Seasonal variation of minimum dietary diversity and its associated factors among children aged 6–59 months in West Gojjam Zone, Ethiopia

Seasonal variation of minimum dietary diversity and its associated factors among children aged 6–59 months in West Gojjam Zone, Ethiopia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Seasonal variation of minimum dietary diversity and its associated factors among children aged 6–59 months in West Gojjam Zone, Ethiopia Melesse Belayneh Yayeh, Memme Girly Makua This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7130879/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Seasonality significantly affects the availability and access of food groups for children under five years of age in Ethiopia. However, there is limited evidence on the seasonal prevalence of minimum dietary diversity (MDD). Addressing this gap is essential to inform policymakers, program planners, and stakeholders in developing targeted strategies to reduce seasonal minimum dietary diversity inadequacies among children aged 6 to 59 months. Objective : To assess the seasonal variation of minimum dietary diversity and its associated factors among children aged 6 to 59 months in the West Gojjam zone, Ethiopia Methods : A longitudinal cross-sectional study was conducted from December 2023 to September 2024 among 840 children aged 6 to 59 months, selected through multistage sampling. MDD was assessed using a standardized tool and data was collected through questionnaires administered by the interviewer in four rounds. Data were entered into EpiData 4.6 and analyzed in SPSS 29. Multivariate logistic regression identified factors associated with MDD, with the 95% CI of AOR used to measure the strength of association and the level of significance set at P < 0.05. Results : A total of 3,324 children aged 6 to 59 months were enrolled in the four rounds of the study. The prevalence of inadequate MDD was highest in June (82.4%), followed by March (73.6%), December (62.4%) and September (45.5%). Inadequate MDD was significantly associated with being surveyed in December (AOR = 2.21), March (AOR = 2.83), and June (AOR = 2.72), compared to September. Other associated factors included households with <5 members (AOR = 1.64), rural residence (AOR = 1.70), no maternal education (AOR = 1.44), the poorest (AOR = 2.32), the poorer (AOR = 1.57) and the middle (AOR = 1.97) wealth index, lack of postnatal care (AOR = 2.46) and poor maternal knowledge of dietary diversity (AOR = 1.36). Conclusions A high prevalence of inadequate MDD was observed among children aged 6 to 59 months in the west Gojjam zone, with significant seasonal variation, highest in June and lowest in September. Key associated factors included season, household size, rural residence, low maternal education, poor wealth status, lack of postnatal care, and limited maternal knowledge. Seasonal and targeted dietary diversity interventions, along with improved maternal education and postnatal care, are critical, particularly in rural and low-income settings. Minimum dietary diversity under five children seasonal prevalence Ethiopia Figures Figure 1 Figure 2 Introduction The Minimum Dietary Diversity Score (MDDS) is defined as the intake of at least four of the seven recommended food groups, reflecting better diet quality and helping to meet the energy and nutrient needs of young children. The seven food groups include: (1) grains, roots, and tubers; (2) legumes and nuts; (3) dairy; (4) flesh foods; (5) eggs; (6) fruits and vegetables; and (7) other fruits and vegetables [ 1 , 2 ]. However, globally, fewer than 25% of children aged 6 to 23 months meet the recommended dietary diversity, and only a small proportion receive nutritionally adequate diets [ 1 ] This contributes to the high burden of undernutrition, with 149.2 million children under five stunted and 45.4 million wasted worldwide. In sub-Saharan Africa, 55 million children are stunted and 11.3 million wasted [ 3 ], the prevalence of MDD is 25.1%, ranging from 5.6% in Burkina Faso to 43.9% in South Africa [ 2 ] and in Ethiopia, it ranges from 88.5% [ 3 ] to 28.8% [ 4 ], with a pooled estimate of 26.78% [ 5 ], due to the variation of seasonal changes [ 6 ]. Seasonal variations in food availability reach their peak during the pre-harvest period, when households face shortages due to dependence on rainfed agriculture and seasonal weather patterns [ 7 , 8 ]. Seasonal variations in dietary diversity are well documented, particularly in agrarian communities in Bangladesh [ 9 ], Ghana [ 8 ], Malawi [ 10 ], Burkina Faso [ 11 – 15 ] and Kenya [ 16 ] indicates that child dietary diversity often peaks during the pre-harvest period, a time typically marked by food scarcity and a higher risk of infectious diseases. Seasonal variation in the inadequate minimum dietary diversity among children under five years of age is a major public health concern that contributes to malnutrition in Ethiopia. Research in southwest Ethiopia shows that inadequate dietary diversity is more prevalent during the pre-harvest season compared to the post-harvest period [ 17 ]. Similarly, data from Northwest Ethiopia show prevalence rates of 47% in December, 56% in March, 76.8% in June, and 41.5% in September [ 18 ]. The achievement of minimum dietary diversity among children under five years of age remains a significant challenge in sub-Saharan Africa (SSA), including Ethiopia, largely due to widespread poverty. Many families in the region struggle with low income, limiting their capacity to afford adequate complementary feeding and to meet the dietary diversity needs essential for young children's nutrition and due to a number factors [ 14 , 16 , 18 ]. Several factors are significantly associated with minimum dietary diversity among children. These include sociodemographic factors such as maternal education, wealth index, maternal occupation, urban residence, and home gardening; child-related factors such as age and sex; knowledge and awareness factors such as media exposure and maternal knowledge about dietary diversity; and utilization of maternal and child health services and agricultural practices [ 5 , 19 – 29 ]. Despite increasing research on child dietary diversity in seasonal contexts, there is still a significant gap in understanding the specific seasonal dynamics driving these variations. Most existing studies rely on one-time assessments of the prevalence of the prevalence of the overall prevalence of minimum dietary diversity prevalence [ 3 , 21 , 22 , 25 , 28 – 37 ], often overlooking the complex seasonal fluctuations and their differential impacts on vulnerable groups, particularly children under five years of age. Few studies have examined the seasonal prevalence of child dietary diversity in drought-prone areas of Southwest Ethiopia [ 17 , 38 ]. To our knowledge, no studies have specifically examined the seasonal prevalence of minimum dietary diversity among children aged 6 to 59 months within communities in the study area that depend heavily on rain-fed agriculture. This study offers valuable information on the timing of seasonal interventions, emphasizing the need for more targeted and seasonally responsive strategies from policy makers, program planners, and other stakeholders. Therefore, the objective of this study was to assess the seasonal variation of minimum dietary diversity and its associated factors among children aged 6 to 59 months in the west Gojjam zone, Ethiopia. Methods Study Setting and Period The study was carried out in three selected districts, Jamabitehnane, Burie Zuria, and Degadamot, located in the West Gojjam Zone of Ethiopia. The West Gojjam Zone has an estimated total population of 3,335,515, comprising approximately 833,878 households and 451,762 children under the age of five years of age. Specifically, the Jabitehnane District is home to 246,376 people in 57,297 households; Burie Zuria has a population of 141,248 with 32,849 households; and Degadamot hosts 192,127 residents in 44,681 households. The study area is agriculturally rich and known for the cultivation of a wide range of crops, including cereals such as teff, maize, millet, barley, and wheat; legumes such as beans, peas, and grass peas; vegetables such as cabbage, collard greens, tomatoes, and potatoes; as well as fruits such as papayas, mangoes, and avocados. In addition to crop production, livestock farming is a key livelihood activity, with cattle, chickens, sheep, and goats being the most frequently raised animals in the zone [ 11 ]. Data collection for the study was carried out in four separate rounds, each corresponding to a major agricultural season in the area. December 2–26, 2023, March 2–25, 2024, June 2–22, 2024, and September 2–21, 2024. Study Design A longitudinal cross-sectional study was conducted to assess the seasonal prevalence of dietary diversity and its associated factors among 6–59 months of children in the West Gojjam zone, Ethiopia. Study population The study population comprised children aged 6 to 59 months and their mothers or caregivers, randomly selected from the designated kebeles for more than a year, were included in the study period. Children were excluded if they had not yet begun complementary feeding, had been sick in the week preceding data collection, or had participated in a special ceremony the day before the survey. Sampling size and sample technique The sample size to evaluate minimum dietary diversity among 659 months of age was calculated using a single population proportion formula n = \(\:\frac{{\left(\frac{Z}{2}\right)}^{2}*PQ}{{d}^{2}}\) = \(\:\frac{{\left(\frac{Z}{2}\right)}^{2}*P(1-p)}{{d}^{2}}\) , n = Sample size; P = prevalence of minimum inadequate dietary diversity of 47.9% in the study area [ 12 ]; Z = standard normal distribution value for the 95% confidence interval (1.96); d = margin error, set at 5%. The initial sample size was calculated as 382 households. To account for potential non-response, a 10% adjustment (38 households) was added, resulting in 420 households. Considering the multistage sampling design and to improve representativeness, a design effect of 2 was applied, yielding 840 households per round. As data were collected in four rounds to capture seasonal variations, the total sample size was 840 × 4 = 3,360 participants. A multistage sampling technique was used to select study participants. In the first stage, three districts were claimed to be selected to represent different agroecological zones: Jabitehnane (Jiga, Mankusa, and Woynima) represents the lowlands; Bure Zuria (Wundegi, Shakwa, and TiyaTiya) represents the midlands; and Degadamot (Shangie, Dekulkana, and Shewa) represents highlands and mountainous areas. In the second stage, nine kebeles (three per district) were selected using simple random sampling. A complete list of households within each selected kebele was compiled. In the final stage, eligible households were selected through systematic random sampling. Household lists maintained by health extension workers were used as the sampling frame to accurately identify and enroll women who met the inclusion criteria ( Fig. 1 . (a)) Study variables Dependent variable Minimum dietary diversity (MDD) refers to the proportion of children aged 6 to 59 months who consumed at least four of the following seven food groups in the past 24 hours: (1) grains, roots, and tubers; (2) legumes and nuts; (3) dairy products; (4) flesh foods; (5) eggs; (6) fruits and vegetables; and (7) other fruits and vegetables [ 1 , 14 ]. Independent variables Independent variables were identified from relevant literature and categorized into three groups: (1) Sociodemographic characteristics, including household-level factors (maternal age, sex of the household head, marital status, religion, residence, maternal and paternal education and occupation) and child-level factors (age and sex); (2) Socioeconomic and environmental characteristics, such as family size, wealth index, type of toilet facility, source of drinking water, food insecurity in the household and maternal/caregiver knowledge of dietary diversity; and (3) Maternal and child health services utilization, including maternal services (use of family planning, antenatal care, place of delivery and postnatal care visits) and child health services (exclusive breastfeeding, immunization, vitamin A supplementation, and recent illnesses such fever, cough, and diarrhea). Data collection procedures and quality assurance Data were collected through face-to-face interviews using a structured, pretested questionnaire adapted from previously validated sources. To facilitate fieldwork, the questionnaire was translated into Amharic (the local language) and then backtranslated into English to ensure consistency. The questionnaire comprised five sections: (1) sociodemographic characteristics of children, (2) utilization of child and maternal health services, (3) environmental and knowledge-related factors, (4) household food security, and (5) minimum dietary diversity. Minimum dietary diversity among children was assessed using a standardized dietary assessment tool [ 14 ]. Caregivers (mothers, fathers, or guardians) were asked whether the child had consumed foods from seven specific food groups in the 24 hours prior to the interview. Data collection was carried out by ten trained Bachelor's nurses and supervised by four master public health field supervisors. Interviews were held at the end of each season and the beginning of the next, specifically during the study period. A total of 840 participants were surveyed in all rounds: 840 mother–child pairs in December, 838 in March, 834 in June and 812 in September, as illustrated in ( Fig. 1 (b)). Each interview session lasted approximately 20 to 30 minutes. To ensure data quality, the consistency of the data collection tool was thoroughly checked and a detailed protocol was developed to guide data collectors and supervisors. This protocol emphasized key aspects such as data quality, ethical standards, task preparation, communication skills, and familiarity with the critical items of the questionnaire. A two-day training workshop was conducted for all data collectors, covering informed consent procedures and proper administration of the questionnaire. Furthermore, a pilot test was carried out in the Dembecha district with 42 household heads who were not part of the main study. Feedback from the pilot informed revisions, including adjustments to the text, correction of typographical errors, and modification of certain items to improve clarity and relevance. Operational Definition The minimum dietary diversity score was