Market integration and resident health in China

Abstract

This paper uses data from the China Health and Nutrition Survey (CHNS) to study the impact of market integration on residents’ health. The empirical results based on the probit model show that market integration has a significant dampening effect on resident incidence. For every one-unit increase in the degree of market integration, the probability of residents becoming sick decreases by approximately 1.45%. Moreover, after a series of robustness tests, the conclusion is still valid. This study further analyses the potential mechanism and finds that the promotion of market integration can improve the medical conditions available to residents, optimize the nutritional indices of residents, and reduce labor load of residents, thus improving their health. The results of the heterogeneity test show that there are certain differences in the impact of market integration on the health level of residents of different genders, ages and income classes. At the same time, this study also verifies that there is a synergistic effect between internet penetration and market integration.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-025-85972-6.

Introduction

Under the impetus of globalization, market integration has become a significant characteristic of today’s world economic development. This is especially apparent in China, where the pace of market integration has accelerated notably since the reform and opening up¹. In recent years, constructing an integration market has been a key strategic initiative of the Chinese government to establish a new development pattern. In 2022, the Chinese government issued the Opinions on Accelerating the Construction of a Unified National Market². This means accelerating the construction of an integration market, breaking down local protection and market segmentation, clearing critical bottlenecks constraining economic circulation and facilitating the broader flow of goods and factor resources. Therefore, market integration profoundly impacts the structure and functions of various aspects of society by facilitating the flow of population, capital, and labor across regions^1,2. As a result, residents’ health may also be influenced by market integration.

Health, as a critical form of human capital, plays a decisive role in economic growth and development³. The Chinese government places high importance on the health of its citizens and released the “Healthy China 2030” Planning Outline in 2016, which explicitly aims to “significantly improve the health level of the population by 2030"³. Recent data on Chinese health indicators show a steady improvement in the health status of residents. The “China Nutrition and Chronic Disease Report (2020)” revealed that since 2015, there has been continuous improvement in the nutritional status of Chinese residents, with an increase in average adult height. In 2019, the premature death rate due to major chronic diseases such as cardiovascular disease, cancer, chronic respiratory disease and diabetes was 16.5% in China. This figure is 2% points lower than that in 2015. Among the many factors affecting health, regional economic conditions play a significant role⁴. Currently, no research has explored the impact of market integration on residents’ health. However, several studies have shown that the factor mobility induced by market integration has multiple impacts on residents’ health. Initially, changes in living environments may expose residents to varying levels of environmental pollution and life stress, thereby affecting their physical and psychological health^5,6. Furthermore, increased capital and labor mobility may lead to a decline in medical resources and service levels in some areas, posing additional medical challenges and health risks to residents⁷. Adjustments and changes in the social security system also affect the level of health protection for residents, potentially resulting in a lack of health coverage for vulnerable groups^8,9. Therefore, exploring the impact of market integration on health is crucial for understanding changes in health levels and promoting health improvements.

With increasing marketization, China has made great achievements in terms of market integration. According to the “China Provincial Marketization Index Report (2021)” published by the Beijing Institute of National Economy, the average marketization index across Chinese provinces has steadily increased from 6.9 to 8.2⁴. Against this backdrop of economic development, there is growing concern about whether the process of market integration could impact residents’ health. To explore this issue, this paper constructs a market integration index and uses long-term panel data from the China Health and Nutrition Survey (CHNS) to analyze the potential impacts of market integration on residents’ health. The main contributions of this paper are as follows. First, this paper fills the research gap on the relationship between market integration and residents’ health and validates the potential positive effects of market integration on health levels; second, it discusses potential mechanisms of influence, integrating medical conditions, nutritional indices, and labor load to explore specific impact mechanisms; and third, it further discusses the heterogeneity of these positive effects among different demographic groups and regions.

The structure of this paper is as follows. The second section discusses existing research findings and proposes the theoretical hypotheses of this study. The third section describes the data, variables, and empirical models used in this study. The fourth section reports the empirical estimation results, including baseline results, robustness checks, heterogeneity analysis, and mechanism analysis. The fifth section concludes with the implications of the findings.

Literature review and theoretical hypotheses

Literature review

Market integration plays a crucial role in economic globalization and regional economic collaboration, resulting in significant and diverse impacts. On the one hand, the advancement of market integration can stimulate economic growth. This position involves fostering collaboration between the government and markets, advocating for industrial restructuring and innovation, and improving social welfare¹⁰. Market integration helps goods and services flow freely by removing trade barriers, which speeds up economic activity¹¹. This growth is clearly seen as technology and money move across borders, making the global production network stronger. Market integration is important for improving cooperation between the government and markets¹². This has led to improvements in industrial structures and technological innovations, particularly in high-tech and service industries¹³. Regional companies are more likely to use advanced technologies and management methods when they enter global markets. Previous research has shown that market integration can help cities become more environmentally friendly and sustainable by encouraging the efficient use of resources and the adoption of green technologies^14,15. However, market integration can help people make more money, spend more money, and feel better overall. For example, market integration can help people make more money by opening up new jobs and making work more efficient. This is important for reducing poverty. Moreover, when markets are integrated, consumers have more options for products and can enjoy lower prices, which helps them reach their full potential as buyers¹⁶. According to Fan et al.¹⁷, market integration can increase the well-being of residents, and this effect is more pronounced in low-income groups. Despite extensive research on market integration, some gaps remain, and currently, no study has discussed how market integration might impact residents’ health.

Existing research typically focuses on specific factors and their direct relationships with resident health, involving political, economic, and social aspects. Politically, political participation can enhance residents’ influence on health policies and access to resources¹⁸; health insurance systems play a crucial role in improving the accessibility of medical services and alleviating medical burdens¹⁹; and China’s accession to the WTO has had a negative impact on the health of Chinese residents²⁰. Economically, economic growth is widely believed to positively affect residents’ health by increasing income levels and improving public services and infrastructure⁴; rising housing prices are negatively correlated with the mental health of urban residents, reflecting the potential harm of economic stress on mental health²¹; and income disparities may exacerbate health inequalities^22,23. Considering environmental factors, air pollution exacerbates economic disparities between urban and rural areas by reducing health levels²⁴, and residents’ subjective perceptions of their living environment are closely related to their health status⁵. Considering that the internet has a bidirectional impact on residents’ health, providing more health information but also potentially leading to information overload or misinformation^25,26, considering literacy factors, improving residents’ health literacy can effectively mitigate health inequalities, especially among low-income and less-educated groups²⁷.

