Prevalence of ARI, fever, and diarrhea among under-five children and the influencing factors in southwestern coastal region of Bangladesh

Abstract

Background

Acute respiratory infection (ARI), fever, and diarrhea are the prominent causes of the burden of childhood communicable diseases along with mortality in developing countries which contributes to nutritional deficiencies, reduced resistance to infections and impaired growth and development. Therefore, the present study aims to investigate the prevalence of ARI, fever, and diarrhea among under-five children and the influencing factors in the southwestern coastal region of Bangladesh by incorporating the social ecological model.

Methods

The study was conducted in six villages of Dacope upazila under Khulna district of Bangladesh following cross-sectional survey method. Data were collected from 348 randomly selected caregivers with at least one child aged 6 to 59 months. A semi-structured interview schedule was used for data collection from the participants through face-to-face interviews from July to October 2024. Bivariate and multivariate analyses were conducted to determine the factors influencing the prevalence of ARI, fever, and diarrhea among under-five children.

Results

Results showed that ARI prevalence among under-five children was 64.7%, followed by fever at 42.2%, and diarrhea at 13.5% in the southwestern coastal region. Findings also revealed that various individual factors such as child sex, child feeding frequency, and birth weight; interpersonal factors like house type, type of family, and household vulnerability; and community-level factors such as place of residence and availability of qualified doctors in the locality were the significant predictors of the prevalence of these diseases. However, we did not find any significant influence of policy-level factors on the prevalence of these diseases. Children who were fed ≥ 7 times a day and those residing in Nolian village had higher odds of having ARI than their counterparts. On the other hand, children with normal birth weight, children who were fed 5–6 times and ≥ 7 times a day, and children living in Hoglabunia village had higher odds of getting fever. Nonetheless, children living in semi-pacca houses had lower odds of experiencing fever compared to their counterparts. Moreover, boys, children from higher vulnerable households, and children residing in the community where qualified doctors are available had higher odds of getting diarrhea, whereas children from nuclear families had lower odds of having diarrhea than their counterparts.

Conclusion

The study suggests introducing targeted nutrition education programs for both mothers and infants through community outreach. Besides, generating sustainable income opportunities to reduce coastal households’ vulnerabilities. Additionally, infrastructural development is essential to ensure access to quality healthcare services in geospatially disadvantaged regions, especially in southwestern coastal region of Bangladesh.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-025-24415-3.

Introduction

Globally, 4.9 million children under the age of five died In 2022 and acute respiratory infection (ARI), fever, pneumonia, diarrhea, and malaria, along with premature birth and complications from the intrapartum period remain the leading causes of death for children under 5 worldwide [1, 2]. Sub-Saharan Africa and south Asia account for more than 80% of this under-5 deaths In 2022 globally [2]. Communicable diseases among under-five children including ARI, fever, and diarrhea contributes to nutritional deficiencies, reduced resistance to infections and impaired growth and development [3]. Annually, 1.7 billion childhood diarrhea cases occur worldwide, with 0.44 million under-five children dying from diarrhea each year [4]. Besides, ARI accounts for 15% of mortality in children under the age of five globally [5]. In developing countries, ARI, fever, and diarrhea are prominent causes of the burden of childhood disease along with mortality [6, 7] particularly, in south Asia and sub-Saharan Africa, where access to healthcare, safe water, and sanitation remains limited [8]. To achieve the Sustainable Development Goals (SDGs) target of reducing child deaths to 25 per 1,000 live births by 2030 [9], low- and middle-income nations must immediately address the burden of childhood communicable diseases particularly, ARI, fever and diarrhea.

Bangladesh has a high annual rate of under-five child mortality as 45 deaths per 1,000 live births and is grappling with child morbidity [10]. Though Bangladesh has achieved the Millennium Development Goals (MDGs) 4 which target 48/1000 live births by the year 2015, however, childhood illness has not decreased at the same pace [11]. In Bangladesh, like many other developing countries, ARI, pneumonia, diarrhea, and fever are the main causes of child morbidity and mortality [10, 12] as well as related to impaired physical growth and development of children. According to the latest Bangladesh Demographic and Health Survey (BDHS) data of 2017-18, 3% of the under-five children experienced ARI, while 33% had fever, and 5% had diarrhea [10]. In Bangladesh, each year, approximately half a million children die due to diarrhea and 25% mortality rate due to ARI [10, 13]. However, metrics with regard to under-five child deaths due to fever are yet to be revealed [14].

Common colds and the flu are the most frequent ARI among under-five children, affecting both the upper and lower respiratory tracts [15]. Existing literature in Bangladesh and other developing countries in Asia and Africa revealed that ARI prevalence was influenced by child age [12, 16–18], child sex [15, 16, 19], type of delivery [12], exclusive breast feeding practice [15, 20], mother’s age [16], parental education [12, 16], low level of wealth index [12, 17], household food insecurity [7], a higher number of children in the household [12], unsafe drinking water and unhygienic toilet facility [12], use of unclean/biomass fuel [18], regional difference [12, 19, 21].

Besides, the common cold, dengue, malaria, chikungunya, diarrhea, typhoid [10], viral infections (including strep throat, chickenpox, the flu, and pneumonia), inflammation, and trauma [22] are the main causes of fever in children. Moreover, the prevalence of fever among under-five children was associated with different factors including younger children [12, 23, 24], male children [19], higher birth order [23], underweight children [21, 23], cesarean section delivery [12], parental education [12, 23], inadequate access to better water and sanitation [12, 25], family wealth index [12, 23], lack of exclusive breastfeeding [20], a higher number of children in the household [12], and regional difference [12, 19, 21].

Furthermore, diarrheal diseases continue to be a major public health concern, disproportionately impacting susceptible groups such as children under five years because of their restricted access to sanitary facilities, clean water, and quality medical care [26]. Previous studies carried out in Bangladesh and other developing countries in Africa and Asia documented various factors influencing the diarrhea prevalence including children of younger age [12, 16, 18, 23], male children [19, 27], delivery by cesarean Sect. [12], lack of exclusive breastfeeding practice [28], mothers’ with no formal education [19, 23, 29], unsafe drinking water [12, 23], unhygienic sanitation facility [12, 28, 29], mothers’ poor handwashing practices [28, 29], improper disposal of child’s stools [29, 30], media exposure [31, 32], nuclear family type [7], low family wealth index [12, 16], and place of residence [12, 33, 34].

The health and livelihoods of the coastal population in Bangladesh, particularly the poor are repeatedly exaggerated by climate change and suffers from climate-induced illness [35] particularly, the younger age groups are more vulnerable to communicable disease. The coastal people are more vulnerable compared to other areas due to their geographical location which is more prone to natural disasters and salinity intrusion, higher incidence of poverty, natural resource and agriculture-based economy, lack of improved water and sanitation facilities, lack of healthcare services and so on. Over 30% of the 35 million people living in Bangladesh’ coastal regions lack adequate resources [36], and the central coastal zone has a relatively low coverage of water, sanitation and hygiene (WASH) facilities (25.2%) compared to the mainland [37]. The main causes of coastal households’ increased vulnerability are a weaker social network, limited access to WASH facilities exacerbated by the increasing frequency and intensity of natural disasters linked to climate change, and poor access to health facilities [38] which ultimately affect the health and wellbeing of children under five.

