Journal of Psychosocial Nursing and Mental Health Services

CNE Article 

Exploring the Risk Factors for Depressive Symptoms Among Chinese Rural Older Adults

Zi Yan, PhD, MPH, MEd; Ruoyan Lu, MS; Yueping Li, MPH; Zhenquan Zheng, BS

Abstract

The purpose of the current study was to examine risk factors for depressive symptoms among older adults in rural China. Data were derived from the National Health Services Survey in China. A total of 2,586 rural adults age ≥60 were included in the study. Sociodemographic factors, health risk factors, and behavioral factors were measured, along with self-rated depressive symptoms. Older age (>70 years), lower education level, and living without a partner were associated with depressive symptoms. After adjusting for socioeconomic status and social support, individuals who had at least one chronic disease, experienced pain, and were unable to take care of themselves or perform household chores were more likely to report depressive symptoms (all p < 0.001). Community health care and nursing services should focus on pain control, improvement of daily physical function, and social support for older adults in rural China. [Journal of Psychosocial Nursing and Mental Health Services, 58(2), 41–47.]

Abstract

The purpose of the current study was to examine risk factors for depressive symptoms among older adults in rural China. Data were derived from the National Health Services Survey in China. A total of 2,586 rural adults age ≥60 were included in the study. Sociodemographic factors, health risk factors, and behavioral factors were measured, along with self-rated depressive symptoms. Older age (>70 years), lower education level, and living without a partner were associated with depressive symptoms. After adjusting for socioeconomic status and social support, individuals who had at least one chronic disease, experienced pain, and were unable to take care of themselves or perform household chores were more likely to report depressive symptoms (all p < 0.001). Community health care and nursing services should focus on pain control, improvement of daily physical function, and social support for older adults in rural China. [Journal of Psychosocial Nursing and Mental Health Services, 58(2), 41–47.]

The prevalence of depression in the older adult population appears to be high worldwide. An analysis of 15 countries in North America and Europe showed that depression is the most common mental disorder in older adults, with a 3.3% prevalence for current cases of major depression and a lifetime incidence of 16.5% for major depression (Volkert, Schulz, Härter, Wlodarczyk, & Andreas, 2013). This higher prevalence rate is strongly correlated with older age (Blixen, Wilkinson, & Schuring, 1994; Volkert et al., 2013). Older adults in developing countries also experience depression (Dardas et al., 2019). A recent study reported a depression rate of 11.4% among community-dwelling older adults in rural India (Behera et al., 2016).

In China, the burden of depression has increased in response to an increasingly aging population (Bao et al., 2015). Zhang, Xu, and Nie's (2011) meta-analysis reported that 22.6% of Chinese older adults had depressive symptoms. In 2016, 139 million people in China were older than 65. This number is projected to grow to at least 300 million by 2050, which equates to 44% of the worldwide population (Bao et al., 2015).

Although there is no clear evidence supporting a relationship between rates of depression in a country and its economic status, there is sufficient evidence of the relationship between an individual's socioeconomic status and depression (McInerney, Mellor, & Nicholas, 2012). In addition, individuals with lower education levels have more depressive symptoms than those with higher levels of education, and a higher risk of developing depression (Koster et al., 2006). In the older adult population, those with higher levels of education are at a reduced risk of depression (Miech & Shanahan, 2000).

Social support is a protective factor for depression, and high social support counteracts the negative effects of depression (Baiyewu, Yusuf, & Ogundele, 2015; Bruce, 2015; Lee, Kahana, & Kahana, 2016). A study conducted in China reported that loneliness is a predictor of depression among older adults living in nursing homes, even after controlling for age, gender, marital status, education level, and medical history (Gan, Xie, Duan, Deng, & Yu, 2015).

