Background
China, with over 1.3 billion citizens is the world's most populous country [
1]. Demographic ageing is occurring at a rate unprecedented for any world region; the proportion of Chinese aged 65 and over will increase from 4% in 2000 to 14% by 2025, amounting to 200 million older people [
2]. The prevention and control of chronic diseases is recognised as an urgent priority in China [
3,
4]. The long term care needs of dependent older people has, comparatively, received much less attention [
5‐
7]. A little over half of China's population lives in rural settings, [
8] the proportion among older people is likely to be higher.
The literature on rural/urban differences in health in China suggests three main areas for further study. First, there may be differences in chronic disease prevalence and mortality. Data from the China Health and Nutrition survey showed a 30% increased mortality for those aged 50 and over in rural compared with urban areas, partly mediated through the lack of amenities and lower wages in rural areas [
9]. However, in the third Chinese National Health Service Survey (CNHSS), [
10] the prevalence of self-reported physician diagnoses of chronic diseases was lower among rural than urban residents. In the 1991 Beijing Longitudinal Study on Aging (BLAS), [
11] urban residents were 3.2 times more likely to report chronic disease diagnoses, 4.5 times more likely to report diabetes and 2.5 to three times more likely to report respiratory disease, heart disease and hypertension. On the other hand, levels of disability were similar in the CNHSS, [
10] and considerably higher in rural areas in BLAS [
11]. Hypertension, when measured directly as opposed to by self-report, is more prevalent in rural areas, [
11] and awareness is higher in urban areas [
12]. Hence, rural communities seem to be advantaged with respect to some health outcomes, and disadvantaged in others. More research is required to confirm these findings, and to clarify the reasons for the apparent discrepancies.
Second, in China, financing, coverage and access to healthcare depends, largely upon where you live. Only 61% of rural residents, compared with 82% of urban dwellers can access health services within one kilometre of their homes [
13]. In urban China, there are two employee-based health insurance schemes, one for government and the other for public and private company employees. There is limited cover for dependents, based on a personal annual subscription. Discounts are available for poor people, those with mental disorders, and retirees. In rural China, the government contributes to a common fund which covers healthcare costs but only proportionate to the amount contributed. In 2003, 79% of rural and 45% of urban residents did not have meaningful health insurance [
12]. Almost 50% of health care costs are covered by out-of-pockets payments [
14] and more than 35% of urban and 45% of rural households cannot afford any health care [
15]. The consequences of these disparities for rural and urban older people, in terms of their ability to access healthcare and to manage their chronic diseases, need to be determined.
Third, social protection (encompassing the range of formal and informal mechanisms to provide safety nets and support to poor and disadvantaged members of society) is under threat for older people in China, as its population ages rapidly. In traditional societies social protection is provided by the family and community. With modernisation, these responsibilities are shared by wider society through intergenerational transfers legislated for and managed by the state [
16]. However, in the future there will be fewer children available to provide support and care because of the one child policy [
17], and social protection by the state, both in terms of pension coverage and insurance against catastrophic healthcare expenditure, remains very patchy [
18]. It is important to understand how these processes may be playing out with respect to older people living in urban and rural communities.
In summary, the urban bias of public policy is particularly marked in China, and older people living in rural areas may be especially vulnerable. The Research Agenda on Ageing Project [
19] has advocated more research on this group, including demographic and migration patterns; social transitions; family exchanges; health behaviours and use of and access to healthcare. In this paper we seek to pursue this agenda by
a)
comparing the socio-demographic and health characteristics of representative samples of older people in two Beijing communities, urban Xicheng and rural Daxing.
b)
describing the patterns of recent health service utilization among rural and urban elderly and estimating the independent effect of health conditions, socio-demographic and socioeconomic factors on access to and use of these services.
c)
comparing the levels of disability and needs for care, informal care arrangements and extent of carer strain with respect to dependent older people in urban Xicheng and rural Daxing.
Results
In all, 2162 (1160 urban and 1002 rural) participants completed the survey, with 95.7% responding in rural Daxing and 74.3% in urban Beijing, where more eligible people refused to participate or could not be contacted after at least four attempts. The urban elderly were better educated and older, and less likely to be widowed than their rural counterparts (Table
1). Living alone was unusual in either setting, but urban residents were more likely to be living with their spouse only, and less likely to be living with children. Pension coverage was much lower in the rural (3.8%) than the urban sample (90.5%). Conversely, family transfers and rental income were much more common in the rural sample. Only nine urban participants and one rural participant reported receiving a disability pension.
