Prevalence and Determinants of Prone Sleeping Position in Infants: Results from Two Cross-Sectional Studies on Risk Factors for SIDS in Germany

Background: the clustering of metabolic syndrome (MetS) risk factors is becoming more prevalent in children, leading to the development of type 2 diabetes (T2D) and cardiovascular diseases in early adulthood. The impact of MetS risk factors on cardiac autonomic modulation (CAM) or vice versa has been noted to track from childhood to pre-adolescence and adolescence. Understating associations in this age group may help to improve the clinical outcomes of the MetS, even when MetS symptoms are not visible. Potential damage from each individual MetS component and the ability to predict early cardiac damage or upcoming cardiovascular events is very important. Therefore, the present systematic review and meta-analysis investigated the associations between CAM and MetS risk factors individually to verify which of the MetS risk components were significantly correlated with heart rate variability (HRV) indices before or at the onset of the MetS among young people. The purpose of this review was to outline the importance of potentially screening HRV indices in young people even with only one MetS risk factor, as a pre-indicator for early cardiovascular risk stratification. Methods: cross-sectional studies that examined the relationship of MetS risk factors with HRV indices were searched using four databases including PubMed, the Cochrane clinical trials library, Medline and the Web of Science. Correlation coefficients with 95% confidence intervals (95% CI), and random effects meta-analyses of the association between MetS risk factors with HRV indices were performed. Results: out of 14 cross-sectional studies and one case-control study, 8 studies (10 data sets) provided association data for the meta-analysis. Our results indicated significant positive correlations for systolic blood pressure (SBP) (correlation coefficient 0.13 (95%CI: 0.06; 0.19), I2 = 47.26%) and diastolic blood pressure (DBP) (correlation coefficient 0.09 (95%CI: −0.01; 0.18), I2 = 0%) with a Low Frequency/High Frequency ratio (LF/HF). Significant negative correlations for waist circumference (WC) (correlation coefficient −0.12 (95%CI: −0.19; −0.04), I2 = 51.50%), Triglycerides (TGs) (correlation coefficient −0.09 (95%CI: −0.15; −0.02), I2 = 0%) and ≥2 MetS risk factors (correlation coefficient −0.10 (95%CI: −0.16; −0.03), I2 = 0%); with high frequency (HF) were revealed. Significant positive correlations for high density lipoprotein (HDL) (correlation coefficient 0.08 (95%CI: 0.05; 0.11), I2 = 0%) and significant negative correlations of ≥2 MetS risk (correlation coefficient −0.04 (95%CI: −0.12; 0.03), I2 = 0.0%) with low frequency (LF) were revealed. Significant negative correlations for TGs (correlation coefficient −0.09 (95%CI: −0.23; 0.05), I2 = 2.01%) with a mean square root of the sum of differences between mean time between two successive intervals (rMSSD) and significant positive correlation of HDL (correlation coefficient 0.09 (95%CI: −0.01; 0.19), I2 = 0.33%) with standard deviation of the time between two successive intervals (SDNN) were also revealed. An Egger’s test indicated that there was no obvious publication bias for any of the above relationships except for TGs and rMSSD. The significance level stipulated for the meta-analysis was p < 0.05. Conclusions: lipid profiles (HDL and TGs), WC and BP were associated with CAM in young people up to the age of 19 years. The use of HRV indices to predict future MetS risk, and relationships with individual risk factors including HDL, BP, WC and TGs, were established. Future studies related to young people (up to the age of 19 years) are recommended to explore the associations reported here further.

