Associations between infant and young child feeding practices and acute respiratory infection and diarrhoea in Ethiopia: A propensity score matching approach.

BACKGROUND: Acute respiratory infection (ARI) and diarrhoea are the leading causes of childhood morbidity and mortality in Ethiopia. Understanding the associations between infant and young child feeding (IYCF) and ARI and diarrhoea can inform IYCF policy interventions and advocacy in Ethiopia. This study aimed to investigate the relationship between IYCF practices and ARI and diarrhoea in Ethiopian children.
METHODS: This study used the Ethiopia Demographic and Health Survey (EDHS) data for the years 2000 (n = 3680), 2005 (n = 3528), 2011 (n = 4037), and 2016 (n = 3861). The association between IYCF practices and (i) ARI and (ii) diarrhoea were investigated using propensity score matching and multivariable logistic regression models. The IYCF practices include early initiation of breastfeeding, exclusive breastfeeding (EBF), predominant breastfeeding, introduction of complementary foods, continued breastfeeding at two years and bottle feeding.
RESULTS: Infants and young children who were breastfed within 1-hour of birth and those who were exclusively breastfed had a lower prevalence of ARI. Infants who were exclusively and predominantly breastfed had a lower prevalence of diarrhoea. Early initiation of breastfeeding (Odds ratio [OR]: 0.81; 95% confidence interval [CI]: 0.72, 0.92) and EBF (OR: 0.65; 95% CI: 0.51, 0.83) were associated with lower risk of ARI. Bottle-fed children had higher odds of ARI (OR: 1.36; 95% CI: 1.10, 1.68). Early initiation of breastfeeding and EBF were associated with lower odds of diarrhoea (OR: 0.88; 95% CI: 0.79, 0.94 for Early initiation of breastfeeding and OR: 0.51; 95% CI: 0.39, 0.65 for EBF). Infants who were predominantly breastfed were less likely to experience diarrhoea (OR: 0.69; 95% CI: 0.53, 0.89).
CONCLUSION: The recommended best practices for preventing ARI and diarrhoeal diseases in infants and young children namely: the early initiation of breastfeeding, EBF and avoidance of bottle feeding should be institutionalized and scale-up in Ethiopia as part of implementation science approach to cover the know-do-gaps.

Introduction

Acute respiratory infection (ARI) and diarrhoea are the leading causes of childhood morbidity and mortality globally, particularly in low- and middle-income countries (LMICs) [1-3]. In 2015, ARI and diarrhoea were the first and the fourth leading causes of childhood mortality worldwide, attributable to over one million global under-five deaths [1, 2]. Previous studies have shown that childhood ARI and diarrhoea were associated with adverse health and developmental outcomes [4-8]. ARI and diarrhoea in children have been associated with frequent hospital visits and admission [6]. Studies conducted in LMICs have shown that early initiation of breastfeeding (EIBF) and exclusive breastfeeding (EBF) were protective against diarrhoea [9-14] and ARI [9, 10].

Evidence from sub-Saharan African [11, 13, 15] and Asian [10, 16] countries have indicated that inappropriate introduction of complementary foods and bottle feeding were associated with the onset of diarrhoea among infants and young children. This is potentially due to the replacement of irreplaceable human milk by complementary foods and contamination of the food and/or teat/nipple of the bottle [17, 18]. Despite the benefits of appropriate breastfeeding, EIBF and EBF prevalence estimates remain low in LMICs, 42% [19] and 37% [14], respectively. This suggests that many infants and young children are at increased risk of experiencing ARI and diarrhoea, and even more likely to die from preventable and treatable diseases like ARI and diarrhoea [1-3].

Based on the World Bank assessment [20], Ethiopia is a low-income country, with strong and broad-based economic growth compared to other nations in the Eastern African region. However, it is one of the poorest countries in Africa, with a per capita income of USD790 per year [20], indicating that access to key social and health amenities that can help to reduce preventable child morbidity and mortality are limited. In the past two decades, Ethiopia has seen substantial reductions in infant mortality (from 97 in 2000 to 43 per 1000 in 2019) and under-five mortality (from 166 in 2000 to 55 per 1000 in 2019) [21, 22]. Despite these improvements, one in 15 children still dies before reaching age five years, and 7 out of 10 of these deaths occur in the first year of birth [21, 23–25]. In these deaths, childhood vaccination and appropriate IYCF practices could play important roles in preventive strategies; however, recent studies have indicated that vaccination coverage (43%) [22] and IYCF practices (e.g., EIBF (75.5%) and EBF at six months (59.9%) [26]) were below the Ethiopian Health Sector Transformation Plan target of 95%, 90% and 72%, respectively [27]. Additionally, a recent study indicated that early cessation of EBF was associated with ARI and diarrhoea [32]. Though useful, this study did not provide relevant evidence for other important IYCF indicators, including EIBF, predominant breatfeeding and introduction of solid, semi-solid or soft foods. These indicators have been showed to either act as ‘protective’ or ‘predictive’ factors for both ARI and diarhoea in LMICs [10, 11, 13].

Understanding and quantifying the relationship between IYCF practices and ARI and diarrhoea among infants and young children is crucial to health practitioners and policymakers in Ethiopia. This information will help in IYCF policy formulation and advocacy, which can, in turn, play an important role in reducing child morbidity and mortality due to ARI and diarrhoea. This assessment is also important in Ethiopia given the current global health efforts–the United Nation’s Sustainable Development Goals (SDG-3.2: ending preventable deaths of newborns and under-five children by 2030) [28] and Global Action Plan for Pneumonia and Diarrhoea (GAPPD: ending preventable pneumonia and diarrhoea deaths by 2025) [8]. Accordingly, this study aimed to investigate the associations between IYCF practices and ARI and diarrhoea in Ethiopian children.

Methods

Data sources

The study used the Ethiopia Demographic and Health Survey (EDHS) data for the years 2000 (n = 3680), 2005 (n = 3528), 2011 (n = 4037), and 2016 (n = 3861). The EDHS used the household questionnaire to collect information on households, and the women’s questionnaire to collect information on child health and nutrition. The surveys were implemented by the Ethiopia Central Statistical Agency (CSA) and Inner City Fund (ICF) International, and funded by the United States Agency for International Development, and the Government of Ethiopia [21, 23–25].

The EDHS used a two-stage stratified cluster sampling technique to select households (the secondary sampling unit) for inclusion in the survey. In stage one, after the nine administrative units were stratified into 12 urban and 11 rural strata, Enumeration Areas (EAs) were selected proportional to the household size of the cluster. In stage two, a fixed number of households were selected from each EA using the list of households as a sampling frame [21, 23–25]. All women aged 15–49 years who were permanent residents or visitors in the selected households the night before the survey were included as respondents. The response rates in the surveys were high, ranging from 94.6% in 2016 to 97.8% in 2000. Our analyses were restricted to living children who lived with the respondents to minimize recall bias, consistent with past studies [11, 15]. A total weighted sample of 15,106 women was used, and additional information on the surveys methodology is provided elsewhere [21, 23–25].

Study setting

Ethiopia is the second most populous country (with more than 110 million population) in Africa after Nigeria [29]. The population age structure of Ethiopia is predominantly young populations with 41.6% under the age of 15 years, and women of reproductive age account for 23.4% of the population [30]. The Ethiopian health service structure follows a three-tier system: primary-level health care (health posts, health centres, and primary hospitals), secondary-level health care (General Hospitals) and tertiary-level health care (teaching and specialized hospitals) [27].

Outcome variables

The outcome variables were ARI and diarrhoea, measured based on maternal recall of symptoms of cough and shortness of breath, and diarrhoea, respectively [31]. ARI was defined as the occurrence of cough accompanied by short and rapid breathing during the two weeks’ period preceding the survey. Diarrhoea was defined as the passage of three or more loose or liquid stools per day during the two weeks’ period preceding the survey [31, 32].

Exposure variables

The main exposure variables were IYCF indicators (EIBF, EBF, predominant breastfeeding, the introduction of complementary foods, continued breastfeeding at two years and bottle feeding) [33]. IYCF indicators were defined as follows:

EIBF was defined as the proportion of children aged 0–23 months who commenced breastfeeding within the first hour of birth.

EBF was defined as the proportion of infants 0–5 months of age who were fed no other food or drink, not even water, except breast milk (including milk expressed or from a wet nurse), but allows the infant to receive oral rehydration salt, drops, and syrups (vitamins, minerals and medicines).

Predominant breastfeeding was defined as the proportion of infants 0–5 months of age who received breast milk (including milk expressed or from a wet nurse) as the predominant source of nourishment, but allows water, water-based drinks, fruit juice, oral rehydration solution, drops, or syrups of vitamins and medicines during the previous day.

Introduction of complementary foods (solid, semi-solid or soft foods) was defined as the proportion of infants 6–8 months of age who received solid, semi-solid or soft foods in the previous 24 hours, during the day and at night.

Continued breastfeeding at two years of age was defined as the proportion of children aged 20–23 months who received breast milk during the previous day.

Bottle feeding was defined as the proportion of children 0–23 months of age who were fed any liquid (including breast milk) or semi-solid food from a bottle during the previous day.

Potential confounders

The potential confounders were selected based on previously published studies [10, 13, 15, 26, 34, 35] and data availability. Potential confounding factors were broadly classified into socio-economic, demographic and behavioural, health service and community-level factors.

Socio-economic factors included mothers' or fathers’ education, maternal employment and household wealth status. Demographic and behavioural factors included maternal age, family size, desire for pregnancy, listening to the radio, reading newspaper/magazine and watching television. Health service factors included ever use of a vaccine, frequency of antenatal care (ANC) visits, place of birth, and timing of first postnatal care (PNC) visit. Community-level factors included a place of residence and region of residence.

The study also considered the type of cooking fuel in the analyses of ARI, and the source of drinking water and type of toilet facility in the analyses of diarrhoea as potential effect measure modifiers. This was done to investigate whether the association between IYCF practices and each outcome differed across each stratum for the type of cooking fuel, source of drinking water and sanitation level. This approach is consistent with previously published studies from Africa [13, 15, 36–38]. In the current study, households that used electricity, natural gas, biogas, or kerosene as a cooking fuel were classified as ‘improved’, while those households that used charcoal, firewood, or dung were grouped as ‘not improved’. This classification was based on previously published studies conducted in LMICs [39-41].