Table 1
Social-demographic characteristics in Daxin (rural) and Beijing (urban)
Age group (MV) | 0 | 0 | | | |
65-69 years | 316(27.2%) | 383(38.2%) | 40.4 | 3 | < 0.001 |
70-74 years | 362(31.2%) | 296(29.5%) | | | |
75-79 years | 254(21.9%) | 202(20.2%) | | | |
80+ years | 228(19.7%) | 121(12.1%) | | | |
Gender (MV) | 0 | 0 | | | |
Female | 661(57.0%) | 556(55.5%) | 0.5 | 1 | 0.49 |
Education level (MV) | 0 | 0 | | | |
No education | 232(20.0%) | 579(57.8%) | 491.9 | 3 | < 0.001 |
Primary education only | 456(39.3%) | 373(37.2%) | | | |
Completed secondary | 335(28.9%) | 45(4.5%) | | | |
Completed tertiary | 137(11.8%) | 5(0.5%) | | | |
Marital status (MV) | 0 | 0 | | | |
Never married | 3(0.3%) | 22(2.2%) | 52.0 | 3 | < 0.001 |
Married or cohabiting | 829(71.5%) | 585(58.4%) | | | |
Widowed | 326(28.1%) | 394(39.3%) | | | |
Divorced or separated | 2(0.2%) | 1(0.1%) | | | |
Previous occupation
1
(MV) | 1 | 1 | | | |
Professional/Managerial/Clerical | 518(45.0%) | 37(3.7%) | 1888.6 | 3 | < 0.001 |
Skilled or semi-skilled | 421(36.5%) | 14(1.4%) | | | |
Unskilled | 207(18.0%) | 13(1.3%) | | | |
Agricultural worker | 7(0.6%) | 938(93.6%) | | | |
Living arrangements (MV) | 0 | 0 | | | |
Alone | 54(4.7%) | 49(4.9%) | 202.0 | 3 | < 0.001 |
With spouse only | 415(35.8%) | 194(19.4%) | | | |
With children | 446(38.4%) | 679(67.8%) | | | |
With others | 245(21.1%) | 80(8.0%) | | | |
With children under 16 | 217(18.7%) | 462(46.1%) | 187.4 | 1 | < 0.001 |
Source of income (MV) | 0 | 0 | | | |
Government or occupational pension | 1050 (90.5%) | 38(3.8%) | 1617.5 | 1 | < 0.001 |
Family transfers | 54(4.7%) | 305(36.4%) | 347.3 | 1 | < 0.001 |
Disability pension | 9(0.8%) | 1(0.1%) | 5.3 | 1 | 0.02 |
Rent | 0 | 122(12.2%) | 149.7 | 1 | < 0.001 |
Paid work | 0 | 6(0.6%) | 7.0 | 1 | 0.008 |
Have health insurance plan | 14(1.2%) | 769(76.9%) | 1327.2 | 1 | < 0.001 |
Number of household assets
2
(MV) | 0 | 0 | | | |
0-3 assets | 6(0.5%) | 108(10.8%) | 113.3 | 1 | < 0.001 |
More than 3 assets | 1154(99.5%) | 894(89.2%) | | | |
All of the self-reported diagnoses and impairments, except hearing problem and limb impairment, were much less common in the rural sample (Table
2). Older people in the rural sample were four times less likely to report three or more limiting impairments and nearly five times more likely to rate their health positively. The picture was different for diagnoses made on the basis of clinical interview and examination. The prevalence of dementia was similar, while that of hypertension was just 20% lower, and that of uncontrolled hypertension 30% higher in the rural sample. Significantly more rural (22.2%) than urban (13.6%) elderly reported chronic pain. Rural residents were more likely to have smoked, and to continue to smoke, to have engaged in hazardous drinking, and to be sedentary, but were less likely to be obese.
Table 2
Health status in Xicheng (urban) and Daxing (rural).
