Age, period, and cohort analysis of smoking intensity among current smokers in Malaysia, 1996-2015

INTRODUCTION

Tobacco use is one of the major preventable risk factors for premature death and disability worldwide. Understanding the trend of tobacco use over time is important for informed policymaking.

METHODS

The present study used an age-period-cohort (APC) approach to examine the changes in mean daily cigarette consumption among random samples of the Malaysian current smoker population over 20 years. We conducted APC analysis using a multilevel Hierarchical Age-Period-Cohort (HAPC) model and data from four nationally representative, repeated cross-sectional surveys (National Health and Morbidity Survey) conducted in 1996, 2006, 2011, and 2015 among individuals aged 18 to 80 years. Analyses were also stratified by gender and ethnicity.

RESULTS

Overall, mean daily cigarette consumption (smoking intensity) among current smokers increased with age until 60, after which a drop was observed. There were increases in daily cigarette consumption across birth cohorts. Age and cohort trends did not vary by gender but by ethnicity. The decreasing cigarette consumption after age 60 among the current smoker population was consistent with those observed among the Chinese and Indians, a trend that was not observed in Malays and other aborigines. In contrast, the increasing cohort trend was consistent with those observed among the Malays and other bumiputras.

CONCLUSION

The present study highlighted important ethnic-specific trends for mean daily cigarette consumption among the current smoker population in Malaysia. These findings are essential in guiding the formulation of interventional strategies or implementation of national tobacco control policies and help achieve the Ministry of Health Malaysia's 2025 and 2045 targets for smoking prevalence.

IMPLICATIONS

This is the first APC study on smoking intensity among current smokers in a multiracial, middle-income nation. Very few studies had performed gender- and ethnic-stratified APC analyses. The ethnic-stratified APC analyses provide useful insights into the overall age and cohort trends observed among the current smoker population in Malaysia. Therefore, the present study could add evidence to the existing literature on the APC trends of smoking intensity. The APC trends are also important in guiding the government to develop, implement, and evaluate anti-smoking strategies.

Association between Perfluoroalkyl and Polyfluoroalkyl Substances and Women's Infertility, NHANES 2013-2016

Perfluoroalkyl and polyfluoroalkyl substances (PFASs) are widely used in consumer products. However, the role of PFAS in infertility is still poorly understood. A total of 788 women from the 2013-2016 nationally representative NHANES were included to explore the association between PFAS exposure and self-reported infertility. Six PFAS, including PFDE, PFNA, PFHxS, n-PFOA, n-PFOS, and Sm-PFOS, were detected by online SPE-HPLC-TIS-MS/MS. We used the generalized linear regression model (GLM), generalized additive models (GAM), and Bayesian kernel machine regression (BKMR) to assess the single effects, non-linear relationships, and mixed effects on women's infertility, respectively. The prevalence of self-reported infertility was 15.54% in this study. In GLM, n-PFOA showed a negative association with self-reported infertility in women for the Q3 (OR: 0.396, 95% CI: 0.119, 0.788) and Q4 (OR: 0.380, 95% CI: 0.172-0.842) compared with Q1 (p for trend = 0.013). A negative trend was also observed in n-PFOS and ∑PFOS (p for trend < 0.05). In GAM, a non-linear relationship was revealed in Sm-PFOS, which exhibits a U-shaped relationship. The BKMR model indicated that there might be a joint effect between PFAS and women's infertility, to which PFNA contributed the highest effect (PIP = 0.435). Moreover, age stratification analysis showed a different dose-response curve in under and above 35 years old. Women under the age of 35 have a more noticeable U-shaped relationship with infertility. Therefore, the relatively low level of mixed PFAS exposure was negatively associated with self-reported infertility in women in general, and the impact of PFAS on infertility may vary among women of different age groups. Further studies are needed to determine the etiological relationship.