However, previous studies in Bangladesh which combinedly focused on the prevalence of communicable diseases particularly, ARI, fever, and diarrhea among under-five children have been conducted based on BDHS data [12, 20]. To the best of our knowledge no community-based study has been conducted in the southwestern coastal region of Bangladesh to unearth the prevalence of communicable diseases particularly ARI, fever, and diarrhea collectively among under-five children and the factors influencing the prevalence of these diseases. Moreover, a comprehensive examination of the influencing factors may highlight areas that require further research or where interventions may have the greatest impact along with formulating and implementing region-specific policies. Therefore, the present study aims to investigate the prevalence of communicable diseases particularly ARI, fever, and diarrhea among under-five children and the influencing factors in the southwestern coastal region of Bangladesh by incorporating the social ecological model.

Theoretical framework

Urie Bronfenbrenner introduced the socio-ecological model (SEM) in the 1970 s as a valuable conceptual framework for understanding human development, and it was formally recognized as a theory in the 1980 s [39]. The SEM provides a comprehensive approach to understand childhood disease prevalence by acknowledging that health is impacted by a variety of levels, including individual, interpersonal, organizational, community, and policy level aspects making it essential for developing effective interventions for childhood diseases [40]. Besides, the SEM has been used to address critical issues like suicide, violence, childhood obesity, promotion of vaccination, and cancer screening [41]. The SEM is a framework that illustrates the interconnectedness of individuals and their environments, demonstrating how behaviors and health outcomes are influenced across multiple levels: individual level (focuses on personal factors e.g. age, sex, education, knowledge, attitudes, and skills etc.); interpersonal level (considers the impact of friends, family, and social relationships on behavior); community-level (examines the influence of social settings and organizations, including rules and policies that promote healthy or unhealthy behaviors); and policy-level (encompasses institutional and governmental decisions that affect health on a larger scale). The SEM highlights the reciprocal relationship between individuals and their environments, emphasizing the importance of addressing various levels to improve health outcomes.

We followed SEM as a guiding framework in our study to identify the factors influencing the prevalence of ARI, fever and diarrhea among under-five children. In accordance with the SEM, we have classified the factors related to the under-five children under individual factors such as child age, sex, birth order, birth weight, stunting, wasting and undernutrition, feeding frequency, exclusive breast-feeding practice, and type of delivery. On the other hand, caregivers and household factors were grouped into interpersonal factors like caregivers’ education, occupation, exposure to mass media, type of family, household asset, household food insecurity, household vulnerability, type of house, cooking place, cooking fuel, sources of water in the household, and sanitation facility of the household. Moreover, community-level factors were place of residence, scarcity of drinking water in the community, distance of upazila health complex, and availability of qualified doctor in the locality. Finally, we considered availability of community healthcare center in the community as policy-level factor because it is related to the policy of the government of Bangladesh to set up a community clinic in every village to ensure basic healthcare services to the common people (see Fig. 1).

Fig. 1.

Categorization of the factors influencing the prevalence of ARI, fever, and diarrhea among under-five children based on the social ecological model

Methods and materials

Study site

The study was explanatory in nature and carried out in Dacope upazila (upazila is considered as sub-district) of Khulna district of Bangladesh following cross-sectional survey method. Khulna, one of the country’s 19 coastal districts [42] spans approximately 4,389 square kilometers [43] and has a population of over 2.6 million [44]. Dacope upazila under Khulna district of Bangladesh has been selected to carry out the study (see Map 1) based on its proximity to the coast of the Bay of Bengal. This upazila consisting of one municipality, 9 union, mauzas and 97 villages with a total population of 1,52,316 [45]. The study was conducted in purposively selected six villages considering their location adjacent to the coastal area, with three villages selected from Pankhali union (union is the smallest administrative and local government unit in Bangladesh) (Pankhali, Hoglabunia, and Katabunia villages) and three villages from Sutarkhali union (Sutarkhali, Nolian, and Kalabogi villages).

Map 1.

Map of the study area

Khulna district has been chosen as the study area due to its representation of the southwestern coastal region of Bangladesh, where the population faces significant vulnerabilities compared to other parts of the country. Besides, Khulna division had one of the highest percentage of households with unimproved sources of drinking water (43) and in Khulna district 32.1% of people living below the poverty line [46]. Furthermore, water-borne diseases like diarrhea, dysentery, skin diseases, fevers, pneumonia are more prevalent among children in the coastal regions of Bangladesh due to its more proneness to flood and salinity as well as lack of access to safe water and poor hygiene practices [47, 48]. Moreover, according to the BDHS survey data 2017-18, the prevalence of communicable diseases particularly, ARI among under-five children was 2%, fever (31.3%), and diarrhea (3.9%) in Khulna division [10]. Therefore, considering the above-mentioned criteria, Khulna district, a southwestern coastal region of Bangladesh is selected as the study area.

Participants and sampling

In this study, participants were selected in line with the following inclusion criteria: (i) participants were the caregivers, such as mothers, fathers, grandparents or any person who take care of the children; (ii) the age of the children were within 6 months to 59 months; (iii) if the caregivers have more than one under-five children, then data have been collected about the youngest child; and (iv) the caregivers had been residing in the study area for at least 5 consecutive years. Implementing a minimum five-year residency requirement for caregivers can enhance stability in their living situations, promote deeper connections with the community, and provide a thorough understanding of the communicable diseases that are most common in this region.

A census was conducted at the household level to gather essential information about the population in the study area, while strictly following the inclusion criteria of the participants. According to the census, a population list was developed, and a serial number was assigned. In this study, 3650 caregivers in total were included according to the conducted census. A sample of 348 caregivers was determined with 95% confidence level and 5% margin of error using Cochran’s [49] random sampling formula. Afterwards, we selected 58 participants from each village (each village is considered as stratum) following disproportionate stratified random sampling technique for equal representation of the selected six villages in the study area. To enhance fairness and promote randomization, we randomly chose participants from the population list.

Data collection

A semi-structured interview schedule was followed to collect data from the participants. The interview schedule consisted of several sections focusing on sociodemographic profile of the caregivers and children, household information, household vulnerability context, asset ownership, food insecurity, access to water and sanitation facilities, information about communicable diseases prevalence particularly ARI, fever, and diarrhea (see Supplementary File 1). The quality of the data collection tool was evaluated and reviewed by the three experts to ensure content validity, and to test the index of item-objective congruence (IOC) values for the interview schedule. The data collection tool was revised considering the experts’ comments and suggestions. The feedback and recommendations provided by the experts were considered and used to revise the data collection tool. The first author collected the data from the field with the assistance of some trained data collectors through face-to-face interviews from July to October 2024 after getting the research ethics approval. We confirm that our research was conducted in accordance with the ‘Declaration of Helsinki’ which involves human participants, such as caregivers and children under five. Besides, written informed consent was taken from the respondents who participated in our study. The participants were assured that the collected data will be kept confidential and anonymous.

