Preamble

Research on the Prevalence and Characteristics of Overweight and Obesity among Adults Aged 18–44 in China in 2013

Abstract

Objective: To analyze the prevalence and epidemiological characteristics of overweight and obesity among adults aged 18–44 in China in 2013, providing a scientific basis for the prevention and control of chronic diseases.

Methods: Data were derived from the 2013 China Chronic Disease and Risk Factor Surveillance survey. A multi-stage stratified cluster random sampling method was employed to select 74,455 permanent residents aged 18–44 from 298 surveillance points across 31 provinces (autonomous regions and municipalities) in mainland China. Physical measurements, including height and weight, were collected. After weighting the sample based on the 2010 national census data, the prevalence of overweight and obesity was calculated across different genders, age groups, and regions.

Results: In 2013, the standardized prevalence of overweight among Chinese adults aged 18–44 was 30.1%, and the standardized prevalence of obesity was 11.9%. The prevalence of overweight and obesity was significantly higher in men (34.5% and 13.9%, respectively) than in women (25.4% and 9.8%, respectively) ($P < 0.05$). Regarding regional distribution, the prevalence of overweight and obesity was higher in urban areas (31.2% and 12.7%) compared to rural areas (28.8% and 11.0%), and higher in eastern regions compared to central and western regions ($P < 0.05$). Furthermore, the prevalence of overweight and obesity showed an increasing trend with age within the 18–44 age bracket ($P < 0.05$).

Conclusion: Overweight and obesity have become significant public health challenges among young and middle-aged adults in China. Targeted intervention strategies should be implemented, focusing particularly on men, urban residents, and individuals in the eastern regions to curb the rising trend of obesity-related chronic diseases.

Introduction

In recent decades, with the rapid development of the social economy and changes in residents' lifestyles, the prevalence of overweight and obesity in China has increased significantly. Overweight and obesity are independent risk factors for various chronic non-communicable diseases, including hypertension, type

1.050021 河北省石家庄市，河北省疾病预防控制中心慢性非传染性疾病防治所

School of Public Health, North China University of Science and Technology, Tangshan, Hebei Province, China.

背景

In recent years, the issues of overweight and obesity have become increasingly prominent, evolving into a major global public health challenge. China has responded by launching the "Weight Management Year" initiative, which aims to prevent and control chronic diseases associated with overweight and obesity at their source. However, due to disparities in economic development levels and geographical conditions across different regions,

the prevalence of overweight and obesity varies significantly by location. Specifically, how has the trend of overweight and obesity evolved in Hebei Province in recent years? What key areas should prevention and control efforts focus on? There is an urgent need to address these questions.

This study aims to understand the prevalence and trends of overweight and obesity among residents aged 18–44 in Hebei Province between 2013 and 2020, dynamically analyze the influencing factors, and provide a scientific basis for the "Healthy Hebei" initiative and the formulation of weight management strategies. Data were collected from the 2013 Hebei Provincial Cardiovascular Disease Prevalence Survey (conducted May–September) and the 2020 Hebei Provincial Resident Cardiovascular Disease and Risk Factor Monitoring Project (conducted April–December). Various obesity indicators were used to comprehensively measure changes in the prevalence of overweight and obesity. Multivariate logistic regression models were employed to explore influencing factors and their interactions, and changes in these factors were analyzed.

In 2020, the standardized prevalence rates of overweight, obesity, body fat percentage (BFP)-defined obesity, abdominal obesity, and high waist-to-height ratio (WHtR) among residents aged 18–44 in Hebei Province were all higher than those in 2013. In 2013, the detection rates were 32.24%, 11.49%, 24.86%, 27.03%, and 45.01%, respectively; by 2020, these rates had risen to 32.85%, 25.75%, 57.93%, 40.77%, and 59.73%. Multivariate logistic regression analysis showed that, overall, older age groups (compared to the 18–20 age group), males, married individuals, and those with hypertension faced a higher risk of all types of obesity ($P < 0.05$). Additionally, education level of junior high school or below, being married, occupations such as self-employment or agricultural labor, physical inactivity, high-fat diets, fish and egg intake $> 1,000$ g/week, sleep duration $< 6$ h/d, and hypertension also increased the risk of various types of obesity ($P < 0.05$).

Multiplicative interaction analysis revealed that married patients with hypertension had 1.551 times (95% CI = 1.400–1.758, $P < 0.05$), 1.418 times (95% CI = 1.170–1.720, $P < 0.05$), and 1.652 times (95% CI = 1.454–1.935, $P < 0.05$) the risk of obesity, BFP-defined obesity, and high WHtR, respectively, compared to the reference group. Compared to the reference group, individuals with both sleep duration $< 6$ h/d and a high-fat diet had a higher risk of abdominal obesity (OR = 1.428, 95% CI = 1.075–1.897, $P < 0.05$). Furthermore, hypertensive patients who were self-employed or agricultural laborers had 3.248 times (95% CI = 1.418–7.44, $P < 0.05$) and 3.100 times (95% CI = 1.606–5.984, $P < 0.05$) the risk of high WHtR, respectively.

Compared with 2013, among the common influencing factors for various obesity types in 2020, the proportion of males slightly decreased in the overweight and BFP-defined obesity populations ($P < 0.05$) but increased in the abdominal obesity population ($P < 0.05$). The proportion of individuals in the 31–35 and 36–40 age groups reached over 20% across all obesity types. The proportion of married individuals slightly decreased in the two systemic obesity categories ($P < 0.05$) but slightly increased in the two central obesity categories ($P < 0.05$). Notably, the proportion of hypertensive patients across all obesity types increased significantly, more than doubling the 2013 figures ($P < 0.05$). In conclusion, the prevalence of various types of obesity among residents aged 18–44 in Hebei Province in 2020 was significantly higher than in 2013. Attention should be paid to the dynamic trends of influencing factors for overweight and obesity among young and middle-aged populations in Hebei. Targeted preventive measures should be implemented to enhance health awareness and improve weight management.

