Health-related quality of life and associations on socio-demographic and clinical factors in schizophrenia based on the QLICD-SC scale: A cross-sectional study

doi:10.21203/rs.3.rs-1970127/v2

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Health-related quality of life and associations on socio-demographic and clinical factors in schizophrenia based on the QLICD-SC scale: A cross-sectional study

https://doi.org/10.21203/rs.3.rs-1970127/v2

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Purpose

This paper aimed at providing evidence for developing countermeasures to improve patients’ quality of life by using the scale Quality of Life Instruments for Chronic Diseases-Schizophrenia (V2.0)(QLICD-SC)), which is modular and sensitivity.

Methods

163 people who met the diagnostic criteria for schizophrenia of the International Classification of Diseases(10th Revision) and were hospitalized at the Affiliated Hospital of Guangdong Medical University from May 2014 to December, 2015 were selected. Patients' clinical objective indexes, including blood routine, urine routine, blood biochemical examination, blood gas analysis etc. were collected by reviewing the medical records. Patients were assessed by the QLICD-SC (V2.0), a quality of life measurement scale for Schizophrenia. Simple correlation analysis was used to explore the correlation between the QLICD-SC (V2.0) scores and various clinical objective indicators, and multiple linear regression was used to further screen for correlates.

Results

There were 163 participants, ranging in age from 16 to 69, with a 30.67 ± 11.44 average age. The majority of them were men(57.1%), had a high school diploma(77.9%), and were married (65.6%). According to multiple linear regression, the variables included in the model are education, sex, eosinophilic granulocyte, hematocrit, percentage of monocytes, phosphorus (R² = 0.065 ~ 0.222, P < 0.05).

Conclusion

Some clinical indicators such as hematocrit and socio-demographic factors may reflect alterations in the quality of life of individuals with schizophrenia.

Quality of life

schizophrenia

associations

socio-demographic factors

clinical indicators

Schizophrenia is a serious mental disease and symptoms range widely, such as hallucinations and delusions, which may shorten patients’ life expectancy for about 15 years because it increases their suicide risk by approximately 10 percent [1, 2]. Currently, the lifetime prevalence of schizophrenia takes up around 1 percent all over the world [3], and that rate in China is 0.61 percent according to the China Mental Health Survey (CMHS). Although the figure is not extremely high, considering China’s population of 1.4 billion, indicates that a large number of people suffer from mental disorders [4]. Worse still, schizophrenia is a long course of disease with high recurrence rate, resulting in long-term drug treatment but is slow-acting and often produces side effects [5]. This highlights the importance of enhancing the Quality of life( QOL) also called Health-Related Quality of Life (HRQOL) for schizophrenic people in China. During this long-term treatment process, doctors will be able to manage therapeutic regimens more effectively, according to the factors that affect the patient’s HRQOL.

The World Health Organisation (WHO) (1998) provides a definition for QOL: The survival experiences of people in various cultures and value systems in relation to their objectives, standards, and priorities [6]. QOL provides crucial information about a person's emotional and social experience that is unattainable through traditional assessments [7]. Nowadays, QOL is an increasingly important area in health and medicine [8] so scientific scales in a multidimensional manner have been instrumental in the understanding of it [9, 10, 11], such as the quality of life scale (QOLS) [9], generic quality of life inventory —74 (GQOLI-74) [10], 36 Health Survey (SF-36) and the WHO Quality of Life Scale Brief Version (WHOQOL-BREF) [11]. But these generic scales are not specific and insensitive enough and fail to reflect the HRQOL of patients comprehensively [12]. For instance, using SF-36 to compare the HRQOL in schizophrenia and multiple sclerosis revealed that both groups' impairment was similar [13]. Apart from that, some modular and systematic scales are available, such as the Schizophrenia quality of life scale(SQLS), which is consisted of psychological aspects, motivation and energy as well as symptoms and side-effects but without social domain [14]. However, prejudice and discrimination by society may pose burdens to mental and physical health affecting patients’ HRQOL. Additionally, the 18-item Schizophrenia Quality of Life Questionnaire (S-QoL18), which has eight aspects and is shorter for more broad use in clinical practice [15], needs to have its sensitivity to change confirmed. Most importantly, the scales above are foreign versions whose validation may be affected if used in China directly. For this purpose, we have developed Quality of Life Instruments for Chronic Diseases-Schizophrenia (V2.0)(QLICD-SC) [16], which was used in this paper to examine the HRQOL status and its influencing factors of Chinese people. QLICD is a Chinese QOL tool system referred to as ‘Quality of Life Instruments for Chronic Disease’, which integrates Chinese culture, rendering it more suitable for Chinese people. Moreover, general modules and specific modules are included.

