Using latent class cluster analysis to screen high risk clusters of birth defects between 2009 and 2013 in Northwest China

Screening high-risk population of persistent postpartum hypertension in women with preeclampsia using latent class cluster analysis

BACKGROUND

A significant proportion of women with preeclampsia (PE) exhibit persistent postpartum hypertension (PHTN) at 3 months postpartum associated with cardiovascular morbidity. This study aimed to screen patients with PE to identify the high-risk population with persistent PHTN.

METHODS

This retrospective cohort study enrolled 1,000 PE patients with complete parturient and postpartum blood pressure (BP) profiles at 3 months postpartum. The enrolled patients exhibited new-onset hypertension after 20 weeks of pregnancy, while those with PE superimposed upon chronic hypertension were excluded. Latent class cluster analysis (LCCA), a method of unsupervised learning in machine learning, was performed to ascertain maternal exposure clusters from eight variables and 35 subordinate risk factors. Logistic regression was applied to calculate odds ratios (OR) indicating the association between clusters and PHTN.

RESULTS

The 1,000 participants were classified into three exposure clusters (subpopulations with similar characteristics) according to persistent PHTN development: high-risk cluster (31.2%), medium-risk cluster (36.8%), and low-risk cluster (32.0%). Among the 1,000 PE patients, a total of 134 (13.4%) were diagnosed with persistent PHTN, while the percentages of persistent PHTN were24.68%, 10.05%, and 6.25% in the high-, medium-, and low-risk clusters, respectively. Persistent PHTN in the high-risk cluster was nearly five times higher (OR, 4.915; 95% confidence interval (CI), 2.92-8.27) and three times (OR, 2.931; 95% CI, 1.91-4.49) than in the low- and medium-risk clusters, respectively. Persistent PHTN did not differ between the medium- and low-risk clusters. Subjects in the high-risk cluster were older and showed higher BP, poorer prenatal organ function, more adverse pregnancy events, and greater medication requirement than the other two groups.

CONCLUSION

Patients with PE can be classified into high-, medium-, and low-risk clusters according to persistent PHTN severity; each cluster has cognizable clinical features. This study's findings stress the importance of controlling persistent PHTN to prevent future cardiovascular disease.

Association between single-nucleotide polymorphisms of NKX2.5 and congenital heart disease in Chinese population: A meta-analysis

NKX2.5 is a transcription factor that plays a key role in cardiovascular growth and development. Several independent studies have been previously conducted to investigate the association between the single-nucleotide polymorphism (SNP) 606G >C (rs3729753) in the coding region of NKX2.5 and congenital heart disease (CHD). However, the results of these studies have been inconsistent. Therefore, the present study aimed to reveal the relationship between NKX2.5 SNP 606G >C and the risk of CHD as possible in the Chinese population through meta-analysis. After retrieving related articles in PubMed, MEDLINE, EMBASE, Web of science, Cochrane, China National Knowledge Infrastructure, Wanfang DATA, and VIP database until August 2021, a total of eight studies were included in the present meta-analysis. The qualified research data were then merged into allele, dominant, recessive, heterozygous, homozygous, and additive models. Overall results of the current meta-analysis showed that 606G >C was not associated with CHD of the Chinese population in any model. In addition, subgroup analysis based on CHD type gave the same negative result. Results of sensitivity analysis showed that there was no significant correlation after the deletion of each study. Furthermore, it was noted that the results were negative and the heterogeneity was not significant. In conclusion, it was evident that NKX2-5 SNP 606G >C may not lead to the risk of CHD in Chinese population.

A Latent Class Analysis of Health Lifestyles in Relation to Suicidality among Adolescents in Mauritius

Suicidality, which includes suicidal thoughts, planning, and suicide attempts, results mainly from a combination of psychological, sociological, and environmental factors. Despite a high prevalence of suicidality among adolescents in Africa, only a few studies have considered these factors simultaneously. The objective of the study was to identify the prevalence of suicidality, to draw up profiles of concomitant risks, and to examine the associations between these profiles and suicidality in Mauritius. This study used data from the 2017 Mauritian Global School-based Student Health Survey including 3012 adolescents with a mean age of 14.9 ± 1.4 years. Factors related to lifestyle such as consumptions of alcohol and tobacco, physical activity, violence, parental support, anxiety, and loneliness were considered. A latent class analysis was performed to identify the profiles. Finally, a modified Poisson regression analysis with generalized estimating equations, adjusted with sociodemographic characteristics, was used to assess the association between these profiles and suicidality. Overall, more than one in ten adolescents had at least one of the suicidality behaviors. Three profiles were identified: 1 = "low risk group" (63.9%); 2 = "problems with violence" (15.2%); 3 = "problems with violence, alcohol, tobacco and psychological distress" (20.9%). Profiles 2 and 3 were mainly made up of males. Adolescents under 15 represented the majority of individuals in profile 2. Finally, the risk of suicidality was higher in adolescents belonging to profiles 2 and 3 compared to profile 1 for the three suicidality behaviors (profile 3: Prevalence ratio (PR) for suicidal thoughts = 1.26, 95% CI = 1.19-1.34; PR for planning = 1.23, 95% CI = 1.17-1.30; PR for attempt = 1.23, 95% CI = 1.17-1.29). This study highlights the high prevalence of suicidality and a list of concomitant risks, emphasizing this suicidality in Mauritian adolescents. Therefore, these results recommend focusing preventive efforts toward a simultaneous consideration of these factors.

