Prevalence and factors associated with overweight and obesity in patients with severe mental disorders in Shenzhen: results from the urban Chinese population

doi:10.21203/rs.3.rs-1975014/v1

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Prevalence and factors associated with overweight and obesity in patients with severe mental disorders in Shenzhen: results from the urban Chinese population

https://doi.org/10.21203/rs.3.rs-1975014/v1

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Background: Although overweight and obesity are important risk factors for the physical health of severe mental disorders (SMD), few studies have been reported. Morbidity and mortality associated with physical disorders of SMD can be reduced if detected and managed in the early stages of physical disorders. The objective was to analyse the prevalence of overweight and obesity in patients with SMD and factors associated with sociodemographic and disease characteristics in a cross-sectional population-based study.

Methods: This analysis examined prevalence of overweight and obesity of 14,868 managed SMD patients in urban area of Shenzhen city, based on data from the information monitoring system in 2020. Sociodemographical and physiological characteristics of overweight and obesity of SMD patients were described. The multivariate logistic regression models were used to identify the factors associated with the prevalence of overweight and obesity of SMD.

Results: Records of 14, 868 participants were included for analysis. The prevalence of overweight and obesity in patients with SMD in this study was 32.6% and 16.1%, respectively. In multivariate analysis, married, Shenzhen household registration, number of years of management 5-10 years and >10 years, participation in family physician services, taking clozapine or aripiprazole, FPG>6.1 mmol/L, hypertension, TC≥5.2mmol/L, TG≥1.7mmol/L, the more frequent the number of follow-ups in the past year were associated with higher odds of overweight and obesity, while older, having tertiary education, and mental retardation with mental disorders had lower odds of overweight and obesity. Compared to their respective reference categories, living status with parents, spouse and children, taking risperidone, aripiprazole, amisulpride and perphenazine, FPG>6.1 mmol/L, hypertension, TC≥5.2mmol/L, TG≥1.7mmol/L, the more frequent the number of follow-ups in the past year were associated with higher odds of obesity, while having tertiary education and schizophrenia had lower odds of obesity.

Conclusions: We observed a high prevalence of overweight and obesity with SMD in this study. The findings highlight the need for integrated management of overweight and obesity risk factors among patients with SMD.

severe mental disorders

Overweight

Obesity

China

In China, severe mental disorders (SMD) mainly include six kinds: schizophrenia, bipolar disorder, schizoaffective disorder, paranoid psychosis, epilepsy-induced mental disorder, and mental retardation associated with mental disorder [1]. The burden of disease from SMD continues to rise, associated with poorer health outcomes and increased mortality, in addition to contributing to most of the prevalence [2]. The average death rate of patients with SMD is 2–3 times higher than that of the general population, and their life expectancy is shortened by 10–20 years [3]. Although people with SMD are at higher risk of death from unnatural causes than the general population, the majority of deaths among people with SMD are due to physical health conditions, both non-communicable and communicable. In addition, patients with SMD are more likely to have lifestyles that are risk factors for non-communicable diseases, such as lack of physical activity and unhealthy diets [4].

Obesity and overweight are a major risk factors for chronic non-communicable diseases. In 2019, the number of deaths due to chronic non-communicable diseases in China accounted for 88.5% of the total deaths, and the base number of patients with chronic diseases is still expanding [5, 6]. Obesity is considered as an independent risk factor for such cardiovascular diseases. Not only does it greatly increase the risk of cardiovascular diseases such as hypertension, coronary heart disease, myocardial infarction, angina pectoris and stroke, but it is also associated with increased mortality from cardiovascular diseases and cardiovascular diseases [7–9]. Patients with SMD are more severely affected by overweight and obesity, and the increase rate of obesity is higher than that of the general population [10, 11]. A survey in European and American countries reported that 26–55% of SMD were obesity, and the obesity rate of schizophrenia patients was about 4.3 times that of the general population [12–14]. A recent cross-sectional study in China reported that the obesity rate of schizophrenia was 16.4%-20.9% [15, 16], higher than that of the general population [17]. There is growing evidence that obesity and overweight lead to an increased incidence of cardiovascular disease, which in turn is the most common cause of SMD premature natural death [18]. Therefore, obesity and overweight pose a greater potential threat to the physical health of patients with SMD.

However, SMD for a variety of reasons have led to high obesity and overweight rates. Growing evidence has reported an association between the use of second-generation antipsychotics (SGAs) and an1 increased risk of obesity, weight gain, type 2 diabetes, and increased risk of dyslipidemia [19, 20]. Lack of exercise [21], sedentary lifestyle [22], poor diet [23], and adverse life events in childhood [24] are also important factors affecting obesity and overweight in patients with SMD. Other important factors include genetic susceptibility of patients, several psychosocial and socio-economic risk factors such as being female [25], older and lower educational level [26], etc. In the last decades, despite a series of governmental policies to improve the health status of patients with SMD living in the community, the overall quality of life remains relatively low [27].

Most studies have focused on schizophrenia, but there are relatively few reports on the study of bipolar disorder, schizoaffective disorder, paranoid psychosis, epileptic-induced mental disorder, mental retardation associated with mental disorders. In China, few large-sample studies have been reported on physical health of community-dwelling patients with SMD managed based on a health monitoring information system. Considering that patients with SMD return to the community after hospital discharge or outpatient, studying the physical health of such populations will be of great public health significance for targeted interventions and adjustment of health management strategies. The purpose of the present study was to examine the prevalence of overweight and obesity in patients with SMD and to identify the association between overweight and obesity and certain socio-demographic and clinical factors in these patients.