The source of drinking water and type of toilet facility were classified as ‘improved’ or ‘not improved’, based on the taxonomy of the WHO and UNICEF Joint Monitoring Programme (JMP) for Water and Sanitation [42] as applied in past studies [13, 15]. Households that used piped water, public tap or standpipe, a tube well or borehole, protected well/spring, rainwater and/or bottled water were classified as ‘improved’. Households that used unprotected well/spring, tanker truck/cart, surface water, and/or sachet water were grouped as ‘not improved’. Type of toilet facility was also grouped as ‘improved’ (included flush/pour-flush toilets or flush/pour-flush toilets piped to the sewer system, septic tank or pit latrine; ventilated improved pit (VIP) latrine; pit latrine with slab and/or composting toilet). ‘Not improved’ type of facility included flush/pour-flush not piped to sewer, septic tank or pit latrine; pit latrine without slab/open pit; bucket or hanging toilet/hanging latrine and no facility/bush/field.

Analytical strategy

The initial analysis involved the tabulation of frequencies and percentages of socioeconomic, demographic, health-service and community-level factors over the survey years (2000–2016). Prevalence of ARI and diarrhoea were calculated for each of the exposure variables (i.e., EIBF, EBF, predominant breastfeeding, the introduction of solid, semi-solid and soft foods, continued breastfeeding at two years, and bottle feeding). The EDHS data from 2000 to 2016 were combined to increase the study power and precision of estimates. Before statistical analyses, all variables were checked for missing properties; nevertheless, there was no evidence of missingness at random.

Propensity score matching (PSM) and multivariable logistic regression were used to investigate the associations between IYCF practices and ARI and diarrhoea. Observational studies (including cross-sectional surveys) are helpful to investigate the association between exposure and outcome variables [43]. However, in observational studies, unlike randomized controlled trials (RCTs), exposure selection depends on the participant's self-selection in which individuals with specific characteristics may be exposed than other participants [43, 44]. This non-randomized self-selection in the exposure can confound the measure of association between the exposures and the outcomes [43, 45]. To minimise the imbalance in participant characteristics between exposed and unexposed groups, Rosenbum and Rubin [46] proposed the PSM approach that takes into account the fundamental differences between the two groups. PSM is a technique to balance the propensity scores of the exposed and unexposed groups so that direct comparisons of covariates in both groups are meaningful [46]. Propensity scores are defined as “the conditional probability of being treated or exposed given the covariates” [47]. The key assumption in propensity score analyses is that participants whose propensity scores are equivalent have comparable covariate distribution [43]. Additional information on the theories and practices of PSM have been published elsewhere [44, 47–49].

In observational studies, researchers have indicated that PSM and multivariable logistic regression modelling are ‘best’ used in combination when investigating the association between two variables of interest [47, 50, 51]. For this study, the combined use of PSM and multivariable logistic regression have the following advantages over ordinary logistic regression. Firstly, PSM minimizes the potential effect of selection bias due to self-selection of mothers who may have breastfed their babies [52, 53]. Secondly, PSM helps to account for the systematic differences in background characteristics between infants and young children who were appropriately fed and those who were inappropriately fed [43, 54]. Thirdly, PSM summarises the background characteristics of all study participants into a single measure and relaxes the linearity assumption of regression analysis [52]. Finally, PSM methods show the area where there is no sufficient overlap of covariate distributions between the exposed and unexposed groups, and where estimates using ordinary logistic regression would have relied on extrapolation [44, 47].

In the present analyses, a five-staged analytical approach was applied to investigate the association between IYCF practices and ARI and diarrhoea. In stage one, the propensity score was estimated using binary logistic regression by specifying each IYCF indicator to the outcome and background characteristics (potential confounders) as predictors. The survey weight was included as a covariate in the estimation process of the propensity score, consistent with previously published studies [49, 55]. In stage two, the balance in propensity score was checked between the exposed and unexposed groups (for each of the IYCF) for sufficient overlap (common support) by examining the propensity score graphs. In stage three, the balance of covariates across the exposed and unexposed groups was checked by calculating the standardized mean difference (SMD) for each covariate. Less important potential confounders with SMD of greater than 10% were excluded from further analyses. In stage four, nearest neighbour 1:1 matching with a caliper (0.1) was applied to create a matched exposed and unexposed groups with equivalent propensity score. Observations that were not in the common support region (no sufficient overlap in the graph) were excluded from further analyses (. In the final stage, multivariable logistic regression was separately used to estimate the association between IYCF and ARI and diarrhoea. Adjustment for survey year was also conducted, and interaction tests between potential effect measure modifiers (type of cooking fuel, type of toilet system and source of drinking water) and each IYCF indicator were conducted.

Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated as the measure of association between the exposure and outcome variables. We reported the adjusted ORs for PSM (Table 3) and unadjusted and adjusted ORs for ordinary logistic regression models for comparison of estimates (. Unadjusted ORs for PSM was not reported as potential confounders are part of the propensity score estimation process in PSM [47]. All analyses were conducted using ‘svy’ command to adjust for sampling weights, clustering and stratification in Stata (version 14.0, Stata Corp, College Station, TX, USA). ‘Pscore’ and ‘psmatch2’ were used for PSM; and the ‘melogit’ function was used for the logistic regression modelling [56].

Table 3

The association between infant and young child feeding, and acute respiratory infection and diarrhoea in Ethiopia, 2000 to 2016.

IYCF factors	Acute respiratory infection			Diarrhoea
	*Adjusted			*Adjusted
	n	OR (95% CI)	P value	n	OR (95% CI)	P value
Early initiation of breastfeeding
No	4839	1.00	0.001	4832	1.00	0.010
Yes	4839	0.81 (0.72, 0.92)		4832	0.85 (0.75, 0.96)
Exclusive breastfeeding
No	1452	1.00	0.001	1397	1.00	< 0.001
Yes	1452	0.65 (0.51, 0.83)		1397	0.51 (0.39, 0.65)
Predominant breastfeeding
No	1029	1.00	0.159	1053	1.00	0.006
Yes	1029	0.80 (0.59, 1.09)		1053	0.69 (0.53, 0.89)
Introduction of complementary foods
No	736	1.00	0.620	825	1.00	0.453
Yes	736	0.92 (0.66, 1.28)		825	1.08 (0.87, 1.35)
Continued breastfeeding at 2 years
No	341	1.00	0.078	358	1.00	0.009
Yes	341	1.59 (0.95, 2.68)		358	1.57 (1.12, 2.21)
Bottle feeding
No	2059	1.00	0.004	2100	1.00	0.173
Yes	2059	1.36 (1.10, 1.68)		2100	(0.95, 1.28)

n: count of IYCF indicators in propensity score-matched data;

* indicates adjusted ORs in propensity score-matched data

Ethics approval and consent to participate

The surveys were conducted after ethical approval were obtained from the National Research Ethics Review Committee (NRERC) in Ethiopia. During the survey, permission from administrative offices and verbal consent from study participants was obtained before the commencement of data collection. For this study, the datasets used were obtained from Measure DHS/ICF with approval.

Results

Characteristics of the study participants

Nearly two-thirds of mothers (71.5%) did not attain any schooling, and more than half (55.0%) of mothers had no employment. Among the study participants, less than half (48.3%) of mothers were in 25–34 years’ age group. The majority (95.5%) of mothers resided in households that used improved cooking fuel. More than half (54.8%) of mothers resided in households that did not use improved source of drinking water [Table 1].

Table 1

Characteristics of the study participants in Ethiopia, 2000–2016.

