The relationship between the neck and low back pain in association with gender

doi:10.21203/rs.3.rs-2360236/v1

Background: There are very few large population studies in Turkey that evaluate the risk factors associated with low back and neck pain in terms of gender. This study aimed to reveal the determinants of the co-occurrence of low back pain (LBP) and neck pain (NP) in terms of gender by synthesizing evidence regarding the risk factors of LBP and NP disease burden.

Methods: The study obtains the up-to-date 2019 Turkey Health Survey data from the Turkish Statistical Institute and covers 8163 families with 16253 individuals aged 18 and older. The dependent variable consisted of those who had neither LBP nor NP, had one, and had both, within the last 12 months using the random-effects ordered probit model.

Results: The 1-year total prevalence of LBP and/or NP in the Turkish population in 2019 was 39.49%. The dual burden of disease was 2.34 times higher in women than in men. In both sexes, the prevalence of dual disease increased significantly with increasing age and in the presence of severe obesity (P<0.05). When double disease prevalence in women compared with men, it was investigated that it was 2.49 times less common in unmarried people, 1.76 times less in those with a bachelor's degree, 1.79 times less in those who walked for more than an hour a day, and 2.83 times less in those who consumed one meal or more of fruit a day. As the monthly income of women increases, the probability of having a double disease decreases by 2.2 times compared to the probability of contracting a single disease. However, when the prevalence of double disease in women was compared with men, it was 3.94 times higher for the employed, 6 times higher for smokers, and 1.5 times higher for those with depression.

Conclusions: By disaggregating the data according to gender, statistical relationships between each group's LBP and NP burden and some risk factors were revealed to facilitate the treatment of modifiable risk factors.

Low back pain

neck pain

obesity

probit model

random effects

risk factors

tobacco

LBP and NP create a great hurdle for individuals, families, and countries [1]. LBP and NP are among the leading causes of the global burden of disease (GBD), and GBD of these diseases has been increasing in recent years [2]. Many factors affect the onset and course of LBP and NP, some of which can be changed and others cannot. There is a widespread consensus that many environmental and personal factors influence the onset and course of these two diseases [3, 4, 5].

In recent years, the relationship between these two diseases and gender has been the focus of the attention of researchers [6]. Gender is a known risk factor for pain, and women generally experience more intense and prolonged physical pain [6, 7]. Reasons such as fluctuations in the menstrual cycle, pregnancy, childbearing, raising children, and abdominal weight gain are the main features that distinguish women from men in terms of musculoskeletal diseases [8]. Studies referencing different layers of the population, for example, in working women in Norway and Sweden [9], in a national study of musculoskeletal disease burden in Spain [10], in China in approximately 14000 adults under 60 years of age [11] and in Brazil [12] that investigated the relationship of LBP and related factors with gender, found the prevalence of LBP to be higher in women. In a systematic analysis including 195 countries in 2020, the global point prevalence, global annual incidence, and years of disability of NP were again found to be higher in women [13].

Each disease is generally handled separately in the literature, and the possible relationship level between its prevalence and risk factors is explained [1, 12]. A limited number of studies on risk factors and gender differences have evaluated the burden of these two diseases together [14–15]. However, there has been no study in the literature that considers the relationship between the prevalence of those who experience both, those who experience one of these two pains, and those who do not experience either, and the risk factors for individuals. In addition, the literature lacks studies that consider the existence of heterogeneity among family members. In the current study, the relationship between the 1-year prevalence of individuals without both diseases, with a single disease, and with both diseases in the past year and risk factors was statistically analyzed. By dividing the population into vertical (male and female) and horizontal strata (risk factors such as age, education-income level, obesity, and depression), the statistical relationship between the prevalence of sequentially determined burdens of these two diseases and the characteristics of individuals has been empirically demonstrated for the first time in the literature. In addition to controlling for the presence of heterogeneity, which includes genetic transmission between family members and unobservable behaviors such as motivation and reactions among family members, gender-based awareness was statistically elicited.

Data collection and participants

The most up-to-date data have been compiled from the Turkey Health Survey (THS) micro dataset conducted by the Turkish Statistical Institute (TSI) in 2019. The survey consists of four different survey parts (“basic characteristics of the household”, “0–6 age group”, “7–14 age group” and “15 + age group”) using the computer-assisted face-to-face interview (CAFI) system. The “National Address Data (NAD)” base, which forms the basis of the Address-Based Population Registration System (ABPRS)”, is used to reach families. The codes of the addresses in the NAD determine the addresses where at least one person is a permanent resident and at the same time match the ABPRS. A two-stage stratified cluster sampling method was used to collect data. The first stage sampling unit is a cluster while the second stage includes households. The first-stage sampling units consist of 947 clusters (94700 families in total), each containing 100 families. In the second stage, 10 families are selected from each cluster, so the total sample size consists of 9470. However, because some families did not participate in the survey by paying administrative fines and some families could not be Sat home at the time of the survey, a total of 8325 families were interviewed, and a participation rate of 88% was obtained. In the current study, the inclusion and exclusion criteria were established as follows: While individuals aged 18 and over were included, individuals under 18 years old were excluded. A total of 8163 families with individuals aged 18 and over and 16253 individuals were included in the study.

Risk Factors (Demographic, Socioeconomic, And Psychological Factors)

The definition of these risk factors and their corresponding statistical values are given in Table 1. Since the rate of heavy physical work status among women was very low, this work variable was excluded from the analysis of women.