Diagnosed diseases (MV) | 0 | 0 | |
Dementia | 84(7.2%) | 56(5.6%) | 0.96(0.70-1.32) |
History of hypertension, and/or meets ESH criteria | 726(62.6%) | 500(49.9%) | 0.80(0.74-0.87) |
Uncontrolled hypertension (ESH criteria) | 471(40.6%) | 487(48.6%) | 1.29(1.10-1.33) |
ICD-10 Depression | 3(0.3%) | 7(0.7%) | 3.05(0.83-11.2) |
Self-reported diagnoses (MV) | 1 | 0 | |
Diabetes | 195(16.8%) | 9(0.9%) | 0.05(0.03-0.10) |
Ischaemic heart disease (myocardial infarction or angina) | 115(9.9%) | 12(1.2%) | 0.12(0.07-0.23) |
Stroke | 109(9.4%) | 18(1.8%) | 0.20(0.12-0.34) |
Chronic obstructive pulmonary disease | 36(3.1%) | 16(1.6%) | 0.54(0.30-0.96) |
Self-reported impairments (MV) | 0 | 0 | |
Arthritis | 165(14.2%) | 20(2.0%) | 0.14(0.09-0.23) |
Eye problem | 194(16.7%) | 65(6.5%) | 0.41(0.31-0.55) |
Hearing problem | 142(12.2%) | 86(8.6%) | 0.83(0.64-1.08) |
Cough problem | 33(2.8%) | 14(1.4%) | 0.51(0.27-0.96) |
Breathing problem | 52(4.5%) | 19(1.9%) | 0.45(0.27-0.74) |
Heart problem | 329(28.4%) | 31(3.1%) | 0.11(0.08-0.16) |
Gastrointestinal problem | 67(5.8%) | 12(1.2%) | 0.22(0.12-0.40) |
Fainting problem | 62(5.3%) | 10(1.0%) | 0.19(0.10-0.37) |
Limb problem | 72(6.2%) | 44(4.4%) | 0.77(0.53-1.12) |
Skin problem | 12(1.0%) | 2(0.2%) | 0.20(0.04-0.94) |
Three or more physical impairments | 208(17.9%) | 39(3.9%) | 0.23(0.17-0.33) |
Pain that interferes with life | 158(13.6%) | 222(22.2%) | 1.60(1.31-1.94) |
Locomotion (observed) (MV) | 0 | 0 | |
Obvious abnormality of walking | 53(4.6%) | 27(2.7%) | 0.64(0.41-1.04) |
WHODAS II disability score (MV) | 10 | 2 | |
Mean | 8.1 ± 20.1 | 8.0 ± 14.6 | 1.20(0.96-.49)1
0.59(0.51-0.67)2
|
Self-rated health (MV) | 0 | 0 | |
'Good' or 'very good' | 176(15.2%) | 690(68.9%) | 4.59(3.94-5.35) |
Dependency
| 0 | 0 | |
Needs any care | 183(15.8%) | 54(5.4%) | 0.41(0.30-0.54) |
Needs much care | 119(10.3%) | 30(3.0%) | 0.34(0.23-0.51) |
Chronic disease risk factors (MV) | 12 | 4 | |
Ever smoked | 284(24.5%) | 336(33.5%) | 1.28(1.12-1.46) |
Current smoker | 193(16.6%) | 305(30.4%) | 1.68(1.43-1.97) |
20 or more pack years of smoking | 180(15.5%) | 274(27.3%) | 1.62(1.38-1.91) |
Hazardous drinker in early life | 26(2.2%) | 73(7.3%) | 2.89(1.83-4.52) |
Current hazardous drinker | 17(1.5%) | 42(4.2%) | 2.66(1.55-4.56) |
No walks of > 0.5 km in last month | 209(18.0%) | 384(38.3%) | 1.39(1.32-1.47) |
Obesity (meets waist circumference criterion for metabolic syndrome) | 530(45.7%) | 158(15.8%) | 0.35(0.30-0.41) |
Rural residents (6.1%) were strikingly less likely than urban residents (38.6%) to have used any health services over the three months prior to the survey. Underutilisation of services by rural residents was apparent even after controlling for age, gender and number of limiting physical impairments (Prevalence ratio 0.24, 95% CI 0.19 to 0.32). Underutilisation by rural elderly was equally apparent for primary care services (3.8% versus 20.9%, adjusted PR 0.32, 95% CI 0.23 to 0.45), hospital doctor services (2.2% versus 23.4%, adjusted PR 0.14, 95% CI 0.09 to 0.22) and hospital admission (0.5% versus 2.4%, adjusted PR 0.43, 95% CI 0.15-1.20). Hypertension was less likely to be detected among rural compared with urban residents, and detected cases were much less likely to be controlled (Table
3). The net result was that only 2.6% of all cases of hypertension were controlled in rural Daxing compared with 35.1% in urban Xicheng.
