Journal of Physiological Anthropology最新文献

We conducted an epidemiological study of Tibetan highlanders in Tsarang Village, Mustang District, Nepal, and reported the findings in Arima et al. (Journal of Physiological Anthropology, 43:25, 2024). Subsequently, Sienna R. Craig and colleagues, who have conducted long-term research in the same region, published a commentary on our study, providing an opportunity for further scholarly discussion. In their commentary, Craig et al. highlighted differences between our study and theirs in the reference values used for disease classification, as well as the limited explanation provided in our article regarding the rationale for selecting these values. They further noted that these differences may have contributed to discrepancies in the summary and interpretation of population health indicators between the two studies. In this commentary, we seek to clarify the background and rationale underlying the reference values and analytical choices adopted in our study, and to discuss how differences in study design and population characteristics may influence prevalence estimates and interpretations of health status. Through this discussion, we aim to contribute to a more nuanced understanding of health assessment among Tibetan highlanders living at high altitude.

Background: Air temperature that is considered as cold varies according to individuals. Urban people who live in temperate climates are accustomed to mild cold with varying wind speeds, but relatively few studies have examined the effects of wind speed in mild cold on individuals wearing winter clothing, especially compared to studies conducted in severe cold environments. We examined thermoregulatory responses to varying wind speeds in mild cold, considering anthropometric characteristics of individuals.

Methods: Ten healthy males (23.9 ± 3.3 years in age, 175.8 ± 4.9 cm in height, 74.4 ± 7.0 kg in body weight) participated in the following four wind conditions (0, 2, 4.5, and 7 m·s^-1) at an air temperature of -5 °C (wind chill temperature: -5 to approximately -12 °C). Subjects wore winter clothing (I_T, 2.1 clo), and every trial consisted of 80 min (10-min rest, 60-min walking, and 10-min recovery).

Results: Rectal and gastrointestinal temperatures remained stable across all wind conditions, suggesting sufficient insulation from the winter clothing. However, peripheral skin temperatures decreased significantly with higher wind speeds (all Ps < 0.05), with finger temperature averaging 12.7 °C at 7 m·s^-1. Overweight subjects showed less frequent shivering than normal-weight subjects. Both body surface area (BSA) and body mass index (BMI) were negatively correlated with overall thermal comfort and positively correlated with shivering frequency (all Ps < 0.05). BSA was also negatively correlated with toe temperature (P = 0.001).

Conclusions: While typical winter clothing (2.1 clo) effectively maintains core temperature in wind chill conditions down to -12 °C, extremities, particularly the hands, require better insulation. Peripheral skin temperatures and thermal comfort provide reliable indicators for assessing cold stress. Morphological properties of the body also influenced cold responses, with overweight individuals exhibiting less frequent shivering and larger body surface areas correlating with greater cold sensitivity. These findings offer insights into optimizing winter clothing design to improve comfort and safety in windy conditions in mild cold.

Background: Somatotypes describe changes in body structure and allow estimations of biological differences and similarities between subjects. They can also highlight the relationship between body composition and risk factors for worsening health.

Objectives: The study aimed to evaluate lifestyle disease risk in adult men and women based on resting blood pressure and body composition. Somatotyping was used to determine body type as endomorphic, mesomorphic, or ectomorphic.

Methods: The study used the anthropological measurements of 344 subjects, 179 men and 165 women, to determine somatotype using the Sheldon method. Body composition analysis employed an electrical bioimpedance method, while a sphygmomanometer measured heart rate and systolic and diastolic blood pressure. The study has been explicitly described as a cross-sectional study involving 344 adults aged 18-75 years (mean = 40.8 years), including 179 men (18-73 years, mean = 40.3 years) and 165 women (18-75 years, mean = 41.4 years).

Results: Men were more likely to be mesomorphic, and women were more likely to have an endomorphic somatotype. Individuals with a predominantly mesomorphic somatotype had higher total muscle mass. Furthermore, mesomorphs had the highest levels of body composition components (muscle, bone, fat-free mass, and water), and ectomorphs had the lowest. Generally, somatotype components correlated significantly with age, with a greater proportion of endomorphy and mesomorphy in older age groups. Body mass index (BMI) and waist circumference varied in women depending on somatotype. In men, BMI, waist circumference, and waist-to-hip ratio (WHR) were also somatotype dependent, with similarly elevated values found in endomorphs and mesomorphs and lower values in ectomorphs. Resting blood pressure was associated with somatotype in women, while ectomorphy was negatively associated with risk factors for disease in older men.