Data collection was conducted at household level, utilizing a replacement method to improve the accuracy and reliability of the findings. The study aimed at collecting information about the youngest child in the case of caregivers who were taking care of more than one under-five child to gain deeper insights into the prevalence of communicable diseases, particularly ARI, fever and diarrhea as well as the influencing factors. Besides, to effectively measure the nutritional status of children particularly, stunting, wasting and undernutrition, we adopted a standardized anthropometric measurement tool, specifically height-measuring vertical scales and digital weighing machines. Our trained data collectors meticulously measured every child’s height, confirming proper alignment of the child’s head, shoulders, buttocks, and heels with a flat surface. Children’s heights were recorded in centimeters and weight was measured in kilograms to maintain accuracy and facilitate comprehensive analysis.

Measures

Prevalence of ARI, fever, and diarrhea among under-five children

The prevalence of ARI, fever, and diarrhea among under-five children are the outcome variables in this study. ARI prevalence was assessed whether the child had cough, runny nose, and chest-related short or fast breathing (Yes = 1 and no = 0) during the last 4 weeks preceding the survey. On the other hand, the incidence of fever was assessed whether the child had high body temperature usually a core body (rectal) temperature ≥ 38.0 °C (100.4 °F) (Yes = 1 and no = 0). Diarrhea prevalence was assessed whether the child had three or more loose or watery stools per day, or blood in stools (Yes = 1 and no = 0).

Socioeconomic information of the caregivers

Socioeconomic information of the caregivers includes relation of the caregivers (Mother, father, grandparents), age of the caregivers (≤ 20, 21–30, ≥ 31), religious status (Muslim and non-Muslim), living arrangement (With spouse and with relatives), place of residence (Pankhali, Hoglabunia, Katabunia, Sutarkhali, Nolian, and Kalabogi village), caregivers’ education (non-literate, primary [1–5], secondary [6–10], and higher education [≥ 11]), caregivers’ occupation (Farming/fishing/fish cultivation, day labor, housewife, bamboo crafting, and others [Business/job/tailor etc.]), caregivers’ monthly income (Bangladeshi Taka [BDT] no income, < 5000, and ≥ 5000). Caregivers’ exposure to mass media was classified into yes = 1 (if the caregivers were exposed to any of using mobile, listening radio, watching television, and reading magazines and newspapers) and no = 0 (if the caregivers were not exposed to anyone).

Information of the under-five children

Age of the children (6–12 months, 13–24 months, 25–36 months, 37–48 months, and 49–59 months), child sex (Girl/boy), birth order (1, 2 and ≥ 3). Furthermore, birth weight of the under-five children was categorized in accordance to the World Health Organization (WHO) [50] recommended groups e.g. underweight (< 2.5 kg), normal weight (2.5–3.9 kg), and overweight (≥ 4 kg). Besides, children’s nutritional status was measured by three standard indices of physical growth such as stunting (height-for-age), wasting (weight-for-height) and undernutrition (weight-for-age) [51]. Therefore, stunting was categorized into normal height (Z-score is ‘0’ to less than + 2), moderately stunted (Z-score is below − 2.0), and severely stunted (Z-score is below − 3.0). Wasting status was classified into normal weight (Z-score is ‘0’ to less than + 2), moderately wasted (Z-score is below − 2.0), and severely wasted (Z-score is below − 3.0). Finally, undernutrition was grouped into normal weight (Z-score is ‘0’ to less than + 2), overweight (Z-score is above + 2.0), moderately underweight (Z-score is below − 2.0), and severely underweight (Z-score is below − 3.0). Moreover, feeding frequency was categorized into ≤ 4 times, 5–6 times, and ≥ 7 times; exclusive breastfeeding practice in the first six months (No and yes), and type of delivery (Caesarean and normal delivery).

Household information

Household information includes family type (Extended and nuclear family), type of house (Katcha [houses made from mud, thatch, or other low quality materials], pacca [houses mad with high quality materials throughout, such as floor, roof, and walls], and semi-pacca [houses that is made with bricks but roof is with tin]), cooking place (Out-house and in-house), cooking fuel (Non-biomass fuel and biomass fuel [Wood, dung, plant-derived, compressed rice husks]). In addition, households’ sources of drinking water (Improved [Deep tubewell/rainwater/purified water/bottled water] and not improved [Pond/canal/river/shallow tubewell]), and sanitation facilities (Unhygienic [Fixed katcha/hanging latrine beside water/open space/no fixed space] and hygienic [piped sewer systems/pit latrine/pit latrine with ring slab]) were included. Besides, scarcity of safe drinking water in the community (No and yes), availability of community healthcare center in the locality (Yes/no), distance of upazila health complex was measured in kilometer and categorized into < 10 km, 10–20 km, and ˃ 20 km. In addition, availability of qualified doctors in the locality was assessed based on the respondents’ perception on whether there is any Bachelor of Medicine and Bachelor of Surgery (MBBS) doctor available in their locality, and categorized into yes and no.

Household asset index

The household asset index consisted of 27 items used in the BDHS [10] was adopted in this study which was measured on a dichotomized scale of yes = 1 and no = 0. The highest score of the household asset index is 16 and the lowest score is 0 with a mean score of 6. Thus, the household asset index was categorized into three groups such as low (below the mean score 6), moderate (6–10) and high (11–16).

Household food insecurity

Household food insecurity was measured based on Coates’ [52] household food insecurity access scale (index). After that, the households were categorized as food secure, mildly food insecure, moderately food insecure and severely food insecure according to the scale.

Household vulnerability index

To assess the vulnerability of the household in the southwestern coastal region, a modified version of an index developed by Hahn et al. [53] was used. The index consisted of 7 sub-components such as socio-demographic profile, livelihood strategies, social networks, health, food, water and disasters and a total of 23 statements with values ranges from 0 to 1. The total value of the index ranges from 2 to 17 and the average value is 10. Therefore, the household vulnerability index was categorized into low (below the mean score of 10), moderate (10–13) and high vulnerability (14–17).

Data analysis

After the completion of field survey, data were analyzed by the Statistical Package for the Social Sciences (SPSS) V.21. Percentage analysis was conducted to assess the prevalence of ARI, fever, and diarrhea among under-five children. Additionally, Pearson’s χ2 test and Fisher’s exact test (where the cell count is < 5) were conducted to identify the factors influencing the prevalence of ARI, fever, and diarrhea among under-five children using the significance level of p < 0.10. Moreover, the significant variables in bivariate analyses were used in doing binary logistic regression analysis. The results of binary logistic regression were presented by the adjusted odds ratio (AOR) with 95% confidence interval (CI) and a significance level of p < 0.10.

Results

Prevalence of ARI, fever, and diarrhea among under-five children

Table 1 shows information about the prevalence of ARI, fever, and diarrhea among under-five children in the southwestern coastal region of Bangladesh. Results revealed that the highest prevalence of communicable disease among under-five children was ARI at 64.7%, followed by fever (42.2%), and diarrhea (13.5%) respectively.

