Improving child nutrition for sustainable poverty reduction in Africa

"While famines and other episodes of severe hunger receive significant press coverage and attract much public attention, chronic hunger and malnutrition are considerably more prevalent in Africa. It is estimated that 14 percent of children are born with low birthweights every year, around 45 million preschool children are malnourished, and 192 million Africans of all ages are hungry.... This brief argues that failing to give adequate attention to child nutrition issues is shortsighted if African governments seek sustainable reductions in poverty. In poorly nourished populations, reductions in hunger and improvements in nutrition provide considerable productivity gains and save resources that can then be used for other pressing investments. It is the existence of these sizeable gains together with the availability of cost-effective interventions that underlies the economic case for improving child nutrition in Africa." from Text

Child nutrition, child health, and school enrollment : a longitudinal analysis

Better health and nutrition are thought to improve children's performance in school, and therefore their productivity after school. Most literature ignores the fact that child health and schooling reflect behavioral choices, so the estimated impact of health and nutrition on a child's schooling reflects biases in the studies. Using an explicit dynamic model for preferred estimates, the authors use longitudinal data to investigate how children's health and nutrition affect school enrollment in rural Pakistan. They use price shocks when children were of preschool age to control for behavior determining the measure of children's health and nutrition stock. The authors find that children's health and nutrition is three times more important for enrollment than is suggested by"naive estimates"that assume that children's health and nutrition is predetermined rather that determined by household choices. Not only does improved nutrition increase enrollments, it does so more for girls, thus closing a portion of the gender gap. These results strongly reinforce the importance of using estimation methods that are consistent with the economic theory of households to explore the impact of some choice variables on others, using socioeconomic behavioral data. Private behaviors and public policies that affect the health and nutrition of children have much greater effect on school enrollment and on eventual productivity than suggested by early literature methods.Teaching and Learning,Health Monitoring&Evaluation,Primary Education,Early Child and Children's Health,Public Health Promotion,Science Education,Scientific Research&Science Parks,Economic Theory&Research,Primary Education,Health Monitoring&Evaluation

Attrition in longitudinal household survey data

Longitudinal household data can have considerable advantages over much more widely used cross-sectional data. The collection of longitudinal data, however, may be difficult and expensive. One problem that has concerned many analysts is that sample attrition may make the interpretation of estimates problematic. Such attrition may be particularly severe in areas where there is considerable mobility because of migration between rural and urban areas. Many analysts share the intuition that attrition is likely to be selective on characteristics such as schooling and that high attrition is likely to bias estimates made from longitudinal data. This paper considers the extent of and implications of attrition for three longitudinal household surveys from Bolivia, Kenya, and South Africa that report very high per-year attrition rates between survey rounds. Our estimates indicate that (1) the means for a number of critical outcome and family background variables differ significantly between attritors and nonattritors; (2) a number of family background variables are significant predictors of attrition; but (3) nevertheless, the coefficient estimates for “standard” family background variables in regressions and probit equations for the majority of the outcome variables considered in all three data sets are not affected significantly by attrition. Therefore, attrition apparently is not a general problem for obtaining consistent estimates of the coefficients of interest for most of these outcomes. These results, which are very similar to results for developed economies, suggest that for these outcome variables—despite suggestions of systematic attrition from univariate comparisons between attritors and nonattritors, multivariate estimates of behavioral relations of interest may not be biased due to attrition.Household surveys Methodology ,

Attrition in longitudinal household survey data

Longitudinal household data can have considerable advantages over much more widely used cross-sectional data. The collection of longitudinal data, however, may be difficult and expensive. One problem that has concerned many analysts is that sample attrition may make the interpretation of estimates problematic. Such attrition may be particularly severe in areas where there is considerable mobility because of migration between rural and urban areas. Many analysts share the intuition that attrition is likely to be selective on characteristics such as schooling and that high attrition is likely to bias estimates made from longitudinal data. This paper considers the extent of and implications of attrition for three longitudinal household surveys from Bolivia, Kenya, and South Africa that report very high per-year attrition rates between survey rounds. Our estimates indicate that (1) the means for a number of critical outcome and family background variables differ significantly between attritors and nonattritors; (2) a number of family background variables are significant predictors of attrition; but (3) nevertheless, the coefficient estimates for “standard” family background variables in regressions and probit equations for the majority of the outcome variables considered in all three data sets are not affected significantly by attrition. Therefore, attrition apparently is not a general problem for obtaining consistent estimates of the coefficients of interest for most of these outcomes. These results, which are very similar to results for developed economies, suggest that for these outcome variables—despite suggestions of systematic attrition from univariate comparisons between attritors and nonattritors, multivariate estimates of behavioral relations of interest may not be biased due to attrition.Household surveys Methodology ,