Conclusions: Somatotype may provide complementary information to individual measurements for assessing biological risk and predisposition to disease among adults, especially women. As such, somatotype can be considered a useful and appropriate tool for describing health-related characteristics across different populations, including both healthy and diseased individuals.

Background: Body mass index (BMI) is a key indicator of population health and often shifts alongside socio-economic change. Few studies have tracked these dynamics over long periods in transitional economies. Russia's late-twentieth-century transformations offer a rare opportunity to examine such links. This study develops and validates a time-series model of BMI in 19 years old, relating changes in socio-economic and demographic indicators to BMI trends and producing scenario-based forecasts.

Materials and methods: We analyzed national time-series data published by the NCD Risk Factor Collaboration for 1975-2016 (males and females, age 19), along with indicators of urbanization, fertility, infant and all-cause mortality, life expectancy, and nutritional proxies (protein supply, animal-source calories, meat). Predictors were standardized. Per sex, we estimated the following: (i) first-difference OLS, (ii) dynamic regressions with a lagged BMI term (ARDL(1,0)), and (iii) smooth-trend models with a natural cubic spline in year. Diagnostics included augmented Dickey-Fuller and Durbin-Watson tests. Model selection triangulated elastic net, partial least squares, and stepwise regression. Rolling-origin one-step-ahead forecasts used only information available at time t; bootstrap resampling assessed sign stability.

Results: Across specifications, the urbanization share was the most robust correlate of BMI. For males, higher urbanization was consistently and inversely associated with BMI; for females, the association was small and model sensitive (frequently negative but not uniformly significant). Effects of life expectancy and mortality attenuated and often lost significance once smooth time structure was included, indicating shared long-run movement rather than distinct short-run covariation; infant mortality added little independent signal. Nutrition proxies contributed limited, non-robust information. ARDL(1,0) one-step-ahead forecasts outperformed random-walk and trend-only baselines. Under a baseline scenario (continuation of recent socio-economic patterns), projected BMI in 2050 is approximately 26.6 kg/m² (males) and 26.7 kg/m² (females). Forecasts use only information available at time t (lagged predictors/nowcasts) and are conditional on assumed exogenous trajectories; longer-horizon projections are scenario based rather than unconditional.

Conclusions: After explicit treatment of nonstationarity, macrodemographic structure, especially urbanization, shows the most consistent links to BMI at age 19, whereas national-scale nutrition proxies are weak at this grain. Findings are descriptive, not causal; forecasts should be interpreted with caution. Incorporating finer-grained behavioral, dietary, and environmental data will help clarify mechanisms and improve long-term forecasting.

Background: Although males typically have longer limbs and greater muscle mass than females, previous studies have reported no significant sex differences in self-selected walking speed. This suggests that females may adopt alternative biomechanical strategies to compensate for their anatomical disadvantages. However, the specific mechanisms that enable females to achieve a walking speed comparable to males remain unclear.

Methods: One hundred and fifty-one young adults (76F,75M) performed a 3-min barefoot walking at their self-selected walking speed on a 10-m walkway. During walking, spatiotemporal gait parameters, vertical ground reaction forces, and foot and ankle joint kinematics were recorded. Anthropometric measurements and body composition were also obtained to assess physical capacity. Walking speed was compared between males and females, and contributing factors to walking speed were analyzed.

Results: Self-selected walking speed was not significantly different between sexes. However, when normalized by leg length, females exhibited significantly longer stride lengths and faster walking speeds than males (p < 0.05). Females also demonstrated greater ankle joint range of motion and walked with significantly greater ankle plantarflexion at toe-off, which likely contributed to increased forefoot pushing force. Additionally, females exhibited longer normalized stride lengths and faster stride times, resulting in faster normalized walking speeds compared to males.

Conclusion: The findings suggest that females compensate for relatively shorter limb lengths and lower muscle mass by relying more on distal joint flexibility and passively generated push-off power, particularly at the ankle. Females may also adjust stride length and stride time to achieve walking speeds comparable to males despite anatomical differences. Interventions aimed at modifying push-off strategies may enhance walking efficiency and could inform the development of targeted, sex-specific gait training programs.