Table 1

Descriptive statistics of all variables
Variables	Frequency (n = 16.253)	Percent	Frequency (n = 16.253)	Percent	Frequency (n = 16.253)	Percent
Discrete Variables	Full Sample		Male		Female
Gender:
Female (reference group)	8874	56.60	-	-	-	-
Male	7379	45.40	-	-	-	-
Age Categories:
Age < 30 (ref. group)	3361	20.68	1582	21.44	1779	20.05
30–44	5003	30.78	2237	30.32	2766	31.17
45–64	5432	33.42	2460	33.34	2971	33.48
Age > 64	2457	15.12	1100	14.90	1358	15.30
Diseases
Only LBP	2618	16.11	1145	15.52	1473	16.60
Only NP	1019	6.27	348	4.72	671	7.56
LBP or NP (only one disease from two)	3637	22.38	1478	20.03	2144	24.16
LBP and NP (both LBP and NP)	2781	17.11	732	9.92	2064	23.26
No LBP or no NP	9835	60.51	5169	70.05	4666	52.58
Marital Status:
Never married	2794	17.19	1575	21.34	1218	13.73
Married (ref. group)	11712	72.06	5442	73.75	6271	70.66
Divorced/Spouse died	1747	10.75	362	4.91	1385	15.61
Education Levels:
Not finishing a school (ref. group)	2174	13.38	384	5.20	1790	20.18
Primary school	5572	34.28	2489	33.73	3083	34.74
Secondary school	2223	13.68	1227	16.63	997	11.23
High school	3217	19.79	1701	23.05	1515	17.07
College	3067	18.87	1578	21.39	1489	16.78
Employment types:
Working	6469	39.80	4436	60.12	2032	22.90
Job seeking	1588	9.77	980	13.28	608	6.85
Retired	2438	15.00	1788	24.23	651	7.33
Other employment type (disabled people, housewives, housekeepers, and compulsory military service) (ref. group):	5758	35.43	175	2.37	5584	62.93
Body mass index:
Normal Weight (ref. group)	6456	39.72	2816	38.16	3638	41.00
Over weight	6012	36.99	3150	42.69	2862	32.25
Obese	2794	17.19	1150	15.59	1645	18.53
Over obese	991	6.10	263	3.56	729	8.22
Compulsory health insurance:
Yes	14966	92.08	6682	90.55	8283	93.34
No (ref. group)	1287	7.92	687	9.45	591	6.66
Private health insurance:
Yes	619	3.81	313	4.24	306	3.45
No (ref. group)	15634	96.19	7066	95.76	8568	96.55
Walking time:
Yes	2724	16.76	1726	23.39	998	11.25
No (ref. group)	13529	83.24	5653	76.61	7876	88.75
Sports:
Yes	1224	7.53	764	10.35	460	5.18
No (ref. group)	15029	92.47	6615	89.65	8414	94.82
Resting:
Yes	5794	35.65	2612	35.40	3182	35.86
No (ref. group)	10459	64.35	4767	60.60	5692	64.14
Muscles building:
Yes	678	4.17	579	7.85	-	-
No (ref. group)	15575	95.83	6800	92.15	-	-
No (ref. group)	14585	89.74	6913	93.68	7672	86.45
Tobacco:
Yes	7740	47.62	5218	70.71	252	28.41
No (ref. group)	8513	52.38	2161	29.29	6353	71.59
Alcohol:
Yes	853	5.25	621	8.42	233	2.63
No (ref. group)	15400	94.75	6758	91.58	8641	97.37
Fruit consumption:
Yes	14712	90.52	6689	90.65	8023	90.41
No (ref. group)	1541	9.48	690	9.35	851	9.59
Vegetables consumption:
Yes	15629	96.16	7049	95.53	8579	96.68
No (ref. group)	624	3.84	330	4.47	295	3.32
Fruit juice:
Yes	3987	24.53	1872	25.37	2124	23.94
No (ref. group)	12266	75.47	5507	74.63	6750	76.06
Soft drink:
Yes	5612	34.53	2983	40.43	2629	29.63
No (ref. group)	10641	65.47	4396	59.57	6245	70.37
Depression:
Yes	1668	10.26	466	6.32	1202	13.55
Income levels:
Income < 3400 Turkish Lira (₺) (ref. group)	7787	47.91	3299	44.71	4489	50.58
Income 3400–6900 ₺	5846	35.97	2790	37.81	3056	34.44
Income > 6900 ₺	2620	16.12	1280	17.48	1329	14.98
Household type::
One-person household	1278	7.86	466	6.31	812	9.15
Couple without kids	2916	17.94	1418	19.22	1499	16.89
Other family type (ref. group)	12059	74.20	5495	74.48	6563	73.96
Regions:
İstanbul	2090	12.86	945	12.81	1145	12.90
West Marmara	1732	10.66	799	10.83	934	10.53
East Marmara	763	4.70	358	4.85	405	4.56
Aegean	917	5.61	395	5.35	517	5.82
Mediterranean	1654	10.18	767	10.39	887	10.00
West Anatolia	385	2.37	155	2.10	230	2.59
Central Anatolia	2292	14.11	1059	14.35	1235	13.92
West Black Sea	1121	6.90	417	5.65	704	7.93
East Black Sea	3445	21.20	1657	22.46	1788	20.15
Southeastern Anatolia	684	4.21	295	4.00	391	4.40
Other Region (ref. group)	1170	7.20	532	7.21	638	7.20
Continuous Variables
Variable:	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.
Numbers of kids aged 0–6	0.35	0.68	0.33	0.66	0.36	0.69
Numbers of kids aged 7–14	0.42	0.76	0.39	0.73	0.44	0.78
Numbers of adults	2.51	1.12	2.61	1.11	2.43	1.12
Not: ref. shows the categories are taken as reference for the relevant variable; Std. Dev: Standard Deviation

Statistical Model

The ordered dependent variable consists of disease burden as those without LBP and NP, those with one, and those with both, sequentially. This dependent variable consists of two basic questions asked to the subjects. In the questionnaire, questions such as “Have you experienced lumbar problems (LBP, herniated disc, and other low back diseases) in the last 12 months?” for LBP and “Have you experienced neck region problems (NP, neck hernia, and other neck diseases) in the last 12 months?” for neck pain were asked. They cover the nonspecific of these two diseases. Those who had one and those who had both were sequentially divided into three groups: those who did not have LBP and NP were coded as 0, those who had one were coded as 1, and those who had both were coded as 2. Naturally, as the dependent variable goes from zero to two, it expresses the increasing weight of the back pain and neck-related disease burden in individuals.

Every individual 18 and over in a family was questioned in terms of these two diseases. In this case, while families are included in one dimension as a cluster, some data types in which family members are included as subjects in the other dimension are longitudinal, defined as “panel data”. Heterogeneity in family members is inevitable. Analyses that do not consider such family-specific heterogeneity with no counterfactual observed are lacking in many statistical features (such as bias, consistency, and efficiency of parameter estimates). In addition, since not every family has the same level of individuals, the present data have an unbalanced (unequal) panel structure. Since the family includes individuals aged 18 and over, the burden of disease differs from individual to individual within the family, and the burden of disease also varies between families. In accordance with the data structure described above, we preferred the random-effects panel probit model to clarify the statistical relationship between the ordered disease burden and the characteristics of the individuals.