In recent years, scholars have concluded that schizophrenics' HRQOL is influenced by gender, employment status, monthly income, and social support [17, 18, 19]. However, focusing on socio-demographic elements alone is far from enough. Instead, clinical objective indicators may influence HRQOL. There may be a material basis for HRQOL, and whether there is a correlation between macroscopic HRQOL performance and microscopic experimental indicators needs to be explored. A wide range of studies have revealed that people with schizophrenia have abnormally high amounts of inflammatory cytokines in their blood [20, 21]. Yüksel et al. pointed out that Galectin-1 could be a predictive biomarker for the development of schizophrenia and higher tumor necrosis factor-α(TNF-α) and interleukin-6 (IL-6)levels can be found in schizophrenia patients [22]. Therefore, the aim of this paper was to explore the connection between HRQOL and socio-demographic factors as well as HRQOL and objective clinical indicators. It is hoped that this research will contribute to a deeper understanding of the link among these factors and HRQOL which helps future clinical treatment intervention and further enhance the HRQOL of patients.

Study design and setting

A Cross-sectional Study was conducted with persons who fit the criteria from the Affiliated Hospital of Guangdong Medical University in Zhanjiang, China, between May 2014 and December, 2015. Zhanjiang is a coastal city in Guangdong Province, which is situated in south of China.

Participants

All schizophrenia in-patients at this hospital who met the criteria throughout the survey period were selected to participate in the study using cluster random sampling method. Inclusion criteria: (1) Patients were given a schizophrenia diagnosis according to the ICD-10 diagnostic criteria. (2) Patients with conscious state; (3) Primary school education or above, able to complete the questionnaire independently; (4) Informed consent: patients who voluntarily participate in the investigation and sign the informed consent form. Exclusion criteria: (1) patients suffering from mental disorders due to hypoevolutismus, brain organic disease or somatic diseases; (2) patients suffering from mental disorders due to the use of psychoactive substances or patients who have used psychoactive drugs; (3) patients suffering from mental derangement or acute psychotic episodes; (4) Critical and uncooperative patients.

Instruments and variables

QLICD-SC (V2.0) used as a survey tool in the present study is the schizophrenia scale in the Quality of Life Instruments for Chronic Diseases, whose split-half reliability is 0.920 and Cronbach α is 0.910, indicating that it has good internal consistency, reliability and an ability to reflect the real feeling of patients correctly. The standardized response mean(SRM) of QLICD-SC(V2.0) is higher than 0.20, indicating good scale responsiveness [24]. The QLICD-SC (V2.0) consists of a general module (QLICD-GM) and a schizophrenia specific module involving 13 items, in which QLICD-GM includes physiological function (9 items), psychological function (11 items), social function (8 items), in total, 3 domains, 9 sides and 28 items. The whole scale has 41 items, each of which is a five-level hierarchical item. In terms of scoring method, the original score is the item score for positive items, while for negative items, they should be subtracted the original score from 6 to obtain the item score. A higher score of positive items indicates a better HRQOL, but a higher score of reverse items indicates a worse HRQOL. The scores in each domain are added up result in a total original score, which will be transformed into the standard score (SS) by extremum difference analysis, that is, SS = (RS min) × 100/R [25] to facilitate comparison. SS is standardized score, RS is raw score, Min is minimum score, and R is range of scores. Also, a self-made general information questionnaire including socio-demographic characteristics was used during the survey.