[Crown width model for planted Korean pine in eastern Liaoning mountains based on mixed effect linear quantile]

Crown width is a critical variable in reflecting the individual tree growth status and in developing forest growth and yield models. With the crown width base model as reference, we developed the crown width quantile regression models for different quantiles (0.50, 0.90, 0.93, 0.95, 0.96, 0.99) based on the data of 2763 Korean pines in 66 permanent plots from the 10-55 years old plantations in Dabiangou forest farm, mountainous areas of eastern Liaoning Province. We used the reparameterization method by introducing the single tree competition index (R_d) and used the dummy variable method by introducing stand density and forest layer variables. We then selected optimal quantile of maximum crown width in the stand by comparing our model developed routine to the traditional methods. The final crown width linear mixed effect quantile regression model was developed based on the optimal quantile at the plot level. The influence of each variable on crown width was analyzed to reflect the difference of crown width among individual trees in the stand. The models with different stand densities and forest layers had significant difference based on F statistical test: the R_a² of the model increased by 0.0104, the root mean square error decreased by 0.0115 and the mean square error reduction was 7.4%, after the variables of forest layer, forest density, and competition being incorporated into the basic model. The developed quantile regression model performed better than that of the ordinary least square method in simulating the maximum crown width of a single tree in the forest stand. The selected best quantile of the quantile regression model for the upper forest layer and lower forest layer was 0.96 and 0.93, respectively. The linear quantile regression model with the mixed effect was superior to the traditional quantile regression model in Akaike, Bayesion and HQ information criterion and other evaluation para-meters, the standard error for the parameters of estimates was significantly reduced, and the introduced mixed effect well explained differences among different plots. For the upper forest layer and lower forest layer, the maximum crown width decreased with increasing stand density, increased with increasing relative diameters. The influence of stand density on the crown width of the lower forest layer was greater than that of the upper forest layer. The crown width would increase first and then decrease with the increases of DBH when the stand density was large enough. The mixed effect of the quantile regression model developed here could significantly improve the fitting stability of the model. The sustainable development of Korean pine plantation in the mountainous area of eastern Liaoning Pro-vince should be realized by adjusting stand density and moderate tending and thinning in the future.

[Applicability of mixed effect model in the prediction of forest fire]

Fire is an important influencing factor in forest ecosystems. Establishing an accurate forest fire forecasting model is important for forest fire management. We used different meteorological factors as predictors to construct a forest fire prediction model in Fujian Province, based on Logistic regression and generalized linear mixed effect model. We compared the fitness and prediction accuracy of the two models, judged the applicability of the mixed effect model in forest fire forecasting. The results showed that the AUC and accuracy values of the Logistic base model were 0.664 and 60.4%, respectively. Models considering random effects gave better fitting and validating statistics. Among them, the two-level mixed model containing both area and altitude difference effects performed best, with increases of 0.057 and 6.0% for the AUC and accuracy values, respectively. By applying the model to predict the probability of forest fires in Fujian Province, we found that the middle-incidence and high-incidence areas of forest fires distributed in northwest and south Fujian, whereas the low-incidence areas of forest fires distributed in southwest and east Fujian, which was consistent with the observed data. The data fitting and forest fire prediction of the mixed effects model was better than those of the Logistic basic model. Therefore, it could be used as an important tool for forest fire prediction and management.

[Ground diameter-height models of naturally regenerated seedlings and saplings under broad-leaved mixed forest in Maoershan Mountains.]

Based on the investigation data of seedlings and saplings from 48 plots in natural broad-leaved forest of Maoershan Experimental Forest Farm of Northeast Forestry University in Heilongjiang Province, the optimum model of ground diameter (D₀) - height (H) was selected from eight alternative models as the basic model for the main regeneration tree species, and then the stand factors were parameterized, and the mixed effect model of sampling plot level was developed. The basic model and the mixed effect model were tested by independent samples. The results showed that there was a significant positive correlation between ground diameter and tree height of seedlings and saplings and that power function or model containing power function could better fit the relationship. The introduction of stand factors [dominant height of forest (H_T), average diameter at breast height (D_g), basal area of forest (BA)] could improve the fitting effect of the model, with the residual root mean square error (RMSE) of each tree species decreasing by 1.3%-7.4% (average 3.8%), adjusted coefficient of determination (R_a²) only increasing by 0.1%-1.1% (average 0.6%) and Akaike info criterion (AIC) decreasing by 3.2%-35.2% (average 11.4%). Mixed effect models were developed for 10 tree species, such as Ulmus propinqua, Tilia and Fraxinus mandshurica. The R_a² of mixed effect models was larger than that of the basic model, with an enhancement of 0.5%-3.5% (average 2.2%). RMSE and AIC decreased by 3.9%-20.3% (ave-rage 13.9%) and 4.0%-44.4% (average 22.3%) than that of the basic model. Model test results showed that, compared with the basic model, the average absolute error (MAE) of mixed effect model was reduced by 0.0001-0.46 m, with an average reduction of 0.08 m, and the average prediction error percentage (MPSE) decreased by 0.1%-6.2%, with an average reduction of 2.0%. The mixed effect model could improve the fitting effect and prediction ability of the model. The ground diameter-height model of seedlings and samplings of main regeneration species in broad-leaved mixed forest was developed in this study, which provides a reference for structure analysis and stand growth prediction of natural broad-leaved forest.