In summary, previous research has primarily focused on the economic benefits of market integration, with less attention paid to its potential health effects. Additionally, residents’ health is influenced by multiple dimensions. However, no studies have examined how economic, political, and social factors collectively impact residents’ health. Given that market integration is a comprehensive concept encompassing the unification of factor markets, resource markets, and commodity markets, as well as the standardization of institutions and facilities, it can be viewed as a situation where economic, political, and social factors work together. Thus, studying the effects of market integration on residents’ health can effectively fill this gap. Furthermore, market integration can indirectly influence residents’ lifestyles, access to healthcare services, and environmental quality by promoting the free flow of resources, optimizing resource allocation, and enhancing economic efficiency. Therefore, the theoretical pathways through which market integration affects residents’ health exist. In the long term, exploring the relationship between market integration and residents’ health not only helps us understand the potential impacts of comprehensive economic indicators on public health but also holds significant importance for developing more effective health and economic policies.

Theoretical hypotheses

Although academic focus on the impact of market integration on improving residents’ health levels is relatively scarce, both the branches of market integration and resident health contain theoretical presuppositions regarding their relationship. Based on a review of the literature, this paper proposes three mechanisms through which the advancement of market integration affects residents’ health levels:

First, market integration can improve the level of medical conditions available to residents, thereby positively impacting their health. On the one hand, medical standards improve with the advancement of market integration. Market integration breaks down regional trade barriers and administrative restrictions, promoting the free flow and optimal allocation of resources, including capital, technology, and human resources²⁸. The allocation of medical resources is influenced not only by government leadership but also by the interaction of market, institutional, and cultural factors²⁹. Thus, as markets integrate, medical technologies and talent can be more rationally distributed and optimized, progressively enhancing the level of medical services. Residents can more conveniently access high-quality medical resources, including advanced medical equipment, technology, and professional medical personnel³⁰. On the other hand, market integration can help reduce disparities in healthcare and job prospects across different areas. According to Ma et al.³¹, there are differences in health conditions between cities and the countryside in China, leading to unequal access to medical services. In this situation, market integration can help ensure that medical resources are used well and make it easier for people to obtain medical help. This can especially help people in areas where there are not enough medical services, so they can obtain the care they need quickly and effectively. This can lead to better results and faster recovery for patients. Moreover, market integration helps people earn more money, allowing them to pay for better healthcare services such as improved health insurance, regular check-ups, and expert medical treatment as necessary³². As a result, market integration can improve healthcare quality, offer improved medical protection for people, and support the overall well-being of residents.

Second, combining markets helps to increase the quality and safety of food, which in turn has a positive effect on people’s health through better nutrition. As the market becomes more integrated, the food market opens up and offers residents a wider range of food options³³. Families can buy a variety of different foods, such as meat, dairy, eggs, and vegetables, that are full of protein and nutrients. This can help improve their diet and improve their nutritional status³⁴. Moreover, the merging of markets has improved the rules for food safety and quality control³⁵, which has lowered the chances of food safety issues and has guaranteed the health of people’s diets. Eating a variety of nutritious foods can help people obtain all the nutrients they need to boost their body’s defenses and immune system, which is good for staying healthy and improving overall well-being³⁶. As a result, residents benefit from improved nutrition due to market integration, leading to better nutritional security and overall health.

Finally, the progress of market integration has somewhat reduced the workload for residents, which is good for their health. Studies in the medical field have shown that the amount of work residents do can greatly affect their physical pain, heart health, anxiety, and even how long they live^37,38. As the economy grows and more jobs become available, people have a wider range of career options and different ways of working³⁹. Moreover, when markets come together, it helps to make work more efficient and distribute labor resources better, which means that people do not have to work for long periods of time. This helps people better manage their work and personal life, reducing stress and physical strain. It can improve mental and physical health and lessen the negative impact of work on health³⁷. Therefore, when markets come together, it helps make labor load better for individuals, thereby enhancing their overall health levels.

In conclusion, as markets become more connected, medical resources are distributed and improved more efficiently. This leads to better access to high-quality medical services for residents, allowing them to receive timely and effective treatment for diseases and stay healthy. Furthermore, connecting markets also helps to grow the food market, offering a wider variety of food options and improving people’s eating habits and nutrition. The merging of markets boosts the economy, leading to higher incomes and better living conditions for residents. This allows them to access top-notch medical conditions and nutritious food. Moreover, as the market becomes more integrated, it creates more job opportunities for residents and improves the quality of their work life, decreasing their workload. In general, connecting markets help improve people’s health by improving medical conditions, nutritional indices, and labor load. Therefore, this paper proposes the following two hypotheses:

Hypothesis 1

Market integration is beneficial to residents’ health.

Hypothesis 2

Market integration promotes residents’ health by improving medical conditions, optimizing nutritional indices, and reducing labor load.

Data, variables and empirical models

Data sources

This paper employs data from the China Health and Nutrition Survey (CHNS) to examine the potential impacts of market integration on individual health outcomes. The analysis is conducted using data collected from six survey waves in the years 1997, 2000, 2004, 2006, 2009, and 2011. Additional regional data are sourced from the National Bureau of Statistics of China.

Variables

Dependent Variable: Drawing from the methodologies of Liu et al.⁴⁰ and Xie & Feng⁴¹, this study employs an individual illness indicator to assess health conditions. The measure is derived from the following question: “Have you been ill or injured in the past four weeks?” This indicator is a dummy variable assigned a value of 1 if the individual has been ill or injured in the past four weeks and 0 otherwise.

Core Explanatory Variable: Following Fan et al.¹⁷, this paper measures the degree of market integration using a market index that encompasses aspects such as the relationship between the government and the market, the development of the nonstate economy, the maturity of product and factor markets, and the environment of market intermediaries and legal institutions. Each component of the index reflects a facet of market integration and consists of various subindices. First, the individual indicator scores for the base year (1997) are set, with the maximum and minimum values being 10 and 0, respectively (i.e., the province with the best score for that indicator receives a score of 10, while the lowest receives a score of 0). Next, the scores of other provinces are determined within this range of 0 to 10, creating a single index corresponding to each indicator. Then, the weights for the composite indicators are determined using principal component analysis, resulting in a total index. The specific calculation method can be found in the appendix. Furthermore, inspired by Cao et al.⁴², this study employs the price index method to construct integration indices for goods, services, capital goods, and labor markets, serving as proxies for national unified market development. The indices cover various sectors and are averaged to represent the overall market integration index.