Survey Methods

Only schizophrenic patients who could read and interpret the questionnaires were allowed to participate in the study. The investigators (a well-trained medical student) introduced the survey and the questionnaires to the patients on the second day of their hospitalization and received their informed consent from those who accepted to participate in the study and met the inclusion criteria. During their 15-minute interview with an investigator, these participants were requested to complete the QLICD-SC and the general information questionnaire. Investigators reviewed the answers right away to make sure they were complete. 60 biochemical indexes such as granulocyte, hematocrit, percentage of monocytes, phosphorus, etc. were collected from the hospital medical record information systems including biochemical blood tests, liver function tests, routine urine tests and blood routine and so on.

Statistical analysis

Epidata 3.1 was used to input the initial data, while SPSS was used to conduct the statistical analysis. First, statistical description was applied to analyze the distribution of basic characteristics as well as the total score and domain scores of HRQOL of patients with schizophrenia. Then due to the large number of clinical indicators, a simple correlation analysis was conducted with the scores of HRQOL which included physical, psychological and social function, the specific module, and the total score of the scale to screen statistically significant indicators. Finally, the multiple linear regression (backward method) was used to screen the association factors with the inclusion standard (p-in) is 0.05 and the exclusion standard (p-out) is 0.10.

In the process of data collection, some socio-demographic factors were missed due to the research patients' failure or reluctance to provide information. The lack of clinical objective indicators may be because these patients were not required to measure certain items, or researchers failed to record the items in time, and they were absent at random. Indicators with an excessive amount of missing data were removed.

Quality Control

The present study measured patients' HRQOL using the QLICD-SC (V2.0), a specificity scale for schizophrenia, to prevent some biases and guarantee high quality. The researchers briefly introduced the survey to patients and delivered the scale after obtaining the patients' agreement. They were expected to supervise and assist nearby, whilst explaining the content of the scale if necessary. Then, they rechecked the data immediately and used proper methods to analyze it.

Sample characteristics

The sample characteristics of 163 patients with schizophrenia are presented in Table 1. The patients were aged 11 to 69 years old, with a 30.67 ± 11.44 average age. All the patients are Han Chinese. The majority of them were men (57.1%), had a high school diploma (77.9%) and married (65.6%). A few patients (38.7%) were in poor economic and financial conditions.

Table 1

Socio-demographic characteristics of the Sample(n = 163)
Characteristics	N	%
Gender
Male	93	57.1
Female	70	42.9
Nation
Han	163	100
Others	0	0
Marriage
Married	107	65.6
Others	54	33.1
Missing	2	1.2
Education
Primary school	12	7.4
Junior high school	67	41.1
Senior high School	60	36.8
College	15	9.2
Undergraduate and above	7	4.3
Missing	2	1.2
Diagnosis
Schizophrenia	131	80.4
Schizophrenia and pharyngitis	14	8.6
Schizophrenia and other	13	8.0
Missing	5	3.1
Occupation
Worker	41	25.2
Farmer	25	15.3
Teachers	6	3.7
Cadres	5	3.1
Self-employed	10	6.1
Student	33	20.2
Others	40	24.5
Missing	3	1.8
Family status
Poor	63	38.7
Moderate	70	42.9
Good	21	12.9
Missing	9	5.5
Medical insurance
Urban employee Medical format	30	18.4
Cooperative medical care	115	70.6
Self-paid	10	6.1
Missing	8	4.9
Treatment
Anti-psychotic	14	8.6
Anti-psychotic + antidepressant	7	4.3
Anti-psychotic + other	70	42.9
Anti-psychotic + antidepressant + others	21	12.9
Others	6	3.7
Missing	45	27.7

HRQOL Scores of patients with schizophrenia

See Table 2 for each domain and total score of the patients’ HRQOL. The physical function amounted to 61.09 ± 11.80; the psychological function was 48.02 ± 14.30; the social function was 63.21 ± 15.08; the specific module was 33.01 ± 20.55, and the total score of the scale was 49.09 ± 10.26.