A total of 45.40% (N = 7379) of 8163 families and 16253 individuals who were formed by individuals aged 18 and over were male, and 54.60% (N = 8874) were female. While 60.51% (N = 9835) of these individuals did not experience any of the two diseases in the last 12 months, 22.38% (N = 3637) experienced only one of the two diseases (16.11% of these patients had LBP, and 6.27% had NP) and 17.11% (N = 2781) of the subjects had both diseases. The 1-year prevalence of these two diseases was 39.49%. A total of 70.05% of the men had neither of the two diseases, 20.03% had a single disease, and 9.92% had a dual disease. A total of 52.58% of women had neither of these two diseases, 24.16% had a single disease, and 23.26% had both diseases. Compared with men, the burden of a single disease in women was 1.20 times, and the burden of a double disease was 2.34 times higher. On the other hand, since both the pooled data and the descriptive statistical values by gender of the independent variables are given in detail in Table 1, they will not be discussed here.

A crucial statistical test in the analysis of back pain-neck burden prevalence is undoubtedly gender equality, that is, the test for equality of parameters of all risk factors between men and women. The likelihood ratio (LR) test is performed based on the log-likelihood values of grouped and pooled samples to test such a hypothesis. To reach such a test result, pooled data were first analyzed by applying the random-effects ordered probit model, and the log-likelihood value of the model was stored as LL and the number of relevant parameters as kp. Then, the data were divided into male and female observations, and the random-effects ordered probit model was adapted to each data set. The likelihood value of each model was recorded as LLm and LLw, while the number of parameters for each model was stored as km and kw, respectively. Then, the null hypothesis claiming that there is no gender-specific differential was tested by calculating the likelihood ratio (LR) test under χ² distribution and with (degrees of freedom (df) = km + kw - kp) degrees of freedom (LR test = 2*(LLm + LLw - LLp)). The LR test result rejected the null hypothesis, showing a significant difference in the prevalence of waist-neck disease burden in terms of gender differential (LR statistical value = 226.79, df = 46, and P < 0.000) (Table 2).

Table 2

Maximum likelihood estimates of the panel random-effects ordered probit model
Variables	Pooled Sample		Male Sample		Female Sample
Variables	Coefficient*100	Prob.	Coefficient*100	Prob.	Coefficient*100	Prob.
Constant	-12.019	0.266	-23.492	0.235	-40.400***	0.004
Individual characteristics
Age 30–44	34.010***	0.000	16.640**	0.014	40.740***	0.000
Age 45–64	53.527***	0.000	36.846***	0.000	67.992***	0.000
Age > 64	60.523***	0.000	45.040***	0.000	82.721***	0.000
Unmarried	-35.647***	0.000	-21.980***	0.033	-30.293***	0.000
Married	-12.367***	0.002	-1.340	0.881	0.196	0.967
Elementary school	-20.552***	0.000	-24.750***	0.002	-10.877***	0.011
Secondary school	-30.128***	0.000	-26.285***	0.003	-21.593***	0.000
High school	-34.101***	0.000	-30.797***	0.000	-28.918***	0.000
College	-36.351***	0.000	-35.089***	0.000	-32.343***	0.000
Working	-24.274***	0.585	-38.970***	0.000	7.507*	0.063
Job seeking	-29.339***	0.293	-43.973***	0.000	-4.651	0.564
Retired	-29.778***	0.330	-35.024***	0.001	8.133	0.165
Overweight	12.377***	0.000	12.716***	0.001	18.655***	0.000
Obese	22.438***	0.000	19.761***	0.000	26.825***	0.000
Overobese	32.445***	0.000	42.952***	0.000	28.512***	0.000
General health insuruance	6.128	0.156	-0.801	0.901	10.655*	0.067
Private health insurance	-2.884	0.648	-16.132*	0.083	7.515	0.356
Walking	-13.270***	0.000	-10.339**	0.014	-10.125**	0.029
Sports time	-7.616	0.101	-11.393*	0.063	1.301	0.853
Resting	8.594**	0.001	4.877	0.182	8.908***	0.005
Heavy physical job	3.038	0.608	8.213	0.214	-	-
Tobacco	-5.472**	0.022	3.390	0.375	11.051***	0.001
Alcohol	-2.476	0.617	5.023	0.408	4.491	0.621
Fruit consumption	-21.124***	0.000	-14.685**	0.013	-22.932***	0.000
Vegetable consumption	3.999	0.506	3.769	0.658	-1.038	0.903
Juices (%100)	-4.130	0.124	-4.576	0.255	-4.270	0.229
Carbonated drinks	-8.587***	0.001	-4.353	0.246	-7.352**	0.027
Depression	67.341***	0.000	65.164***	0.000	62.144***	0.000
Family characteristics
Income 3400–6900	2.680	0.342	0.516	0.901	-1.152	0.743
Income > 6900	-0.039	0.999	-0.325	0.956	-12.257**	0.017
Single person family	-3.113	0.547	-5.771	0.523	0.824	0.896
Childless Couple	-0.861	0.808	-7.778	0.141	2.726	0.537
# of kids aged 0–6	-10.838***	0.000	0.031	0.992	-12.102***	0.000
# kids aged 7–14	-1.937	0.282	1.407	0.601	-2.362	0.293
# of adults	-2.023	0.149	-3.939*	0.057	0.194	0.908
Istanbul	13.258**	0.017	28.569***	0.000	0.773	0.911
Western Marmara	0.999	0.865	5.052	0.547	-3.137	0.666
Eastern Marmara	-10.406	0.144	12.542	0.221	-31.160***	0.001
Aegean	20.971***	0.002	36.701***	0.000	10.083	0.226
Mediterranean	0.074	0.990	14.997*	0.078	-11.740	0.113
Western Anatolia	13.175	0.130	30.693**	0.018	-3.305	0.757
Central Anatolia	-0.583	0.916	12.374	0.121	-13.678**	0.049
Western Black Sea	0.772	0.912	10.920	0.284	-5.144	0.517
Eastern Black Sea	13.598**	0.010	27.504***	0.000	1.139	0.864
Southeastern Anatolia	8.511	0.249	9.241	0.391	9.625	0.307
Threshold parameter (µ)	85.725***	0.000	91.150***	0.000	84.041***	0.000
Sigma (σ)	50.011***	0.000	47.575***	0.000	49.023***	0.000
Log-likelihood (LL) value	-13,949.204		-5,598.639		-8,237.172
Restricted LL value	-14,035.984		-5,605.372		-8,250.219
Chi-squared value (\(\chi _{1}^{2}\))	2518.430***	0.000	13.466	0.000	26.094	0.000
\(\chi _{{47}}^{2}\)	226.79***	0.000
Note: ^{*, ,} and ^* show statistical significance at the %1, %5, and % 10 levels, respectively, while Prob. stands for probability value.

