scholarly journals Analyzing Infant Mortality in Rural Bangladesh: A Frailty Modeling Approach

2021 ◽  
Vol 69 (2) ◽  
pp. 63-69
Author(s):  
Bikash Pal ◽  
Ahsan Rahman Jaamee
Keyword(s):  
Infant Mortality ◽  
Hierarchical Structure ◽  
Health Survey ◽  
Survival Data ◽  
Frailty Model ◽  
Survival Model ◽  
Demographic And Health Survey ◽  
Rural Bangladesh ◽  
Optimal Estimates ◽  
Parameters Of Interest

In practice, it may happen that data may arise from a hierarchical structure i.e., a cluster is nested within another cluster. In this case, nested frailty model is appropriate to analyze survival data to obtain optimal estimates of the parameters of interest. To identify significant determinants of infant mortality in rural Bangladesh, survival data have been extracted from Bangladesh Demographic and Health Survey (BDHS), 2014. Because of the presence of two-level clustering in data, nested frailty model has been employed for the purpose of analysis. Recommendations have been suggested based on the results obtained from the survival model to reduce the infant mortality in rural Bangladesh to a great extent. Dhaka Univ. J. Sci. 69(2): 63-69, 2021 (July)

Log-Logistic Proportional Odds Model for Analyzing Infant Mortality in Bangladesh

2016 ◽  
Vol 29 (1) ◽  
pp. 60-69
Author(s):  
Most. Fatima-Tuz-Zahura ◽  
Khandoker Akib Mohammad ◽  
Wasimul Bari
Keyword(s):  
Infant Mortality ◽  
Regression Model ◽  
Health Survey ◽  
Maternal Education ◽  
Proportional Odds Model ◽  
Demographic And Health Survey ◽  
Place Of Delivery ◽  
Product Limit ◽  
Parametric Survival ◽  
Relevant Covariates

Log-logistic parametric survival regression model has been used to find out the potential determinants of infant mortality in Bangladesh using the data extracted from Bangladesh Demographic and Health Survey, 2011. First, nonparametric product-limit approach has been used to examine the unadjusted association between infant mortality and covariate of interest. It is found that maternal education, membership of nongovernmental organizations, age of mother at birth, sex of child, size of child at birth, and place of delivery play an important role in reducing the infant mortality, adjusting relevant covariates.

scholarly journals Time to death and its associated factors among infants in sub-Saharan Africa using the recent demographic and health surveys: shared frailty survival analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sofonyas Abebaw Tiruneh ◽  
Ejigu Gebeye Zeleke ◽  
Yaregal Animut
Keyword(s):  
Survival Analysis ◽  
Infant Mortality ◽  
Health Survey ◽  
Associated Factors ◽  
Demographic And Health Survey ◽  
Sub Saharan Africa ◽  
Time To Death ◽  
Live Births ◽  
Shared Frailty ◽  
Sub Saharan

Abstract Background Globally, approximately 4.1 million infants died, accounting for 75% of all under-five deaths. In sub-Saharan Africa (SSA), infant mortality was 52.7/1000 live births in 2018 This study aimed to assess the pooled estimate of infant mortality rate (IMR), time to death, and its associated factors in SSA using the recent demographic and health survey dataset between 2010 and 2018. Methods Data were retrieved from the standard demographic and health survey datasets among 33 SSA countries. A total of 93,765 samples were included. The data were cleaned using Microsoft Excel and STATA software. Data analysis was done using R and STATA software. Parametric shared frailty survival analysis was employed. Statistical significance was declared as a two-side P-value < 0.05. Results The pooled estimate of IMR in SSA was 51 per 1000 live births (95% Confidence Interval (CI): 46.65–55.21). The pooled estimate of the IMR was 53 in Central, 44 in Eastern, 44 in Southern, and 57 in Western Africa per 1000 live births. The cumulative survival probability at the end of 1 year was 56%. Multiple births (Adjusted Hazard ratio (AHR) = 2.68, 95% CI: 2.54–2.82), low birth weight infants (AHR = 1.28, 95% CI: 1.22–1.34), teenage pregnancy (AHR = 1.19, 95 CI: 1.10–1.29), preceding birth interval <  18 months (AHR = 3.27, 95% CI: 3.10–3.45), birth order ≥ four (AHR = 1.14, 95% CI:1.10–1.19), home delivery (AHR = 1.08, 95% CI: 1.04–1.13), and unimproved water source (AHR = 1.07, 95% CI: 1.01–1.13), female sex (AHR = 0.86, 95% CI: 0.83–0.89), immediately breastfeed (AHR = 0.24, 95% CI: 0.23–0.25), and educated mother (AHR = 0.88, 95% CI: 0.82–0. 95) and educated father (AHR = 0.90, 95% CI: 0.85–0.96) were statistically significant factors for infant mortality. Conclusion Significant number of infants died in SSA. The most common cause of infant death is a preventable bio-demographic factor. To reduce infant mortality in the region, policymakers and other stakeholders should pay attention to preventable bio-demographic risk factors, enhance women education and improved water sources.

