China ranked ****** in Asia in terms of the digital wellbeing. In a 2023 global evaluation, Digital Quality of Life index, covering *** countries, China scored an average of **** points in five digital aspects. Internet quality and e-government were the country's strengths.

According to a report on Chinese cities from 2024 that provided a ranking of their cultural vitality and quality of life, Shanghai led the list with a total composite score of ***. Beijing and Hangzhou came in second and third. The overall city ranking, which comprised ten subsets, was headed by China's capital Beijing.

The data is used to measuring happiness resources of China. This evaluation index system is constructed from 5 primary indexes, 18 secondary indexes and 55 tertiary indexes.
Considering the data acquisition, this paper selects 30 provincial administrative units as the basic sample (excluding Tibet, Hong Kong, Macao and Taiwan in China). The period ranges from 2005 to 2019, which ensures a sufficient length of time for investigating the development characteristics of China's happiness resources. The data for this paper mainly come from the “China Statistical Yearbook,” the statistical yearbook of various provinces, the “educational statistics yearbook of China,” the annual work report of government departments at all levels, the EPS database, etc. In particular, the financial transparency data come from the China financial transparency report issued by the public policy research center of Shanghai University of Finance and Economics. For all the indicators of price factors that are involved in our research, the price adjustment is conducted based on the data from 2004. To address the problem of missing data for individual indicators in certain years, the interpolation method, mean method and average annual growth rate are used to fill in the missing data.

According to the UN's World Happiness Report, China's happiness index ranged at 5.97 points in 2024. China ranked 60th out of 143 countries. Finland, Denmark, and other European countries held the top spots in the ranking, while Afghanistan stayed at the bottom of the list. What is the happiness index? The happiness index is based on a Cantril ladder survey which is carried out annually worldwide by the polling company Gallup. Nationally representative samples of respondents are asked to value the quality of their lives at the survey moment on a 0 to 10 scale, with the worst possible life as zero and the best possible life as ten. The first World Happiness Report was published in 2012, and since then, governments are increasingly using its insights to orient public policies towards happiness. Surge in happiness in China In 2024, the happiness index in China was the highest since the beginning of the survey series. The growth in the sense of happiness has been consistent over the years except for a short period of 2018-2019. As happiness is hard to quantify, the reasons behind the dip in the curve during that time can only be hypothesized. The happiness index of 5.19 points in 2019, which was in the lower 50 percentile, did not seem to correlate with any of the usual suspects: the GDP growth, pollution levels, corruption or the perception of it, or even income inequality. The possible factors that could have affected people’s happiness were unemployment, insufficient social safety net, and several political issues. However, the country saw a surge in the sense of happiness from 2021 onwards. Successful containment of the COVID-19 pandemic that gave a greater feeling of security, fast economic recovery, and increase in the national pride could have been a few of the reasons behind the recent rising optimism in China.

About ** percent of Chinese respondents considered physical health as the most important aspect in life, according to a survey on Chinese people's general health status conducted in the end of 2020. Having a happy familly and a good mental health were other top priorities among the respondents in the survey.

The lack of quality data has left academia with an unclear picture of what religious life is like in China. Much of what is known comes from government statistics, anecdotal reports from missionaries and religious organizations, or field research. The objective of this study was to design and collect a state of the art random sample of Chinese citizens and assess their religious and spiritual life. A high quality team of Chinese scholars was assembled for the project. The survey was designed in fall 2006. In the spring of 2007, Dr. Anna Sun led a research team to field test the survey in China. In May 2007 the data were collected. The survey was a face-to-face interview. Respondents were selected using a multi-stage method to select metropolitan cities, towns and administrative villages. The final survey was administered in 56 locales throughout China, including 3 municipal cities (Beijing, Shanghai, Chongqing), 6 province capital cities (Guangzhou, Nanjing, Wuhan, Hefei, Xi'an and Chengdu). In addition, 11 regional level cities, 16 small towns, and 20 administrative villages were sampled. Within each locale, households were sampled within neighborhoods, and neighborhoods were sampled within administratively defined total neighborhood committees (government defined collections of neighborhoods). A KISH grid procedure was used to randomly select one respondent from each household for a face-to-face in-home interview.