Control Variables: Drawing from the methodologies of Liu et al.⁴⁰ and Xie and Feng⁴¹, the following control variables are selected in this study. The control variables are organized into four levels: age, years of education, sex, BMI, daily smoking quantity, drinking frequency, marital status, primary occupation, rural residency, and presence of chronic diseases. Family Characteristics: Number of family members, method of water access, toilet facilities, lighting conditions, and per capita family income. Community Characteristics: Population density, sanitation facilities, health quality, and level of urbanization. Regional Characteristics: Per capita GDP, regional economic growth rate, level of industrialization, and residents’ savings rate. The research results of many scholars have shown that the above factors may have an impact on residents health^4,5,23,27. It is therefore appropriate to select these control variables.

Other variables: In line with the theoretical hypotheses previously discussed, this study selects the following mechanism variables. (1) Medical conditions: distance to the nearest medical facility, number of doctors per hundred people, and number of hospital beds per hundred people in the community, based on Liu et al.⁴⁰. (2) Nutritional indices: The proportion of calories derived from proteins and fats in an individual’s diet³⁶. (3) Labor load: Number of working days per week, hours worked per day, and work intensity³⁸. In addition, this paper includes the highest level of education attained by an individual and the internet penetration rate in the region as moderating variables to discuss how these factors might affect the impact of market integration on morbidity rates. This paper also conducts expanded analyses on the heterogeneous effects of market integration based on individual gender, age, and income disparities.

This paper preprocesses the data as follows: (1) Due to the special nature of the underage population, only individuals aged 18 and above are included. (2) Considering the entry and exit of samples in the CHNS data from 1997 to 2011, the survey data across six years are matched and merged by individual ID to create a balanced panel dataset. (3) Observations with missing key variables are excluded, resulting in 14,418 valid observations. (4) Income and other price-related variables are adjusted using the 1997 consumer price index. The specific descriptions and descriptive statistics of these variables are presented in Table 1.

Table 1.

Descriptive statistics.

VarName	Description	Mean	SD
Illness	Whether the individual has been sick or injured in the past four weeks (1 = yes, 0 = no)	0.13	0.34
Market	Market integration index	5.94	1.78
Age	Individual age (years)	52.01	12.70
Edu_year	Individual years of education (years)	5.89	4.14
Gender	Individual gender (1 = male, 0 = female)	0.43	0.50
BMI	Individual BMI (0 = weight/height2 below 18, 1 = between 18 and 24, 2 = above 24)	1.33	0.54
Smoke	Average number of cigarettes smoked per day	4.43	8.79
Drink	Individual’s drinking frequency (0 = no drinking, 1 = less than once a month, 2 = 1–2 times a month, 3 = 1–2 times a week, 4 = 3–4 times a week, 5 = almost every day)	1.10	1.81
Marriage	Individual marital status (1 = married, 0 = not married)	0.88	0.32
Job	Main occupation of individual	3.75	3.36
Village	Whether the individual lives in a rural area (1 = yes, 0 = no)	0.72	0.45
CDS	Whether the individual has hypertension or diabetes (1 = yes, 0 = no)	0.11	0.32
hh_member	Number of family members	3.28	1.48
Water	Access to drinking water at home (1 = indoor tap water, 2 = hospital tap water, 3 = hospital well water, 4 = bottled water, 5 = others)	1.83	1.06
Toilet	Household toilet conditions (0 = no toilet, 1 = indoor flush, 2 = indoor no flush, 3 = outdoor flush public toilet, 4 = outdoor, outdoor nonflush public toilet, 5 = open cement pit, 6 = open earth pit, 8 = others)	3.44	2.12
Lighting	Household lighting conditions (1 = electric lights, 2 = kerosene lights, 3 = oil lights, 4 = candles, 5 = others)	1.00	0.20
hh_income_per	Log value of household income per capita	8.06	1.67
com_density	Community population density index	5.71	1.36
com_sanitation	Community Health Conditions index	5.99	3.01
com_health	Community Health Quality Index	5.37	2.41
com_urbanization	Level of community urbanization	58.83	19.25
GDP_per_ln	Log value of regional GDP per capita	9.33	0.71
Growth_rate	Provincial economic growth rate	0.15	0.05
GDP_industry	Provincial industrialization level = industrial GDP/total GDP	0.42	0.07
Saving_rate	Provincial household savings rate = household savings at the end of the year/total GDP	0.60	0.09
Distance	Distance from community center to nearest medical facility (km)	0.03	0.08
Doctor	Number of doctors per 100 people in the community	22.57	43.36
Bed	Number of beds per 100 people in the community	25.84	52.13
Protein	The percentage of calories an individual gets from protein = Protein intake (g) *4/total calories	0.12	0.03
Fat	The percentage of calories an individual gets from fat = Fat intake (g) *9/total calories	0.29	0.11
Workdays_per_week	Individual working days per week (days)	4.49	2.39
Workhours_per_day	Individual working hours per day (hours)	5.54	3.39
Workhours_intensity	Individual work intensity (hours worked per week less than 11 = 1, between 11 and 30 = 2, between 31 and 40 = 3, between 41 and 50 = 4, more than 50 = 5)	3.82	1.52
Internet	Regional internet penetration rate	22.34	9.42
ind_income_net	Log value of individual net income	6.50	3.64
Segment	Market segmentation index	0.0012	0.0008
Hospitalize	Whether the individual has sought medical attention in the past four weeks (1 = yes, 0 = no)	0.11	0.32
Treatment	What kind of treatment did the individual receive (2 = inpatient, 1 = outpatient, 0 = None)	0.12	0.36
Cost	Log value of the cost of treatment for illness or injury	0.61	1.89
Lamplight	Average night light intensity	3.17	3.47

Models

To investigate the impact of market integration on resident morbidity, this paper sets the benchmark regression model (1). Since whether an individual is sick or injured in the past four weeks is a binary variable, this paper constructs a probit model to study the potential impact of market integration on the morbidity of residents. To eliminate the bias caused by the omission of community and time effects, this paper adopts the robust two-way fixed effects method for estimation in the regression process. The specific model setting method is as follows:

1

Illness is a dummy variable. illness takes the value 1 if individual i living in region r has been sick or injured in the past four weeks during the survey in year t and 0 otherwise. Market_rt represents the level of market integration in region r in year t. , , , and represent the control variables at the individual, household, community and province levels, respectively. h represents the individual’s family, and c represents the community in which the individual lives. and denote community fixed effects and year fixed effects, respectively. is the interference term.