scholarly journals Factors affecting infant mortality in the general population: evidence from the 2016 Ethiopian demographic and health survey (EDHS); a multilevel analysis

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Adhanom Gebreegziabher Baraki ◽  
Temesgen Yihunie Akalu ◽  
Haileab Fekadu Wolde ◽  
Ayenew Molla Lakew ◽  
Kedir Abdela Gonete
Keyword(s):  
General Population ◽  
Infant Mortality ◽  
Multilevel Analysis ◽  
Health Survey ◽  
Demographic And Health Survey ◽  
Factors Affecting

scholarly journals Spatial Distribution of Infant Mortality in Ethiopia: Using Demographic Health Survey, the Ethiopia

2022 ◽  
Author(s):  
Berhanu Awoke Kefale ◽  
Ashenafi Abate Woya ◽  
Abay Kassa Tekile ◽  
Getasew Mulat Bantie
Keyword(s):  
Spatial Distribution ◽  
Infant Mortality ◽  
Health Survey ◽  
Associated Factors ◽  
Health Care Services ◽  
Hot Spot ◽  
Wealth Index ◽  
Demographic And Health Survey ◽  
P Value ◽  
Birth Size

Abstract Background Mortality is one of the demographic variables that affect population trends. Among mortality of children, Infant mortality contributed to more than 75% of all under-five deaths globally. It disproportionately affects those living in the different regions of countries and within the region. Exploring the spatial distribution and identifying associated factors is important to design effective intervention programs to reduce infant mortality. Thus, this study aimed to assess the spatial distribution and associated factors of infant mortality in Ethiopia using the 2016 Ethiopian Demographic and Health Survey (EDHS). Method The Data this study were used Ethiopian Demographic and Health Survey in 2016. A total of 11,023 live births from the EDHS data were included in the analysis. Spatial analysis was done to explore spatial distribution of infant mortality using ArcGIS version 10.4. Results This study revealed that the spatial distribution of infant mortality was non-random in the country with Moran’s index 0.1546 (P-value=0.0185). The Afar and Somali regions of Ethiopia were identified in this study on the hot spot of infant mortality. Conclusions The spatial distribution of infant mortality varies across the country. ANC usage, sex of a child, birth interval, birth size, birth type, birth order, wealth index, residence, region, and the spatial variable (Si) were significant predictors of infant mortality. Therefore, it needs interventions in the hot spot areas. Focusing on maternal health care services, rural residences, multiple births, infants having a smaller birth size, and male infants deserves special attention.

Trends in and determinants of neonatal and infant mortality in Nigeria based on Demographic and Health Survey data

2020 ◽  
pp. 1-11
Author(s):  
Kamalesh Kumar Patel ◽  
Jang Bahadur Prasad ◽  
Rajeshwari A. Biradar
Keyword(s):  
Infant Mortality ◽  
Health Survey ◽  
Mortality Rates ◽  
Demographic And Health Survey ◽  
Infant Mortality Rate ◽  
North West ◽  
Infant Deaths ◽  
Live Births ◽  
The North ◽  
West Region

Abstract This study aimed to assess the changes in neonatal and infant mortality rates in Nigeria over the period 1990 to 2018 using Nigerian Demographic and Health Survey (NDHS) data, and assess their socio-demographic determinants using data from the most recent survey conducted in 2018. The infant mortality rate was 87 per 1000 live births in 1990, and this increased to 100 per 1000 live births in 2003 – an increase of around 15% over 13 years. Neonatal and infant mortality rates started to decline steadily thereafter and continued to do so until 2013. After 2013, neonatal morality rose slightly by the year 2018. Information for 27,465 infants under 1 year of age from the NDHS-2018 was analysed using bivariate and multivariate analysis and the Cox proportional hazard technique. In 2018, infant deaths decreased as wealth increased, and the incidence of infant deaths was greater among those of Islam religion than among those of other religions. A negative association was found between infant deaths and the size of a child at birth. Infant mortality was higher in rural than in urban areas, and was higher among male than female children. Both neonatal and infant death rates varied by region and were found to be highest in the North West region and lowest in the South region. An increasing trend was observed in neonatal mortality in the 5-year period from 2013 to 2018. Policy interventions should be focused on the poor classes, women with a birth interval of less than 2 years and those living in the North West region of the country.

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