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An Assessment of the Impact of Public Health Activities to Reduce the Prevalence of the Prone Sleeping Position During Infancy: The Tasmanian Cohort Study

Preventive Medicine ◽

10.1006/pmed.1994.1055 ◽

1994 ◽

Vol 23 (3) ◽

pp. 402-408 ◽

Cited By ~ 18

Author(s):

A.L. Ponsonby ◽

T. Dwyer ◽

S.V. Kasl ◽

J.A. Cochrane ◽

N.M. Newman

Keyword(s):

Public Health ◽

Cohort Study ◽

Sleeping Position ◽

Prone Sleeping Position ◽

Prone Sleeping ◽

The Impact

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A meta-analysis of cross-sectional studies on the frequency and risk factors associated with canine morbillivirus infection in China

Microbial Pathogenesis ◽

10.1016/j.micpath.2021.105258 ◽

2021 ◽

pp. 105258

Author(s):

Bo Dong ◽

Xiaodong Zhang ◽

Jincong Wang ◽

Gaoqiang Zhang ◽

Chengyu Li ◽

...

Keyword(s):

Risk Factors ◽

Meta Analysis ◽

Cross Sectional ◽

Factors Associated ◽

Cross Sectional Studies

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Associated factors vs risk factors in cross-sectional studies

Patient Preference and Adherence ◽

10.2147/ppa.s98023 ◽

2015 ◽

pp. 1635 ◽

Cited By ~ 2

Author(s):

David Antay-Bedregal ◽

Evelyn Camargo-Revello ◽

German F. Alvarado

Keyword(s):

Risk Factors ◽

Associated Factors ◽

Cross Sectional ◽

Cross Sectional Studies

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Sudden Unexpected Death of Two Infants in Baby Carriers

Klinische Pädiatrie ◽

10.1055/a-1545-4590 ◽

2021 ◽

Author(s):

Dennis Storz ◽

Christof Dame ◽

Anke Wendt ◽

Alexander Gratopp ◽

Christoph Bührer

Keyword(s):

Risk Factors ◽

Infant Development ◽

Sudden Infant Death ◽

Developed Countries ◽

Bottle Feeding ◽

Sudden Unexpected Death ◽

Sudden Infant ◽

Unexpected Death ◽

Sleeping Position ◽

Prone Sleeping Position

Sudden unexpected death in infancy (SUDI), previously termed sudden infant death syndrome (SIDS), is the second leading cause of death in infants beyond the neonatal period in Germany, and a major cause of infant mortality in economically well developed countries (OECD Health Statistics, 2019). The risk of SUDI peaks at the age of 2–4 months and then decreases continuously till the end of the first year. A complex multifactorial cause, rather than a single characteristic factor, may cause SUDI within a critical period of infant development (Guntheroth WG et al., Pediatrics 2002; 110: e64–e64). Risk factors include prematurity, male gender, bottle-feeding, prone sleeping position, overheating, as well as exposure to smoke amongst others (Carpenter RG et al., Lancet 2004; 363: 185–191). Thus, health professionals consistently advise and educate parents about avoidable risk factors of SUDI at routine well-baby examinations. Since the advent of SUDI prevention strategies in the 1980s, the incidence has decreased 10fold, from 1,55/1.000 live births in 1991 to 0,15/1000 in 2015. This number seems to have reached a steady state (Statistisches Bundesamt Germany, 2015).

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Cot death and prone sleeping position.

BMJ ◽

10.1136/bmj.298.6686.1518-c ◽

1989 ◽

Vol 298 (6686) ◽

pp. 1518-1519 ◽

Cited By ~ 1

Keyword(s):

Sleeping Position ◽

Cot Death ◽

Prone Sleeping Position ◽

Prone Sleeping

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Risk factors associated with premature myocardial infarction: a systematic review protocol

BMJ Open ◽

10.1136/bmjopen-2018-023647 ◽

2019 ◽

Vol 9 (2) ◽

pp. e023647

Author(s):

Sagar B Dugani ◽

Ana Patricia Ayala Melendez ◽

Roger Reka ◽

Yousif M Hydoub ◽

Shannon N McCafferty ◽

...