Keywords: Overweight; Obesity; Obesity, abdominal; Prevalence; Factor analysis, statistical; Hebei

Chinese General Practice https Hebei Centre for Disease Control and Prevention Shijiazhuang 050021 China awareness of the residents，and do a good job of weight management.

With changes in socio-economics, lifestyles, and dietary structures, the problems of overweight and obesity have become increasingly prominent. These issues not only diminish quality of life but also increase the overall burden of disease \cite{1-3}, evolving into a major global public health challenge. From 2000 to 2023, the rates of overweight, obesity, and central obesity among adult residents aged 18–44 in ten Chinese provinces have shown a rapid upward trend. Concurrently, the incidence of chronic diseases such as hypertension and diabetes has gradually begun to affect younger populations \cite{6-8}.

Obesity has been confirmed as a primary contributing factor to various chronic conditions, including diabetes, hypertension, and cardiovascular disease. Consequently, as a reversible risk factor, implementing intervention measures for obesity is of great significance for reducing the incidence of various chronic diseases among young and middle-aged populations. To this end, research is being conducted to address these challenges.

LIU Xiaoli
Chief Physician
North China University of Science and Technology
Tangshan 063210, China

Background

The problem of overweight and obesity has become increasingly prominent in recent years and has become a major global public health problem. China has also launched the “Weight Management Year” campaign， hoping to prevent and control chronic diseases related to overweight and obesity from the source. However，due to differences in economic and geographical conditions，the prevalence of overweight and obesity varies in different regions. What is the trend of overweight and obesity prevalence in Hebei Province in recent years，and where are the key points for prevention and control ？

This problem urgently needs to be solved. Objective To grasp the trend and change of overweight and obesity prevalence among residents aged 18-44 in Hebei Province between 2013（from May to September） and 2020（from April to December）.

Dynamically analyse the influencing factors and provide an objective basis for prevention and treatment strategies and measures for healthy Hebei and weight management.

Methods

We collected data from the 2013 Hebei Provincial Cardiovascular Disease Epidemiological Survey and the 2020 Hebei Provincial Residents Cardiovascular Disease and Risk Factor Surveillance Project cross-sectional survey，and used different obesity indicators to comprehensively measure the prevalence of overweight and obesity among residents aged 18-44 years. The influencing factors and the interaction between each factor of overweight and obesity were explored by using the multifactorial logistic regression model，and the changing situation was analyzed.

Results

In 2020， the detection rates of standardised overweight，obesity，body fat percentage obesity，abdominal obesity and high waist-to- height ratio（WHtR） of Hebei residents aged 18-44 years will be higher than those in 2013（the number of individuals detected with overweight，obesity，high body fat percentage，abdominal obesity and high waist-to-height ratio after standardization based on the 2010 national census population / the standard population count of individuals aged 18-44 from the 2010 national census），which were 32.24%，11.49%，24.86%，27.03% and 45.01%，respectively；and in 2020，32.85%，25.75%， 57.93%，40.77% and 59.73%，respectively. Multivariate Logistic regression analyses of the factors affecting different types of obesity in the adult population of China showed that men，older age groups（compared with the 18-20 groups），married and hypertensive individuals had a higher risk of various types of obesity. In addition to the above factors，insufficient physical activity，educational level of junior high school and below，occupation as self-employed and agricultural workers，high-fat diet，intake of fish and eggs >1 000 g/week，and sleep <6 h/d also increased the risk of different types of obesity. The results of the multiplicative interaction analysis showed that the risk of obesity，body fat percentage obesity，and high waist-to-hip ratio in married hypertensive patients was 1.551（95% =1.400-1.758， 0.05），1.418（95% =1.170-1.720， 0.05）， and 1.652（95% =1.454-1.935， 0.05） times that of the reference group，respectively；the risk of abdominal obesity was higher in people with short sleep duration and a high-fat diet（ 1.428，95% =1.075-1.897， 0.05）；the risk of high waist-to-hip ratio in self-employed or agricultural workers with hypertension was 3.248（95% =1.418-7.44， 0.05） and 3.100（95% =1.606-5.984， 0.05） times that of the reference group，respectively. Compared to 2013，in 2020， among the common influencing factors of various obesity types，the proportion of males in the overweight and body fat percentage obesity groups slightly decreased，while in other obesity types，the proportion increased；the proportion of people in different obesity types in the age groups of 31-35 and 36-40 reached over 20%；the proportion of married individuals in the two types of generalized obesity groups slightly decreased，while in the two types of central obesity groups，the proportion slightly increased; the proportion of hypertensive patients in various obesity types significantly increased，more than doubling compared to 2013.

Conclusion

In 2020，the detection rate of all types of obesity among residents aged 18-44 years in Hebei Province will be significantly higher than that in 2013，and attention should be paid to the dynamic trends of risk factors related to overweight/ obesity in young and middle-aged populations in Hebei Province，so as to take targeted preventive measures，enhance the health Key words Overweight；Obesity；Obesity，abdominal；Prevalence；Root cause analysis；Hebei

Both the "Healthy China Action (2019–2030)" and the "Healthy China · Hebei Action (2020–2030)" have established clear objectives to enhance public awareness and skills regarding weight management, with the ultimate goal of preventing and controlling overweight and obesity. As the primary creators of social and familial wealth, young and middle-aged adults face overweight and obesity issues that can indirectly impair work efficiency and reduce labor productivity.