calculated by adding the number of food groups consumed by each child in the previous 24 hours during each survey month, with scores ranging from 0 (no food groups) to 7 (all food groups). Children who consumed at least four food groups were classified as having adequate minimum dietary diversity in each month surveyed. The outcome variable was binary: 0 = adequate MDD and 1 = inadequate MDD [ 15 ]. Data Analysis Data were entered and validated using EpiData version 3.4 and subsequently exported to SPSS version 29 for analysis. After the categorization of the variables, descriptive statistics, including frequencies, percentages, tables, and figures, were generated. Binary logistic regression was used to identify factors associated with minimum dietary diversity among children aged 6 to 59 months. Independent variables with a value of p < 0.05 in the bivariate analysis were included in the multivariate model to adjust for possible confounders. The strength of the associations was evaluated using crude and adjusted odds ratios (COR and AOR), along with 95% confidence intervals (CI). Statistical significance was defined as p < 0.05. The fitness of the model was assessed using the Hosmer-Lemeshow goodness of fit test, with a p value of 0.862 indicating an adequate fit. Multicollinearity was also evaluated, and variance inflation factors (VIF) ranging from 1.134 to 3.586 and tolerance values between 0.314 and 0.986 confirmed the absence of multicollinearity issues. Ethical Considerations Ethical approval for this study was obtained from the Department of Health Studies, University of South Africa (UNISA), on 13 October 2023 (Ref. 117606980_CERC_CHS_2023). Additional permissions were obtained from the Amhara Public Health Institute and the West Gojjam Zone Administration. Participants were fully informed about the voluntary nature of the study, the absence of coercion or incentives, and their right to withdraw at any time without penalty. Written informed consent was obtained from all participants and personal identifiers were removed to maintain anonymity. All data were securely stored in a password-protected database. The study was carried out in full adherence to ethical principles, including respect for autonomy, beneficence, non-maleficence, and justice. Results Sociodemographic characteristics A total of 3,324 children aged 6 to 59 months, along with their mothers, were included in the study over the course of one year, resulting in a response rate of 98.9%. The mean age of the mothers was 29 years (±10.43). More than half of the mothers (52.9%) were between 25 and 34 years of age and the vast majority were married (93.6%). Most households were male-headed (81.8%) and Orthodox Christianity was the predominant religion among the respondents (93.5%). A large proportion of the participants lived in rural areas (84.0%). Regarding educational status, more than half of mothers (58.5%) had no formal education, and the most common occupation was farming (56.0%). Similarly, 56.0% of fathers had no formal education, 32.5% had completed primary education, and the majority (86.5%) were engaged in farming. In terms of child characteristics, the mean age of the children was 37 months (±13.18). The largest age group was children between 24 and 35 months (23.8%), followed by those between 12 and 23 months (22.3%). Slightly more than half of the children were male (53.6%) (Table 1). Table 1 Socio-demographic characteristics of households and children in the west Gojjam Zone, Ethiopia, 2024 (n = 3,324) Variables Category Frequency Percent Household variables Age of mothers 18-24 years 766 23.3 25-34 years 1760 52.9 35-44 years 708 21.3 ≥ 45 years 84 2.5 Household head sex Female 606 18.2 Male 2718 81.8 Marital status of mothers Single 214 93.6 Married 3110 6.4 Religion Orthodox 3108 93.5 Muslim 135 4.1 Protestant 81 2.4 Residence Urban 532 16.0 Rural 2792 84.0 Mother educational status No education 1946 58.5 Primary level 1099 33.1 Secondary level 186 5.8 Tertiary level 93 2.8 Mother Occupation Housewife 315 9.5 Farmer 1862 56.0 merchants 98 2.9 employee 154 4.6 Educational status of Father No education 1862 56.0 Primary level 1081 32.5 Secondary level 246 7.4 Tertiary level 135 4.1 Occupational status of Father Farmer 2876 86.5 Employed 301 9.1 Merchant 147 4.4 Child variables Child Age 6-11 months 353 10.6 12-23 months 742 22.3 24-35 months 791 23.8 36-47 months 726 21.8 48-59 months 712 21.4 Child sex Male 1781 53.6 Female 1543 46.4 Socioeconomic and environmental characteristics Of the total of children's households surveyed, approximately two out of three (66.6%) had fewer than five family members. In terms of wealth index, more than one in three households (35.1%) were classified as the poorest, while about one in five (21.5%) fell into the poorer category. Access to essential services was limited. More than half of the households (55.9%) relied on unimproved sources of drinking water. Similarly, access to sanitation was inadequate, with approximately three in five households (58.9%) using unimproved toilet facilities. Regarding knowledge of dietary diversity, more than three out of four respondents (76.3%) had poor knowledge. In terms of food security, more than two thirds of households (67.8%) were found to be food insecure (Table 2). Table 2 Socio-economic and environmental characteristics of the study participants in the west Gojjam zone, Ethiopia, 2024 (n = 3,324) Variables Category Frequency Percent Household Size <5 members 2215 66.6 ≥5 members 1109 33.4 Wealth index Poorest 1168 35.1 Poorer 716 21.5 Middle 625 18.8 Richer 510 15.3 Richest 305 9.2 Drinking water sources Unimproved 1854 55.9 improved 1466 44.1 Toilet facilities types Improved 1366 41.1 Unimproved 1958 58.9 Yes 2178 65.5 Knowledge of Dietary diversity Poor 2536 76.3 Good 788 23.7 Food insecurity Secure 1070 32.2 insecure 2254 67.8 Maternal and Child Maternal Health Service Utilization Characteristics Among the total of the respondents, only one in three mothers (33.4%) had used family planning services. Antenatal care (ANC) utilization was also low, with more than three-quarters (77.9%) of mothers not attending ANC visits. Regarding the place of delivery, more than half of mothers (56.6%) gave birth at home, while 62.4% of the respondents reported follow-up of postnatal care. Exclusive breastfeeding was practiced by 62.2% of mothers practiced exclusive breastfeeding. However, a substantial proportion of children (65.4%) had not received complete immunization, although 65.5% had received vitamin A supplementation. Concerning child morbidity in the two weeks preceding the survey, one-fourth of the children (25.4%) had experienced fever, nearly one-fourth (24.1%) had a cough, and more than one-fifth (22.3%) had diarrhoea (Table 3). Table 3 Maternal and child maternal health service utilization characteristics of study participants in the West Gojjam Zone, Ethiopia, 2024 (n = 3,324) Variables Category Frequency Percent Maternal health services Family planning utilization Not utilized 2115 66.6 Utilized 1109 33.4 ANC utilization Not utilized 3590 77.9 Utilized 734 22.1 Place of delivery Health facility 1441 43.4 Home 1883 56.6 Post-natal visit No 1250 37.6 Yes 2074 62.4 Child feeding and health related characteristics Exclusive breast feeding No 1258 37.8 Yes 2066 62.2 Immunization status Not immunized 2173 65.4 Immunized 1151 34.6 Vitamin A supplementation No 1146 34.5 Yes 2178 65.5 Morbidity in the previous 2 weeks Yes 2391 71.9 Fever Yes 847 25.4 Cough Yes 802 24.1 diarrhoea Yes 742 22.3 Frequency of minimum dietary diversity This study observed seasonal variations in the consumption of different food groups among children in December 2023, March 2024, June 2024, and September 2024 in the study area. Consumption of grains, tubers, and roots remained constant throughout the year, ranging from 96% to 99%. The intake of legumes and nuts declined from 92% in December to 78% in March and 79% in June, then recovered to 93% in September. Flesh food consumption fluctuated, dropping to 31% in June and peaking at 55% in September. Similarly, the proportion of children who consumed dairy products fell from 31% in December to a low of 12% in June, before climbing to 42% in September. Egg consumption decreased in June (24%) after remaining relatively stable in earlier months, then increased to 40% in September. Furthermore, the consumption of fruits and vegetables rich in vitamin A, as well as other fruits and vegetables, exhibited the highest seasonal variability, reaching its lowest levels in March and June (8% and 5%, respectively) and increased in September to 45% and 35%. Overall, September shows the highest dietary diversity across most food groups, likely reflecting post-harvest abundance. In contrast, June and March tend to have the lowest consumption of several key food groups, pointing to seasonal food insecurity or limited access during these months (Table 4). Table 4 seasonal consumption of minimum dietary diversity among children aged 6 to 59 months in the study period in West Gojjam zone, Ethiopia Food Groups December, 2023 (n=840) March, 2024 (n=838) June, 2024 (n=834) September, 2024 (812) Grains, tubers and roots 99% 97% 96% 99% legumes and nuts 92% 78% 79% 93% Flesh foods 31% 40% 31% 55% Dairy products 31% 14% 12% 42% Eggs 35% 37% 24% 40% Vitamin A rich and vegetables 13% 8% 11% 45% other fruits and vegetables 12% 9% 5% 35% Seasonal prevalence of minimum dietary diversity The prevalence of inadequate minimum dietary diversity among children varied significantly between the different seasons. The highest prevalence was observed in June, with 82.4% (95% CI: 78.9, 86.7%) of children who showed inadequate dietary diversity, followed by 73.6% (95% CI: 70.2, 77.8%) in March and 62.4% (95% CI: 59.1, 67.4%) in December. The lowest prevalence was recorded in September, at 45.5% (95% CI 41.4, 49.8%). These findings suggest a clear seasonal pattern, where inadequate dietary diversity was more prevalent during the pre-harvest months (June and March), compared to the post-harvest months (December and September). This indicates that food availability and access, closely linked to seasonal changes, may significantly influence children's dietary diversity (Fig. 2). Factors associated with minimum dietary diversity In binary logistic regression, several factors were significantly associated with inadequate dietary diversity among children, including season, child sex, household head sex, family size, residence, maternal education, wealth index, ANC and PNC follow-up, and maternal knowledge. However, in the multivariate analysis, only season, household size, residence, maternal education (no formal education), wealth index (poorest, poorer, and middle), follow-up of PNC, and poor maternal knowledge remained significantly associated, while household head and child sex, maternal education (primary and secondary), use of ANC, and the richer wealth category were not significantly associated with dietary diversity of children. The study found that seasonal variation emerged as a significant predictor of inadequate dietary diversity. Compared to the post-harvest month of September, the odds of inadequate dietary diversity were significantly higher during the pre-harvest months; December (AOR = 2.210; 95% CI 1.749, 2.792), March (AOR = 2.828; 95% CI 2.218, 3.606), and June (AOR = 2.718; 95% CI 2.136, 3.457). Similarly, children in larger households (5 members) were 1.64 times more likely to experience inadequate dietary diversity than those in smaller households (<5 members) (AOR = 1.640; 95% CI: 1.332, 2.018; p < 0.001) and children living in rural areas were significantly more likely to have inadequate dietary diversity compared to their urban counterparts (AOR = 1.696; 95% CI: 1.311, 2.195; p < 0.001). Children whose mothers did not have formal education were 1.44 times more likely to have inadequate dietary diversity compared to those whose mothers had higher education (AOR = 1.438; 95% CI: 1.242, 2.793; p < 0.05). Furthermore, children from the poorest households had more than twice the odds of inadequate dietary diversity (AOR = 2.318; 95% CI 1.890, 2.843; p < 0.001) compared to those of the richest households. Elevated odds were also observed among children from households of poorer households (AOR = 1.568; 95% CI 1.064, 2.308) and middle income (AOR = 1.968; 95% CI 1.064, 2.309). Children whose mothers did not follow-up postnatal care (PNC) had 2.5 times higher odds of inadequate dietary diversity (AOR = 2.459; 95% CI 2.029, 2.979; p < 0.001) compared to those whose mothers did. Finally, maternal knowledge of dietary diversity played a significant role. Children of mothers with poor knowledge had 36.2% increased odds of inadequate dietary diversity compared to those whose mothers had good knowledge (AOR = 1.362; 95% CI: 1.118, 1.659; p < 0.05) (Table 4). Table 5 Bivariable and multivariable logistic regression of factors associated with minimum dietary diversity among children aged 6 to 59 months in the West Gojjam Zone, Ethiopia, 2024. Character Dietary Diversity Crude OR (95%CI) Adjusted OR (95%CI) Inadequate Adequate Season December 632 208 1.926(1.560 2.378) 2.210 (1.749, 2.792)** March 671 167 2.547(2.043, 3.175) 2.828(2.218, 3.606)** June 638 196 2.063(1.667, 2.554) 2.718(2.136, 3.457)** September 497 315 1 1 Children Sex Male 1279 502 1 1 Female 1159 384 1.185(1.015, 1.383) 1.113(0.955, 1.315) Household head sex Male 2117 601 3.127(1.003, 3.757) 2.318(0.980, 2.843) Female 321 285 1 1 Household size <5 members 1505 710 1 1 ≥5 members 933 176 2.501(2.080, 3.006) 1.640(1.332, 2.018)** Residence Rural 2088 704 1.542 (1.265, 1.881) 1.696(1.311, 2.195)** Urban 350 182 1 1 Educational status of mothers No education 1338 608 1.698(1.427, 2.020) 1.438 (1.242 2.793)* Primary 867 232 2.460(1.637, 3.698) 1.954 (0.986, 2.785) Secondary 157 29 2.031(1.190, 3.467) 1.838(0.896, 3.021) Higher 76 17 1 1 Wealth index Poorest 684 484 2.547(1.123, 5.624) 2.318(1.890, 2.843)** Poorer 591 125 1.857(1.355, 2.545) 1.568(1.064, 2.308)** Medium 530 95 2.191(1.573, 3.052) 1.968 (1.064, 2.309)* Richer 414 96 0.555(0.421, 0.731) 0.730 (0.505, 1.055) Richest 219 86 1 1 ANC utilization Not utilized 1961 629 1.680(1.408, 2.004) 1.208(0.988, 1.473) Utilized 477 257 1 1 Postnatal care visit No 1043 297 2.453(2.059, 2.922) 2.459(2.029, 2.979)** Yes 1395 679 1 1 Knowledge about DDS Poor 1880 656 1.181(1.016, 1.467) 1.362(1.118, 1.659)* Good 558 230 1 1 Note: **: p value <0.001, *: P value<0.05 significantly associated with MDDS Discussion The longitudinal cross-sectional study examined the seasonal variation of minimum dietary