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. 2021 Nov 27;7(12):e08495. doi: 10.1016/j.heliyon.2021.e08495

Dietary diversity (DD) and associated factors among Lactating women (LW) in Pawie district, Northwest, Ethiopia, 2019: community-based cross-sectional study

Sileshi Mulatu a,, Habtamu Dinku a, Chalachew Yenew b
PMCID: PMC8645438  PMID: 34917799

Abstract

Background

Low Dietary Diversity (DD) result in severe problem among the vulnerable group in low-income countries (LICs), whose diets are predominantly starchy staples. Lactating Women (LW) from LICs are considered a nutritionally vulnerable group. It results in many consequences on the health and well-being of children, households, communities, and the nation. However, there is little empirical evidence on factors contributing to low DD among LW in Ethiopia and the proposed study site. Therefore, this study aimed at assessing the DD and associated factors among LW in Pawie district, Northwest Ethiopia.

Methods

A Community-based cross-sectional study was conducted among 806 LW from March to May 2019 G.C. DD assessed using 24 h dietary recall methods with structured questionnaires.

A mean dietary diversity score (DDS) was computed for ten food groups. Food insecurity measured using a 9-item Household Food Insecurity Access Scale (HFIAS). The multivariable logistic regression model was used to see the relevant associations. The variables which have a significant association with DD were identified based on AOR, P-value ≤ 0.05, and 95% Cl.

Results

A total of 806 LW aged 15–49 years were interviewed with a response rate of 100%. About two-third of LW had low DD (<5 food groups). Fathers occupation being daily laborer [AOR = 1.82, 95% CI (.339, 9.784)], birth interval less than 24 months [AOR = 3.7, 95 % CI (1.743, 7.885)], family size greater than six members [AOR = 1.55, 95 % CI (1.046, 2.313)] and food insecurity [AOR = 2.23, 95 % CI (1.626, 3.066)] were more likely associated with the low DD among LW compared to their counterpart.

Conclusion

The DD among LW was low. Low Dietary Diversity was statistically associated with low birth intervals, large family sizes, and food insecurity. Hence, attention should be paid to the identified factors of low DD of LW to improve their health, and that of their children as well as their family.

Keywords: Lactating women, Dietary diversity, Household Food Insecurity Access Scale, Pawie, Ethiopia


Lactating women, Dietary diversity, Household Food Insecurity Access Scale, Pawie, Ethiopia.

1. Introduction

Dietary diversity (DD) defined as the number of different food groups consumed over a given reference period, capable of ensuring adequate intake of essential nutrients that can promote the health, physical and mental development. Hence, lactating Women(LW) are vulnerable to malnutrition due to the physiological vulnerability that comes with childbearing is the first reason, and maternal nutrient needs increase during lactation [1].

Low Dietary Diversity results in severe problems among LW in LICs, whose diets are predominantly starchy staples. Similarly, the consumption of animal products, seasonal fruits, and vegetables are generally absent or minimal. The DD in LW is critical because they require additional energy and nutritious foods [2, 3]. LW's having a good DD, their children, adolescents, and adults may have good health, growth, and development. In a few studies, what LW consumed is strongly associated with what their children, adolescents, and adults eat [1, 4].

In Northern Ghana, 52% of LW dietary diversity scores were less than five different food groups. The five most widely consumed food groups were cereals and grains, fish and seafood, dark green leafy vegetables, species, condiments and beverages, and other vegetables apart from vitamin A rich vegetables such as tomatoes, onion, and egg-plant [5]. Besides, In West Gojam, Ethiopia, adequate DD for LW was 47.2% [6].

In Southwestern Bangladesh: a lower educational achievement, the husband is a daily wage earner, and higher household size (3 or high family members) may likely be associated with low mean DDS of LW [7]. In Northern Ghana: age, marital status, household membership structure, ethnicity, and literacy as significant socio-economic determinants of DD of LW [5]. Besides, in Aksum town, Tigray, Northern Ethiopia, reported that factors like the difference in education, feeding culture, average monthly income, not practicing home gardening, and source of drinking water were strongly associated with low DD of LW [8].

To prevent and correct a nutritional vulnerability in LW, one of the best interventions is DD and might be a means of achieving the sustainable development goals (SDGs) in an integrated manner [9, 10]. Despite a few studies on diversified nutritional requirements for LW, there are not enough studies on factors associated with low DD among LW in Ethiopia and the proposed study site. As a result, substantial numbers of LW in Ethiopia are exceedingly vulnerable to inadequate DD and nutritional deficiencies [9, 10, 11]. Therefore, this study aimed at assessing the DD and associated factors among LW in the Pawie district, Northwest Ethiopia.