Previous research indicates that in 2019, the prevalence of overweight and obesity among residents aged 18–44 in the coastal areas of Fujian Province was 21.41% and 7.40%, respectively. A study conducted in Zhengzhou pointed out a high rate of excessive body fat among young and middle-aged individuals engaged in light physical labor; specifically, the growth rates of overweight and obesity were most pronounced among men aged 20–39 and women aged 30–49. Currently, there is a paucity of research focusing on the prevalence of overweight and obesity among young and middle-aged populations, and findings vary significantly across different regions. Furthermore, there is a lack of dynamic analysis regarding influential factors over time. Consequently, this study focuses on residents aged 18–44 in Hebei Province using data from 2013 and 2020. By applying various obesity measurement indicators, we analyze the shifting prevalence of overweight, obesity, and central obesity in Hebei Province. This study aims to dynamically examine changes in relevant influencing factors to provide a theoretical basis for developing prevention and control strategies, enabling the early prevention of related chronic diseases and reducing the overall disease burden in Hebei Province.

1.1 资料来源

Data for this study were obtained from the Hebei Provincial Cardiovascular Disease Epidemiological Survey conducted from May to September 2013, and the Hebei Provincial Cardiovascular Disease and Risk Factor Monitoring Project conducted from April to December 2020. Both surveys employed a multi-stage stratified random sampling method. Initially, 10 counties (cities or districts) in Hebei Province were selected as survey sites. Within each site, two townships (or sub-districts) were selected using simple random sampling (SRS). Subsequently, three village (or neighborhood) committees were selected from each township using SRS. Finally, residents aged 18 years and older who had resided at the survey site for at least six months during the previous year were selected from each committee using SRS, stratified by age and sex.

The present study specifically analyzed data from permanent residents aged 18 to 44 years. Following data cleaning and the exclusion of participants with missing records for height, weight, waist circumference, or body fat percentage, the final sample sizes were 9,535 residents for 2013 and 6,650 residents for 2020. This study was reviewed and approved by the Ethics Committee of Fuwai Hospital (Approval No. 2020-1360), and all participants provided written informed consent.

1.2.1 问卷调查

Using a standardized questionnaire developed by the National Center for Cardiovascular Diseases, trained and certified investigators conducted face-to-face interviews with the study participants. The scope of the survey encompassed demographic and lifestyle factors, including age, gender, place of residence, educational attainment, marital status, and occupation. Additionally, the investigation collected detailed data regarding physical activity levels, dietary habits, sleep patterns, and the prevalence of chronic diseases.

1.2.2 体格检查

The field measurements were conducted on-site by investigators who had undergone standardized training and passed a qualification assessment. The measured indicators included height, weight, body fat, and waist circumference (WC). Additionally, the body mass index (BMI) and waist-to-height ratio (WHtR) were calculated. For the measurement of weight and body fat, an InBody (Model:

H20B) body composition analyzer was utilized. Prior to measurement, subjects were required to wear light clothing, void their bladder and bowels, refrain from strenuous exercise, and ensure their skin was naturally dry. During the measurement process, subjects stood barefoot on the device, ensuring their hands and feet were properly aligned and in full contact with the electrodes. Subjects were instructed to maintain an upright posture with their head level and eyes looking straight ahead, while keeping their arms extended forward and downward without touching the torso until the device displayed the final results.

1.2.3 质控方法

To ensure the reliability and comparability of the results and to control for potential recall and reporting biases during the survey, the following measures were implemented: all investigators underwent standardized training and passed a qualification assessment before conducting field research; measurement and recording instruments were strictly standardized; informed consent was obtained from all participants, and all survey information was kept strictly confidential. Regarding questionnaire design, questions were formulated to be clear and unambiguous, prioritizing objective indicators wherever possible. Additionally, visual aids and supplementary information were provided to assist participants with recall, and the recall period for reported events was limited to the timeframe immediately preceding the survey. Quality control officers performed random audits by selecting participants for repeat measurements and information verification.

Sufficient physical activity is defined as accumulating $\ge 150$ minutes of moderate-intensity activity per week; otherwise, it is classified as insufficient physical activity. A high-fat diet is defined as an average intake of livestock and poultry meat $\ge 75$ g/d.

Hypertension is defined as having a systolic blood pressure $\ge 140$ mmHg, or having been previously diagnosed with hypertension at a township (community) level hospital or higher, or having taken antihypertensive medication within the past two weeks.

Criteria for obesity: (1) Previous studies have demonstrated a strong correlation and consistency between body fat percentage (BFP) and Body Mass Index (BMI), suggesting that changes in BFP can reflect changes in BMI. However, BMI may sometimes underestimate the prevalence of obesity. Therefore, this study utilizes both BMI and BFP as indicators to assess the systemic obesity status of the subjects. Using $24.0$ kg/m$^2$ as the threshold...

2 为超

Abstract

Obesity has become a significant global public health challenge. According to the criteria established for the Chinese population, individuals with a Body Mass Index (BMI) $\ge 28.0 \text{ kg/m}^2$ are classified as obese. This condition is closely associated with an increased risk of various metabolic disorders, cardiovascular diseases, and other chronic health complications. In this study, we utilize this threshold to categorize the study population and analyze the underlying physiological and environmental factors contributing to weight gain.

2 ≤BMI<28.0 kg/m

2 为肥胖；以男性体脂率≥25%

(2) WC and WHtR demonstrate high consistency among men with a height of 160 to <180 cm and women with a height of 150 to <170 cm; however, consistency is poor among individuals outside these height ranges. Furthermore, WHtR outperforms WC in predicting the clustering of cardiovascular disease risk factors. For the purposes of this study, obesity based on body fat percentage is defined as $\ge 25\%$ for men or $\ge 35\%$ for women.

[16]. Consequently, this study utilizes both WC and WHtR as metrics to assess central obesity in subjects. Abdominal obesity is defined as a waist circumference $\ge 90.0$ cm for men or $\ge 85$ cm for women, while a high waist-to-height ratio is defined as $\text{WHtR} \ge 0.5$.