ObjectiveTo investigate 20-year trends and disparities in quality of life among older adults in China from 1998 to 2018.MethodsOur study was based on eight representative nationwide health surveys among older adults conducted in China from 1998 to 2018. Quality of life data were obtained from 91,993 individuals aged 65 years or above. All surveys included identical indicators of self-reported quality of life, demographic factors, socioeconomic status, lifestyle habits, and health status. The trends in the standardized prevalence of poor quality of life from 1998 to 2018 were examined by locally weighted scatterplot smoothing regression (LOWESS) analysis. We assessed the prevalence of poor quality of life and its related factors by logistic regression models after adjusting for potential confounders.ResultsThe prevalence of poor quality of life was 38.2% (95% CI: 37.9–38.5%). The trends of poor quality of life showed an inverted “U” shape, that the prevalence increased from 27.8% in 1998 to 43.6% in 2008, and then decreased from 39.2% in 2011 to 32.1% in 2018. Disparities in the prevalence of poor quality of life were exacerbating among participants with low or moderate household income per capita and participants with high household income per capita from 1998 to 2018. After controlling potential confounders, living in rural areas, aged below 80 years, unmarried, living alone, low household income, current smoker, poor dietary diversity, never participating in organized social activities, with chronic diseases, functional disability, poor self-reported health, and unhealthy psychological status were risk factors related with poor quality of life in the multivariate model (all p < 0.05).ConclusionDuring the past two decades, poor quality of life in Chinese older adults showed an inverted “U” trend from 1998 to 2018 that the prevalence of poor quality of life peaked in 2008 and declined since China's deepening health system reform in 2009. However, disparities in the poor quality of life were exacerbating among participants with different socioeconomic statuses. Strengthening the health system is of great importance in improving the quality of life. More efforts are needed to reduce the disparities in the quality of life among the population at the different socioeconomic levels.

About 87 percent of Chinese respondents considered mental health as the most determining factor in health, according to a survey on Chinese people's general health status conducted in the end of 2020. The same survey found out that most of the respondents wanted to put more efforts into improving their health.

Quality of life (QoL) is an important index that allows health practitioners to understand the overall health status of an individual. One commonly used reliable and valid QoL instrument with parallel items on parent and child questionnaires, the Pediatric Quality of Life Inventory Version 4.0 (PedsQL), has been being developed since 1997. However, the use of parent- and child-reported PedsQL is still under development. Using multitrait-multimethod (MTMM) analyses and absolute agreement analyses across parent and child questionnaires can further help health practitioners understand the construct of PedsQL, and the feasibility of PedsQL in clinical. We analyzed the questionnaires of 254 parent–child dyads. MTMM through confirmatory factor analyses and percent of smallest real difference (SRD%) were used for analyzing. Our results supported the construct validity of the PedsQL. Four traits (physical, emotional, social, and school) and two methods (parent-proxy reports and child self-reports) were distinguished by MTMM. Moreover, the results of absolute agreements suggested that parent-rated and child-rated PedsQL are close (SRD% = 17.88–30.55 %)； thus, a parent-rated PedsQL can be a secondary outcome representing a child’s health. We conclude that the PedsQL is useful for measuring children’s QoL, and has helpful clinical implications.

The empirical datasets in this paper were obtained from two databases, Chinese General Social Survey (CGSS) and the China premium database of CEIC. The datasets of CGSS are initiated by the National Survey Research Center of Renmin University of China, and has been implemented every one to two years since 2003, with the most recent year being 2015. The empirical study in this paper will select survey data for three years, 2012, 2013, and 2015, which capture the period of rapid house price increase in China. Meanwhile, the datasets of CGSS are high-quality cross-sectional data, which not only contain rich information on demographics, income (individual and household), housing and marriage perceptions, but also cover rich information on individual health status, such as self-rated physical health, height and weight (used to calculate BMI), which is also of interest in our paper. In addition, it includes subjective social status, mental health status, and health-related behaviors for the mechanistic analysis in this paper.