Variables	2000 (N = 3680)	2005 (N = 3528)	2011 (N = 4037)	2016 (N = 3861)	2000–2016 (N = 15,106)
	n (%)	n (%)	n (%)	n (%)	n (%)
Socioeconomic factors
Maternal education
No schooling	3434 (81.1)	3120 (77.9)	2802 (66.8)	2460 (60.3)	11846 (71.5)
Primary school	582 (13.7)	705 (17.6)	1204 (28.7)	1262 (30.9)	3753 (22.7)
Secondary and higher	220 (5.2)	183 (4.5)	191 (4.5)	360 (8.8)	954 (5.8)
Maternal employment
No employment	1640 (38.7)	2915 (72.8)	2096 (50.4)	2416 (59.2)	9066 (55.0)
Formal employment	373 (8.8)	284 (7.1)	686 (16.5)	508 (12.4)	1851 (11.2)
Informal employment	2222 (52.5)	804 (20.1)	1379 (33.1)	1160 (28.4)	5565 (33.8)
Partner education
No schooling	2599 (62.2)	2230 (56.2)	1989 (48.1)	1744 (45.2)	8562 (53.1)
Primary school	1098 (26.3)	1289 (32.5)	1765 (42.7)	1548 (40.1)	5700 (35.3)
Secondary and higher	480 (11.5)	449 (11.3)	380 (9.2)	569 (14.7)	1878 (11.6)
Household wealth status
Poor	129 5(30.6)	1711 (42.7)	1913 (45.6)	1846 (45.2)	6765 (40.9)
Middle	1197 (28.3)	879 (21.9)	878 (20.9)	859 (21.0)	3812 (12.1)
Rich	1743 (41.2)	1417 (35.4)	1407 (33.5)	1378 (33.8)	5946 (36.0)
Demographic factors
Maternal age
15–24 years	1408 (33.3)	1267 (31.6)	1285 (30.6)	1207 ((29.6)	5167 (31.3)
25–34 years	1936 (45.7)	1900 (47.4)	2077 (49.5)	2067 (50.6)	7980 (48.3)
35–49 years	891 (21)	840 (21.0)	835 (1.9)	809 (19.8)	3375 (20.4)
Family size
≤ 3	471 (11.1)	426 (10.6)	485 (11.6)	484 (11.8)	1866 (11.3)
4–5	1445 (34.1)	1321 (33.0)	1447 (34.5)	1411 (34.6)	5624 (34.0)
6+	2319 (54.8)	2260 (56.4)	2265 (54.9)	2188 (53.6)	9032 (54.7)
Listening radio
No	3161 (74.7)	2576 (64.3)	2094 (49.9)	2973 (72.8)	10805 (65.4)
Yes	1072 (25.3)	1431 (35.7)	2101 (50.1)	1110 (27.2)	5714 (34.6)
Reading magazine
No	3985 (94.1)	3761 (94.0)	3846 (91.7)	3802 (93.1)	15394 (93.2)
Yes	250 (5.9)	238 (6.0)	349 (8.3)	281 (6.9)	1118 (6.8)
Watching TV
No	4007 (94.7)	3637 (90.9)	2763 (65.9)	3333 (81.6)	13740 (83.3)
Yes	225 (5.3)	363 (9.1)	1428 (34.1)	750 (18.4)	2765 (16.8)
Desire for pregnancy
Desired the pregnancy	3456 (81.6)	3293 (82.2)	3755 (89.5)	3740 (91.6)	14243 (86.2)
Not desired the pregnancy	778 (18.4)	714 (17.8)	442 (10.5)	343 (8.4)	2277 (13.8)
Household factors
Type of fuel for cooking
Improved	256 (6.0)	87 (2.2)	178 (4.3)	215 (5.3)	735 (4.5)
Not improved	3980 (94.0)	3919 (97.8)	4012 (95.7)	3865 (94.7)	15776 (95.5)
Source of drinking water
Improved	1842 (43.5)	2247 (56.1)	1511 (36.0)	1862 (45.6)	7463 (45.2)
Not improved	2394 (56.5)	1760 (43.9)	2686 (64.0)	2221 (54.4)	9060 (54.8)
Type of toilet system
Improved	590 (13.9)	387 (9.7)	523 (12.5)	415 (10.2)	1914 (9.5)
Not improved	3646 (86.1)	3620 (90.3)	3674 (87.5)	3668 (89.8)	14608 (88.4)
Health service factors
Ever received vaccine
No	1448 (45.9)	1343 (52.0)	1245 (42.2)	1121 (42.5)	5157 (45.6)
Yes	1705 (54.1)	1238 (48.0)	1690 (57.6)	1518 (57.5)	6151 (54.4)
Antenatal Visit
None	3122 (74.2)	2845 (71.3)	2369 (56.6)	1412 (34.8)	9748 (59.3)
1–3 visits	691 (16.4)	664 (16.6)	1085 (25.9)	1288 (31.7)	3727 (22.6)
4+ visits	396 (9.4)	479 (12)	735 (17.6)	1362 (33.5)	2972 (18.1)
Mode of delivery
Vaginal birthing	4205 (99.5)	3968 (99)	4115 (98.1)	3978 (97.4)	16266 (98.5)
Caesarean section	23 (0.5)	39 (1.0)	82 (1.9)	105 (2.6)	250 (1.5)
Place of birth
Home	4028 (95.1)	3763 (93.9)	3721 (88.7)	2593 (63.5)	14104 (85.4)
Health facility	208 (4.9)	242 (6.1)	476 (11.4)	1490 (36.5)	2416 (14.6)
Delivery assistance
Health professional	3397 (24.1)	432 (11.4)	491 (12.1)	1521 (43.9)	2829 (18.5)
Traditional birth attendant	3103 (22.0)	522 (13.8)	253 (6.2)	1387 (40.0)	3002 (19.6)
Others untrained	7621 (54.0)	2829 (74.8)	3304 (81.6)	560 (16.1)	9460 (61.9)
Timing of postnatal check-up
None	4006 (94.6)	3786 (94.5)	4065 (96.9)	3776 (92.3)	15632 (94.6)
Within a week	179 (4.2)	176 (4.4)	42 (1.0)	154 (3.8)	551 (3.3)
After a week	50 (1.2)	46 (1.1)	90 (2.1)	153 (3.7)	338 (2.10)
Community-level factors
Place of residence
Urban	405 (9.6)	296 (7.4)	558 (13.3)	492 (12.0)	1750 (10.6)
Rural	3831 (90.4)	3711 (92.6)	3639 (86.7)	3591 (88.0)	14773 (89.4)
Region of residence
Tigray	251 (5.9)	242 (6.1)	261 (6.2)	299 (7.3)	1053 (6.4)
Afar	35 (8.4)	37 (9.2)	37 (8.8)	39 (9.6)	149 (1.0)
Amhara	1092 (25.8)	946 (23.6)	923 (22.0)	751 (18.4)	3712 (22.5)
Oromia	1736 (41.0)	1548 (38.6)	1815 (43.2)	1827 (44.8)	6926 (41.9)
Somali	47 (11.1)	153 (3.8)	120 (2.9)	170 (4.2)	490 (3.0)
Benishangul	43 (1.0)	37 (9.3)	48 (1.1)	43 (1.1)	171 (1.0)
SNNPR*	931 (22.0)	953 (23.8)	867 (20.7)	815 (20.0)	3566 (21.6)
Gambella	10 (2.4)	10 (2.5)	13 (3.2)	10 (2.4)	43 (2.6)
Metropolis	89 (2.1)	80 (2.0)	113 (2.7)	130 (3.2)	413 (2.5)

n (%): weighted count and proportion for each variable

*SNNPR: Southern Nations Nationalities and Peoples Region

Prevalence of ARI and diarrhoea by IYCF practices

Infants who were exclusively breastfed had a lower prevalence of ARI (9.9%; 95% CI: 8.3%, 11.8%) compared to those who were not exclusively breastfed (15.0%; 95% CI: 12.8%, 17.5%). Infants who commenced breastfeeding within the first hour of birth had a lower prevalence of ARI (13.9%; 95% CI: 12.7%, 15.1%) compared to those whose mothers delayed initiation of breastfeeding (17.3%; 95% CI: 15.7%, 18.9%) [Table 2]. The proportion of diarrhoea was lower among infants aged 0–5 months who were exclusively breastfed (7.7%; 95% CI: 6.3%, 9.4%) compared to those who were not exclusively breastfed (15.7%; 95% CI: 13.6%, 18.1%). Infants aged 0–5 months who were predominantly breastfed had a lower prevalence of diarrhoea (10.1%; 95% CI: 8.8%, 11.7%) compared to those who were not predominantly breastfed (15.3%; 95% CI: 13.6%, 18.1%) [Table 2].

Table 2

Prevalence of acute respiratory infection and diarrhoea by infant and young child feeding in Ethiopia, 2000 to 2016.

IYCF factors		Prevalence of ARI			Prevalence of diarrhoea
	a	b	% (95% CI)	P value	b	% (95% CI)	P value
Early initiation of breastfeeding
No	6517	1125	17.3 (15.7, 18.9)	<0.001	1607	24.7 (23.0, 26.4)	0.031
Yes	8589	1387	13.9 (12.7, 15.1)		2245	22.5 (21.1, 23.9)
Exclusive breastfeeding
No	2106	316	15.0 (12.8, 17.5)	<0.001	331	15.7 (13.6, 18.1)	<0.001
Yes	2447	243	9.9 (8.3, 11.8)		188	7.7 (6.3, 9.4)
Predominant breastfeeding
No	1129	162	14.4 (11.6, 17.7)	0.107	172	15.3 (12.6, 18.4)	0.002
Yes	3424	396	11.6 (10.0, 13.4)		347	10.1 (8.8, 11.7)
Introduction of complementary foods
No	1204	227	18.8 (15.5, 22.6)	0.019	322	26.7 (23.3, 30.4)	0.978
Yes	1133	153	13.5 (10.8, 16.8)		303	26.8 (23.2, 30.7)
Continued breastfeeding at 2 years
No	403	48	11.9 (8.0, 17.4)	0.037	80	20.0 (14.9, 26.3)	0.022
Yes	1717	301	17.5 (15.1, 20.3)		470	27.4 (24.1, 31.0)
Bottle feeding
No	13129	2182	15.0 (14.0, 16.1)	0.217	3425	23.6 (22.4, 24.8)	0.200
Yes	1977	330	16.7 (14.2, 19.5)		427	21.7 (19.0, 24.6)

a indicates the total sub-sample in each exposure variables

b indicates weighted count in unmatched data

Association between IYCF and ARI

EIBF was associated with a lower odds of ARI among infants and young children compared to their counterparts (OR: 0.81; 95% CI: 0.72, 0.92). Infants who were exclusively breastfed were less likely to experience ARI compared to those who were not exclusively breastfed (OR: 0.65; 95% CI: 0.51, 0.83). Infants and young children aged 0–23 months who were bottle-fed were more likely to experience ARI compared to those who were not bottle-fed (OR: 1.36; 95% CI: 1.10, 1.68) [Table 3]. Similar results were observed in ordinary multivariable logistic regression models, where EIBF and EBF were associated with lower risk of ARI (

Considering the modifying effect of cooking fuel on ARI, multivariate analyses showed that the relationship between EIBF and ARI was stronger in households with unimproved cooking fuel. Similar results were evident in the association between EBF and bottle feeding with ARI [Table 4].

Table 4

Modifying effect of cooking fuel on acute respiratory infection in Ethiopia, 2000–2016.

IYCF factors	Acute respiratory infection			P for interaction
	Type of cooking fuel
	n	Improved	Not improved
		*OR (95% CI)	*OR (95% CI)
Early initiation of breastfeeding
No	4839	1.00	1.00	0.940
Yes	4839	0.77 (0.33, 1.79)	0.82 (0.72, 0.93)
Exclusive breastfeeding
No	1452	1.00	1.00	0.274
Yes	1452	1.06 (0.33, 3.37)	0.62 (0.48, 0.80)
Predominant breastfeeding
No	1029	1.00	1.00	0.104
Yes	1029	2.18 (0.66, 7.17)	0.74 (0.53, 1.03)
Introduction of complementary foods
No	736	1.00	1.00	0.361
Yes	736	0.79 (0.05, 13.28)	0.94 (0.67, 1.32)
Continued breastfeeding at 2 years
No	341	1.00	1.00	0.896
Yes	341	1.64 (0.31, 8.69)	1.75 (1.03, 2.96)
Bottle feeding
No	2059	1.00	1.00	0.379
Yes	2059	1.00 (0.46, 2.20)	1.44 (1.16, 1.78)

n: count of IYCF indicators in propensity score-matched data

*indicates adjusted ORs in propensity score-matched data

P for interaction: p-value of likelihood ratio test for the interaction between survey years and a given IYCF indicator

Association between IYCF and diarrhoea

Infants and young children aged 0–23 months who were breastfed within the first hour of birth were less likely to experience diarrhoea compared to those who were not breastfed within the first hour of birth (OR: 0.88; 95% CI: 0.79, 0.94). EBF and predominant breastfeeding were associated with lower odds of diarrhoea among Ethiopian infants (OR: 0.51; 95% CI: 0.39, 0.65 for EBF and OR: 0.69; 95% CI: 0.53, 0.89 for predominant breastfeeding). Children aged 20–23 months whose mothers continued breastfeeding at two years had a higher odds of experiencing diarrhoea compared to those whose mothers discontinued breastfeeding (OR: 1.57; 95% CI: 1.12, 2.21) [Table 3]. Similar results were evident in ordinary multivariable logistic regression models, where EIBF, EBF and predominant breastfeeding were associated with lower odds of diarrhoea (

In the stratified analysis that considered the modifying effect of the type of toilet and source of drinking water on diarrhoea, EIBF and EBF were strongly associated with lower risk of diarrhoea in households with unimproved type of toilet system and source of drinking water (Table 5).