Data sources

All data for this study were obtained from the Shenzhen Mental Health Prevention and Control Management System. Shenzhen is a coastal city located in the south of Guangdong Province, China, with one of the highest economic levels in the country and a highly mobile population. By the end of December 2020, a total of 32,349 patients with server mental disorders were registered in the Shenzhen Mental Health Prevention and Control Management System. There were 31580 patients (97.62%) who accepted the community health management follow-up service, 448 patients (1.38%) refused services, and 321 patients (0.99%) missed visits. This information monitoring system was established and started to operate in 2006. The data system is managed by the professional staff of Shenzhen Mental Health Center.

First, there are two ways for screening and reporting of patients with SMD. One is screening and assessment of suspected patients by community workers based on the Abnormal Behavior Inventory and inviting psychiatrists to confirm the diagnosis. The other is an assessment and diagnosis by psychiatrists in medical institutions (psychiatric and non-psychiatric hospitals) based on the International Statistical Classification of Diseases and Related Health Problems (10th edition) (ICD-10). When a diagnosis of SMD (i.e., schizophrenia, bipolar disorder, schizoaffective disorder, paranoid psychosis, epilepsy-induced mental disorder, and mental retardation associated with mental disorder) is confirmed, the community health management program for SMD will be introduced. After the patient and guardian fully understand the program, they will voluntarily participate and sign an informed consent form, and then the psychiatrist will register the report in the Shenzhen Mental Health Prevention and Control Management System, and the relevant information will be transferred to the primary mental health institution in the area where the patient lives.

Second, establish health management cases for patients with diagnosed SMD. Patients were contacted by general practitioners from primary mental health institutions after uniform training and assessment to inform them about community health management and mental health policies. Standardized tools were used to collect sociodemographic information and assess the patient's mental status. After the individual health management case is established, the patient is formally integrated into community health management project and the first follow-up is conducted.

Third, follow-up. General practitioners in primary mental health institutions follow up patients according to their disease status, mainly assessing their recovery status, psychiatric symptoms, risk assessment, insight, medication compliance, adverse drug reactions, social function, and physical health status, and then judging the stability of the disease in order to adjust the follow-up cycle and adopt targeted health interventions. Follow-up is once every 3 months if the disease is stable; once every 1 month for basic stability; and once every half month for instability. During the follow-up period, patients could apply to enter or leave the cohort at any time. The study was approved by the Medical Ethics Review Committee of Shenzhen Kangning Hospital.

Study measures

We used body mass index (BMI) as the main outcome measure in the study of physical health management of SMD. Patients with SMD registered in the Shenzhen Mental Health Prevention and Control Management System will not only receive regular mental health assessments and health advice, but will also receive an annual health check-up according to their wishes, all of which are free of charge [28]. When a patient makes an appointment for a physical exam at a primary mental health facility, the general practitioners measures height and weight, and the patient wears light clothing and no shoes. BMI is defined as weight (kg) divided by the square of height (m2). Overweight and obesity are defined according to the cut-off values of BMI within the Chinese population [29]. BMI < 23.9 kg/m2 is considered normal weight or underweight, BMI ≥ 24-27.9 kg/m2 is considered overweight, and BMI ≥ 28 kg/m2 is considered obesity.

Statistical analyses

Statistical analyses were performed using SPSS version 21.0 and R version 3.5.1. We use the mean or median, as appropriate, to summarize the measured variables, while the count variables are reported as frequencies and percentages. Normality of continuous variables was tested with the Shapiro-Wilk test. The measurement data were analyzed using independent t-test and Wilcoxon rank test according to the normal distribution test, and chi-square test for the count data. One-way binary logistic regression was used to assess OR and 95% confidence intervals for factors associated with overweight and obesity (BMI ≥ 24 kg/m² vs BMI < 24 kg/m² ) and obesity (BMI ≥ 28 kg/m² vs BMI < 28 kg/m² ). Variables with statistically significant univariate analysis were again entered into a multivariate logistic regression model. Forest plots were performed using the R package "ForestPlot". A two-sided α = 0.05 was used as the test level, and P < 0.05 was considered a statistically significant.

General characteristics of the study population

The study included 14868 patients with SMD, 6932 males and 7936 females. The mean values of age, DUP, and years in custody were 41.79 years, 0.39 years, and 5.44 years, respectively; 8126 cases (54.7%) were married, 7356 (49.5%) were not employed, 3340 (22.5%) were in primary school and below, 1193 (8.0%) were living alone, 8881 (8.0%) were non-local household members ( 59.7%), 9388 (63.1%) without medical insurance, and 12,006 (80.8%) with non-poor family economy; the disease diagnosis was most often schizophrenia (57.2%), followed by bipolar disorder (24.7%);12,037 (81.0%) participated in family doctor service. There were 4841 (32.6%) overweight cases and 2396 (16.1%) obesity cases; the mean values of fasting blood glucose, TC and TG were 5.30 mmol/L, 4.74 mmol/L and 1.44 mmol/L. The mean values of fasting glucose, TC, and TG were 5.30 mmol/L, 4.74 mmol/L, and 1.44 mmol/L, respectively. SBP and DBP were 118.59 mm Hg and 75.27 mm Hg, respectively (Table 1).There were significant differences between men and women in Age, years of enrollment management, marriaged, employment status, level of education, living status, disease diagnosis, participate in family ph1ysician services, fasting glucose, TC, TG, BMI, SBP, DBP (Table 1).

