This study was performed within the ongoing Mal-ED (Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health) study [4]. The Mal-ED study (icddr,b protocol # 2008-020) was approved by the Research Review Committee and the Ethical Review Committee of icddr,b in 2008. For participation in this study, written informed consent was obtained from the guardians of each participating child. With case-control design, the study was conducted among residents of an under-privileged urban community in Bauniabadh slum in Mirpur, Dhaka, Bangladesh [5]. Cases were stunted children length-for-age z-score (LAZ) < -2 of the median of a WHO standard aged 6 to 24 months. Controls were well-nourished children aged 6 to 24 months with LAZ > -1.

FRAs also interviewed the mothers using a pretested, structured questionnaire. Information collected from the interviews included: age and sex of child, colostrum and breastfeeding practices, mother’s age at first pregnancy, parental education, family size, information about drinking water and latrine, and monthly family income. Household food security was evaluated using Household Food Insecurity Access Scale (HFIAS) generic questions [6], and was categorized as per HFIAS’s guideline [6].

Data were entered into Microsoft Office Access and exported to STATA 13 for analysis. Dual data entry method was used to minimize data entry error. Bivariate analysis was done for all explanatory variables to identify those associated with children stunting. Only significant variables in the bivariate analysis were included in logistic regression model. Odds ratios (95% confidence intervals) were calculated to identify the factors associated with stunting, and P-value <0.05 was considered statistically significant.

Total 689 children (389 cases and 300 controls) participated in this case control study. In bivariate analysis, we found significant association of stunting with child’s age, maternal undernutrition and education, household head’s education, treatment of drinking water, sharing toilet, monthly family income, food insecurity, and hand washing habits (Table I). No association was found with child’s gender, breastfeeding and complementary feeding practice, mother’s age at first pregnancy, family size, and morbidity (Table I).

TABLE I Socio-demographic Characteristics, Nutritional Practice and Hands Washing Habits of Study Population

Logistic regression analysis revealed that the risk factors for stunting were child’s age >12 to 17 months (AOR 3.13, 95% CI: 2.08, 4.70) and 18 to 24 months (AOR 4.21, 95% CI:2.69, 6.61); mother’s BMI <18.5 (AOR 3.55, 95% CI: 2.34, 5.38); mother’s education <5 years (AOR1.53, 95% CI: 1.04, 2.23); consumption of untreated drinking water (AOR 1.51, 95% CI: 1.03, 2.21); and monthly family income <100 USD (AOR=1.98, 95% CI: 1.38, 2.84) (Fig. 1).

Fig. 1 Adjusted odds ratios for risk factors significantly associated with stunting.

This study aimed to identify the factors associated with stunting among children aged 6 to 24 months. Logistic regression analysis identified that the factors significantly associated with stunting were: (i) more than 12 months of child’s age, ii) mother’s undernutrition (BMI <18.5), iii) mother’s education less than 5 years, iv) consumption of untreated drinking water, and v) monthly family income less than 100 USD.

Limitation of the study is that there may be some recall bias related to previous history recorded from mothers. Another limitation is the data for this study emerged from only one slum of Bangladesh.

Svefors, et al. [7] and Chowdhury, et al. [8] also found that age group >12-24 months was a risk factor of stunting. A recent study from Tanzania [9] also found maternal under-nutrition as a risk factor. Less educated mother as a risk factor of stunting is also echoed by other studies [9-11]. Educational level of mother is vital because educated mothers can better access the health services, usually provide better care, have better hygienic practices, and also have higher status in the family. The effect of maternal factors on infant outcomes has been described earlier [12]. We found that untreated drinking water was another risk factor of stunting, and the study by Chirande, et al. [9], from Tanzania also found unsafe sources of drinking　water　as a risk factor of stunting.

The effect of income on stunting, as observed in our study, can be explained by its importance in the purchase of food and consumer goods that promote and protect the health of children. It is also known that better economic conditions increase the living standard of the families, which allow them to take essential care of the children. The previous study from our group showed similar findings as stunted children more often had short-statured, malnourished and illiterate/less educated mothers, and were more often from lowest quintile of asset index [13].

The findings of this study reiterate the role of maternal nutritional status and education, quality of drinking water and family income as important contextual factors of childhood stunting. Our study recommends that to reduce the under-five stunting rate in the slums, targeted programs should be developed to improve maternal nutrition and education, drinking water and family income.

Acknowledgements: This research study was funded by the Bill & Melinda Gates Foundation; the Foundation for the NIH; the National Institutes of Health and Fogarty International Center funded the MAL-ED project, and the core donors who provide unrestricted support to icddr,b for its operations and research. Current donors providing unrestricted support include: Government of the People’s Republic of Bangladesh; the Department of Foreign Affairs, Trade and Development (DFATD), Canada; Swedish International Development Cooperation Agency (SIDA) and the Department for International Development (UK Aid). We gratefully acknowledge these donors for their support and commitment to icddr,b’s research efforts.

Contributors: MAA, MM, MMI, DM, AMSA, RH, TA, MIH: concept of study and data collection;. MAA, MM, TA, MIH: data entry, cleaning and analysis.. All authors are responsible for writing and revision of the draft.

Funding: Bill & Melinda Gates Foundation, and icddr, b. Competing interest: None stated.