To prove that the improvement of medical conditions is a possible mechanism for market integration to reduce the morbidity of residents, this paper sets the following benchmark regression model (2). Similarly, this paper adds four control variables at the individual, family, community and region levels to the model. To eliminate the bias caused by the omission of community and time effects, this paper adopts the robust two-way fixed effects method for estimation in the regression process. where medcine_ct represents the medical conditions of community c in year t, which is decomposed into three specific indicators in this paper: distance, doctor and bed. The specific model setting method is as follows:

2

In addition, considering that there may be a nonlinear relationship between the nutritional indices and labor load of residents and the level of market integration, this paper refers to Tian³⁶ to construct the benchmark regression model (3).

3

where Indexit represents the nutritional indices (protein and fat) or labor load (workdays_per_week, workhours_per_day and workhours_intensity) of individual i in year t. f(Market_rt) is the unknown market function with nonparametric specification. We propose kernel-weighted local polynomial estimation to improve the modeling of slope effects, especially in marginal areas, and to obtain confidence intervals and optimal bandwidths from the sample itself.

Empirical results

Baseline regression

This paper empirically tests the impact of market integration on residents’ health by constructing a probit model. Table 2 reports the regression results for Model (1). The results indicate that market integration significantly reduces the incidence of illness among residents. For every one-unit increase in the level of market integration, the probability of illness decreases by approximately 1.45%. This means that the promotion of market integration has tangible benefits for public health. For example, in a region with a population of 10 million, a 1.45% reduction in disease incidence could mean 145,000 fewer cases of illness per year. This effect not only reduces the medical burden and alleviates the pressure on the healthcare system, but also provides a healthier workforce to support economic growth. The results for the control variables are largely as expected. At the individual level, the probability of illness increases with age. Additionally, males, individuals with a higher BMI, those suffering from chronic diseases, and those living in rural areas are more likely to be ill. At the family level, a larger family size tends to decrease the incidence rate. Poorer toilet facilities in the household are associated with a greater likelihood of illness. At the community level, for every one-unit increase in urbanization, the illness rate among residents increases by approximately 0.11%. At the regional level, economic growth has a significant inhibitory effect on local morbidity rates; a 1% increase in the economic growth rate leads to a 39.80% reduction in the illness rate.

Table 2.

Impact of market integration on resident morbidity.

	(1)
	Illness
Market	− 0.0145**
	(0.0073)
Age	0.0022***
	(0.0003)
edu_year	− 0.0014
	(0.0009)
Gender	− 0.0175**
	(0.0073)
BMI	− 0.0130**
	(0.0052)
Smoke	− 0.0006
	(0.0004)
Drink	− 0.0011
	(0.0018)
Marriage	0.0024
	(0.0084)
Job	− 0.0019**
	(0.0009)
Village	0.1712**
	(0.0743)
CDS	0.1199***
	(0.0075)
hh_member	− 0.0050**
	(0.0021)
Water	0.0053
	(0.0037)
Toilet	0.0048**
	(0.0020)
Lighting	− 0.0008
	(0.0132)
hh_income_per	− 0.0002
	(0.0017)
com_density	0.0021
	(0.0068)
com_sanitation	− 0.0005
	(0.0024)
com_health	0.0004
	(0.0016)
com_urbanization	0.0011**
	(0.0005)
GDP_per_ln	0.1218**
	(0.0578)
Growth_rate	− 0.3980***
	(0.1385)
GDP_industry	0.0017
	(0.1101)
Saving_rate	− 0.1021
	(0.0659)
Community-FE	Yes
Wave-FE	Yes
N	14,340

The table reports the marginal effect; Robust standard errors are in parentheses; **Is significant at 5% level, ***is significant at 1% level; “Community-FE” represents Community fixed effects and “Wave-FE” represents year fixed effects.

Additionally, this paper replaces the market integration variable (Market) in Model (1) with five subindices measuring aspects of market integration and conducts regression analyses, the results of which are shown in Table 3. The indices for government-market relations (relation), factor markets (factor), and legal and institutional frameworks (law) all reduce the incidence of illness among residents to some extent. Of these, a positive government-market relationship has the most significant negative impact on the incidence of illness, followed by market intermediation and the legal and institutional environment. While the development level of factor markets does reduce illness rates, its impact is relatively limited. There was no significant relationship between the level of nonfinancial economic development and local illness rates. Notably, for every unit increase in the development of product markets, the illness rate among residents increases by approximately 1.13%. The results for the control variables remain consistent with previous findings. Due to space constraints, the detailed coefficient estimates for the control variables can be found in SI Table 2 in the appendix. This suggests that an overly developed product market may have negative health impacts, such as promoting overconsumption or the spread of unhealthy products. However, this negative effect can be partially offset by other factors. It indicates that merely developing the product market is not enough to promote health; supportive institutional and policy environments are equally crucial. This calls for the government to play a more active role in managing the relationship between market development and public health.

Table 3.

The disaggregated market integration index serves as an explanatory variable.

	(1)	(2)	(3)	(4)	(5)
	Illness	Illness	Illness	Illness	Illness
Relation	− 0.0197***
	(0.0057)
Nonstate		0.0003
		(0.0058)
Product			0.0113**
			(0.0053)
Factor				− 0.0064*
				(0.0033)
Law					− 0.0090***
					(0.0033)
IND-controls	Yes	Yes	Yes	Yes	Yes
HH-controls	Yes	Yes	Yes	Yes	Yes
COM-controls	Yes	Yes	Yes	Yes	Yes
PRO-controls	Yes	Yes	Yes	Yes	Yes
Community-FE	Yes	Yes	Yes	Yes	Yes
Wave-FE	Yes	Yes	Yes	Yes	Yes
N	14,340	14,340	14,340	14,340	14,340

The table reports the marginal effect; Robust standard errors are in parentheses; *Is significant at 10% level, **is significant at 5% level, ***is significant at 1% level; “IND-Controls”, “HH-Controls”, “COM-Controls” and “PRO-Controls” represent the control variables at the individual, household, community and province levels, respectively; “Community-FE” represents Community fixed effects; and “Wave-FE” represents year fixed effects. The same applies below.