diversity and its associated factors among children aged 6 to 59 months in the west Gojjam zone, Ethiopia. The FAO recommends a minimum indicator of dietary diversity for children, based on the consumption of at least four of seven defined food groups within a 24-hour period. This dichotomous measure serves as a benchmark for assessing adequate dietary diversity in children. This study found that inadequate dietary diversity among children varied by season, with the highest rates in June (82.4%), followed by March (73.6%) and December (62.4%) and the lowest in September (45.5%). Factors significantly associated with inadequate dietary diversity included season, child sex, family size, residence, maternal education (no formal education), wealth status (poorest to middle), postnatal care follow-up and maternal knowledge of dietary diversity. In this study, the findings indicate that the pre-harvest season (short season) of March had a high diet diversity compared to the post-harvest seasons (September and December). This finding was in agreement with the study in Ethiopia [ 16 ] and in Western Kenya showed that a significantly higher proportion of children consumed food of inadequate dietary diversity was 37.6% in the post-harvest season (November month surveyed) compared to 47.4% in the pre-harvest season (July/August month) [ 17 ]. The prevalence of seasonal insufficient dietary diversity was lower than in the study in Kenya (93.2%)[ 18 ], Ethiopia (91.5%) [ 15 ] and (Rwanda 77%, Burundi 84%) [ 19 ]; Tanzania [ 20 ]. However, it was higher compared to the study conducted in Addis Ababa, Ethiopia, 39.1% [ 21 ]; and the Morondava (53.4%) and Moramanga (57.9%) districts of Madagascar, respectively [ 22 ]. The differences could be attributed to the community-based and season-focused nature of this study, which could result in lower overall estimates of minimum dietary diversity compared to studies based on small-scale or health facilities. Furthermore, variations in socioeconomic status, dietary habits, cultural practices, caregiver workload, study design, and the use of self-reported data and recall methods may have influenced the estimates of dietary diversity observed. In this study, seasonality was found to be a key factor influencing the availability and accessibility of food groups for the consumption of children. In this study, the children surveyed in June and March were more likely to have inadequate dietary diversity compared to those surveyed in September. These findings are consistent with studies conducted in Ghana [ 23 ], Burkina Faso [ 24 ], Western Kenya [ 25 ] and Southern Ethiopia [ 16 ] and northern Ethiopia [ 13 ]. The possible reason could be that seasonal variations have a huge impact on the availability of food groups, socioeconomic status, and the workload of mothers/caregivers. In this study, household size was significantly associated with minimum dietary diversity. Children living in households with five or more members were 1.64 times more likely to have inadequate dietary diversity compared to those in smaller households with fewer than five members. This study is comparable with a study conducted in southern Ethiopia [ 26 ]. This may be due to the fact that as the size of the household increases, the demand for the recommended diet also increases, potentially leading to a shortage of diverse and nutritious foods. Limited resources, such as food, income, and time, are often stretched thin in larger families, reducing the ability to provide adequate dietary variety. Additionally, financial constraints and divided caregiving responsibilities may limit the individualized attention needed to ensure proper feeding practices for young children. In the present study, residence was significantly associated with dietary diversity among children aged 6 to 59 months. Mothers living in rural areas were 1.7 times more likely to provide inadequate dietary diversity compared to those in urban areas. This finding is consistent with a study conducted in Ethiopia [ 27 ]. A possible explanation is that rural mothers often have limited awareness of dietary diversity and appropriate feeding practices, in part due to restricted access to the media that promote the importance of complementary feeding. In contrast, urban areas typically provide better access to markets, a wider variety of food options, better access to mass media, and more income-generating opportunities, all of which can positively influence children's dietary practices. In the current study, maternal educational status was significantly associated with children's dietary diversity. Children of mothers without formal education were 1.44 times more likely to have inadequate minimum dietary diversity compared to those whose mothers had achieved tertiary education. This finding is consistent with studies conducted at the national level in Ethiopia [ 15 ], as well as in northwest Ethiopia [ 28 ], Madagascar, and Afar, northern Ethiopia [ 29 , 30 ]. The possible explanation is that higher maternal education is associated with greater exposure to health and nutrition information through paid employment, mass media (such as radio, television, and newspapers), and participation in health education sessions and child feeding demonstrations at health facilities factors that contribute to improved child feeding practices. In the present study, the low economic status of households was identified as another key determinant of inadequate dietary diversity among children. Similar findings have been reported in studies conducted in Ethiopia [ 31 ] and Nepal [ 32 ]. These findings can be attributed to the fact that the low economic status of the family limits the ability to purchase a variety of nutritious foods, leading to poor dietary diversity among children. Economically disadvantaged households often rely on monotonous staple-based diets due to limited financial resources, reduced access to markets, and poor food security, all of which contribute to inadequate child nutrition. In the current study, postnatal care emerged as a significant factor influencing dietary diversity among children under five years of age. Mothers who did not receive postnatal care for their index child were 2.5 times more likely to have children with inadequate dietary diversity compared to those who received such care. This finding is consistent with studies conducted in Dabat District, northern Ethiopia [ 27 ], East Africa countries [ 7 ], in a systematic review and meta-analysis in Ethiopia [ 33 ], and in eastern Ethiopia [ 34 ]. A possible explanation is that postnatal care provides opportunities for counseling on appropriate complementary feeding practices, along with practical demonstrations by healthcare providers on how to prepare diverse and nutritious foods, particularly during postnatal and vaccination visits. Finally, the study revealed that children of mothers with poor knowledge of dietary diversity were 1.36 times more likely to experience inadequate dietary diversity compared to their counterparts. This finding is consistent with studies conducted in Ethiopia [ 12 , 35 ], Tanzania [ 20 ], and Malawi [ 36 ]. This can be explained by the fact that mothers with limited knowledge about dietary diversity often lack awareness of the importance of offering a variety of nutrients rich foods to their children. Consequently, they may not prioritize or have the ability to provide the recommended range of food groups necessary for optimal child nutrition. In addition, insufficient understanding of proper feeding practices and the benefits of diverse diets can result in a less frequent inclusion of essential foods, ultimately leading to inadequate dietary diversity among their children. Strengths and limitations of the study The strengths of this study include its large sample size, seasonal assessment, minimal loss of follow-up, and the use of standardized measurement tools. However, several limitations should be noted. The cross-sectional design limits the ability to establish causal relationships between exposures and outcomes. Recall bias may have influenced responses, particularly for food insecurity questions. Furthermore, data used for factor analysis and descriptive statistics were aggregated throughout all seasons, which may have masked seasonal variations. Future studies are recommended to adopt mixed methods and cover broader geographic areas that reflect the diverse seasonal patterns of the country. Conclusions A substantial seasonal variation in minimum dietary diversity was observed among children aged 6 to 59 months in the West Gojjam Zone, Ethiopia, with the highest prevalence of inadequate minimum dietary diversity recorded in June and the lowest in September. Key factors significantly associated with dietary diversity included season, child sex, family size, residence, maternal education (no formal education), household wealth status (poorest to middle), postnatal care visit, and maternal knowledge of dietary diversity. To address these challenges, interventions should aim to reduce seasonal disparities, improve household socioeconomic status, strengthen maternal education, and promote diversified food consumption among children aged 6 to 59 months. Abbreviations AOR Adjusted Odds Ratio CI Confidence Interval COR Crude Odds Ratio EDHS Ethiopian Demographic and Health Survey MDDS Minimum dietary diversity score Declarations Ethics approval and consent to participate This study involved human participants and received ethical approval from the Health Research Ethics Committee of the Department of Health Studies, University of South Africa (UNISA), under reference number 11760680_CREC_CHS_2023. Permission letters were issued by the Amhara Public Health Institute (reference number APHI/03/2053) and the West Gojjam Zone administration (reference number 1443/11/2016) to the study districts. All participants provided their informed written consent in accordance with the ethical principles outlined in the Declaration of Helsinki. Consent for publication All authors have given their consent for the submission of this manuscript to the journal for publication. Clinical Trial Number Not applicable. Availability of data and materials. The primary data used in this study are included in the article; for clarifications, the readers can contact the corresponding author directly. Competing Interests The authors declare that they have no conflicts of interest. Funding The study received support from Bahir Dar University through grant ID BDU1789/2023, which financed data collection costs. The funding body had no influence on the design, supervision, analysis, or interpretation of the study and did not impose any restrictions on publication. Authors' Contributions MBY and MGM were responsible for the conception of the study idea, data collection, and data analysis and interpretation. MBY drafted the initial manuscript, while MGM contributed to the study design and provided substantial revisions to the final draft. All authors reviewed and approved the final version of the manuscript. Acknowledgements We sincerely thank Bahir Dar University for funding the data collection for this study and the University of South Africa, particularly the Faculty of Human Sciences and the Department of Health Studies, for their support throughout the research. We also extend our heartfelt appreciation to the administrators of the West Gojjam Zone and the study districts for their cooperation. Finally, we are deeply grateful to the data collectors, supervisors, and study participants for their invaluable contributions to this work. References Ruel MT. Operationalizing dietary diversity: a review of measurement issues and research priorities. J Nutr. 2003;133(11 Suppl 2):S3911–26. Aboagye RG, Seidu AA, Ahinkorah BO, Arthur-Holmes F, Cadri A, Dadzie LK, et al. Dietary Diversity and Undernutrition in Children Aged 6–23 Months in Sub-Saharan Africa. Nutrients. 2021;13(10):3431. Woldegebriel AG, Desta AA, Gebreegziabiher G, Berhe AA, Ajemu KF, Woldearegay TW. Dietary Diversity and Associated Factors among Children Aged 6–59 Months in Ethiopia: Analysis of Ethiopian Demographic and Health Survey 2016 (EDHS 2016). Int J Pediatr. 2020;2020:1–8. Wuneh AG, Ahmed W, Bezabih AM, Reddy PS. Dietary Diversity and Meal Frequency Practices among Children Aged 6–23 Months in Agro Pastoral Communities in Afar Region, Ethiopia: A Cross-sectional Study. Ecol Food Nutr. 2019;58(6):575–96. Mulatu S, Mekonnen GB, Tsehay YT, Mamo ST, Messelu MA, Belay AE, et al. Dietary Diversity and Associated Factors among Children 6–23 Months Old in Ethiopia: Systematic Review and Meta-Analysis. Discov Med. 2024;36(186):1527–43. Hirvonen K, Taffesse AS, Hassen IW. Seasonality and household diets in Ethiopia. Public Health Nutr. 2016;19(10):1723–30. Bryson JM, Patterson K, Berrang-Ford L, Lwasa S, Namanya DB, Twesigomwe S, et al. Seasonality, climate change, and food security during pregnancy among Indigenous and non-Indigenous women in rural Uganda: Implications for maternal-infant health. PLoS ONE. 2021;16(3):e0247198. Abizari AR, Azupogo F, Nagasu M, Creemers N, Brouwer ID. Seasonality affects dietary diversity of school-age children in northern Ghana. PLoS ONE. 2017;12(8):e0183206. Stevens B, Watt K, Brimbecombe J, Clough A, Judd J, Lindsay D. The role of seasonality on the diet and household food security of pregnant women living in rural Bangladesh: a cross-sectional study. Public Health Nutr. 2017;20(1):121–9. Ferguson EL, Gibson RS, Opare-Obisaw C, Osei‐Opare F, Lamba C, Ounpuu S. Seasonal food consumption patterns and dietary diversity of rural preschool Ghanaian and Malawian children. Ecol Food Nutr. 1993;29(3):219–34. Somé JW, Jones AD. The influence of crop production and socioeconomic factors on seasonal household dietary diversity in Burkina Faso. PLoS ONE. 2018;13(5):e0195685. Savy M, Martin-Prével Y, Traissac P, Eymard-Duvernay S, Delpeuch F. Dietary Diversity Scores and Nutritional Status of Women Change during the Seasonal Food Shortage in Rural Burkina Faso. J Nutr. 2006;136(10):2625–32. Arsenault JENLAPAKLHMM et al. Seasonal differences in food and nutrient intakes among young children and their mothers in rural Burkina Faso. J Nutr Sci. 2014;1–9. Becquey E, Delpeuch F, Konaté AM, Delsol H, Lange M, Zoungrana M, et al. Seasonality of the dietary dimension of household food security in urban Burkina Faso. Br J Nutr. 2012;107(12):1860–70. Arsenault JE, Nikiema L, Allemand P, Ayassou KA, Lanou H, Moursi M, et al. Seasonal differences in food and nutrient intakes among young children and their mothers in rural Burkina Faso. J Nutr Sci. 2014;3:e55. M’Kaibi FKSNOSDPL. Effects of agricultural biodiversity and seasonal rain on dietary adequacy and household food security in rural areas of Kenya. BMC Public Health. 