Table 2

QLICD-SC (V2.0) domains and total score (standardized score) in schizophrenic patients
Domains	(mean ± SD)	Minimum	Maximum
Physical functions (PHD)	61.09 ± 11.80	19.44	97.22
Psychological functions (PSD)	48.02 ± 14.30	18.18	90.91
Social Functions(SOD)	63.21 ± 15.08	21.88	96.88
Special modules(SPD)	33.01 ± 20.55	0	96.15
Total scale score(TOT)	49.09 ± 10.26	22.56	83.54

Correlations between HRQOL domain scores and clinical indicators and socio-demographic factors

Simple correlation analysis was performed between clinical objective indicators and QOL scores in each domain and total score (see Table 3). The results illustrated that 8 clinical indicators had associations with different HRQOL scores. With the increase of eosinophilic granulocyte, patients’ scores in physical function increased (r = 0.216, P < 0.05), but with the increase of phosphorus, it decreased (r=-0.284, P < 0.05). Apolipoprotein A1 is positively associated with psychological functions (r = 0.188, P < 0.05) and erythrocyte, hematocrit is positively associated with social functions (r = 0.215 ~ 0.237, P < 0.05). Higher serum creatinine and the percentage of monocytes were both associated with lower special modules scores (r=-0.230~-0.205, P < 0.05), while total bile acid is positively correlated with it (r = 0.192, P < 0.05). A higher percentage of monocytes was negatively correlated with the total scores (r=-0.215, P < 0.05).

Table 3

Simple correlation analysis between scores of quality of life and Clinical indicators (r value)
Clinical indicators	Physical function	Psychological function	Social Function	Special module	Total scale score
Percentage of Monocytes	0.065	-0.202	0.007	-0.230^*	-0.215^*
Eosinophilic Granulocyte	0.216^*	-0.009	0.067	0.106	0.141
Erythrocyte	0.136	-0.139	0.215^*	-0.083	-0.012
Hematocrit	0.179	-0.035	0.237^*	0.049	0.133
Total Bile Acid	-0.138	0.021	-0.070	0.192^*	0.076
Serum Creatinine	0.070	-0.114	0.097	-0.205^*	-0.128
Phosphorus	-0.284 ^**	-0.131	-0.130	-0.025	-0.176
Apolipoprotein A1	-0.108	0.188^*	-0.156	0.158	0.100
Note: ^P < 0. 05, ^*P < 0.01

Results of multiple linear regression analysis

In the present study, the HRQOL scores of physical, psychological and social function, general module, specific module and total scale were taken as dependent variables, and the 13 factors (8 clinical indicators with statistical significance and 5 socio-demographic factors) were used as independent variables for multiple linear regression analysis. These factors were quantified (recoded) before multiple linear regression (see Table 4 in detail). Table 5 showed the outcomes of the multiple linear regression. The variables of physical function included in the model were education, phosphorus and eosinophilic granulocyte, and the determination coefficient R² was 0.185. The variable of psychological functions included in the model was sex (R² = 0.065). Meanwhile, the variables included in the model of social function include education, hematocrit(R² = 0.131). The variables included in the model of special modules were sex, eosinophilic granulocyte, hematocrit, percentage of monocytes(R² = 0.201). The variables included in the total scale score model were eosinophilic granulocyte, hematocrit, percentage of monocytes (R² = 0.222).