Table 1

Sociodemographical and physiological characteristics of the study population in the study
variables	All(%), N = 14868	Male(%), N = 6932	Female(%), N = 7936	Statistics	P value
Age ^a (year)	41.79 (14.17)	39.32 (13.51)	43.95 (14.39)	-20.238	0.000
DUP ^b (year)	0.39 (0.08, 3.05)	0.37 (0.08,3.07)	0.41 (0.08,3.04)	-0.866	0.387
Number of years in the register ^a	5.44 (3.31)	5.56 (3.38)	5.33 (3.24)	4.301	0.000
FPG ^b (mmol/L)	5.30 (4.82, 5.86)	5.27 (4.80,5.80)	5.30 (4.89,5.90)	-5.147	0.000
TC ^b (mmol/L)	4.74 (4.09, 5.46)	4.72 (4.05,5.44)	4.75 (4.12,5.48)	-2.278	0.023
TG ^b (mmol/L)	1.44 (0.98, 2.18)	1.56 (1.04,2.38)	1.34 (0.92,2.02)	-12.178	0.000
BMI ^a (kg/m ²)	24.32 (4.07)	24.35 (3.89)	24.30 (4.22)	0.813	0.416
BMI				17.062	0.000
Normal	7631 (51.3)	3479 (50.2)	4152 (52.3)
Overweight	4841 (32.6)	2374 (34.2)	2467 (31.1)
Obesity	2396 (16.1)	1079 (15.6)	1317 (16.6)
SBP ^a (mm Hg)	118.59 (13.98)	120.26 (12.92)	117.13 (14.69)	13.815	0.000
DBP ^a (mm Hg)	75.27 (9.90)	76.42 (9.90)	74.26 (9.80)	13.346	0.000
Marriage				585.339	0.000
Single/divorced/widowed	6742 (45.3)	3876 (55.9)	2866 (36.1)
Married	8126 (54.7)	3056 (44.1)	5070 (63.9)
Employment				111.847	0.000
Unemployed	7356 (49.5)	3108 (44.8)	4248 (53.5)
employed	7512 (50.5)	3824 (55.2)	3688 (46.5)
education				95.195	0.000
primary school and below	3340 (22.5)	1312 (18.9)	2028 (25.6)
junior high school	5303 (35.7)	2554 (36.8)	2749 (34.6)
high school	3722 (25.0)	1847 (26.6)	1875 (23.6)
college school and above	2503 (16.8)	1219 (17.6)	1284 (16.2)
Living status				155.794	0.000
Alone	1193 (8.0)	651 (9.4)	542 (6.8)
with parents, spouse and children	12137 (81.6)	5374 (77.5)	6763 (85.2)
with siblings and relatives	1084 (7.3)	623 (9.0)	461 (5.8)
with friends and fellow villagers	412 (2.8)	261 (3.8)	151 (1.9)
with others	42 (0.3)	23 (0.3)	19 (0.2)
Type of household registration				2.445	0.118
Local	5987 (40.3)	2838 (40.9)	3149 (39.7)
Non-local	8881 (59.7)	4094 (59.1)	4787 (60.3)
Medical insurance				2.251	0.134
No	9388 (63.1)	4333 (62.5)	5055 (63.7)
Yes	5480 (36.9)	2599 (37.5)	2881 (36.3)
Family financial status				0.023	0.880
Below the local poverty standard	2862 (19.2)	1338 (19.3)	1524 (19.2)
Non-poverty	12006 (80.8)	5594 (80.7)	6412 (80.8)
Disease diagnosis				221.205	0.000
schizophrenia	8507 (57.2)	3695 (53.3)	4812 (60.6)
bipolar disorder	3675 (24.7)	1760 (25.4)	1915 (24.1)
schizoaffective disorder	666 (4.5)	266 (3.8)	400 (5.0)
delusional disorder	146 (1.0)	58 (0.8)	88 (1.1)
psychotic disorder due to epilepsy	421 (2.8)	246 (3.5)	175 (2.2)
mental retardation with mental disorders	1453 (9.8)	907 (13.1)	546 (6.9)
Participate in family physician services				4.368	0.037
No	2831 (19.0)	1270 (18.3)	1561 (19.7)
Yes	12037 (81.0)	5662 (81.7)	6375 (80.3)
^a Mean (standard deviation)
^b Median (interquartile range)
DUP, duration of untreated psychosis; FPG, fasting plasma glucose; TC, total cholesterol; TG, triglyceride; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure.

3.2 Logistic regression analysis of overweight and obesity

Table 2 shows the univariate logistic regression analysis for obesity or overweight. We found that age, marriage, education level, living status, type of household registration, schizophrenia, mental retardation with psychotic disorder, DUP, years of enrollment management, participation in family physician services, olanzapine, clozapine, risperidone, aripiprazole, amisulpride, FPG, hypertension, TC, TG, and number of follow-up in the past year were associated with overweight and obesity. Therefore, we included these factors in a multivariate logistic regression model for analysis.

Multivariate logistic regression analysis showed (Fig. 1) that age ≥ 60 years, education in high school and college school and above, and mental retardation with mental disorders had lower odds of overweight and obesity. While married, Shenzhen household registration, number of years of management 5–10 years, number of years of management > 10 years, participation in family physician services, clozapine, aripiprazole, FPG, hypertension, TC, TG, number of follow-ups in the past year were associated with higher odds of overweight and obesity.