2. Methods

2.1. Study area

The study was conducted in the Pawie district. It is tracking down in Benishangul-Gumuz Regional State, Northwest Ethiopia. The study area has an estimated 5, 244 square kilometers, which is located at 623 and 447 KMs away from the capital city of Ethiopia (Addis Ababa), and the regional capital city Assossa respectively. According to the 2016 Metekel zone finance and economic development projection, a total of 51,895 population are living in the district (of which 25,639 female and 26, 257 male). Administratively Pawe district has 20 (one urban and 19 rural) kebeles (the smallest administrative unit in Ethiopia). According to the 2016 bi-annual report of the Pawie district health office, there were 2,425 LW in the district. Currently, Pawe district has one general hospital, four public health centers, and 20 health posts [11].

Grains, potato, sorghum, pea and beans, and vegetables (cabbage, carrots, and tomatoes) are the primary agricultural products.

2.2. Study design and period

A community-based cross-sectional study was conducted from March to May 2019 to assess dietary diversity and associated factors among lactating women in Pawie district Benishangul Gumuz Regional State, Northwest Ethiopia.

2.3. Study population

All lactating women who lived in the Pawie district for at least six months were eligible for the study, LW who was permanently residing in the selected kebeles were considered the study units.

2.4. Sample size determination

In this study, the sample size was determined, by using the single population proportion formula. Taking the prevalence of good DDS as 47.8% for lactating women [1] to obtain the maximum sample size with 5% marginal error, 95% CI, a 5% non-response rate. The minimum required sample size was 403. Since it is a multistage we use 2 design effects. Then, the final sample size of this study was 806.

2.5. Sampling procedures

Multistage sampling technique was employed to select kebeles, households, and lactating women. From a total of 20 rural kebeles of Pawie district, five kebeles were selected by simple random sampling (lottery method) technique. LW was allocated to each selected kebeles by proportionate allocation. From each selected kebele, LW were designated by a simple random sampling method.

2.6. Data collection procedures

The data was collected with a face-to-face interview by the data collectors using a structured and pre-tested questionnaire. The questionnaires was adapted from English published articles and Food and Agriculture Organization (FAO) guidelines for measuring individual DD, 2011 and Household Food Insecurity Access Scale (HFIAS) to measure household food insecurity [12]. Written and structured questionnaire that consist of socio-demographic data, DD of LW and risk factors for DD used. The questionnaire had four main contents: socio-demographic data characteristics; a source of food, DD, and other individual-related factors; food security-related questions. The level of DD measured using minimum DD for a woman (MDD-W), the dichotomous indicator/tools developed by the FAO [13, 14].

A total of 16 food groups (cereals, white tubers and roots, vitamin A-rich vegetables and tubers, dark green leafy vegetables, other vegetables, vitamin A-rich fruits, other fruits, organ meat, flesh meat, eggs, fish and seafood, legumes, seeds and nuts, milk and milk products, oils and fats, sweets, spices, condiments, and beverages) considered. These food groups further regrouped into ten food groups (i.e., all starchy staples, pulses (beans, peas, and lentils), nuts and seeds, all dairy, flesh foods (including organ meat), eggs, vitamin A-rich dark green leafy vegetables, other vitamin A-rich vegetables and fruits, other vegetables, and other fruits) during analysis [3, 4].

The Minimum Dietary Diversity Score (DDS) was calculated for each LW during the previous 24 h to classify the mother's dietary diversity as good DD (≥5 food groups) or poor DD (<5 food groups) from ten food groups. Then, the outcome variable coded as a good DD ≥ 5 food groups as “1” and poor DD < 5 food groups as “0” for logistic regression analysis [12, 15].

The score of the respondents has taken, and respondents were classified as having good DD and poor DD by taking their responses if they consume greater or equal to five food groups and less than five food groups respectively [15, 16]. Then, LW who consume more than five food groups in the last 24 h classified as having good DD and poor DD otherwise. The rest questioner was adapted and modified from WHO and similar studies [4, 17, 18].

2.7. Data quality control

For administering the structured questionnaire, 2 Public Health Nutrition and 8 health extension workers were employed as supervisors and data collectors sequentially. The training was given for two days for both supervisors and data collectors on the objective, the relevance, confidentiality of information, respondent's right, time of data collection, and reorganization of the collected data from respective sub-cities, and submission on due time.

In addition, a pre-test was conducted on 5% of the actual sample size out of sampled kebele. The principal investigator and the supervisors checked the collected data for completeness, and corrective measures were taken accordingly. The collected data were cleaned, coded, and explored before analysis.

