Mothers’ Exposure to the Media and Its Effect on Child Health in Cameroon

Fuein Vera Kum; Ofeh Evina Anchi; Lucy Ajubeseh

doi:doi:10.11648/j.hep.20261101.11

Research Article |

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Mothers’ Exposure to the Media and Its Effect on Child Health in Cameroon

Fuein Vera Kum^*

, Ofeh Evina Anchi

, Lucy Ajubeseh

Published in International Journal of Health Economics and Policy (Volume 11, Issue 1)

Received: 5 December 2025 Accepted: 23 December 2025 Published: 19 January 2026

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Abstract

The purpose of this study was to investigate the determinants of mothers’ exposure to the media and examine its effect on child health in Cameroon. Data was obtained through a survey from the Cameroonian Demographic and Health survey (CDHS) 2018. The study employed a Probit regression to examine the determinants of mothers’ exposure to the media and its effect on child health in Cameroon. The results from this analysis revealed that, an increase in the household membership negatively and significantly affects mothers’ exposure to the media for those having a Television (-0.0391) and those having mobile phones (-0.0426). Also, those living in the rural area with regards to place of residence shows a positive significant effect (0.7689) as concerns television ownership and a negative significant effect (-0.3404) for mobile phone ownership. Households having electricity depicts a significant negative and positive effect respectively with regards to television (-1.0727) and mobile phone (0.6185) ownership. Being more educated as per the different categories of education shows a positive statistically significant effect on mother’s exposure to the media as compared to not being educated for both television and mobile phone ownership. The results equally revealed that, the frequency of listening to the radio and watching a television more than once a week had a positive effect on child’s health as compared to not listening to the radio or watching Television at all (0.113 and 0.495 respectively), though statistically significant only for watching television. The frequent use of the internet (at least once a week) had a positive statistically significant effect on child’s health in Cameroon at 10%, with a coefficient of 0.337. From the results, we recommend that, the government should prioritize improving access to electricity in households across Cameroon, especially in underserved areas and also implement programs that promote maternal education and media literacy to increase awareness of health-related media messages.

Published in	International Journal of Health Economics and Policy (Volume 11, Issue 1)
DOI	10.11648/j.hep.20261101.11
Page(s)	1-16
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2026. Published by Science Publishing Group

Keywords

Cameroon, Child Health, Media, Mothers’ Exposure

1. Introduction

The mass media in any society within which they function play roles that are germane to the development of that society, and of the members within the society, thus creating a social ecosystem that in turn impinges on the operations of the mass media. Mass media, as the phrase implies, are mass-based pathways to reaching a mass audience that comprises people of varying backgrounds, who need the media to keep up with the pace of events around them. There is an ‘umbilical cord’ relationship between the mass media and society. Scholars interested in media-enhanced socio-economic development agree that there is a causal relationship between the mass media (radio, Television -TV, newspapers and magazines as well as other associated platforms for mass-based engagements and interactions) and the society

[41, 48]

With the introduction of the Sustainable Development Goal (SDG) framework in 2015, the international community reaffirmed its commitment to enhance child development and put an end to needless child deaths (United Nations-UN, 2022). Though global development has been uneven, children today have a higher chance of surviving than they had twenty years ago. According to the most recent projections, in order to meet the third (3) SDG target of bringing the mortality rate of children under five years old down to at least 25 per 1000 livebirths by 2030, 54 of the 193 UN member nations will need to take urgent action (UN Inter-agency Group for Child Mortality Estimation- IGCME, 2022). Sub-Saharan Africa and central and southern Asia are home to the majority of these nations.

Health is a consumer good that individuals demand and consume to increase their utility and overall well-being

[27]

. Good health is globally recognized as a fundamental human right for all (World Health Organization-WHO, 2017). A healthy and well-informed population serves as assurance to the country’s growth and development, reason why the WHO has the universal health coverage as its first goal with the tagline of health for all, everyone everywhere. (World Health Day, 2019). The United Nations International Children’s Emergency Fund (UNICEF’s 2016-2030) strategy for health highlights that media will likely play a key role in demand generator, social and behaviour change, community engagement and social accountability efforts to improve maternal, newborn and child health outcomes. Hence UNICEF’s use of technology and social media will likely play a key role in this age group, given their growing reach and penetration globally.

In recent times, there have also been initiatives involving the utilization of mass media campaigns to achieve wide coverage towards attainment of improved well-being

[31]

. Communication is a vital component of healthcare delivery. It has long been invaluable in health promotion which, in the last few decades of the 20^th century, became a critical part of public healthcare delivery programs

[13, 16, 21]

. In a bid to tackle varying health concerns, the Nigerian government and other nations across the globe had resorted to the utilization of communication campaigns to reach out to the public with the aim of influencing their engagement in desired health practices. Specifically, several governments have resorted to the use of communication campaigns through the mass media to reach out to the people, with the main purpose of influencing them into carrying out desired healthy practices

[9, 13, 21]

Mass media promotes health through two key strategies. These strategies are reaching a wide audience across different boundaries at the same time and by exposing the public to specific messages that influence public belief, attitude and behavior

[56]

. Awareness creation through mass media has the potential to encourage positive behaviors and discourage negative health-related behaviors through direct and indirect pathways. Television and radio are the widely used media for creating awareness among a larger audience in SSA; nevertheless, print media such as magazine and newspaper, and outdoor media such as billboards and posters have also proven to be effective

[19, 36]

. Mass media is shown to be an effective medium of reaching mothers at a large scale to enhance their utilization of maternal health services, especially in developing countries. For example, women who read newspapers or reported watching television in Bangladesh were almost three times more likely to utilize a maternal health service

[4]

In Cameroon, efforts have been made by the government to improve media platforms (radios, televisions, newspaper print) over the years. This has made great impact on mother’s exposure to the media. Improving from single sources of information from the national stations on radio and television, towards private stations has widened the scope of mother’s exposure to the media. Formally the CRTV was the only channel through which information was passed out to the population in all the ten regions of Cameroon, with de-regulation, private channels now exist and information and programs on child health nutrition and vaccines are advertised through this radio, television channels repeatedly such that even in the neighborhood information on certain health talks could be gotten by mothers especially.

Cameroon’s inclusion with UNICEF has helped support its Water Sanitation and Hygiene (WASH) awareness, raising campaigns in the channels like radio, television and the internet to disseminate information. These wash campaigns have been shown to improve household health and reduce water related illnesses. Thereby, reducing expenses and frequent visit to the hospital. Studies conducted in various African countries have shown that media exposure can shape diverse aspects of health outcomes, including nutrition, immunization, and mental well-being, as is the aim of UNICEF. As such, media exposure and socio-economic factors have become very crucial in either facilitating or inhibiting the realization of health policies

[5]

. Also creating awareness and sensitization through the media third can help the attainment of the third (3) SDG target which is that of bringing the mortality rate of children under five years old down to at least 25 per 1000 livebirths by 2030.

Cameroon is one of such African countries where health policies have been designed and implemented with the goal to improve on community health outcomes. However, the combined effects of the economic crisis of the mid 1980s and the liberal and market-based programs resulted in a significant reduction of social programs and public interventions that negatively affected the country’s social structure, including the health sector

[44, 46]

. However, after regaining macroeconomic stability, and attaining the completion point of the Highly Indebted Poor Countries Initiative in the mid-2000s, the country engaged the 2001-2015 health sector strategy which was aimed at strengthening health districts, reducing morbidity, decreasing maternal and child mortality, and improving inter-sectoral management for health.