The presence of chronic disease predicts depression among older adults (Scott et al., 2007). A study with approximately 85,000 older adults from 17 countries reported that individuals who had one or more chronic diseases were more likely to be diagnosed with depression (Scott et al., 2007). Another factor that might be associated with depression is chronic pain. The rate of depression increases with the level of pain (Behera et al., 2016). However, some researchers also argue that depression predicts increased levels of chronic pain, as opposed to pain predicting higher levels of depression (Mossey & Gallagher, 2004). Overall health status and depression are often linked, yet it is unclear whether overall health is causally related to depression. Although some researchers argue that the presence of depression causes a decrease in overall health, others believe that depression is a strong predictor of a decline in health status among individuals (Moussavi et al., 2007).

Research regarding the role of health behaviors and depressive symptoms provides inconsistent results. Some research reports smoking and depressive symptoms are correlated, especially in adult populations (Tjora et al., 2014). Some studies even suggest that individuals who smoke are more likely to be depressed (Vogel, Hurford, Smith, & Cole, 2003). Similarly, an international longitudinal study reported that excessive alcohol consumption is related to a higher incidence of depression (Bellos et al., 2016). However, a recent review shows that depression may also influence behavioral changes, though the causal relationship is unclear (Fluharty, Taylor, Grabski, & Munafò, 2017). The authors also called for more research to determine whether behavioral factors, such as smoking and drinking, are risk factors for depression (Fluharty et al., 2017).

In summary, although multiple risk factors have been found to be associated with depressive symptoms among the older adult population, most studies have been conducted in Western countries. Due to China's unique sociocultural, economic, and political environment, risk factors that are related to depressive symptoms among Chinese older adults may be different from other countries. Exploring depressive symptoms and associated risk factors among Chinese older adults living in a rural community is the first step toward understanding depression among this population. This exploration also further contributes to the development of preventive and control strategies for depression (Sorrell, 2016). To that extent, the purpose of the current study was to explore risk factors related to depressive symptoms among Chinese older adults in rural communities.

Method

Data were derived from the Fifth National Health Services Survey in Fujian Province, China. Face-to-face interviews were conducted in participants' homes. Fujian Province is a relatively developed area in China. In 2013, the per capita gross domestic product (GDP) was RMB 57,856 (∼$8,900 U.S. dollars), higher than the national average of RMB 41,908 (∼$6,447 U.S. dollars). Of its 37.74 million residents, 14.81 million lived in rural areas. Using multi-stage random sampling, the survey included eight counties, 40 townships (districts), 80 villages (communities), 4,800 households, and 14,393 residents in Fujian who provided usable responses. Of total participants, 82.1% completed the questionnaire themselves, whereas the remaining were completed by a family member. For the current study, data provided by 2,586 rural older adults age ≥60 were included.

Measures

Depressive symptoms were measured by a single question asking participants whether they felt depressed. Possible responses were not at all, somewhat depressed, and very depressed. Participants who responded not at all were classified as the no depressive symptoms group; those who chose either of the latter responses were classified as the depressed symptoms group. Single-item measures for depression were found valid and reliable compared to other previously validated measures (Lefèvre et al., 2012; Young, Nguyen, Roth, Broad-berry, & Mackay, 2015).

Based on the literature review, three groups of factors were examined that may be associated with depressive symptoms: sociodemographic factors, health risk factors, and behavioral factors. Sociodemographic factors were age, gender, education, having a partner, and socioeconomic status. All participants were classified into one of five economic status groups: highest, higher, median, lower, and lowest, meaning <20%, 20% to <40%, 40% to <60%, 60% to 80%, and >80%, respectively, of annual household expenditure per capita. This measure was used because some studies suggest that for developing countries expenditure data provide a better proxy of household economic status than income data, as the latter are likely to be underreported (Xu, Toobert, Savage, Pan, & Whitmer, 2008). Health risk factors measured were body mass index, having at least one chronic disease, lack of mobility, experiencing pain or feeling uncomfortable, unable to undertake self-care, and unable to perform household chores. Behavioral factors measured were smoking status, drinking alcohol in the previous 12 months, and not exercising at least once per week.