Table 3
Detection and control of hypertension, by site
Detection and control of hypertension (MV) | 0 | 0 | | | |
The proportion of all hypertension cases that are detected | 78.5%(570/726) | 50.8%(254/500) | 103.2 | 1 | < 0.001 |
The proportion of detected cases that are treated | 96.8%(552/570) | 99.6%(253/254) | 6.0 | 1 | 0.015 |
The proportion of detected cases that are controlled | 44.7%(255/570) | 5.1%(13/254) | 125.7 | 1 | < 0.001 |
The proportion of all cases that are controlled | 35.1% (255/726) | 2.6% (13/500) | 181.5 | 1 | < 0.001 |
In both urban and rural sites, numbers of physical impairments were the strongest independent predictors of health service utilisation, after controlling for age, gender, education, assets, pension availability and health insurance (Table
4). Dementia was associated with health service utilization only in rural Daxing, but the association was no longer apparent after controlling for covariates. Economic factors (household assets, receipt of pension and health insurance) predicted health service utilization only in urban Xicheng.
Table 4
Predictors of health service utilization (crude and adjusted robust Prevalence Ratios [PRs] with 95% confidence intervals [CI])
Dementia | 1.12(0.86-1.45) | 2.19(1.05-4.57) | 0.94(0.73-1.20) | 1.54(0.82-3.06) |
Number of limiting physical illnesses | | | | |
None | 1 (ref) | 1 (ref) | 1(ref) | 1 (ref) |
1-2 | 2.32(1.76-2.84) | 4.02(2.31-7.00) | 2.26(1.79-2.87) | 3.82(2.12-6.85) |
3 or more | 3.78(2.98-4.81) | 8.91(4.52-17.6) | 3.74(2.94-4.75) | 8.31(4.06-17.0) |
Age (per 5 year increment) | 1.03(0.96-1.10) | 0.93(0.73-1.17) | 1.00(0.96-1.08) | 0.80(0.61-1.04) |
Gender (male vs. female) | 0.91(0.79-1.04) | 0.87(0.53-1.41) | 0.89(0.77-1.03) | 0.99(0.58-1.70) |
Education (per level) | 1.04(0.99-1.09) | 0.90(0.77-1.07) | 1.02(0.96-1.08) | 0.86(0.63-1.19) |
Assets (per quarter) | 1.28(1.14-1.44) | 0.90(0.77-1.05) | 1.23(1.09-1.38) | 0.84(0.70-1.02) |
Any government or occupational pension | 1.51(1.10-2.08) | 1.31(0.43-3.98) | 1.46(1.07-1.99) | 1.17(0.39-3.57) |
Have health insurance | 1.87(1.33-2.62) | 1.75(0.90-3.41) | 1.94(1.28-2.95) | 1.58(0.82-3.06) |
Among the 237 participants who were rated as needing care we described levels of disability and dependency, informal care arrangements and carer strain by site (Table
5). In both settings, people with dementia were more disabled than other needing care (mean WHODAS II score 61.1, SD 30.6 versus 33.1, SD 25.7 in Xicheng; 65.5, SD 24.3, p < 0.001 versus 33.6, SD 22.7, p < 0.001 in Daxing) and more likely to be rated as needing care 'much of the time' (77% versus 57%, p = 0.005 in Xicheng; 64% versus 46%, p = 0.18 in Daxing). Carers of people with dementia spent more time assisting with basic activities of daily living (tests for trend
χ
2 = 14.1,
P = 0.001 in Xicheng,
χ
2 = 9.9,
P = 0.007 in Daxing), particularly communication, dressing, eating, grooming and toileting. Caregiver strain, measured using the Zarit Burden Interview was also higher among those caring for people with dementia (mean ZBI score 26.4, SD 20.6, p < 0.001 versus 12.1, SD 12.6, p < 0.001 in Xicheng; 17.1, SD 14.9 versus 5.3, SD 7.7 in Daxing, p < 0.001). It was therefore important to control for dementia diagnosis, as well as the age and gender of the participant when comparing care-related variables between rural and urban settings (Table
5). Adjusted analyses suggested no differences in levels of disability or dependency between rural and urban older people needing care. However, rural carers spent less time assisting with core activities of daily living, and reported lower levels of strain. Paid care was a common option in urban Beijing; one half of dependent people with dementia and slightly less than one half of all urban dependent people paid for daytime care, with a similar proportion using night time care. Only one rural family used paid daytime care. Instead, rural carers were nearly 12 times more likely to give up or cut back on work to care, and nearly three times more likely to benefit from additional informal care from friends or family.