This strategy was closely followed by the 2016-2020 National Health Development Plan (NHDP) which was to serve like a continuation of the former by ensuring health promotion, disease prevention, case management; strengthening of the health system and governance and strategic steering. In the wake of the unanimous endorsement of the World Health Assembly Resolution on Digital Health by Member States in May 2018, highlighting the value of digital technologies in contributing to the advancement of universal health coverage, ministries of health were urged to take stock of their use of digital technologies for health, including health information systems at the national and subnational levels. Cameroon adopted two approaches to operationalize digital health activities in Cameroon: a desk study and an interactive exchange between key players in the health system.

A cross examination of the effectiveness of the digital approach to health care management would bring to the lamplight some challenges that are peculiar of it. According to the authors, such challenges include health communication problems, and interaction issues between patients and physicians

[7].

Others such as resistance of medical professionals to the adoption of new technologies as most of the health professionals have imagined that some clinical processes are at risk when they use new technologies

[29]

. Yet other possible challenges include Misinformation, Cyberbullying, Patient privacy concerns, Distraction and inadequate exposure to media.

Taking the challenge of inadequate exposure to media, it can be observed that Cameroon has a diverse population with varying socioeconomic and cultural backgrounds, which may influence the impact of media exposure on child health

[44]

. Understanding this relationship is crucial for informing policies and interventions aimed at promoting child health and well-being in the country. In addition, the Cameroon government incurred high cost in immunization for children amounting to about $12.73 per child which required approximately $147,668 thousand dollars for the entire population highlighting a significant gap in understanding this important issue

[44, 51]

. Also, the motivation of community health workers which are still insufficient, adds up to cost if the effect on child health is not felt to the utmost.

Given the rapid technological advancements and increasing media penetration in the country which tries to improve internet coverage, harmonize different cultures, and reduce the huge urban-rural gap as compared to the high broadband access and urban-rural parity in developed countries; the crucial role that mothers have to play in managing child welfare since they are looked upon to be more of caregivers associated to the home; as well as the need to enforce a healthy uprising human capital for inclusive growth, it is essential to investigate how maternal exposure to various media platforms may be influencing child health outcomes in Cameroon

[5, 37]

. It is therefore important first to understand mother’s exposure as to what influences them, to avoid bias and have a good causal inference for specific targets and interventions. Identifying therefore the specific pathways through which maternal media exposure impacts child health can inform the development of targeted interventions and policies aimed at promoting child well-being in the country

[12, 26]

. Therefore, this study aims to address the gap in the literature by investigating the effect of mother ’s exposure to the media on child health in Cameroon, considering the broader socioeconomic and cultural context.

2. Literature Review

Exposure refers to the extent and nature of an individual's contact with a particular stimulus, such as media content or environmental factors

[6, 44]

. In the context of maternal media exposure, exposure is often conceptualized as the degree to which mothers engage with and are influenced by various media platforms including television, radio, print, and digital platforms

[12, 25, 38, 47]

. Scholars have conceptualized mothers’ media exposure as a multidimensional construct, encompassing factors such as the frequency, duration, and content of media consumption

[12, 25]

Media refers to the various channels, platforms, and technologies used for communication, dissemination of information, and entertainment. It encompasses a wide range of formats, including traditional media such as newspapers, radio, and television, that are characterized by one-way communication, and content is created by a few but consumed by many

[17]

. The traditional media could be termed print media (newspapers, magazines) or broadcast media with audio-visual content

[32, 49]

. Together with digital media like websites, social media, and streaming services (Netflix, Youtube, …), they all play a crucial role in shaping public opinion, informing society, and facilitating dialogue on a global scale

[39]

Health can also be defined in other disciplines in the following ways: in medicine: "Health is a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity. Psychologically, "Health is a state of optimal well-being where individuals realize their own abilities, can cope with the normal stresses of life, work productively, and contribute to their community"

[58]

. Economists define health in terms of its economic implications and consider it both as a consumer good and a capital good. As a consumer good, health is viewed as a product or service that individuals demand and consume to improve their well-being. It is considered a valuable commodity that individuals are willing to invest in to maintain or enhance their physical and mental well-being

[29]

. On the other hand, health is also seen as a capital good, as it is an investment that yields future benefits and contributes to long-term economic growth. A healthy population can be more productive, leading to increased human capital and economic development

[22]

The intersection of media and child health is a complex area of research that has evolved over the years. Some authors highlight how media exposure can impact children's health behaviors, body image, and mental health outcomes conversely to others that suggest that media can also serve as a platform for health promotion and education when used strategically

[10]

. Child health is a multidimensional concept that encompasses the physical, mental, emotional, and social well-being of children

[12, 51]

. Scholars have defined child health as the overall state of a child's physical, cognitive, and psychosocial development, including factors such as growth, nutrition, disease prevention, and emotional and behavioral functioning

[38, 47]

. The definition of child health has evolved to recognize the importance of environmental, social, and cultural factors in shaping children's overall well-being

[6]

. Several theories in literature explain these concepts better.

The Health Belief Model introduced in the 1950s, remains today one of the most widely applied conceptual frameworks of health behavior used by health educators, other health professionals, and psychologists

[50]

. At the time there were medical diagnostic tools such as chest x-rays for tuberculosis (TB) screening that were underused. There was a parallel need to increase use of preventive services such as immunization and medical adherence in general, in addition to health screening. At the beginning, the Health Belief Model was rooted in information-giving to increase people’s awareness of and concern about the serious health risks associated with certain preventable illnesses, including illnesses that could be cured if caught early enough. Health educators also wanted people to understand that they could reduce these health risks by taking certain actions. The (primarily) psychologists theorized that people are afraid of getting serious illnesses, and that health-related behaviors reflect both a person’s level of fear of perceived health threats and the expected fear-reduction potential of taking a recommended action

[43]

. The Health Belief Model can also help identify leverage points for change. A smoker who may not think he is capable of quitting on his own i.e., who has low self-efficacy can be coached on proven ways to quit and encouraged to enroll in a supportive smoking-cessation program

[23]

. The Health Belief Model of behavioral change was later categorized as individual centered. They assume that people are rational and will do the right thing once they are provided adequate information and understand that change is in their personal self-interest. This could be evidenced from the recent COVID-19 or Poliomylities outbreaks where vaccination is encouraged but needs perceived susceptibility, severity, benefits, barriers and self-efficiency which could be enhanced through the media.

The Grossman ideal of health investment is a well-known economic model that explains the relationship between health, education, and labour market outcomes. It was first introduced by Michael Grossman in his 1972 paper on the " Concept of Health Capital and the Demand for Health." According to the Grossman model, individuals make investments in both health and education that increase their future productiveness and earnings potential. Grossman posits that education and health are complementary investments and that education leads to better health outcomes and better health leads to elevated levels of education

[28]

. Thus the general aim of reducing child mortality that endangers future human capital needs to be enforced

[55]

Numerous authors have developed and altered the Grossman model over time. For instance, some argued that people's judgments on health investments are dependent on their existing and potential addictions to unhealthy habits like smoking or drinking

[34, 35]

. Some suggested another alteration to the Grossman model by introducing the idea of subjective health expectations

[32]

. They suggested that people make commitments about their health investments based on both their subjective expectations for how their health would develop in the future and their current state of health. The Grossman model has some drawbacks, according to its detractors. For instance, the model makes the assumption that everyone has equal access to resources for health and education, which is not necessarily the case in reality. In addition, the model fails to take into consideration how social and cultural variables affect choices about health and education. It implies that increasing contributions in health and education can enhance employment market outcomes for both women and may aid in child health in Cameroon.