Table 5

Modifying effect of water and sanitation on diarrhoea in Ethiopia, 2000–2016.

IYCF factors	Diarrhoea			P for interaction	Diarrhoea			P for interaction
	Type of toilet				Source of drinking water
	n	Improved,	Not improved,		n	Improved	Not improved
		*OR (95% CI)	*OR (95% CI)			*OR (95% CI)	*OR (95% CI)
Early initiation of breastfeeding
No	4832	1.00	1.00	0.625	4826	1.00	1.00	0.559
Yes	4832	0.88 (0.68, 1.15)	0.84 (0.75, 0.94)		4882	0.82 (0.71, 0.94)	0.88 (0.76, 1.02)
Exclusive breastfeeding
No	1383	1.00	1.00	0.379	1400	1.00	1.00	0.854
Yes	1383	0.65 (0.30, 1.41)	0.48 (0.37, 0.62)		1400	0.44 (0.30, 0.66)	0.48 (0.34, 0.66)
Predominant breastfeeding
No	999	1.00	1.00	0.591	995	1.00	1.00	0.613
Yes	999	0.72 (0.37, 1.41)	0.63 (0.47, 0.85)		995	0.63 (0.43, 0.93)	0.72 (0.50, 1.04)
Introduction of complementary foods
No	746	1.00	1.00	0.392	824	1.00	1.00	0.409
Yes	746	1.02 (0.52, 1.98)	1.02 (0.79, 1.33)		824	1.21 (0.87, 1.69)	1.03 (0.74, 1.46)
Continued breastfeeding at 2 years
No	377	1.00	1.00	0.818	360	1.00	1.00	0.724
Yes	377	1.56 (0.79, 3.09)	1.39 (0.97, 1.99)		360	1.47 (0.92, 2.36)	1.74 (0.91, 3.32)
Bottle feeding
No	2117	1.00	1.00	0.261	2109	1.00	1.00	0.208
Yes	2117	0.91 (0.69, 1.21)	1.11 (0.93, 1.32)		2109	1.00 (0.82, 1.22)	1.23 (0.95, 1.58)

n: count of IYCF indicators in propensity score-matched data

*indicates adjusted ORs in propensity score-matched data

P for interaction: p-value of likelihood ratio test for the interaction between survey years and each IYCF indicator

Discussion

The present study found that EIBF and EBF were associated with a lower risk for infants and young children to experience ARI in Ethiopia, while bottle-feeding was associated with a higher risk of ARI. EIBF, EBF and predominant breastfeeding were associated with a lower risk of diarrhoea among infants and young children in Ethiopia. Continued breastfeeding at 2 years of age was associated with an increased risk of diarrhoea. The associations between EIBF, EBF and bottle feeding with ARI were stronger in households with unimproved type of cooking fuel. Similarly, in households with unimproved toilet system and source of drinking water, EIBF and EBF had stronger associations with diarrhoea.

Since 1990, despite substantial declines in global child mortality, respiratory infections still remain leading causes of death among children younger than five year of age [57]. Evidence suggests that the increased risk of ARI in children depends on a range of factors, including sub-optimal breastfeeding, malnutrition, household environment (such as crowding and air pollution), poor vaccine coverage and antibiotic misuse [57-60]. Consistent with the literature, our findings showed that children who commenced breastfeeding within the first hour of birth and were exclusively breastfed had a reduced risk of experiencing ARI compared to their counterparts. The biological mechanism for the protective effect of optimal breastfeeding against ARI may be due to the presence of immunological substances (such as oligosaccharides, immunoglobulins, hormones, and enzymes) in breastmilk [61, 62]. These immunological substances provide passive immunity to the infant, as well as assist in the maturation of the infant immune system [61, 62]. Also, improved childhood nutrition status from optimal breastfeeding can partially explain the protective effect of breastfeeding against ARI [58, 61].

Evidence has shown that optimal breastfeeding is associated with reduced childhood morbidity and mortality attributable to diarrhoeal diseases [12, 63]. Consistent with past studies [8, 11, 13, 15, 59], this study found that EIBF and EBF were associated with a lower risk of diarrhoea. Optimal breastfeeding can reduce the incidence of diarrhoea via three mechanisms. Firstly, breastfeeding eliminates the infant’s exposure to contaminated foods and fluids. Secondly, breastmilk provides the infant with anti-microbial and immunological substances that stimulate the gastrointestinal tract of the infant to develop passive immunity against pathogens [61, 62]. Finally, breastfeeding improves the nutritional status of the infant which can, in turn, lower the risk of childhood diarrhoea [58, 61].

Previous studies conducted in Vietnam [64], Nepal [65], and Brazil [66] have suggested that predominant breastfeeding, which is the provision of non-milk fluids (such as water, tea, and juices) in addition to breastmilk to infants, can increase the risk of childhood diarrhoea. However, the present study found that predominant breastfeeding was associated with a lower odds of infants to experience diarrhoea in Ethiopia. Our finding was consistent with studies conducted in sub-Saharan African [11, 13, 15] and South Asian countries [39, 40], which showed that predominant breastfeeding was associated with a lower risk of diarrhoea in children. Despite the variations in the literature on the health effect of predominant breastfeeding, some authors have argued that promoting both EBF and predominant breastfeeding may be beneficial to the infant as some studies found lower risk of ARI and diarrhoea among predominantly breastfed infants [11, 13]. In many African countries, the provision of water and non-milk fluids to infants is a common socio-cultural practice [67-69] (often promoted by the mothers-in-law and/or grandmothers) [70, 71] as mothers reported that providing water to infants immediately after breastfeeding helps to quench thirst or stop hiccups [69]. However, the provision of water can be a source of infection for infants and young children in those environments. In a low income country like Ethiopia, where access to potable water is limited and sanitation is poor [72], advocating for predominant breastfeeding alongside EBF may predispose infants and young children to experience diarrhoea.

Based on the immunological, nutritional, hygienic, economic and psychological advantages of breastfeeding to the infant, the mother and the community [14], the WHO/UNICEF recommends that mothers should continue breastfeeding until the child is two years of age and beyond [33]. Our study suggested that children who continued breastfeeding at two years of age had higher odds of experiencing diarrhoea compared to those who had discontinued breastfeeding at two years of age. This finding was supported by studies conducted in LMICs that showed the positive relationship between continued breastfeeding and childhood diarrhoea [10, 13, 15]. While it is important to introduce complementary foods to infants at around six months of age, those complementary foods can be contaminated due to unhygienic preparation, unsafe storage, insufficient cooking time and use of unhygienic feeding utensils [73, 74]. The concurrent provision of potentially contaminated complementary foods and breastmilk to children around the age of 2 years could be a possible reason for the observed association between continued breastfeeding at two years and diarrhoea

Previous research has indicated that breastfed infants have fewer infections and hospitalizations rate compared to bottle-fed infants [15, 75]. The current study showed that children aged 0–23 months who were bottle-fed had a higher risk of experiencing ARI compared to their counterparts. Past studies have shown that infants who were bottle-fed had lower opportunities for receiving antibodies and other immune complexes from their mothers [61, 62]. It is also possible that the relationship between bottle feeding and ARI is evident because bottle feeding may promote a higher rate of swallowing and more frequent interruption of breathing, which may increase the risk for micro-aspiration, and can lead to chest infection [76, 77].

Policy implications of the study findings

Taken together, the present study suggests that interventions aiming to reduce the burden of ARI and diarrhoea among Ethiopian children should consider context-specific stand-alone and/or integrated IYCF interventions in both the community and health facility. Relevant policy initiatives to improve IYCF practice among mothers and subsequently reduce diarrhoea and ARI burden in Ethiopia have been described in detail elsewhere [78]. This paper will highlight key interventions alongside the current Ethiopian Government strategy to increase IYCF practices.

Community-based interventions such as group nutritional education and counselling, family or social support, integrated mass media coverage, and community mobilization have been shown to improve IYCF in LMICs [79]. The successful implementation of any of these community-based interventions for IYCF would require a wide variety of key community stakeholders in Ethiopia, including policymakers, health practitioners, experienced behaviour communication change agents, community and women leaders [80]. A recent study conducted in Ethiopia suggested that sociocultural structure and belief systems (particularly at the household level) do not fully support the promotion of optimal IYCF [81]. The involvement of close family members (fathers and/or grandmothers) have been shown to increase optimal IYCF practices [82-84]. Therefore, community-based interventions that aim to improve IYCF in Ethiopia must consider the involvement of these close family members who play an important role in mothers' decisions to initiate, cease or continue breastfeeding in the early postnatal period [85, 86].

Facility-based interventions play a pivotal role in increasing optimal IYCF participation. For example, the Baby Friendly Hospital Initiatives (BFHI) is an effective approach to increase breastfeeding in BFHI-certified facilities. The BFHI is a global effort launched by WHO and UNICEF to implement policies that protect, promote and support breastfeeding [87]. Evidence on the successful implementation of the BFHI has been published elsewhere [88, 89]. However, in Ethiopia, none of the health facilities are accredited for BFHI [90], suggesting that Ethiopian mothers are not receiving appropriate and skilled IYCF support from available health facilities. This gap in the initiation and implementation of BFHI in Ethiopia suggests that initiating and implementing BFHI at the health facility level would play a crucial role in improving IYCF and reduce the disease burden attributable to ARI and diarrhoea in Ethiopia.

In 2008, the Federal Democratic Republic of Ethiopia launched the National Nutrition Strategy (NNS) to improve child health outcomes, including IYCF [91]. Although significant improvements in child nutritional status, morbidity and mortality have been observed in Ethiopia [21, 22], additional policy interventions are still required. Hence, in 2015, the Government of Ethiopia introduced the Health Sector Transformation Plan [27], with the aim to increase a range of health outcomes for Ethiopians, including IYCF practices. Although this initiative is needed and well-deserved, there is a need for Ethiopian health stakeholders to strengthen the BFHI in order to improve IYCF behaviours. This measure is crucial to improve IYCF and subsequently reduce ARI and diarrhoea burden in Ethiopia because a recent assessment of IYCF scored BFHI service zero out of ten points in the country [90]. Also, future studies that evaluate the success, challenges and opportunities of the Ethiopian Health Sector Transformation Plan within the context of the impact on IYCF may be needed to guide refinement of future programs.