Data Analysis

All data were analyzed using SPSS 21.0. Chi-square test was used to examine the association among sociodemographic, health risk, and behavioral factors with depressive symptoms in rural older adults. Binary logistic regression was undertaken to determine the magnitude of the relationship for those factors that were found to be related to depression.

Results

Of the 2,586 participants, 1,461 (56.5%) were 60 to 69 years old; 1,263 (48.8%) were female; 2,258 (87.3%) had attended elementary school or less; 1,903 (73.6%) had a partner; and 1,867 were classified as having a median or low household economic status (72.2%), including 271 (10.5%) participants living under the poverty line (Table 1).

Participant Demographics (N = 2,586)

Table 1:

Participant Demographics (N = 2,586)

Three hundred sixty-six (14.2%) participants reported depressive symptom. Those aged 70 to 79 years and those aged >80 years were more likely to report depressive symptoms than the 60- to 69-year-old group (p < 0.001). More females reported depressive symptoms than males (p < 0.05). Participants whose formal education terminated at elementary school or earlier were more likely to report depressive symptoms than those with a higher education level (p < 0.01). This relationship to education was also true for older adults without a partner (p < 0.001). There were no significant differences in depressive symptoms based on economic status (p > 0.05), but those who were living below the poverty line were more likely to report elevated depressive symptoms (p < 0.001) (Table 1).

In addition, older adults who were underweight, had at least one chronic disease, were not mobile, were unable to care for themselves, unable to perform household chores, and experienced pain were more likely to report depressive symptoms (all p < 0.001). The rate of depressive symptoms was low for smokers (p < 0.01) and those who had drunk alcohol in the previous 12 months (p < 0.01). There was no significant difference in the incidence of depressive symptoms between the exercise and non-exercise groups (p > 0.05).

Binary logistic regression showed that after controlling factors such as gender, age, education level, poverty, and having a partner, the risk factors of depressive symptoms included experiencing pain (odds ratio [OR] = 10.52, p < 0.001), poor physical function and inability to undertake self-care (OR = 2.77, p < 0.001), and inability to perform household chores (OR = 2.59, p < 0.001) (Table 2). Smoking, drinking, and lack of mobility were no longer associated with depressive symptoms.

Association Between Health Behaviors, Chronic Disease, Physical Function, and Depressive Symptoms Among Chinese Rural Older Adults After Controlling for Demographic and Socioeconomic Factors

Table 2:

Association Between Health Behaviors, Chronic Disease, Physical Function, and Depressive Symptoms Among Chinese Rural Older Adults After Controlling for Demographic and Socioeconomic Factors

Discussion

The current study examined risk factors associated with depressive symptoms among older adults in rural China. The prevalence rate of depressive symptoms among Chinese older adults in the rural parts of Fujian was 14.2%, which is lower than the previously reported rate of 23.6% among older adults in China (Li, Zhang, Shao, Qi, & Tian, 2014) and the reported rate of 74.46% in Chinese older adults who did not have children or whose children had departed from home (Xie, Zhang, Peng, & Jiao, 2010).

Risk factors related to depressive symptoms were older age, being female, low education level, and having no partner, which were all consistent with previous studies among Asian populations (Hu et al., 2007; Tsai, Yeh, & Tsai, 2005). After adjusting for demographic and socioeconomic factors, having pain was revealed as the most profound factor related to depressive symptoms among older adults in rural China. Although this conclusion was consistent with previous research (Behera et al., 2016), the current study revealed that Chinese rural older adults were on average 10 times more likely to have depressive symptoms when pain presented, which was much higher than previous studies. Although no causal relationship can be identified from the current study design, it is possible that this relationship is reciprocal (Hamer, Bates, & Mishra, 2011). Previous studies have also revealed that pain may influence depressive symptoms by limiting an individual's activity participation levels (Parmelee, Harralson, Smith, & Schumacher, 2007). Regardless, offering pain relief remedies may help lower the risk of depressive symptoms, or help control the pain associated with depressive symptoms.