Table 2

Results of univariate logistic regression analysis for overweight and obesity
variables	Number of cases (n = 7237)	OR(95%CI)	P-value
Gender(Female)	3784	0.92 (0.86–0.98)	0.010
Age(Ref: 18–44)
45–59	2335	1.41 (1.31–1.51)	0.000
≥ 60	899	1.45 (1.12–1.38)	0.000
Marriage (Married)	4273	1.41 (1.33–1.51)	0.000
Employment (employed)	3658	1.00 (0.94–1.07)	0.960
education (Ref: primary school and below)
junior high school	2720	1.06 (0.97–1.15)	0.211
high school	1755	0.90 (0.82–0.98)	0.021
college school and above	1095	0.78 (0.70–0.87)	0.000
Living status(Ref: Alone)
with parents, spouse and children	6069	1.35 (1.20–1.52)	0.000
with siblings and relatives	497	1.14 (0.97–1.35)	0.117
with friends and fellow villagers	145	0.73 (0.58–0.92)	0.009
with others	18	1.01 (0.54–1.88)	0.972
Type of household registration (Local)	4443	1.14 (1.07–1.22)	0.000
Medical insurance (Yes)	2621	0.95 (0.89–1.01)	0.115
Family financial status (Non-poverty)	5788	0.91 (0.84–0.99)	0.020
Disease diagnosis
schizophrenia	4284	1.17 (1.10–1.25)	0.000
bipolar disorder	1777	0.98 (0.91–1.06)	0.653
schizoaffective disorder	348	1.16 (0.99–1.36)	0.059
delusional disorder	65	0.85 (0.61–1.17)	0.313
psychotic disorder due to epilepsy	186	0.83 (0.68–1.01)	0.062
mental retardation with mental disorders	577	0.67 (0.60–0.75)	0.000
DUP (Ref: <2 year)
2–5 year	763	1.01 (0.91–1.13)	0.862
5–10 year	493	0.92 (0.81–1.05)	0.196
> 10 year	751	1.20 (1.07–1.34)	0.002
Number of years in the register (Ref:<2 year)
2–5 year	1975	1.16 (1.05–1.29)	0.003
5–10 year	3433	1.24 (1.13–1.36)	0.000
> 10 year	666	1.40 (1.22–1.60)	0.000
Participate in family physician services (Yes)	5974	1.22 (1.13–1.33)	0.000
Olanzapine (Yes)	2128	1.09 (1.01–1.17)	0.019
Clozapine (Yes)	1064	1.41 (1.28–1.56)	0.000
Risperidone (Yes)	1545	1.21 (1.11–1.31)	0.000
Quetiapine (Yes)	808	1.00 (0.90–1.11)	0.980
Ziprasidone (Yes)	126	1.10 (0.86–1.41)	0.459
Aripiprazole (Yes)	885	1.11 (1.00-1.22)	0.049
Amisulpride (Yes)	356	1.23 (1.06–1.44)	0.008
Perphenazine (Yes)	200	1.47 (1.18–1.82)	0.001
Sulpiride (Yes)	217	1.20 (0.98–1.46)	0.073
Lithium carbonate (Yes)	635	1.10 (0.98–1.23)	0.116
FPG (> 6.1 mmol/L)	1844	2.20 (2.02–2.39)	0.000
Hypertension (Yes)	857	2.45 (2.17–2.78)	0.000
TC (≥ 5.2mmol /L)	2057	1.76 (1.62–1.91)	0.000
TG (≥ 1.7mmol /L)	2704	2.92 (2.69–3.17)	0.000
Number of follow-ups in the past year (Ref: ≤4)
5–8	3640	1.37 (1.22–1.53)	0.000
9–12	2490	1.48 (1.29–1.70)	0.000
≥ 13	937	1.71 (1.40–2.10)	0.000
Number of face-to-face follow-ups in the past year (Ref: ≤2)
3–4	365	0.99 (0.67–1.46)	0.957
5–6	2209	1.31 (0.91–1.89)	0.152
≥7	4615	1.58 (1.10–2.29)	0.014

3.3 Logistic regression analysis of obesity

Table 3 shows the univariate logistic regression analysis for obesity. We found that marriage, employment status, level of education, living status, medical insurance, family financial status, schizophrenia, bipolar disorder, number of years in the register, participate in family physician services, clozapine, risperidone, aripiprazole, amisulpride, perphenazine, FPG, hypertension, TC, TG, and number of follow-ups in the past year were associated with obesity. Therefore, we included these factors in a multivariate logistic regression model for analysis.

Multivariate logistic regression analysis showed that education in high school, college school and above, and schizophrenia had lower odds of obesity. While living status with parents, spouse and children, risperidone, aripiprazole, amisulpride, perphenazine, FPG, hypertension, TC, TG, number of follow-ups in the past year were associated with higher odds of obesity (Fig. 2).