With the development of China’s economy entering a new stage, the quality of life, which centers on the well-being of residents, provides an essential hand in promoting the transformation of the regional economy from high-speed development to high-quality development. Based on a panel threshold regression model, we examine in this paper whether quality of life helps regional economies realize developmental convergence. The research shows that: (1) The quality of life overall can promote regional economic development and passes the series test with relatively robust results. (2) The quality of life has a non-linear effect on regional economic growth, which is mainly manifested in the fact that the impact is more significant in regions with higher levels of quality of life and weaker in regions with lagging quality of life and may widen the gap between regions at the same time. (3) We categorize the study regions to test further regional heterogeneity based on regional location and development status. At the Quality of Life Level-I regions, their influence on economic development has a more substantial pulling effect. Therefore, each region should seize the strategic opportunity to improve the quality of life, focus on the balanced development of the quality of life, strengthen policy support and social security, and strive to promote the coordinated development of China’s regional economy.

(1) Human well-being on the Qinghai Tibet Plateau based on the human development index: the human well-being on the Qinghai Tibet Plateau (Qinghai and Xizang provinces) is measured quantitatively using the comprehensive human development index, an objective well-being assessment indicator. Referring to the functional structure framework of human welfare in China in the new era, the functional structure of human groups is divided into basic functions, harmonious functions, development functions and sustainable functions. On the basis of the four functions, functional indicators and specific indicator systems are further designed, that is, health, education, integration of urban and rural areas, living standards and coping with climate change account for 1/5 of the five functional indicators, and the secondary indicators are also set with equal rights. This data can reflect the comprehensive development level of human beings in Qinghai and Xizang to a certain extent, and has certain reference significance for the future development planning of the Qinghai Tibet Plateau. (2) Regional Social Relations Comprehensive Index: Based on data collected from the 2010-2019 China Regional Economic Statistical Yearbook, China Urban Statistical Yearbook, China Civil Affairs Statistical Yearbook, Provincial (Autonomous Region) Statistical Yearbook and Statistical Bulletin, relevant City Statistical Bulletin, etc., a regional social relations evaluation index system was constructed on the basis of regional social relations analysis in provincial-level areas of the Qinghai Tibet Plateau. The weights of various indicators were determined, and the regional social relations comprehensive index of 37 prefecture level cities on the Qinghai Tibet Plateau was calculated. Based on this data, obtain a spatiotemporal distribution map of regional social relations at the prefecture level on the Qinghai Tibet Plateau. (3) Human economic well-being related data: Based on data from the China Statistical Yearbook of six provinces in the Qinghai Tibet Plateau region from 2000 to 2017, and considering the complexity of human well-being, 18 indicators were selected to construct a human economic well-being indicator system suitable for evaluating the Qinghai Tibet Plateau region from four aspects: income and consumption, production materials, living materials, and resource acquisition capacity; Based on data from 17 prefecture level cities in the Qinghai Tibet Plateau region from 2007 to 2018, including the China Urban Statistical Yearbook, provincial (autonomous region) statistical yearbooks and bulletins, and relevant urban statistical bulletins, and considering the actual situation of typical cities in the Qinghai Tibet Plateau region, 22 indicators were selected to construct a human welfare index system from five aspects: income and consumption, means of production, means of livelihood, resource acquisition ability, and physical health. This indicator helps to better understand the actual conditions of basic living conditions such as economy, material resources, and means of production of residents in various regions of the Qinghai Tibet Plateau. (4) Habitat quality of the Qinghai Tibet Plateau: This dataset is based on the InVEST model and uses land use data, road data, and terrain data to calculate the habitat quality of the Qinghai Tibet Plateau from 2000 to 2020. The data span is 20 years, with data provided every 5 years and a resolution of 1000m. Among them, the land use data is sourced from the global 30 meter land cover fine classification product（ http://data.casearth.cn/sdo/list ）. The DEM data is sourced from the National Qinghai Tibet Plateau Science Data Center（ http://data.tpdc.ac.cn ）. The road data is sourced from the OpenStreetMap website（ http://openstreetmap.org/ ）. (5) Educational welfare: Based on the education statistical data of various provinces from 2013 to 2021 released on the official website of the Ministry of Education of the People's Republic of China, the compilation of science and technology statistical data of higher education institutions, the Statistical Yearbook of China's Disability Affairs, the Statistical Yearbook of China's Education Funds, relevant research reports, and other publicly available data, the entropy weight method is selected to objectively determine the weights of each evaluation indicator. The natural breakpoint method is used to grade the various educational welfare evaluation data obtained in 2013 and 2021, and to draw educational welfare evaluation maps and comprehensive educational welfare evaluation maps of various levels and types of schools. This provides a more accurate understanding of the spatiotemporal pattern of various educational welfare and comprehensive educational welfare on the Qinghai Tibet Plateau, and provides scientific basis and decision-making reference for relevant departments. (6) Human welfare in the Dadu River Basin: Based on meteorological data from

The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities.