In addition, physical functions, such as the inability to provide self-care and perform household chores, were also risk factors for depressive symptoms. As with pain, whether depressive symptoms cause loss of physical function or vice versa is unable to be determined (Kraemer, Stice, Kazdin, Offord, & Kupfer, 2001). In a longitudinal study, depressive symptoms predicted declines in all domains of physical function among older adults (Turvey et al., 2009). Other studies have reported depressive symptoms as a consequence of loss of physical function (Scopaz, Piva, Wisniewski, & Fitzgerald, 2009). In this case, improving physical functioning may help decrease depressive symptoms. Unfortunately, access to relevant services, such as occupational therapy, remains limited for rural older adults in China (Shi & Howe, 2016). Other activities that could improve physical function, such as tai chi, should be promoted.

Unlike previous studies, the current study showed that smoking and drinking behaviors were inversely associated with depressive symptoms, but only when demographic and socioeconomic factors were not controlled. This finding may be due to the fact that only individuals in more favorable financial situations in China can afford non-essential goods, such as cigarettes and alcohol, especially older adults living in rural areas. Meanwhile, previous studies have shown that a better financial situation is a protective factor for depressive symptoms, which may cancel out the negative effects of smoking and drinking (McInerney et al., 2012). Overall, the relationship between risk behaviors and depressive symptoms among Chinese rural older adults needs further exploration.

Limitations

There are several limitations of the current study. First, the study sample was restricted to Fujian Province, which is not representative of the entire country. Second, although several risk factors for depressive symptoms were identified, the study design did not permit the identification of any causal relationship. There may be a mediation effect between those risk factors and depressive symptoms, which should be examined in future studies.

Implications for Practice

Living with pain is a primary factor associated with depression among Chinese rural older adults. In the Chinese culture, pain is considered something individuals have to tolerate or endure (Edrington et al., 2009). The current results suggest that community-based nursing programs for older adults are needed in rural China. These programs should focus on providing education and treatment for pain management, as well as helping older adults improve daily physical function. As women without a partner are at higher risk of developing depression, nurses and mental health professionals should pay special attention when working with this population. Screening protocols and counseling services for depression should be provided upon diagnosis.

Conclusion

The average lifespan in China has increased to 75.99 years (The World Bank, 2017), a benefit of the fast-growing economy and increased access to health care in the past decade. Although people's physical health has improved, mental health has received much less attention, especially that of older adults in rural areas. The current study identified risk factors that are strongly related to depressive symptoms among older adults in rural China, thus providing much needed additional evidence in this area.