Table 3

Results of univariate logistic regression analysis for obesity
Variables	Number of cases (n = 2396)	OR(95%CI)	P-value
Gender (Female)	1317	1.08 (0.99–1.18)	0.088
Age (Ref: 18–44)
45–59	729	1.07 (0.97–1.18)	0.195
≥60	262	0.92 (0.80–1.06)	0.240
Marriage (Married)	1372	1.13 (1.04–1.24)	0.005
Employment (employed)	1143	0.87 (0.80–0.95)	0.003
Level of education (Ref: primary school and below)
junior high school	888	0.90 (0.81–1.01)	0.081
high school	582	0.83 (0.74–0.94)	0.004
college school and above	318	0.65 (0.57–0.76)	0.000
Living status (Ref: Alone)
with parents, spouse and children	2041	1.47 (1.23–1.76)	0.000
with siblings and relatives	162	1.28 (1.01–1.63)	0.045
with friends and fellow villagers	47	0.94 (0.66–1.33)	0.720
with others	2	0.36 (0.09–1.52)	0.167
Type of household registration (Local)	1466	1.08 (0.98–1.18)	0.113
Medical insurance (Yes)	840	0.91 (0.83-1.00)	0.046
Family financial status (Non-poverty)	1885	0.86 (0.77–0.95)	0.005
Disease diagnosis
schizophrenia	1417	1.10 (1.01–1.20)	0.038
bipolar disorder	550	0.89 (0.80–0.99)	0.029
schizoaffective disorder	123	1.19 (0.97–1.45)	0.091
delusional disorder	17	0.68 (0.41–1.14)	0.142
psychotic disorder due to epilepsy	63	0.91 (0.70–1.20)	0.515
mental retardation with mental disorders	226	0.95 (0.82–1.11)	0.540
DUP (Ref: <2 year)
2–5 year	252	1.00 (0.87–1.16)	0.999
5–10 year	171	1.01 (0.84–1.19)	0.993
>10 year	234	1.03 (0.89–1.20)	0.711
Number of years in the register (Ref:<2 year)
2–5 year	649	1.11 (0.96–1.27)	0.150
5–10 year	1137	1.16 (1.02–1.32)	0.021
> 10 year	228	1.30 (1.08–1.56)	0.005
Participate in family physician services (Yes)	2001	1.23 (1.09–1.38)	0.001
Olanzapine (Yes)	673	0.98 (0.89–1.08)	0.617
Clozapine (Yes)	352	1.22 (1.08–1.38)	0.002
Risperidone (Yes)	543	1.23 (1.10–1.36)	0.000
Quetiapine (Yes)	274	1.03 (0.90–1.19)	0.638
Ziprasidone (Yes)	50	1.33 (0.97–1.82)	0.076
Aripiprazole (Yes)	323	1.22 (1.07–1.39)	0.003
Amisulpride (Yes)	135	1.35 (1.11–1.64)	0.002
Perphenazine (Yes)	81	1.62 (1.26–2.08)	0.000
Sulpiride (Yes)	67	1.02 (0.78–1.33)	0.882
Lithium carbonate	213	1.08 (0.92–1.26)	0.353
FPG (> 6.1 mmol/L)	723	2.08 (1.88–2.30)	0.000
Hypertension (Yes)	376	2.46 (2.16–2.80)	0.000
TC ≥ 5. 2 (mmol /L)	745	1.60 (1.44–1.77)	0.000
TG ≥ 1.7 (mmol /L)	1025	2.49 (2.25–2.77)	0.000
Number of follow-ups in the past year (Ref: ≤4)
5–8	1133	1.44 (1.21–1.71)	0.000
9–12	856	1.70 (1.40–2.08)	0.000
≥ 13	353	2.03 (1.55–2.65)	0.000
Number of face-to-face follow-ups in the past year (Ref: ≤2)
3–4	115	1.08 (0.60–1.96)	0.789
5–6	671	1.25 (0.71–2.19)	0.438
≥ 7	1596	1.64 (0.94–2.87)	0.084

This is the first community-based study to explore the physical health of SMD in China. The results of the study are important scientific guidance for improving community management strategies and measures for SMD and improving the physical health level of patients. In this study, we found that about half of the participants were overweight and obesity. Married, Shenzhen household registration, management years 5–10 years, management years > 10 years, participation in family physician services, clozapine, aripiprazole, FPG, hypertension, TC, TG, number of follow-ups in the past year had a higher risk of overweight and obesity. Age ≥ 60, high school, college school and above, and mental retardation with mental disorders were less likely to be overweight and obesity. All these data suggest that obesity in SMD has become a serious public health burden for the Chinese population and needs more attention and intervention.

We found that the prevalence of obesity in patients with SMD in Shenzhen was close to the prevalence of obesity in the general population [30], but higher than the average of the general population in large cities [31]. The findings are also similar to the survey results of obesity (16%-20%) of schizophrenia patients in China [15, 32]. Meanwhile, we found that the prevalence of overweight in patients with SMD in Shenzhen was lower than that of the general population and the general population in large cities, but was close to the global findings on the overweight rate of patients with SMD [30, 31, 33]. A study from 39,034 rural adults showed that the overweight rate in the rural population was 34.5% and the obesity rate was 16.8%, both of which our study found to be below this level[34]. The possible reasons for this phenomenon are as follows: First of all, our research population is concentrated in Shenzhen, a city with 100% urbanization rate in China, and its economy is relatively developed. Residents have more labor opportunities and exercise space, so they can get more exercise. Second, urban residents have access to more medical resources and more health knowledge. Since 2010, the Chinese government has carried out a number of national prevention and control programs for obesity [35]. And the result shave shown that interventions tend to be implemented and effective in urban areas, but have little effect in rural areas [36]. Thirdly, population migration leads to a change in diet structure, and Shenzhen is dominated by internal migrant population. Related studies have shown [37] that changes in diet structure are more likely to lead to obesity, especially animal-based diet, and urban residents are more likely to take in more protein. Fourthly, patients with SMD have a sense of stigma [38], and the stress caused by low income, unemployment and discrimination can not only affect their recovery and life, but also lead to obesity [39].

Although antipsychotic drugs can better for treat psychiatric disorders, they can also cause a number of problems such as metabolic disorders [40–42]. In our study, patients with SMD treated with clozapine and aripiprazole were more likely to be overweight and obesity, while patients with SMD treated with perphenazine, risperidone, Aripiprazole and amsulfamide were more likely to be obesity. This finding is consistent with most research reports that antipsychotics might reduce the body's caloric consumption, leading to increased appetite in patients who, in turn, lack sufficient exercise, leading to weight gain [40–43]. Previous studies have reported [9, 44, 45] that obesity and overweight can lead to vascular aging, dyslipidemia and carotid atherosclerosis, impaired glucose tolerance and abnormal blood glucose, increasing the risk of hypertension [46], coronary atherosclerotic heart disease [47], type 2 diabetes [48], stroke and many cancers [49, 50]. In this study, we found an association between overweight and obesity and hypertension, TC, TG [32], and FPG [9] in patients with SMD, suggesting an increased risk of cardiovascular disease.