Objective: Depression manifests significant emotional dysregulation, characterized by heightened sadness susceptibility and attenuated happiness responsiveness in individuals with depression (IWD). This study employs structured emotion induction protocols to analyze physiological response disparities between IWD and healthy controls (HC) across multiple affective states, establishing empirical foundations for optimizing affective computing-based depression screening.

Methods: Dual-phase statistical identification was conducted using Mann-Whitney U tests: initially verifying emotion elicitation validity by comparing HRV features between emotional states and resting conditions, subsequently detecting IWD/HC response differences within each emotion. Machine learning frameworks were then constructed leveraging HRV features and intergroup differential response patterns.

Results: Comparative analysis revealed generally consistent directional patterns and response magnitudes across groups for most features, while critical divergences emerged characterized by heightened sadness reactivity in IWD alongside attenuated happiness responsiveness. Implemented models achieved 76.8% accuracy (AUC = 0.772, 95% CI 0.699-0.841) under sadness-specific conditions, outperforming anger/happiness-induced models (≈ 70% accuracy) and substantially surpassing resting-state baselines.

Conclusion: Systematic investigation of HRV-mediated elicitation patterns through discrete emotion induction confirms clinically significant differential responsiveness between groups, empirically validating heightened sadness susceptibility in IWDs.

Significance: These findings offer valuable guidance for refining affective computing-based depression screening algorithms, while contributing to the mechanistic understanding of disorder-specific physiological responses to emotional stimuli.

Aim: The phase angle (PhA), assessed using bioelectrical impedance analysis (BIA), is becoming increasingly popular as an index of muscle quality associated with various health-related outcomes. This study aimed to clarify the relationship between PhA and sedentary behavior (SB), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA), which were objectively measured using accelerometers in older adults with disabilities requiring care.

Methods: We recruited 90 older adults (39 men and 51 women, mean age of 78.7 ± 6.7 years) with disabilities under the long-term care insurance system. Skeletal muscle mass index (SMI) and PhA of the lower limbs were measured using a multifrequency BIA instrument. Daily durations of SB, LPA, and MVPA per day were measured using a triaxial accelerometer. Nutritional status was assessed using the long form of the Mini Nutritional Assessment (MNA).

Results: The MVPA duration was significantly associated with lower limb PhA after adjusting for age, sex, SB and LPA durations, MNA score, and medical history (p = 0.037), whereas SB and LPA durations were not associated with lower limb PhA. The duration of SB, LPA, and MVPA were not significantly associated with lower limb SMI, whereas the MNA score was.

Conclusions: Lower limb PhA, but not lower limb SMI, was associated with MVPA duration, independent of nutritional status and medical history. Enhancing the duration of MVPA is needed to maintain the PhA and prevent further decline in physical function in older adults who require long-term care due to disabilities.

Since psychological and physiological responses to repeated exposure to mild heat has not been fully studied, the present study was designed to confirm overshooting responses in thermal sensation after repeated exposure to mild heat (i.e., the cooling period), the manner of change in the thermal sensation responses (TSRs) and the thermal comfort responses (TCRs) during the cooling period, and effect of short-term heat acclimation during repeated exposure to mild heat. In the summer, eight young adult male subjects (a mean age of 21.1 ± 1.4 years; a mean height of 173.1 ± 5.6 cm and a mean weight of 58.8 ± 7.5 kg) with clothing insulation (I_cl, clo) of 0.3 clo first stayed in the control room at 26 °C for 15 min, then moved to the main testing room at 33 °C for 10 min (condition 1), 15 min (condition 2), or 20 min (condition 3), and finally returned to the control room for 15 min. The exposure was repeated five times. TSR and TCR were recorded in a 5-min interval from the beginning of the first exposure. The tympanic temperature (T_ty), skin temperatures at the chest, forearm, front of the thigh, and front of the shin, and ECG and heart rate were continuously monitored. Local sweat rates at the same sites of skin temperature were monitored at the end of each exposure. Changes in T_ty and mean skin temperature ( ${\overline{T}}_{\mathrm{sk}}$ ) indicated no significant difference between conditions and no indication of short-term heat acclimation. Since the subjects voted nearly "cold" when ${\overline{T}}_{\mathrm{sk}}$  remained high at the beginning of the cooling period, overshooting responses in thermal sensation were repeatedly observed in all conditions. The subjects voted "slightly cool" at the end of cooling period while ${\overline{T}}_{\mathrm{sk}}$  kept decreasing during the cooling period. The thermally neutral ${\overline{T}}_{\mathrm{sk}}$  was then estimated to be 0.3 °C-4.2 °C lower than ${\overline{T}}_{\mathrm{sk}}$  observed prior to the first exposure. Thus, a residual effect on TSR during the cooling period was confirmed. Changes in the mean sweat rate, TSR and TCR showed significant differences between conditions but no indication of short-term heat acclimation. However, change in heart rate and ECG analysis implied the effect of short-term heat acclimation.