Grossman in the preventive health theory introduces the concept of health capital and develops a theoretical framework to analyze the demand for health and the role of preventive care. He argues that individuals can invest in their health capital through activities such as preventive care, which can reduce the probability of illness and improve overall health outcomes

[24]

. The theory assumes that preventive care measures, such as screenings, vaccinations, lifestyle interventions, and health education, can effectively reduce the risk of developing certain diseases or conditions. The theory also assumes that individuals have a preference for current health and well-being over future health benefits. It recognizes that investing in preventive care may involve upfront costs or efforts that individuals may be reluctant to undertake if they do not immediately perceive the benefits.

The preventive theory is widely applied in public health initiatives aimed at promoting population health and preventing diseases. This includes initiatives such as immunization programs, health education campaigns, screenings, and early detection programs with the aim to reduce the incidence and impact of diseases within communities

[37]

. However, over diagnosis and Overtreatment raise critics about the potential of these services in preventive care. Over diagnosis occurs when individuals are diagnosed with conditions that may never cause symptoms or harm, leading to unnecessary medical interventions. Overtreatment refers to the administration of medical treatments or procedures that may not provide significant benefits but come with potential risks and costs. Critics argue that an overemphasis on preventive care may lead to over diagnosis and overtreatment, resulting in unnecessary burdens on patients and healthcare systems. Thus the call for a more cautious approach to preventive care, ensuring that interventions are targeted to those who are most likely to benefit

[30]

. Moynihan and Doust discuss the potential harms of over diagnosis and argue for a shift in the approach to preventive care. They suggest that the focus should be on identifying and targeting interventions to individuals at higher risk, rather than implementing broad-based screening programs. The authors advocate for a more nuanced understanding of the benefits and harms of preventive care, considering the potential for over diagnosis and overtreatment

[42]

With regards to communication, the Uses and Gratifications Theory suggests that individuals choose media content that fulfills specific needs or goals, such as information, personal identity, entertainment, or social interaction. This theory posits that audiences are active participants in consuming media and are not just passive receivers. The origin of the Uses and Gratifications Theory can be traced back to early studies in the 1940s and 1950s, but it was popularized in the 1970s by communication scholars

[57]

titled "Utilization of Mass Communication by the Individual," which laid the foundation for the Uses and Gratifications Theory. The Cultivation Theory developed by George Gerbner in the late 1960s on its part proposed that heavy television viewing systematically cultivates perceptions of social reality. According to the theory, television is thought to cultivate attitudes, values and beliefs through repeated exposure over time rather than through any one exposure. Gradually, the more time people spend watching television, the more likely they are to believe social reality aligns with what they observe on television

[24]

. Thus, information related to child health can easily be passed on to viewers with a frequency in watching television in the case of Nigeria

[52]

and

[1]

The study highlighted the pervasive nature of media exposure among mothers and its potential impact on parenting practices and child health outcomes

[14, 33]

. The findings suggested that maternal exposure to media, especially concerning health-related information, could influence parental decisions and behaviors that impact child health. Another study explored the link between maternal media use and child behavior

[24]

. The study found that mothers who spent more time engaging with media had children with higher rates of behavioral problems. This indicates a potential negative association between maternal media exposure and child health outcomes. Furthermore, the study delved into the influence of social media on maternal perceptions of child health

5, 52]. The researchers found that mothers who frequently accessed social media platforms were more likely to experience heightened anxiety about their child's health, potentially leading to over-utilization of healthcare services.

According to the study, mothers in countries like France and Germany are frequent consumers of health-related information through various media channels, including television, radio, and the internet

[53]

. This exposure has been associated with increased awareness of child health issues and higher rates of seeking preventive healthcare services. In the UK highlighted the significant role of social media in shaping maternal perceptions and behaviors related to child health

[14]

. The study found that mothers who actively engaged with health-related content on platforms like Facebook and Instagram were more likely to follow recommended practices for child nutrition and immunization. Collaborative research efforts in Europe have also explored the broader implications of media exposure on maternal and child health. The EU-funded project aimed to assess the effectiveness of public health campaigns disseminated through mass media channels in improving maternal knowledge and behaviors across multiple European countries. The project's findings underscored the need for targeted communication strategies that take into account cultural and regional variations in media consumption patterns.

In Africa, some researchers demonstrated the impact of community radio programs on maternal health-seeking behaviors and child health outcomes. The study highlighted how targeted media interventions tailored to local contexts can effectively empower mothers with essential health information and promote positive health practices within communities

[20]

. The study in Nigeria revealed that mothers who frequently accessed health information through television and radio were more likely to adopt appropriate feeding practices and seek timely healthcare for their children

[1]

. Similarly, a survey conducted in Ethiopia found a positive association between maternal exposure to health-related messages on social media platforms and improved child vaccination rates

[8]

The use of mass media by mothers and its association with their children’s early development was assessed: and a comparison between urban and rural areas was done

[32]

. This study examined the association between the use of five types of mass media among mothers living in rural and urban areas and the early childhood development (ECD) of their children. Methods they analysed nationally representative and internationally standardized Multiple Indicator Cluster Survey data collected in 2013 and 2019 in Bangladesh. The ECD was calculated using four domains of development: physical health, literacy-numeracy, learning and social-emotional. Mothers’ use of newspapers/magazines, radio, television, internet and mobile phones was the study factor. They used Poisson regression with robust variance. Mobile phones and television were the dominant types of media, both in terms of the number of users and the frequency of use. Overall, 68.87% of the children were on track in terms of their ECD and 31.13% were not. A significantly larger proportion of urban children (74.23%) than rural children (67.47%) were on track in their ECD. The prevalence of children being on track of ECD increases by 4% (a PR 1.04; 95%CI: 1.01–1.06) for each additional media use among women who lived in urban areas and increases by 7% if women live in rural areas.

The impact of radio programs on maternal health practices in rural communities of Cameroon was examined

[45]

. The study revealed that mothers who regularly listened to health-related radio broadcasts demonstrated increased knowledge about preventive health measures for children, leading to improved immunization rates and decreased incidences of common childhood illnesses. These findings highlight the potential of radio as a widely accessible medium for disseminating health information to remote populations in Cameroon.

The role of social media platforms in influencing maternal perceptions of child health in urban areas of Cameroon was explored

[54]

. The research indicated that mothers who engaged with health content on social media demonstrated higher levels of awareness about child nutrition, hygiene practices, and disease prevention strategies. This suggests that leveraging digital platforms can be an effective way to reach urban mothers and promote positive health behaviors within communities.

While there is a scarcity of specific studies focusing on this topic in Cameroon, existing research (

[31, 11, 34 , 21, 40, 2-4]

) provides valuable insights into the potential effects of media on maternal knowledge, attitudes, and behaviors regarding child health but very little like

[45]

and

[54]

has been done with regard to mothers exposure to the media and child health in Cameroon and thus the reason for this work. They focus only on the radio and social media respectively. However, this study first looks into the determinants of mothers’ media exposure for better policy implications, given the upsurge in technology. Also, the use of the most recent adopted and advised anthropometric measure- WHZ (Weight for Height Z-score) for child health by the WHO is used as compared to BMI, HAZ and WAZ used by different authors.

After reviewing the host of methodologies employed by different authors such as the Multivariate logistic regressions that brings out odds ratios

[4]

); Weighting, Multilevel mixed-effect models accounting for cluster-level variations and correct inferences, Fixed and random effects estimates

[2]

; a descriptive cross-sectional design

[40]

; Poisson regression with robust variance

[32]

, this study employs the Probit regression given the binary nature of the dependent variable in each case (mothers’ exposure and child health).

3. Methodology

This study employs the causal and an ex-post research design. It makes use of secondary data from the 2018 Cameroonian Demographic and Health survey (CDHS). The Cameroonian Demographic and Health Survey (DHS) is a nationally representative survey that provides comprehensive data on various health indicators, including maternal and child health, reproductive health, and household characteristics. The survey collects information from a large sample of households across different regions of Cameroon, offering valuable insights into the population's health status and healthcare utilization.