Robustness test

(1) Replacement of the explanatory variable: This study substitutes the market integration index with a market segmentation index and incorporates it into Model (1) for regression analysis. According to the results in Table 4, an increase in the market segmentation index significantly increases the probability of illness among residents. This finding supports the previous conclusion that market integration can reduce the incidence of illness. Moreover, the results of the control variables remain consistent with previous findings. Due to space constraints, detailed estimates of the control variable coefficients can be found in SI Table 3 in the appendix.

Table 4.

Effect of the degree of market segmentation on the incidence of adults.

	(1)
	Illness
Segment	38.0538***
	(9.3393)
IND-controls	Yes
HH-Controls	Yes
COM-Controls	Yes
PRO-Controls	Yes
Community-FE	Yes
Wave-FE	Yes
N	14,340

***Is significant at the 1% level.

(2) Replacement of the dependent variable: Considering that whether one has been ill or injured in the past four weeks may not fully capture the complexity of overall health status, this paper replaces the measurement with the following three approaches as part of a robustness check. First, individuals’ perceptions of “illness” or “injury” may vary, leading to potential bias in this variable. Therefore, “whether one sought medical care in the past four weeks” (hospitalize) is used as the dependent variable in a probit model regression. Second, different illnesses or injuries may vary in severity. Thus, this paper constructs “treatment type” (treatment) as the dependent variable to distinguish the severity of health problems. Specifically, values of 2, 1, and 0 are assigned to cases of inpatient treatment, outpatient treatment, and no treatment, respectively, and an ordered logit model is used for estimation. Finally, the logarithm of an individual’s medical expenses (cost) is also used as the dependent variable in a tobit model, aiming to better reflect the complexity of health status. The estimates presented in Table 5 are consistent with previous results.

Table 5.

Change the way health levels are measured.

	(1)	(2)	(3)
	Hospitalize	Treatment	Cost
Market	− 0.0850**	− 0.1644*	− 0.1088***
	(0.0426)	(0.0867)	(0.0378)
IND-controls	Yes	Yes	Yes
HH-controls	Yes	Yes	Yes
COM-controls	Yes	Yes	Yes
PRO-controls	Yes	Yes	Yes
Community-FE	Yes	Yes	Yes
Wave-FE	Yes	Yes	Yes
N	14,244	14,418	14,418

*Is significant at the 10% level, **is significant at the 5% level, ***is significant at the 1% level.

(3) Change in sample scope: Previous research has confirmed that China’s accession to the WTO has impacted residents’ health levels²⁰. To eliminate potential biases in the results due to the period before and after joining the WTO, this study removes data from the survey years 1997 and 2000, retaining only the data from 2004 to 2011 for regression analysis. Table 6 reports the empirical results after changing the sample scope. The results demonstrate that even after removing the data from the two years prior to China joining the WTO, the conclusion that market integration reduces the incidence of illness among residents remains valid.

Table 6.

Change in sample scope.

	(1)
	Illness
Market	− 0.0405**
	(0.0160)
IND-controls	Yes
HH-controls	Yes
COM-controls	Yes
PRO-controls	Yes
Community-FE	Yes
Wave-FE	Yes
N	9500

**Is significant at the 5% level.

(4) Inclusion of lagged variables: Considering that individual health levels vary, this study introduces a lagged variable of the dependent variable in Model (1) to exclude the possibility that previous trends in illness rates are correlated with market integration. According to the results in Table 7, after including the lagged variable, the conclusion that market integration reduces the incidence of illness among residents still holds. Moreover, the effects of the five subindices of the market integration index on illness rates remain consistent with the findings reported in Table 3.

Table 7.

Inclusion of lagged variables.

	(1)	(2)	(3)	(4)	(5)	(6)
	Illness	Illness	Illness	Illness	Illness	Illness
Market	− 0.0969*
	(0.0515)
Relation		− 0.1240***
		(0.0363)
Nonstate			− 0.0056
			(0.0380)
Product				0.1038***
				(0.0325)
Factor					− 0.0526**
					(0.0211)
Law						− 0.0825***
						(0.0220)
IND-controls	Yes	Yes	Yes	Yes	Yes	Yes
HH-controls	Yes	Yes	Yes	Yes	Yes	Yes
COM-controls	Yes	Yes	Yes	Yes	Yes	Yes
PRO-controls	Yes	Yes	Yes	Yes	Yes	Yes
Community-FE	Yes	Yes	Yes	Yes	Yes	Yes
Wave-FE	Yes	Yes	Yes	Yes	Yes	Yes
Pre-trend	Yes	Yes	Yes	Yes	Yes	Yes
N	12,015	12,015	12,015	12,015	12,015	12,015

The table reports the marginal effect; Robust standard errors are in parentheses; *Is significant at the 10% level, **is significant at the 5% level, ***is significant at the 1% level; “IND-Controls”, “HH-Controls”, “COM-Controls” and “PRO-Controls” represent the control variables at the individual, household, community and province levels, respectively; “Community-FE” represents Community fixed effects and “Wave-FE” represents year fixed effects; “Pre-trend” represents that a one-period lag of the dependent variable is added to the model.

(5) Replacement model: Table 8 presents the estimation results after changing the model. This paper uses a logit model to examine the potential relationship between market integration and health, and the results are consistent with the baseline results, indicating that market integration indeed promotes health. In addition, only about 13% of the sample was observed to have been ill or injured, which could be considered a rare event with low occurrence probability. Therefore, a complementary log-log (cloglog) model was further employed for estimation, and the results remain robust.

Table 8.

Replacement model.

	(1)	(2)
	Logit	Cloglog
Market	− 0.1454*	− 0.1302*
	(0.0761)	(0.0689)
IND-controls	Yes	Yes
HH-controls	Yes	Yes
COM-controls	Yes	Yes
PRO-controls	Yes	Yes
Community-FE	Yes	Yes
Wave-FE	Yes	Yes
Pre-trend	Yes	Yes
N	14,340	14,340

*Is significant at the 10% level.

(6) Nonlinear relation: If the relationship between market integration and health is nonlinear, a linear model might produce misleading results. Therefore, this paper uses quantile regression and Box-Tidwell transformation to verify whether a nonlinear relationship exists between the two. Table 9 presents the results of the quantile regression. The inhibitory effect of market integration on disease incidence is significant across different sample intervals, with little variation in coefficients, suggesting that there is no significant nonlinear relationship between the two. The results of the Box-Tidwell transformation are shown in SI Table 4 of the appendix, where the insignificance of the interaction term’s coefficient similarly indicates that there is no nonlinear relationship.

Table 9.

Quantile regression.

