified, experienced interviewers under supervision. They were trained in the use of measurement tools and equipment, which helped them to better understand these instruments. Biological and anthropometric measurements were taken after the questionnaire had been completed, to avoid any influence on the interviewers’ questions. Blood pressure was measured with an OMRON electronic sphygmomanometer, recommended for community surveys, and height was accurately measured with a caliper fathometer. Capillary blood glucose was assessed using ACCU-CHEK Active® test strips. All these devices were of the same brand for each team, to minimize equipment bias. Stress was assessed using the HAD scale, and interviews with secondary targets were conducted in a confidential setting after obtaining free and informed consent. Overall, data collection and analysis techniques enabled triangulation of the data collected, guaranteeing results deemed valid. Despite the biases inherent in studies based on declarative data, we are confident in the validity and reliability of our results, which could be generalized to the entire population of the commune of Kpomassè.

The difficulties and limitations encountered in the course of this study are many and varied. They relate in particular to several points:

- Exploration of the variable of birth weight proved impossible, as only one person had this information.

- The absence of a statistical link between diabetes mellitus in adults and the use of insecticides in the home or pesticides in the field means that a link between pesticide exposure and the onset of diabetes cannot be definitively ruled out. A further study should be undertaken to establish a link between plasma organochlorine concentrations and the onset of diabetes. Similarly, we can’t say that we’ve explored every avenue in terms of chemical exposure. We had explored the most likely according to the literature review.

- On the nutritional front, the unavailability of resources to recruit nutritionists hampered the possibility of quantifying energy intake, for example, by recalling 24-hour diets. However, the results point to nutritional problems that need to be resolved.

The prevalence of diabetes mellitus among adults in the Kpomassè commune in 2024 stands at 14.94%. This figure is notably higher compared to the 9.5% found in the rural regions of Benin during the 2015 STEP survey. This 5.44% increase over nine years may be attributed to the larger study sample in the STEP survey as well as the global rise in diabetes prevalence, particularly noted in Africa and Benin. This trend, significantly influenced by globalization in Africa, can generally be ascribed to a combination of lifestyle changes (notably decreased physical activity) and dietary shifts, driven by industrialization and urbanization. In the commune of Kpomassè, risk factors for diabetes are also found. Indeed, 39.94% of the subjects surveyed had elevated blood pressure, 41.23% were at least overweight, 23.05% had abdominal obesity, and 39.94% were stressed. The majority of subjects, that is 75.65%, did not practice physical activity. 58.76% of adult subjects had at least low alcohol consumption. Finally, 37.99% of subjects consumed sweet products or fried foods at most once a week. These factors are all elements that can explain the high prevalence of diabetes.

At the national level, our findings differ from those reported by Dovonou et al. in Parakou in 2021 [18] and Amoussou-guenou et al. in Porto Novo in 2014 [12] , which reported prevalences of 2.84% and 6.7%, respectively. These discrepancies may be due to differences in the examined populations, the periods of the respective studies, as well as the distinct biological characteristics of the populations involved.

Our study demonstrates a significant association between stress and diabetes incidence. Specifically, adults experiencing stress had a 2.50-fold higher risk (95% CI [1.21 - 5.03]) of developing diabetes compared to those without stress. Chronic stress, in particular, has complex biological effects that contribute to the onset and progression of diabetes. It activates the sympathetic nervous system, prompting the release of stress hormones such as adrenaline and noradrenaline, which sustain insulin resistance and elevate blood glucose levels. Moreover, chronic stress stimulates the hypothalamic-pituitary-adrenal axis, resulting in increased cortisol production, which enhances glucose release by the liver and decreases its utilization by peripheral tissues. Additionally, chronic stress can cause systemic inflammation, which is linked to insulin resistance and beta cell damage in the pancreas [16] [23] [24] . Among the factors likely to explain chronic stress in the commune of Kpomassè, income could be a source of permanent stress. Indeed, our study shows that there is a statistically significant link between income and stress (p = 0.005). Among the subjects suffering from stress, 94.31% had an income of less than 52,000 CFA francs. Insufficient monthly income to meet the most basic needs could explain the high prevalence of chronic stress in this population.

Our findings align with those of Novak et al., who conducted a study on men, published in 2013, demonstrating that men under constant stress had a higher risk of diabetes [hazard ratio 1.52 (95% CI 1.26 - 1.82)] compared to men without stress [25] . Furthermore, a longitudinal study by Harris et al. in 2017 on women in Australia found that moderate to high stress levels were associated with a 2.3-fold increase in the risk of type 2 diabetes after three years [26] .

Gender was statistically linked to the incidence of diabetes in our study. Adult males had a 2.12 times greater risk of developing diabetes (95% CI [1.04 - 4.31]) compared to females. This predominance in males could be explained through two perspectives. Biologically, certain studies indicate that estrogens have a protective role in preventing diabetes. Estrogens influence the overall metabolism by regulating blood glucose levels, particularly by acting on pancreatic GLP-1-producing cells and intestinal L cells, which are also responsible for GLP-1 production [27] . This hormone is especially protective in women before menopause [27] . Behaviorally, women are reported to have a healthier lifestyle than men [28] . This observation is confirmed in our study. Indeed, there was a significant statistical link between sex and alcohol consumption (p = 0.000). Among the subjects consuming alcohol at least lightly, 64.64% are male. Likewise, although there was no association between sex and tobacco consumption, 68.42% of subjects who consumed tobacco were also male.

