Introduction

Malaria is a fatal but preventable and curable parasitic disease that is widespread throughout the world, with a major impact on global public health and the economic development of affected countries [1, 2]. Globally, there were an estimated 247 million cases and 619,000 deaths from malaria in 2021, and the number of malaria cases continue to rise between 2020 and 2021, showing a trend that could complicate the achievement of malaria control targets in 2030 [1]. It is widespread in tropical and subtropical regions, particularly in Africa and South-East Asia [2, 3]. The African region disproportionately bears the greatest global burden of malaria, with respectively 234 million cases (95%) and 593,000 deaths (96%) due to the disease worldwide in 2021 [1, 4]. Africa remains the region most affected by this deadly disease, partly because too many people lack access to preventive measures and treatment [1]. Malaria continues to take a heavy toll on the health, economic and social development and livelihoods of populations since malaria transmission is endemic in most low- and middleincome settings particularly in many African countries [2, 4-6]. Yet the use of impregnated mosquito nets has been shown to be more likely to break the malaria transmission cycle in endemic countries [7]. Indeed, insecticide-treated nets (ITNs), and more particularly long-lasting insecticide-treated nets (LLINs), are known to be highly effective in reducing malaria morbidity and mortality [8-10]. The World Health Organization (WHO) recommends achieving high coverage rates of long-lasting insecticide-treated nets in endemic areas through free or heavily subsidized distribution of LLINs, in order to maximize the effectiveness of malaria control programs [7, 9, 11]. However, achieving universal coverage and use of LLINs remains a challenge on the African continent, due to the socio-economic context that influences household behavior and vulnerable groups such as pregnant women and children under five [12-14].

In Cameroon, malaria is the most widespread endemic disease, responsible for few millions reported cases and absenteeism from school and work annually [15]. Cameroon population at risk of malaria is estimated at 27,795,843 inhabitants in 2022 with an incidence rate of 113.4 per 1,000 population and a prevalence rate of 24% among children under five years [16-18]. Thus, Cameroon is among the fifteen countries most affected by malaria, with 3% of all malaria cases worldwide and 3% of malaria deaths in 2019, this makes it the third most affected country in Central Africa with 12.7% of cases [19]. Cameroon’s health services reported 3,327,381 cases of malaria representing about 29.6% of all consultations nationwide in 2022 [20, 21]. The goal of Cameroon’s current National Strategic Plan (NSP) for malaria control 2019-2023 is to contribute to improving the people welfare by reducing the health, economic and social burden of malaria nationwide through effective prevention and case management [15, 22]. Prevention includes ITN distribution via mass campaigns and routine channels, promotion of ITN use, IPTp, seasonal malaria chemoprevention (SMC) for children 3 to 59 months of age. The routine ITN distribution strategy expands beyond distribution to pregnant women through ANC to include the Expanded Program for Immunization platform for children under five years [22].

Some studies have shown that LLINs are currently a fundamental tool for protection against mosquito bites and malaria transmission, particularly among women and children under five, the group most at risk of the disease [23-26]. Other studies have focused on the socio-demographic determinants of ITN use [19], showing that economic and socio-behavioural factors, such as perceived susceptibility to malaria, knowledge of ITNs and attitude towards ITNs, which may favour non-use of ITNs, need to be further investigated [27, 28]. Indeed, both coverage and appropriate ITN utilization is important for malaria prevention since either some of the ITNs that are owned by a household can be left unused or even those that are utilized were not given priority for the needy members of the households such as women and children and utilization cannot be consistent [29, 30]. Numerous other studies have concluded that the economic and social status of the individual is associated with levels of malaria preventive practice in the community [31-34]. Although some researches on ITN utilization have been carried out in many settings, almost all of them have focused on utilization alone rather than factors associated with the demand for ITN utilization [35-38].

In Cameroon, to best of our knowledge there was no previous study on economic and social determinants of ITNs utilization among pregnant women in study area. Therefore, the findings of study will be helpful for policy makers and the partners to recommend and redesign appropriate vector control interventions or used to improve women’s demand for ITNs utilization in the country. Thus, this study aimed to assess the economic and social determinants of women’s demand for insecticide-treated mosquito nets in Cameroon.

Methods

This study used population-level secondary data based on the fifth Cameroon Demographic and Health Survey (DHS-V) [18] to analyze the economic and social determinants of women’s demand for ITN in Cameroon. DHS-V data were obtained from ICF International Macro Demographic and Health Surveys through online registration and a formal request for access to the dataset. Additional authorization was requested from the Ministry of Public Health and the National Institute of Statistics of Cameroon. The study covered a total sample of 9,733 women from households nationwide. The data analysis adopted a logistic regression model where the dependent variable is a binary indicator “demand for ITNs” which indicates whether women of childbearing age have demanded ITNs for use in malaria prevention. The independent variables are a set of economic and social indicators with 2 or more modalities. The model therefore constructs a binary logistic model to estimate the probability of a binary response as a function of a set of predictor variables. The set of independent variables includes the woman’s characteristics. Our dependent variable “demand for ITNs” is defined as follows:

The multivariate logistic regression model inspired by the work of other authors [6, 19] was used to assess the determinants of women’s demand for ITNs according to a set of economic, social and demographic indicators that may influence demand for ITNs for use in malaria control.

The model to be estimated can be written as follows:

With the following detailed specifications:

Where:

 is a vector of coefficients for the model to be estimated, 

is the constant term and  is the error term.