This is the first study to evaluate the prevalence of these two diseases by gender, covering all regions in the Turkish population. In the Turkish population sample, the prevalence of NP alone in 1 year in 2019 was 6.27%, LBP alone was 16.11%, and both LBP and NP were 17.11%. A total of 39.49% of the sample was exposed to LBP and/or neck pain. The 1-year prevalence of NP was 34% [16] in the British population, the 1-year prevalence of LBP was 42.4% [17] in Sweden, and the 1-year prevalence of LBP in Africa was 33% in adolescents and 50% in adults [18].

The parameters that derive the maximum likelihood value of the random-effects ordinal probit model for pooled and sex differences are presented in Table 2. However, our next discussion has focused on marginal effects, as it is more appropriate to discuss the prevalence probability of each disease burden rather than discussing parameters in the maximum likelihood function. In the random-effects ordered probit model, the marginal effects showing the change in the prevalence rates of the ordered dependent variables concerning a one-unit change in the independent variables are presented in Table 3.

Table 3

Marginal effects of covariates on the different prevalences of male, female, and pooled samples
Variables	Pooled sample						Male Sample						Female Sample
	Pain free		Single pain(NP or LBP)		Dual pain (NP&LBP)		Pain free		Single pain (NP or LBP)		Dual pain (NP&LBP)		Pain free		Single pain (NP or LBP)		Dual pain (NP&LBP)
	Coeff.*100	p value	Coeff.*100	p value	Coeff.*100	p value	Coeff.*100	p value	Coeff.*100	p value	Coeff.*100	p value	Coeff.*100	p value	Coeff.*100	p value	Coeff.*100	p value
Individual characteristics
Age 30–44	-11.755***	0.000	4.426***	0.000	7.329***	0.000	-5.204**	0.014	2.804**	0.012	2.400**	0.017	-14.512***	0.000	3.663***	0.000	10.849***	0.000
Age 45–64	-18.487**	0.000	6.715***	0.000	11.772***	0.000	-11.647***	0.000	6.130***	0.000	5.518***	0.000	-23.978***	0.000	5.522***	0.000	18.457***	0.000
Age > 64	-21.215***	0.000	6.518***	0.000	14.696***	0.000	-14.789***	0.000	7.243***	0.000	7.546***	0.000	-28.538***	0.000	3.847***	0.000	24.691***	0.000
Unmarried	11.696***	0.000	-5.252***	0.000	-6.444***	0.000	6.540**	0.027	-3.727**	0.032	-2.813**	0.021	10.645***	0.000	-3.637***	0.000	-7.009***	0.000
Married	4.251***	0.003	-1.677***	0.002	-2.574***	0.003	0.413	0.881	-0.227	0.881	-0.186	0.882	-0.070	0.967	0.021	0.967	0.050	0.967
Elementary school	6.947***	0.000	-2.905***	0.000	-4.042***	0.000	7.454***	0.001	-4.191***	0.001	-3.263***	0.001	3.877**	0.011	-1.164**	0.013	-2.713***	0.010
Secondary school	9.922***	0.000	-4.435***	0.000	-5.487***	0.000	7.709***	0.001	-4.449***	0.002	-3.259***	0.001	7.629***	0.000	-2.523***	0.001	-5.106***	0.000
High school	11.247***	0.000	-4.994***	0.000	-6.253***	0.000	9.052***	0.000	-5.205***	0.000	-3.847***	0.000	10.188***	0.000	-3.415***	0.000	-6.772***	0.000
College	11.942***	0.000	-5.344***	0.000	-6.598***	0.000	10.205***	0.000	-5.917***	0.000	-4.288***	0.000	11.365***	0.000	-3.868***	0.000	-7.498***	0.000
Working	8.219***	0.585	-3.409***	0.584	-4.810***	0.000	12.190***	0.000	-6.503***	0.000	-5.687***	0.001	-2.683*	0.063	0.758*	0.054	1.925*	0.066
Job seeking	9.634***	0.289	-4.338***	0.300	-5.296***	0.000	12.308***	0.000	-7.342***	0.000	-4.966***	0.000	1.658	0.563	-0.501	0.575	-1.157	0.558
Retired	9.825***	0.328	-4.373***	0.334	-5.452***	0.000	10.246***	0.001	-5.908***	0.001	-4.338***	0.000	-2.909	0.166	0.802	0.140	2.107	0.176
Overweight	-4.242***	0.000	1.693***	0.000	2.549***	0.000	-3.933***	0.001	2.151***	0.001	1.782***	0.001	-6.666***	0.000	1.840***	0.000	4.826***	0.000
Obese	-7.784***	0.000	2.914***	0.000	4.871***	0.000	-6.281***	0.000	3.305***	0.000	2.975***	0.000	-9.586***	0.000	2.395***	0.000	7.191***	0.000
Over obese	-11.374***	0.000	3.903***	0.000	7.471***	0.000	-14.320***	0.000	6.794***	0.000	7.526***	0.000	-10.182***	0.000	2.362***	0.000	7.820***	0.000
General health insurance	-2.078	0.153	0.865	0.163	1.213	0.146	0.247	0.901	-0.136	0.901	-0.111	0.901	-3.787*	0.065	1.190*	0.084	2.597*	0.057
Private health insurance	0.981	0.647	-0.404	0.651	-0.578	0.643	4.773*	0.069	-2.739*	0.081	-2.034*	0.055	-2.688	0.357	0.741	0.326	1.947	0.368
Walking	4.473***	0.000	-1.894***	0.002	-2.580***	0.001	3.138**	0.012	-1.755**	0.014	-1.383**	0.011	3.601**	0.028	-1.120**	0.038	-2.481**	0.024
Sports time	2.577*	0.097	-1.080	0.108	-1.498*	0.090	3.426*	0.056	-1.936*	0.063	-1.490**	0.048	-0.465	0.853	0.135	0.852	0.330	0.854
Resting	-2.944***	0.001	1.180**	0.000	1.764***	0.000	-1.507	0.183	0.826	0.182	0.681	0.186	-3.182***	0.005	0.911***	0.004	2.271***	0.006
Heavy physical job	-1.041	0.610	0.417	0.604	0.624	0.613	-2.572	0.222	0.014	0.211	1.187	0.234	-	-	-	-	-	-
Tobacco	1.868**	0.022	-0.759**	0.022	-1.109**	0.022	-1.040	0.374	0.575	0.376	0.465	0.371	-3.950***	0.001	1.109***	0.001	2.841***	0.001
Alcohol	0.843	0.616	-0.346	0.619	-0.497	0.613	-1.563	0.412	0.849	0.406	0.714	0.420	-1.605	0.621	0.453	0.608	1.152	0.626
Fruit consumption	7.347***	0.000	-2.713***	0.000	-4.634***	0.000	4.652**	0.016	-2.464**	0.012	-2.188**	0.021	8.200***	0.000	-2.017***	0.000	-6.183***	0.000
Vegetable consumption	-1.359	0.504	0.562	0.511	0.797	0.499	-1.150	0.655	0.640	0.659	0.511	0.651	0.371	0.903	-0.108	0.903	-0.263	0.904
Juices (%100)	1.406	0.123	-0.577	0.127	-0.829	0.120	1.401	0.252	-0.777	0.255	-0.625	0.248	1.523	0.228	-0.454	0.237	-1.070	0.225
Carbonated drinks	2.921***	0.001	-1.201***	0.001	-1.720***	0.001	1.338	0.245	-0.738	0.246	-0.600	0.243	2.621**	0.027	-0.785**	0.031	-1.836**	0.025
Comorbidity
Depression	-23.633***	0.000	6.598***	0.000	17.035***	0.000	-22.132***	0.000	9.633***	0.000	12.500***	0.000	-21.817***	0.000	3.733***	0.000	18.083***	0.000
Family characteristics
Income 3400–6900	-0.916	0.342	0.371	0.340	0.0546	0.343	-0.159	0.901	0.088	0.901	0.072	0.901	0.411	0.743	-0.121	0.744	-0.291	0.743
Income > 6900	0.013	0.999	-0.054	0.999	-0.079	0.999	0.001	0.955	-0.055	0.956	-0.045	0.955	4.357**	0.017	-1.362**	0.024	-2.995**	0.014
Single person family	1.059	0.545	-0.436	0.550	-0.624	0.542	1.754	0.517	-0.980	0.523	-0.774	0.509	-0.294	0.896	0.086	0.895	0.209	0.896
Childless Couple	0.294	0.808	-0.120	0.809	-0.174	0.808	2.366	0.136	-0.1321	0.142	-1.045	0.129	-0.974	0.537	0.281	0.531	0.693	0.540
# of kids aged 0–6	3.701***	0.000	-1.503***	0.000	-2.199***	0.000	-0.001	-0.992	0.001	-0.992	0.001	-0.992	4.321***	0.000	-1.264***	0.000	-3.057***	0.000
# kids aged 7–14	0.661	0.282	-0.269	0.282	-0.393	0.282	-0.433	0.601	0.239	0.601	0.195	0.601	0.843	0.293	-0.247	0.293	-0.596	0.293
# of adults	0.691	0.149	-0.281	0.150	-0.410	0.149	1.213*	0.058	-0.668*	0.058	-0.545*	0.057	-0.069	0.908	0.020	0.908	0.049	0.908
Istanbul	-4.580**	0.018	1.765**	0.012	2.816**	0.022	-9.221***	0.001	4.718***	0.000	4.503***	0.001	-0.276	0.911	0.080	0.910	0.196	0.911
Western Marmara	0.342	0.865	0.138	0.864	0.203	0.865	-1.571	0.551	0.854	0.546	0.717	0.557	1.119	0.666	-0.334	0.672	-0.785	0.663
Eastern Marmara	3.505	0.138	-1.489	0.155	-2.017	0.125	-3.968	0.232	2.106	0.214	1.862	0.251	10.888***	0.001	-3.870***	0.003	-7.018***	0.000
Aegean	-7.305***	0.002	2.674***	0.001	4.631***	0.004	-12.100***	0.000	5.919***	0.000	6.181***	0.002	-3.608	0.227	0.977	0.188	2.631	0.241
Mediterranean	-0.025	0.990	0.010	0.990	0.015	0.990	-4.750*	0.084	2.516*	0.072	2.234*	0.099	4.172	0.111	-1.312	0.135	-2.860*	0.100
Western Anatolia	-4.565	0.135	1.733	0.107	2.832	0.152	-10.066**	0.024	4.997**	0.011	5.069**	0.042	1.178	0.757	-0.354	0.762	-0.825	0.754
Central Anatolia	0.199	0.916	-0.081	0.916	-0.118	0.916	-3.892	0.127	2.083	0.116	1.809	0.140	4.858**	0.047	-1.533*	0.064	-3.325**	0.040
Western Black Sea	-0.247	0.912	0.100	0.911	0.147	0.912	-3.442	0.294	1.837	0.278	1.605	0.311	1.833	0.516	-0.555	0.530	-1.278	0.510
Eastern Black Sea	-4.687**	0.011	1.825**	0.008	2.861**	0.013	-8.764***	0.000	4.580***	0.000	4.183***	0.001	-0.407	0.864	0.118	0.864	0.288	0.865
Southeastern Anatolia	-2.934	0.253	1.144	0.233	1.791	0.266	-2.905	0.400	1.557	0.387	1.348	0.415	-3.444	0.307	0.934	0.267	2.510	0.322
Note: ^{*, ,} and ^* show statistical significance at the %1, %5, and % 10 levels, respectively, while Prob. stands for probability value