References

  • Baiyewu, O., Yusuf, A. J. & Ogundele, A. (2015). Depression in elderly people living in rural Nigeria and its association with perceived health, poverty, and social network. International Psychogeriatrics, 27(12), 2009–2015 https://doi.org/10.1017/S1041610215001088 PMID: doi:10.1017/S1041610215001088 [CrossRef]26265242
  • Bao, C., Mayila, M., Ye, Z., Wang, J., Jin, M., He, W. & Chen, K. (2015). Forecasting and analyzing the disease burden of aged population in China, based on the 2010 Global Burden of Disease Study. International Journal of Environmental Research and Public Health, 12(7), 7172–7184 https://doi.org/10.3390/ijerph120707172 PMID: doi:10.3390/ijerph120707172 [CrossRef]26121188
  • Behera, P., Sharan, P., Mishra, A. K., Nongkynrih, B., Kant, S. & Gupta, S. K. (2016). Prevalence and determinants of depression among elderly persons in a rural community from northern India. The National Medical Journal of India, 29(3), 129–135 PMID:27808060
  • Bellos, S., Skapinakis, P., Rai, D., Zitko, P., Araya, R., Lewis, G. & Mavreas, V. (2016). Longitudinal association between different levels of alcohol consumption and a new onset of depression and generalized anxiety disorder: Results from an international study in primary care. Psychiatry Research, 243, 30–34 https://doi.org/10.1016/j.psychres.2016.05.049 PMID: doi:10.1016/j.psychres.2016.05.049 [CrossRef]27344590
  • Blixen, C. E., Wilkinson, L. K. & Schuring, L. (1994). Depression in an elderly clinic population: Findings from an ambulatory care setting. Journal of Psychosocial Nursing and Mental Health Services, 32(6), 43–49 PMID:7932308
  • Bruce, M. L. (2015). Caring for depression in older home health patients. Journal of Psychosocial Nursing and Mental Health Services, 53(11), 25–30 https://doi.org/10.3928/02793695-20151021-01 PMID: doi:10.3928/02793695-20151021-01 [CrossRef]26535761
  • Dardas, L. A., Shoqirat, N., Abu-Hassan, H., Shanti, B. F., Al-Khayat, A., Allen, D. H. & Simmons, L. A. (2019). Depression in Arab adolescents: A qualitative study. Journal of Psychosocial Nursing and Mental Health Services, 57(10), 34–43 https://doi.org/10.3928/02793695-20190528-01 PMID: doi:10.3928/02793695-20190528-01 [CrossRef]31188459
  • Edrington, J., Sun, A., Wong, C., Dodd, M., Padilla, G., Paul, S. & Miaskowski, C. (2009). Barriers to pain management in a community sample of Chinese American patients with cancer. Journal of Pain and Symptom Management, 37(4), 665–675 https://doi.org/10.1016/j.jpainsymman.2008.04.014 PMID: doi:10.1016/j.jpainsymman.2008.04.014 [CrossRef]
  • Fluharty, M., Taylor, A. E., Grabski, M. & Munafò, M. R. (2017). The association of cigarette smoking with depression and anxiety: A systematic review. Nicotine & Tobacco Research: Official Journal of the Society for Research on Nicotine and Tobacco, 19(1), 3–13 https://doi.org/10.1093/ntr/ntw140 PMID: doi:10.1093/ntr/ntw140 [CrossRef]
  • Gan, P., Xie, Y., Duan, W., Deng, Q. & Yu, X. (2015). Rumination and loneliness independently predict six-month later depression symptoms among Chinese elderly in nursing homes. PLoS One, 10(9), e0137176. doi:10.1371/journal.pone.0137176 [CrossRef]26334298
  • Hamer, M., Bates, C. J. & Mishra, G. D. (2011). Depression, physical function, and risk of mortality: National Diet and Nutrition Survey in adults older than 65 years. The American Journal of Geriatric Psychiatry, 19(1), 72–78 https://doi.org/10.1097/JGP.0b013e3181df465e PMID: doi:10.1097/JGP.0b013e3181df465e [CrossRef]