Strengths and limitations of the study

The potential limitations that should be considered while interpreting the result of this study include: firstly, the cross-sectional nature of the study means that clear temporal associations between IYCF, and ARI and diarrhoea cannot be established. Nevertheless, the observed associations are consistent with previously published studies [10, 13, 15]. Secondly, the surveys were based on self-reported measures which could be a source of recall bias as mothers may incorrectly reported the number of loose stools passed by the child, however, the study was restricted to the youngest living child to minimize recall bias.

Thirdly, misclassification bias may have impacted result. This is because the classification of common cold as ARI or a minimal change to normal bowel habit as diarrhoea, as well as incorrect categorization of household-level characteristics such as type of cooking fuel and/or sanitation facility. This may have increased or decreased the measure of association between exposures and outcomes. Fourthly, unobserved confounders such as socio-cultural interactions between the members of the family and across the given community may influence the relationship between optimal IYCF practices and childhood infections.

Despite the above limitations, using nationally representative data with a high response rate is a strength in our study. The use of standardized questionnaire for the data collection is also a strength of this study. Finally, another strength of the study is the adjustment for potential confounders using the PSM approach in the estimation of the association between IYCF and ARI and diarrhoea.

Conclusion

EIBF and EBF were protective against ARI and diarrhoea, while bottle-feeding was associated with a higher odds of ARI in Ethiopian children. Infants who were predominantly breastfed had a lower odds of experiencing diarrhoea. Our study suggests that community- and facility-based interventions that targets improved IYCF practices should be prioritised and scaled-up to reduce the burden of ARI and diarrhoea among Ethiopian children.

Distribution of propensity scores before and after nearest neighbour (0.1) matching in ARI and IYCF indicator.

(DOCX)

Click here for additional data file.

Distribution of propensity scores before and after nearest neighbour (0.1) matching in diarrhoea and IYCF indicator.

(DOCX)

Click here for additional data file.

(DOCX)

Click here for additional data file.

13 Jan 2020

PONE-D-19-33411

Associations between infant and young child feeding practices and acute respiratory infection and diarrhoea in Ethiopia: A propensity score matching approach

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Additional Editor Comments:

I have a few additional comments to add to the comments from the reviewers:

1) You should shorten the introduction substantially and focus on briefly explaining the background of the research question and why it is relevant in the ethiopian context.

2) Can you please confirm that you included all background characteristics in table 1 in the prediction model to generate the probability of exposure to use in the propensity score matching?

3) Please clarify whether you included the outcomes in this prediction model to generate the probability of exposure? To the best of my knowledge of propensity score matching, the probability of exposure should be generated using all background characteristics than can be considered as confounders of the exposure and outcome relationship but not the outcome itself.

4) I struggled to understand why you included some of the background characteristics, including listening radio, reading magazine, watching TC and desire for pregnancy. Please provide a justification.

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: I Don't Know

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

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Reviewer #2: Yes

Reviewer #3: Yes

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5. Review Comments to the Author

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Reviewer #1: The manuscript is technically sound. The authors have employed sound study design and methodology to investigate well-defined exposures and outcomes. The sample size was large enough and the data analysis techniques was robust and rigorous. I believe the authors have made all the data underlying the findings although some files could not be opened probably due to poor internet connection at which I was located during the review. The entire presentation of the manuscript followed a logical sequence with near perfect use of English. However, I have the following suggestions for the authors to consider:

Abstract

Background:

Line 34, ‘are the leading causes of’ not ‘are the leading cause of’ are grammatically more correct

Conclusion:

It would better to conclude by stating that recommended best practices for preventing ARI and diarrhea diseases in infants and young children namely; the early initiation of breastfeeding, exclusive breastfeeding and avoidance of bottle feeding should be institutionalized and scale up in Ethiopia as part of implementation science approach to cover the know-do-gaps.

Main manuscript

Methods:

It would be nice to begin the methods section with brief descriptions of the study designs and settings, although some mentions of Ethiopian settings were made under the introduction

EIBF is better defined as ‘commencement of breastfeeding within 1 hour of birth’ as opposed to ‘infants breastfed or put to breast within 1 hour of birth’. While the former indicates something that has started and continued, the later may mean a one-off event that never happen again. I suggest the authors use a phrase that more appropriately described the event. If feasible, commencement of breastfeeding should be replace put to breast in the entire manuscript.

Analytical strategy

Line 226 – line 254: starting with explanation on RCTs and ending with why PSM approach was used in this study, the entire paragraph may no be necessary for this section. If at all such explanations are needed, some of them should go under study design or more appropriate in the discussion section. I don’t think these detailed descriptions of RCT, use of PSM approach and its advantages is required under data analysis methods. Discussions here should be limited to how the data were analyzed.

Results

The authors repeatedly described the difference in prevalence of ARI and diarrhea among the exposed and unexposed as significant. However, neither in the narrative nor in table 2 were the associated p-values stated. Rather, would it be safer to modify the narration by removing the word ‘significantly’?

I am also wondering if it would add value to the interpretation of the odd ratios of developing outcomes comparing the exposed and unexposed if P-values are included in the results narrative or in the corresponding tables. I noticed some of the confidence intervals included 1 which is a neutral effect.

Study weakness

Another weakness to consider is that description of ‘loose or watery stool’ to define diarrhea might not have objectively capture infants who had diarrhea and who had not as such descriptions are too subjective.

Reviewer #2: General comments

• The study is relevant to Ethiopia and other countries with low income status. The topic is particularly relevant to Ethiopia where there is very high prevalence of under-five malnutrition and child mortality. It could provide important insight about the situation of IYCF practices and its association with common childhood illnesses (diarrhea and ARI). The findings of the study could be used to inform planning and policy making exercise in the country and the wider region of sub-Saharan Africa.

• The article is well but it could benefit from professional language editor.

Abstract

Page 2, line 46.

• The authors wrote “…..exclusively breastfed had a lower prevalence of ARI.” I think using the word incidence is a better than prevalence.

• Too many abbreviations in the abstract. It is better to minimize the abbreviations.

Introduction

• The introduction clearly illustrates the problem of ARI and diarrhea; the magnitude and consequence of inappropriate infant and young child feeding (IYCF) in low income settings. However, the rationale for the study is not clearly stated. I think the authors need to strengthen the rationale for the study. A number of studies have tried to answer this research question, the authors need to elaborate the research gaps addressed by the study.

• Overall, I feel that it could be shortened with more emphasis on the rational of the study.

• The authors need to include at least recent Ethiopian studies addressing similar research questions using the same dataset (Ethiopian Demographic and Health Survey EDHS). For instance, Nigatu D, et al 2019 assess effect of exclusive breastfeeding cessation on diarrhea and ARI (using EDHS 2011 and 2016) and Amsalu ET, 2019 also assess determinants of ARI( using EDHS 2016).

Method

• Page 8-9, Possible confounders

Immunization status of a child could be one of the predictors of ARI and diarrhea, but the authors did not consider it. Since, information on child immunization is available in EDHS data, could you explain why it is excluded?

Analysis:

• Page 10, line 218-19

The authors wrote “The initial analysis involved the tabulation of frequencies and percentages of ARI and diarrhoea by each study variable.”

What does “each study variable” refers to? Only exposures?

• Page 10, line 226. I do not see the relevance of mentioning RCT as a gold standard method. Rather, it could be more relevant to discuss the advantage of PSM over commonly used multivariable model for this data.

• The four surveys conducted in different time points (from 2000 to 2016). Are these data fairly similar to be combined, even if no interaction of survey year and… In fact, the authors stated that infant mortality decreased from 97 in the year 2000 to 43 per 1000 in 2019.

• How was missing data handled? You may state the EDHS procedures to handle missing data.

• I am not an expert in PSM technique and I suggest an expert in the field should review the appropriateness of the analytic procedures followed.

Result

• The authors should mention the sub-samples of mother-infant pairs included for each exposure.

• Although the overall sample is large. Some exposures seems to have limited power. For instance in table 2. Distribution of ARI over the exposure “continued breastfeeding at 2 years”, one of the cells have only 48 children (weighted). Could you also say something about adequacy power?.

• It would be more informative if you present (as a supplemental table) SDC of sub-samples used for analysis and the trend in IYCF and the outcomes over time.

Discussion.

• In general the discussion address important points but I feel that it can be made more coherent and short.

• The authors need to have a more robust discussion on the possible limitations of the study.

For instance, misclassification bias could be a source of bias because ARI and diarrhea are not diagnosed by clinicians. It is based on mothers recall. For instance, common cold could be confused with ARI.

Besides, it might be challenging for the mother to differentiate between normal bowel habits of children from diarrhea, specifically mild form of diarrhea.

Reviewer #3: Comments to authors

This is an important, interesting and well-written manuscript. I have only minor comments.

Introduction

-It would be useful, if possible, to have information about the percentage of children vaccinated in Ethiopia.

-Line 103: Could it also be due to the replacement of human milk by complementary foods/drinks?

-Line 119-120: The EBF of 59.9%; - which age/age-group? It would be useful to add information on continued breastfeeding until 2 y and the percentage never breastfed. Also, it would be useful to know whether/how the socioeconomic factors are associated with the IYCF indicators in this population.

Methods

As this reviewer has not conducted analysis using the propensity score matching approach, my understanding of the method is limited. Therefore, it was useful for me to have an explanation of this method under methods, but I do not know whether this is of general interest. I recommend that a statistician consider this and review the statistical methods.

Results

-Under “results” it would be useful to have an overview of sample sizes, so it is easier to understand the different «n`s» in e.g. table 2 and 3.

-In general, it would be useful to mention/describe the reference groups in more detail. Were the reference groups mixed groups, e.g. in line 311: Those who were «not predominantly breastfed», what were they fed, were some not breastfed?

-Table 1. Is it necessary to include «Region of residence» in the table?

-Line 297-299: Should findings be reported in «the same direction»?

Discussion

-The accuracy of the definition of diarrhoea as the passage of three of more liquid stools should be discussed, as it is normal with at least 3 or more liquid stools per day in exclusively breastfed infants during the first months (1). How this may have affected the findings should be discussed.

-Is it possible to compare the «effect size» on EIBF and EBF on ARI and diarrhoea with other studies in similar contexts?