Keyword(s):

Risk Factors ◽

Myocardial Infarction ◽

Systematic Review ◽

Selection Criteria ◽

Case Control ◽

Cross Sectional ◽

Factors Associated ◽

Primary Screening ◽

Premature Myocardial Infarction ◽

Cross Sectional Studies

IntroductionPremature myocardial infarction (MI) generally refers to MI in men ≤55 years or women ≤65 years. Premature MI is a major contributor to cardiovascular disease (CVD), which claimed 17.6 million lives globally in 2016. Reducing premature MI and CVD is a key priority for all nations; however, there is sparse synthesis of information on risk factors associated with premature MI. To address this knowledge gap, we are conducting a systematic review to describe the association between risk factors (demographics, lifestyle factors and biomarkers) and premature MI.Methods and analysisThe following databases were searched from inception to June 2018: CENTRAL, CINAHL, Clinical Trials, EMBASE and MEDLINE. We will include original research articles (case–control, cohort and cross-sectional studies) that report a quantitative relationship between at least one risk factor and premature MI. Two investigators will use predetermined selection criteria and independently screen articles based on title and abstract (primary screening). Articles that meet selection criteria will undergo full-text screening based on criteria used for primary screening (secondary screening). Data will be extracted using predetermined data extraction forms. The Newcastle-Ottawa Scale for case–control and cohort studies will be used to evaluate the risk of bias and will be adapted for cross-sectional studies. Whenever feasible, data will be summarised into a random-effects meta-analysis.Ethics and disseminationTo our knowledge, this will be the first study to synthesise results on the relationship between risk factors and premature MI. These findings will inform healthcare providers on factors associated with risk of premature MI and potentially improve primary prevention efforts by guiding development of interventions. These findings will be summarised and presented at conferences and through publication in a peer-reviewed journal.PROSPERO registration numberCRD42018076862.

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Different outcomes for different interventions with different focus!— A cross-country comparison of community interventions in rural Swedish and US populations

Scandinavian Journal of Public Health ◽

10.1177/14034948010290021801 ◽

2001 ◽

Vol 29 (56_suppl) ◽

pp. 46-58 ◽

Cited By ~ 1

Author(s):

L. Weinehall ◽

C. Lewis ◽

A.N. Nafziger ◽

P.L. Jenkins ◽

T.A. Erb ◽

...

Keyword(s):

Risk Factors ◽

New York ◽

Risk Reduction ◽

New York State ◽

Reference Population ◽

Cvd Risk ◽

Cross Sectional ◽

York State ◽

The Us ◽

Cross Sectional Studies

Objectives: There is a need among healthcare providers to acquire more knowledge about small-scale and low budget community intervention programmes. This paper compares risk factor outcomes in Swedish and US intervention programmes for the prevention of cardiovascular disease (CVD). The aim was to explore how different intervention programme profiles affect outcome. Methods: Using a quasi-experimental design, trends in risk factors and estimated CVD risk in two intervention areas (Norsjö, Sweden and Otsego- Schoharie County, New York state) are compared with those in reference areas (Northern Sweden region and Herkimer County, New York state) using serial cross-sectional studies and panel studies. Results: The programmes were able to achieve significant changes in CVD risk factors that the local communities recognized as major concerns: changing eating habits in the Swedish population and reducing smoking in the US population. For the Swedish cross-sectional follow-up study cholesterol reduction was 12%, compared to 5% in the reference population ( p for trend differences < 0.000) . The significantly higher estimated CVD risk (as assessed by risk scores) at baseline in the intervention population was below that of the Swedish reference population after 5 years of intervention. The Swedish panel study provided the same results. In the US, both the serial cross-sectional and panel studies showed a >10% decline in smoking prevalence in the intervention population, while it increased slightly in the reference population. When pooling the serial cross-sectional studies the estimated risk reduction (using the Framingham risk equation) was significantly greater in the intervention populations compared to the reference populations. Conclusions: The overall pattern of risk reduction is consistent and suggests that the two different models of rural county intervention can contribute to significant risk reduction. The Swedish programme had its greatest effect on reduction of serum cholesterol levels whereas the US programme had its greatest effect on smoking prevention and cessation. These outcomes are consistent with programmatic emphases. Socially less privileged groups in these rural areas benefited as much or more from the interventions as those with greater social resources.

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