Our findings are consistent with those reported by Kpozehouen et al. in 2015 [17] , who also found that gender was associated with diabetes incidence (p = 0.0031). Male subjects had a 2.94 times higher risk of developing diabetes than female subjects (95% CI [1.44 - 5.88]).

Our study reveals a significant association between age and the incidence of diabetes among adults in the Kpomassè community. Individuals over the age of 40 are 3.15 times more likely to develop diabetes (95% CI [1.40 - 7.07]) compared to those who are 40 years or younger. This finding can be attributed to both biological and lifestyle factors associated with aging. From a biological perspective, physiological aging, particularly after the age of 40 - 45, leads to the development of insulin resistance. This resistance is often aggravated in individuals with excess adipose tissue, overweight, or obesity. The cells gradually become resistant to insulin, impairing its effective role, and subsequently, blood glucose levels rise. In response, the pancreas increases insulin production. Nevertheless, after 10 to 20 years, the pancreas struggles to keep up with the demand due to sustained insulin resistance and eventually becomes exhausted, failing to produce adequate insulin to manage blood glucose levels [29] . Still on a biological level, in our study, there is a significant statistical link between age and BMI (p = 0.001). Among overweight subjects, 70.51% are over 40 years old. Likewise among obese subjects, 69.39% are over 40 years old. There is also a significant statistical link between age and waist circumference (p = 0.011). Among subjects with abdominal obesity, 66.40% are over 40 years old. On the behavioral front, aging is often accompanied by the adoption of riskier behaviors such as increased sedentariness, decreased physical activity, and the consumption of certain substances. In our study, sedentary lifestyle and age are statistically associated. Adults over 40 are more sedentary than those aged 40 and under. In addition, there is an association between tobacco consumption and age in our study (p = 0.004). Among those who use tobacco, 89.47% are over 40 years old.

Similar findings were observed by Elegbede et al. in Nigeria in 2019 [30] , and Kingori et al. in Kenya in 2019 [31] , where age above 40 was statistically linked to the onset of diabetes.

Our research revealed a significant correlation between sleep duration and the onset of diabetes. Specifically, adults who experienced short sleep durations (<7 hours) exhibited a 2.30 times higher risk (95% CI [1.11 - 4.75]) of developing diabetes compared to those with normal sleep durations (7 to 9 hours). Sleep deprivation or short sleep duration, defined as less than seven hours, increases appetite by affecting appetite-regulating hormones such as leptin, ghrelin, and orexin. This increase in food intake, along with fatigue and daytime sleepiness, leads to reduced energy expenditure during waking hours, thereby heightening the risk of weight gain. Furthermore, a decrease in sleep duration disrupts the circadian rhythm, which controls the synthesis of key hormones like cortisol and growth hormone, both critical to glucose metabolism. This disruption fosters glucose intolerance and gradually contributes to the development of type 2 diabetes, independent of weight gain [32] - [34] . The short sleep duration within the population of Kpomassè can be explained by lifestyle as well as concerns related to lack of money which are a source of permanent stress. Indeed, in the study population, 39.94% were stressed and 89.69% had an average monthly income of less than 52,000 CFA francs.

Our findings align with those of Dovonou et al. in Benin (2021), who demonstrated that abnormal daily sleep duration was statistically associated with the onset of diabetes (p = 0.03; OR: 5.09) [18] .

Our study indicates a significant association between the consumption of fried foods and the incidence of diabetes in adults residing in the commune of Kpomassè. Specifically, individuals who consumed fried foods daily, as well as those who consumed them at least two to three times a week but not daily, exhibited a heightened risk of developing diabetes. The relative risk for daily consumers was 4.14 times (95% CI [1.18 - 14.48]), and for those consuming fried foods two to three times weekly, the risk was 2.73 times (95% CI [1.14 - 6.53]), compared to those who ate these foods no more than once a week. Fried foods are typically high in saturated fats and empty calories, contributors to obesity and insulin resistance, both of which are well-established risk factors for type 2 diabetes [35] . In the commune of Kpomassè, the consumption of fried foods can be explained, among other things, by cultural traditions, taste and texture, and availability of foods. These elements could interact to influence eating behaviors.

These findings are consistent with the results of Cahill et al. (2014), which demonstrated a significant association between frequent consumption of fried foods and an increased risk of developing type 2 diabetes. Their study found that the association was stronger for fried food consumption outside the home [OR: 1.81 (95% CI: 1.58 - 2.08)] compared to at-home consumption [OR: 1.26 (95% CI: 1.09 - 1.47)] [36] .

Health system factors were not fully analyzed due to the fact that all participants surveyed indicated that they had never benefited from nutrition education, non-communicable disease (NCD) awareness or systematic screening for diabetes risk. This situation is attributable to the lack of effective implementation of the new 2018-2022 community health policy and the failure to implement the WHO-PEN program in the commune, due to financial constraints. For a more in-depth assessment, further studies could be envisaged to analyze the impact of these elements on the Kpomassè population, in comparison with currently available data.

NB: Measurements and blood sugar levels will be taken at the end of the exchange.