-In the discussion it is mentioned that reverse causation cannot be excluded as an interpretation of the findings. It is improbable that this can explain the findings of EIBF and ARI/ diarrhoea, although it is relevant for EBF. (It would be interesting to know whether there are studies on how the occurrence of ARI and diarrhoea influence breastfeeding in various contexts, does it lead to intensified breastfeeding or more supplementation of water-based drinks?)

1. Moretti E, Rakza T, Mestdagh B, Labreuche J, Turck D. The bowel movement characteristics of exclusively breastfed and exclusively formula fed infants differ during the first three months of life. Acta paediatrica (Oslo, Norway : 1992). 2019;108(5):877-81.

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Reviewer #1: Yes: Salisu Ishaku Mohammed

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Reviewer #3: Yes: Anne Baerug

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23 Feb 2020

February 23 2020

Maria Christine Magnus, MPH

Academic Editor

PLOS ONE

Dear Dr. Magnus,

RE: Manuscript resubmission – [PONE-D-19-33411] Associations between infant and young child feeding practices and acute respiratory infection and diarrhoea in Ethiopia: A propensity score matching approach

Thank you for the invitation to revise our subject-titled manuscript and for the very constructive comments from the reviewers and editor. A revised manuscript (clean and version with track changes) reflecting the following point-by-point response to the editor and the reviewers’ comments have been submitted for your consideration.

Academic Editor

General comments

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf

http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Response:

The manuscript has been revised to meet PLOS ONE's style requirements.

2. We suggest you thoroughly copyedit your manuscript for language usage, spelling, and grammar. If you do not know anyone who can help you do this, you may wish to consider employing a professional scientific editing service.

Response:

The manuscript has been thoroughly copyedited by co-authors who are native English language speakers.

Additional Editor comments

1. You should shorten the introduction substantially and focus on briefly explaining the background of the research question and why it is relevant in the Ethiopian context.

Response:

We appreciate the Editor comment and note that the entire introduction section has been substantially edited as requested by the Editor (Page 4-6).

2. Can you please confirm that you included all background characteristics in table 1 in the prediction model to generate the probability of exposure to use in the propensity score matching?

Response:

Thank you so much for the observation. We can confirm that all background characteristics were included in model to generate the probability of exposure in the propensity score matching. This information has been noted in the revised manuscript (Page 12, Paragraph 02).

3. Please clarify whether you included the outcomes in this prediction model to generate the probability of exposure? To the best of my knowledge of propensity score matching, the probability of exposure should be generated using all background characteristics than can be considered as confounders of the exposure and outcome relationship but not the outcome itself.

Response:

We appreciate the editor’s concern. We can confirm that the propensity score was generated in the model without the inclusion of the outcome variables.

4. I struggled to understand why you included some of the background characteristics, including listening radio, reading magazine, watching TC and desire for pregnancy. Please provide a justification.

Response:

This study forms part of the requirements for the award of Doctor of Philosophy for the first author. Against this background, we note our previously published studies have elucidated determinants of IYCF practices in many countries, including Ethiopia. Those studies found that those variables (among others) were related with IYCF practices ( Ahmed et al, 2019a; 2019b; Ogbo et al, 2017; 2018; Victor et al, 2014). This justification was noted in the original manuscript (Page 09, Parag 01)

References

1. Ahmed, K. Y., Page, A., Arora, A., & Ogbo, F. A. (2019). Trends and determinants of early initiation of breastfeeding and exclusive breastfeeding in Ethiopia from 2000 to 2016. Int Breastfeed J, 14(1), 40.

2. Ahmed, K. Y., Page, A., Arora, A., & Ogbo, F. A. (2019). Trends and factors associated with complementary feeding practices in Ethiopia from 2005 to 2016. Matern. Child Nutr., e12926

3. Victor R, Baines SK, Agho KE, Dibley MJ. Factors associated with inappropriate complementary feeding practices among children aged 6–23 months in Tanzania. Matern Child Nutr. 2014;10(4):545-61.

4. Ogbo FA, Ogeleka P, Awosemo AO. Trends and determinants of complementary feeding practices in Tanzania, 2004-2016. Trop Med Health. 2018;46:40.

5. Ogbo FA, Eastwood J, Page A, Efe-Aluta O, Anago-Amanze C, Kadiri EA, et al. The impact of sociodemographic and health-service factors on breast-feeding in sub-Saharan African countries with high diarrhoea mortality. Public Health Nutr. 2017;20(17):3109-19.

Reviewer #1

Comments to the Author

The manuscript is technically sound. The authors have employed sound study design and methodology to investigate well-defined exposures and outcomes. The sample size was large enough and the data analysis techniques was robust and rigorous. I believe the authors have made all the data underlying the findings although some files could not be opened probably due to poor internet connection at which I was located during the review. The entire presentation of the manuscript followed a logical sequence with near perfect use of English. However, I have the following suggestions for the authors to consider

Response:

Thank you for the comment. The reviewer’s specific comments are addressed below in this rebuttal.

Background: Line 34, ‘are the leading causes of’ not ‘are the leading cause of’ are grammatically more correct

Response:

Revision done (line 34).

Conclusion: It would better to conclude by stating that recommended best practices for preventing ARI and diarrhea diseases in infants and young children namely; the early initiation of breastfeeding, exclusive breastfeeding and avoidance of bottle feeding should be institutionalized and scale up in Ethiopia as part of implementation science approach to cover the know-do-gaps.

Response:

Thank you, and the suggestion is now reflected in the revised manuscript (Page 3)

It would be nice to begin the methods section with brief descriptions of the study designs and settings, although some mentions of Ethiopian settings were made under the introduction

Response:

We appreciate the comment. However, it is challenging to describe the study design, especially that our analyses were based on secondary data. The information on data sources to let potential readers know of the study design used in the surveys is provided in the methods section (Page 6-7).

In response to the reviewer comment on the study setting, we incorporated this text in the revised manuscript (Page 07, Paragraph 02)

EIBF is better defined as ‘commencement of breastfeeding within 1 hour of birth’ as opposed to ‘infants breastfed or put to breast within 1 hour of birth’. While the former indicates something that has started and continued, the later may mean a one-off event that never happen again. I suggest the authors use a phrase that more appropriately described the event. If feasible, commencement of breastfeeding should be replace put to breast in the entire manuscript.

Response:

Point appreciated and now reflected in the entire revised manuscript.

Line 226 – line 254: starting with explanation on RCTs and ending with why PSM approach was used in this study, the entire paragraph may no be necessary for this section. If at all such explanations are needed, some of them should go under study design or more appropriate in the discussion section. I don’t think these detailed descriptions of RCT, use of PSM approach and its advantages is required under data analysis methods. Discussions here should be limited to how the data were analyzed.

Response:

We have revised the text in response to the reviewer comment (page 11 paragraph 02). We note, however, that the description of the PSM is crucial to potential readers who may have limited knowledge of the PSM for a number of reasons:

I. The PSM is often term a ‘pseudo-RCT’ as it tries to emulate the role of randomization in RCTs;

II. For rarely applied analytical strategies, it is recommended to have a brief explanation of the method; and

III. Our description of the PSM is based on previously published studies that applied a similar method. Please see the following references (Gibson et al 2017; Grube et al 2015; Talukder et al 2019).

Additionally, we believe that the description of the PSM (its relevance and application) is essential to potential readers given that it forms a core part of our research question (and subsequent title). The removal or moving the description of the PSM to the discussion section, or somewhere else may, in fact, defeat the purpose for why we used the PSM as readers may have to go elsewhere to find out what PSM is about. Nonetheless, we would like to defer the final decision on this comment to the Editor, especially that the Editor appears to have good knowledge of the PSM.

References:

1. Gibson LA, Hernandez Alava M, Kelly MP, Campbell MJ. The effects of breastfeeding on childhood BMI: a propensity score matching approach. Journal of public health (Oxford, England). 2017;39(4)

2. Grube, M. M., von der Lippe, E., Schlaud, M., & Brettschneider, A.-K. (2015). Does breastfeeding help to reduce the risk of childhood overweight and obesity? A propensity score analysis of data from the KiGGS study. PLoS One, 10(3)

3. Talukder, A., Akter, N., & Sazzad Mallick, T. (2019). Exploring Association Between Individuals' Stature and Type 2 Diabetes Status: Propensity Score Analysis. Environ. Health Insights, 13,

The authors repeatedly described the difference in prevalence of ARI and diarrhea among the exposed and unexposed as significant. However, neither in the narrative nor in table 2 were the associated p-values stated. Rather, would it be safer to modify the narration by removing the word ‘significantly’?

Response:

Revision done in response to the reviewer suggestion (line 332-342)

I am also wondering if it would add value to the interpretation of the odd ratios of developing outcomes comparing the exposed and unexposed if P-values are included in the results narrative or in the corresponding tables. I noticed some of the confidence intervals included 1 which is a neutral effect.

Response:

Revision done (Table 3).

Another weakness to consider is that description of ‘loose or watery stool’ to define diarrhea might not have objectively capture infants who had diarrhea and who had not as such descriptions are too subjective.

Response:

Point appreciated and the text has been revised accordingly (line 536-538)

Reviewer #2

The study is relevant to Ethiopia and other countries with low income status. The topic is particularly relevant to Ethiopia where there is very high prevalence of under-five malnutrition and child mortality. It could provide important insight about the situation of IYCF practices and its association with common childhood illnesses (diarrhea and ARI). The findings of the study could be used to inform planning and policy making exercise in the country and the wider region of sub-Saharan Africa.

Response: Thank you for the comment. The reviewer’s concerns are addressed below.

The article is well but it could benefit from professional language editor.

Response:

We thank the reviewer for the comment and note that the manuscript has been copyedited by co-authors whose first language is English.

Abstract

Page 2, line 46. • The authors wrote “…..exclusively breastfed had a lower prevalence of ARI.” I think using the word incidence is a better than prevalence.

Response:

We would like to clarify to the reviewer that:

1. Prevalence measures the presence of a disease, a condition or a risk factor such as smoking in a particular population over a given time period and is defined as the proportion of a population who have (or had) a specific attribute in a given time period (Rothman et al, 2008)

Common types of prevalence

The types of prevalence are dependent on the timeframe for the estimate:

• Point prevalence refers to the proportion of a population that has the disease at a specific time.

• Period prevalence refers to the proportion of a population that has the attribute at any point over a period of interest.