Table 4

The variable assignment of multiple linear regression
Variables	Description/recoding
Gender(X1)	Male = 1, Female = 2
Marriage(X2)	Married = 1, Other = 2
Financial status(X3)	Poor = 1 Middle = 2, Good = 3
Age(X4)	Numerical, take the actual value
Education(X5)	Primary school = 1, Junior high school = 2, Senior high school = 3, Junior college = 4,Undergraduate = 5
Percentage of Monocytes(X6)	Measured value
Eosinophilic Granulocyte(X7)	Measured value
Erythrocyte(X8)	Measured value
Hematocrit(X9)	Measured value
Total Bile Acid(X10)	Measured value
Serum Creatinine(X11)	Measured value
Phosphorus(X12)	Measured value
Apolipoprotein A1(X13)	Measured value

Table 5

Factors influencing quality of life scores in schizophrenia screened by multiple linear regression analysis
Domains	Factors	B	Std. Error	Standardized B	t	P
Physical function	Constants	72.766	8.649		8.414	0.000
	Education	2.246	1.261	0.191	1.781	0.079
	Eosinophilic Granulocyte	5.297	2.409	0.234	2.199	0.031
	Phosphorus	-15.238	5.610	-0.291	-2.716	0.008
Psychological function	Constants	37.003	5.019		7.373	0.000
	Sex	7.711	3.396	0.255	2.271	0.026
Social Function	Constants	15.991	15.939		1.003	0.319
	Education	4.398	1.700	0.289	2.587	0.012
	Hematocrit	.897	0.347	0.289	2.586	0.012
Special module	Constants	-29.584	35.133		-0.842	0.403
	Sex	15.833	6.409	0.372	2.470	0.016
	Percentage of Monocytes	-2.649	1.115	-0.274	-2.375	0.020
	Eosinophilic Granulocyte	10.076	4.628	0.241	2.177	0.033
	Hematocrit	1.479	0.631	0.332	2.345	0.022
Total scale score	Constants	33.068	16.984		1.947	0.056
	Sex	5.994	3.034	0.297	1.975	0.052
	Percentage of Monocytes	-1.102	0.537	-0.240	-2.053	0.044
	Eosinophilic Granulocyte	5.348	2.182	0.269	2.451	0.017
	Hematocrit	0.706	0.299	0.335	2.358	0.021
	Phosphorus	-9.873	4.979	-0.215	-1.983	0.051
B: Regression coefficients

The QLICD-SC (V2.0) used in the present study is a schizophrenia scale in the Quality of Life Instruments for Chronic Diseases, including a common module QLICD-GM (general module) and a schizophrenia specific module, which is more practical for studying the HRQOL of schizophrenics. We found that scores of schizophrenic patients ranked highest in social function, followed by physical function, psychological function and special module. Grattan et al. showed that patients had higher psychological stress sensitivity due to schizophrenia symptoms, especially after experiencing negative life events [26]. As a result, people with schizophrenia have lower psychological functioning scores compared to other chronic conditions. Physical function primarily reflects the patients’ basic physiological conditions, such as appetite, sleep and fatigue. Vancampfort (2016) demonstrated that patients’ physical fitness was markedly poorer than healthy controls as a result of typical symptoms such as delusions, hallucinations, or disruptions in daily functioning [27]. Schizophrenia frequently manifests in late adolescence or early adulthood [28]. Patients may fail to express their emotions due to alexithymia, which translate into troubles in social reintegration [29, 30] and affects their score of social function.

There are numerous factors affecting the HRQOL of schizophrenic patients, including socio-demographic factors, physiological factors, psychological factors and clinical principles. Therefore, the present study primarily used simple correlation analysis and multiple linear regression to explore whether clinical objective indicators and socio-demographic factors were related to the QLICD-SC (V2.0) domains and total scale scores. In terms of psychological function, the result of multiple linear regression indicated that sex influences HRQOL. There are gender disparities in the condition of people with schizophrenia, according to several research[17, 31, 32], which may be related to the avenues to deal with stress.