Table 1.

Prevalence of ARI, fever, and diarrhea among under-five children

Variables	Frequency	Percent (%)
Having ARI (n = 348)
No	123	35.3
Yes	225	64.7
Having fever
No	201	57.8
Yes	147	42.2
Having diarrhea
No	301	86.5
Yes	47	13.5

Bivariate analyses of the factors influencing the prevalence of ARI, fever, and diarrhea among under-five children

Pearson’s χ2 test and Fisher’s exact were conducted to assess the relationship of different personal, interpersonal, community, and policy-level factors with the prevalence of ARI, fever and diarrhea among under-five children (Table 2). All the significant variables (at p < 0.10.) were included in the multivariate logistic regression analyses. Findings from bivariate analyses showed that individual factors such as age and feeding frequency of the children; interpersonal factors like cooking place; and community-level factors such as place of residence were significantly associated with ARI prevalence among under-five children. On the other hand, the prevalence of fever was significantly associated with the individual factors e.g. age of the children, birth weight of the children, and feeding frequency of the children; interpersonal factors like type of house; community-level factors such as place of residence, scarcity of water in the community, and distance of upazila health complex. Moreover, the prevalence of diarrhea was significantly related to the individual factors like age, sex, and undernutrition of the children; interpersonal factors such as type of family and household vulnerability index; community-level factors like scarcity of drinking water in the community, distance of upazila health complex, and availability of qualified doctor in the locality. However, in bivariate analysis, policy-level factor like availability of community healthcare center in the locality was not significantly associated with the prevalence of ARI, fever, and diarrhea among under-five children in the study area.

Table 2.

Bivariate analyses of the association between ARI, fever, and diarrhea prevalence and associated factors