In the present study, the prevalence of single and dual disease increased as the age of individuals of both sexes increased. For example, when compared to individuals aged under 30, 30–44, 45–64, and 65 and over male individuals, the single disease burden increased by 2.80%, 6.13%, and 7.24%, respectively, while the double disease burden increased significantly by 2.4%, 5.52%, and 7.55%, respectively. However, although the prevalence of single disease burden in females was the same as that in males (3.66%, 5.52%, and 3.85%, respectively), the prevalence of dual diseases has increased markedly (10.85%, 18.46%, and 24.69%, respectively) (for all comparisons P < 0.05). In this context, female individuals aged 65 and over have a 3.27 times higher risk of contracting the dual disease than males, with a very differential potential. The findings are consistent with the literature. In a study investigating the global prevalence of LBP, LBP was found more often in elderly individuals and women [19].

Compared with individuals who were married, the single and dual disease prevalence of being unmarried (never married, widowed, or divorced) was significantly reduced in both men (3.73% and 2.81%, respectively) and women (3.64% and 7.01%, respectively). (P < 0.05 for all comparisons). The incidence of the dual disease is 2.49 times lower in unmarried women than in unmarried men. Similar findings have been reported in the literature, with unmarried men and women (never married, widowed, or divorced) having a lower prevalence of LBP than married men and women [12–22]. In another study, the risk of NP in singles was 76% less than that in married people [23].