The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.

The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.

A majority of Chinese consumers were concerned of personal aging problems and taking an active approach to slow down the process. According to a survey on Chinese people's general health status conducted in the end of 2020, about ** percent of respondents said that they had paid attention to healthy diets as an anti-aging measure.

The Chinese General Social Survey (CGSS) launched in 2003, is the earliest national representative continuous survey project run by academic institution in China mainland. CGSS is aimed to systematically monitor the changing relationship between social structure and quality of life in both urban and rural China. Social structure refers to dimensions of social group and organization as well as networks of social relationships. Quality of life is the objective and subjective aspects of the people well-being both at the individual and aggregate levels.

This is supporting data for a PhD thesis and consists of three parts: 1) cross-sectional data to explore the relationships between resilience and quality of life in parents of children with cancer; 2) qualitative data including transcripts to identify factors that contribute to resilience in the parents; 3) RCT data to evaluate the effectiveness of a mobile-based resilience training programme in enhancing the parents' resilience.

Abstract

Objectives: To obtain reliable, valid and comparable health, health-related and well-being data over a range of key domains for adult and older adult populations in nationally representative samples To examine patterns and dynamics of age-related changes in health and well-being using longitudinal follow-up of a cohort as they age, and to investigate socio-economic consequences of these health changes To supplement and cross-validate self-reported measures of health and the anchoring vignette approach to improving comparability of self-reported measures, through measured performance tests for selected health domains To collect health examination and biomarker data that improves reliability of morbidity and risk factor data and to objectively monitor the effect of interventions

Additional Objectives: To generate large cohorts of older adult populations and comparison cohorts of younger populations for following-up intermediate outcomes, monitoring trends, examining transitions and life events, and addressing relationships between determinants and health, well-being and health-related outcomes To develop a mechanism to link survey data to demographic surveillance site data To build linkages with other national and multi-country ageing studies To improve the methodologies to enhance the reliability and validity of health outcomes and determinants data To provide a public-access information base to engage all stakeholders, including national policy makers and health systems planners, in planning and decision-making processes about the health and well-being of older adults

Methods: SAGE's first full round of data collection included both follow-up and new respondents in most participating countries. The goal of the sampling design was to obtain a nationally representative cohort of persons aged 50 years and older, with a smaller cohort of persons aged 18 to 49 for comparison purposes. In the older households, all persons aged 50+ years (for example, spouses and siblings) were invited to participate. Proxy respondents were identified for respondents who were unable to respond for themselves. Standardized SAGE survey instruments were used in all countries consisting of five main parts: 1) household questionnaire; 2) individual questionnaire; 3) proxy questionnaire; 4) verbal autopsy questionnaire; and, 5) appendices including showcards. A VAQ was completed for deaths in the household over the last 24 months. The procedures for including country-specific adaptations to the standardized questionnaire and translations into local languages from English follow those developed by and used for the World Health Survey.

Content Household questionnaire 0000 Coversheet 0100 Sampling Information 0200 Geocoding and GPS Information 0300 Recontact Information 0350 Contact Record 0400 Household Roster 0450 Kish Tables and Household Consent 0500 Housing 0600 Household and Family Support Networks and Transfers 0700 Assets and Household Income 0800 Household Expenditures 0900 Interviewer Observations

Individual questionnaire 1000 Socio-Demographic Characteristics 1500 Work History and Benefits 2000 Health State Descriptions and Vignettes 2500 Anthropometrics, Performance Tests and Biomarkers 3000 Risk Factors and Preventive Health Behaviours 4000 Chronic Conditions and Health Services Coverage 5000 Health Care Utilization 6000 Social Cohesion 7000 Subjective Well-Being and Quality of Life (WHOQoL-8 and Day Reconstruction Method) 9000 Interviewer Assessment

