Socioeconomic Inequalities in pediatric Metabolic Syndrome: mediation by parental health literacy

Abstract Background Parental health literacy may explain the relationship between parental socioeconomic status (SES) and pediatric metabolic syndrome (MetS). For this reason, we assessed to what extent parental health literacy mediates the relationships between parental SES and pediatric MetS. Methods We used data from the prospective multigenerational Dutch Lifelines Cohort Study. Our sample consisted of 6,683 children with an average follow-up of 36.2 months (SD 9.3) and a mean baseline age of 12.8 years (SD 2.6). We used natural effects models to assess the natural direct, natural indirect, and total effects of parental SES on MetS. Results On average, an additional four years of parental education, e.g. university instead of secondary school, would lead to cMetS scores that were 0.499 (95% confidence interval (CI) 0.364; 0.635) units lower, which is a small effect (d 0.18). If parental income and occupational level were one standard deviation higher, on average cMetS scores were 0.136 (95%CI 0.052; 0.219) and 0.196 (95%CI 0.108; 0.284) units lower, respectively; these are both small effects (d 0.05 and 0.07, respectively). Parental health literacy partially mediated these pathways; it accounted for 6.7% (education), 11.8% (income), and 8.3% (occupation) of the total effect of parental SES on pediatric MetS. Conclusions Socioeconomic differences in pediatric MetS are relatively small, the largest being by parental education. Improving parental health literacy may reduce these inequalities. Further research is needed into the mediating role of parental health literacy on other socioeconomic health inequalities in children. Key messages • Parental socioeconomic status (SES) has a small inverse relationship with pediatric metabolic syndrome (MetS), which is partially mediated by parental health literacy. • Targeting parental health literacy may reduce inequalities in pediatric MetS. It may also influence other pediatric socioeconomic health inequalities, but further research is needed.


Background:
In May 2020, considering gradual restoration of all economical activities the Government of Pakistan updated containment strategy from locking down the whole country to locking down high-risk areas to mitigate COVID-19 spread. All districts having !300 cases/100,000 population. COVID-19 case incidence and test positivity rates by real-time RT-PCR before and after zonal lockdown were compared to assess whether the locality-based lockdowns can be used as an alternative to country lockdown to contain COVID-19 spread. Methods: Smart lockdowns were implemented in ten localities in the Islamabad Capital Territory (ICT), having a population of 60,000 from 12 May 2020 to June 3, 2020. Movements were restricted. Entry and exit points were guarded by police. Any person with symptoms of fever, cough, or sore throat tested by real-time RT-PCR methods and reported within 24 hours of collection. To compare the rate of active cases and positivity rate by weeks, we performed a z-test for two proportions and set p < 0.05 as the level of significance.

Results:
The red zone had 60,000 persons in 2.00 square kilometers. The rate of active COVID-19 cases significantly decreased (p < 0.0001) during intervention from 300/100,000 population pre-containment time to 22/100,000 population after the first three weeks of lockdown. The COVID-19 positivity rate also decreased significantly (p < 0.0001) from 24% (24/78) precontainment to 5.3% during containment. A total of 3800 people were tested in the following three weeks of intervention and 26 cases were detected.

Conclusions:
The smart lockdowns approach reduced COVID-19 transmission in the ICT district. This type of intervention was Background: Parental health literacy may explain the relationship between parental socioeconomic status (SES) and pediatric metabolic syndrome (MetS). For this reason, we assessed to what extent parental health literacy mediates the relationships between parental SES and pediatric MetS.

Methods:
We used data from the prospective multigenerational Dutch Lifelines Cohort Study. Our sample consisted of 6,683 children with an average follow-up of 36.2 months (SD 9.3) and a mean baseline age of 12.8 years (SD 2.6). We used natural effects models to assess the natural direct, natural indirect, and total effects of parental SES on MetS.
15th European Public Health Conference 2022

Results:
On average, an additional four years of parental education, e.g. university instead of secondary school, would lead to cMetS scores that were 0.499 (95% confidence interval (CI) 0.364; 0.635) units lower, which is a small effect (d 0.18). If parental income and occupational level were one standard deviation higher, on average cMetS scores were 0.136 (95%CI 0.052; 0.219) and 0.196 (95%CI 0.108; 0.284) units lower, respectively; these are both small effects (d 0.05 and 0.07, respectively). Parental health literacy partially mediated these pathways; it accounted for 6.7% (education), 11.8% (income), and 8.3% (occupation) of the total effect of parental SES on pediatric MetS. Conclusions: Socioeconomic differences in pediatric MetS are relatively small, the largest being by parental education. Improving parental health literacy may reduce these inequalities. Further research is needed into the mediating role of parental health literacy on other socioeconomic health inequalities in children.

Key messages:
Parental socioeconomic status (SES) has a small inverse relationship with pediatric metabolic syndrome (MetS), which is partially mediated by parental health literacy. Targeting parental health literacy may reduce inequalities in pediatric MetS. It may also influence other pediatric socioeconomic health inequalities, but further research is needed.

Abstract citation ID: ckac131.192
The impact of the SARS-CoV-2 pandemic on causespecific-mortality: a systematic literature review

Background:
Although investigating the patterns of COVID-19 excess mortality (EM) is relevant, understanding the effects of the pandemic on cause-specific mortality is even crucial and should also be assessed, as this metric allows for a more detailed analysis of the true impact of the pandemic. The aim of this systematic literature review is to estimate the impact of the pandemic on different causes of death, providing a quantitative and qualitative analysis of the phenomenon.

Methods:
We searched MEDLINE to identify studies that reported causespecific mortality during the COVID-19 pandemic. We adopted several inclusion criteria: original article; assessed at least one cause-specific mortality during the pandemic; assessed causes of deaths using the ICD-10 classification; reporting of at least one of the following outcomes: causespecific mortality estimates or cause-specific EM; full-length articles. Several relevant data were extracted (e.g. publication year, data stratification, territory, country income level, allcause EM, and cause-specific mortality, etc.).

Results:
The search identified 548 articles. After title, abstract and fulltext screening, we extracted relevant data from the final set of 14 articles. Cause-specific mortality was reported using different units of measurement. Only 9 studies reported the statistical significance and/or confidence intervals. The most frequently analyzed causes of death were cardiovascular diseases (n = 11), cancer (n = 7), diabetes (n = 6), and suicide (n = 5). We found very heterogeneous patterns of causespecific mortality, for all the specific causes of deaths, except for suicide and road accident.

Conclusions:
The impact of the pandemic on cause-specific deaths has been very heterogeneous and the analyses conducted so far are not exhaustive. We advocate for the urgent need to find a consensus to define uniform methodological approaches to establish the true burden of the COVID-19 pandemic on non-COVID-19 mortality.

Key messages:
We reviewed the body of literature to estimate the impact of the COVID-19 pandemic on different causes of death, and to provide a quantitative and qualitative analysis of the phenomenon. We did not identify unique patterns of cause-specific mortality due to too varied approaches in terms of disease classification and coding, and methodologies used for estimating mortality.