2015;1–11. Belayneh M, Loha E, Lindtjørn B. Seasonal variation of household food insecurity and household dietary diversity on wasting and stunting among young children in a drought prone area in South Ethiopia: a cohort study. Ecol Food Nutr. 2021;60(1):44–69. Yayeh MB, Makua MG. Seasonal prevalence of child undernutrition and its associated factors in the west Gojjam zone, Ethiopia. Archives Public Health. 2025;83(1):146. Assefa D, Belachew T. Minimum dietary diversity and associated factors among children aged 6–23 months in Enebsie Sar Midir Woreda, East Gojjam, North West Ethiopia. BMC Nutr. 2022;8(1):149. Temesgen H, Yeneabat T, Teshome M. Dietary diversity and associated factors among children aged 6–23 months in Sinan Woreda, Northwest Ethiopia: a cross-sectional study. BMC Nutr. 2018;4:5. Bedada Damtie S, Benti Tefera T, Tegegne Haile M. Dietary Diversity Practice and Associated Factors among Children Aged 6–23 Months in Robe Town, Bale Zone, Ethiopia. J Nutr Metab. 2020;2020:1–8. Raru TB, Merga BT, Mulatu G, Deressa A, Birhanu A, Negash B et al. Minimum Dietary Diversity Among Children Aged 6–59 Months in East Africa Countries: A Multilevel Analysis. Int J Public Health. 2023;68. Bandoh DA, Kenu E. Dietary diversity and nutritional adequacy of under-fives in a fishing community in the central region of Ghana. BMC Nutr. 2017;3(1):2. Sema A, Belay Y, Solomon Y, Desalew A, Misganaw A, Menberu T, et al. Minimum Dietary Diversity Practice and Associated Factors among Children Aged 6 to 23 Months in Dire Dawa City, Eastern Ethiopia: A Community-Based Cross-Sectional Study. Glob Pediatr Health. 2021;8:2333794X21996630. Belew AK, Ali BM, Abebe Z, Dachew BA. Dietary diversity and meal frequency among infant and young children: a community based study. Ital J Pediatr. 2017;43(1):73. Temesgen H, Negesse A, Woyraw W, Mekonnen N. Dietary diversity feeding practice and its associated factors among children age 6–23 months in Ethiopia from 2011 up to 2018: a systematic review and meta-analysis. Ital J Pediatr. 2018;44(1):109. Rakotonirainy NH, Razafindratovo V, Remonja CR, Rasoloarijaona R, Piola P, Raharintsoa C, et al. Dietary diversity of 6- to 59-month-old children in rural areas of Moramanga and Morondava districts, Madagascar. PLoS ONE. 2018;13(7):e0200235. Eshete T, Kumera G, Bazezew Y, Mihretie A, Marie T. Determinants of inadequate minimum dietary diversity among children aged 6–23 months in Ethiopia: secondary data analysis from Ethiopian Demographic and Health Survey 2016. Agric Food Secur. 2018;7(1):66. Beyene M, Worku AG, Wassie MM. Dietary diversity, meal frequency and associated factors among infant and young children in Northwest Ethiopia: a cross- sectional study. BMC Public Health. 2015;15(1):1007. Solomon D, Aderaw Z, Tegegne TK. Minimum dietary diversity and associated factors among children aged 6–23 months in Addis Ababa, Ethiopia. Int J Equity Health. 2017;16(1):181. Arimond M, Ruel MT. Dietary diversity is associated with child nutritional status: evidence from 11 demographic and health surveys. J Nutr. 2004;134(10):2579–85. Nguyen PH, Avula R, Ruel MT, Saha KK, Ali D, Tran LM, et al. Maternal and child dietary diversity are associated in Bangladesh, Vietnam, and Ethiopia. J Nutr. 2013;143(7):1176–83. Endalifer ML, Andargie G, Mohammed B, Endalifer BL. Factors associated with dietary diversity among adolescents in Woldia, Northeast Ethiopia. BMC Nutr. 2021;7(1):27. Solomon D, Aderaw Z, Tegegne TK. Minimum dietary diversity and associated factors among children aged 6–23 months in Addis Ababa, Ethiopia. Int J Equity Health. 2017;16(1):181. Yakob T, Israel E, Yakob B, Meshesha M, Jambo E, Utalo T et al. Dietary diversity and its associated factors among school children in conflict affected communities of southern Ethiopia. Front Nutr. 2025;11. Molla W, Adem DA, Tilahun R, Shumye S, Kabthymer RH, Kebede D, et al. Dietary diversity and associated factors among children (6–23 months) in Gedeo zone, Ethiopia: cross - sectional study. Ital J Pediatr. 2021;47(1):233. Dangura D, Gebremedhin S. Dietary diversity and associated factors among children 6–23 months of age in Gorche district, Southern Ethiopia: Cross-sectional study. BMC Pediatr. 2017;17(1):6. Roba KT, O’Connor TP, O’Brien NM, Aweke CS, Kahsay ZA, Chisholm N, et al. Seasonal variations in household food insecurity and dietary diversity and their association with maternal and child nutritional status in rural Ethiopia. Food Secur. 2019;11(3):651–64. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7130879","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":494979851,"identity":"8457028a-b861-4ada-a73d-131370cc410b","order_by":0,"name":"Melesse Belayneh Yayeh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYFAC5gYog4fxAYjkI6yFEa6F2QBEspGihU0CRBHUotve2PjwR8VheYPjvccqv+bYybAxMD98dAOPFrMzB5uNec4cNtxw5lzabdltyUCHsRkb5+DTciOxTZqx7TDjhhs5ZrcltzEDtfCwSePVcv9h+8+f/w7bb7j/xqxYcls9EVpuMLYx8DYcTtxwg8eM8eO2w0RoOZPYLM1zLD155pkcY2nGbcd52JgJ+eX44YMff9RY2/YdP2P48ee2ant+9uaHj/FpgYJmBoUDwITAA2IzE1YOAnUM8g3AWP1BnOpRMApGwSgYYQAAekxOHX1s8HsAAAAASUVORK5CYII=","orcid":"","institution":"Bahir Dar University","correspondingAuthor":true,"prefix":"","firstName":"Melesse","middleName":"Belayneh","lastName":"Yayeh","suffix":""},{"id":494979853,"identity":"2cb1ec35-4ce9-4014-9626-3a4113254b8a","order_by":1,"name":"Memme Girly Makua","email":"","orcid":"","institution":"University of South Africa (UNISA)","correspondingAuthor":false,"prefix":"","firstName":"Memme","middleName":"Girly","lastName":"Makua","suffix":""}],"badges":[],"createdAt":"2025-07-15 13:08:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7130879/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7130879/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88442483,"identity":"fb066d5c-0a36-4052-b646-f1614dadfe61","added_by":"auto","created_at":"2025-08-06 13:06:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":661568,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSampling procedure to select study participants (a) and number of participants interviewed in each season (b) in the West Gojjam Zone, Ethiopia, 2023/2024 [13].\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-7130879/v1/d0f06841175a5a21428b8907.png"},{"id":88442058,"identity":"382fb08d-9fbd-47fa-93bc-98ccd3571727","added_by":"auto","created_at":"2025-08-06 12:58:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":144359,"visible":true,"origin":"","legend":"\u003cp\u003eSeasonal prevalence of minimum dietary diversity among children aged 6 to 59 months in the West Gojjam Zone, Ethiopia, 2024.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-7130879/v1/8b921f4dc1a2056598bfa577.png"},{"id":94065640,"identity":"602da442-8304-4d2d-91df-ddec7c1cbf82","added_by":"auto","created_at":"2025-10-22 07:53:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2162113,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7130879/v1/7e0d7bbb-2176-46f7-a42f-d2ad278f2e8c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Seasonal variation of minimum dietary diversity and its associated factors among children aged 6–59 months in West Gojjam Zone, Ethiopia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe Minimum Dietary Diversity Score (MDDS) is defined as the intake of at least four of the seven recommended food groups, reflecting better diet quality and helping to meet the energy and nutrient needs of young children. The seven food groups include: (1) grains, roots, and tubers; (2) legumes and nuts; (3) dairy; (4) flesh foods; (5) eggs; (6) fruits and vegetables; and (7) other fruits and vegetables [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, globally, fewer than 25% of children aged 6 to 23 months meet the recommended dietary diversity, and only a small proportion receive nutritionally adequate diets [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] This contributes to the high burden of undernutrition, with 149.2\u0026nbsp;million children under five stunted and 45.4\u0026nbsp;million wasted worldwide. In sub-Saharan Africa, 55\u0026nbsp;million children are stunted and 11.3\u0026nbsp;million wasted [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], the prevalence of MDD is 25.1%, ranging from 5.6% in Burkina Faso to 43.9% in South Africa [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] and in Ethiopia, it ranges from 88.5% [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] to 28.8% [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], with a pooled estimate of 26.78% [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], due to the variation of seasonal changes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSeasonal variations in food availability reach their peak during the pre-harvest period, when households face shortages due to dependence on rainfed agriculture and seasonal weather patterns [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Seasonal variations in dietary diversity are well documented, particularly in agrarian communities in Bangladesh [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], Ghana [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], Malawi [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], Burkina Faso [\u003cspan additionalcitationids=\"CR12 CR13 CR14\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and Kenya [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] indicates that child dietary diversity often peaks during the pre-harvest period, a time typically marked by food scarcity and a higher risk of infectious diseases.\u003c/p\u003e\u003cp\u003eSeasonal variation in the inadequate minimum dietary diversity among children under five years of age is a major public health concern that contributes to malnutrition in Ethiopia. Research in southwest Ethiopia shows that inadequate dietary diversity is more prevalent during the pre-harvest season compared to the post-harvest period [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Similarly, data from Northwest Ethiopia show prevalence rates of 47% in December, 56% in March, 76.8% in June, and 41.5% in September [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe achievement of minimum dietary diversity among children under five years of age remains a significant challenge in sub-Saharan Africa (SSA), including Ethiopia, largely due to widespread poverty. Many families in the region struggle with low income, limiting their capacity to afford adequate complementary feeding and to meet the dietary diversity needs essential for young children's nutrition and due to a number factors [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSeveral factors are significantly associated with minimum dietary diversity among children. These include sociodemographic factors such as maternal education, wealth index, maternal occupation, urban residence, and home gardening; child-related factors such as age and sex; knowledge and awareness factors such as media exposure and maternal knowledge about dietary diversity; and utilization of maternal and child health services and agricultural practices [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite increasing research on child dietary diversity in seasonal contexts, there is still a significant gap in understanding the specific seasonal dynamics driving these variations. Most existing studies rely on one-time assessments of the prevalence of the prevalence of the overall prevalence of minimum dietary diversity prevalence [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan additionalcitationids=\"CR29 CR30 CR31 CR32 CR33 CR34 CR35 CR36\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], often overlooking the complex seasonal fluctuations and their differential impacts on vulnerable groups, particularly children under five years of age. Few studies have examined the seasonal prevalence of child dietary diversity in drought-prone areas of Southwest Ethiopia [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo our knowledge, no studies have specifically examined the seasonal prevalence of minimum dietary diversity among children aged 6 to 59 months within communities in the study area that depend heavily on rain-fed agriculture. This study offers valuable information on the timing of seasonal interventions, emphasizing the need for more targeted and seasonally responsive strategies from policy makers, program planners, and other stakeholders. Therefore, the objective of this study was to assess the seasonal variation of minimum dietary diversity and its associated factors among children aged 6 to 59 months in the west Gojjam zone, Ethiopia.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eStudy Setting and Period\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe study was carried out in three selected districts, Jamabitehnane, Burie Zuria, and Degadamot, located in the West Gojjam Zone of Ethiopia. The West Gojjam Zone has an estimated total population of 3,335,515, comprising approximately 833,878 households and 451,762 children under the age of five years of age. Specifically, the Jabitehnane District is home to 246,376 people in 57,297 households; Burie Zuria has a population of 141,248 with 32,849 households; and Degadamot hosts 192,127 residents in 44,681 households. The study area is agriculturally rich and known for the cultivation of a wide range of crops, including cereals such as teff, maize, millet, barley, and wheat; legumes such as beans, peas, and grass peas; vegetables such as cabbage, collard greens, tomatoes, and potatoes; as well as fruits such as papayas, mangoes, and avocados. In addition to crop production, livestock farming is a key livelihood activity, with cattle, chickens, sheep, and goats being the most frequently raised animals in the zone [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eData collection for the study was carried out in four separate rounds, each corresponding to a major agricultural season in the area. December 2\u0026ndash;26, 2023, March 2\u0026ndash;25, 2024, June 2\u0026ndash;22, 2024, and September 2\u0026ndash;21, 2024.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy Design\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA longitudinal cross-sectional study was conducted to assess the seasonal prevalence of dietary diversity and its associated factors among 6\u0026ndash;59 months of children in the West Gojjam zone, Ethiopia.