Interestingly, not all patients with SMD are prone to obesity and overweight. Our study found that mental retardation with mental disorders had a lower risk of obesity and overweight, while schizophrenia had a lower risk of obesity. Most patients with mental retardation had difficulty in self-care and require care from others, and those with severe disabilities can become completely disabled, with refusal to eat and occasional self-vomiting likely to be the main causes of this phenomenon [51], which is more likely to occur with mental retardation with mental disorders. More than half of the SMD participating in this study were community-dwelling patients with schizophrenia, and most of them were non-local residents who need to participate in work to pay for various living expenses and medical expenses [52].

However, physical health management in community mental health services needs more attention in the future. Our study found that patients with SMD who participated in family physician services, had longer years of management, and had more follow-up visits were more likely to be overweight and obesity. The possible reason is that community mental health services in China have always been focused on providing better mental health services and rehabilitation services for patients with SMD, while paying less attention to their physical health and lack of relevant physical health management [53]. At present, the family physician service is in the initial stage in China, and there are still many deficiencies. Meanwhile, there is a large gap in the quality assurance of primary health care in China, and the education and training of primary health care practitioners are poor, which requires a more complete work training system and higher training quality [54].

In addition, our study identified several risk factors for obesity in Chinese patients with SMD. Married patients with SMD were more likely to be obesity and overweight. Studies have shown that having a partner is more likely to lead to overweight and obesity [55, 56]. Men and women are more than twice as likely to become obesity after marriage as single people, and obesity in one spouse will increase the risk of obesity on the other. At the same time, we also found that patients with Shenzhen household registration, living with parents, spouses or children were more prone to overweight and obesity. The possible reason for this phenomenon is that patients with registered residence in Shenzhen have better treatment in social welfare, medical insurance, housing and other aspects than those without registered residence. Patients living with parents, spouse or children may get better care and easily form a sedentary and eating lifestyle, which leads to obesity and overweight. Furthermore, in our study, patients with SMD with higher education were less likely to be overweight and obesity than those with lower education. Previous studies have confirmed that people with low education are more likely to be obesity and overweight. People's education will affect people's way of life. People with high education may pay more attention to maintaining physical fitness and healthy diet, and are more willing to go out.

The advantage of our study is that we provide population-based data on the physical health of patients with SMD in Chinese communities. However, there are still several deficiencies in this study. First of all, the server mental disorders involved in this study were all patients receiving community mental health services, so more epidemiological investigations with large samples are needed to obtain more representative research results. Second, there is no variable data in the study such as exercise, eating habits, lifestyle, genomics data, and more antipsychotic drug use data that are considered to be potential risk factors for BMI.

In summary, we reported a high prevalence of overweight and obesity in patients with SMD in the community, and their physical health is often neglected. Our study provides insights into the intervention of controllable risk factors for overweight and obesity in Chinese patients with SMD. Research on the physical health of this population will have great public health significance for targeted interventions and adjustment of health management strategies, and more efforts should be made to improve the overall management of people with SMD in urban communities.

Ethics approval and consent to participate

All procedures performed in this study was in accordance with the ethical standards of the institutional, national and international research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study protocol was approved by the Human Ethics Committee of Shenzhen Kangning Hospital (NO. 2022-07-29-1). All the respondents participated in the study with informed consent before the investigation.

Consent for publication

Not applicable.

Availability of data and materials

The datasets generated and/or analysed during the current study are not publicly available due The data from this study are under certain restrictions according to the Shenzhen Municipal Health Commission and always under the supervision of the principal investigator of the study but are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This study was supported by the by Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties (No.SZGSP013) and Shenzhen Key Medical Discipline Construction Fund (No.SZXK072).

Authors’ contributions

Xiaodong Peng and Wei Shan participated in the study design and wrote the initial draft of the paper. Zhijian Zhou and Guojun Wang participated in the data analysis and revised the manuscript. Tiebang Liu participated in the design of the study and critically revised the manuscript. All authors critically reviewed the draft and helped revise the manuscript. All authors read and approved the final manuscript.