Pregnant women at increased risk of adverse perinatal outcomes: A combination of less healthy behaviors and adverse psychosocial and socio-economic circumstances

Smoking during pregnancy is associated with a multitude of health behaviors and with the psychosocial and socio-economic circumstances of pregnant women. Limited research has so far been conducted on the clustering of these characteristics and on their effect on pregnancy outcomes. This study aimed to identify different groups of pregnant women based on their behavioral, psychosocial and socio-economic characteristics and their pregnancy outcomes. In total, 2455 women who were 12 weeks pregnant completed a questionnaire on smoking behavior, health behaviors and psychosocial and socio-economic characteristics. Neonatal and maternal outcomes were extracted from the Dutch perinatal registration. Subgroups were identified with latent class analysis and adverse pregnancy outcomes were compared between subgroups with logistic regression. Women were classified into four latent classes. Two classes represented the healthy higher-educated pregnant women who did not smoke: one group of multigravida women and one of primigravida women, also characterized by less pregnancy-specific knowledge and more pregnancy-related stress. The remaining women were grouped into two less healthy groups. One group frequently quit smoking, reported less healthy eating, less physical activity and comparable stress levels as the healthy higher-educated groups. The last group contained the most smokers, had the highest scores on psychosocial and pregnancy-related stress and the most adverse socio-economic circumstances. This group had an increased risk of adverse maternal outcomes, in particular developing diabetes during pregnancy. A comprehensive and integrated approach is needed to improve outcomes in pregnancies with a combination of adverse health, psychosocial, and socio-economic conditions.

The association between awareness and behavior concerning the need for protection when using pesticide sprays and neurologic symptoms: A latent class cluster analysis

Pesticide exposure is a major health risk factor among agricultural workers, and poor protective behavior and a lack of awareness concerning the risks of pesticide use in developing countries may increase the intensity of pesticide exposure. This cross-sectional study aimed to explore the relationship between neurologic symptoms and protective behavior and awareness in relation to pesticide use in China. Latent class cluster analysis was used to categorize participants into 3 latent cluster subgroups, namely, a poor protective behavior subgroup, an excellent protective awareness and behavior subgroup, and a poor protective awareness subgroup, using a person-centered approach. Multivariate regression models were used to detect the association between the latent class cluster subgroups and self-reported neurologic symptoms. The results showed that poor protective behavior in pesticide use was an important negative predicator of neurologic symptoms such as reduced sleep quality, frequency of nightmares, debility, hypopsia, and hypomnesis. These findings suggest that targeted interventions for agricultural workers, especially local greenhouse farmers, are urgently needed to improve pesticide protection behavior.

Comparison of Self-Rated Health among Characteristic Groups of Vegetable Greenhouse Farmers Based on Exposure to Pesticide Residuals: A Latent Profile Analysis

Objective

The current study was aimed at using a latent profile analysis (LPA) model to classify greenhouse farmers into a potential cluster according to their exposure to pesticide residuals. Further, the association between self-rated health (SRH) and the cluster exposed to pesticide residual was explored.

Methods

Four hundred sixty-four farmers from vegetable greenhouses were selected, their SRH information was gathered through questionnaires from the “Self-Rated Health Measurement Scale (SRHMS)” Version 1.0, and the corresponding pesticide residuals were detected in a laboratory. The linear mixed regression model was employed for association assessment.

Results

Two latent clusters were extracted as samples, and the results showed that a high amount of pesticide residual accounted for poor physical health, but did not show statistical significance. In addition, an inverse significant association was observed between psychosocial symptoms and negative emotion and pesticide residual level. Furthermore, a diversity of significant relationship was observed in social health and its corresponding dimensions with latent cluster.

Conclusions

LPA offers a holistic and parsimonious method to identify high-risk health clusters of greenhouse workers in various health aspects and allows for a personality-targeted intervention by a local health department.