	(1)	(2)	(3)
	> 25%	> 50%	> 75%
Market	− 0.0481*	− 0.0359***	− 0.0150*
	(0.0258)	(0.0103)	(0.0089)
IND-controls	Yes	Yes	Yes
HH-controls	Yes	Yes	Yes
COM-controls	Yes	Yes	Yes
PRO-controls	Yes	Yes	Yes
Community-FE	Yes	Yes	Yes
Wave-FE	Yes	Yes	Yes
N	3783	7406	10,936

*Is significant at the 10% level, ***is significant at the 1% level.

(7) Instrumental variable: The relationship between market integration and residents’ health may involve a bidirectional causality issue. For example, a healthier population may be more productive and engage in more frequent economic activities. Therefore, improvements in health outcomes could also contribute to greater market integration. This paper selects the average nighttime light intensity at the provincial level (lamplight) as an instrumental variable. On the one hand, this variable reflects the level of economic development in a region; the higher the average light intensity, the more urbanized and economically developed the area is. On the other hand, no research has shown a direct link between average light intensity and residents’ morbidity, making it a suitable instrumental variable. Table 10 presents the estimation results using the instrumental variable, demonstrating that the choice of instrument is appropriate. Moreover, after using the instrumental variable, the regression results are consistent with the baseline results in direction, and the coefficients are close.

Table 10.

IV.

	IV-1	IV-2
	(1)	(2)
	Market	Illness
Lamplight	0.3686***
	0.0032
Market		− 0.0254**
		(0.0103)
Kleibergen-Paap rk Wald F	13376.17
Kleibergen-Paap rk LM	1966.964***
(P)	(0.0000)
IND-controls	Yes	Yes
HH-controls	Yes	Yes
COM-controls	Yes	Yes
PRO-controls	Yes	Yes
Community-FE	Yes	Yes
Wave-FE	Yes	Yes

**Is significant at the 5% level, ***is significant at the 1% level.

Heterogeneity

(1) Gender: Given that some diseases exhibit significant incidence rate disparities between genders, this study specifically examines how gender affects the impact of market integration on residents’ illness rates. The sample was divided into male and female groups, and Model (1) was applied separately for regression analysis. According to the results presented in Table 11, market integration has a more significant effect on reducing illness rates among males. Specifically, for every unit increase in market integration, the probability of illness among male residents decreases by approximately 2.97%. In contrast, this effect is less pronounced among females, suggesting that gender differences play a moderating role in the impact of market integration on illness rates. The differential impact of market integration on the health of male and female residents may stem from differences in biology, social roles, and health behaviors between the genders. Biologically, men and women exhibit significant differences in susceptibility to certain diseases, which may result in varied health effects of market integration between the sexes⁴³. Additionally, the division of gender roles in society may influence health outcomes. Men often engage in more physically demanding jobs and are exposed to higher-risk work environments, making them more likely to benefit from the economic improvements and better working conditions brought about by market integration. Market integration promotes economic growth and labor mobility, potentially offering men more economic opportunities, which can improve their health. In contrast, women, who often bear more caregiving responsibilities and participate less in the labor market in many cultural contexts, may experience more limited health benefits from market integration⁴⁴.

Table 11.

Heterogeneity by gender.

	(1)	(2)
	Male	Female
Market	-0.0297***	-0.0022
	(0.0110)	(0.0099)
IND-controls	Yes	Yes
HH-controls	Yes	Yes
COM-controls	Yes	Yes
PRO-controls	Yes	Yes
Community-FE	Yes	Yes
Wave-FE	Yes	Yes
N	5772	8118

The table reports the marginal effect; Robust standard errors are in parentheses; ***Is significant at the 1% level; “IND-Controls”, “HH-Controls”, “COM-Controls” and “PRO-Controls” represent the control variables at the individual, household, community and province levels, respectively; “Community-FE” represents Community fixed effects; and “Wave-FE” represents year fixed effects. The same applies below.

(2) Age: The sample was divided into three age groups: young (18–40 years), middle-aged (40–60 years), and elderly (over 60 years). The regression results reported in Table 12 indicate that the effect of market integration on reducing illness rates is particularly pronounced among elderly people. For every one-unit increase in market integration, the probability of illness among elderly people decreases by approximately 6.72%. Elderly people typically have greater susceptibility and incidence rates of diseases⁴⁵. Thus, factors such as improved accessibility to medical services, optimized distribution of medical resources, and dissemination of health knowledge during the process of market integration may have more direct and significant impacts on their health. For example, through market integration, elderly people can access high-quality medical services more conveniently, including specialist consultations, advanced treatment methods, and more efficient medical appointment systems. This not only alleviates social issues related to difficult registration and hospitalization but also provides elderly people with higher quality and timely medical services, effectively reducing their risk of illness. The more access elderly people have to healthcare, the greater the improvement in their health condition^46,47.

Table 12.

Heterogeneity by age.

	(1)	(2)	(3)
	Youth	Middle age	Agedness
Market	− 0.0002	− 0.0074	− 0.0672**
	(0.0165)	(0.0092)	(0.0292)
IND-Controls	Yes	Yes	Yes
HH-Controls	Yes	Yes	Yes
COM-Controls	Yes	Yes	Yes
PRO-Controls	Yes	Yes	Yes
Community-FE	Yes	Yes	Yes
Wave-FE	Yes	Yes	Yes
N	1890	9205	2101

**Is significant at the 5% level.

(3) Income: Does the effect of market integration on illness rates vary among different income groups? To explore this question, the sample was divided into three income groups: low, middle, and high. The results of the regression analysis for these groups are reported in Table 13. The negative impact of market integration on illness rates is more pronounced among low-income residents. Specifically, for every unit increase in market integration, the illness rate among low-income residents decreases by approximately 2.81%. Low-income residents face more severe issues related to quality of life and basic living conditions⁴⁸. For example, this group may more frequently encounter unsafe drinking water sources and unsanitary sanitation facilities, as well as malnutrition or an imbalanced diet due to economic constraints. These factors collectively increase the disease risk for low-income residents. In the process of market integration, as the economy grows and resource distribution is optimized, improvements in medical and health conditions, increased accessibility to nutritious food, and dissemination of health knowledge bring greater health benefits to low-income residents. In contrast, the middle- and high-income groups already enjoy better living conditions, so the health improvement effects of market integration on them are relatively limited. Overall, the health benefits of market integration are more pronounced for low-income residents, highlighting the significant role of income disparities in health outcomes.