This rich dataset conducted by the National Institute of Statistics (NIS) of Cameroon in collaboration with The International Classification of Functioning, Disability and Health (ICF) International allows researchers to investigate the relationship between mother's exposure to the media and child health outcomes in Cameroon, considering factors such as maternal education, household wealth, access to healthcare services, and media consumption habits. The data collection methodology involved a multistage sampling design, where clusters were selected systematically from all regions of Cameroon. Within each cluster, households were randomly selected to participate in the survey, and eligible women of reproductive age were identified for interviews. Information was collected through face-to-face interviews using structured questionnaires administered by trained surveyors. The survey questionnaire covered a wide range of topics related to maternal and child health, healthcare utilization, family planning, nutrition, and socio-economic factors. Data on media exposure, including television viewing habits, radio listening patterns, and internet usage, were also captured to analyze the influence of media on maternal behaviors and child health outcomes.

In the context of analyzing mother’s exposure to the media on child health in Cameroon, a binary probit model was specified to estimate mother’s exposure to the media and child health in Cameroon given the dependent variable had a binary outcome. The binary probit model is a regression model that estimates the probability of an event occurring. It assumes a linear relationship between the independent variables and the outcome of the event.

P(Y=1)=Φ(β0+β1X1+β2X2+…+βkXk)(1)

We specify two models below with respect to the determinants of mother’s exposure to the Media (MEM) and then the effect on child health as follows: first, mother’s exposure to the media is captured with the possession of a Television and a Mobile Phone. Mother’s exposure to the media is 0/1 variable. 1 for watching television (TV) and using a phone (Mph), and 0 other wise. These two aspects alone (TV and Mph) are used to evaluate the determinants because they both have a visual impact that is more practically enhancing and makes the world more of global village.

Probit ({MEM}_{k})

β_{0} + β_{2} {HseMem}_{i} + β_{3} Resi + β_{4} HsElec + β_{5} {Eduat}_{i} + β_{5} {Lit}_{i} + ε_{i}

(2)

Where k varies between 1 and 2 (TV and Mph), equation (2) can be split into equations (3) and (4) below respectively.

Probit (HsTV) = β_{0} + β_{2} {HseMem}_{i} + β_{3} Resi + β_{4} HsElec + β_{5} {Eduat}_{i} + β_{5} {Lit}_{i} + ε_{i}

(3)

Probit (HsMph) = β_{0} + β_{2} {HseMem}_{i} + β_{3} Resi + β_{4} HsElec + β_{5} {Eduat}_{i} + β_{5} {Lit}_{i} + ε_{i}

(4)

Meaning of the model

Where, HsTV, HsMph represents mothers’ exposure through watching television and having a mobile phone respectively (Dependent Variables);

HseMem = household members that range from 1 to 40;

Resi= place of residence which is a binary variable indicating the (1 for rural, 0 for urban). (Independent variable);

HsElec= Household has electricity which is a binary variable indicating the (1 for having electricity, 0 for not having electricity). (Independent variable);

Eduat= Educational attainment captured through no education, incomplete primary education, primary education, incomplete secondary education, complete secondary education and higher education (control variable).

Lit= Literacy which is a binary variable indicating the (1 for being a literate, 0 for not being a literate) (control variable).

ε = The error term.

For the second model that concerns the extent to which mother’s exposure affects child health, Child health is captured by anthropometric indicators such as HAZ, WAZ and or WHZ or their 0/1 equivalents when for example, HAZ>-2 and 0 otherwise.

In our model, we made use of WHZ which is backed by Literature and the World Health measure. WHZ which stands for weight for height Z-Score has been approved as a better measure for child health on a global basis in every situation by the WHO given that these two aspects can be gotten with the physical presence of the child, and are further used to calculate the Body Mass Index for adults. However, age can be gotten only for those that are aware of their ages and are not unconscious at the moment of investigation

[18]

. This justifies the use of only WHZ to capture child health in this study. In this model, mothers’ exposure to the media is captured based on the frequency of usage and with respect to data availability, we make use of frequency of listening to the radio, watching the TV and using the Internet. However, it is worth noting that the internet is used mostly via mobile phones.

Probit (CHLDHLT) = β_{0} + β_{1} {FrRadio}_{i} + β_{2} {FrTv}_{i} + β_{3} Frint + β_{4} Cubrf + β_{5} {Ckdbdg}_{i} + β_{6} {Rvebcg}_{i} + + ε_{i}

(5)

Meaning of the model

Where, CHLDHLT represents child health (Dependent Variable) {1=good health and 0= bad health} however, it is captured using Weight for Height Z-score (WHZ that is, it takes the value 1 when WHZ>-2 and 0 otherwise).

FrRadio =Frequency of listening to the radio (independent Variable)

FrTv = Frequency of watching a television (independent Variable)

FrInt= Frequency of using the internet (independent Variable)

Cubrf = currently breast feeding (Control Variable)

Ckdbdg= Checked before discharged (Control Variable)

Rvebcg= Child received BCG (Control Variable)

ε = The error term.

4. Findings and Discussion

This section presents findings of the determinants of mothers’ exposure to the media and its effect on child health in Cameroon. The findings are based on a descriptive and inferential statistics. The descriptive statistics focuses on providing a summary statistic of the variables used as presented in Table 1 and 2 below.

4.1. Descriptive Statistics on the Determinants of Mothers’ Exposure to the Media in Cameroon

Table 1. Summary of Descriptive Statistics on determinants of mothers’ exposure.

Variable	Obs	Mean	Std. Dev.	Min	Max
HsTV	7833	.886	1.64	0	1
HsMph	7833	.77	.421	0	1
HseMem	7833	6.714	4.507	1	40
Resi	7833	1.459	.498	0	1
HsElec	7833	1.038	1.597	0	1
EduAt	7833	2.053	1.322	0	5
Lit	7833	1.315	.871	0	1

Source: Author computation (2025)

Results from Table 1 above reveals that the mean value of having a television is 0.886 with a standard deviation of 1.64 which is lower than the mean revealing that there is a moderate dispersion of having a television in the sample. The value of having a television in the sample fluctuates between 0 and 1. The mean value of having a mobile phone is 0.77 with a standard deviation of 0.421. Having a mobile phone is binary in nature. The average of house hold members, place of residence and having electricity is 6.714, 1.459 and 1.038 with a standard deviation of 4.507, 0. 498 and 1.597 which reveals that there is a high dispersion of these variables in the sample with values ranging between 0 and 40. The average value of educational attainment is 2.053 with a standard deviation of 1.322 which is lower than the mean revealing that there is a moderate dispersion in the sample. Values of those having a radio in the sample fluctuate between 0 and 5.

The mean value of literacy is 1.315 with a standard deviation of 0. 871 which reveals that there is a low dispersion in the sample given that the standard deviation is less than the mean value with values ranging between 0 and 4.

4.2. Descriptive Statistics on the Effect of Mothers’ Exposure to the Media on Child Health in Cameroon

Table 2. Descriptive Statistics on Extent of Exposure.