As the education level of individuals increases, the prevalence of single and dual illiterate people and/or individuals who do not have any diploma from primary school, secondary school, high school, and undergraduate male individuals, single disease burden decreases significantly by 4.19%, 4.45%, 5.21%, and 5.92%, and double disease burden decreases significantly by 3.26%, 3.26%, 4.29%, and 5.69%, respectively. In the same comparison, the prevalence of carrying dual disease further decreased (2.71%, 5.11%, 6.77%, and 7.50%, respectively) when compared with the prevalence of single disease burden in women (1.16%, 2.52%, 3.42%, and 3.87%, respectively) (P < 0.05 for all comparisons). Especially as the education level of women increases, the prevalence of single and double disease decreases significantly. Graduate women are almost three times less likely to experience single and dual disease than women with primary school degrees. In particular, women at the undergraduate level are approximately 1.76 times less likely to have the dual disease than men. One study [24] and three systematic reviews reported that LBP is less affected in individuals with higher education than in individuals with secondary or lower education [25]. Similar to study findings, a study evaluating NP and LBP also found that subjects with lower education levels were more likely to suffer from NP and LBP [19].

When the referred employment category (disabled people, homemakers, cleaners, and those in compulsory military service) and employees were compared, a significant negative relationship was found between the likelihood of working men having a single illness (6.50%) and double illness (5.69%), and a positive relationship was found between the active work of women and their probability of having a single (0.76%) and double (1.93%) illness. Working women are 3.94 times more likely to have a dual illness than men. Such an outcome may be due to the sum of workloads inside and outside the home. The findings are consistent with the literature results, in which acute and chronic diseases are more common in working women than in non-working women [26]. For the men seeking a job, the odds of catching a single and dual illness are 7.34% and 4.97%, respectively, and for men who receive a pension are 5.91% and 4.34%, respectively, less than those who do not (P < 0.05 for all comparisons).

As the weight of individuals increases, the prevalence of single and dual disease increases significantly in both men and women. Compared with normal-weight individuals, in overweight, obese, and extremely obese male individuals, the single disease burden increased by 2.15%, 3.31%, and 6.79% points, respectively, while the double disease burden increased significantly by 1.78%, 2.96%, and 7.53%, respectively. However, the prevalence of single disease burden in female individuals was lower than that in males (1.84%, 2.40%, and 2.36%, respectively). In comparison, the prevalence of carrying dual disease increased significantly (4.83%, 7.19%, and 7.82%, respectively) (for all comparisons, P < 0.05). The prevalence of dual disease was 7.75% in extremely obese men compared to normal-weight men and 7.82% in extremely obese women compared to normal-weight women. Excessive obesity increases the risk of carrying dual diseases at approximately the same rate in men and women. The relationship between obesity and LBP is well known, but it should be kept in mind that it also increases the risk of NP. The consensus supported by studies [27] and systematic reviews is that obesity (BMI > 30 kg/m2) is associated with musculoskeletal diseases, including chronic NP [20] and LBP [28], and is directly related to chronic spinal pain (CSP) [21].

Women with general health insurance (GSS) were 1.19% and 2.60% more likely to have a single and double disease, respectively, than those who did not. On the other hand, the prevalence of single and dual diseases in males with private health insurance (PHI) was significantly lower by 2.74% and 2.03%, respectively. People with PHI in Turkey have higher socioeconomic and educational levels. These people can go to private health institutions without paying or paying a low fee and access health services more efficiently. This result is consistent with the literature, showing individuals with lower economic status had a higher prevalence of chronic LBP [29] and CSP [21] than those with higher economic status.

Compared with those who did not walk for more than one hour a day, a negative association was obtained between individuals walking for more than one hour a day and their probability of developing back and/or neck disease. Men and women who walked for more than an hour a day had a 1.75% and 1.12% lower risk of developing a single illness, respectively. However, male and female individuals have a 1.38% and 2.48% lower risk of contracting a dual disease, respectively. On the other hand, as the time (minutes) devoted to sports by male individuals per week increases, the prevalence of single and dual diseases significantly mitigates by 1.94% and 1.49%, respectively (P < 0.05 for all comparisons). The burden of carrying a double disease in women walking for more than 1 hour is approximately twice as low as for a single disease. Again, women who walk for more than an hour a day are 1.79 times less likely to contract the dual disease than men. Considering a large number of studies investigating the relationship between LBP and walking [30] and exercise [31], walking and exercise have a neutral or beneficial effect on the risk of LBP. The coexistence of NP and LBP has been reported to be associated with not performing physical exercise and being obese [19].

The study found that the probability of catching a single and double disease in men who consume tobacco was 0.57% and 0.47% points, respectively, and 1.11% and 2.84% points in women compared with nonsmokers (P < 0.05 for all comparisons). The risk of developing the dual disease among female smokers was 6 times higher than that among male smokers. The findings are compatible with the literature. In studies investigating risk factors in people with LBP [32, 33] and in a meta-analysis [34], the incidence of LBP was higher in smokers. Although the probability of contracting single and double diseases was insignificant for men who consumed alcohol, it was determined that they were 0.85% and 0.71% higher, respectively, and 0.53% and 1.15% higher for women. Again, a significant relationship was found between LBP and alcohol abusers [33].

As the consumption of one or more fruits per day boosts in individuals, the prevalence of single and dual diseases alleviates significantly in both sexes. For example, when compared with individuals consuming fruits less than once per day, in male individuals who consume one or more fruits per day, single and double disease burden significantly shrank by 2.46% and 2.18%, respectively, and in female individuals by 2.02% and 6.18%, respectively (P < 0.05 for all comparisons). In other words, the double disease burden of female individuals is approximately three times less than the single disease burden. In this context, female individuals who consume one or more fruits per day have a 2.83 times lower risk of catching dual disease than males. On the other hand, women who consume carbonated beverages have a significantly lower risk of developing single and dual diseases by 0.78% and 1.84%, respectively, than those who do not (P < 0.05 for all comparisons). Such findings are also compatible with the literature. In a recent study, higher daily consumption of fruits, whole grains, and dairy products was associated with a 20–26% lower probability of CSP (for all trends P < 0.028) [21].