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy population\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe study population comprised children aged 6 to 59 months and their mothers or caregivers, randomly selected from the designated kebeles for more than a year, were included in the study period. Children were excluded if they had not yet begun complementary feeding, had been sick in the week preceding data collection, or had participated in a special ceremony the day before the survey.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSampling size and sample technique\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe sample size to evaluate minimum dietary diversity among 659 months of age was calculated using a single population proportion formula n\u003cb\u003e=\u003c/b\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{{\\left(\\frac{Z}{2}\\right)}^{2}*PQ}{{d}^{2}}\\)\u003c/span\u003e\u003c/span\u003e=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{{\\left(\\frac{Z}{2}\\right)}^{2}*P(1-p)}{{d}^{2}}\\)\u003c/span\u003e\u003c/span\u003e, n\u0026thinsp;=\u0026thinsp;Sample size; P\u0026thinsp;=\u0026thinsp;prevalence of minimum inadequate dietary diversity of 47.9% in the study area [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]; Z\u0026thinsp;=\u0026thinsp;standard normal distribution value for the 95% confidence interval (1.96); d\u0026thinsp;=\u0026thinsp;margin error, set at 5%. The initial sample size was calculated as 382 households. To account for potential non-response, a 10% adjustment (38 households) was added, resulting in 420 households. Considering the multistage sampling design and to improve representativeness, a design effect of 2 was applied, yielding 840 households per round. As data were collected in four rounds to capture seasonal variations, the total sample size was 840 \u0026times; 4\u0026thinsp;=\u0026thinsp;3,360 participants.\u003c/p\u003e\u003cp\u003eA multistage sampling technique was used to select study participants. In the first stage, three districts were claimed to be selected to represent different agroecological zones: Jabitehnane (Jiga, Mankusa, and Woynima) represents the lowlands; Bure Zuria (Wundegi, Shakwa, and TiyaTiya) represents the midlands; and Degadamot (Shangie, Dekulkana, and Shewa) represents highlands and mountainous areas. In the second stage, nine kebeles (three per district) were selected using simple random sampling. A complete list of households within each selected kebele was compiled. In the final stage, eligible households were selected through systematic random sampling. Household lists maintained by health extension workers were used as the sampling frame to accurately identify and enroll women who met the inclusion criteria (\u003cb\u003eFig.\u0026nbsp;1\u003c/b\u003e. (a))\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy variables\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eDependent variable\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMinimum dietary diversity (MDD) refers to the proportion of children aged 6 to 59 months who consumed at least four of the following seven food groups in the past 24 hours: (1) grains, roots, and tubers; (2) legumes and nuts; (3) dairy products; (4) flesh foods; (5) eggs; (6) fruits and vegetables; and (7) other fruits and vegetables [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eIndependent variables\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIndependent variables were identified from relevant literature and categorized into three groups: (1) Sociodemographic characteristics, including household-level factors (maternal age, sex of the household head, marital status, religion, residence, maternal and paternal education and occupation) and child-level factors (age and sex); (2) Socioeconomic and environmental characteristics, such as family size, wealth index, type of toilet facility, source of drinking water, food insecurity in the household and maternal/caregiver knowledge of dietary diversity; and (3) Maternal and child health services utilization, including maternal services (use of family planning, antenatal care, place of delivery and postnatal care visits) and child health services (exclusive breastfeeding, immunization, vitamin A supplementation, and recent illnesses such fever, cough, and diarrhea).\u003c/p\u003e\u003cp\u003e\u003cb\u003eData collection procedures and quality assurance\u003c/b\u003e\u003c/p\u003e\u003cp\u003eData were collected through face-to-face interviews using a structured, pretested questionnaire adapted from previously validated sources. To facilitate fieldwork, the questionnaire was translated into Amharic (the local language) and then backtranslated into English to ensure consistency. The questionnaire comprised five sections: (1) sociodemographic characteristics of children, (2) utilization of child and maternal health services, (3) environmental and knowledge-related factors, (4) household food security, and (5) minimum dietary diversity.\u003c/p\u003e\u003cp\u003eMinimum dietary diversity among children was assessed using a standardized dietary assessment tool [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Caregivers (mothers, fathers, or guardians) were asked whether the child had consumed foods from seven specific food groups in the 24 hours prior to the interview.\u003c/p\u003e\u003cp\u003eData collection was carried out by ten trained Bachelor's nurses and supervised by four master public health field supervisors. Interviews were held at the end of each season and the beginning of the next, specifically during the study period. A total of 840 participants were surveyed in all rounds: 840 mother\u0026ndash;child pairs in December, 838 in March, 834 in June and 812 in September, as illustrated in (\u003cb\u003eFig.\u0026nbsp;1\u003c/b\u003e (b)). Each interview session lasted approximately 20 to 30 minutes.\u003c/p\u003e\u003cp\u003eTo ensure data quality, the consistency of the data collection tool was thoroughly checked and a detailed protocol was developed to guide data collectors and supervisors. This protocol emphasized key aspects such as data quality, ethical standards, task preparation, communication skills, and familiarity with the critical items of the questionnaire. A two-day training workshop was conducted for all data collectors, covering informed consent procedures and proper administration of the questionnaire. Furthermore, a pilot test was carried out in the Dembecha district with 42 household heads who were not part of the main study. Feedback from the pilot informed revisions, including adjustments to the text, correction of typographical errors, and modification of certain items to improve clarity and relevance.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOperational Definition\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe minimum dietary diversity score was calculated by adding the number of food groups consumed by each child in the previous 24 hours during each survey month, with scores ranging from 0 (no food groups) to 7 (all food groups). Children who consumed at least four food groups were classified as having adequate minimum dietary diversity in each month surveyed. The outcome variable was binary: 0\u0026thinsp;=\u0026thinsp;adequate MDD and 1\u0026thinsp;=\u0026thinsp;inadequate MDD [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eData were entered and validated using EpiData version 3.4 and subsequently exported to SPSS version 29 for analysis. After the categorization of the variables, descriptive statistics, including frequencies, percentages, tables, and figures, were generated. Binary logistic regression was used to identify factors associated with minimum dietary diversity among children aged 6 to 59 months. Independent variables with a value of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in the bivariate analysis were included in the multivariate model to adjust for possible confounders. The strength of the associations was evaluated using crude and adjusted odds ratios (COR and AOR), along with 95% confidence intervals (CI). Statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The fitness of the model was assessed using the Hosmer-Lemeshow goodness of fit test, with a p value of 0.862 indicating an adequate fit. Multicollinearity was also evaluated, and variance inflation factors (VIF) ranging from 1.134 to 3.586 and tolerance values between 0.314 and 0.986 confirmed the absence of multicollinearity issues.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEthical Considerations\u003c/b\u003e\u003c/p\u003e\u003cp\u003e Ethical approval for this study was obtained from the Department of Health Studies, University of South Africa (UNISA), on 13 October 2023 (Ref. 117606980_CERC_CHS_2023). Additional permissions were obtained from the Amhara Public Health Institute and the West Gojjam Zone Administration. Participants were fully informed about the voluntary nature of the study, the absence of coercion or incentives, and their right to withdraw at any time without penalty. Written informed consent was obtained from all participants and personal identifiers were removed to maintain anonymity. All data were securely stored in a password-protected database. The study was carried out in full adherence to ethical principles, including respect for autonomy, beneficence, non-maleficence, and justice.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eSociodemographic characteristics\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eA total of 3,324 children aged 6 to 59 months, along with their mothers, were included in the study over the course of one year, resulting in a response rate of 98.9%. The mean age of the mothers was 29 years (\u0026plusmn;10.43). More than half of the mothers (52.9%) were between 25 and 34 years of age and the vast majority were married (93.6%). Most households were male-headed (81.8%) and Orthodox Christianity was the predominant religion among the respondents (93.5%). A large proportion of the participants lived in rural areas (84.0%). Regarding educational status, more than half of mothers (58.5%) had no formal education, and the most common occupation was farming (56.0%). Similarly, 56.0% of fathers had no formal education, 32.5% had completed primary education, and the majority (86.5%) were engaged in farming.\u003c/p\u003e\n\u003cp\u003eIn terms of child characteristics, the mean age of the children was 37 months (\u0026plusmn;13.18). The largest age group was children between 24 and 35 months (23.8%), followed by those between 12 and 23 months (22.3%). Slightly more than half of the children were male (53.6%) (Table 1).\u003c/p\u003e\n\u003cp\u003eTable 1 Socio-demographic characteristics of households and children in the west Gojjam Zone,\u003cem\u003e\u0026nbsp;\u003c/em\u003eEthiopia, 2024 (n = 3,324)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"628\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 244px;\"\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003eVariables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercent\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 628px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHousehold variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eAge of mothers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e18-24 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e766\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e23.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e25-34 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e52.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e35-44 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e708\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e21.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026ge; 45 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eHousehold head sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e606\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e18.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e2718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e81.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eMarital status of mothers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e93.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e3110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eReligion\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eOrthodox\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e3108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e93.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eMuslim\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eProtestant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e16.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e2792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e84.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eMother educational status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eNo education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1946\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e58.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003ePrimary level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e33.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eSecondary level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eTertiary level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eMother Occupation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eHousewife\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e9.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eFarmer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1862\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e56.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003emerchants\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eemployee\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eEducational status of Father\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eNo education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1862\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e56.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003ePrimary level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e32.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eSecondary level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eTertiary level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eOccupational status of Father\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eFarmer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e2876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e86.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e9.