Variable	Obs	Mean	Std. Dev.	Min	Max
Weight Height	7833	.779	.415	0	1
Fr Radio	.	.	.	.	.
not at all	7833	.623	.485	0	1
less than once a week	7833	.2	.4	0	1
at least once a week	7833	.177	.382	0	1
Fr Television	.	.	.	.	.
not at all	7833	.435	.496	0	1
less than once a week	7833	.144	.351	0	1
at least once a week	7833	.42	.494	0	1
Fr Internet	.	.	.	.	.
not at all	7833	.8	.4	0	1
less than once a week	7833	.028	.165	0	1
at least once a week	7833	.066	.249	0	1
almost every day	7833	.106	.308	0	1
Cur BreastFd	.	.	.	.	.
No	7832	.827	.378	0	1
Yes	7832	.173	.378	0	1
Child CkdBf Dis~d	.	.	.	.	.
No	1163	.138	.346	0	1
Yes	1163	.855	.353	0	1
don't know	1163	.007	.083	0	1
Rve bcg	.	.	.	.	.
No	1106	.119	.324	0	1
vaccination date o~d	1106	.678	.467	0	1
reported by mother	1106	.199	.399	0	1
vaccination marked~d	1106	.003	.052	0	1
don't know	1106	.001	.03	0	1

Source: Author’s computation (2025)

Fr Radio= Frequency of listening to the radio, Fr Television= Frequency of watching a television, Fr Internet= frequency of using the internet, Cur BreastF= Currently breastfeeding, Child CkdBf Dis~d= Child checked before discharged and Rve bcg=Child received bcg.

Results from Table 2 above reveals that the mean value of having a child health is 0.779 with a standard deviation of 0.415 which is lower than the mean revealing that there is a moderate dispersion of child health in the sample. The value of the frequency of not listening to the radio at all in the sample fluctuates between 0 and 1. The average of the frequency of listening to the radio less than once a week and at least once a week is 0.2 and 0.177 with a standard deviation of 0.4, and 0.382 which reveals that there is a high dispersion of these variables in the sample with values ranging between 0 and 1. The average value of the frequency of not watching television at all, watching television less than once a week and the frequency of watching a television at least once a week is 0.435, 0.144, and 0.42 with a standard deviation of 0.496, 0.351 and 0.49 which is lower than the mean revealing that there is a moderate dispersion in the sample which ranges between 0 and 1.

The mean value of the frequency of not using the internet at all, of using the internet once a week, of using it at least once a week and the frequency of using it almost every day is 0.8, 0.028, 0.066 and 0.106 with a standard deviation of 0.4, 0.165, 0.249 and 0.308 respectively which fluctuate between 0 and 1.

The mean value of a mother not currently breastfeeding and currently breastfeeding is 0.827 and 0.173 with a standard deviation of 0.378 and 0.278 which reveals that there is a low dispersion in the sample given that the standard deviation is less than the mean value with values ranging between 0 and 1.

The mean value of a child not checked before discharged, a checked before discharged and the mother not knowing if the child was checked is 0.128, 0.855 and 0.007 with a standard deviation of 0.346, 0.353 and 0.083 respectively which ranges between o and 1.

The mean value of a child not receiving bcg, having a vaccination date on the card, reported by mother, vaccination marked on card and the mother not knowing if the child received bcg is 0.119, 0.678, 0.199, 0.003 and 0.001 with their respective standard deviation.

In order to ascertain that multicollinearity is not a major concern in the model, the Variance Inflation Factors (VIF) test is further conducted and results are displayed in the table below. Johnston et al. (2018) ascertains the fact VIF ≥ 2.5 indicates considerable collinearity. This is controlled for both households having Television (TV) and those with Mobile Phones (MpH). Result from the VIF test reveal that multicolinearity is not a major concern in the model since the mean VIF of (1.582) and (1.47) is lower than the critical value of 2.5. The main objective of this section is to investigate the determinants of mother’s exposure to the media on child health in Cameroon. Specifically, the study intends to assess first the determinants of mother’s exposure to the media in Cameroon and then to explore the extent to which mother’s exposure to the media affects child health.

4.3. Probit Regression on the Determinants of Mother’s Exposure to the Media

Table 3. Regression on the Determinants of Mother’s Exposure to the Media.

Those having a Television

Those having Mobile Phones

VARIABLES

(1) Coefficient

(2) Marginal effects

VARIABLES

(1) Coefficient

(2) Marginal effects

HseMem

-.0390651***

(0.004)

-.0155817***

(0.002)

HseMem

-.0426233***

(0.004)

-.0107946***

(0.001)

Resi (rural)

.7688559***

(0.04)

.3066705***

(0.014)

Resi (rural)

-.3404359***

(0.039)

-.087325***

(0.010)

HsElec

-1.07272***

(0.037)

-.4278716***

(0.015)

HsElec

.618538***

(0.039)

.1566483***

(0.010)

1.EduAt

-.150*(0.077)

-.03864*

(0.199)

1.EduAt

.0639842*

(0.056)

.0200202*

(0.018)

2.EduAt

0.409***

(0.0805)

0.104389***

(0.2080)

2.EduAt

.2718229***

(0.063)

.0786033***

(0.019)

3.EduAt

0.694***

(0.083)

0.17288***

(0.0218)

3.EduAt

.3254347***

(0.067)

.0920479***

(0.020)

4.EduAt

1.272***

(0.150)

0.29685***

(0.03358)

4.EduAt

1.034954***

(0.216)

.2084658***

(0.026)

5.EduAt

1.351***

(0.147)

0.312353***

(0.0326)

5.EduAt

1.49841***

(0.268)

.2377833***

(0.019)

Lit

.0026232 (-0.029)

.0010463 (0.011)

Lit

.3128858***

(0.028)

.0792401***

(0.007)

_cons

.4221636***

(0.075)

_cons

.3207704 ***

(0.052)

Mean	0.886	SD	1.640	Mean	0.770	SD	0.421
Pseudo r-squared	0.469	Number of obs	7833	Pseudo r-squared	0.197	Number of obs	7833
Chi-square	5090.009	Prob > chi2	0.000	Chi-square	1668.529	Prob > chi2	0.000
Akaike crit. (AIC)	5774.401	Bayesian crit. (BIC)	5823.164	Akaike crit. (AIC)	6807.594	Bayesian crit. (BIC)	6884.221
* p<.01, p<.05, * p<.1 Standard errors in parentheses

Source: Author’s computation (2025)

The probit regression results reveal several significant determinants of mothers' exposure to the media in Cameroon. The coefficient of household members is -0.039 and -0.043 respectively for those having TV and Mobile Phones. This indicates that for a one-unit increase in household members, the probability of mothers' exposure to the media decreases by 0.039 and 0.043 units respectively. This variable is statistically significant at the 1% level for both dependent variables, suggesting that household members have an impact on mothers' media exposure. In terms of marginal effect, a one-point increase in household members by one will lead to about 1.5% and 1.18% decrease in the probability of mother’s exposure to the media (through TV and Mobile Phone respectively). However, this result was found to be statistically significant at 1% level of significance. Thus, there is a significant effect of household members of mothers on mothers' exposure to the media. This suggests that living in a larger household may lead to reduced access to media sources or reduced media consumption behaviors given the plethora of interest by the different occupants.

The coefficient of mothers’ Place of residence is 0.769, showing that the place of residence significantly affects mothers' media exposure positively. This suggests that mothers living in the rural areas have higher media exposure through the TV as compared to those living in the urban area. The marginal effect of mothers’ residence is 0.307, showing that mothers resident in rural areas are 30.7 percentage points more likely to be exposed to the media through the TV. With regards to those having a mobile phone, the coefficient of mothers living in the rural area is -0.34 and a marginal effect of -0.087. This indicates that mothers living in the rural area are 8.7 percentage points less likely to be exposed to the media through mobile phones as compared to those in urban areas. This variable is statistically significant at the 1% level, suggesting that mothers living in the rural areas have an impact on mothers' media exposure. This could be due to varying accessibility to media outlets or infrastructure constraints in different regions of Cameroon. Also, rural areas in Cameroon may have limited access to media infrastructure, leading to lower exposure levels among mothers. The negative coefficient may persist due to slower improvements in media accessibility in rural regions compared to urban areas.