Statistical Methods

Data analysis was performed using SPSS version 22.0. Categorical data are presented as relative numbers, with intergroup comparisons conducted using the $\chi^2$ test. Multivariate unconditional logistic regression analysis was employed to analyze influencing factors, with...

0.05 为差异有统计学意义。以2010 年全国第6 次人

The census data serves as the standard for evaluating the accuracy and reliability of demographic models. By utilizing these comprehensive datasets, researchers can establish a baseline for population distribution, age structures, and socio-economic indicators. In the context of machine learning and deep learning applications, census data provides the ground truth necessary for training supervised models and validating the predictive performance of spatial interpolation techniques.

Furthermore, the integration of census data allows for the calibration of multi-source datasets, such as satellite imagery and mobile signaling data. When these diverse data streams are aligned with the official census, it becomes possible to correct for sampling biases and ensure that the resulting demographic estimates are representative of the actual population. This methodological rigor is essential for urban planning, resource allocation, and the development of evidence-based public policy.

2 检验和趋势χ

[18]. The survey results were standardized for age and gender. The standardized detection rate was calculated as the number of detected cases after standardization based on the 2010 national census population divided by the total 2010 national census population aged 18–44 years.

To compare the proportions of influencing factors for different types of obesity between 2013 and 2020, the data were subjected to weighting adjustments.

2 结果

2.1 Basic Characteristics of Residents Aged 18–44 in Hebei Province in 2013 and 2020

Among the 9,539 residents included in the 2013 survey, the majority were aged 21–30 years [4,148 (43.49%)]. The sample consisted of 4,810 males (50.42%) and 4,729 females (49.58%), with 3,824 (40.09%) residing in urban areas and 5,715 (59.91%) in rural areas. Regarding educational attainment, most participants had a junior high school education or below [6,129 (64.25%)]. A total of 7,247 (75.97%) were married, and the most common occupation was agricultural labor [4,326 (45.35%)]. In terms of lifestyle and health status, 8,213 (86.10%) reported insufficient physical activity, 4,696 (49.23%) followed a high-fat diet, 3,340 (35.02%) had a weekly intake of fish and eggs exceeding 1,000 g, 3,258 (34.16%) had a sleep duration of less than 6 hours per day, and 653 (6.85%) were diagnosed with hypertension.

Among the 6,653 residents included in the 2020 survey, the majority were aged 31–40 years [2,919 (43.87%)]. The sample included 3,299 males (49.59%) and 3,354 females (50.41%), with 2,697 (40.54%) living in urban areas and 3,956 (59.46%) in rural areas. Educational attainment was primarily junior high school or below [3,155 (47.42%)]. There were 4,617 (69.40%) married individuals, and agricultural laborers remained the largest occupational group [2,531 (38.04%)]. Furthermore, 4,798 (72.12%) reported insufficient physical activity, 3,109 (46.73%) had a high-fat diet, 3,396 (51.05%) consumed more than 1,000 g of fish and eggs per week, 2,415 (36.30%) slept less than 6 hours per day, and 1,450 (21.79%) were diagnosed with hypertension.

Comparative analysis revealed statistically significant differences ($P < 0.05$) between the 2013 and 2020 cohorts regarding age, educational level, marital status, occupation, physical activity, high-fat diet, fish and egg intake, sleep duration, and the prevalence of hypertension. However, no statistically significant differences were observed between the two years in terms of gender or place of residence ($P > 0.05$), as shown in [TABLE:1]. In 2020, the standardized prevalence rates of overweight, obesity, body fat percentage-defined obesity, abdominal obesity, and high waist-to-height ratio (WHtR) among residents aged 18–44 in Hebei Province were all significantly higher than those in 2013, showing substantial increases. Specifically, the standardized prevalence rates in 2013 for overweight, obesity, body fat percentage-defined obesity, abdominal obesity, and high WHtR were 32.24%, 11.49%, 24.86%, 27.03%, and 45.01%, respectively. By 2020, these standardized prevalence rates had risen to 32.85%, 25.75%, 57.93%, 40.77%, and 59.73%, respectively (see [TABLE:2]).

2 检验结果显示，2013 年和2020 年，男

Overall, the prevalence of overweight, obesity, body fat percentage-defined obesity, abdominal obesity, and high waist-to-height ratio (WHtR) among both males and females increased significantly with age ($P < 0.001$). To analyze the influencing factors of various types of obesity among residents aged 18–44, multivariate logistic regression models were constructed. In these models, the dependent variables were defined as the presence or absence of overweight, obesity, body fat percentage-defined obesity, abdominal obesity, and high WHtR (assigned as: No = 0, Yes = 1), while age and other demographic factors served as independent variables.

[TABLE:1] Comparison of basic characteristics of included residents in 2013 and 2020

2 值

Age: 634.310 ($p < 0.001$)

Educational attainment: 568.363 ($p < 0.001$)

Marital status: 86.517 ($p < 0.001$)

Occupation: 494.963 ($p < 0.001$)

Agricultural workers (engaged in farming, forestry, animal husbandry, or fishery)

ab 488.1 <0.001

High-fat diet: 9.801, $P < 0.01$

Fish and egg intake: 638.622, $P < 0.001$

$< 600$ g/week: 3,604 (37.78%) vs. 1,348 (20.26%)

$> 1,000$ g/week: 3,340 (35.02%) vs. 3,396 (51.05%)

b 613.198 <0.001

<6 h/d 3 258（34.16） 2 415（36.30）

9 h/d 691（7.24） 1 274（19.15）

Hypertension 775.053 <0.001

Indicates missing data for the year 2020.

Chinese General Practice. Prevalence rates of various types of obesity among residents aged 18–44 in Hebei Province in 2013 and 2020. Note: WHtR = waist-to-height ratio.