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eMerchant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 628px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChild variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eChild Age\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e6-11 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e353\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e12-23 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e22.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e24-35 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e23.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e36-47 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e726\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e21.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e48-59 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e712\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e21.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eChild sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e53.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1543\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e46.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eSocioeconomic and environmental characteristics\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eOf the total of children\u0026apos;s households surveyed, approximately two out of three (66.6%) had fewer than five family members. In terms of wealth index, more than one in three households (35.1%) were classified as the poorest, while about one in five (21.5%) fell into the poorer category. Access to essential services was limited. More than half of the households (55.9%) relied on unimproved sources of drinking water. Similarly, access to sanitation was inadequate, with approximately three in five households (58.9%) using unimproved toilet facilities. Regarding knowledge of dietary diversity, more than three out of four respondents (76.3%) had poor knowledge. In terms of food security, more than two thirds of households (67.8%) were found to be food insecure (Table 2).\u003c/p\u003e\n\u003cp\u003eTable 2 Socio-economic and environmental characteristics of the study participants in the west Gojjam zone, Ethiopia, 2024 (n = 3,324)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"628\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 244px;\"\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003eVariables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercent\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eHousehold Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026lt;5 members\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e2215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e66.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026ge;5 members\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e33.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eWealth index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003ePoorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e35.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003ePoorer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e21.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e18.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eRicher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e15.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eRichest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eDrinking water sources\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eUnimproved\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e55.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eimproved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1466\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e44.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eToilet facilities types\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eImproved\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e41.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eUnimproved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1958\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e58.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e2178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e65.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eKnowledge of Dietary diversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e2536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e76.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e788\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e23.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eFood insecurity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eSecure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e32.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003einsecure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e2254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e67.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eMaternal and Child Maternal Health Service Utilization Characteristics\u003c/h2\u003e\n\u003cp\u003eAmong the total of the respondents, only one in three mothers (33.4%) had used family planning services. Antenatal care (ANC) utilization was also low, with more than three-quarters (77.9%) of mothers not attending ANC visits. Regarding the place of delivery, more than half of mothers (56.6%) gave birth at home, while 62.4% of the respondents reported follow-up of postnatal care. Exclusive breastfeeding was practiced by 62.2% of mothers practiced exclusive breastfeeding. However, a substantial proportion of children (65.4%) had not received complete immunization, although 65.5% had received vitamin A supplementation. Concerning child morbidity in the two weeks preceding the survey, one-fourth of the children (25.4%) had experienced fever, nearly one-fourth (24.1%) had a cough, and more than one-fifth (22.3%) had diarrhoea (Table 3).\u003c/p\u003e\n\u003cp\u003eTable 3 Maternal and child maternal health service utilization characteristics of study participants in the West Gojjam Zone, Ethiopia, 2024 (n = 3,324)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"608\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003eVariables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercent\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 608px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaternal health services\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eFamily planning utilization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eNot utilized\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e2115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e66.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eUtilized\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e1109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e33.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eANC utilization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eNot utilized\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e3590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e77.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eUtilized\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e22.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003ePlace of delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eHealth facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e1441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e43.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eHome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e1883\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e56.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003ePost-natal visit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e1250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e37.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e2074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e62.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 608px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChild feeding and health related characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eExclusive breast feeding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e1258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e37.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e2066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e62.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eImmunization status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eNot immunized\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e2173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e65.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eImmunized\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e1151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e34.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eVitamin A supplementation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e1146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e34.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e2178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e65.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eMorbidity in the previous 2 weeks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e2391\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e71.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eFever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e25.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eCough\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e802\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e24.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003ediarrhoea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e22.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eFrequency of minimum dietary diversity\u003c/h2\u003e\n\u003cp\u003eThis study observed seasonal variations in the consumption of different food groups among children in December 2023, March 2024, June 2024, and September 2024 in the study area. Consumption of grains, tubers, and roots remained constant throughout the year, ranging from 96% to 99%. The intake of legumes and nuts declined from 92% in December to 78% in March and 79% in June, then recovered to 93% in September. Flesh food consumption fluctuated, dropping to 31% in June and peaking at 55% in September. Similarly, the proportion of children who consumed dairy products fell from 31% in December to a low of 12% in June, before climbing to 42% in September. Egg consumption decreased in June (24%) after remaining relatively stable in earlier months, then increased to 40% in September. Furthermore, the consumption of fruits and vegetables rich in vitamin A, as well as other fruits and vegetables, exhibited the highest seasonal variability, reaching its lowest levels in March and June (8% and 5%, respectively) and increased in September to 45% and 35%.\u0026nbsp;Overall, September shows the highest dietary diversity across most food groups, likely reflecting post-harvest abundance. In contrast, June and March tend to have the lowest consumption of several key food groups, pointing to seasonal food insecurity or limited access during these months\u0026nbsp;(Table 4).\u003c/p\u003e\n\u003cp\u003eTable 4 seasonal consumption of minimum dietary diversity among children aged 6 to 59 months in the study period in West Gojjam zone, Ethiopia\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"634\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 195px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFood Groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDecember, 2023\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=840)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarch, 2024\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=838)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJune, 2024\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=834)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeptember, 2024\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(812)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 195px;\"\u003e\n \u003cp\u003eGrains, tubers and roots\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e99%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003e97%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e96%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003e99%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 195px;\"\u003e\n \u003cp\u003elegumes and nuts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e92%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003e78%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e79%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003e93%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 195px;\"\u003e\n \u003cp\u003eFlesh foods\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e31%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003e40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e31%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003e55%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 195px;\"\u003e\n \u003cp\u003eDairy products\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e31%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003e14%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003e42%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 195px;\"\u003e\n \u003cp\u003eEggs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e35%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003e37%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e24%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003e40%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 195px;\"\u003e\n \u003cp\u003eVitamin A rich and vegetables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e13%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003e8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003e45%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 195px;\"\u003e\n \u003cp\u003eother fruits and vegetables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003e9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003e35%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eSeasonal prevalence of minimum dietary diversity\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe prevalence of inadequate minimum dietary diversity among children varied significantly between the different seasons. The highest prevalence was observed in June, with 82.4% (95% CI: 78.9, 86.7%) of children who showed inadequate dietary diversity, followed by 73.6% (95% CI: 70.2, 77.8%) in March and 62.4% (95% CI: 59.1, 67.4%) in December. The lowest prevalence was recorded in September, at 45.5% (95% CI 41.4, 49.8%). These findings suggest a clear seasonal pattern, where inadequate dietary diversity was more prevalent during the pre-harvest months (June and March), compared to the post-harvest months (December and September). This indicates that food availability and access, closely linked to seasonal changes, may significantly influence children\u0026apos;s dietary diversity (Fig. 2).