2.8. Data processing and analysis

The data were entered, coded, and cleaned using the Epi data and exported to SPSS software version 21 for analysis. Frequencies and cross-tabulations used to summarize descriptive statistics of the data. Bivariate logistic regression was employed to see the association of each variable with dependent variables. Finally, independent variables with p-values < 0.2 in the bivariate logistic regression were entered into multivariate logistic regressions to control the effect of confounding. All variables with P–values less than 5% considered to have a significant relationship with the outcome variable.

2.9. Ethical considerations

Ethical clearance was obtained from the institutional review board of the school of nursing, College of Medicine and Health Sciences, Bahir Dar University. The letter was submitted to Pawie district health office. An official permission letter from the office was obtained for the next steps.

The written permission letter from the district health office was submitted to each kebeles administrative office, which is the actual data collection conducted. All lactating mothers were informed about the objective of the study. Then after the objectives of the study was explained, all mothers' age was >18, and informed verbal consent from every LW was obtained. The right to participate or withdraw from the study at any time without any requirement was disclosed to the participant clearly. Furthermore, the confidentiality of the information obtained from participants was guaranteed by all data collectors and investigators by using code numbers and keeping the questionnaires locked.

3. Results

3.1. Socio-demographic characteristics of the LW

A total of 806 LW aged 15–49 years interviewed, with a response rate of 100%. Of the total LW, 50% were in the age group 20–29, 586 (72.7 %) were Amhara. Of the entire study participants, 474 (58.8%) were Orthodox. Nearly two-thirds, 493 (61.2%) LW were unable to read and write, and 570 (70.7%) participants were housewives. 521 (64.6%) of the study participants had a family member of 4–6 members, whereas 639 (79.3%) birth intervals were greater than 24 months (Table 1).

Table 1.

Socio-demographic and economic related characteristics among lactating women (n = 806) at Pawie district Benishangul Gumuz regional state, Northwest, Ethiopia, 2019.

Background characteristics Frequencies Percentage (%)
Age of the mother (in years) (n = 806)
 <20 years 98 12.2
 20–29 years 388 48.1
 30–39 years 289 35.9
 40 and above 31 3.8
Ethnicity (n = 806)
 Amhara 586 72.7
 Agew 66 8.2
 Kembata 60 7.4
 Oromo 59 7.3
 Others 35 4.3
Religion (n = 806)
 Orthodox 474 58.8
 Muslim 256 31.8
 Protestant 60 7.4
 Catholic 16 2.0
Marital status (n = 806)
 Married 748 92.8
 Divorced 50 6.2
 Widowed 8 1.0
Maternal educational level (n = 806)
 Unable to read and write 493 61.2
 Able to read and write 142 17.6
 Primary school 96 11.9
 Secondary and above 75 9.3
Educational level of the father (n = 806)
 Unable to read and write 392 48.6
 Able to read and write 211 26.2
 Primary 94 11.7
 Secondary and above 109 13.5
Maternal occupation status (n = 806)
 House wife 570 70.7
 Governmental employee 73 9.1
 Merchant 99 12.3
 Daily laborers 64 7.9
Occupation status of the father (n = 806)
 Farmer 522 64.8
 Merchant 163 20.2
 Gove employee 69 8.5
 Daily laborer 52 6.5
Income (in etb) (n = 806)
 <500 ETB 63 7.8
 500–1000 ETB 253 31.4
 1001–2000 ETB 316 39.2
 >2000 ETB 174 21.6
Family size (n = 806)
 <3 members 125 15.5
 4–6 members 521 64.6
 >6members 160 19.9
Birth interval (n = 806)
 <2 Years 167 20.7
 ≥2 Years 639 79.3

3.2. Health service utilization and child feeding of the LW

A 532 LW were getting the water from the piped source. Almost all participants had a functional toilet. 757 (95.9%) of LW had at least one Antenatal care (ANC)” follow-up, and from these greater than two-third of LW had more than three times follow-ups in the last pregnancy, but only 128 (15.9%) of LW have had Postnatal care (PNC) follow-up to the previous delivery.

Almost all LW didn't suffer from any chronic disease illness during their breastfeeding period, but only 29 (3.6%) of LW had a history of illness in the last two weeks. 676 (83.8%) of LW gave birth at a health facility, and all LW practice exclusive breastfeeding (Table 2).

Table 2.

Health service utilization and child feeding among LW (n = 806) at Pawie district Benishangul Gumuz regional state, Northwest, Ethiopia, 2019.