The coefficient of household having electricity is -1.073 for the TV and 0.618 for the mobile phone, thus implying that households with electricity is associated with a decrease in probit index for media exposure with the TV. Thus having electricity decreases probability of media exposure by 42.8 percentage points for the case of television. Meanwhile, households with electricity and mobile phones tend to have higher media exposure as compared to household without electricity, as there is an increase in probit index by 0.618 and a marginal effect of 0.157. Thus, there is a significant effect of mothers’ household having electricity on mothers' exposure to the media. This finding underscores the importance of infrastructure development in improving media access and usage in Cameroon and the electrification efforts expand in Cameroon in recent years, leading to improved access to media platforms.

The coefficients of educational attainment indicate an increasingly positive relationship as mothers achieve more in education. That is being more educated (from incomplete primary to higher) increases the probability of mothers' exposure to the media using a TV as compared to those with no education. This is evident from the increase in their coefficients (0.15, 0.409, 0.694, 1.272, 1.351). This result was found to be statistically significant at 10% and 1% levels of significance. Thus, there is a significant effect of mothers’ educational attainment on their exposure to the media (captured through TV). The same line of influence is witnessed with those having mobile phones as mothers become more educated.

The coefficient of being literate is 0.002 and 0.313 respectively for both having a TV and a Mobile Phone, indicating an increase in the probit index for mothers' media exposure as far as literature is concerened. When there is an increase in literacy as compared to those that cannot read, the probability of media exposure increase. The marginal effect of a mother being a literate as compared to those that cannot read is 0.001 and 0.079 for TV and Mobile phones respectively. However, this result was found to be statistically significant at 1% level of significance. Thus, there is a significant effect of mothers’ literacy on mothers' exposure to the media. This suggests that education plays a significant role in shaping mothers' media consumption patterns and information-seeking behaviors. These results are in line with that of

[20]

who conducted a study on mass media exposure and maternal healthcare utilization in South Asia.

The constant term of 0.422 and 0.642 in the probit regression represents the baseline probability of mothers' media exposure when all other variables are zero or not applicable. However, this result was found to be statistically significant at 1% level of significance.

4.4. Probit Regression of Mother’s Exposure to Media on Child Health

The second objective of this study was to explore the extent to which mother’s exposure to the media affects child health. The probit regression results related to the extent of mothers' exposure to the media shed light on the frequency of watching television and using the internet as significant predictors.

From Table 4 below, the frequency of listening to a radio less than once a week has a coefficient of -0.100, and it is insignificant. This means that compared to not listening to the radio at all, there is no significant impact on child health for those who listen to the radio less than once a week as compared to those who do not listen to the radio. The probability of the frequency of listening to the radio decreases by 0.100. The marginal effect is -0.027, which is also insignificant. This suggests that listening to the radio less than once a week is associated with decreased probability of good child health. Frequency of listening to a radio at least once a week has a coefficient of 0.113, which is insignificant, and a marginal effect of 0.028, also insignificant. This indicates that listening to a radio at least once a week is not significantly related to child health. This implies that compared to not listening to the radio at all, there is no significant impact on child health for those who listen to the radio at least once a week.

Table 4. Probit regression on the extent of mother’s exposure.

VARIABLES	(1)	(2)
VARIABLES	Coefficient	Marginal effects
1.Fr_Radio	-.1007834	-0.027
1.Fr_Radio	(.138)	(0.038)
2.Fr_Radio	.1126053	0.028
2.Fr_Radio	(.153)	(0.037)
1.Fr_Telev~n	.4951131**	0.128***
1.Fr_Telev~n	(.193)	(0.046)
2.Fr_Telev~n	.3221653**	0.090**
2.Fr_Telev~n	(.134)	(0.039)
1.Fr_Inter~t	.1335706	0.035
1.Fr_Inter~t	(.276)	(0.068)
2.Fr_Inter~t	.3368023*	0.079**
2.Fr_Inter~t	(.199)	(0.041)
3.Fr_Inter~t	.1690586	0.043**
3.Fr_Inter~t	(.157)	(0.038)
1.Cur_Brea~d	.0012502	0.000**
1.Cur_Brea~d	(.107)	(0.028)
1.Child_Ck~d	.0602886	0.016**
1.Child_Ck~d	(.155)	(0.042)
2.Child_Ck~d	-.1466148	-0.042
2.Child_Ck~d	(.695)	(0.212)
1.Rve_bcg	.1680227	0.046**
1.Rve_bcg	(.197)	(0.057)
2.Rve_bcg	.093814	0.026**
2.Rve_bcg	(.223)	(0.064)
3.Rve_bcg	-.0455697	-0.014
3.Rve_bcg	(.773)	(0.234)
_cons	.4156356*
_cons	(.239)

Mean dependent var	0.816	SD dependent var	0.388
Pseudo r-squared	0.030	Number of obs	805
Chi-square	22.983	Prob > chi2	0.042
Akaike crit. (AIC)	773.282	Bayesian crit. (BIC)	838.954
* p<.01, p<.05, * p<.1

Standard errors in parentheses

Source: Author computation (2024)

The frequency of watching television less than once a week has a coefficient of 0.495, which is significant. This shows that the probability of watching a television less than once a week will increase by 0.495 as compared to not watching television at all, there is a significant positive impact on child health for those who watch television at least once a week. The marginal effect is 0.128, also significant. This suggests that watching television less than once a week is associated with increased probability of good child health compared to not watching at all. The frequency of watching television at least once a week has a coefficient of 0.322, significant at 5%. This shows that compared to not watching television at all, there is a significant positive impact on child health for those who watch television at least once a week. The marginal effect is 0.090, stipulating a 9 percentage point increase in the probability of good child health as compared to not watching at all. Consistent exposure to television content allows mothers to access ongoing health messages.

The frequency of using the internet less than once a week has a coefficient of 0.134, which is insignificant. This indicates that compared to not using the internet at all, the z-score will increase by 0.134 and it is no significant impact on child health for those who use the internet less than once a week. The frequency of using the internet at least once a week has a positive coefficient of 0.337, and a marginal effect of 0.035 which are all significant. This suggests that using the internet at least once a week is associated with a 3.5 percentage point increase in the probability of good child health compared to not using it at all. The frequency of using the internet at least every day has a coefficient of 0.169, which is insignificant. However, the marginal effect is 0.043, and it is significant. This suggests that using the internet at least every day has a tendency of increasing the probability of good child health by 4.3 percentage points on child health compared to not using it at all or even using it once. Internet usage is becoming more prevalent in Cameroon, providing mothers with additional platforms for health information. The positive coefficient continues as internet penetration and usage rates rise, enabling increased exposure to health-related content. These results are in line with that of the authors who carried out a study on the association between exposure to mass media and maternal health care services utilization among women in sub-Saharan Africa

[2]

The coefficient of currently breast feeding is 0.0013 and it is statistically insignificant. This indicates that compared to not currently breast feeding, the probability of currently breast feeding will increase by 0.0013 and an insignificant impact on child health for those who are currently breast feeding as compared to those who are not currently breast feeding. The marginal effect of currently breastfeeding, compared to not currently breastfeeding is 0.0003, and it is significant.