• Lifetime prevalence refers to the proportion of a population who at some point in life up to the time of assessment has ever had the disease or attribute.

2. Incidence is a measure of the likelihood of new cases of disease or injury in a population within a specified period of time, that is;

Incidence has two main types:

• Incidence proportion (IP): Incidence proportion is the proportion of an initially disease-free population that develops the disease within a specified period of time.

• Incidence rate (IR): The incidence rate is a measure of incidence that incorporates time directly into the denominator.

In the present study, ARI was measured as “the occurrence of cough accompanied by short and rapid breathing during the two weeks’ period preceding the survey” in accordance with Measure DHS reports, which did not separately categorize new cases from old cases within the 2-weeks interval. Similarly, diarrhoea was defined as the passage of three or more loose or liquid stools per day during the two weeks’ period preceding the survey, consistent with Measure DHS. This information was noted in the original manuscript, Page 07, Paragraph 02. Epidemiologically, we believe that ‘period’ prevalence is the correct measure as it accounts for both new and old cases of ARI and diarrhoea that would have occurred in the two prior to the surveys.

Reference

1. Kenneth J. Rothman, Sander Greenland, Timothy L. Lash. Chapter 3 - Measures of Occurrence. Modern epidemiology, . 3rd edition ed2008.

Too many abbreviations in the abstract. It is better to minimize the abbreviations.

Response:

Revision done (page 2–3)

Introduction

The introduction clearly illustrates the problem of ARI and diarrhea; the magnitude and consequence of inappropriate infant and young child feeding (IYCF) in low income settings. However, the rationale for the study is not clearly stated. I think the authors need to strengthen the rationale for the study. A number of studies have tried to answer this research question, the authors need to elaborate the research gaps addressed by the study. Overall, I feel that it could be shortened with more emphasis on the rational of the study.

Response:

We appreciate the reviewer comment and note that the introduction section has been substantially edited in response to the Editor comment above (Page 4-6)

The authors need to include at least recent Ethiopian studies addressing similar research questions using the same dataset (Ethiopian Demographic and Health Survey EDHS). For instance, Nigatu D, et al 2019 assess effect of exclusive breastfeeding cessation on diarrhea and ARI (using EDHS 2011 and 2016) and Amsalu ET, 2019 also assess determinants of ARI ( using EDHS 2016).

Response:

Studies now included in the revised manuscript as requested by the reviewer (Page 05 and page 09)

Methods

Page 8-9, Possible confounders Immunization status of a child could be one of the predictors of ARI and diarrhea, but the authors did not consider it. Since, information on child immunization is available in EDHS data, could you explain why it is excluded?

Response: Thank you for the comment and observation. We have incorporated the variable (ever use of vaccine) as a potential confounder in the entire manuscript, including the analyses, results and discussion as appropriate.

Page 10, line 218-19 The authors wrote “The initial analysis involved the tabulation of frequencies and percentages of ARI and diarrhoea by each study variable.” What does “each study variable” refers to? Only exposures?

Response:

The reviewer has eyes for details – thank you for the observation! Revision done now (page 10 paragraph 03)

Page 10, line 226. I do not see the relevance of mentioning RCT as a gold standard method. Rather, it could be more relevant to discuss the advantage of PSM over commonly used multivariable model for this data.

Response:

As noted above, the exposition of PSM approach is essential to potential readers; nonetheless, we have revised the text in response to the reviewer comment (page 11 paragraph 02).

Here is our response to Reviewer #1 on this comment: We note, however, that the description of the PSM is crucial to potential readers who may have limited knowledge of the PSM for a number of reasons:

IV. The PSM is often term a ‘pseudo-RCT’ as it tries to emulate the role of randomization in RCTs;

V. For rarely applied analytical strategies, it is recommended to have a brief explanation of the method; and

VI. Our description of the PSM is based on previously published studies that applied a similar method. Please see the following references (Gibson et al 2017; Grube et al 2015; Talukder et al 2019).

Additionally, we believe that the description of the PSM (its relevance and application) is essential to potential readers given that it forms a core part of our research question (and subsequent title). The removal or moving the description of the PSM to the discussion section, or somewhere else may, in fact, defeat the purpose for why we used the PSM as readers may have to go elsewhere to find out what PSM is about. Nonetheless, we would like to defer the final decision on this comment to the Editor, especially that the Editor appears to have good knowledge of the PSM.

References:

1. Gibson LA, Hernandez Alava M, Kelly MP, Campbell MJ. The effects of breastfeeding on childhood BMI: a propensity score matching approach. Journal of public health (Oxford, England). 2017;39(4)

2. Grube, M. M., von der Lippe, E., Schlaud, M., & Brettschneider, A.-K. (2015). Does breastfeeding help to reduce the risk of childhood overweight and obesity? A propensity score analysis of data from the KiGGS study. PLoS One, 10(3)

3. Talukder, A., Akter, N., & Sazzad Mallick, T. (2019). Exploring Association Between Individuals' Stature and Type 2 Diabetes Status: Propensity Score Analysis. Environ. Health Insights, 13

The four surveys conducted in different time points (from 2000 to 2016). Are these data fairly similar to be combined, even if no interaction of survey year and… In fact, the authors stated that infant mortality decreased from 97 in the year 2000 to 43 per 1000 in 2019.

Response:

We thank the reviewer for the comment. We also think that the reviewer may have good knowledge about the DHS, which are standardised data, collected every 5 years in many low- and middle-income countries. To answer the reviewer question, Yes, the data are relatively similar despite being collected over varied time points. We note that the first and senior authors have both published over 25 articles in international journals using the DHS data in time and space [e.g., Ahmed et al. 2019a and 2019b, Ogbo et al., 2016, 2017, and 2018]. Our reference to the reduction in infant mortality is to highlight the main issues relating to a possibly lack of key IYCF measures that may be used to further reduce under 5 mortalities in Ethiopia.

References

1. Ahmed, K. Y., Page, A., Arora, A., & Ogbo, F. A. (2019). Trends and determinants of early initiation of breastfeeding and exclusive breastfeeding in Ethiopia from 2000 to 2016. Int Breastfeed J, 14(1), 40.

2. Ahmed, K. Y., Page, A., Arora, A., & Ogbo, F. A. (2019). Trends and factors associated with complementary feeding practices in Ethiopia from 2005 to 2016. Matern. Child Nutr., e12926.

3. Ogbo, F. A., Agho, K., Ogeleka, P., Woolfenden, S., Page, A., & Eastwood, J. (2017). Infant feeding practices and diarrhoea in sub-Saharan African countries with high diarrhoea mortality. PLoS One, 12(2), e0171792.

4. Ogbo, F. A., Nguyen, H., Naz, S., Agho, K. E., & Page, A. (2018). The association between infant and young child feeding practices and diarrhoea in Tanzanian children. Trop. Med. Health, 46, 2.

5. Ogbo, F. A., Page, A., Idoko, J., Claudio, F., & Agho, K. E. (2016). Diarrhoea and suboptimal feeding practices in Nigeria: Evidence from the national household surveys. Paediatr. Perinat. Epidemiol., 30(4), 346-355.

How was missing data handled? You may state the EDHS procedures to handle missing data.

Response:

Thank you. In the analysis, we checked for missingness at random (MAR), but none was evident in the data. This information has been noted in the revised manuscript (line 245-246).

I am not an expert in PSM technique and I suggest an expert in the field should review the appropriateness of the analytic procedures followed.

Response:

As noted above, we have some reasons to believe that the Academic Editor has good knowledge of PSM and note that our PSM approach was appropriately conducted, consistent with past studies (Marinovich et al, 2018, Grube et al., 2015, and Talukder et al., 2019).

References:

1. Marinovich M, Regan A, Gissler M, Magnus MC, Håberg S, Padula A, et al. Developing evidence-based recommendations for optimal interpregnancy intervals in high-income countries: Protocol for an international cohort study. BMJ Open. 2018;9.

2. Grube, M. M., von der Lippe, E., Schlaud, M., & Brettschneider, A.-K. (2015). Does breastfeeding help to reduce the risk of childhood overweight and obesity? A propensity score analysis of data from the KiGGS study. PLoS One, 10(3), e0122534-e0122534.

3. Talukder, A., Akter, N., & Sazzad Mallick, T. (2019). Exploring Association Between Individuals' Stature and Type 2 Diabetes Status: Propensity Score Analysis. Environ. Health Insights, 13, 1178630219836975.

Result

• The authors should mention the sub-samples of mother-infant pairs included for each exposure.

Response:

Revision done (Table 2)

Although the overall sample is large. Some exposures seems to have limited power. For instance in table 2. Distribution of ARI over the exposure “continued breastfeeding at 2 years”, one of the cells have only 48 children (weighted). Could you also say something about adequacy power?.

Response:

We agree the reviewer that some of the exposures have small sample sizes, and this is due to the short age interval used for the definitions of those indicators. The small sample size may account for the large effect sizes and the wide CIs, particularly with the continued breastfeeding at 2-years.

It would be more informative if you present (as a supplemental table) SDC of sub-samples

used for analysis and the trend in IYCF and the outcomes over time.

Response:

The subsamples for the exposure have been included in the revised Table 2. We agree with the reviewer that the examination of trends of the exposure variables is a crucial information but it is beyond the scope of the present research question and subsequent analyses. Notably, information relating to trends on the exposures have been published elsewhere by the authors (Kedir et al., 2019a and 2019b).

References

1. Ahmed, K. Y., Page, A., Arora, A., & Ogbo, F. A. (2019). Trends and determinants of early initiation of breastfeeding and exclusive breastfeeding in Ethiopia from 2000 to 2016. Int Breastfeed J, 14(1), 40. doi:10.1186/s13006-019-0234-9

2. Ahmed, K. Y., Page, A., Arora, A., & Ogbo, F. A. (2019). Trends and factors associated with complementary feeding practices in Ethiopia from 2005 to 2016. Matern. Child Nutr., e12926. doi:10.1111/mcn.12926

Discussion

In general the discussion address important points but I feel that it can be made more coherent and short.

Response:

We thank the reviewer for the comment and note that the discussion section of the manuscript is organized, robust and tailored to the exposure-outcome relationship, especially that some of the observed associations are contrary to some findings in the literature. We offered relevant explanations for all key IYCF indicators. Notably, in page 21, the delineation of the varying relationship between predominant breastfeeding and diarrhoea demonstrate our understanding of the topic and implications. We also note that past studies on the topic have been published by the authors (Ogbo et al 206, 2017 and 2018).