Development of approximate number sense across the elementary school years: A cross-cultural longitudinal study

In recent years, there has been growing interest among researchers in exploring approximate number sense (ANS)-the ability to estimate and discriminate quantities without the use of symbols. Despite the growing number of studies on ANS, there have been no cross-cultural longitudinal studies to estimate both the development of ANS and the cross-cultural differences in ANS growth trajectories. In this study, we aimed to estimate the developmental trajectories of ANS from the beginning of formal education to the end of elementary school in two countries, Russia and Kyrgyzstan, which have similar organization of their educational systems but differences in socioeconomic status (SES) and in the results of large-scale educational assessments. To assess the developmental trajectories of ANS, we used a four-wave longitudinal study with 416 participants from two countries and applied the mixed effect growth approach and the latent class growth approach. Our analysis revealed that the rate of growth in ANS accuracy was higher for the Russian sample than for the Kyrgyz sample and that this difference remained significant even after controlling for fluid intelligence. We identified two latent classes of growth trajectories: the first class had a significant growth in ANS, whereas the second class had no growth. Comparing the distribution of latent classes within the two countries revealed that there was a significantly larger proportion of schoolchildren from the second class in Kyrgyzstan than in Russia.

Role of Qualified Physicians as Antenatal Care Providers in Reducing Birth Complications in Home-delivered Rural Women in Bangladesh

Introduction

Bangladesh has made significant strides in maternal and neonatal death by ensuring qualified antenatal care (ANC) visits during the pregnancy period of women. To ensure this qualified ANC, the government of Bangladesh has increased the number of qualified physicians and skilled birth attendants at health facilities and encouraged pregnant women to take this eligible ANC during pregnancy. Despite this progress, the majority of deliveries among rural women still occur at home, assisted by traditional birth attendants. These traditional birth attendants at home or even skilled birth attendants at the health facility or home are not always cable of helping women to overcome severe delivery complications. Proper birth preparation before pregnancy through qualified ANC might be a solution here. Taking advice for appropriate birth preparation from a qualified physician (medical doctor) would ensure qualified ANC. In this study, we examined how ANC from a qualified physician, as compared to other trained providers, influences rural women delivering at home to prepare for birth and reduces severe delivery complications.

Methods

The data of 1554 rural women who delivered at home were extracted from the 2014 Bangladesh Demographic and Health Survey data. A mixed-effects logistic regression model was carried out for the binary delivery complications data, to assess the influence of qualified physicians as ANC providers on delivery complications by adjusting the effect of other socio-demographic covariates and clustering.

Results

Of the women from rural areas who delivered at home, 42% reported delivery complications. Those who received ANC from a qualified physician were 32% less likely (OR 0.68; 95% CI 0.50, 0.91) to report facing delivery complications as compared to those who had received ANC from other trained or unqualified providers adjusted by socio-demographic determinants in Bangladesh.

Conclusions

Developing a sustained and effective strategy could be a precedent for promoting ANC from qualified physicians for rural women delivering at home, to decrease delivery complications as well as creating healthy environments for safe deliveries.

A time-varying effect model for studying gender differences in health behavior

This study proposes a time-varying effect model that can be used to characterize gender-specific trajectories of health behaviors and conduct hypothesis testing for gender differences. The motivating examples demonstrate that the proposed model is applicable to not only multi-wave longitudinal studies but also short-term studies that involve intensive data collection. The simulation study shows that the accuracy of estimation of trajectory functions improves as the sample size and the number of time points increase. In terms of the performance of the hypothesis testing, the type I error rates are close to their corresponding significance levels under all combinations of sample size and number of time points. Furthermore, the power increases as the alternative hypothesis deviates more from the null hypothesis, and the rate of this increasing trend is higher when the sample size and the number of time points are larger.