Geographic coverage

National coverage

Analysis unit

households and individuals

Universe

The household section of the survey covered all households in the People's Republic of China. Two special administrative regions Hong Kong and Macau are excluded. Institutionalised populations are also excluded. The individual section covered all persons aged 18 years and older residing within individual households. As the focus of SAGE is older adults, a much larger sample of respondents aged 50 years and older were selected with a smaller comparative sample of respondents aged 18-49 years

Kind of data

Sample survey data [ssd]

Sampling procedure

The People's Republic of China(PRC) administers 22 provinces. These were grouped into Eastern, Central and Western provinces based on geographical location and economic status.PRC used a stratified multistage cluster sample design. Eight provinces were sampled. Strata were defined by the eight province(Guangdong,Hubei,Jilin,Shaanxi,Shandong,Shanghai,Yunnan,Zhejiang) and locality (urban or rural), there were 16 strata in total. One district(urban) and one county(rural) was randomly selected from each province. From each district/county 4 communities/townships were selected probability proportional to size; the measure of size being the number of households in the community/township. From each community/township 2 residential blocks/villages were selected probability proportional to size; the measure of size being the number of households in the residential blocks/villages. In each selected residential block/village 84 households were randomly selected:70 50 plus households and 14 18-49 households. All 50 plus members of the 50 plus households were eligible for the individual interview. One person aged 18-49 was eligible for the individual interview, and the individual to be included was selected using a Kish Grid.

Stages of selection Strata: Province, Locality=16 PSU: Township/Community=64 surveyed SSU: Village/Neighbourhood Community=127 surveyed TSU: Households=10278 surveyed QSU: Individuals=15050 surveyed

Mode of data collection

Face-to-face [f2f] PAPI and CAPI

Research instrument

The questionnaires were based on the WHS Model Questionnaire with some modification and many new additions. A household questionnaire was administered to all households eligible for the study. An Individual questionniare was administered to eligible respondents identified from the household roster. A Proxy questionnaire was administered to individual respondents who had cognitive limitations. The questionnaires were developed in English and were piloted as part of the SAGE pretest in 2005. All documents were translated into Chinese. All SAGE generic questionnaires are available as external resources.

Cleaning operations

Data editing took place at a number of stages including: (1) office editing and coding (2) during data entry (3) structural checking of the CSPro files (4) range and consistency secondary edits in Stata

Response rate

Household Response rate=95% Cooperation rate=99%

Individual: Response rate=93% Cooperation rate=98%

The Chinese Longitudinal Healthy Longevity Survey (CLHLS) provides information on health status and quality of life of the elderly aged 65 and older in 22 provinces of China in the period 1998 to 2014. The study was conducted to shed light on the determinants of healthy human longevity and oldest-old mortality. To this end, data were collected on a large percent of the oldest population, including centenarian and nonagenarian; the CLHLS provides information on the health, socioeconomic characteristics, family, lifestyle, and demographic profile of this aged population. Data are provided on respondents' health conditions, daily functioning, self-perceptions of health status and quality of life, life satisfaction, mental attitude, and feelings about aging. Respondents were asked about their diet and nutrition, use of medical services, and drinking and smoking habits, including how long ago they quit either or both. They were also asked about their physical activities, reading habits, television viewing, and religious activities, and were tested for motor skills, memory, and visual functioning. In order to ascertain their current state of health, respondents were asked if they suffered from such health conditions as hypertension, diabetes, heart disease, stroke, cancer, emphysema, asthma, tuberculosis, cataracts, glaucoma, gastric or duodenal ulcer, arthritis, Parkinson's disease, bedsores, or other chronic diseases. Respondents were further queried about assistance with bathing, dressing, toileting, or feeding, and who provided help in times of illness. Other questions focused on siblings, parents, and children, the frequency of family visits, and the distance lived from each other. Demographic and background variables include age, sex, ethnicity, place of birth, marital history and status, history of childbirth, living arrangements, education, main occupation before age 60, and sources of financial support.

Data and code for figures and tables in "The quality of direct-to-consumer telemedicine consultations for sexually transmitted infections in China: An analysis of visits by standardized patients"

Additional file 2. The database of this study.