\u003c/p\u003e\n\u003ch2\u003eFactors associated with minimum dietary diversity\u003c/h2\u003e\n\u003cp\u003eIn binary logistic regression, several factors were significantly associated with inadequate dietary diversity among children, including season, child sex, household head sex, family size, residence, maternal education, wealth index, ANC and PNC follow-up, and maternal knowledge.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, in the multivariate analysis, only season, household size, residence, maternal education (no formal education), wealth index (poorest, poorer, and middle), follow-up of PNC, and poor maternal knowledge remained significantly associated, while household head and child sex, maternal education (primary and secondary), use of ANC, and the richer wealth category were not significantly associated with dietary diversity of children.\u003c/p\u003e\n\u003cp\u003eThe study found that seasonal variation emerged as a significant predictor of inadequate dietary diversity. Compared to the post-harvest month of September, the odds of inadequate dietary diversity were significantly higher during the pre-harvest months; December (AOR = 2.210; 95% CI 1.749, 2.792), March (AOR = 2.828; 95% CI 2.218, 3.606), and June (AOR = 2.718; 95% CI 2.136, 3.457). Similarly, children in larger households (5 members) were 1.64 times more likely to experience inadequate dietary diversity than those in smaller households (\u0026lt;5 members) (AOR = 1.640; 95% CI: 1.332, 2.018; p \u0026lt; 0.001) and children living in rural areas were significantly more likely to have inadequate dietary diversity compared to their urban counterparts (AOR = 1.696; 95% CI: 1.311, 2.195; p \u0026lt; 0.001). Children whose mothers did not have formal education were 1.44 times more likely to have inadequate dietary diversity compared to those whose mothers had higher education (AOR = 1.438; 95% CI: 1.242, 2.793; p \u0026lt; 0.05). Furthermore, children from the poorest households had more than twice the odds of inadequate dietary diversity (AOR = 2.318; 95% CI 1.890, 2.843; p \u0026lt; 0.001) compared to those of the richest households. Elevated odds were also observed among children from households of poorer households (AOR = 1.568; 95% CI 1.064, 2.308) and middle income (AOR = 1.968; 95% CI 1.064, 2.309). Children whose mothers did not follow-up postnatal care (PNC) had 2.5 times higher odds of inadequate dietary diversity (AOR = 2.459; 95% CI 2.029, 2.979; p \u0026lt; 0.001) compared to those whose mothers did. Finally, maternal knowledge of dietary diversity played a significant role. Children of mothers with poor knowledge had 36.2% increased odds of inadequate dietary diversity compared to those whose mothers had good knowledge (AOR = 1.362; 95% CI: 1.118, 1.659; p \u0026lt; 0.05) (Table 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 5 Bivariable and multivariable logistic regression of factors associated with minimum dietary diversity among children aged 6 to 59 months in the West Gojjam Zone, Ethiopia, 2024.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"657\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDietary Diversity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCrude OR\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted OR\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInadequate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdequate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 657px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeason\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eDecember\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1.926(1.560 2.378)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e2.210 (1.749, 2.792)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eMarch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e671\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e2.547(2.043, 3.175)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e2.828(2.218, 3.606)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eJune\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e2.063(1.667, 2.554)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e2.718(2.136, 3.457)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eSeptember\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 657px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChildren Sex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e502\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e384\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1.185(1.015, 1.383)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1.113(0.955, 1.315)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 657px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHousehold head sex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e2117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e3.127(1.003, 3.757)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e2.318(0.980, 2.843)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e321\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 657px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHousehold size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026lt;5 members\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e710\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026ge;5 members\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e933\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e2.501(2.080, 3.006)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1.640(1.332, 2.018)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 657px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e2088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1.542 (1.265, 1.881)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1.696(1.311, 2.195)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 657px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational status of mothers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eNo education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1.698(1.427, 2.020)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1.438 (1.242 2.793)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e2.460(1.637, 3.698)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1.954 (0.986, 2.785)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e2.031(1.190, 3.467)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1.838(0.896, 3.021)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eHigher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 657px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWealth index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003ePoorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e684\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e2.547(1.123, 5.624)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e2.318(1.890, 2.843)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003ePoorer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e591\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1.857(1.355, 2.545)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1.568(1.064, 2.308)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e530\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e2.191(1.573, 3.052)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1.968 (1.064, 2.309)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eRicher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e414\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e0.555(0.421, 0.731)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e0.730 (0.505, 1.055)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eRichest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 657px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eANC utilization\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eNot utilized\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1961\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e629\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1.680(1.408, 2.004)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1.208(0.988, 1.473)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eUtilized\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 657px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePostnatal care visit\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e2.453(2.059, 2.922)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e2.459(2.029, 2.979)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e679\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 657px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKnowledge about DDS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e1880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1.181(1.016, 1.467)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1.362(1.118, 1.659)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e558\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 657px;\"\u003e\n \u003cp\u003eNote: **: p value \u0026lt;0.001, *: P value\u0026lt;0.05 significantly associated with MDDS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe longitudinal cross-sectional study examined the seasonal variation of minimum dietary diversity and its associated factors among children aged 6 to 59 months in the west Gojjam zone, Ethiopia. The FAO recommends a minimum indicator of dietary diversity for children, based on the consumption of at least four of seven defined food groups within a 24-hour period. This dichotomous measure serves as a benchmark for assessing adequate dietary diversity in children. This study found that inadequate dietary diversity among children varied by season, with the highest rates in June (82.4%), followed by March (73.6%) and December (62.4%) and the lowest in September (45.5%). Factors significantly associated with inadequate dietary diversity included season, child sex, family size, residence, maternal education (no formal education), wealth status (poorest to middle), postnatal care follow-up and maternal knowledge of dietary diversity.\u003c/p\u003e\u003cp\u003eIn this study, the findings indicate that the pre-harvest season (short season) of March had a high diet diversity compared to the post-harvest seasons (September and December). This finding was in agreement with the study in Ethiopia [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and in Western Kenya showed that a significantly higher proportion of children consumed food of inadequate dietary diversity was 37.6% in the post-harvest season (November month surveyed) compared to 47.4% in the pre-harvest season (July/August month) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The prevalence of seasonal insufficient dietary diversity was lower than in the study in Kenya (93.2%)[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], Ethiopia (91.5%) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and (Rwanda 77%, Burundi 84%) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]; Tanzania [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, it was higher compared to the study conducted in Addis Ababa, Ethiopia, 39.1% [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]; and the Morondava (53.4%) and Moramanga (57.9%) districts of Madagascar, respectively [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The differences could be attributed to the community-based and season-focused nature of this study, which could result in lower overall estimates of minimum dietary diversity compared to studies based on small-scale or health facilities. Furthermore, variations in socioeconomic status, dietary habits, cultural practices, caregiver workload, study design, and the use of self-reported data and recall methods may have influenced the estimates of dietary diversity observed.\u003c/p\u003e\u003cp\u003eIn this study, seasonality was found to be a key factor influencing the availability and accessibility of food groups for the consumption of children. In this study, the children surveyed in June and March were more likely to have inadequate dietary diversity compared to those surveyed in September. These findings are consistent with studies conducted in Ghana [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], Burkina Faso [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], Western Kenya [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and Southern Ethiopia [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and northern Ethiopia [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The possible reason could be that seasonal variations have a huge impact on the availability of food groups, socioeconomic status, and the workload of mothers/caregivers.\u003c/p\u003e\u003cp\u003eIn this study, household size was significantly associated with minimum dietary diversity. Children living in households with five or more members were 1.64 times more likely to have inadequate dietary diversity compared to those in smaller households with fewer than five members. This study is comparable with a study conducted in southern Ethiopia [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This may be due to the fact that as the size of the household increases, the demand for the recommended diet also increases, potentially leading to a shortage of diverse and nutritious foods. Limited resources, such as food, income, and time, are often stretched thin in larger families, reducing the ability to provide adequate dietary variety. Additionally, financial constraints and divided caregiving responsibilities may limit the individualized attention needed to ensure proper feeding practices for young children.