Practice for management and treatment of severe mental disorders (2018) [http://www.gov.cn/gongbao/content/2018/content_5338247.htm.]
Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet 2017, 390(10100):1260–1344.
Liu NH, Daumit GL, Dua T, Aquila R, Charlson F, Cuijpers P, Druss B, Dudek K, Freeman M, Fujii C et al: Excess mortality in persons with severe mental disorders: a multilevel intervention framework and priorities for clinical practice, policy and research agendas. World Psychiatry 2017, 16(1):30–40.
Correll CU, Solmi M, Veronese N, Bortolato B, Rosson S, Santonastaso P, Thapa-Chhetri N, Fornaro M, Gallicchio D, Collantoni E et al: Prevalence, incidence and mortality from cardiovascular disease in patients with pooled and specific severe mental illness: a large-scale meta-analysis of 3,211,768 patients and 113,383,368 controls. World Psychiatry 2017, 16(2):163–180.
Report on Nutrition and Chronic Disease Status of Chinese Residents (2020). In., vol. 42. Acta Nutrimenta Sinica; 2020: 521.
Dhawan D, Sharma S: Abdominal Obesity, Adipokines and Non-communicable Diseases. J Steroid Biochem Mol Biol 2020, 203:105737.
Piché ME, Tchernof A, Després JP: Obesity Phenotypes, Diabetes, and Cardiovascular Diseases. Circ Res 2020, 126(11):1477–1500.
Fontaine KR, Redden DT, Wang C, Westfall AO, Allison DB: Years of life lost due to obesity. Jama 2003, 289(2):187–193.
Powell-Wiley TM, Poirier P, Burke LE, Després JP, Gordon-Larsen P, Lavie CJ, Lear SA, Ndumele CE, Neeland IJ, Sanders P et al: Obesity and Cardiovascular Disease: A Scientific Statement From the American Heart Association. Circulation 2021, 143(21):e984-e1010.
Holt RI, Peveler RC: Obesity, serious mental illness and antipsychotic drugs. Diabetes Obes Metab 2009, 11(7):665–679.
Holt RI: Obesity - an epidemic of the twenty-first century: an update for psychiatrists. J Psychopharmacol 2005, 19(6 Suppl):6–15.
Manu P, Dima L, Shulman M, Vancampfort D, De Hert M, Correll CU: Weight gain and obesity in schizophrenia: epidemiology, pathobiology, and management. Acta Psychiatr Scand 2015, 132(2):97–108.
Janssen EM, McGinty EE, Azrin ST, Juliano-Bult D, Daumit GL: Review of the evidence: prevalence of medical conditions in the United States population with serious mental illness. Gen Hosp Psychiatry 2015, 37(3):199–222.
Gurpegui M, Martínez-Ortega JM, Gutiérrez-Rojas L, Rivero J, Rojas C, Jurado D: Overweight and obesity in patients with bipolar disorder or schizophrenia compared with a non-psychiatric sample. Prog Neuropsychopharmacol Biol Psychiatry 2012, 37(1):169–175.
Wang J, Zhang Y, Yang Y, Liu Z, Xia L, Li W, Li Z, Xie X, Deng W, Zhang K et al: The prevalence and independent influencing factors of obesity and underweight in patients with schizophrenia: a multicentre cross-sectional study. Eat Weight Disord 2021, 26(5):1365–1374.
Li Q, Du X, Zhang Y, Yin G, Zhang G, Walss-Bass C, Quevedo J, Soares JC, Xia H, Li X et al: The prevalence, risk factors and clinical correlates of obesity in Chinese patients with schizophrenia. Psychiatry Res 2017, 251:131–136.
Obesity and overweight [https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight.]
Brown S, Kim M, Mitchell C, Inskip H: Twenty-five year mortality of a community cohort with schizophrenia. Br J Psychiatry 2010, 196(2):116–121.
Leucht S, Cipriani A, Spineli L, Mavridis D, Orey D, Richter F, Samara M, Barbui C, Engel RR, Geddes JR et al: Comparative efficacy and tolerability of 15 antipsychotic drugs in schizophrenia: a multiple-treatments meta-analysis. Lancet 2013, 382(9896):951–962.
Stroup TS, Gray N: Management of common adverse effects of antipsychotic medications. World Psychiatry 2018, 17(3):341–356.
Vancampfort D, Probst M, Sweers K, Maurissen K, Knapen J, De Hert M: Relationships between obesity, functional exercise capacity, physical activity participation and physical self-perception in people with schizophrenia. Acta Psychiatr Scand 2011, 123(6):423–430.
Janney CA, Ganguli R, Tang G, Cauley JA, Holleman RG, Richardson CR, Kriska AM: Physical activity and sedentary behavior measured objectively and subjectively in overweight and obese adults with schizophrenia or schizoaffective disorders. J Clin Psychiatry 2015, 76(10):e1277-1284.
Sugawara N, Yasui-Furukori N, Sato Y, Saito M, Furukori H, Nakagami T, Ishioka M, Kaneko S: Dietary patterns are associated with obesity in Japanese patients with schizophrenia. BMC Psychiatry 2014, 14:184.
Guenzel N, Houfek J, Watanabe-Galloway S: Adverse Events in Childhood as a Risk Factor for Elevated BMI among People with Schizophrenia and Bipolar Disorder. Issues Ment Health Nurs 2016, 37(11):829–838.
Hui L, Ye M, Tang W, Zhang F, Liu J, Liu L, Chen Y, Chen DC, Tan YL, Yang FD et al: Obesity correlates with fewer symptoms in schizophrenia treated with long-term clozapine: gender difference. Psychiatry Res 2015, 225(3):741–742.
Subramaniam M, Lam M, Guo ME, He VY, Lee J, Verma S, Chong SA: Body mass index, obesity, and psychopathology in patients with schizophrenia. J Clin Psychopharmacol 2014, 34(1):40–46.
Peng X, Wang S, Bi J, You L, Zhou Z, Tan W, Xie H, Hu C, Ng CH, Liu T: Gender differences in socio-demographics, clinical characteristic and quality of life in patients with schizophrenia: A community-based study in Shenzhen. Asia Pac Psychiatry 2021, 13(2):e12446.
National Basic Public Health Service Specifications (Third Edition) [http://www.nhc.gov.cn/jws/s3578/201703/d20c37e23e1f4c7db7b8e25f34473e1b.shtml]