Attrition in longitudinal household survey data - some tests for three developing-country samples

For capturing dynamic demographic relationships, longitudinal household data can have considerable advantages over more widely used cross-sectional data. But because the collection of longitudinal data may be difficult and expensive, analysts must assess the magnitudes of the problems, specific to longitudinal, but not to cross-sectional data. One problem that concerns many analysts is that sample attrition may make the interpretation of estimates problematic. Such attrition may be especially severe where there is considerable migration between rural, and urban areas. And attrition is likely to be selective on such characteristics as schooling, so high attrition is likely to bias estimates. The authors consider the extent, and implications of attrition for three longitudinal household surveys from Bolivia, Kenya, and South Africa that report very high annual attrition rates between survey rounds. Their estimates indicate that: 1) the means for a number of critical outcome, and family background variables differ significantly between those who are lost to follow-up, and those who are re-interviewed. 2) A number of family background variables are significant predictors of attrition. 3) Nevertheless, the coefficient estimates for standard family background variables in regressions, and probit equations for the majority of outcome variables in all three data sets, are not significantly affected by attrition. So attrition is apparently not a general problem for obtaining consistent estimates of the coefficients of interest for most of these outcomes. These results, which are very similar to those for industrial countries, suggest that multivariate estimates of behavioral relations may not be biased because of attrition. This wold support the collection of longitudinal data.Statistical&Mathematical Sciences,Public Health Promotion,Health Monitoring&Evaluation,Scientific Research&Science Parks,Educational Sciences,Science Education,Scientific Research&Science Parks,Health Monitoring&Evaluation,Poverty Assessment,Statistical&Mathematical Sciences

The Role of Personality, Self-Disclosure, and Envy in Maladaptive Social Media Engagement

Through online social networks, individuals establish and maintain social connections to satisfy their need to belong. Recent research suggests that taken too far, one’s need to belong can increase envy and lead to maladaptive social media behavior aligned with obsessive-compulsive disorder. This study examines the role of two personality traits, one’s intrinsic need to belong and trait reactance, on feelings of envy and the self-disclosure processes that lead to obsessive-compulsive disorder on social networks. A sample of 354 U.S. adult users of Facebook completed a survey measuring individuals’ need to belong, trait reactance, envy, self-disclosure, and online social network obsessive-compulsive disorder. Regression analyses reveal that need to belong and trait reactance both independently and interactively relate to envy, and that self-disclosure mediates the relationship between envy and obsessive-compulsive disorder on social networks. Those with low trait reactance appear at the lowest risk of online social network OCD no matter their need to belong. The highest risk profile for online OCD is found in those with both high trait reactance and high need to belong. Overall, our findings support further exploration of one’s intrinsic need to belong and trait reactance as personality indicators of risk for online social network OCD

Investigating the frequency and nature of medication-related problems in the women’s health unit of an Australian tertiary teaching hospital

Background: Despite the large burden medication-related morbidity and mortality places on the Australian health care system, there is little known about the extent of this problem in a women’s health (obstetric and gynecology) setting. Objective: Determine the frequency and nature of medication-related problems (MRPs) occurring in a women’s health unit (WHU) of an Australian teaching hospital. Methods: A prospective audit of consecutive cases of patients treated in the WHU at a tertiary-level teaching hospital was undertaken by a clinical pharmacist over a 5-week period. Data collected included the following: patient characteristics, type of MRP (using a modified version of the Hepler-Strand classification system), medication involved (according to the World Health Organisation Anatomical Therapeutic Chemical classification system), and clinical significance (using a 2-level severity index). Results: A total of 454 potential MRPs were identified over the 5-week period among 241 patients. A total of 39 MRPs (8.6%) identified were deemed to be of moderate/high clinical significance. The highest number of MRPs (221; 49%) was identified among women admitted following a cesarean delivery, with 83 of 85 women in this group experiencing at least 1 MRP. Additional factors associated with an increased likelihood of patients experiencing a MRP included increased age, length of hospital stay, and number of regular medications taken prior to and during admission (P < 0.05). Conclusion: The widespread nature of identified MRPs in this setting suggests that various approaches to minimizing these problems and mitigating the associated burden on the health care system are warranted.Rebecca Thompson, Lisa Whennan, Jasmine Liang, Chris Alderman and Luke E. Grzeskowia