A multivariate logistic regression model was established using gender, place of residence, educational level, marital status, occupation, physical activity, high-fat diet, fish and egg intake, sleep duration, and hypertension as independent variables. The results indicated that, overall, compared with the 18–20 age group, older age groups had a higher risk of developing all types of obesity ($P < 0.05$). Males faced a higher risk of all types of obesity than females ($P < 0.05$). Individuals with an educational level of junior high school or below had a higher risk of being overweight and having a high WHtR compared to those with a junior college/undergraduate degree or higher ($P < 0.05$). Married individuals had a higher risk of obesity, body fat percentage-defined obesity, abdominal obesity, and high WHtR than non-married individuals ($P < 0.05$). Self-employed individuals and agricultural workers faced a higher risk of high WHtR than managers in government agencies, enterprises, or public institutions ($P < 0.05$). Those with insufficient physical activity had a higher risk of being overweight than those with sufficient physical activity ($P < 0.05$). Individuals with a high-fat diet had a higher risk of abdominal obesity than those without ($P < 0.05$). Those with a fish and egg intake of >1,000 g/week had a higher risk of abdominal obesity and high WHtR than those consuming 600–1,000 g/week ($P < 0.05$). Individuals with a sleep duration of <6 h/d had a higher risk of abdominal obesity and high WHtR than those sleeping 6–9 h/d ($P < 0.05$). Finally, patients with hypertension had a higher risk of obesity, body fat percentage-defined obesity, abdominal obesity, and high WHtR than non-hypertensive individuals ($P < 0.05$), as shown in [TABLE:4].

Multiplicative interaction of different influencing factors on the risk of various types of obesity. A logistic regression model was established by incorporating the influencing factors as product terms. After adjusting for gender and age, the analysis results showed that married patients with hypertension had 1.551 times the risk of obesity (95% CI = 1.400–1.758, $P < 0.05$), body fat percentage-defined obesity, and high WHtR compared to the reference group.

1.418 倍（95%

The risk of abdominal obesity was 1.418 times higher (95% CI: 1.170–1.720, $P < 0.05$) and 1.652 times higher (95% CI: 1.454–1.935, $P < 0.05$) for those with high fat intake and hypertension, respectively. Compared to the reference group, individuals who slept less than 6 hours per day and consumed a high-fat diet faced a significantly higher risk of abdominal obesity (OR = 1.428, 95% CI: 1.075–1.897, $P < 0.05$). Furthermore, among hypertensive patients, those employed as self-employed individuals or agricultural laborers had a 3.248-fold (95% CI: 1.418–7.44, $P < 0.05$) and 3.100-fold (95% CI: 1.606–5.984, $P < 0.05$) higher risk of high WHtR, respectively, compared to the reference group.

No multiplicative interactions were observed among other influencing factors ($P > 0.05$). When comparing the changes in the constituent ratios of influencing factors for different types of obesity among individuals aged 18–44 in Hebei Province between 2013 and 2020, weighted adjustments revealed several trends. Compared to 2013, the proportion of males among the overweight and body fat-based obese populations decreased slightly in 2020 ($P < 0.05$), whereas their proportion in the abdominally obese population increased ($P < 0.05$). Across all obesity types, individuals in the 31–35 and 36–40 age groups accounted for more than 20% of the total. The proportion of married individuals decreased slightly in the two categories of systemic obesity ($P < 0.05$) but increased slightly in the two categories of central obesity ($P < 0.05$). Notably, the proportion of hypertensive patients across all obesity types rose significantly, more than doubling the 2013 figures ($P < 0.05$). Additionally, among the overweight population, the proportion of individuals with a junior high school education or below decreased ($P < 0.05$), while the proportion of those with insufficient physical activity in 2020 was 1.76 times that of 2013 ($P < 0.05$). Within the two central obesity categories, more than 50% of individuals consumed more than 1000 g of fish and eggs per week, while the proportion of those sleeping less than 6 hours per day showed only a slight decline ($P < 0.05$). In 2020, the proportion of individuals with high fat intake increased within the abdominally obese population ($P < 0.05$). Among the high WHtR population, the proportion of individuals with a junior high school education or below and those engaged in agricultural labor decreased ($P < 0.05$), whereas the proportion of self-employed individuals increased ($P < 0.05$), as shown in [TABLE:5] and Table 6.

3 讨论

To understand the prevalence trends of overweight and obesity among young and middle-aged adults in Hebei Province, analyze the dynamic changes in their influencing factors, and formulate corresponding prevention and control strategies with regional focus, this study analyzed the epidemiological characteristics of overweight and obesity among residents aged 18–44 in Hebei Province in 2013 and 2020.

Although BMI is commonly used to assess generalized obesity, it cannot reflect the distribution of visceral fat. Body fat percentage (BFP) represents the percentage of body fat relative to total body weight, whereas the degree of abdominal fat accumulation has a stronger correlation with obesity-related diseases. Both waist circumference (WC) and waist-to-height ratio (WHtR) can reflect abdominal fat distribution. Among these, WHtR adjusts for height based on WC and has no gender differences, allowing it to better reflect visceral fat.

Therefore, this study comprehensively utilized BMI, BFP, WC, and WHtR to measure the status of overweight and obesity among the population aged 18–44 in Hebei Province in 2013 and 2020. The results showed that compared with 2013, the rates of overweight, obesity, BFP-defined obesity, and central obesity in 2020 all showed a significant upward trend, which is consistent with the findings of a study on overweight and obesity trends in ten Chinese provinces. In 2013 and 2020, the standardized rates of overweight, obesity, and abdominal obesity among residents in Hebei Province were 32.24%–32.85%, 11.49%–25.75%, and 27.03%–40.77%, respectively.