Food group consumption in previous 24 h Number Percent (%)
Source of drinking water
 Piped water 532 66.0
 Hand dug well 86 10.7
 River 36 4.5
 Protected well 148 18.4
 Un protected well 4 .5
Functional toilet service
 Yes 792 98.3
 No 14 1.7
ANC follow up in the last pregnancy
 Non 49 6.1
 1 visit 17 2.1
 2–3 Visit 201 24.9
 4 and above 539 66.9
Place of delivery
 Health center 676 83.8
 Home 130 16.2
PNC service
 No 678 84.1
 Yes 128 15.9
Do you have any chronic disease
 No 802 99.6
 Yes 4 .4
History of illness in the previous 2 weeks
 No 777 96.4
 Yes 29 3.6
Practice exclusive breastfeed
 No 16 1
 Yes 798 99

3.3. Dietary Diversity (DD) of the LW

A 71.6% of the LW consumed cereals, white roots, and tubers in the previous 24 h, whereas 54.1% consumed vitamin A-rich vegetables and tubers in the previous 24 h. Similarly, 50.2% consumed other fruits and vegetables in the previous 24 h. 68.1% consumed fats and oils in the previous 24 h, and two-third were organ meat and fish meat in the previous 24 h during their lactation period. Based on the categories, 297 (36.8%) of the LW had a good DDS (consumed ≥ five food groups), and 63.2% were with low DDS (consumed < five food group) (Table 3).

Table 3.

DD among LW (n = 806) at Pawie district, Benishangul Gumuz regional state, Northwest, Ethiopia, 2019.

Food group consumption in previous 24 h Number Percent
Grains, white roots and tubers, and plantains in the previous 24 h
 No 229 28.4
 Yes 577 71.6
Pulses (beans, peas, and lentils) in last 24 h
 No 257 31.9
 Yes 549 68.1
Other vitamin A-rich fruits and vegetables in the previous 24 h
 No 370 45.9
 Yes 436 54.1
Dark green leafy vegetables in the previous 24 h
 No 278 34.5
 Yes 528 65.5
Other vegetables in the previous 24 h
 No 405 50.2
 Yes 401 49.8
Other fruits in the previous 24 h
 No 549 68.1
 Yes 257 31.9
Meat, poultry, and fish in the previous 24 h
 No 600 74.4
 Yes 206 25.6
Eggs in the previous 24 h
 No 477 59.2
 Yes 329 40.8
Legumes, nuts, and seeds in the previous 24 h
 No 513 63.6
 Yes 293 36.4
Milk and milk products in the previous 24 h
 No 412 51.1
 Yes 394 48.9
Women DD
 Good DD 297 36.8
 Low DD 509 63.2

The cut-offs for good DD is greater or equal to five food group is good DD.

3.4. Food security characteristics of the LW

As shown in Table 4, Food security characteristics of the LW, from the nine HFIAS items; Only 221 (27.4%) of the LW worried about running out of food 157 (25.8%), whereas from the total 1/4th of the LW were unable to eat preferred foods. 168(20.8%) of the LW was eating a limited variety of food, and only15% of LW consumed the food that they did not go to eat really, and over 1/4th of LW were skipping their meals in the last 24 h. The overall prevalence of food insecurity, 334 (41.4%) of the LW was food insecure (Table 4).

Table 4.

HFIAS items among LW (n = 806) at Pawie District Benishangul Gumuz regional state, Northwest, Ethiopia, 2019.

Characteristics Number Percent
Worried about running out of food
 No 585 72.6
 Yes 221 27.4
Unable to eat preferred foods
 No 586 72.7
 Yes 220 27.3
Eat a limited variety of foods
 No 638 79.2
 Yes 168 20.8
Eat foods that you did not want to eat
 No 685 85.0
 Yes 121 15.0
Eat a smaller meal
 No 676 83.9
 Yes 130 16.1
Skipping meals
 No 581 72.1
 Yes 225 27.9
No food to eat of any kind in the household
 No 754 93.5
 Yes 52 6.5
Go to sleep at night hungry
 No 745 92.4
 Yes 61 7.6
Go a whole day and night without eating anything
 No 761 94.4
 Yes 45 5.6
Food Security Status
 Food secure 472 58.6
 Food insecure 334 41.4

3.5. Factors associated with DD of the LW

Table 5 shows bivariate and multivariate analysis of factors associated with DD of LW. In the multivariate analysis, the father's occupation being a daily laborer, was two times more likely to have low DD than the counterparts [(AOR 1.820, 95% CI (. 339, 9.784)]. LW with a birth interval of less than 24 months, family size greater than six, and food insecure were 3.7, 1.5, and 2.2 times more likely, to have low DD than those with a birth interval greater than 24 months, family size less than six members and who were food secure respectively [(AOR = 3.7, 95 % CI (1.743, 7.885)], [AOR = 1.55, 95 % CI (1.046, 2.313)], and [AOR = 2.23, 95 % CI (1.626, 3.066)] respectively (Table 5).

Table 5.

Factors associated with DD among LW (n = 806) at Pawie district Benishangul Gumuz regional state, Northwest, Ethiopia, 2019.