Table 13.

Heterogeneity by income.

	(1)	(2)	(3)
	Low income	Middle income	High income
Market	− 0.0281*	0.0067	− 0.0146
	(0.0161)	(0.0120)	(0.0142)
IND-controls	Yes	Yes	Yes
HH-controls	Yes	Yes	Yes
COM-controls	Yes	Yes	Yes
PRO-controls	Yes	Yes	Yes
Community-FE	Yes	Yes	Yes
Wave-FE	Yes	Yes	Yes
N	4590	4417	4401

*Is significant at the 10% level.

(4) Internet penetration: In the digital era, differences in internet penetration across regions may also become a key factor affecting residents’ health, thus influencing the estimates of this study. Therefore, the internet penetration rate of each region was included in Model (1) along with an interaction term. According to the results displayed in Table 14, the coefficient of the interaction term is negative, indicating a synergistic effect between internet penetration and market integration. First, as a core component of information technology, the internet significantly improves the circulation and sharing of information, making it easier for residents to access health-related knowledge and information. This dissemination of information plays a crucial role in enhancing public health awareness, changing unhealthy lifestyles, and timely detection and treatment of diseases. Second, the internet promotes the spread of health education through online health courses and public lectures, increasing residents’ understanding of preventive health measures. Finally, the internet can enhance the quality and efficiency of medical services, for example, through telemedicine and online appointment systems, reducing waiting times and improving the utilization of medical resources. Thus, the widespread adoption of the internet strengthens the impact of market integration on reducing illness rates among residents.

Table 14.

Moderating effect of the internet penetration rate.

	(1)
	Illness
c.market#c.internet	-0.0025*
	(0.0014)
Market	0.0351
	(0.0834)
Internet	0.0099
	(0.0263)
_cons	-6.9971*
	(3.8458)
IND-controls	Yes
HH-controls	Yes
COM-controls	Yes
PRO-controls	Yes
Community-FE	Yes
Wave-FE	Yes
N	11,950

Robust standard errors are in parentheses; *Is significant at the 10% level; “IND-Controls”, “HH-Controls”, “COM-Controls” and “PRO-Controls” represent the control variables at the individual, household, community and province levels, respectively; “Community-FE” represents Community fixed effects; and “Wave-FE” represents year fixed effects. The same applies below.

Mechanism analysis

In the theoretical hypothesis section, this study proposes that market integration can affect the incidence rate of illnesses among residents through three potential mechanisms: medical conditions, nutritional indices, and labor load. The specific results are as follows:

(1) Medical conditions: Table 15 presents the estimation results of Model (2)⁵. Column (1) shows that market integration can shorten the distance from community centers to medical facilities. This change implies a reduction in the time and potential transportation costs for residents to access medical services, thereby enhancing the convenience of obtaining medical conditions. This is particularly important for the timely treatment of patients with acute and chronic illnesses, helping to improve treatment outcomes and overall health levels. The specific mechanism by which market integration achieves these improvements is through increased market openness and competition, which drives investment in healthcare infrastructure and optimizes resource allocation. For example, as the market opens further, the supply of public and private healthcare services increases, leading to the expansion of existing medical facilities, while also encouraging private capital and foreign investment into the healthcare sector, thereby enhancing the overall accessibility of medical services. Columns (2) and (3) indicate that market integration can increase the number of doctors and hospital beds per hundred people. Specifically, for every unit increase in market integration, the number of doctors per hundred people increases by approximately ten, and the number of hospital beds increases by approximately six. This increase reflects, to a certain extent, how market integration has facilitated the enhancement of medical service provision capabilities, including the training of medical personnel, the expansion of medical facilities, and the upgrading of medical equipment. More doctors and beds mean more efficient medical services and better medical coverage, providing residents with more extensive and higher-quality medical services. These changes reflect that market integration has enhanced the capacity for healthcare service provision, not only in terms of quantity but also in the quality of medical resources. Market integration promotes the flow of healthcare resources across regions, attracting higher-level doctors and the introduction of advanced medical equipment. For instance, market openness fosters collaboration in professional medical education and talent training, improving doctors’ skills, while also enhancing the quality of healthcare services through technology transfer and equipment upgrades. Thus, the optimization of medical conditions is a potential mechanism through which market integration can affect residents’ health.

Table 15.

The impact of market integration on medical conditions.

	(1)	(2)	(3)
	Distance	Doctor	Bed
Market	− 0.0108***	10.8581***	6.4503***
	(0.0018)	(1.1060)	(1.5542)
Village	0.0000	0.0000	0.0000
	(0.0000)	(0.0000)	(0.0000)
_cons	0.3212***	11.2803	− 83.9951
	(0.0904)	(61.1940)	(72.0958)
IND-controls	Yes	Yes	Yes
HH-controls	Yes	Yes	Yes
COM-controls	Yes	Yes	Yes
PRO-controls	Yes	Yes	Yes
Community-FE	Yes	Yes	Yes
Wave-FE	Yes	Yes	Yes
N	8056	5653	5415

***Is significant at the 1% level.

(2) Nutritional indices: This paper employs a local polynomial smoothing technique to illustrate the nonlinear relationship between nutritional indices and the market integration index, as shown in Fig. 1. After controlling for other variables, the nutritional indices changed over time. On the one hand, the proportion of calories residents obtain from protein increases steadily with the level of market integration, eventually stabilizing at approximately 14%. This indicates that a healthy, normally active 70 kg adult male resident consumes approximately 252 kilocalories from protein each day, which represents a stable and appropriate proportion. This change reflects a shift toward a healthier dietary structure, specifically an increased intake of high-protein foods. This may be attributed to the diversification of the food market and increased availability of international food products brought about by market integration, enabling residents to access higher-quality protein sources more easily. On the other hand, the proportion of calories obtained from fats shows a fluctuating upward trend as the level of market integration increases. Notably, there is a slight decline in fat-derived energy when the market integration index is at a medium level (approximately between 4 and 7), which could be related to strengthened food quality regulation during market adjustments. However, overall, the change in the proportion of fat-derived energy remains within a reasonably healthy range, indicating that while market integration enhances the quality of residents’ diets, it also promotes the formation of healthy eating habits. These findings highlight how connecting markets can help improve people’s nutrition and lead to better health by improving the quality of their diets. On one hand, market integration significantly expands the range of available food options, particularly high-nutritional-value foods, by opening up food markets. This diversification in food supply enables residents to more easily access foods rich in high-quality protein, vitamins, and minerals, thereby promoting a healthier dietary structure. On the other hand, market integration optimizes pricing mechanisms and improves distribution efficiency, which lowers the relative cost of nutritious foods. As transportation networks improve and logistics costs decrease, the market can more efficiently distribute and circulate fresh foods and high-nutrition products, allowing residents in various regions easier access to healthy food.