In 2013, the overweight and obesity rates of residents aged 18–44 were similar to those of Hebei Province (32.2% and 12.1%, respectively).

[TABLE: Multivariate binary Logistic regression analysis of influencing factors for various types of obesity among residents aged 18-44 in Hebei Province]. Compared with the 2020 data for Hebei Province, the standardized overweight rate (39.6%) of residents over 20 years old in Shanxi Province in 2018 was slightly higher, the obesity rate (20%) was slightly lower, and the central obesity rate (60.2%) was significantly higher than that of Hebei Province (40.8%). These differences may be related to variations in population structure, regional economy, and lifestyle or dietary habits across different years and provinces.

The research results show that in 2020, the standardized rates of overweight, obesity, BFP-defined obesity, abdominal obesity, and high WHtR among the population aged 18–44 in Hebei Province were significantly higher than those in 2013. Further multivariate Logistic regression results found that age is the primary factor influencing the changes in various types of obesity rates, which is consistent with the findings of Xing Xiuya. Some argue that men have a higher social acceptance of obesity and pay less attention to physical appearance than women, which may be one reason for the higher obesity rate in men; however, other studies have pointed out that women have higher body fat content \cite{19, 25}, which is a risk factor for obesity.

This study found that individuals with lower educational attainment have a higher risk of obesity, which is consistent with several domestic and international studies \cite{26-28}. However, Wang Ru et al. \cite{10, 29} proposed that those with higher education levels have a higher prevalence of central obesity due to long sedentary periods and a lack of exercise. The prevalence of various types of obesity is higher among married populations, which may be related to a decrease in self-focus. This study also found that excessive intake of fish and eggs increases the risk of central obesity, possibly because excessive protein intake affects metabolism. Regarding occupation, managers in government agencies, enterprises, and public institutions may pay more attention to their personal image and weight control, while individual business owners and agricultural laborers are relatively less concerned. Some researchers believe that short sleep duration is an influencing factor for obesity, while long sleep duration is unrelated \cite{30-31}; this is consistent with the results of this study, potentially because insufficient sleep leads to decreased leptin levels, which in turn induces overeating. Furthermore, this study found that people with hypertension have a higher risk of various types of obesity, consistent with the findings of Zheng Xin et al.

In response to the rapid increase in various obesity rates among residents aged 18–44 in Hebei Province between 2013 and 2020, a dynamic analysis of the changes in the constituent ratios of related influencing factors is crucial for formulating obesity prevention measures that align with the actual conditions of Hebei Province. The study found that compared with 2013, changes in gender, population structure, and marital status in 2020 may increase the risk of various types of obesity. The proportion of men and married individuals decreased only slightly in certain obese populations while increasing in other obesity types, indicating that the influence of gender and marital status persists. Regarding population structure, the proportions of the 21–25, 26–30, and 41–44 age groups decreased, while the proportions of the 31–35 and 36–40 age groups increased; the peak age distribution showed a backward shift, indicating a trend toward aging. Having hypertension increases the risk of all types of obesity, and the proportion of hypertensive patients in 2020 grew several-fold.

[TABLE: Comparison of influencing factors for overweight, obesity, and body fat percentage obesity among residents aged 18-44 in Hebei Province in 2013 and 2020]. The data represent the constituent ratios of influencing factors after weighting.

The impact remains significant; in terms of population structure, the proportion of the 21–25, 26–30, and 41–44 age groups decreased, while the 31–35 and 36–40 age groups increased, showing a shift toward older age groups. Hypertension increases the risk of all types of obesity, and the proportion of hypertensive patients in 2020 has grown exponentially.

Furthermore, regarding unhealthy lifestyles, the proportion of individuals with insufficient physical activity among the overweight population in 2020 increased significantly, reaching 1.76 times that of 2013, which may...

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Body Fat Percentage and Obesity

Obesity is traditionally defined as an excessive accumulation of body fat that poses a risk to health. While the Body Mass Index (BMI) is the most widely used clinical tool for screening obesity due to its simplicity, it often fails to distinguish between lean muscle mass and adipose tissue. Consequently, body fat percentage (BFP) has emerged as a more precise metric for assessing an individual's true adiposity and associated metabolic risks.

The Limitation of BMI in Obesity Assessment

BMI is calculated solely based on height and weight ($\text{BMI} = \text{weight}/\text{height}^2$). However, this formula does not account for body composition. For instance, athletes with high muscle mass may be classified as "overweight" or "obese" by BMI standards despite having very low body fat. Conversely, individuals with a "normal" BMI may possess high levels of visceral fat—a condition often referred to as "normal weight obesity"—which carries significant risks for type 2 diabetes and cardiovascular disease.

Defining Obesity via Body Fat Percentage

Body fat percentage provides a direct measurement of fat mass relative to total body weight. While universal thresholds are still debated within the scientific community, the World Health Organization (WHO) and various clinical guidelines generally categorize obesity based on the following BFP thresholds:

• For Men: A body fat percentage exceeding 25% is typically classified as obese.
• For Women: A body fat percentage exceeding 35% is typically classified as obese.

These thresholds account for biological differences, as women naturally require higher essential fat levels for reproductive and endocrine functions.

Measurement Techniques

Accurately determining body fat percentage requires specialized diagnostic tools. Common methods used in clinical and research settings include:

1. Dual-Energy X-ray Absorptiometry (DEXA): Often considered the gold standard, DEXA provides a highly accurate breakdown of bone mineral density, lean mass, and fat mass.
2. Bioelectrical Impedance Analysis (BIA): A common method found in smart scales that estimates body composition by measuring the resistance of electrical flow through body tissues.
3. Skinfold Calipers: A manual method that estimates total body fat by measuring the thickness of subcutaneous fat at specific sites.
4. Hydrostatic Weighing: A technique that calculates body density by comparing a person's land weight to their underwater weight.