\u003c/p\u003e\u003cp\u003eIn the present study, residence was significantly associated with dietary diversity among children aged 6 to 59 months. Mothers living in rural areas were 1.7 times more likely to provide inadequate dietary diversity compared to those in urban areas. This finding is consistent with a study conducted in Ethiopia [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. A possible explanation is that rural mothers often have limited awareness of dietary diversity and appropriate feeding practices, in part due to restricted access to the media that promote the importance of complementary feeding. In contrast, urban areas typically provide better access to markets, a wider variety of food options, better access to mass media, and more income-generating opportunities, all of which can positively influence children's dietary practices.\u003c/p\u003e\u003cp\u003eIn the current study, maternal educational status was significantly associated with children's dietary diversity. Children of mothers without formal education were 1.44 times more likely to have inadequate minimum dietary diversity compared to those whose mothers had achieved tertiary education. This finding is consistent with studies conducted at the national level in Ethiopia [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], as well as in northwest Ethiopia [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], Madagascar, and Afar, northern Ethiopia [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The possible explanation is that higher maternal education is associated with greater exposure to health and nutrition information through paid employment, mass media (such as radio, television, and newspapers), and participation in health education sessions and child feeding demonstrations at health facilities factors that contribute to improved child feeding practices.\u003c/p\u003e\u003cp\u003eIn the present study, the low economic status of households was identified as another key determinant of inadequate dietary diversity among children. Similar findings have been reported in studies conducted in Ethiopia [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] and Nepal [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. These findings can be attributed to the fact that the low economic status of the family limits the ability to purchase a variety of nutritious foods, leading to poor dietary diversity among children. Economically disadvantaged households often rely on monotonous staple-based diets due to limited financial resources, reduced access to markets, and poor food security, all of which contribute to inadequate child nutrition.\u003c/p\u003e\u003cp\u003eIn the current study, postnatal care emerged as a significant factor influencing dietary diversity among children under five years of age. Mothers who did not receive postnatal care for their index child were 2.5 times more likely to have children with inadequate dietary diversity compared to those who received such care. This finding is consistent with studies conducted in Dabat District, northern Ethiopia [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], East Africa countries [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], in a systematic review and meta-analysis in Ethiopia [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], and in eastern Ethiopia [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. A possible explanation is that postnatal care provides opportunities for counseling on appropriate complementary feeding practices, along with practical demonstrations by healthcare providers on how to prepare diverse and nutritious foods, particularly during postnatal and vaccination visits.\u003c/p\u003e\u003cp\u003eFinally, the study revealed that children of mothers with poor knowledge of dietary diversity were 1.36 times more likely to experience inadequate dietary diversity compared to their counterparts. This finding is consistent with studies conducted in Ethiopia [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], Tanzania [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and Malawi [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. This can be explained by the fact that mothers with limited knowledge about dietary diversity often lack awareness of the importance of offering a variety of nutrients rich foods to their children. Consequently, they may not prioritize or have the ability to provide the recommended range of food groups necessary for optimal child nutrition. In addition, insufficient understanding of proper feeding practices and the benefits of diverse diets can result in a less frequent inclusion of essential foods, ultimately leading to inadequate dietary diversity among their children.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStrengths and limitations of the study\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe strengths of this study include its large sample size, seasonal assessment, minimal loss of follow-up, and the use of standardized measurement tools. However, several limitations should be noted. The cross-sectional design limits the ability to establish causal relationships between exposures and outcomes. Recall bias may have influenced responses, particularly for food insecurity questions. Furthermore, data used for factor analysis and descriptive statistics were aggregated throughout all seasons, which may have masked seasonal variations. Future studies are recommended to adopt mixed methods and cover broader geographic areas that reflect the diverse seasonal patterns of the country.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eA substantial seasonal variation in minimum dietary diversity was observed among children aged 6 to 59 months in the West Gojjam Zone, Ethiopia, with the highest prevalence of inadequate minimum dietary diversity recorded in June and the lowest in September. Key factors significantly associated with dietary diversity included season, child sex, family size, residence, maternal education (no formal education), household wealth status (poorest to middle), postnatal care visit, and maternal knowledge of dietary diversity. To address these challenges, interventions should aim to reduce seasonal disparities, improve household socioeconomic status, strengthen maternal education, and promote diversified food consumption among children aged 6 to 59 months.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eAOR\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAdjusted Odds Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eCI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence Interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eCOR\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCrude Odds Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eEDHS\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEthiopian Demographic and Health Survey\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eMDDS\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMinimum dietary diversity score\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThis study involved human participants and received ethical approval from the Health Research Ethics Committee of the Department of Health Studies, University of South Africa (UNISA), under reference number 11760680_CREC_CHS_2023. Permission letters were issued by the Amhara Public Health Institute (reference number APHI/03/2053) and the West Gojjam Zone administration (reference number 1443/11/2016) to the study districts. All participants provided their informed written consent in accordance with the ethical principles outlined in the Declaration of Helsinki.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eAll authors have given their consent for the submission of this manuscript to the journal for publication.\u003c/p\u003e\n\u003ch2\u003eClinical Trial Number\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials.\u003c/h2\u003e\n\u003cp\u003eThe primary data used in this study are included in the article; for clarifications, the readers can contact the corresponding author directly.\u003c/p\u003e\n\u003ch2\u003eCompeting Interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThe study received support from Bahir Dar University through grant ID BDU1789/2023, which financed data collection costs. The funding body had no influence on the design, supervision, analysis, or interpretation of the study and did not impose any restrictions on publication.\u003c/p\u003e\n\u003ch2\u003eAuthors' Contributions\u003c/h2\u003e\n\u003cp\u003eMBY and MGM were responsible for the conception of the study idea, data collection, and data analysis and interpretation. MBY drafted the initial manuscript, while MGM contributed to the study design and provided substantial revisions to the final draft. All authors reviewed and approved the final version of the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe sincerely thank Bahir Dar University for funding the data collection for this study and the University of South Africa, particularly the Faculty of Human Sciences and the Department of Health Studies, for their support throughout the research. We also extend our heartfelt appreciation to the administrators of the West Gojjam Zone and the study districts for their cooperation. Finally, we are deeply grateful to the data collectors, supervisors, and study participants for their invaluable contributions to this work.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRuel MT. Operationalizing dietary diversity: a review of measurement issues and research priorities. J Nutr. 2003;133(11 Suppl 2):S3911\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAboagye RG, Seidu AA, Ahinkorah BO, Arthur-Holmes F, Cadri A, Dadzie LK, et al. Dietary Diversity and Undernutrition in Children Aged 6\u0026ndash;23 Months in Sub-Saharan Africa. Nutrients. 2021;13(10):3431.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWoldegebriel AG, Desta AA, Gebreegziabiher G, Berhe AA, Ajemu KF, Woldearegay TW. 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BMC Nutr. 2021;7(1):27.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSolomon D, Aderaw Z, Tegegne TK. Minimum dietary diversity and associated factors among children aged 6\u0026ndash;23 months in Addis Ababa, Ethiopia. Int J Equity Health. 2017;16(1):181.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYakob T, Israel E, Yakob B, Meshesha M, Jambo E, Utalo T et al. Dietary diversity and its associated factors among school children in conflict affected communities of southern Ethiopia. Front Nutr. 2025;11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMolla W, Adem DA, Tilahun R, Shumye S, Kabthymer RH, Kebede D, et al. Dietary diversity and associated factors among children (6\u0026ndash;23 months) in Gedeo zone, Ethiopia: cross - sectional study. Ital J Pediatr. 2021;47(1):233.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDangura D, Gebremedhin S. Dietary diversity and associated factors among children 6\u0026ndash;23 months of age in Gorche district, Southern Ethiopia: Cross-sectional study. BMC Pediatr. 2017;17(1):6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoba KT, O\u0026rsquo;Connor TP, O\u0026rsquo;Brien NM, Aweke CS, Kahsay ZA, Chisholm N, et al. Seasonal variations in household food insecurity and dietary diversity and their association with maternal and child nutritional status in rural Ethiopia. Food Secur. 2019;11(3):651\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Minimum dietary diversity, under five children, seasonal prevalence, Ethiopia","lastPublishedDoi":"10.21203/rs.3.rs-7130879/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7130879/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Seasonality significantly affects the availability and access of food groups for children under five years of age in Ethiopia. However, there is limited evidence on the seasonal prevalence of minimum dietary diversity (MDD). Addressing this gap is essential to inform policymakers, program planners, and stakeholders in developing targeted strategies to reduce seasonal minimum dietary diversity inadequacies among children aged 6 to 59 months.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e: To assess the seasonal variation of minimum dietary diversity and its associated factors among children aged 6 to 59 months in the West Gojjam zone, Ethiopia\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: A longitudinal cross-sectional study was conducted from December 2023 to September 2024 among 840 children aged 6 to 59 months, selected through multistage sampling. MDD was assessed using a standardized tool and data was collected through questionnaires administered by the interviewer in four rounds. Data were entered into EpiData 4.6 and analyzed in SPSS 29. Multivariate logistic regression identified factors associated with MDD, with the 95% CI of AOR used to measure the strength of association and the level of significance set at P \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: A total of 3,324 children aged 6 to 59 months were enrolled in the four rounds of the study. The prevalence of inadequate MDD was highest in June (82.4%), followed by March (73.6%), December (62.4%) and September (45.5%). Inadequate MDD was significantly associated with being surveyed in December (AOR = 2.21), March (AOR = 2.83), and June (AOR = 2.72), compared to September. Other associated factors included households with \u0026lt;5 members (AOR = 1.64), rural residence (AOR = 1.70), no maternal education (AOR = 1.44), the poorest (AOR = 2.32), the poorer (AOR = 1.57) and the middle (AOR = 1.97) wealth index, lack of postnatal care (AOR = 2.46) and poor maternal knowledge of dietary diversity (AOR = 1.36).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e A high prevalence of inadequate MDD was observed among children aged 6 to 59 months in the west Gojjam zone, with significant seasonal variation, highest in June and lowest in September. Key associated factors included season, household size, rural residence, low maternal education, poor wealth status, lack of postnatal care, and limited maternal knowledge. Seasonal and targeted dietary diversity interventions, along with improved maternal education and postnatal care, are critical, particularly in rural and low-income settings.\u003c/p\u003e","manuscriptTitle":"Seasonal variation of minimum dietary diversity and its associated factors among children aged 6–59 months in West Gojjam Zone, Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-06 12:50:00","doi":"10.21203/rs.3.rs-7130879/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4a2c5380-455e-494a-aaa7-e1e6f1ce666c","owner":[],"postedDate":"August 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-22T07:53:28+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-06 12:50:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7130879","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7130879","identity":"rs-7130879","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}