The coefficient for the child's BCG vaccination date being on the book is 0.168, which is insignificant. This shows that having the BCG vaccination date documented on a card increases the probability of child's BCG vaccination date being on the book and does not have a statistically significant impact on child health compared to not receiving the vaccination. The marginal effect of the BCG vaccination date on the card, compared to not receiving the vaccination, is 0.046, and it is significant. This indicates that having the BCG vaccination date recorded on a card has a significant effect on child health compared to not receiving the vaccination. The coefficient for the child's BCG reported by mother is 0.094 and it is statistically significant. This implies that having the BCG vaccination reported by mother have a statistically significant impact on child health compared to not receiving the vaccination. The marginal effect of the BCG vaccination reported by mother, compared to not receiving the vaccination, is 0.026, and it is significant. This indicates that having the BCG vaccination as reported by mother has a significant effect on child health compared to not receiving the vaccination.

Result from the VIF test reveals that multicollinearity is not a major concern in the model since the mean VIF (1.497) is lower than the critical value of 2.5 and the values of individual variables do not exceed 10. Consequently, we can confidently conclude that the model does not suffer from any major problem of multicollinearity.

5. Conclusion

The purpose of the study was to examine the effect of mother’s exposure to the media on child health in Cameroon. Specifically, this study intended to assess the determinants of mother’s exposure to the media in Cameroon and to explore the extent to which mother’s exposure to the media affects child health. The study adopted descriptive research designs to establish the effect of mother’s exposure to the media on child health in Cameroon. The target population of the study was households (mothers) in Cameroon. The study relied on secondary data that was collected by the Cameroonian Demographic and Health survey (CDHS) which was collected in 2018.

Findings from data analysis indicate that for a one-unit increase in household members, the probability of mothers' exposure to the media decreases by 0.039 and 0.043 units respectively for using the TV and Mobile Phone. Mothers living in the rural areas have higher media exposure through the TV as compared to those living in the urban area, while the mothers living in the rural area are 8.7 percentage points less likely to be exposed to the media through mobile phones as compared to those in urban areas. The coefficient of households having electricity is -1.073 for the TV and 0.618 for the mobile phone, thus implying that households with electricity is associated with a decrease in probit index for media exposure with the TV while households with electricity and mobile phones tend to have higher media exposure as compared to household without electricity, as there is an increase in probit index by 0.618 and a marginal effect of 0.157. Educational attainment indicates an increasingly positive relationship as mothers achieve more in education. With regards to the extent of exposure on child health, watching television less than once a week is associated with increased probability of good child health compared to not watching at all. The frequency of watching television at least once a week has a coefficient of 0.322, significant at 5%. The frequency of using the internet at least once a week has a positive coefficient of 0.337, and a marginal effect of 0.035 which are all significant. This suggests that using the internet at least once a week is associated with a 3.5 percentage point increase in the probability of good child health compared to not using it at all.

On the basis of the findings above, the government could prioritize improving access to electricity in households across Cameroon, especially in underserved areas. This will not only enhance mothers' exposure to the media but also facilitate better health communication and education initiatives, ultimately improving child health outcomes. The government could also implement programs that promote maternal education and media literacy to increase awareness of health-related media messages. By investing in education, the government can empower mothers to make informed decisions regarding their children's health based on the information they receive from the media. She could also enforce regulations to ensure that media content related to child health is accurate, reliable, and easily accessible to mothers. Additionally, collaborate with media outlets to promote health-related programs that educates and informs mothers about best practices for enhancing child health.

Given the significant impact of mothers' television viewing frequency on child health, policy recommendations should focus on creating and broadcasting targeted health campaigns through television programs. Collaborating with media outlets to integrate health-related segments, advertisements, and educational content during popular TV shows can effectively reach mothers and influence their health-related behaviors. As mothers' internet usage frequency influences child health outcomes, policy recommendations may be centered on promoting access to reliable and trusted health resources online. Establishing partnerships with health organizations, government agencies, and reputable websites to create and disseminate evidence-based health information tailored for mothers can help bridge the gap between media exposure and positive health practices. However, all these can only be encouraged since the reactions are subjective to their conditions as mothers.

Abbreviations

CDHS	Cameroon Demographic Health Survey
DHS	Demographic Health Survey
ICF	International Classification of Functioning, Disability and Health
IGCME	Inter-Agency Gap for Child Mortality Estimation
MEM	Mothers’ Exposure to the Media
MPh	Mobile Phone
NHDP	National Health Development Plan
NIS	National Institute of Statistics
SDG	Sustainable Development Goals
TV	Television
UN	United Nations
UNICEF	United Nations Children Emergency Fund
WASH	Water, Sanitation and Hygiene
WHO	World Health Organization

Funding

The authors received no specific funding for this work.

Conflicts of Interest

The authors have declared no conflicts of interest.

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Kum, F. V., Anchi, O. E., Ajubeseh, L. (2026). Mothers’ Exposure to the Media and Its Effect on Child Health in Cameroon. International Journal of Health Economics and Policy, 11(1), 1-16. https://doi.org/10.11648/j.hep.20261101.11

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Kum, F. V.; Anchi, O. E.; Ajubeseh, L. Mothers’ Exposure to the Media and Its Effect on Child Health in Cameroon. Int. J. Health Econ. Policy 2026, 11(1), 1-16. doi: 10.11648/j.hep.20261101.11

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Kum FV, Anchi OE, Ajubeseh L. Mothers’ Exposure to the Media and Its Effect on Child Health in Cameroon. Int J Health Econ Policy. 2026;11(1):1-16. doi: 10.11648/j.hep.20261101.11

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@article{10.11648/j.hep.20261101.11,
  author = {Fuein Vera Kum and Ofeh Evina Anchi and Lucy Ajubeseh},
  title = {Mothers’ Exposure to the Media and Its Effect on Child Health in Cameroon},
  journal = {International Journal of Health Economics and Policy},
  volume = {11},
  number = {1},
  pages = {1-16},
  doi = {10.11648/j.hep.20261101.11},
  url = {https://doi.org/10.11648/j.hep.20261101.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.hep.20261101.11},
  abstract = {The purpose of this study was to investigate the determinants of mothers’ exposure to the media and examine its effect on child health in Cameroon. Data was obtained through a survey from the Cameroonian Demographic and Health survey (CDHS) 2018. The study employed a Probit regression to examine the determinants of mothers’ exposure to the media and its effect on child health in Cameroon. The results from this analysis revealed that, an increase in the household membership negatively and significantly affects mothers’ exposure to the media for those having a Television (-0.0391) and those having mobile phones (-0.0426). Also, those living in the rural area with regards to place of residence shows a positive significant effect (0.7689) as concerns television ownership and a negative significant effect (-0.3404) for mobile phone ownership. Households having electricity depicts a significant negative and positive effect respectively with regards to television (-1.0727) and mobile phone (0.6185) ownership. Being more educated as per the different categories of education shows a positive statistically significant effect on mother’s exposure to the media as compared to not being educated for both television and mobile phone ownership. The results equally revealed that, the frequency of listening to the radio and watching a television more than once a week had a positive effect on child’s health as compared to not listening to the radio or watching Television at all (0.113 and 0.495 respectively), though statistically significant only for watching television. The frequent use of the internet (at least once a week) had a positive statistically significant effect on child’s health in Cameroon at 10%, with a coefficient of 0.337. From the results, we recommend that, the government should prioritize improving access to electricity in households across Cameroon, especially in underserved areas and also implement programs that promote maternal education and media literacy to increase awareness of health-related media messages.},
 year = {2026}
}