Clinical Implications

High body fat

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This leads to an increased risk of overweight within the population. Among the two groups categorized by central obesity, there has been no significant improvement in sleep deprivation, with the proportion of affected individuals decreasing only slightly. Concurrently, issues regarding imbalanced dietary structures have become more prominent. Specifically, there is an increasing proportion of individuals consuming excessive amounts of high-protein foods, such as fish and eggs, as well as high-fat diets; this trend may be correlated with the rising prevalence of both types of central obesity. Furthermore, among the occupations associated with a high risk of an elevated waist-to-height ratio, the proportion of individual business owners has increased significantly. The study also found that among populations with different types of obesity...

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2013 to 2020

[TABLE: Comparison of influencing factors for abdominal obesity and high WHtR among residents aged 18-44 in Hebei Province in 2013 and 2020]

$> 1,000$ g/week: 978 (38.26, 37.35)

<6 h/d 967（37.83，44.86

983 (36.82, 37.98) and 352 (13.77, 13.53) represent the weighted constituent ratios of the influencing factors. There are interactions among various influencing factors within the data; for instance, interactions exist between the high prevalence of hypertension and marital status or occupational type, as well as between high-fat diets and sleep deprivation. The changes in the constituent ratios of these influencing factors, superimposed with their internal interactions, may also be associated with the increasing prevalence of various types of obesity.

The primary strength of this study lies in its dynamic analysis of the trends in overweight/obesity and their influencing factors in Hebei Province using monitoring data from 2013 and 2020. This provides baseline data for the real-time adjustment of policies related to the "Healthy Hebei" initiative. Furthermore, the study employs various obesity evaluation indicators, offering a more comprehensive analytical perspective, and maintains strict quality control throughout the research process to ensure data authenticity and reliability. However, this study has certain limitations. First, the cross-sectional design precludes the inference of causal relationships between obesity and various risk factors. Second, changes in socioeconomic and technological levels, medical standards, and the social health environment across different survey years may influence population lifestyles, dietary and exercise habits, and the level of awareness regarding obesity, which in turn affects the prevalence of overweight and obesity. Future research plans include supplementary investigations and analyses of these factors. Finally, this study did not incorporate obesity indicators such as the Body Roundness Index (BRI) or the waist-to-hip ratio. Among these, the Body Roundness Index reflects the overall roundness of the body while accounting for waist circumference relative to height, thereby providing a better representation of body fat distribution.

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2013 to 2020

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a ） 81.008 <0.001

a ） 67.348 <0.001

The waist-to-hip ratio (WHR) is defined as the ratio of waist circumference to hip circumference. It is typically utilized in conjunction with the waist-to-height ratio (WHtR) to collectively reflect the status of central obesity. These indicators facilitate a more comprehensive, multi-dimensional assessment of the obesity epidemic in Hebei Province. Consequently, we plan to incorporate these metrics into our subsequent research.

4 小结

From 2013 to 2020, the prevalence of overweight and various types of obesity among residents aged 18–44 in Hebei Province showed an upward trend, indicating that obesity prevention and control should become a priority for the "Healthy Hebei" initiative. It is necessary to propose targeted preventive measures based on the actual conditions of Hebei Province and the evolving influential factors associated with different types of obesity. Simultaneously, efforts should be made to strengthen the development of health-supportive environments and encourage active public participation. Residents should be guided toward scientific dietary habits and healthy daily routines. Furthermore, medical interventions for patients with hypertension should be intensified to facilitate weight management and improve overall population health.

Author Contributions: Tang Lijuan proposed the primary research objectives and was responsible for the study's conception, design, implementation, and manuscript drafting. Qi Qi and Zhang Fan were responsible for data collection and organization. Gao Yifu and Cao Yajing were responsible for the collection and organization of relevant literature. Yue Fujuan and Gao Jinchai were responsible for manuscript revision. Liu Xiaoli was responsible for quality control and review, overall accountability for the article, and supervisory management.

The authors declare no conflicts of interest.

a ） 47.558 <0.001 160（3.97，3.18

a ） 46.949 <0.001 2036（50.50，64.91

489（12.13，12.01

Chinese General Practice https

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Abstract

Objective: To analyze the cancer burden attributable to overweight and obesity in the Chinese population from 1990 to 2019 and to predict the trends for the period 2020–2030, providing a scientific basis for the prevention and control of obesity-related cancers.

Methods: Data were extracted from the Global Burden of Disease Study 2019 (GBD 2019). Indicators such as mortality rates and disability-adjusted life years (DALYs) were used to describe the cancer burden attributable to high body mass index (BMI). The Joinpoint regression model was employed to analyze the trends in age-standardized mortality rates (ASMR) and age-standardized DALY rates (ASDR). Furthermore, the Nordpred Power regression model was utilized to predict the cancer burden attributable to overweight and obesity in China from 2020 to 2030.

Results: From 1990 to 2019, the number of cancer deaths and DALYs attributable to high BMI in China increased significantly, rising from 62,300 deaths and 1.74 million DALYs in 1990 to 158,100 deaths and 4.04 million DALYs in 2019. The ASMR and ASDR showed an overall upward trend, with Average Annual Percent Changes (AAPC) of 1.4% (95% CI: 1.1%–1.7%) and 1.3% (95% CI: 1.0%–1.6%), respectively. The burden was consistently higher in males than in females. Colorectal cancer, liver cancer, and esophageal cancer were the leading causes of death attributable to high BMI. Prediction results suggest that the cancer burden attributable to overweight and obesity in China will continue to rise from 2020 to 2030, with a more pronounced increase in the male population.

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Abstract

Objective To understand the current status of weight control measures taken by overweight and obese residents aged 18 and above in Hunan Province and to analyze the influencing factors, providing a scientific basis for the development of targeted weight management strategies.