  • Hu, Z., Chen, R., Xu, S., Ma, S., Zhou, C. & Qin, X. (2007). Survey on prevalence of geriatric depression and influence factors in rural community. Chinese Journal of Public Health, 3, 257–258.
  • Koster, A., Bosma, H., Kempen, G. I., Penninx, B. W., Beekman, A. T., Deeg, D. J. & van Eijk, J. T. (2006). Socioeconomic differences in incident depression in older adults: The role of psychosocial factors, physical health status, and behavioral factors. Journal of Psychosomatic Research, 61(5), 619–627 https://doi.org/10.1016/j.jpsychores.2006.05.009 PMID: doi:10.1016/j.jpsychores.2006.05.009 [CrossRef]17084139
  • Kraemer, H. C., Stice, E., Kazdin, A., Offord, D. & Kupfer, D. (2001). How do risk factors work together? Mediators, moderators, and independent, overlapping, and proxy risk factors. The American Journal of Psychiatry, 158(6), 848–856 https://doi.org/10.1176/appi.ajp.158.6.848 PMID: doi:10.1176/appi.ajp.158.6.848 [CrossRef]11384888
  • Lee, J. E., Kahana, B. & Kahana, E. (2016). Social support and cognitive functioning as resources for elderly persons with chronic arthritis pain. Aging & Mental Health, 20(4), 370–379 https://doi.org/10.1080/13607863.2015.1013920 PMID: doi:10.1080/13607863.2015.1013920 [CrossRef]
  • Lefèvre, T., Singh-Manoux, A., Stringhini, S., Dugravot, A., Lemogne, C., Consoli, S. M. & Nabi, H. (2012). Usefulness of a single-item measure of depression to predict mortality: The GAZEL prospective cohort study. European Journal of Public Health, 22(5), 643–647 https://doi.org/10.1093/eurpub/ckr103 PMID: doi:10.1093/eurpub/ckr103 [CrossRef]
  • Li, D., Zhang, D. J., Shao, J. J., Qi, X. D. & Tian, L. (2014). A meta-analysis of the prevalence of depressive symptoms in Chinese older adults. Archives of Gerontology and Geriatrics, 58(1), 1–9. doi:10.1016/j.archger.2013.07.016 [CrossRef]
  • McInerney, M., Mellor, J. M. & Nicholas, L. H. (2013). Recession depression: Mental health effects of the 2008 stock market crash. Journal of Health Economics, 32(6), 1090–1104 https://doi.org/10.1016/j.jhealeco.2013.09.002 PMID: doi:10.1016/j.jhealeco.2013.09.002 [CrossRef]24113241
  • Miech, R. & Shanahan, M. (2000). Socioeconomic status and depression over the life course. Journal of Health and Social Behavior, 41(2), 162–176 https://doi.org/10.2307/2676303 doi:10.2307/2676303 [CrossRef]
  • Mossey, J. M. & Gallagher, R. M. (2004). The longitudinal occurrence and impact of co-morbid chronic pain and chronic depression over two years in continuing care retirement community residents. Pain Medicine, 5(4), 335–348 https://doi.org/10.1111/j.1526-4637.2004.04041.x PMID: doi:10.1111/j.1526-4637.2004.04041.x [CrossRef]15563319
  • Moussavi, S., Chatterji, S., Verdes, E., Tandon, A., Patel, V. & Ustun, B. (2007). Depression, chronic diseases, and decrements in health: Results from the World Health Surveys. Lancet, 370(9590), 851–858 https://doi.org/10.1016/S0140-6736(07)61415-9 PMID: doi:10.1016/S0140-6736(07)61415-9 [CrossRef]17826170
  • Parmelee, P. A., Harralson, T. L., Smith, L. A. & Schumacher, H. R. (2007). Necessary and discretionary activities in knee osteoarthritis: Do they mediate the pain-depression relationship?Pain Medicine, 8(5), 449–461 https://doi.org/10.1111/j.1526-4637.2007.00310.x PMID: doi:10.1111/j.1526-4637.2007.00310.x [CrossRef]17661863
  • Scopaz, K. A., Piva, S. R., Wisniewski, S. & Fitzgerald, G. K. (2009). Relationships of fear, anxiety, and depression with physical function in patients with knee osteoarthritis. Archives of Physical Medicine and Rehabilitation, 90(11), 1866–1873 https://doi.org/10.1016/j.apmr.2009.06.012 PMID: doi:10.1016/j.apmr.2009.06.012 [CrossRef]19887210