Female individuals with a monthly income higher than 6900 Turkish Lira (TL) have a significantly lower risk of developing a single and dual disease by 1.36% and 3.00 points, respectively, when compared with females with a monthly income lower than 3400 TL (P < 0.05 for all comparisons). As the socioeconomic level of women increases, the probability of carrying both diseases shrinks. As the monthly income of women increases, the probability of developing a double disease decreases by 2.2 times compared to the probability of getting a single disease. A study conducted on a population over the age of 65 found that low socioeconomic status was associated with high LBP [24]. On the other hand, as the number of children aged 0–6 years increased in the family, the probability of developing single and dual diseases among women decreased significantly by 1.26% and 3.06%, respectively (P < 0.05 for all comparisons). A study stated that LBP was linearly associated with being married and increasing the number of children [22].

When compared with male individuals living in the Eastern Anatolian region, the prevalence of single and dual diseases in males living in the Istanbul, Aegean, Mediterranean, Western Anatolian, and Eastern Black Sea regions was significantly higher (4.72% and 4.50%, 5.92% and 6.18%, 2.52% and 2.23%, 5.00% 5.07% and 4.58% and 4.18%, respectively). (P < 0.05 for all comparisons). This result is compatible with the literature. Such a finding can be associated with the lower socioeconomic level and education level of those living in Eastern Anatolia in interregional comparisons in Turkey [35]. There is also a significant positive relationship between the probability of both male and female individuals having depression and the probability of developing a single or dual illness. Men with depression were more than 2.5 times more likely to have a single illness (9.63%) than women (3.73%), while women with a double illness were 1.5 times more likely to have a single illness (12.5% and 18.08%, respectively) (P < 0.05 for all comparisons). There is increasing evidence that pain problems increase the risk of depression. Depression is a strong and independent predictor of the onset of an episode of intense and/or disabling of these two diseases [36]. In another study, depression and somatization disorder had a significantly positive association with LBP [37]. According to a systematic review, initial symptoms of depression were found to worsen the prognosis of LBP [38].

In a large population study in Turkey in which the risk factors associated with LBP and NP were evaluated considering the gender differential, 39.49% of the population experienced LBP and/or NP within 1 year in 2019 in adults aged 18 and over. The prevalence of both diseases was found to be significantly higher in women than in men. Increasing age, being married, low education level, obesity, walking for less than an hour a day, smoking, consuming less than one serving of fruit per day, and a history of depression are risk factors for dual disease in both genders, while active work of women, those with general health insurance having a low income, a low number of children aged 0–6, living in the western Marmara and Central Anatolian regions were determined as risk factors for dual disease. Identifying distinctions regarding other personal factors and gender differences in LBP and NP may also be more beneficial in patient planning to prevent pain and disability. In this study, the evidence for general personal risk factors for LBP and NP, which are important components of the global burden of disease, was synthesized, and the determinants of the coexistence of these two diseases in terms of gender were indicated. Putting these modifiable personal risk factors with quantitative values in terms of gender differentials helps develop appropriate and dynamic health policies to alleviate disability and contribute to their treatment.

In addition, heterogeneity among family members was converted into a numerical value to provide statistical properties such as possible unbiasedness, consistency, and efficiency of the parameters. Based on available information, preventing the first attack of LBP or NP is impossible. However, prevention of relapses, disability, and costs to the individual and society can be a target. Suggestions such as physical activity, consuming fruits, quitting smoking, reaching a healthy weight, and treating depression will be effective in the prevention of LBP and NP as well as in the prevention of many chronic diseases. In this context, it can provide convenience in the provision of an individual-centered and subgroup-oriented health service, especially in rehabilitation programs that are expected to be more clearly revealed by separating the disease-triggering elements of these pains in terms of gender. To prevent these two diseases from becoming chronic and causing disability, detailed sharing of risk factors with the patient will facilitate treatment.

Acknowledgments

We thank the Turkish Statistical Institute for providing the data. Inferences in the text belong to the authors, not necessarily reflecting the viewpoint of the Institution.

Authors’ Contributions

Conceptualization: FB, FU, AB, AK. Data curation: FB, FU, AB. Formal analysis: FB, FU, AB. Methodology: FU, AB. Writing – original draft: FB, FU, AB, AK. Writing – review & editing: FB, FU, AB, AK.

Funding

No funding was received for this study.

Availability of data and materials

The compiled data from Turkey Health Survey can be released if requested.