Variables Poor Good COR at 95%CI AOR at 95% CI
Age of the mother (in years) (n = 806)
 <20 years 44 54 1.94 (.852, 4.434) 1.74 (.691, 4.407)
 20–29 years 238 150 .99 (.471, 2.115) .88 (.382, 2.053)
 30–39 years 173 116 1.06 (.496, 2.270) .90 (.392, 2.054)
 40 and above 19 12 1 1
Maternal educational level
 Unable to read and write 271 222 1.30 (.790, 2.137) 1.22 (.475, 3.132)
 Able to read and write 91 51 .89 (.499, 1.584) .76 (.297, 1.957)
 Primary school 66 30 .72 (.382, 1.359) .59 (.261, 1.320)
 Secondary and above 46 29 1 1
The educational level of the father
 Unable to read and write 226 166 1.13 (.731, 1.739) .52 (.223, 1.200)
 Able to read and write 118 93 1.21 (.756, 1.937) .63 (.273, 1.458)
 Primary 64 30 .72 (.403, 1.284) .51 (.232, 1.120)
 Secondary and above 66 43 1 1
Maternal occupation status
 Housewife 317 253 1 1
 Governmental employee 51 22 1.89 (1.079, 3.313) .51 (.147, 1.793)
 Merchant 61 38 1.02 (.491, 2.127) .76 (.176, 3.260)
 Daily laborers 45 19 1.47 (.753, 2.889) .84 (.194, 3.658)
Occupation status of the father
 Farmer 291 231 1.00 1.00
 Merchant 103 60 1.74 (.799, 3.808) 1.90 (.468, 7.725)
 Gove employee 42 27 1.58 (.793, 3.154) 1.97 (.479, .142)
 Daily laborer 38 14 2.15 (1.140, 4.073) 1.82 (.339, 9.784)∗∗
The birth interval of the mothers
 <2 Years 122 45 2.21 (1.518, 3.218) 3.71 (1.743, 7.885)∗∗∗
 ≥2 Years 352 287 1 1
Income (in ETB)
 <500 ETB 38 25 .89 (.494, 1.600) .79 (.420, 1.496)
 500- 1000 ETB 139 114 1.11 (.751, 1.636) 1.07 (.702, 1.625)
 1001- 2000 ETB 197 119 .82 (.560, 1.190) .80 (.536, 1.201)
 >2000 ETB 100 74 1 1
Marital status
 Married 438 310 1 1
 Divorced 32 18 .71 (.176, 2.852) .60 (.141, 2.552)
 Widowed 4 4 .56 (.125, 2.524) .53 (.112, 2.555)
Family size
 <3 members 82 43 1 1
 4-6 members 291 230 1.09 (.729, 1.626) 1.23 (.693, 2.176)
 >6members 101 59 1.02 (.718, 1.464) 1.56 (1.046, 2.313)∗∗
Food security
 Food secure 242 230 1 1
 Food insecure 232 102 2.16 (1.61, 2.902) 2.23 (1.626, 3.066)∗∗∗

∗AOR = “Adjusted odds ratio”, COR = “Crude odds

∗∗ = P < 0.05, ∗∗∗ = P < 0.01.

Bold and Italic value indicates the factors were significant from the total variables.

4. Discussion

Good DD for the mother's during lactation is vital for good health as well as for that their children. Various factors influence the DD of LW, and this cause for health problem of the mothers and poor growth and development of the child. According to the Essential Nutrition Action (ENA) and existing research, good DD during lactation for all LW is critical for maternal health, the health of their children, family, and nation [12]. The main aim of this study is to determine the DD and associated factors of LW in the Pawie district in Benishangul Gumuz regional state in Northwest Ethiopia.

In this finding, 36.8 % of the LW had good DD, and 63.2 % did not receive minimum DD. This is higher than the study done in Pakistan [19], Kenya [20], Ethiopia (Shashemane, Debub Bench district, and Finote Selam District, Northwest Ethiopia) [21, 22, 23]. The difference might be due to the measurement of DD, the category of food group, and the study setting. i.e., some studies used 14 food groups, and others used ten food groups consuming four and consuming five or more food groups classified as adequate DD.

This finding is almost consistent with the study done in Bale zone [10], Northeast Ethiopia [24], Aksum Tigray [25]East Gojam Zone [6], A systematic review and meta-analysis finding of Ethiopia [26, 27], and Southern Ethiopia [1]. All studies have similar sociodemographic, socioeconomic, and seasonal variations characteristics might be the possible reason for similarities.

