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Estimating forest plant area index (PAI) with the simultaneous separation of overstory vegetation (OV) and understory vegetation (UV) is essential to study forest carbon and water cycles. Measuring PAI of OV and UV using conventional field surveys within forests is challenging, particularly for subtropical regions of China, where terrain slope can exceed 10°. The effective PAI (PAIe) instead of PAI for UV is usually measured by the conventional method of subtracting PAIe of OV from total PAIe. We find PAIe obtained using this strategy is underestimated by 25%–85%. Thus, we propose an approach to estimate PAIe and PAI of both OV and UV on sloped terrain by using single-station (SS) terrestrial laser scanner (TLS) data. Results are verified by comparing them with multistation (MS) TLS data acquired coincidentally. Then we analyze the effects of horizontal range and slope correction on PAI estimated from SS TLS data. The results show that the correlation between SS and MS PAI (PAIe) is strong, with $R^{2}$ of 0.88 (0.81) and 0.52 (0.75) ( ${p}~\lt 0.01$ ) for OV and UV, respectively. We recommend imposing a horizontal 20-m radius range for data acquired from SS TLS for PAI estimations. The difference between PAI estimations with and without a slope correction can be neglected. These results demonstrate that SS TLS data can serve as a means for PAI estimations of both OV and UV, which should help facilitate large-scale estimation in the subtropical forests of China.

Aim: This study aimed to estimate the chronic disease-free life expectancy (CDFLE) for distinct joint phenotypes of physical activity and obesity defined by six indicators in resource-limited areas. Subject and methods: In this study, a total of 38,789 participants aged 18 to 79 were recruited from the Henan rural cohort study. Logistic regression analysis was applied to assess the independent and combined effects of obesity and physical activity on chronic disease. The CDFLE according to obesity indicators and physical activity was measured via the Sullivan method. Results: Compared to participants who were physically active and nonobese defined by BMI, the multivariable-adjusted OR (95% CI) of the risk for prevalent chronic disease was 2.024 (1.833, 2.236) among those with obesity and physical inactivity, and the corresponding estimate for obese but physically active participants was 1.684 (1.550, 1.829). Compared with nonobese and physically active individuals, those with physical inactivity plus obesity classified by BMI, waist circumference, waist-to-hip ratio, waist-to-height ratio, body fat percent, and visceral fat index lost 4.42 (2.73, 6.12), 4.10 (2.95, 5.25), 4.84 (3.69, 5.98), 4.59 (3.47, 5.70), 3.86 (2.59, 5.13), and 3.81 (2.63, 4.99) years of CDFLE at age 50, respectively. The corresponding estimates for those who were obese but physically active were 2.75 (0.78, 4.72), 2.64, (1.43, 3.85), 3.14 (1.99, 4.30), 3.23 (2.09, 4.38), 2.22 (0.96, 3.48), and 1.85 (0.66, 3.03) years. Conclusion: Healthy body weight and physical activity were beneficial for chronic disease and CDFLE, and physical activity attenuated the negative effects of obesity.