Wu Y, Huxley R, Li L, Anna V, Xie G, Yao C, Woodward M, Li X, Chalmers J, Gao R et al: Prevalence, awareness, treatment, and control of hypertension in China: data from the China National Nutrition and Health Survey 2002. Circulation 2008, 118(25):2679–2686.
Pan XF, Wang L, Pan A: Epidemiology and determinants of obesity in China. Lancet Diabetes Endocrinol 2021, 9(6):373–392.
He Y, Zhao W, Zhang J, Zhao L, Yang Z, Huo J, Yang L, Wang J, He L, Sun J et al: Data Resource Profile: China National Nutrition Surveys. Int J Epidemiol 2019, 48(2):368-368f.
Tian Y, Liu D, Wang D, Wang J, Xu H, Dai Q, Andriescue EC, Wu HE, Xiu M, Chen D et al: Obesity in Chinese patients with chronic schizophrenia: Prevalence, clinical correlates and relationship with cognitive deficits. Schizophr Res 2020, 215:270–276.
Afzal M, Siddiqi N, Ahmad B, Afsheen N, Aslam F, Ali A, Ayesha R, Bryant M, Holt R, Khalid H et al: Prevalence of Overweight and Obesity in People With Severe Mental Illness: Systematic Review and Meta-Analysis. Front Endocrinol (Lausanne) 2021, 12:769309.
Liu X, Wu W, Mao Z, Huo W, Tu R, Qian X, Zhang X, Tian Z, Zhang H, Jiang J et al: Prevalence and influencing factors of overweight and obesity in a Chinese rural population: the Henan Rural Cohort Study. Sci Rep 2018, 8(1):13101.
Wang L, Zhou B, Zhao Z, Yang L, Zhang M, Jiang Y, Li Y, Zhou M, Wang L, Huang Z et al: Body-mass index and obesity in urban and rural China: findings from consecutive nationally representative surveys during 2004-18. Lancet 2021, 398(10294):53–63.
Pfledderer CD, Burns RD, Byun W, Carson RL, Welk GJ, Brusseau TA: School-based physical activity interventions in rural and urban/suburban communities: A systematic review and meta-analysis. Obes Rev 2021, 22(9):e13265.
Shu L, Zheng PF, Zhang XY, Si CJ, Yu XL, Gao W, Zhang L, Liao D: Association between Dietary Patterns and the Indicators of Obesity among Chinese: A Cross-Sectional Study. Nutrients 2015, 7(9):7995–8009.
Hampson ME, Watt BD, Hicks RE: Impacts of stigma and discrimination in the workplace on people living with psychosis. BMC Psychiatry 2020, 20(1):288.
Tomiyama AJ: Stress and Obesity. Annu Rev Psychol 2019, 70:703–718.
De Hert M, Detraux J, van Winkel R, Yu W, Correll CU: Metabolic and cardiovascular adverse effects associated with antipsychotic drugs. Nat Rev Endocrinol 2011, 8(2):114–126.
Schneider-Thoma J, Chalkou K, Dörries C, Bighelli I, Ceraso A, Huhn M, Siafis S, Davis JM, Cipriani A, Furukawa TA et al: Comparative efficacy and tolerability of 32 oral and long-acting injectable antipsychotics for the maintenance treatment of adults with schizophrenia: a systematic review and network meta-analysis. Lancet 2022, 399(10327):824–836.
Cernea S, Dima L, Correll CU, Manu P: Pharmacological Management of Glucose Dysregulation in Patients Treated with Second-Generation Antipsychotics. Drugs 2020, 80(17):1763–1781.
Zhang Q, Lian J, He M, Deng C, Wang H, Huang XF: Olanzapine reduced brown adipose tissue thermogenesis and locomotor activity in female rats. Prog Neuropsychopharmacol Biol Psychiatry 2014, 51:172–180.
Chen Z, Iona A, Parish S, Chen Y, Guo Y, Bragg F, Yang L, Bian Z, Holmes MV, Lewington S et al: Adiposity and risk of ischaemic and haemorrhagic stroke in 0·5 million Chinese men and women: a prospective cohort study. Lancet Glob Health 2018, 6(6):e630-e640.
Organization WH: Management of physical health conditions in adults with severe mental disorders. In., edn.; 2018: 89.
Harvey A, Montezano AC, Touyz RM: Vascular biology of ageing-Implications in hypertension. J Mol Cell Cardiol 2015, 83:112–121.
Roos CJ, Quax PH, Jukema JW: Cardiovascular metabolic syndrome: mediators involved in the pathophysiology from obesity to coronary heart disease. Biomark Med 2012, 6(1):35–52.
Vancampfort D, Stubbs B, Mitchell AJ, De Hert M, Wampers M, Ward PB, Rosenbaum S, Correll CU: Risk of metabolic syndrome and its components in people with schizophrenia and related psychotic disorders, bipolar disorder and major depressive disorder: a systematic review and meta-analysis. World Psychiatry 2015, 14(3):339–347.
Jahromi AS, Shojaei M, Ghobadifar MA: Insulin resistance and serum levels of interleukin-17 and interleukin-18 in normal pregnancy. Immune Netw 2014, 14(3):149–155.
Vucenik I, Stains JP: Obesity and cancer risk: evidence, mechanisms, and recommendations. Ann N Y Acad Sci 2012, 1271(1):37–43.
Hove O: Weight survey on adult persons with mental retardation living in the community. Res Dev Disabil 2004, 25(1):9–17.
Younger DS: Health Care in China. Neurol Clin 2016, 34(4):1115–1125.
Liang D, Mays VM, Hwang WC: Integrated mental health services in China: challenges and planning for the future. Health Policy Plan 2018, 33(1):107–122.
Li X, Krumholz HM, Yip W, Cheng KK, De Maeseneer J, Meng Q, Mossialos E, Li C, Lu J, Su M et al: Quality of primary health care in China: challenges and recommendations. Lancet 2020, 395(10239):1802–1812.
The NS, Gordon-Larsen P: Entry into romantic partnership is associated with obesity. Obesity (Silver Spring) 2009, 17(7):1441–1447.
Cobb LK, McAdams-DeMarco MA, Gudzune KA, Anderson CA, Demerath E, Woodward M, Selvin E, Coresh J: Changes in Body Mass Index and Obesity Risk in Married Couples Over 25 Years: The ARIC Cohort Study. Am J Epidemiol 2016, 183(5):435–443.

No competing interests reported.

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Prevalence and factors associated with overweight and obesity in patients with severe mental disorders in Shenzhen: results from the urban Chinese population

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