On the other hand, the finding of this study is lower as compared with another study which is done in Nepal [28], Debre Tabor Ethiopia [29], Addis Ababa [30], and Raya Azebo Zone [31]. These might explained by the difference in the study period, which can result in food security status change, socio-demographic, socio-cultural, geographical variation (for instance, in most parts of Ethiopia produce many types of food verity like root and tuber crops, fruits, and vegetables, Teff, Degussa, cereals), while these countries may not cultivate such types of food verity, these factors are possibly caused variation in DD of LW.

In the current study, Father's occupational status being a daily laboring father, two times more likely to have low LD. Similarly, finding in Debre Tabor, Ethiopia [29], Jakarta [32], father's occupation at the lower occupational levels showed a lack of understanding of the importance of DD and reported a low DD. The true and included the late introduction of the variety of food as a food source a daily pattern. This is evidenced by the study in Ambo district West Shewa Oromia daily laborer occupation was strongly associated with mothers DD [33]. Because mothers whose husbands did daily labor did not consume the recommended dietary type since they are of low economic status, and even the mothers themselves spent most of their time in the work area as compared to the housewife.

Mothers with families seize >6 family members were 1.5 times higher risk for poor dietary diversity as compared to mothers who have less than six family sizes in this study. This is supported by the studies conducted in Wolega, Guto Gido woreda, and Nekemte referral hospital family size (AOR = 4.604, 95%CI = 1.903–11.140 have significant relation with mothers’ DD in the study area [34, 35]. When a woman had large family size, she becomes less concerned about her good DD since the food supply to the family is low and mothers worry only about what feed for her child or family than she which important determinants of her health as well as her child.

In this study, Mothers whose birth interval <24 months 3 times more likely to have a risk for poor DD as compared to their counterpart. Because, the mothers have no time to care for themselves rather they caring and worry for their little child and the next child, that may challenge their economy as well as they may have less the chances of meeting nutrient requirements for the family by improving nutritional status.

Mothers who had food insecurity were two times more likely to have poor DD as compared to the mothers who were food secured in the current study. Similarly, in a study in Mali and Debub Bench zone, women from extremely food insecure households were less likely to have good DD [22, 36]. When the woman had food security, they became more concerned with good DD, and immediately put it into practice. This is supported by a study conducted in Boston, food insecurity may worsen diet quality and health of women's in their life [37].

The husband's educational status, age, marital status, monthly income, owns agricultural land, and employment status were not associated with the DD of mothers during their lactation periods in the current study. It was disproved by a cross-sectional survey conducted in southwestern Bangladesh [7], in northern Ghana [5], In Aksum town, Tigray, Northern Ethiopia [8]. This inconsistency may be occurred due to the sample size, study setting, and statistical analysis differences.

5. Conclusions

Nearly two-thirds of the LW doesn't achieve the minimum DDS, and father's occupation, low birth intervals, family size being large family, and being a food-insecurity household were the significant predictors of minimum DDS in this study. Federal Ministry of Health, regional health bureaus, and agricultural government: prioritizing, planning, designing, and initiating DD intervention programs to improve maternal nutrition through appropriate food-based approaches strengthen nutrition education programs on proper maternal MDD practices and DD intake during lactation periods focused on the main predictors. In general, it is not the only task of the government; it requires multi-sectorial involvements, so every sector works cooperatively to improve the nutrition outcomes of LW. The health personals work on family planning, ANC and PNC should counsel the Women to increase the awareness of LW on how to improve the DD.

6. Strength and limitation of the study

The strength of this study was we used a large sample, a community-based, and required statistical analysis. However, the limitations of the study were that the data was collected by interview of the mothers about the previous 24 h of recall dietary diversity assessment, so there might be recall biases about what they consumed within the last previous 24 h [38, 39].

Declarations

Author contribution statement

Sileshi Mulatu, Chalachew Yenew: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Wrote the paper.

Habtamu Dinku: Conceived and designed the experiments; Wrote the paper.

Funding statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability statement

Data will be made available on request.

Declaration of interests statement

The authors declare no conflict of interest.

Additional information

No additional information is available for this paper.

Acknowledgements

We authors would like to forward our heartfelt gratitude to study subjects for their willingness to participate in our study. In addition, we are adding our unlimited thanks to the Pawie health Science College and Bahir Dar University for securing ethical issues of the study.