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TY  - JOUR
T1  - Mothers’ Exposure to the Media and Its Effect on Child Health in Cameroon
AU  - Fuein Vera Kum
AU  - Ofeh Evina Anchi
AU  - Lucy Ajubeseh
Y1  - 2026/01/19
PY  - 2026
N1  - https://doi.org/10.11648/j.hep.20261101.11
DO  - 10.11648/j.hep.20261101.11
T2  - International Journal of Health Economics and Policy
JF  - International Journal of Health Economics and Policy
JO  - International Journal of Health Economics and Policy
SP  - 1
EP  - 16
PB  - Science Publishing Group
SN  - 2578-9309
UR  - https://doi.org/10.11648/j.hep.20261101.11
AB  - The purpose of this study was to investigate the determinants of mothers’ exposure to the media and examine its effect on child health in Cameroon. Data was obtained through a survey from the Cameroonian Demographic and Health survey (CDHS) 2018. The study employed a Probit regression to examine the determinants of mothers’ exposure to the media and its effect on child health in Cameroon. The results from this analysis revealed that, an increase in the household membership negatively and significantly affects mothers’ exposure to the media for those having a Television (-0.0391) and those having mobile phones (-0.0426). Also, those living in the rural area with regards to place of residence shows a positive significant effect (0.7689) as concerns television ownership and a negative significant effect (-0.3404) for mobile phone ownership. Households having electricity depicts a significant negative and positive effect respectively with regards to television (-1.0727) and mobile phone (0.6185) ownership. Being more educated as per the different categories of education shows a positive statistically significant effect on mother’s exposure to the media as compared to not being educated for both television and mobile phone ownership. The results equally revealed that, the frequency of listening to the radio and watching a television more than once a week had a positive effect on child’s health as compared to not listening to the radio or watching Television at all (0.113 and 0.495 respectively), though statistically significant only for watching television. The frequent use of the internet (at least once a week) had a positive statistically significant effect on child’s health in Cameroon at 10%, with a coefficient of 0.337. From the results, we recommend that, the government should prioritize improving access to electricity in households across Cameroon, especially in underserved areas and also implement programs that promote maternal education and media literacy to increase awareness of health-related media messages.
VL  - 11
IS  - 1
ER  -

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Author Information

Fuein Vera Kum

Department of Economics of the Faculty of Economics and Management Sciences, University of Bamenda, Bambili, Cameroon

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http://orcid.org/0000-0002-3580-6157
Ofeh Evina Anchi

Department of Economics of the Faculty of Economics and Management Sciences, University of Bamenda, Bambili, Cameroon

Contact Email

http://orcid.org/0009-0002-2558-8261
Lucy Ajubeseh

Department of Economics of the Faculty of Economics and Management Sciences, University of Bamenda, Bambili, Cameroon

http://orcid.org/0009-0002-8120-8403

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Table 1

Table 1. Summary of Descriptive Statistics on determinants of mothers’ exposure.
Table 2

Table 2. Descriptive Statistics on Extent of Exposure.
Table 3

Table 3. Regression on the Determinants of Mother’s Exposure to the Media.
Table 4

Table 4. Probit regression on the extent of mother’s exposure.

Plain Text BibTeX RIS

APA Style

Kum, F. V., Anchi, O. E., Ajubeseh, L. (2026). Mothers’ Exposure to the Media and Its Effect on Child Health in Cameroon. International Journal of Health Economics and Policy, 11(1), 1-16. https://doi.org/10.11648/j.hep.20261101.11

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ACS Style

Kum, F. V.; Anchi, O. E.; Ajubeseh, L. Mothers’ Exposure to the Media and Its Effect on Child Health in Cameroon. Int. J. Health Econ. Policy 2026, 11(1), 1-16. doi: 10.11648/j.hep.20261101.11

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AMA Style

Kum FV, Anchi OE, Ajubeseh L. Mothers’ Exposure to the Media and Its Effect on Child Health in Cameroon. Int J Health Econ Policy. 2026;11(1):1-16. doi: 10.11648/j.hep.20261101.11

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@article{10.11648/j.hep.20261101.11,
  author = {Fuein Vera Kum and Ofeh Evina Anchi and Lucy Ajubeseh},
  title = {Mothers’ Exposure to the Media and Its Effect on Child Health in Cameroon},
  journal = {International Journal of Health Economics and Policy},
  volume = {11},
  number = {1},
  pages = {1-16},
  doi = {10.11648/j.hep.20261101.11},
  url = {https://doi.org/10.11648/j.hep.20261101.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.hep.20261101.11},
  abstract = {The purpose of this study was to investigate the determinants of mothers’ exposure to the media and examine its effect on child health in Cameroon. Data was obtained through a survey from the Cameroonian Demographic and Health survey (CDHS) 2018. The study employed a Probit regression to examine the determinants of mothers’ exposure to the media and its effect on child health in Cameroon. The results from this analysis revealed that, an increase in the household membership negatively and significantly affects mothers’ exposure to the media for those having a Television (-0.0391) and those having mobile phones (-0.0426). Also, those living in the rural area with regards to place of residence shows a positive significant effect (0.7689) as concerns television ownership and a negative significant effect (-0.3404) for mobile phone ownership. Households having electricity depicts a significant negative and positive effect respectively with regards to television (-1.0727) and mobile phone (0.6185) ownership. Being more educated as per the different categories of education shows a positive statistically significant effect on mother’s exposure to the media as compared to not being educated for both television and mobile phone ownership. The results equally revealed that, the frequency of listening to the radio and watching a television more than once a week had a positive effect on child’s health as compared to not listening to the radio or watching Television at all (0.113 and 0.495 respectively), though statistically significant only for watching television. The frequent use of the internet (at least once a week) had a positive statistically significant effect on child’s health in Cameroon at 10%, with a coefficient of 0.337. From the results, we recommend that, the government should prioritize improving access to electricity in households across Cameroon, especially in underserved areas and also implement programs that promote maternal education and media literacy to increase awareness of health-related media messages.},
 year = {2026}
}

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TY  - JOUR
T1  - Mothers’ Exposure to the Media and Its Effect on Child Health in Cameroon
AU  - Fuein Vera Kum
AU  - Ofeh Evina Anchi
AU  - Lucy Ajubeseh
Y1  - 2026/01/19
PY  - 2026
N1  - https://doi.org/10.11648/j.hep.20261101.11
DO  - 10.11648/j.hep.20261101.11
T2  - International Journal of Health Economics and Policy
JF  - International Journal of Health Economics and Policy
JO  - International Journal of Health Economics and Policy
SP  - 1
EP  - 16
PB  - Science Publishing Group
SN  - 2578-9309
UR  - https://doi.org/10.11648/j.hep.20261101.11
AB  - The purpose of this study was to investigate the determinants of mothers’ exposure to the media and examine its effect on child health in Cameroon. Data was obtained through a survey from the Cameroonian Demographic and Health survey (CDHS) 2018. The study employed a Probit regression to examine the determinants of mothers’ exposure to the media and its effect on child health in Cameroon. The results from this analysis revealed that, an increase in the household membership negatively and significantly affects mothers’ exposure to the media for those having a Television (-0.0391) and those having mobile phones (-0.0426). Also, those living in the rural area with regards to place of residence shows a positive significant effect (0.7689) as concerns television ownership and a negative significant effect (-0.3404) for mobile phone ownership. Households having electricity depicts a significant negative and positive effect respectively with regards to television (-1.0727) and mobile phone (0.6185) ownership. Being more educated as per the different categories of education shows a positive statistically significant effect on mother’s exposure to the media as compared to not being educated for both television and mobile phone ownership. The results equally revealed that, the frequency of listening to the radio and watching a television more than once a week had a positive effect on child’s health as compared to not listening to the radio or watching Television at all (0.113 and 0.495 respectively), though statistically significant only for watching television. The frequent use of the internet (at least once a week) had a positive statistically significant effect on child’s health in Cameroon at 10%, with a coefficient of 0.337. From the results, we recommend that, the government should prioritize improving access to electricity in households across Cameroon, especially in underserved areas and also implement programs that promote maternal education and media literacy to increase awareness of health-related media messages.
VL  - 11
IS  - 1
ER  -

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