Reference

1. Ogbo, F. A., Agho, K., Ogeleka, P., Woolfenden, S., Page, A., & Eastwood, J. (2017). Infant feeding practices and diarrhoea in sub-Saharan African countries with high diarrhoea mortality. PLoS One, 12(2), e0171792.

2. Ogbo, F. A., Nguyen, H., Naz, S., Agho, K. E., & Page, A. (2018). The association between infant and young child feeding practices and diarrhoea in Tanzanian children. Trop. Med. Health, 46, 2.

3. Ogbo, F. A., Page, A., Idoko, J., Claudio, F., & Agho, K. E. (2016). Diarrhoea and suboptimal feeding practices in Nigeria: Evidence from the national household surveys. Paediatr. Perinat. Epidemiol., 30(4), 346-355.

The authors need to have a more robust discussion on the possible limitations of the study. For instance, misclassification bias could be a source of bias because ARI and diarrhea are not diagnosed by clinicians. It is based on mothers recall. For instance, common cold could be confused with ARI. Besides, it might be challenging for the mother to differentiate between normal bowel habits of children from diarrhea, specifically mild form of diarrhea.

Response:

This information was noted in the original manuscript but has been clarified in the revised manuscript (page 26–27).

Reviewer #3

This is an important, interesting and well-written manuscript. I have only minor comments.

Response:

Thank you for the comment. The reviewer’s concerns are addressed below.

Introduction

It would be useful, if possible, to have information about the percentage of children vaccinated in Ethiopia.

Response:

Done (page 5 paragraph 02)

Line 103: Could it also be due to the replacement of human milk by complementary foods/drinks?

Response:

Revision done (101–102).

Line 119-120: The EBF of 59.9%; - which age/age-group? It would be useful to add information on continued breastfeeding until 2 y and the percentage never breastfed. Also, it would be useful to know whether/how the socioeconomic factors are associated with the IYCF indicators in this population.

Response:

We appreciate the reviewer comment. However, we are constrained by the word limit to fully incorporate additional information relating to continued breastfeeding until 2 years and the percentage of never breastfed as noted by the Academic Editor and Reviewer # 2. We note that information relating to the determinants of breastfeeding and complementary feeding has been published elsewhere by the authors (Ahmed et al, 2019a and 2019b)

References

1. Ahmed, K. Y., Page, A., Arora, A., & Ogbo, F. A. (2019). Trends and determinants of early initiation of breastfeeding and exclusive breastfeeding in Ethiopia from 2000 to 2016. Int Breastfeed J, 14(1), 40. doi:10.1186/s13006-019-0234-9

2. Ahmed, K. Y., Page, A., Arora, A., & Ogbo, F. A. (2019). Trends and factors associated with complementary feeding practices in Ethiopia from 2005 to 2016. Matern. Child Nutr., e12926. doi:10.1111/mcn.12926

Methods

As this reviewer has not conducted analysis using the propensity score matching approach, my understanding of the method is limited. Therefore, it was useful for me to have an explanation of this method under methods, but I do not know whether this is of general interest. I recommend that a statistician consider this and review the statistical methods.

Response:

As noted above, we have some reasons to believe that the Academic Editor has good knowledge of PSM and note that our PSM approach was appropriately conducted, consistent with past studies (Marinovich et al, 2018).

References:

1. Marinovich M, Regan A, Gissler M, Magnus MC, Håberg S, Padula A, et al. Developing evidence-based recommendations for optimal interpregnancy intervals in high-income countries: Protocol for an international cohort study. BMJ Open. 2018;9.

2. Grube, M. M., von der Lippe, E., Schlaud, M., & Brettschneider, A.-K. (2015). Does breastfeeding help to reduce the risk of childhood overweight and obesity? A propensity score analysis of data from the KiGGS study. PLoS One, 10(3), e0122534-e0122534.

3. Talukder, A., Akter, N., & Sazzad Mallick, T. (2019). Exploring Association Between Individuals' Stature and Type 2 Diabetes Status: Propensity Score Analysis. Environ. Health Insights, 13, 1178630219836975.

Results

-Under “results” it would be useful to have an overview of sample sizes, so it is easier to understand the different «n`s» in e.g. table 2 and 3.

Response:

The information relating to the sample sizes has been incorporated in Table 2 in the revised manuscript.

In general, it would be useful to mention/describe the reference groups in more detail. Were the reference groups mixed groups, e.g. in line 311: Those who were «not predominantly breastfed», what were they fed, were some not breastfed?

Response:

Information relating to the reference groups for each IYCF indicator is now noted in the definitions for assessing IYCF according to the WHO. In relation to the predominant breastfeeding mentioned, infants aged 0–5 months were feed with is now noted in the definition, that is, breast milk, including milk expressed or from a wet nurse, and other fluids such as water and juice (Page 08–09).

Table 1. Is it necessary to include «Region of residence» in the table?

Response:

Yes, it was necessary to include residence based on past studies (Ahmed et al 2019a and 2019b) The justification is noted in the original manuscript (line 186–187):

References

1. Ahmed, K. Y., Page, A., Arora, A., & Ogbo, F. A. (2019). Trends and determinants of early initiation of breastfeeding and exclusive breastfeeding in Ethiopia from 2000 to 2016. Int Breastfeed J, 14(1), 40. doi:10.1186/s13006-019-0234-9

2. Ahmed, K. Y., Page, A., Arora, A., & Ogbo, F. A. (2019). Trends and factors associated with complementary feeding practices in Ethiopia from 2005 to 2016. Matern. Child Nutr., e12926. doi:10.1111/mcn.12926

Line 297-299: Should findings be reported in «the same direction»?

Response:

The text has been edited in the revised manuscript (Line 327–329)

The accuracy of the definition of diarrhoea as the passage of three of more liquid stools should be discussed, as it is normal with at least 3 or more liquid stools per day in exclusively breastfed infants during the first months (1). How this may have affected the findings should be discussed.

Response:

Point appreciated, and now reflected in the limitation section of the discussion in the revised manuscript (Page 26, Paragraph 02):

Is it possible to compare the «effect size» on EIBF and EBF on ARI and diarrhoea with other studies in similar contexts?

Response:

Response: Yes, it is possible to compare the effect sizes of EIBF and EBF and ARI and diarrhoea with other studies in similar contexts. However, we are constrained with words as we draw on Reviewer # 2 comment which indicated that the original discussion may be too lengthy. Additionally, we believe that our discussion of the results is focus and provides explanations for why there may varied results from the analyses, consistent with reporting of epidemiological studies. The comparison of effect sizes of EIBF and EBF and ARI and diarrhoea with other studies in similar contexts may be as an another research question that we can explore in a meta-analysis of observational studies in the future. Thank you for the suggestions.

In the discussion it is mentioned that reverse causation cannot be excluded as an interpretation of the findings. It is improbable that this can explain the findings of EIBF and ARI/ diarrhoea, although it is relevant for EBF. (It would be interesting to know whether there are studies on how the occurrence of ARI and diarrhoea influence breastfeeding in

various contexts, does it lead to intensified breastfeeding or more supplementation of water-based drinks?)

Response:

We agree with reviewer that reverse causation cannot be excluded as an interpretation of the findings. However, our search of the literature did not find any studies to support our claim. Accordingly, we have revised the text (Page 26, paragraph 02).

We thank the reviewers for the valuable comments and time in reading our manuscript.

We look forward to your final discussion in due course. Please contact me should you require any further information.

Sincerely,

Kedir Yimam Ahmed, MPH

The Corresponding author

Ahmed, K. Y., Page, A., Arora, A., & Ogbo, F. A. (2019). Trends and determinants of early initiation of breastfeeding and exclusive breastfeeding in Ethiopia from 2000 to 2016. Int Breastfeed J, 14(1), 40. doi:10.1186/s13006-019-0234-9

Ahmed, K. Y., Page, A., Arora, A., & Ogbo, F. A. (2019). Trends and factors associated with complementary feeding practices in Ethiopia from 2005 to 2016. Matern. Child Nutr., e12926. doi:10.1111/mcn.12926

Croft, Trevor, N., Aileen, M. J. M., Courtney, K. A., & et al. (2018). Guide to DHS Statistics: DHS-7. Rockville, Maryland, USA Retrieved from https://dhsprogram.com/pubs/pdf/DHSG1/Guide_to_DHS_Statistics_DHS-7.pdf

Gibson, L. A., Hernandez Alava, M., Kelly, M. P., & Campbell, M. J. (2017). The effects of breastfeeding on childhood BMI: a propensity score matching approach. Journal of public health (Oxford, England), 39(4), e152-e160. doi:10.1093/pubmed/fdw093

Grube, M. M., von der Lippe, E., Schlaud, M., & Brettschneider, A.-K. (2015). Does breastfeeding help to reduce the risk of childhood overweight and obesity? A propensity score analysis of data from the KiGGS study. PLoS One, 10(3), e0122534-e0122534. doi:10.1371/journal.pone.0122534

Ogbo, F. A., Agho, K., Ogeleka, P., Woolfenden, S., Page, A., & Eastwood, J. (2017). Infant feeding practices and diarrhoea in sub-Saharan African countries with high diarrhoea mortality. PLoS One, 12(2), e0171792. doi:10.1371/journal.pone.0171792

Ogbo, F. A., Nguyen, H., Naz, S., Agho, K. E., & Page, A. (2018). The association between infant and young child feeding practices and diarrhoea in Tanzanian children. Trop. Med. Health, 46, 2. doi:10.1186/s41182-018-0084-y

Ogbo, F. A., Page, A., Idoko, J., Claudio, F., & Agho, K. E. (2016). Diarrhoea and suboptimal feeding practices in Nigeria: Evidence from the national household surveys. Paediatr. Perinat. Epidemiol., 30(4), 346-355. doi:10.1111/ppe.12293

Talukder, A., Akter, N., & Sazzad Mallick, T. (2019). Exploring Association Between Individuals' Stature and Type 2 Diabetes Status: Propensity Score Analysis. Environ. Health Insights, 13, 1178630219836975. doi:10.1177/1178630219836975

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13 Mar 2020

Associations between infant and young child feeding practices and acute respiratory infection and diarrhoea in Ethiopia: A propensity score matching approach

PONE-D-19-33411R1

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17 Mar 2020

PONE-D-19-33411R1

Associations between infant and young child feeding practices and acute respiratory infection and diarrhoea in Ethiopia: A propensity score matching approach

Dear Dr. Ahmed:

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