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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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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:Child 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.We 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 ?2 statistic and multiple logistic regression (MLR) based on maximum likelihood estimate.Using the MLR, for neonatal mortality, diarrhea showed the highest positive coefficient (??=?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 (??=?0.744; P?<?0.001), while father's education was negative correlation (??=?-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 (??=?1.042; P?<?0.010) and (??=?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 (??=?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.In 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.

Project description:IntroductionEarly childhood is a vital part of human life because most of the brain developments occur in this particular period. Early childhood disability is a significant global public health burden, which can negatively impact the children's quality of life and their overall productivity. It is also a major social and economic problem in Bangladesh. Therefore, it is very important to understand the associated factors for early childhood disability, which may help disability prevention, better management and policy formulation. The main objective of this study is to investigate the child, family, and community-level factors associated with early childhood disability in Bangladesh.MethodsA cross sectional nationally representative data was derived from Multiple Indicator Cluster Survey (MICS), 2019. A total of 14,072 Bangladeshi children under five years of age were selected for this study. Various types of statistical analysis (simple, bivariate, multivariable) were performed. To assess the bivariate relationship between chosen categorical variables (independent) and early childhood disability (dependent), a chi-square test was used. The multivariable ordinal logistic regression was used to find out the association of disability with child, family, and community-level factors.ResultsThe results show that 2.0% of the children have at least one disability and 0.8% have more disabilities. Several factors namely not attending in early childhood education [Odds Ratio (OR) = 0.65; 95% confidence interval (CI) = 0.13-1.17 Ρ = 0.01], having mother's functional difficulty (OR = 1.23; 95% (CI) = 0.58-1.88 Ρ <0.001), unhappy mother's life (OR = 0.85; 95% CI = 0.30-1.39 Ρ <0.001), parents without internet access (OR = 0.68; 95% CI = 0.06-1.29 Ρ = 0.03) and parents using mobile phone (OR = 0.52; 95% CI = 0.09-0.95 Ρ = 0.02) were found to be important for early childhood disability in Bangladesh.ConclusionEarly childhood disability is still neglected in Bangladesh and further epidemiological studies are recommended. The findings of this study may help policy makers and relevant stakeholders to develop interventions for reducing the overall burden of early childhood disability.

Project description:BackgroundAlthough in many low- and middle-income countries undernutrition is steadily decreasing, nutritional challenges persist in remote communities, such as those in mountainous areas of Lao PDR. Isolated, with limited access to food and to health care and other public services, local diets are low in both quantity and diversity. Data needed to guide policy and planning are lacking.ObjectivesThe study aimed to identify the extent of malnutrition and associated factors among children aged 12-47 months in remote mountainous communities in Lao PDR.MethodsA cross-sectional survey was conducted in Nong district, Savannakhet province, covering 173 households, involving heads of households, mothers and their children aged 12-47 months.ResultsThe prevalence of undernutrition was very high among the 173 children studied: 72.8% were stunted, 50.3% underweight and 10.4% wasted. Key factors showing significant positive associations with nutritional status were assets (mobile phone or electric rice mill), collection of non-timber forest products, and household dietary diversity. Negative associations were found with experience of malaria and consuming high amounts of white roots and tubers. Immediate causes of malnutrition were prevalent; half the children had insufficient consumption of all micro- and macronutrients. Diseases were highly prevalent; 30% had recently experienced fever. The households in these villages were quite homogeneous. All scored high on causes of malnutrition; 90% of households experienced food insecurity, nearly all lived below the poverty line, and almost two-thirds of household heads and nearly all mothers had had no education.ConclusionThis study identified multiple factors influencing child malnutrition, including low household food diversity, food insecurity, and poor feeding practices among ethnic minority people living in a difficult environment with limited resources. Child undernutrition in these poor communities is complex. Interventions are needed in different sectors, including agricultural production, knowledge on feeding and health services.

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

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

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