Appendix A. Supplementary data

The following is the supplementary data related to this article:

Questionaries
mmc1.docx (26.8KB, docx)

References

  • 1.Boke M.M., Geremew A.B. Low dietary diversity and associated factors among lactating mothers in Angecha districts, Southern Ethiopia: community based cross-sectional study. BMC Res. Notes. 2018;11:892. doi: 10.1186/s13104-018-4001-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Marie T., Ruel, Deitchler Megan, Arimond Mary. Developing simple measures of women’s diet quality in developing countries: overview article in. J. Nutr. 2010;140(11):2048S–2050S. doi: 10.3945/jn.110.123695. [DOI] [PubMed] [Google Scholar]
  • 3.Haileslassie Kiday, Afework Mulugeta, Girma Meron. Feeding practices, nutritional status and associated factors of lactating women in Samre Woreda, South Eastern Zone of Tigray, Ethiopia. BMC Nutr. J. 2013;12(28) doi: 10.1186/1475-2891-12-28. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Haileslassie K., Mulugeta A., Girma M. Feeding practices, nutritional status and associated factors of lactating women in Samre Woreda, South Eastern Zone of Tigray, Ethiopia. Nutr. J. 2013 Dec 1;12(1):28. doi: 10.1186/1475-2891-12-28. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Saaka M., Mutaru S., Osman S.M. Determinants of dietary diversity and its relationship with the nutritional status of pregnant women. J. Nutr. Sci. 2021;10 doi: 10.1017/jns.2021.6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Yeneabat T., et al. Maternal dietary diversity and micronutrient adequacy during pregnancy and related factors in East Gojjam Zone, Northwest Ethiopia, 2016. BMC Pregnancy Childbirth. 2019;19(1):1–9. doi: 10.1186/s12884-019-2299-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Shamim A.A., et al. Pregnant women diet quality and its sociodemographic determinants in southwestern Bangladesh. Food Nutr. Bull. 2016;37(1):14–26. doi: 10.1177/0379572116632137. [DOI] [PubMed] [Google Scholar]
  • 8.Weldehaweria N.B., et al. Dietary diversity and related factors among lactating women visiting public health facilities in Aksum town, Tigray, Northern Ethiopia. BMC Nutr. 2016;2(1):38. [Google Scholar]
  • 9.Ukegbu Patricia Ogechi A study of the nutritional status and dietary intake of lactating women in Umuahia, Nigeria. Am. J. Health Res. 2014;2(1):20–26. [Google Scholar]
  • 10.Hailu S., Woldemichael B. Dietary diversity and associated factors among pregnant women attending antenatal care at public health facilities in Bale Zone, Southeast Ethiopia. Nutr. Diet. Suppl. 2019;11:1–8. [Google Scholar]
  • 11.Pawie District Health Office . 2015. Bi–Annual Report of Health Development Army. Bi–annual Report. [Google Scholar]
  • 12.Minimum Dietary Diversity for Women. FANTA III; 2016. [Google Scholar]
  • 13.Hanley-Cook G.T., et al. Minimum Dietary Diversity for Women of Reproductive Age (MDD-W) data collection: validity of the list-based and open recall methods as compared to weighed food record. Nutrients. 2020;12(7):2039. doi: 10.3390/nu12072039. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Adubra L., et al. The minimum dietary diversity for women of reproductive age (MDD-W) indicator is related to household food insecurity and farm production diversity: evidence from rural Mali. Curr. Develop. Nutr. 2019;3(3):nzz002. doi: 10.1093/cdn/nzz002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Worku Amelmal, Abebe Solomon Mekonnen, Wassi Molla Mesele. Dietary practice and associated factors among type 2 diabetic patients: a cross sectional hospital based study, Addis Ababa, Ethiopia. Spring. Open J. 2015;4(15) doi: 10.1186/s40064-015-0785-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Alemayehu Mekonnen Sisay, Tesema Endalamaw Mengesha. Dietary practice and associated factors among pregnant women in Gondar town North west, Ethiopia. Int. J. Nutr. Food Sci. 2015;4(6):707–712. [Google Scholar]
  • 17.WHO . 2014. UNICEF, UNFPA, World Bank, United Nations. [Google Scholar]
  • 18.Berihu Amanuel, Abera Gerez giher Buruh, Berhe Hailemariam, Kidanu Kalayou. Mother’s knowledge on nutritional requirement of infant and young child feeding in mekelle, Ethiopia, cross sectional study. Global J. Med. Res. Interdis. 2013;1(6) [Google Scholar]
  • 19.Ali F., Thaver I., Khan S.A. Assessment of dietary diversity and nutritional status of pregnant women in Islamabad, Pakistan. J. Ayub Med. Coll. Abbottabad. 2014;26(4):506–509. [PubMed] [Google Scholar]
  • 20.Kiboi W., Kimiywe J., Chege P. Determinants of dietary diversity among pregnant women in Laikipia County, Kenya: a cross-sectional study. BMC Nutr. 2017;3(1):1–8. [Google Scholar]