Fig. 1.

Local polynomial smoothing for nutritional indices. Notes: The solid lines refer to the fitted value of each nutritional index, and the gray area refers to the 95% confidence interval.

(3) Labor load: Figure 2 utilizes a local polynomial smoothing method to depict the nonlinear relationship between labor load and the market integration index. First, the average number of working days per week for residents decreases as the level of market integration increases. This trend indicates that when the market is more integrated, improving labor efficiency and optimizing the labor market structure can help individuals accomplish the same or more work in less time. Particularly at lower levels of market integration, residents may face longer working hours, possibly linked to the inefficiency of the labor market and a high proportion of labor-intensive industries. Second, the average daily working hours also decrease with increasing levels of market integration. This reduction may reflect more flexible work arrangements brought about by market integration, such as flexible working hours, an increase in remote work opportunities, and more effective work distribution. These factors collectively contribute to shorter working hours and enhance the balance between work and life. Third, there is a similar decline in the intensity of work. When the market is highly integrated, the work intensity is between 2.5 and 3, corresponding to approximately 11–40 h of work per week. For a resident who works five days a week, the maximum labor intensity is eight hours of work per day, while for some other occupations, the average daily work might be less than three hours. This represents a healthy level of labor intensity. This implies that in highly integrated markets, residents experience lower work intensity and more reasonable working hours, suggesting that market integration may promote a more humane work environment and the implementation of labor protection policies. A key mechanism for these changes is the restructuring of the labor market. Market integration tends to drive economic modernization, shifting labor from traditional, low-efficiency sectors (e.g., agriculture or low-end manufacturing) into more productive and less physically demanding service or technology sectors. As businesses become more competitive, they are incentivized to invest in labor-saving technologies and optimize workforce management, which can result in fewer work hours and a reduced physical burden on workers. Moreover, as market integration encourages competition and mobility, workers gain more bargaining power, leading to improved labor standards, stronger enforcement of labor rights, and better working conditions. Market integration also fosters the development of human capital through education and training, allowing workers to take on higher-skilled, less physically demanding jobs, further reducing labor burdens. In this context, the reduction of labor burden can effectively alleviate work-related stress and mental and physical fatigue, which are major contributors to chronic illnesses. By improving working conditions, market integration plays a crucial role in enhancing overall health outcomes for residents.

Fig. 2.

Local polynomial smooth for labor load. Notes: The solid lines refer to the fitted value of each nutritional index, and the gray area refers to the 95% confidence interval.

Conclusion

Does market integration influence residents’ health? Given the lack of literature directly examining how this comprehensive factor affects the health levels of Chinese residents, this paper makes an initial attempt and systematically elaborates on the impact of market integration on residents’ morbidity. Empirical research results show that the advancement of market integration significantly reduces residents’ morbidity, indicating that market integration can significantly enhance residents’ health levels. The robustness of this study’s conclusions remains unchanged, whether further replacing explanatory variables, changing the sample scope, or incorporating lagged terms. The results of the mechanism tests suggest that market integration affects residents’ health mainly through three pathways: medical conditions, nutritional indices, and labor load. Heterogeneity tests show that in terms of gender, market integration has a more significant effect on reducing the morbidity of male residents; in terms of age, the effect of market integration on reducing morbidity is particularly evident in elderly individuals, with each unit increase in the level of market integration reducing the probability of illness in elderly residents by approximately 6.72%. In terms of income, the impact of market integration on morbidity varies among different income groups and is more pronounced for low-income residents. After considering the impact of internet use on residents’ health, it was found that there is a synergistic effect between market integration and internet use on residents’ health.

The conclusions of this paper confirm the critical role of market integration development in improving residents’ health and provide empirical evidence and policy implications for protecting residents’ health rights in the future promotion of market integration. Based on the above conclusions, this paper has the following policy implications. First, strengthen investment in healthcare infrastructure, especially in underdeveloped regions. As market integration deepens and resources flow more broadly, the government should prioritize investment in healthcare infrastructure, particularly in remote and rural areas. Specific measures may include building more medical centers, general hospitals, and specialized medical institutions, expanding telemedicine networks, and increasing the training and deployment of primary healthcare personnel. Additionally, the construction of medical facilities in rural and urban fringe areas should be enhanced to reduce the gap in medical services between regions. Second, the state should properly utilize the information technology and communication means brought about by market integration and increase investment in health and nutrition education. By enhancing residents’ understanding of healthy diets and lifestyles, they can make healthier choices. For example, implement a nationwide health education program, especially targeting rural and low-income groups, utilizing various formats such as television, social media, and community activities to promote knowledge about healthy lifestyles and balanced diets. At the same time, the government can cooperate with the private sector to promote nutrient-rich foods and improve residents’ dietary structure. Third, relevant departments should pay attention to promoting labor market flexibility and protecting workers’ rights in the process of market integration. As market integration progresses, the structure and demand of the labor market are also changing. The government should promote the mobility of labor and the equalization of employment opportunities by enacting flexible labor policies and reforming labor laws. At the same time, workers’ rights should be protected, especially when facing economic transformation and new industry development, to prevent them from facing unemployment or health issues due to skill mismatches. Fourth, establish a collaborative mechanism between the market and the public health system. The government should create a mechanism that allows for the coordinated advancement of market integration and the development of the public health system. By strengthening cross-sector collaboration, it can ensure that public health resources are allocated reasonably alongside market integration. For example, enhancing the construction of health information systems will ensure that the data and information resources generated by market integration can also serve the public health sector, thereby improving health monitoring and early warning capabilities.

Electronic supplementary material

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Author contributions

All authors contributed to this manuscript, and all authors agreed to submit the manuscript.

Funding

The authors confirm that there is no funding for this publication.

Data availability

The data that support the findings of this study are available from China Health and Nutrition Survey (CHNS), but restrictions apply to the availability of these data, which were used under licence for the current study and so are not publicly available. The data are, however, available from the authors upon reasonable request and with the permission of China Health and Nutrition Survey (CHNS). The data can be found at: https://www.cpc.unc.edu/projects/china.

Declarations

Competing interests

The authors declare no competing interests.