Therefore,

 are coefficients of the model to be estimated and  is the error term

   is a set of economic and social factors that can influence the demand for ITNs:  

 : Woman age at child’s birth(years) i;

 : Education level of the woman i;

 : Education level of the husband i;

 : Marital status of the woman i;

 : Employment status of the woman i;

 : Religion of the woman i;

 : Economic welfare status of the woman i;

 : Accessibility to media by the woman i;

 : Domestic‘s violence on the woman i;

 : Antenatal care attendance by the woman i;

 : Region of residence the woman i;

 : Residence area of the woman i

Data analysis was performed in Excel and Stata software (version 14). Odds ratios were calculated. The data of this study were initially analysed on the basis of descriptive statistics and the Chi2 dependence test. This technique provided an initial view of the level of association between woman’s demand for ITNs and the economic and social determinants. The data analysis used two techniques: descriptive analysis (bivariate and multivariate) and multivariate explanatory analysis. Different associations were made and the results were considered statistically significant at a 95% confidence level with p<0.05.

Results Socioeconomic and demographic characteristics of women

The study involved a total sample of 9,733 women throughout the country. Table 1 presents the socio-economic and demographic characteristics of the women, with a bivariate analysis of their demand for ITNs in Cameroon. It shows that the majority (75.92%) of women had not expressed a demand for ITNs, compared with only 28.8% of women who had demanded ITNs. The majority (49.02%) of women were in the 25-34 age bracket, followed by the 15-24 age bracket (31.84%) and finally the 35-49 age bracket (19.14%), whose ITN demand levels were 11.93%, 8.21% and 3.95% respectively, with a statistically significant difference between the different age groups (p<0.00). The majority of women had secondary education (38.50%), followed by women with primary education (33.29%), women with no education (23.08%) and finally women with higher education (5.14%), whose ITN demand levels were 12.49%, 8.23%, 1.26% and 2.10% respectively, with a statistically significant difference between the different education levels (p<0.00). The majority of spouses of the women in our sample had secondary education (35.40%), followed by spouses with primary education (32.99%), spouses with no education (20.75%) and finally spouses with higher education (7.71%). Here, ITN demand levels are 10.37%, 7.94%, 0.95% and 2.89% respectively, with statistically significant difference between the different education levels (p<0.00). The results show that 80.97% of the women were married, of whom only 5.54% expressed demand for ITNs, compared with 18.55% of single women (p<0.00). The majority of women (55.64%) lived in rural areas, with 10.20% of women demanding ITNs versus

13.88% of women in urban areas (p<0.00). We also note that 67.51% of women were employed, 17.37% of whom demanded ITNs, compared with 6.71% of unemployed women (p<0.00).

The majority of women practiced the Christian religion (70.39%), followed by Muslim women (26.09%), and animists, “no religion” and women of other religions made up 3.52% of our sample; ITN demand levels were 20.48%, 3.20% and 0.41% respectively (p<0.00). The poorest and poor women constituted 18.48% and 23.49% respectively, while 23.95% belonged to the medium wealth status and 19.47% and 14.52% belonged to the richer and richest status respectively. ITN demand levels of 1.66% and 4.89% among the poorest and poor women, respectively, and 6.40%, 5.51% and 5.62% among the middle-class, riche and richest, respectively, were also noted in these classes, with a statistically significant difference between the different quintiles of economic well-being or wealth (p<0.00). Some 84.05% of the women in the sample had no access to the media and recorded an ITN demand level of 17.91%, compared with 6.17% among women who did have access to the media and expressed a demand for ITNs (p<0.00). Approximately 76.42% of women in the sample were not exposed to domestic violence against women and recorded an ITN demand level of 18.09% versus 22.97% of women who were exposed to domestic violence with an ITN demand level of 5.92% (p<0.01). Some 89.30% of women had had an antenatal consultation at a health center, compared with 10.70% at a traditional birth attendant, with ITN demand levels of 22.22% and 1.86% respectively (p<0.00).  A majority of women (18.92%) were from the Central region, followed by women from the Far North region (13.35%), the North (12.50%) and at the bottom of the table the North-West regions (4.86%). Demand for ITNs varied between 0.55% and 6.02%, across the country’s ten regions, with a statistically significant difference (p<0.00).

Logistic Regression Results for the ITN Demand Function

The results of the logistic regression of the ITN demand function are presented in Table 2. These results show that a woman’s age is an important determinant of ITN demand. Indeed, compared to women in the 15-24 age group, women in the 2534 and 35-49 age groups were respectively 0.9 and 0.8 times less likely (OR=0.96 and 0.83 respectively; P<0.05) to demand ITN than women in the 15-24 age group, with a statistically significant difference in ITN demand between the different age groups (p<0.05).  Women with primary, secondary and tertiary education were 2; 2.6; 3.1 times more likely to demand ITNs (p<0.01) than women with no education. Women having husbands with primary, secondary and tertiary levels of education were 2.2; 1.9; 1.8 times more likely to demand ITNs (p<0.01) than wives of husbands with no education. The results also show that women who were exposed to domestic violence if the woman neglected the use ITNs were 1.2 times more likely (p<0.05) to demand ITNs than women who were not exposed. Single women were about 1.4 times more likely (P>0.1) to demand ITNs than married women.  Muslim, animist, no religion and other religion women were respectively 0.7 and 0.5 times less likely (p<0.05) to request ITNs than Christian women of all faiths. Women living in rural areas were 1.7 times more likely (p<0.05) to request ITNs than women living in urban areas.

Table 2: Logit Estimation of the Demand Function for ITN by Women