Regarding physical function, phosphorus is one of the factors, which also affects the total score. Numerous studies stressed that phosphorus levels correlate with the severity of psychiatric disorders [33, 34, 35]. For instance, schizophrenia patients have reduced amounts of phosphorus, according to Jamilian(2012) and Baj (2020) [33, 34]. In Chen's (2017) experiment, phosphorus levels rose after 3.8 weeks of antipsychotic medication therapy, indicating higher HRQOL [35]. But this study's findings revealed a negative association between phosphorus and HRQOL ratings may be because the blood samples were taken on the second day of admission and the patients' symptoms improved after medication but phosphorus levels did not change significantly in the short term. However, high level phosphorus in the body leads to phosphorus and calcium antagonism, the blood calcium in the blood reduces, resulting in osteoporosis, which also affects HRQOL. Stubbs B’ s(2014) study proved that the bone loss of schizophrenics occurred earlier, causing the prevalence of osteoporosis to be higher than in healthy people [36]. Therefore, monitoring phosphorus content in blood helps clinicians have a deeper understanding of patients’ HRQOL, although the mechanism is still unclear and not entirely consistent [37].

When it comes to special module, eosinophils is one of the factors, which will increase after taking antipsychotics [38]. That may be the reason why the patients’ condition alleviate and scores in special module and total scale increase. However, the abnormal increase of eosinophils can lead to serious problems. For example, olanzapine has been found to cause drug reactions with eosinophilia and systemic symptoms (DRESS) [39]. The DRESS syndrome can also be attributed to aripiprazole and quetiapine, as the drugs possibly lead to abnormal amounts of eosinophils [40, 41]. Therefore, paying more attention to these indicators can reflect patients’ condition, which is beneficial to doctors take action to treat patients even before significant symptoms appear.

This paper has the limitation that it is cross-sectional in design. Therefore, the effect of the treatment intervention cannot be analyzed. Thus, longitudinal investigations are expected to do. In addition, the subjects were all hospital patients, which had regional limitations. Future studies should widen the scope of investigation to include other variables. The coefficient of determination R² for each model was not high enough, suggesting that our selection clinical indicators for measurement have certain limitations. Further analysis should be made on the factors affecting the HRQOL of schizophrenic patients.

By using QLICD-SC (V2.0), some indicators such as education, sex, eosinophilic granulocyte, hematocrit, percentage of monocytes, phosphorus influencing the QOL of schizophrenic people were screened out which generated fresh insight into clinical treatment. In conclusion, the present study evident that socio-demographic factors and clinical indicators play a crucial role in the HRQOL of patients.

China Mental Health Survey (CMHS)

World Health Organization (WHO)

Quality of Life(QoL)

Quality of Life Instruments for Chronic Disease( QLICD)

Standardized response mean(SRM)

Physical function (PHD)

Psychological functions (PSD)

Social Functions(SOD)

Special modules(SPD)

Total scale score(TOT)

eosinophilia and systemic symptoms (DRESS)

Ethics approval and consent to participate

The study protocol and the informed consent form were approved by the IRB (institutional review board) of the affiliated hospital of Guangdong Medical University (PJ2012052, YJYS2019010). The respondents were voluntary and provided written consent for participation.

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

CHW designed the study. JDX performed the data collection. SYR performed data analyses and drafted the manuscript. CHW and YXL revised the manuscript deeply. All authors contributed to interpreting the data, and have read and approved the final manuscript.

Funding

The paper is supported by the National Natural Science Foundation of China (71373058, 30860248), Universities' Young Innovative Talents Project of Guangdong Province (2021KQNCX024), Basic and Applied Basic Research Funding of Guangdong Province (2021A1515110436) and Discipline construction project of Guangdong Medical University (4SG22265G).

Acknowledgements

Not applicable

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No competing interests reported.

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Health-related quality of life and associations on socio-demographic and clinical factors in schizophrenia based on the QLICD-SC scale: A cross-sectional study

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