Variables	Having ARI		p value (Test Value)	Having fever		p value (Test Value)	Having diarrhea		p value (Test Value)
	No	Yes		No	Yes		No	Yes
Individual factors
Age of the children
6-12 months	12 (9.8)	44 (19.6)	0.032** (10.550a)	25 (12.4)	31 (21.1)	0.006*** (14.543a)	48 (15.9)	8 (17.0)	0.027** (9.517b)
13-24 months	18 (14.6)	48 (21.3)		41 (20.4)	25 (17.0)		56 (18.6)	10 (21.3)
25-36 months	30 (24.4)	48 (21.3)		36 (17.9)	42 (28.6)		62 (20.6)	16 (34.0)
37-48 months	34 (27.6)	49 (21.8)		53 (26.4)	30 (20.4)		72 (23.9)	11 (23.4)
49-59 months	29 (23.6)	36 (16.0)		46 (22.9)	19 (12.9)		63 (20.9)	2 (4.3)
Sex of the children
Girl	59 (48.0)	101 (44.9)	0.582 (0.303a)	96 (47.8)	64 (43.5)	0.435 (0.610a)	145 (48.2)	15 (31.9)	0.038** (4.326a)
Boy	64 (52.0)	124 (55.1)		105 (52.2)	83 (56.5)		156 (51.8)	32 (68.1)
Birth order
1	55 (44.7)	100 (44.4)	0.746 (0.586a)	89 (44.3)	66 (44.9)	0.804 (0.436a)	134 (44.5)	21 (44.7)	0.319 (2.217 b)
2	50 (40.7)	98 (43.6)		84 (41.8)	64 (43.5)		125 (41.5)	23 (48.9)
≥3	18 (14.6)	27 (12.0)		28 (13.9)	17 (11.6)		42 (14.0)	3 (6.4)
Birth weight
Underweight	17 (13.8)	38 (16.9)	0.490 (1.428a)	39 (19.4)	16 (10.9)	0.067* (5.504a)	50 (16.6)	5 (10.6)	0.374 (2.116 b)
Normal weight	101 (82.1)	182 (80.9)		155 (77.1)	128 (87.1)		241 (80.1)	42 (89.4)
Overweight	5 (4.1)	5 (2.2)		7 (3.5)	3 (2.0)		10 (3.3)	0 (0.0)
Stunting status
Normal height	11 (8.9)	25 (11.1)	0.773 (0.514a)	17 (8.5)	19 (12.9)	0.397 (1.847a)	33 (11.0)	3 (6.4)	0.232 (2.840b)
Moderately stunted	43 (35.0)	73 (32.4)		69 (34.3)	47 (32.0)		104 (34.6)	12 (25.5)
Severely stunted	69 (56.1)	127 (56.4)		115 (57.2)	81 (55.1)		164 (54.5)	32 (68.1)
Wasting status
Normal weight	44 (35.8)	106 (47.1)	0.106 (4.469a)	90 (44.8)	60 (40.8)	0.221 (3.022a)	129 (42.9)	21 (44.7)	0.101 (4.510b)
Moderately wasted	58 (47.2)	83 (36.9)		84 (41.8)	57 (38.8)		118 (39.2)	23 (48.9)
Severely wasted	21 (17.1)	36 (16.0)		27 (13.4)	30 (20.4)		54 (17.9)	3 (6.4)
Individual factors
Undernutrition status
Normal weight	10 (8.1)	24 (10.7)	0.518 (2.314b)	19 (9.5)	15 (10.2)	0.701 (1.441b)	29 (9.6)	5 (10.6)	0.024** (8.908b)
Overweight	1 (0.8)	7 (3.1)		4 (2.0)	4 (2.7)		5 (1.7)	3 (6.4)
Moderately underweight	76 (61.8)	130 (57.8)		124 (61.7)	82 (55.8)		186 (61.8)	20 (42.6)
Severely underweight	36 (29.3)	64 (28.4)		54 (26.9)	46 (31.3)		81 (26.9)	19 (40.4)
Feeding frequency
≤ 4 times	67 (54.5)	120 (53.3)	0.002*** (12.688a)	119 (59.2)	68 (46.3)	0.040** (6.442a)	157 (52.2)	30 (63.8)	0.153 (3.758 a)
5-6 times	48 (39.0)	61 (27.1)		58 (28.9)	51 (34.7)		100 (33.2)	9 (19.1)
≥ 7 times	8 (6.5)	44 (19.6)		24 (11.9)	28 (19.0)		44 (14.6)	8 (17.0)
Type of delivery
Caesarian	54 (43.9)	80 (35.6)	0.126 (2.340a)	79 (39.3)	55 (37.4)	0.721 (0.128a)	114 (37.9)	20 (42.6)	0.540 (0.376 a)
Normal	69 (56.1)	145 (64.4)		122 (60.7)	92 (62.6)		187 (62.1)	27 (57.4)
Exclusive breastfeeding practices
No	16 (13.0)	30 (13.3)	0.932 (0.007a)	26 (12.9)	20 (13.6)	0.855 (0.033a)	40 (13.3)	6 (12.8)	0.922 (0.010a)
Yes	107 (87.0)	195 (86.7)		175 (87.1)	127 (86.4)		261 (86.7)	41 (87.2)
Interpersonal factors
Caregivers’ education
Non literate	3 (2.4)	8 (3.6)	0.678 (1.579b)	6 (3.0)	5 (3.4)	0.984 (0.158a)	9 (3.0)	2 (4.3)	1.249 (0.753b)
Primary	34 (27.6)	65 (28.9)		58 (28.9)	41 (27.9)		88 (29.2)	11 (23.4)
Secondary	74 (60.2)	122 (54.2)		112 (55.7)	84 (57.1)		167 (55.5)	29 (61.7)
Higher education	12 (9.8)	30 (13.3)		25 (12.4)	17 (11.6)		37 (12.3)	5 (10.6)
Interpersonal factors
Caregivers’ occupation
Farming/fishing/fish cultivation	2 (1.6)	5 (2.2)	0.808 (1.792b)	5 (2.5)	2 (1.4)	0.761 (2.028b)	6 (2.0)	1 (2.1)	0.911 (1.173b)
Day labor	1 (0.8)	5 (2.2)		5 (2.5)	1 (0.7)		5 (1.7)	1 (2.1)
Housewife	101 (82.1)	188 (83.6)		165 (82.1)	124 (84.4)		251 (83.4)	38 (80.9)
Bamboo crafting	10 (8.1)	13 (5.8)		13 (6.5)	10 (6.8)		19 (6.3)	4 (8.5)
Others	9 (7.3)	14 (6.2)		13 (6.5)	10 (6.8)		20 (6.6)	3 (6.4)
Type of family
Extended family	66 (53.7)	119 (52.9)	0.891 (0.019a)	103 (51.2)	82 (55.8)	0.402 (0.702a)	154 (51.2)	31 (66.0)	0.059* (3.574a)
Nuclear family	57 (46.3)	106 (47.1)		98 (48.8)	65 (44.2)		147 (48.8)	16 (34.0)
Caregivers’ exposure to mass media
No	59 (48.0)	88 (39.1)	0.110 (2.557a)	84 (41.8)	63 (42.9)	0.842 (0.040a)	127 (42.2)	20 (42.6)	0.963 (0.002a)
Yes	64 (52.0)	137 (60.9)		117 (58.2)	84 (57.1)		174 (57.8)	27 (57.4)
Household asset index
Low	61 (49.6)	121 (53.8)	0.756 (0.561a)	101 (50.2)	81 (55.1)	0.303 (2.391a)	157 (52.2)	25 (53.2)	1.000 (0.065b)
Moderate	55 (44.7)	92 (40.9)		86 (42.8)	61 (41.5)		127 (42.2)	20 (42.6)
High	7 (5.7)	12 (5.3)		14 (7.0)	5 (3.4)		17 (5.6)	2 (4.3)
Household food insecurity index
Food secure household	29 (23.6)	69 (30.7)	0.144 (5.419a)	54 (26.9)	44 (29.9)	0.484 (2.452a)	86 (28.6)	12 (25.5)	0.116 (5.909a)
Mildly food insecure household	30 (24.4)	53 (23.6)		47 (23.4)	36 (24.5)		72 (23.9)	11 (23.4)
Moderately food insecure household	50 (40.7)	67 (29.8)		74 (36.8)	43 (29.3)		105 (34.9)	12 (25.5)
Severely food insecure household	14 (11.4)	36 (16.0)		26 (12.9)	24 (16.3)		38 (12.6)	12 (25.5)
Interpersonal factors
Household vulnerability index
Low	52 (42.3)	92 (40.9)	0.645 (0.877a)	85 (42.3)	59 (40.1)	0.174 (3.501a)	130 (43.2)	14 (29.8)	<0.001*** (18.899a)
Moderate	58 (47.2)	115 (51.1)		103 (51.2)	70 (47.6)		152 (50.5)	21 (44.7)
High	13 (10.6)	18 (8.0)		13 (6.5)	18 (12.2)		19 (6.3)	12 (25.5)
Type of house
Katcha	92 (74.8)	163 (72.4)	0.840 (0.349b)	137 (68.2)	118 (80.3)	0.041** (6.376a)	218 (72.4)	37 (78.7)	0.565 (1.146b)
Pacca	6 (4.9)	14 (6.2)		14 (7.0)	6 (4.1)		19 (6.3)	1 (2.1)
Semi-pacca	25 (20.3)	48 (21.3)		50 (24.9)	23 (15.6)		64 (21.3)	9 (19.1)
Cooking place
Out-house	104 (84.6)	172 (76.4)	0.074* (3.186a)	161 (80.1)	115 (78.2)	0.671 (0.181a)	241 (80.1)	35 (74.5)	0.378 (0.776 a)
In-house	19 (15.4)	53 (23.6)		40 (19.9)	32 (21.8)		60 (19.9)	12 (25.5)
Cooking fuel
Non-biomass fuel	5 (4.1)	4 (1.8)	0.288 (1.566b)	4 (2.0)	5 (3.4)	0.502 (0.661b)	9 (3.0)	0 (0.0)	0.267 (1.443 b)
Biomass fuel	118 (95.9)	221 (98.2)		197 (98.0)	142 (96.6)		292 (7.0)	47 (100)
Sources of water of the household
Improved	46 (37.4)	98 (43.6)	0.265 (1.243a)	89 (44.3)	55 (37.4)	0.199 (1.649a)	127 (42.2)	17 (36.2)	0.436 (0.608a)
Not-improved	77 (62.6)	127 (56.4)		112 (55.7)	92 (62.6)		174 (57.8)	30 (63.8)
Sanitation facility of the household
Unhygienic	81 (65.9)	157 (69.8)	0.452 (0.566a)	134 (66.7)	104 (70.7)	0.419 (0.654a)	204 (67.8)	34 (72.3)	0.531 (0.392a)
Hygienic	42 (34.1)	68 (30.2)		67 (33.3)	43 (29.3)		97 (32.2)	13 (27.7)
Community-level factors
Place of residence
Pankhali village	22 (17.9)	36 (16.0)	0.092* (9.469b)	32 (15.9)	26 (17.7)	<0.001*** (25.829a)	51 (16.9)	7 (14.9)	0.150 (7.920b)
Hoglabunia village	27 (22.0)	31 (13.8)		44 (21.9)	14 (9.5)		51 (16.9)	7 (14.9)
Katabunia village	22 (17.9)	36 (16.0)		33 (16.4)	25 (17.0)		49 (16.3)	9 (19.1)
Sutarkhali village	15 (12.2)	43 (19.1)		24 (11.9)	34 (23.1)		44 (14.6)	14 (29.8)
Nolian village	14 (11.4)	44 (19.6)		25 (12.4)	33 (22.4)		54 (17.9)	4 (8.5)
Kalabogi village	23 (18.7)	35 (15.6)		43 (21.4)	15 (10.2)		52 (17.3)	6 (12.8)
Scarcity of safe drinking water in the community
No	28 (22.8)	47 (20.9)	0.684 (0.165a)	51 (25.4)	24 (16.3)	0.043** (4.110a)	70 (23.3)	5 (10.6)	0.050** (3.828a)
Yes	95 (77.2)	178 (79.1)		150 (74.6)	123 (83.7)		231 (76.7)	42 (89.4)
Distance of upazila health complex
< 10 km	55 (44.7)	76 (33.8)	0.124 (4.173a)	85 (42.3)	46 (31.3)	0.012** (8.813a)	117 (38.9)	14 (29.8)	0.012** (8.902a)
10–20 km	32 (26.0)	74 (32.9)		49 (24.4)	57 (38.8)		83 (27.6)	23 (48.9)
>20 km	36 (29.3)	75 (33.3)		67 (33.3)	44 (29.9)		101 (33.6)	10 (21.3)
Availability of qualified doctor in the locality
No	119 (96.7)	219 (97.3)	0.496 (0.096b)	194 (96.5)	144 (98.0)	0.325 (0.656b)	295 (98.0)	43 (91.5)	0.033** (4.478b)
Yes	4 (3.3)	6 (2.7)		7 (3.5)	3 (2.0)		6 (2.0)	4 (8.5)
Policy-level factors
Availability of community healthcare center
No	22 (17.9)	36 (16.0)	0.652 (0.204a)	33 (16.4)	25 (17.0)	0.884 (0.021a)	49 (16.3)	9 (19.1)	0.623 (0.241a)
Yes	101 (82.1)	189 (84.0)		168 (83.6)	122 (83.0)		252 (83.7)	38 (80.9)