Ethics approval and consent to participate

The study attained the approval of the Turkish Statistical Institute (TSI) with authorization number 23.08.2019/19496. It was also approved by the local ethics committee of the College of Medicine with approval number 26.12.2019/556.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Fehrmann E, Tuechler K, Kienbacher T, Mair P, Spreitzer J, Fischer L, et al. Comparisons in muscle function and training rehabilitation outcomes between avoidance-endurance model subgroups. Clin J Pain. 2017;33(10):912–20.
Vos T, Abajobir AA, Abate KH, Abbafati C, Abbas KM, Abd-Allah F, et al. Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet. 2017;390(10100):1211–59.
Dunn KM, Hestbaek L, Cassidy JD. Low back pain across the life course. Best Pract Res Clin Rheumatol. 2013;27(5):591–600.
Hogg-Johnson S, van der Velde G, Carroll LJ, Holm LW, Cassidy JD, Guzman J, et al. The burden and determinants of neck pain in the general population: results of the Bone and Joint Decade 2000–2010 Task Force on Neck Pain and Its Associated Disorders. J Manip Physiol Ther. 2009;32(2):46–60.
Haldeman S, Carroll L, Cassidy JD. Findings from the bone and joint decade 2000 to 2010 task force on neck pain and its associated disorders. J Occup Environ Med. 2010;52(4):424–7.
Fillingim RB, King CD, Ribeiro-Dasilva MC, Rahim-Williams B, Riley IIIJL. Sex, gender, and pain: a review of recent clinical and experimental findings. J Pain. 2009;10(5):447–85.
Glambek M, Nielsen MB, Gjerstad J, Einarsen S. Gender differences in the relationship between workplace bullying and subjective back and neck pain: A two-wave study in a Norwegian probability sample. J Psychosom Res. 2018;106:73–5.
Wijnhoven HA, De Vet HC, Picavet HSJ. Prevalence of musculoskeletal disorders is systematically higher in w0men than.in men. Clin J Pain. 2006;22(8):717–24.
lhlebaek C, Hansson TH, Lærum E, Brage S, Eriksen HR, Holm SH, et al. Prevalence of low back pain and sickness absence: A "borderline” study in Norway and Sweden. Scandinavian Journal of Public Health. 2006;34{5):555–558.
Carmona L, Ballina J, Gabriel R, Laffon A. The burden of musculoskeletal diseases in the general population of Spain: results from a national survey. Ann Rheum Dis. 2001;60(11):1040–5.
Barrero LH, Hsu YH, Terwedow H, Perry MJ, Dennerlein JT, Brain JD, et al. Prevalence and physical determinants of low back pain in a rural Chinese population. Spine. 2006;31(23):2728–34.
Bento TPF, dos Santos Genebra CV, Maciel NM, Cornelio GP, Simeão SFAP, de Vitta A, et al. Low back pain and some associated factors: is there any difference between genders? Braz J Phys Ther. 2020;24(1):79–87.
Safiri S, Kolahi AA, Hoy D, Buchbinder R, Mansournia MA, Bettampadi D, Ferreira ML.Global, regional, and national burden of neck pain in the general population, 1990–2017: systematic analysis of the Global Burden of Disease Study. 2017. BMJ. 2020;368.
Angst F, Angst J, Ajdacic-Gross V, Aeschlimann A, Rössler W. Epidemiology of back pain in young and middle-aged adults: a longitudinal population cohort survey from age 27–50 years. Psychosomatics. 2017;58(6):604–13.
Shariat A, Cardoso JR, Cleland JA, Danaee M, Ansari NN, Kargarfard M, et al. Prevalence rate of neck, shoulder and lower back pain in association with age, body mass index and gender among Malaysian office workers. Work. 2018;60(2):191–9.
Louw QA, Morris LD, Grimmer-Somers K. The prevalence of low back pain in Africa: a systematic review. BMC Musculoskelet Disord. 2007;8(1):1–14.
Palmer KT, Walker-Bone K, Griffin MJ, Syddall H, Pannett B, Coggon D, et al. Prevalence and occupational associations of neck pain in the British population. Scandinavian Journal of Work, Environment & Health. 2001:49–56.
Bergman STEFAN, Herrström PER, Högström KRISTINA, Petersson IF, Svensson BJORN, Jacobsson LT. Chronic musculoskeletal pain, prevalence rates, and sociodemographic associations in a Swedish population study. J Rhuematol. 2001;28(6):1369–77.
Fernandez-de-Las-Penas C, Alonso-Blanco C, Hernández-Barrera V, Palacios-Ceña D, Jiménez-García R, Carrasco-Garrido P. Has the prevalence of neck pain and low back pain changed over the last 5 years? A population-based national study in Spain. Spine J. 2013;13(9):1069–76.
Kaaria S, Laaksonen M, Rahkonen O, Lahelma E, Leino-Arjas P. Risk factors for chronic neck pain: A prospective study among middle-aged employees. Eur J Pain. 2012;16(6):911–20.
Zick SM, Murphy SL, Colacino J. Association of chronic spinal pain with diet quality. Pain Reports. 2020;5(5).
Silman AJ, Ferry S, Papageorgiou AC, Jayson MI, Croft PR. Number of children as a risk factor for low back pain in men and women. Arthritis & Rheumatism: Official Journal of the American College of Rheumatology. 1995;38(9):1232–5.
Madadizadeh F, Vali L, Rafiei S, Akbarnejad Z. Risk factors associated with musculoskeletal disorders of the neck and shoulder in the personnel of Kerman University of Medical Sciences. Electron Physician. 2017;9(5):4341.
Ikeda T, Sugiyama K, Aida J, Tsuboya T, Watabiki N, Kondo K, et al. Socioeconomic inequalities in low back pain among older people: the JAGES cross-sectional study. Int J Equity Health. 2019;18(1):1–11.
Meucci RD, Fassa AG, Faria NMX. Prevalence of chronic low back pain: systematic review. Rev Saude Publica. 2015;49:73.
Ahmad-Nia S. Women's work and health in Iran: a comparison of working and non-working mothers. Soc Sci Med. 2002;54(5):753–65.
Van Nieuwenhuyse A, Crombez G, Burdorf A, Verbeke G, Masschelein R, Moens G, et al. Physical characteristics of the back are not predictive of low back pain in healthy workers: a prospective study. BMC Musculoskelet Disord. 2009;10(1):1–9.
Dario AB, Ferreira ML, Refshauge KM, Lima TS, Ordoñana JR, Ferreira PH. The relationship between obesity, low back pain, and lumbar disc degeneration when genetics and the environment are considered: a systematic review of twin studies. spine J. 2015;15(5):1106–17.
Meucci RD, Fassa AG, Paniz V, Silva MC, Wegman DH. Increase of chronic low back pain prevalence in a medium-sized city of southern Brazil. BMC Musculoskelet Disord. 2013;14(1):1–11.
Hendrick P, Te Wake AM, Tikkisetty AS, Wulff L, Yap C, Milosavljevic S. The effectiveness of walking as an intervention for low back pain: a systematic review. Eur Spine J. 2010;19(10):1613–20.
Shiri R, Coggon D, Falah-Hassani K. Exercise for the prevention of low back pain: systematic review and meta-analysis of controlled trials. Am J Epidemiol. 2018;187(5):1093–101.
Yang H, Haldeman S. Behavior-related factors associated with low back pain in the US adult population. Spine. 2018;43(1):28–34.
Shemory ST, Pfefferle KJ, Gradisar LM. Modifiable risk factors in patients with low back pain. Orthopedics. 2016;39(3):e413–6.
Shiri R, Karppinen J, Leino-Arjas P, Solovieva S, Viikari-Juntura E. The association between smoking and low back pain: a meta-analysis. Am J Med. 2010;123(1):87. e7-87. e35.
Sahin İ, Gümez Y. Efficiency of education: The case in eastern and south-eastern Turkey. Soc Indic Res. 2000;49(2):213–36.
Carroll LJ, Cassidy JD, Cote P. Depression as a risk factor for onset of an episode of troublesome neck and low back pain. Pain. 2004;107(1–2):134–9.
Robertson D, Kumbhare D, Nolet P, Srbely J, Newton G. Associations between low back pain and depression and somatization in a Canadian emerging adult population. J Can Chiropr Assoc. 2017;61(2):96.
Pinheiro MB, Ferreira ML, Refshauge K, Maher CG, Ordoñana JR, Andrade TB, et al. Symptoms of depression as a prognostic factor for low back pain: a systematic review. Spine J. 2016;16(1):105–16.

The relationship between the neck and low back pain in association with gender

Status:

Version 1

Abstract

Background

Methods

Data collection and participants

Risk Factors (Demographic, Socioeconomic, And Psychological Factors)

Statistical Model

Results

Discussion

Conclusion

Declarations

References

Status:

Version 1