Dataset Information

On exploring and ranking risk factors of child malnutrition in Bangladesh using multiple classification analysis.

ABSTRACT:

Background

Logistic regression analysis is widely used to explore the determinants of child malnutrition status mainly for nominal response variable and non-linear relationship of interval-scale anthropometric measure with nominal-scale predictors. Multiple classification analysis relaxes the linearity assumption and additionally prioritizes the predictors. Main objective of the study is to show how does multiple classification analysis perform like linear and logistic regression analyses for exploring and ranking the determinants of child malnutrition.

Methods

Anthropometric data of under-5 children are extracted from the 2011 Bangladesh Demographic and Health Survey. The analysis is carried out considering several socio-economic, demographic and environmental explanatory variables. The Height-for-age Z-score is used as the anthropometric measure from which malnutrition status (stunting: below -2.0 Z-score) is identified.

Results

The fitted multiple classification analysis models show similar results as linear and logistic models. Children age, birth weight and birth interval; mother's education and nutrition status; household economic status and family size; residential place and regional settings are observed as the significant predictors of both Height-for-age Z-score and stunting. Child, household, and mother level variables have been ranked as the first three significant groups of predictors by multiple classification analysis.

Conclusions

Detecting and ranking the determinants of child malnutrition through Multiple classification analysis might help the policy makers in priority-based decision-making.

Trial registration

"Retrospectively registered".

SUBMITTER: Bhowmik KR

PROVIDER: S-EPMC7050713 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Publications

On exploring and ranking risk factors of child malnutrition in Bangladesh using multiple classification analysis.

Bhowmik Kakoli Rani KR Das Sumonkanti S

BMC nutrition 20170907

<h4>Background</h4>Logistic regression analysis is widely used to explore the determinants of child malnutrition status mainly for nominal response variable and non-linear relationship of interval-scale anthropometric measure with nominal-scale predictors. Multiple classification analysis relaxes the linearity assumption and additionally prioritizes the predictors. Main objective of the study is to show how does multiple classification analysis perform like linear and logistic regression analyse ...[more]

PMID: 32153851

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Project description:ObjectiveThe current study is an attempt to explore under-five child malnutrition in a low-income population setting using the Extended Composite Index of Anthropometric Failure (ECIAF).DesignData from the Bangladesh Demographic and Health Survey 2017-2018 were analysed. Malnutrition using ECIAF was estimated using stunting, wasting underweight and overweight. Multilevel logistic regression models identified factors associated with malnutrition. Geospatial analysis was conducted using R programming.SettingBangladesh.ParticipantsChildren under 5 years of age.ResultsIn Bangladesh, as indicated by the ECIAF, approximately 40·8 % (95 % CI: 39·7, 41·9) of children under five experience malnutrition, whereas about 3·3 % (95 % CI: 2·9, 3·7) were overweight. Children of parents with no formal education (56·3 %, 95 % CI: 50·8, 61·8), underweight mothers (53·4 %, 95 % CI: 50·4, 56·3), belonging to the lowest socio-economic strata (50·6 %, 95 % CI: 48·3, 53·0), residing in rural areas (43·3 %, 95 % CI: 41·9, 44·6) and aged below 3 years (47·7 %, 95 % CI: 45·2, 50·2) demonstrated a greater age- and sex-adjusted prevalence of malnutrition. The Sylhet division (Eastern region) exhibited a higher prevalence of malnutrition (> 55·0 %). Mothers with no formal education (adjusted OR (AOR): 1·51, 95 % CI: 1·08, 2·10), underweight mother (AOR: 1·54, 95 % CI: 1·03, 1·83), poorest socio-economic status (AOR: 2·14, 95 % CI: 1·64, 2·81), children aged 24-35 months (AOR: 2·37, 95 % CI: 1·97, 2·85) and fourth and above birth order children (AOR: 1·41, 95 % CI: 1·16, 1·72) were identified key factors associated with childhood malnutrition while adjusting community- and household-level variations.ConclusionsIn Bangladesh, two out of five children were malnourished, and one in thirty-five children was overweight. Continuous monitoring of the ECIAF over time would facilitate tracking changes in the prevalence of different forms of malnutrition, helping to plan interventions and assess the effectiveness of interventions aimed at addressing both undernutrition and overweight.

Project description:BackgroundChild and neonatal mortality is a serious problem in Bangladesh. The main objective of this study was to determine the most significant socio-economic factors (covariates) between the years 2011 and 2014 that influences on neonatal and child mortality and to further suggest the plausible policy proposals.MethodsWe modeled the neonatal and child mortality as categorical dependent variable (alive vs death of the child) while 16 covariates are used as independent variables using χ2 statistic and multiple logistic regression (MLR) based on maximum likelihood estimate.FindingsUsing the MLR, for neonatal mortality, diarrhea showed the highest positive coefficient (β = 1.130; P < 0.010) leading to most significant covariate for both 2011 and 2014. The corresponding odds ratios were: 0.323 for both the years. The second most significant covariate in 2011 was birth order between 2-6 years (β = 0.744; P < 0.001), while father's education was negative correlation (β = -0.910; P < 0.050). In general, 10 covariates in 2011 and 5 covariates in 2014 were significant, so there was an improvement in socio-economic conditions for neonatal mortality. For child mortality, birth order between 2-6 years and 7 and above years showed the highest positive coefficients (β = 1.042; P < 0.010) and (β = 1.285; P < 0.050) for 2011. The corresponding odds ratios were: 2.835 and 3.614, respectively. Father's education showed the highest coefficient (β = 0.770; P < 0.050) indicating the significant covariate for 2014 and the corresponding odds ratio was 2.160. In general, 6 covariates in 2011 and 4 covariates in 2014 were also significant, so there was also an improvement in socio-economic conditions for child mortality. This study allows policy makers to make appropriate decisions to reduce neonatal and child mortality in Bangladesh.ConclusionsIn 2014, mother's age and father's education were also still significant covariates for child mortality. This study allows policy makers to make appropriate decisions to reduce neonatal and child mortality in Bangladesh.