  • Scott, K. M., Bruffaerts, R., Tsang, A., Ormel, J., Alonso, J., Angermeyer, M. C. & Von Korff, M. (2007). Depression-anxiety relationships with chronic physical conditions: Results from the World Mental Health Surveys. Journal of Affective Disorders, 103(1–3), 113–120 https://doi.org/10.1016/j.jad.2007.01.015 PMID: doi:10.1016/j.jad.2007.01.015 [CrossRef]17292480
  • Shi, Y. & Howe, T. H. (2016). A survey of occupational therapy practice in Beijing, China. Occupational Therapy International, 23(2), 186–195 https://doi.org/10.1002/oti.1423 PMID: doi:10.1002/oti.1423 [CrossRef]26765795
  • Sorrell, J. M. (2016). Community-based older adults with mental illness: We can do better. Journal of Psychosocial Nursing and Mental Health Services, 54(11), 25–29 https://doi.org/10.3928/02793695-20161024-05 PMID:27805713
  • Tjora, T., Hetland, J., Aarø, L. E., Wold, B., Wiium, N. & Øverland, S. (2014). The association between smoking and depression from adolescence to adulthood. Addiction (Abingdon, England), 109(6), 1022–1030 https://doi.org/10.1111/add.12522 PMID: doi:10.1111/add.12522 [CrossRef]
  • Tsai, Y. F., Yeh, S. H. & Tsai, H. H. (2005). Prevalence and risk factors for depressive symptoms among community-dwelling elders in Taiwan. International Journal of Geriatric Psychiatry, 20(11), 1097–1102 https://doi.org/10.1002/gps.1413 PMID: doi:10.1002/gps.1413 [CrossRef]16250081
  • Turvey, C. L., Schultz, S. K., Beglinger, L. & Klein, D. M. (2009). A longitudinal community-based study of chronic illness, cognitive and physical function, and depression. The American Journal of Geriatric Psychiatry, 17(8), 632–641 https://doi.org/10.1097/JGP.0b013e31819c498c PMID: doi:10.1097/JGP.0b013e31819c498c [CrossRef]19634203
  • Vogel, J. S., Hurford, D. P., Smith, J. V. & Cole, A. (2003). The relationship between depression and smoking in adolescents. Adolescence, 38(149), 57–74 PMID:12803454
  • Volkert, J., Schulz, H., Härter, M., Wlodarczyk, O. & Andreas, S. (2013). The prevalence of mental disorders in older people in Western countries: A meta-analysis. Ageing Research Reviews, 12(1), 339–353 https://doi.org/10.1016/j.arr.2012.09.004 PMID: doi:10.1016/j.arr.2012.09.004 [CrossRef]
  • The World Bank. (2017). Life expectancy at birth. Retrieved from https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=CN
  • Xie, L. Q., Zhang, J. P., Peng, F. & Jiao, N. N. (2010). Prevalence and related influencing factors of depressive symptoms for empty-nest elderly living in the rural areas of YongZhou, China. Archives of Gerontology and Geriatrics, 50(1), 24–29. doi:10.1016/j.archger.2009.01.003 [CrossRef]
  • Xu, Y., Toobert, D., Savage, C., Pan, W. & Whitmer, K. (2008). Factors influencing diabetes self-management in Chinese people with type 2 diabetes. Research in Nursing & Health, 31(6), 613–625 https://doi.org/10.1002/nur.20293 PMID: doi:10.1002/nur.20293 [CrossRef]18613066
  • Young, Q. R., Nguyen, M., Roth, S., Broadberry, A. & Mackay, M. H. (2015). Single-item measures for depression and anxiety: Validation of the Screening Tool for Psychological Distress in an inpatient cardiology setting. European Journal of Cardiovascular Nursing, 14(6), 544–551 https://doi.org/10.1177/1474515114548649 PMID: doi:10.1177/1474515114548649 [CrossRef]
  • Zhang, L., Xu, Y. & Nie, H. (2011). A meta-analysis of depression among Chinese elders between 2000–2010. Zhongguo Laonianxue Zazhi, 17, 3349–3352.

