A cross-sectional survey was conducted among mothers of children under 6 years old in Greater Jakarta from 7 to 10 May 2019.
Mothers who were 16 years old or older and living in Greater Jakarta were recruited through a local web survey agency. No exclusion criteria were set as long as participants meet all inclusion criteria. The web-based survey was purposefully chosen to examine an association between overweight and the MCH handbook as an information source among mothers who have access to internet. Because smartphone possession rate is higher [9 ] and more child overweight exists in urban than rural area, [13 (link), 16 , 17 (link)] Greater Jakarta was selected as study site. It is known that child overweight in Indonesia is more prevalent in families containing mothers with higher economic level, [14 (link), 17 (link), 20 (link)] and a higher level of education, [11 (link), 13 (link), 17 (link), 19 ] and the participants in the web-based survey were expected to have these characteristics. The target number of participants, 180 mothers, was determined according to sample size calculation and budgetary consideration. An invitation was sent to all mobile panels (30,851 eligible panels out of 963,197 panels as of 2018) who registered to the web survey agency. The first page of the survey contained information, describing the study and asking for their voluntary participation. All participants provided informed consent by reading and responding. Ethics Committee, Faculty of Health Science Technology & Graduate School of Health Care Science, Bunkyo Gakuin University permitted this research (#2018-0034).
In a structured questionnaire, mothers were asked to provide the following information: mother’s sociodemographic information, child’s age, sex, weight (kg), height (cm), hours of watching television, ownership of the MCH handbook, and nutrition practice. Mother’s sociodemographic data included mother’s age, education level, employment type, and household monthly income. Sources of information about child nutrition were collected through multiple choice answers regarding use of the MCH handbook, internet via mobile phone, internet via computer, books or magazines, family members, friends, health professionals, and other sources. Sources of anthropometric data were not identified in the questionnaire.
The World Health Organization 2006 Growth Standard was applied to classify child nutrition status. Child overweight was defined as a weight for height z-score > 2 standard deviations (SD), child stunting was defined as a height/length for age z-score < − 2 SD, child wasting was defined as a weight for height z-score < 2 SD, and child underweight was defined as a weight for age z-score < − 2 SD [22 ].
Descriptive analysis was performed to present the prevalence of overweight, stunting, underweight, wasting, and normal (not malnourished) as well as the distribution of each variable. Because the analysis was based on the child, a mother’s data were used twice if they provided information about more than one child. Sources of information for child nutrition were also described in percentages (%). The Odds Ratio [OR] and 95% Confidential Interval [CI] for the association of factors related to overweight and each nutrition status were estimated using bivariate and multivariate logistic regression analysis. Appropriate cut-off values were applied to create binary variables for all items. The Statistical Package for Social Science (SPSS) software version 28.0 (IBM, Armonk, NY, USA) as used to perform statistical analysis.
Mothers who were 16 years old or older and living in Greater Jakarta were recruited through a local web survey agency. No exclusion criteria were set as long as participants meet all inclusion criteria. The web-based survey was purposefully chosen to examine an association between overweight and the MCH handbook as an information source among mothers who have access to internet. Because smartphone possession rate is higher [9 ] and more child overweight exists in urban than rural area, [13 (link), 16 , 17 (link)] Greater Jakarta was selected as study site. It is known that child overweight in Indonesia is more prevalent in families containing mothers with higher economic level, [14 (link), 17 (link), 20 (link)] and a higher level of education, [11 (link), 13 (link), 17 (link), 19 ] and the participants in the web-based survey were expected to have these characteristics. The target number of participants, 180 mothers, was determined according to sample size calculation and budgetary consideration. An invitation was sent to all mobile panels (30,851 eligible panels out of 963,197 panels as of 2018) who registered to the web survey agency. The first page of the survey contained information, describing the study and asking for their voluntary participation. All participants provided informed consent by reading and responding. Ethics Committee, Faculty of Health Science Technology & Graduate School of Health Care Science, Bunkyo Gakuin University permitted this research (#2018-0034).
In a structured questionnaire, mothers were asked to provide the following information: mother’s sociodemographic information, child’s age, sex, weight (kg), height (cm), hours of watching television, ownership of the MCH handbook, and nutrition practice. Mother’s sociodemographic data included mother’s age, education level, employment type, and household monthly income. Sources of information about child nutrition were collected through multiple choice answers regarding use of the MCH handbook, internet via mobile phone, internet via computer, books or magazines, family members, friends, health professionals, and other sources. Sources of anthropometric data were not identified in the questionnaire.
The World Health Organization 2006 Growth Standard was applied to classify child nutrition status. Child overweight was defined as a weight for height z-score > 2 standard deviations (SD), child stunting was defined as a height/length for age z-score < − 2 SD, child wasting was defined as a weight for height z-score < 2 SD, and child underweight was defined as a weight for age z-score < − 2 SD [22 ].
Descriptive analysis was performed to present the prevalence of overweight, stunting, underweight, wasting, and normal (not malnourished) as well as the distribution of each variable. Because the analysis was based on the child, a mother’s data were used twice if they provided information about more than one child. Sources of information for child nutrition were also described in percentages (%). The Odds Ratio [OR] and 95% Confidential Interval [CI] for the association of factors related to overweight and each nutrition status were estimated using bivariate and multivariate logistic regression analysis. Appropriate cut-off values were applied to create binary variables for all items. The Statistical Package for Social Science (SPSS) software version 28.0 (IBM, Armonk, NY, USA) as used to perform statistical analysis.
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