Project description:(1) Background: Malnutrition is a highly prevalent complication in patients with inflammatory bowel diseases (IBD). It is strongly associated with poor clinical outcomes and quality of life. Screening for malnutrition risk is recommended routinely; however, current malnutrition screening tools do not incorporate IBD specific characteristics and may be less adequate for screening these patients. Therefore, we aimed to identify IBD-related risk factors for development of malnutrition. (2) Methods: A retrospective case-control study among IBD patients attending the IBD clinic of the Tel-Aviv Medical Center for ≥2 consecutive physician consultations per year during 2017-2020. Cases who had normal nutritional status and developed malnutrition between visits were compared to matched controls who maintained normal nutritional status. Detailed information was gathered from medical files, including: demographics, disease phenotype, characteristics and activity, diet altering symptoms and comorbidities, medical and surgical history, annual healthcare utility, nutritional intake and the Malnutrition Universal Screening Tool (MUST) score. Univariate and multivariate analyses were used to identify malnutrition risk factors. The independent risk factors identified were summed up to calculate the IBD malnutrition risk score (IBD-MR). (3) Results: Data of 1596 IBD patients met the initial criteria for the study. Of these, 59 patients developed malnutrition and were defined as cases (n = 59) and matched to controls (n = 59). The interval between the physician consultations was 6.2 ± 3.0 months, during which cases lost 5.3 ± 2.3 kg of body weight and controls gained 0.2 ± 2.3 kg (p < 0.001). Cases and controls did not differ in demographics, disease duration, disease phenotype or medical history. Independent IBD-related malnutrition risk factors were: 18.5 ≤ BMI ≤ 22 kg/m2 (OR = 4.71, 95%CI 1.13-19.54), high annual healthcare utility (OR = 5.67, 95%CI 1.02-31.30) and endoscopic disease activity (OR = 5.49, 95%CI 1.28-23.56). The IBD-MR was positively associated with malnutrition development independently of the MUST score (OR = 7.39, 95%CI 2.60-20.94). Among patients with low MUST scores determined during the index visit, identification of ≥2 IBD-MR factors was strongly associated with malnutrition development (OR = 8.65, 95%CI 2.21-33.82, p = 0.002). (4) Conclusions: We identified IBD-related risk factors for malnutrition, highlighting the need for a disease-specific malnutrition screening tool, which may increase malnutrition risk detection.

Project description:BackgroundThe number of child deaths is a potential indicator to assess the health condition of a country, and represents a major health challenge in Bangladesh. Although the country has performed exceptionally well in decreasing the mortality rate among children under five over the last few decades, mortality still remains relatively high. The main objective of this study is to identify the prevalence and determinants of the risk factors of child mortality in Bangladesh.MethodsThe data were based on a cross-sectional study collected from the Bangladesh Demographic and Health Survey (BDHS), 2011. The women participants numbered 16,025 from seven divisions of Bangladesh - Rajshahi, Dhaka, Chittagong, Barisal, Khulna, Rangpur and Sylhet. The 𝟀2 test and logistic regression model were applied to determine the prevalence and factors associated with child deaths in Bangladesh.ResultsIn 2011, the prevalence of child deaths in Bangladesh for boys and girls was 13.0% and 11.6%, respectively. The results showed that birth interval and birth order were the most important factors associated with child death risks; mothers' education and socioeconomic status were also significant (males and females). The results also indicated that a higher birth order (7 & more) of child (OR=21.421 & 95%CI=16.879-27.186) with a short birth interval ≤ 2 years was more risky for child mortality, and lower birth order with longer birth interval >2 were significantly associated with child deaths. Other risk factors that affected child deaths in Bangladesh included young mothers of less than 25 years (mothers' median age (26-36 years): OR=0.670, 95%CI=0.551-0.815), women without education compared to those with secondary and higher education (OR =0 .711 & .628, 95%CI=0.606-0.833 & 0.437-0.903), mothers who perceived their child body size to be larger than average and small size (OR= 1.525 & 1.068, 95%CI=1.221-1.905 & 0.913-1.249), and mothers who delivered their child by non-caesarean (OR= 1.687, 95%CI=1.253-2.272).ConclusionCommunity-based educational programs or awareness programs are required to reduce the child death in Bangladesh, especially for younger women should be increase the birth interval and decrease the birth order. The government should apply the strategies to enhance the socioeconomic conditions, especially in rural areas, increase the awareness program through media and expand schooling, particularly for girls.

Dataset Information

On exploring and ranking risk factors of child malnutrition in Bangladesh using multiple classification analysis.

Background

Methods

Results

Conclusions

Trial registration

Publications

On exploring and ranking risk factors of child malnutrition in Bangladesh using multiple classification analysis.

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