Background: Mental arithmetic tasks effectively induce psychological stress responses, but anticipatory stress responses before task onset are often overlooked. This study investigates how task difficulty influences anticipatory stress through heart rate variability time-domain analysis.

Methods: This study developed a standardized mental arithmetic task program using Unity, incorporating low, medium, and high levels by adjusting the amount of calculation and time limits. The participants were 12 healthy graduate and doctoral students. During the experiment, heart rate variability time indicators and the average RR interval were used as key physiological indicators to quantify psychological stress response. After the experiment, the participants were asked to complete the NASA Task Load Index (NASA-TLX) questionnaire to assess their workload.

Results: The NASA-TLX scores revealed significant differences in perceived workload among the three levels of task difficulty. The results indicated that task difficulty had a significant impact on anticipatory psychological stress response. High-level tasks elicited significantly greater anticipatory psychological stress responses compared to low-level tasks. Among the indicators used, the standard deviation of normal-to-normal (SDNN) intervals demonstrated particularly strong performance and may serve as a reliable and sensitive measure of anticipatory psychological stress response.

Conclusions: This study provides preliminary evidence supporting the use of SDNN as a complementary physiological indicator of anticipatory psychological stress responses. The findings suggest that task difficulty not only modulates individuals' anticipatory psychological responses on a cognitive level but also significantly shapes the dynamic trajectory of the SDNN during stress development. The observed sensitization effect indicates that higher-difficulty tasks can lead to enhanced anticipatory psychological stress responses in subsequent tasks. These results have potential implications for optimizing psychological stress response intervention strategies and for the development of standardized and replicable paradigms for anticipatory psychological stress research. Future studies should incorporate a larger and more diverse sample to further investigate how individual differences influence anticipatory psychological stress responses.

Background: Identifying and managing obesity in children is essential to prevent obesity-related diseases in adulthood. This study aimed to evaluate the association between body mass index (BMI), degree of obesity, waist circumference, waist-to-height ratio, and body fat-particularly excess body fat.

Methods: Participants included 660 children aged 9-12 years (349 boys and 311 girls). Fat mass, fat-free mass, and body fat percentage were assessed using bioelectrical impedance analysis. The discriminatory ability of BMI, degree of obesity, waist circumference, and waist-to-height ratio to identify excess body fat-defined as body fat percentage exceeding the 85th, 90th, or 95th percentile-was evaluated using receiver operating characteristic (ROC) curve and precision-recall (PR) curve analyses. Classification performance was further evaluated using a confusion matrix, accuracy, precision, recall, F1 score, Cohen's kappa coefficient, and Matthews correlation coefficient (MCC).

Results: The areas under the ROC curve (AUCs) and 95% confidence intervals (CIs) for BMI, degree of obesity, waist circumference, and waist-to-height ratio in identifying obesity based on body fat percentage were > 0.9 in both sexes in most cases. PR AUCs and 95% CIs for BMI and degree of obesity were ≥ 0.8 in most cases. Precision, recall, and F1 scores for BMI and degree of obesity in identifying obesity at the 85th or 95th percentiles were > 70% in nearly all cases. Kappa coefficients indicated substantial agreement between BMI and the 85th or 90th percentiles of body fat percentage, and moderate agreement for the degree of obesity. The MCC index showed a pattern similar to that of the kappa coefficients.

Conclusions: These findings suggest that BMI and degree of obesity are strongly associated with body fat percentage across the 85th, 90th, and 95th percentiles and that obesity classifications based on BMI as well as degree of obesity align closely with those based on body fat percentage.