  • 21.Desta M., et al. Dietary diversity and associated factors among pregnant women attending antenatal clinic in Shashemane, Oromia, Central Ethiopia: a cross-sectional study. J. Nutr. Metab. 2019;2019 doi: 10.1155/2019/3916864. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Fufa D.A., Laloto T.D. Assessment of dietary diversity and associated factors among lactating mothers in Debub Bench District. Heliyon. 2021;7(8) doi: 10.1016/j.heliyon.2021.e07769. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Gebrie Y.F., Dessie T.M. Bayesian analysis of dietary diversity among lactating mothers in Finote Selam district, Northwest Ethiopia: a cross-sectional study. BioMed Res. Int. 2021:2021. doi: 10.1155/2021/9604394. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Aliwo S., et al. Dietary diversity practice and associated factors among pregnant women in North East Ethiopia. BMC Res. Notes. 2019;12(1):1–6. doi: 10.1186/s13104-019-4159-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Weldehaweria, et al. Dietary diversity and related factors among lactating women visiting public health facilities in Aksum town, Tigray, Northern Ethiopia. BMC Nutr. 2016;2(38) [Google Scholar]
  • 26.Azene A.G., et al. Dietary diversity among pregnant women and associated factors in Ethiopia: systematic review and meta-analysis. PLoS One. 2021;16(6):e0251906. doi: 10.1371/journal.pone.0251906. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Bitew Z.W., et al. Dietary diversity and practice of pregnant and lactating women in Ethiopia: a systematic review and meta-analysis. Food Sci. Nutr. 2021;9(5):2686–2702. doi: 10.1002/fsn3.2228. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Shrestha V., et al. Factors associated with dietary diversity among pregnant women in the western hill region of Nepal: a community based cross-sectional study. PLoS One. 2021;16(4):e0247085. doi: 10.1371/journal.pone.0247085. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Engidaw M.T., et al. Dietary diversity and associated factors among lactating mothers in Debre Tabor General Hospital, Northcentral Ethiopia. Int. J. 2019;5(1):17. [Google Scholar]
  • 30.Tefera W., Brhanie T.W., Dereje M. Dietary diversity practice and associated factors among pregnant women attending ANC in Kolfe Keranyo sub city health centers, Addis Ababa, Ethiopia. medRxiv. 2020 [Google Scholar]
  • 31.Jemal K., Awol M. Minimum dietary diversity score and associated factors among pregnant women at alamata general hospital, Raya Azebo zone, Tigray region, Ethiopia. J. Nutr. Metab. 2019;2019 doi: 10.1155/2019/8314359. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Kekalih A., et al. 2019. Dietary Diversity Beliefs and Practices Among Working Mothers in Jakarta: a Qualitative Study; p. 1. Vol. 25 Supplement, 2019. [Google Scholar]
  • 33.Tolera Bekele, Mideksa Samson, Dida Nagasa. Assessment of dietary practice and associated factors among pregnant mother in Ambo district, west Shoa, Oromia, Ethiopia. Ethiop. J. Reprod. Health (EJRH) 2018;10(4) [Google Scholar]
  • 34.Gemeda Daba F.B., Garoma Wondu, Fekadu Habtamu. Assessment of nutritional practices of pregnant mothers on maternal nutrition and associated factors in Guto Gida woreda, East Wollega zone, Ethiopia. Sci. Technol. Arts Res. J. 2013;2(3):105–113. [Google Scholar]
  • 35.Hundera Temesgen Desisa, Wirtu Dessalegn, Gemede Habtamu Fekadu, Kenie Dunkana Negussa. Nutritional status and associated factors among lactating mothers in Nekemte referral hospital and health centers, Ethiopia. Int. J. Nutr. Food Sci. 2015;4(2):216–222. [Google Scholar]
  • 36.Adubra Laura, Savy Mathilde, Fortin Sonia, Kameli Yves, Kodjo Niamké Ezoua, Fainke Kamayera, Mahamadou Tanimoune, Le Port Agnes, Martin-Prevel Yves. The minimum dietary diversity for women of reproductive age (MDD-W) indicator is related to household food insecurity and farm production diversity: evidence from rural Mali. Curr. Develop. Nutr. March 2019;3(Issue 3):nzz002. doi: 10.1093/cdn/nzz002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Mary E., Morales B.A., Berkowitz Seth A. The relationship between food insecurity, dietary patterns, and obesity. HHS Public Access. 2016;5(1):54–60. doi: 10.1007/s13668-016-0153-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Faber J., Fonseca L.M. How sample size influences research outcomes. Dent. Press J. Orthodon. 2014;19(4):27–29. doi: 10.1590/2176-9451.19.4.027-029.ebo. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Wilson M.G., et al. Community-based knowledge transfer and exchange: helping community-based organizations link research to action. Implement. Sci. 2010;5(1):1–14. doi: 10.1186/1748-5908-5-33. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Questionaries
mmc1.docx (26.8KB, docx)

Data Availability Statement

Data will be made available on request.


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