Participant Demographics (N = 2,586)

Variablen (%)p Value
No Depressive Symptoms (n = 2,220)Elevated Depressive Symptoms (n = 366)
Sociodemographic Factors
  Age (years)<0.001
    60 to 691,310 (59)151 (41.3)
    70 to 79654 (29.5)126 (34.4)
    80256 (11.5)89 (24.3)
  Female gender1,063 (47.9)200 (54.6)<0.05
  Education<0.01
    Elementary school or less1,919 (86.4)339 (92.6)
    Junior high school256 (11.5)23 (6.3)
    Senior high school and above45 (2)4 (1.1)
  Having a partner1,679 (75.6)224 (61.2)<0.001
  Economic status>0.05
    Lowest (quintile 1)768 (34.6)136 (37.2)
    Lower (quintile 2)481 (21.7)81 (22.1)
    Median (quintile 3)354 (15.9)47 (12.8)
    Higher (quintile 4)301 (13.6)56 (15.3)
    Highest (quintile 5)316 (14.2)46 (12.6)
  Under poverty line202 (9.1)69 (18.9)<0.001
Risk Factors
  Body mass index<0.001
    Normal weight1,597 (71.9)244 (66.7)
    Underweight316 (14.2)84 (23)
    Overweight307 (13.8)38 (10.4)
  Having at least one chronic disease910 (41)244 (66.7)<0.001
  Difficulty in mobility218 (9.8)178 (48.6)<0.001
  Having pain/feeling uncomfortable415 (18.7)299 (81.7)<0.001
  Unable to take care of oneself110 (5)157 (42.9)<0.001
  Unable to perform household chores171 (7.7)189 (51.6)<0.001
Behavioral Factors
  Smoking622 (28)73 (19.9)<0.01
  Drinking over past 12 months484 (22)53 (14.8)<0.01
  Not exercising at least once per week2,030 (91.4)340 (92.9)>0.05

Association Between Health Behaviors, Chronic Disease, Physical Function, and Depressive Symptoms Among Chinese Rural Older Adults After Controlling for Demographic and Socioeconomic Factors

ParametersOR95% CIp Value
Body mass index>0.05
  Normal weight1
  Underweight0.94[0.66, 1.35]
  Overweight0.63[0.40, 0.99]
Having one or more chronic diseases<0.05
  No1
  Yes1.36[1.02, 1.83]
Difficulty in mobility>0.05
  No1
  Yes0.76[0.48, 1.21]
Unable to provide self-care<0.001
  No1
  Yes2.77[1.69, 4.56]
Unable to perform household chores<0.001
  No1
  Yes2.59[1.58, 4.25]
Having pain/feeling uncomfortable<0.001
  No1
  Yes10.52[7.62, 14.54]
Smoking>0.05
  No1
  Yes0.76[0.51, 1.14]
Drinking>0.05
  No1
  Yes0.91[0.61, 1.37]
Authors

Dr. Yan is Associate Professor, Department of Public Health and Nutrition, School of Health Sciences, Merrimack College, North Andover, Massachusetts; Ms. Lu is Associate Professor, and Mr. Li is Professor and Mr. Zheng is Professor, School of Public Health, Health Research Institute, Fujian Medical University, Fujian, China.

The authors have disclosed no potential conflicts of interest, financial or otherwise. The soft science project was supported by the Science and Technology Department of Fujian Province (2017R0043); and the Startup Fund for scientific research was supported by Fujian Medical University (2016QH011).

Address correspondence to Ruoyan Lu, MS, Associate Professor, and Yueping Li, MPH, Professor, School of Public Health, Fujian Medical University, 1 Xuefu North Road, University Town, Fuzhou, Fujian, China 350108; e-mail: Lry05@163.com; fmulyp@163.com.

Received: July 03, 2019
Accepted: September 03, 2019
Posted Online: November 11, 2019

10.3928/02793695-20191030-01

Sign up to receive

Journal E-contents