Methods Using a multi-stage stratified cluster random sampling method, a cross-sectional survey was conducted among 10,545 permanent residents aged 18 and above from 10 monitoring points in Hunan Province. Data were collected through questionnaire interviews and physical measurements. Overweight and obese individuals were identified based on Body Mass Index (BMI) criteria. Multivariate logistic regression models were employed to analyze the factors influencing the adoption of weight control measures.

Results Among the 4,057 overweight and obese participants, 31.0% had taken measures to lose or maintain weight in the past 12 months. The primary methods reported were dietary control (82.1%) and physical exercise (75.8%). Multivariate logistic regression analysis revealed that several factors were significantly associated with a higher likelihood of taking weight control measures: being female ($OR=1.652$, $95\%CI: 1.385-1.971$), residing in urban areas ($OR=1.282$, $95\%CI: 1.091-1.506$), having a higher level of education (junior high school: $OR=1.451$, $95\%CI: 1.141-1.845$; high school or above: $OR=2.015$, $95\%CI: 1.564-2.596$), and having a higher household income. Furthermore, individuals who perceived themselves as "overweight" ($OR=4.229$, $95\%CI: 3.238-5.524$) or "obese" ($OR=6.787$, $95\%CI: 4.802-9.593$) were significantly more likely to take

Fan Chunxiao, Yang Lili, Wang Chengfeng, et al. Cross-sectional study on the relationship between sleep duration and obesity among American adults [J]. Journal of Qingdao University Medical College, 2016, 52(2): 164-167.

Abstract

Objective: To investigate the relationship between sleep duration and the prevalence of obesity among adults in the United States.

Methods: Data were obtained from the 2011–2012 National Health and Nutrition Examination Survey (NHANES). A total of 4,917 participants aged 20 years and older were included in the study. Sleep duration was categorized into three groups: short sleep ($\le 6$ hours), normal sleep ($7-8$ hours), and long sleep ($\ge 9$ hours). Obesity was defined as a body mass index (BMI) $\ge 30\text{ kg/m}^2$. Multivariate logistic regression models were used to analyze the association between sleep duration and obesity after adjusting for potential confounders such as age, gender, race, education level, marital status, smoking, alcohol consumption, and physical activity.

Results: The prevalence of obesity in the study population was 34.9%. Compared with individuals who had normal sleep duration ($7-8$ hours), those with short sleep duration ($\le 6$ hours) had a significantly higher risk of obesity (OR = 1.35, 95% CI: 1.18–1.54, $P < 0.001$). No significant association was observed between long sleep duration ($\ge 9$ hours) and obesity (OR = 1.02, 95% CI: 0.82–1.27, $P = 0.865$). Subgroup analyses indicated that the association between short sleep and obesity remained significant across different age groups and genders.

Conclusion: Short sleep duration is independently associated with an increased risk of obesity among American adults. Promoting adequate sleep may be an important strategy for the prevention and management of obesity.

Introduction

Obesity has become a major global public health challenge, significantly increasing the risk of chronic diseases such as type 2 diabetes, cardiovascular disease, and certain cancers. In recent decades, the prevalence of obesity has risen dramatically worldwide, particularly in developed countries like the United States. Concurrently, modern lifestyle

Wei Yingqi, Ma Aijuan, Dong Jing, et al. Relationship between leisure screen time, sleep duration, and overweight/obesity among the occupational population in Beijing [J]. Chinese Journal of Prevention and Control of Chronic Diseases.

Deng Yan, Duan Yong. Research progress on the correlation between type 2 diabetes and sleep disorders [J].

Public Health and Preventive Medicine, 2024, 35(3): 128-132.

Analysis of the Current Status and Influencing Factors of Physical Activity among Middle-aged and Elderly Patients with Chronic Diseases in a Community in Beijing

Abstract:
Objective: To investigate the current status of physical activity among middle-aged and elderly patients with chronic diseases in a community in Beijing and to analyze the influencing factors, providing a scientific basis for the development of targeted intervention measures.
Methods: A cross-sectional study was conducted using a multi-stage stratified random sampling method to select middle-aged and elderly patients with chronic diseases from a community in Beijing. The International Physical Activity Questionnaire (IPAQ) was used to assess physical activity levels, and a self-designed questionnaire was used to collect demographic information and health-related data.
Results: The study included 856 participants. The results showed that the median total physical activity was 1,548.5 MET-min/week. Among the participants, 28.4% had a high level of physical activity, 45.2% had a moderate level, and 26.4% had a low level. Multivariable logistic regression analysis indicated that age, educational level, self-rated health status, and the number of chronic diseases were significant factors influencing physical activity levels ($P < 0.05$).
Conclusion: The physical activity level of middle-aged and elderly patients with chronic diseases in this Beijing community is generally at a moderate level, but a significant proportion still lacks sufficient exercise. Interventions should focus on older patients, those with lower educational levels, and those with multiple comorbidities to promote active lifestyles and improve health outcomes.

Introduction

With the acceleration of population aging and changes in modern lifestyles, the prevalence of chronic non-communicable diseases (NCDs) among middle-aged and elderly populations in China has been rising steadily. Chronic diseases, such as hypertension, diabetes, and cardiovascular diseases, have become major public health challenges, significantly impacting the quality of life and increasing the economic burden on society. Physical activity (PA) is widely recognized as a critical non-pharmacological intervention for the prevention and management of chronic diseases. Regular physical activity can improve cardiovascular function, regulate blood glucose levels, and enhance mental well-being.

However, many middle-aged and elderly individuals do not meet the recommended levels of physical activity due

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Analysis of Obesity Prevalence and Its Associated Influencing Factors [J]. Chinese Journal of Public Health, 2020, 36(12): 1817-1821. (Received: 2025-05-14; Revised: 2025-08-25) (Editor: [Name])