Individual and community level determinants of

Ebola-related stigma exists and undermines efforts towards re-integrating survivors. Abstract Rationale Although Ebola-related stigmatization continues to undermine efforts to re-integrate survivors, few studies have examined what influences such stigmatizing attitudes. Objective This paper explores the effects of both individual- and community-level factors on Ebola-related stigma in Ghana. Methods Data were collected from a cross-section of respondents, nested within 40 communities in the Greater Accra Region of Ghana.

Individual and community level determinants of

This article has been cited Individual and community level determinants of other articles in PMC. Abstract Background Neonatal mortality is a global challenge; identification of individual and community determinants associated with it are important for targeted interventions.

However in most low and middle income countries LMICs including Ghana this problem has not been adequately investigated as the impact of contextual factors remains undetermined despite their significant influence on under-five mortality and morbidity. Methods Based on a modified conceptual framework for child survival, hierarchical modelling was deployed to examine about 6, women, aged 15 — 49 years level 1nested within communities level 2 in Ghana by analysing combined data of the and Ghana Demographic and Health Survey.

The aim was to identify individual maternal, paternal, neonatal, antenatal, delivery and postnatal and community socioeconomic disadvantage communities determinants associated with neonatal mortality. Results The results showed both individual and community characteristics to be associated with neonatal mortality.

Infants of multiple-gestation [OR 5. Similarly, infants of grand multiparous mothers [OR 2. Dwelling in a neighbourhood with high socioeconomic deprivation was associated with increased neonatal mortality [OR 3.

Individual and community determinants of neonatal mortality in Ghana: a multilevel analysis

Conclusion Both individual and community characteristics show a marked impact on neonatal survival. Implementation of community-based interventions addressing basic education, poverty alleviation, women empowerment and infrastructural development and an increased focus on the continuum-of-care approach in healthcare service will improve neonatal survival.

Neonatal mortality, Individual factors, Community factors, Multilevel analysis, Ghana Background The first 28 days of life remain the most critical period for an infant to survive during childhood; [ 1 ] approximately 10, newborns die everyday during this period [ 2 ].

As a result of the devastating effects of childhood mortality especially in low and middle income countries LMICsUnited Nations member states unanimously agreed to adopt reduction of under-five mortality by two-thirds between and as the Millennium Development Goal 4 MDG 4 [ 3 ].

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The deadline for the attainment of MDG 4 target is fast approaching. Consequently, in the last two decades, neonatal mortality has shown limited decline globally and in Sub-Saharan Africa SSA [ 19 ]. Low birth weight, prematurity, infections, birth asphyxia and birth trauma have been identified as the leading causes of neonatal deaths worldwide [ 4 ], similar to the major causes of neonatal deaths in SSA [ 11 ] and Ghana [ 12 - 15 ].

Across the globe, there are great variations in neonatal mortality: This indicates a gross lack of information and knowledge of neonatal mortality in LMICs.

In Ghana, neonatal mortality is an important public health issue; 30 per live births are dying within the first 28 days of life [ 16 ]. In order to attain MDG 4 neonatal mortality has to reduce substantially because it accounts for more than half of the infant and under-five mortality [ 16 ].

Most studies to date mainly examined factors influencing under-five and infant mortality in LMICs [ 17 ], whereas only a limited number of studies have specifically identified factors associated with neonatal mortality in SSA.

Early initiation of breastfeeding was shown to be inversely associated with neonatal mortality in Ghana [ 18 ]. Further in LMICs, neonatal low birth weight, male infant, multiple pregnancy and prematurity [ 19 - 21 ], maternal single, nulliparous mothers and short birth spacing [ 19 - 21 ], and health service factors delivery and postnatal services were reported to have independent associations with neonatal mortality [ 1920 ].

These studies focused on the associations between individual-level factors and neonatal mortality. They typically did not disentangle the influence of individual and community determinants on neonatal mortality even when they analysed population-based data with hierarchical nature.

In other words, most of these prior studies disregarded the importance of contextual phenomena because community-level determinants were not appropriately considered in their analyses. Contextual phenomenon is an intuitive core notion of social epidemiology; resting on the observation that people dwelling in the same neighbourhood tend to resemble each other in terms of their health outcomes more than those living in different areas.

In LMICs, neonatal mortality is yet to be adequately examined by multilevel analysis, an analytic method that has the capability of assessing both fixed and random effects in a single model.

Application of multilevel analysis allows to disentangle the influence of individual and community characteristics on neonatal survival based on the level at which they shaped child survival. In contrast, the application of single-level analyses individual or ecological analyses instead of multilevel analyses will make it difficult to deduce whether community-level factors influence neonatal outcomes regardless of the individual characteristics or whether inter-community variation in neonatal mortality is exclusively due to their individual characteristics without any influence of community-level factors.

In addition, there is increasing evidence of associations between community-level factors and under-five stunting and mortality after considering individual factors [ 22 - 24 ].

The present study aims to identify both individual biological or proximate and community contextual, societal or distal factors associated with neonatal mortality in Ghana by examining Ghana Demographic and Health Survey GDHS data using hierarchical modelling. Methods Study design This is a population-based study which examined the combined dataset of the and Ghana Demographic and Health Survey to identify individual and community determinants influencing neonatal mortality in Ghana.

Data collection Comprehensive information on the sampling techniques and procedures applied for data collection in the Ghana Demographic and Health Survey have been published elsewhere [ 1625 ].

The questionnaires covered information on socioeconomic, demographic and health indicators. Informed consent was obtained from all the participants before face-to-face interviews were conducted.

Information was obtained on under-five deaths in the last five years in both occasions. Variables Outcome variable Neonatal mortality was defined during the data collection as the probability of dying within the first month of life. Determinants Individual and community characteristics that were examined for possible associations with neonatal mortality were based on an adapted framework of child survival [ 26 ] taking into account the available information in the and Ghana Demographic and Health Survey.On Individual and Community-Level Determinants of Pertussis Incidence and Vaccination A Thesis Submitted to the Faculty of Drexel University by.

community level factors which is an indicative of a need for further research on community level factors.

Individual and community level determinants of

Hence, utilizing multilevel modeling in determining the effect . Fixed effects of model 2 show the associations between neonatal mortality and individual-level determinants when the community-level covariates were not considered while the fixed effects of model 3 show the associations between neonatal mortality and both individual and community-level determinants.

Sep 28,  · The level 1 model represents the relationships among the individual level variables and the outcome variable while the level 2 model examines the influence of community level factors on the outcome variable. RESEARCH ARTICLE Open Access Individual and community level determinants of childhood full immunization in Ethiopia: a multilevel analysis Samir A.

Abadura1*, Wondwosen T.

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Lerebo2, Usha Kulkarni2 and Zeleke A. Mekonnen3 Abstract. An ecological approach focuses on both individual-level and population-level determinants of health and interventions.

About Determinants of Health The range of personal, social, economic, and environmental factors that influence health status are known as determinants of health.

WHO | The determinants of health