Measurement of explanatory variables
| Variables | Description |
| Age of mother (in year) | Using child’s line no in household and mother’s line no—age of the mother was grouped into 15–19 years, 20–24 years, 25–29 years, 30–34 years, 35–39 years, 40–44 years, 45–49 years. |
| Age of father (in year) | Using child’s line no in household and father’s line no- age of father was grouped into less and equal to 19 years, 20–24 years, 25–29 years, 30–34 years, 35–39 years, 40–44 years, 45–49 years, 50–54 years, more than and equal to 55 years. |
| Age of child (in month) | Age of children was grouped into less than 6 months, 6–10 months, 12–23 months, 24–35 months, 36–47 months, 48–59 months. |
| Sex of child | Sex of children was categorised into male–female. |
| Place of residence | Place of residence was categorised into rural and urban. |
| Division (Province) | The divisional residence of the respondents were categorised into: Barisal, Chittagong, Dhaka, Khulna, Rajshahi, Rangpur, Sylhet. |
| Wealth index | Campsite score of household possession using principal component analysis and was categorised into quintiles; poorest: q1- poorer: q2- middle: q3- richer: q4; and richest: q5. |
| Father education | Father education was categorised into no education; primary (up to grade 5)—secondary (up to grade 10)—higher (grade 11 or above). |
| Father occupation | Profession of the father of the child was categorised into five composite categories· Land owner, farmer, agriculture workers, fishermen, poultry raising, cattle raising were grouped into Agriculture· Similarly, unskilled and semiskilled worker (rickshaw driver, brick breaking, domestic servant, factory worker, carpenter, mason, transport workers), professional work (doctor, lawyer, dentist, accountant, other employed), businessmen (big businessman, small business/trader), other (unemployed/ student, retired, others) were composite categories made. |
| Mother education | Mother education was categorised into no education; primary (up to grade 5)—secondary (up to grade 10)—higher (grade 11 or above). |
| Mother occupation | Using child’s line no in household and mother’s line no- mother occupation was grouped into: currently working and not working. |
| Child malnutrition status | Stunted categorised into Severe if height/age SD was less than—300; moderate if height/age SD was between −300 and −201; well-nourished if height/age SD was above −200. Similarly, wasted-underweight categorised into severe-to-moderate and well nourished. |
| Health professional/worker | This composite variable was created form the frequency of prescribing drug by a qualified doctor or nurse/midwife/ paramedics or family welfare visitor or community skilled birth attendants or medical assistant or community healthcare provider or health assistant· This variable was coded into yes-no. |
| Unqualified/ traditional practitioner | Unqualified/ traditional practitioner was a composite variable and compilation of the variables such as drug prescribed by family welfare assistant—NGO worker—trained traditional birth attendant- untrained traditional birth attendant-unqualified doctor–drug seller—homoeopathic doctor—other· This composite variable was grouped into yes-no. |
| Public sector | Public sector as a source of antibiotics was also a composite variable and created by compiling the following variables: district hospital-Mother and Child Welfare Centre (MCWC)-Upazila Health Complxes (UHC) and Union Health and Family Welfare Centres (UHFWCs) UH and FWC-Expanded Program on Immunization (EPI) outreach-Family Welfare Assistant (FWA)· It was grouped into yes-no. |
| Private sector | A composite variable was created to express the private sector as the source of Antibiotic by considering the following variables: private hospital/clinic-qualified doctor—other private—pharmacy-unqualified doctor-shop· It was coded into yes- no. |
| NGO sector | The variables used to express the NGO sector as a source of Antibiotic were NGO static clinic-NGO satellite clinic-NGO depot holder-NGO field worker-another NGO sector· It was also coded into yes-no. |
| Other | Another source of antibiotics was dummy variables with categories yes and no. |
NGO, non-governmental organisation.