^aChi-square test value ^b Fisher’s Exact test value ***Significant at 1% level; ^**Significant at 5% level; ^*Significant at 10% level

Multivariate analyses of the predictors of ARI, fever, and diarrhea prevalence among under-five children

Out of 27 variables in bivariate analyses, only 4 variables (age of the children, feeding frequency of the children, cooking place and place of residence) were found significant in relation to ARI prevalence among under-five children. On the other hand, 7 variables (age of the children, birth weight of the children, feeding frequency of the children, type of house, place of residence, scarcity of safe drinking water in the community and distance of upazila health complex) were significantly related to the prevalence of fever among under-five children. Besides, 8 variables (child age, sex, undernutrition status, type of family, household vulnerability index, scarcity of safe drinking water in the community, distance of upazila health complex and availability of qualified doctor in the locality) were found significant in relation to diarrhea prevalence among under-five children. These variables were considered to conduct binary logistic regression analysis (see Table 3). Here, the prevalence of ARI, fever and diarrhea among under-five children (Yes = 1 and no = 0) were the outcome variables.

Table 3.

Binary logistic regression analyses of the predictors of ARI, fever, and diarrhea prevalence

Predictors		Having ARI		Having fever		Having diarrhea
		AOR (95% CI)	p value	AOR (95% CI)	p value	AOR (95% CI)	p value
Individual factors
Age of the children
6–12 months(R)
13–24 months		0.967 (0.401–2.337)	0.941	0.644 (0.289–1.437)	0.282	1.333 (0.425–4.180)	0.622
25–36 months		0.665 (0.281–1.572)	0.352	1.404 (0.621–3.176)	0.415	1.909 (0.651–5.594)	0.239
37–48 months		0.607 (0.257–1.431)	0.254	0.572 (0.251–1.302)	0.183	1.593 (0.502–5.055)	0.429
49–59 months		0.550 (0.224–1.353)	0.193	0.524 (0.214–1.284)	0.158	0.247 (0.045–1.365)	0.109
Sex of the children
Girl(R)
Boy		–	–	–	–	1.924 (0.919–4.028)	0.083*
Birth weight of the children
Underweight (R)
Normal weight		–	–	2.584 (1.278–5.226)	0.008***	–	–
Overweight		–	–	1.688 (0.315–9.037)	0.541	–	–
Frequency of feeding children
≤ 4 times(R)
5–6 times		0.805 (0.473–1.368)	0.422	2.180 (1.219–3.898)	0.009***	–	–
≥ 7 times		2.657 (1.030–6.850)	0.043**	2.549 (1.104–5.889)	0.028**	–	–
Undernutrition of the under-five children
Normal weight(R)
Overweight		–	–	–	–	3.146 (0.396–25.021)	0.279
Moderately underweight		–	–	–	–	0.563 (0.173–1.830)	0.340
Severely underweight		–	–	–	–	1.335 (0.403–4.419)	0.637
Interpersonal factors
Type of family
Extended family(R)
Nuclear family		–	–	–	–	0.358 (0.162–0.791)	0.011**
Household vulnerability index
Low (R)
Moderate		–	–	–	-	1.103 (0.494–2.463)	0.811
High		–	–	–	-	4.872 (1.669–14.223)	0.004***
Type of house
Katcha(R)
Pacca		–	–	0.552 (0.178–1.716)	0.305	–	–
Semi-pacca		–	–	0.517 (0.277–0.963)	0.037**	–	–
Cooking place
Out-house(R)
In-house		1.416 (0.730–2.748)	0.303	–	–	–	–
Community-level factors
Place of residence
Pankhali village(R)
Hoglabunia village		0.757 (0.348–1.645)	0.482	0.316 (0.124–0.804)	0.016**	–	–
Katabunia village		1.077 (0.493–2.353)	0.853	0.717 (0.297–1.731)	0.460	–	–
Sutarkhali village		1.797 (0.725–4.450)	0.205	1.444 (0.417–5.007)	0.562	–	–
Nolian village		2.094 (0.904–4.849)	0.085*	2.061 (0.170-24.919)	0.570	–	–
Kalabogi village		1.130 (0.514–2.483)	0.761	0.692 (0.051–9.470)	0.783	–	–
Scarcity of safe drinking water in the community
No(R)
Yes		–	–	1.373 (0.697–2.705)	0.359	2.255 (0.780–6.514)	0.133
Distance of upazila health complex
< 10 km(R)
10–20 km		–	–	1.866 (0.779–4.471)	0.162	2.068 (0.850–5.031)	0.109
>20 km		–	–	0.670 (0.054–8.328)	0.755	0.655 (0.239–1.799)	0.412
Availability of qualified doctor in the locality
No(R)
Yes		–	–	–	–	5.816 (1.204–28.086)	0.028**

AOR Adjusted odds ratio, CI Confidence interval, R Reference category; ***Significant at 1% level; ^**Significant at 5% level; ^*Significant at 10% level

Results revealed that ARI prevalence among under-five children was significantly related to the feeding frequency of the children and place of residence. Moreover, children who were fed ≥ 7 times a day had 2.657 times higher odds of having ARI (AOR = 2.657; 95% CI: 1.030–6.850; p = 0.043) than children who received food ≤ 4 times. On the other hand, children residing in Nolian village had 2.094 times higher odds of having ARI (AOR = 2.094; 95% CI: 0.904–4.849; p = 0.085) compared to children living in Pankhali village.

Besides, the prevalence of fever was significantly associated with birth weight, feeding frequency of the children, type of house, and place of residence. Furthermore, children who had normal birth weight had 2.584 times higher odds of experiencing fever (AOR = 2.584; 95% CI: 1.278–5.226; p = 0.008) compared to children who were underweight at birth. On the other hand, children who received food 5–6 times and ≥ 7 times a day had 2.180 times (AOR = 2.180; 95% CI: 1.219–3.898; p = 0.009) and 2.549 times (AOR = 2.549; 95% CI: 1.104–5.889; p = 0.028) higher odds of having fever respectively than those who were fed ≤ 4 times. Likewise, children living in semi-pacca houses had 0.517 times lower odds of getting fever (AOR = 0.517; 95% CI: 0.277–0.963; p = 0.037) compared to children living in katcha houses. Additionally, children residing in Hoglabunia village had 0.316 times lower odds of experiencing fever (AOR = 0.316; 95% CI: 0.124–0.804; p = 0.016) compared to children living in Pankhali village.

Findings also showed that diarrhea prevalence among under-five children was significantly related to child sex, type of family, household vulnerability index and availability of qualified doctor in the locality. Moreover, boys had 1.924 times higher odds of having diarrhea (AOR = 1.924; 95% CI: 0.919–4.028; p = 0.083) compared to girls. Children from nuclear family had 0.358 times lower odds of getting diarrhea (AOR = 0.358; 95% CI: 0.162–0.791; p = 0.011) than children from extended family. Children from highly vulnerable households had 4.872 times higher odds of experiencing diarrhea (AOR = 4.872; 95% CI: 1.669–14.223; p = 0.004) than children from low vulnerable households. Interestingly, children living in the community where qualified doctors are available had 5.816 times higher odds of getting diarrhea (AOR = 5.816; 95% CI: 1.204–28.086; p = 0.028) than their counterparts.

Discussion

The study investigates the prevalence of ARI, fever, and diarrhea among under-five children and the influencing factors in the southwestern coastal region of Bangladesh which is essential for reducing under-five mortality and morbidity rates by formulating and implementing policies both at local and national levels to achieve the target 3.2 of SDG 3 is ending all preventable deaths under five years of age [54]. Findings revealed that the prevalence of ARI was 64.7%, followed by fever (42%) and diarrhea (13.5%) among children under five. The prevalence of ARI in the present study was higher compared to previous studies conducted in Bangladesh (35.8%) [12], in Ethiopia (16.1%) [55], and in Pakistan (15.9%) [56]. Besides, the prevalence of fever among children under five is 42.2% and it is in line with another study conducted in Bangladesh [20] that reported the prevalence of fever was 42%. Moreover, diarrhea prevalence among under-five children is 13.5% in the current study which is higher compared to previous studies (around 5%) carried out in Bangladesh [12, 16] but lower compared to other developing countries including 22.5% in Pakistan [56] and 29% in Ethiopia [32].

The higher prevalence of ARI, fever, and diarrhea in this study is a result of the study’s location in coastal region that extremely vulnerable to natural disasters like cyclone, storms, flooding and so forth. This is linked to the lack of established water, sanitation, and hygiene services, which further raises the prevalence of these communicable diseases in the study area. Besides, the study acknowledges that the observed variations in the prevalence of communicable diseases could be due to the variations in socioeconomic factors like income and education, healthcare accessibility and even cultural practices around hygiene and food preparation could all play a role.

Different personal, interpersonal, and community-level factors significantly influence the prevalence of ARI, fever, and diarrhea among children under five. Results of regression analysis depicted that the feeding frequency of children and place of residence were the significant predictors of ARI prevalence among under-five children. Besides, birth weight, feeding frequency, type of house, and place of residence were significantly related to the prevalence of fever among under-five children. On the other hand, sex of the children, type of family, household vulnerability index and availability of qualified doctor in the locality were significantly associated to the diarrheal prevalence among under-five children. We followed Urie Bronfenbrenner’s socio-ecological model (SEM) as a guiding framework to identify the factors influencing the prevalence of communicable diseases particularly ARI, fever and diarrhea among under-five children. We have categorized the influencing factors in accordance with the SEM into individual, interpersonal, and community-level factors. However, we did not find any policy-level factor as significant in both bivariate and multivariate analyses.

Individual factors

Consistent with earlier studies [57, 58], the present study demonstrated that child feeding practices contributed to the occurrence of infectious diseases. Among individual factors, feeding frequency was a significant predictor of both ARI and fever prevalence among under-five children. Unexpectedly, children who received food ≥ 7 times a day had higher odds of having ARI and fever than children who were fed ≤ 4 times. This could be because we only focused on the number of feeding instead of emphasizing the quality and quantity of food provided to the children which might lack proper nutrition and it is corroborated by a prior study [59]. However, there is limited information on the impact of feeding practices on the occurrence of ARI and fever among under-five children which needs further investigation. However, it is evident from the existing literature that inadequate and low quality feeding practices increased the risk of malnutrition in children and children who are malnourished have compromised immune systems, making them more vulnerable to infectious diseases which is supported by earlier research conducted in Bangladesh [60, 61], Ethiopia [62], and Nepal [63].

Besides, birth weight is another individual factor which is significantly associated with fever prevalence among under-five children. It is evident from earlier studies conducted in Bangladesh [11, 21, 23] that an increasing link between being underweight or malnourished and having fever which is inconsistent with the present study. Surprisingly, the current study found that children who had normal birth weight had higher odds of having fever compared to children who were underweight at birth. This could be due to less parental concern about children’s health and feeding when a newborn child had normal weight might increase the risk of infectious diseases like fever which requires further investigation.

We also found that boys had higher odds of experiencing diarrhea compared to girls which provides important insight about the gender disparity in the frequency of diarrhea in children. This finding is aligned with previous studies conducted in Bangladesh [16, 64, 65], Ethiopia [27], and Nigeria [19] that male children were more likely to experience diarrhea than female children. The possible reason may be societal norms and gender-based stereotypes that might influence this difference [66] as well as male children are more likely to play outside, they are exposed to infected aerosols from their surroundings [67]. Furthermore, gender-based societal norms and cultural expectations may have distinct effects on exposure to environmental pollutants, general hygiene behaviors, and access to sanitary facilities [68]. Designing effective intervention techniques requires an understanding of the underlying causes of these inequalities. To have deeper understanding of the mechanisms underlying the reported sex disparities, more research should focus on the biological and sociocultural aspects.

Interpersonal factors

Among the interpersonal factors, the present study found that house type is a significant predictor of childhood fever and children who lived in semi-pacca houses had lower odds of having fever compared to children who lived in katcha houses. This could be illustrated by the fact that house type represents a household’s socioeconomic status because better housing represents other facilities like access to safe drinking water and hygiene sanitation, which negatively correlate with disease prevalence and is supported by previous studies in Bangladesh [12], and Ethiopia [69].

Besides, diarrhea prevalence among children under five was significantly influenced by family type and household vulnerability. Moreover, children from nuclear families had lower odds of having diarrhea than children from extended families and it is consistent with previous studies in Ethiopia [27, 70, 71] and other developing countries [72] which found that children from households with more than four family members had greater odds of diarrheal disease than children from households with four or fewer family members. This correlation might be explained by a higher chance of shared exposure to contaminated environments within larger households and possibly more difficulties in maintaining good hygiene practices. In addition, the strain on resources in larger families, in terms of access to improved water, sanitation, and prompt medical care, significantly elevates children’s vulnerability to diarrheal diseases [68].

Children from households with higher vulnerability had higher odds of having diarrhea than children from households with lower vulnerability. This is supported by the prevailing notion in prior studies carried out in Bangladesh [12] and Ethiopia [27, 70] which primarily showed that children living in the poorest families had higher odds of developing diarrheal disease than those living in the wealthiest families. These discrepancies might be due to children from highly vulnerable households are more prone to eating unhygienic and low-quality foods available in the local market which may cause diarrheal disease. In addition, a strong correlation exists between a higher prevalence of diarrhea in children and household vulnerability which is characterized by elements like low socioeconomic status, poor hygiene practices, and limited access to clean water and proper sanitation. This finding could also be explained from an economic perspective that household poverty might be a significant contributing factor to chronic nutritional deficiencies, lower living standards, and access to quality healthcare [73]. These factors, in turn, can result in negative outcomes like chronic child malnutrition, weakened immune systems, and heightened susceptibility to infectious diseases [74].

Community-level factors

Place of residence is evident as a significant determinant of ARI among under-five children in Bangladesh [12, 13, 16, 60] and it is consistent with the present study’s findings. Moreover, children residing in Nolian village had higher odds of having ARI compared to children living in Pankhali village. Similarly, in line with earlier research conducted in Bangladesh and Indonesia [12, 25, 75], the present study showed regional variations in the prevalence of fever among under-five children. Furthermore, children in Hoglabunia village had lower odds of having fever compared to children in Pankhali village. The regional variation of ARI and fever prevalence could be attributed to the geographical and environmental differences in accessing water and sanitation facilities might increase the pathogen spectrum of infections as well as the variations in healthcare infrastructure [76]. Additionally, disparities in food consumption, poor household characteristics, drinking water shortages, unimproved sanitation facilities, cooking materials, temperature, and access to healthcare facilities could all contribute to the regional differences in childhood diseases [17, 77]. The other explanation could be due to cultural factors that influence the likelihood of childhood diseases, such as traditional customs and beliefs as well as community practices in accessing health services. Therefore, local-specific strategies are crucial to minimizing regional disparities in childhood infectious diseases.

The availability of qualified doctors in the locality is a significant predictor of diarrhea prevalence among children under five. In line with prior studies [78, 79], the present study confirms that children’s health and morbidity might be influenced by the preference for medical care and treatment facilities. Surprisingly, children residing in the community where qualified doctors are available had higher odds of having diarrhea than their counterparts. This finding is consistent with another study in Bangladesh that depicted significant association of access to health facility with childhood diarrhea [11]. This might be explained by the fact that diarrhea as a communicable disease transmitted from one to another so if it is treated early through proper treatment might reduce the risk of overall prevalence in a specific area. Nevertheless, poor transportation facilities, lack of healthcare facilities, and distance make it harder to get healthcare in rural areas to treat illnesses, which lowers healthcare utilization in these areas [78]. Thus, the influence of availability of qualified doctors in the community on diarrhea prevalence among under-five children has not studied yet and needs further investigation for better understanding.

Strengths and limitations

To the best of authors knowledge, this is the first community-based study which combinedly investigates ARI, fever, and diarrhea prevalence among under-five children in the southwestern coastal region of Bangladesh. Besides, we followed the social ecological model as a guiding framework for the first time to identify the factors influencing the prevalence of these diseases among under-five children. Additionally, random selection of the participants which is more scientific and mitigates the question of selection bias of the respondents. However, the major limitation of this study lies in the recall bias of the caregivers regarding child diseases. Afterwards, the findings may not be generalizable to the entire younger population in Bangladesh due to the limited sample size. Overall, the findings of this community-based study might be helpful for the policy makers to formulate and implement region-specific policies to combat communicable diseases like ARI, fever, and diarrhea among under-five children in geospatially disadvantaged regions, especially in southwestern coastal region of Bangladesh as well as in other countries with similar traits.

Conclusion

The current study investigates the prevalence of ARI, fever, and diarrhea among under-five children and the influencing factors in the southwestern coastal region of Bangladesh. Findings indicated that ARI has the highest prevalence at 64.7%, followed by fever at 42.2% and diarrhea at 13.5%. Various individual, interpersonal, and community-level factors were influencing the prevalence of these diseases among under-five children. Notably, child feeding practices and place of residence were linked to the prevalence of ARI and fever. Additionally, the prevalence of fever was found to be significantly associated with child’s birth weight and type of house. Moreover, factors related to the prevalence of diarrhea included child sex, family type, household vulnerability, and availability of qualified doctors in the community. The study recommends the initiation of integrated policies and actions from both government and community levels aimed at minimizing the prevalence of communicable diseases among under-five children. Introducing targeted nutrition education programs for both mothers and infants through community outreach. Besides, generating sustainable income opportunities to reduce coastal household vulnerabilities, along with improvements in socioeconomic conditions, housing, and access to safe water and sanitation, are also essential. The study also suggests focusing on infrastructural development to ensure quality healthcare services in the southwestern coastal region, which is more disadvantaged geospatially. Lastly, further research is encouraged to include other coastal regions in Bangladesh and employ both quantitative and qualitative approaches for a better understanding of the issue, leading to the implementation of region-specific policies to combat communicable diseases among under-five children.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

ARI

Acute respiratory infection

SDGs

Sustainable Development Goals

MDGs

Millennium Development Goals

BDHS

Bangladesh Demographic and Health Survey

WASH

Water, sanitation and hygiene

SEM

Socio-ecological model

IOC

Index of item-objective congruence

BDT

Bangladeshi Taka

WHO

World health organization

MBBS

Bachelor of Medicine and Bachelor of Surgery

SPSS

Statistical package for the social sciences

AOR

Adjusted odds ratio

CI

Confidence interval

Author contributions

All authors contributed to the work and gave their approval for the final version for submission. SA developed the idea for the study, supervised data collection, data management, data analysis, and wrote the initial draft of the manuscript. AS was the advisor and supervised the study. AA and WB were the co-advisors and supervised the study as well. AS, AA, and WB revised the manuscript. As a corresponding author, AS states that she had full access to all data and has the final responsibility to submit for publication. The final manuscript has been read and approved by all the authors.

Funding

The authors did not receive any funding for this study.

Data availability

All data are available on reasonable request from the corresponding author.

Declarations

Ethics approval and consent to participate

The study was approved by the Committee of Research Ethics, Faculty of Public Health, Chiang Mai University, Thailand and the reference number is ET020/2024. We also confirm that our research was conducted in accordance with the ‘Declaration of Helsinki’ which involves human participants, such as caregivers and children under five. Besides, written informed consent was obtained from all the participants involved in this study. The participants were assured that the collected data will be kept confidential, anonymous and only be used for research purposes.

Consent for publication

All authors gave their approval for the final version for submission.

Competing interests

The authors declare no competing interests.