Table 5
Levels of disability and dependency, informal care arrangements and carer strain (among those identified as needing care), by site
Disability and dependency (in the care recipient) (MV) | 0 | 2 | |
WHODAS 12 Disability score (mean [SD]) | 44.2 (30.9) | 50.2 (28.4) | 1.7 (-6.8,10.3)1
|
Needs care 'much of the time' | 119 (65.0%) | 30 (55.6%) | 0.81 (0.63, 1.05)2
|
Time spent by the carer assisting with ADL (MV) | 0 | 0 | |
0 hours | 28 (15.3%) | 7 (13.0%) | 0.52 (0.43-0.63)3
|
1-4 hours | 57 (31.1%) | 26 (48.1%) | |
5 hours + | 98 (53.6%) | 21(38.9%) | |
Assistance provided for specific ADL (> one hour/day) (MV) | 0 | 0 | |
Supervision | 16 (8.7%) | 8 (14.8%) | 1.64 (0.70-3.85)2
|
Communication | 65 (35.5%) | 22 (40.7%) | 1.13 (0.78, 1.64)2
|
Using transport | 8 (4.4%) | 2 (3.7%) | 0.93 (0.23, 3.75)2
|
Dressing | 55 (30.1%) | 10 (18.5%) | 0.59 (0.33, 1.05)2
|
Eating | 57 (31.1%) | 15 (27.8%) | 0.78 (0.50, 1.22)2
|
Grooming | 57 (31.1%) | 10 (18.5%) | 0.55 (0.31, 1.00)2
|
Toileting | 73 (39.9%) | 14 (25.9%) | 0.61 (0.38, 0.96)2
|
Bathing | 57 (31.1%) | 10 (18.5%) | 0.55 (0.31, 1.00)2
|
Caregiver Strain
| 3 | 0 | |
Zarit Burden Interview Score (mean [SD]) | 17.9 (17.7) | 11.4 (13.3) | -8.7 (-3.9, -13.5)1
|
Caregiver mental health | | | |
SRQ-20 Score | | | |
Mean (SD) | 0.9(2.3) | 1.3(2.6) | 0.1(-0.6,0.8)1
|
Median (IQR | 0(0,1.0) | 0 (0,1.0) | |
Characteristics of main carer (MV) | 1 | 2 | |
Relationship to older person | | | |
Spouse | 71 (38.8%) | 21 (38.9%) | - |
Child | 69 (37.7%) | 21 (38.9%) | |
Daughter-/son-in-law or other relative | 13 (7.1%) | 11 (20.4%) | |
Non-relative | 30 (16.4%) | 1 (1.9%) | |
Gender | | | |
Female | 123 (67.2%) | 27 (50.0%) | 1.15 (1.05, 1.27)2
|
Care arrangements (MV) | 0 | 1 | |
Daytime paid carer | 83 (45.4%) | 1 (1.9%) | 0.05 (0.01, 0.33)2
|
Night time paid carer | 81 (44.3%) | 0 | - |
Carer cut back on work to care | 7 (3.8%) | 26 (48.1%) | 11.7 (5.20, 26.4)2
|
Additional informal care | 13 (7.1%) | 12 (22.2%) | 2.78 (1.37, 5.63)2
|
Discussion
We carried out a comprehensive one phase survey of two catchment areas in Beijing province; Daxing's rural villages and Xicheng in the heart of Beijing city. There were relatively few non-responders, but the higher proportion in urban Xicheng (25.7%) compared with rural Daxing (4.3%) creates some potential for response bias. We applied the same catchment area sampling techniques and research protocol in both settings, and the same research group supervised the implementation of the research. Given the proximity, shared language and culture of the two sites, we believe that the comparison was apt and likely to be informative regarding the impact of contrasting infrastructure, policies, lifestyles and family structures on health outcomes and chronic disease care. However, clearly, findings from this comparison cannot be generalised to urban and rural settings in China as a whole. In particular, Daxing is less remote, and better resourced than the majority of rural locations in China. We set out to compare rural and urban samples with respect to the health status of older people, their use of health services, and their needs for informal care. For older people, these three elements are very much inter-related. Other studies that have addressed just one or other of these elements in isolation have not provided a comprehensive overview of chronic diseases, their consequences and their management, and how these might differ in urban and rural populations. However, the broad agenda for this paper has meant that we have not been able to address each topic in detail, for which more in-depth dedicated studies will be required.
Self-reported chronic disease diagnoses (diabetes, heart disease and stroke) were more prevalent in urban Xicheng than in rural Daxing. These findings are consistent with reports from previous Chinese surveys, [
37‐
39] but need to be interpreted with caution. There may be systematic under-ascertainment in rural sites because of low levels of awareness and help-seeking, under-detection and under-treatment. Of note, hypertension and dementia, ascertained from clinical assessments in the survey, were similarly prevalent in both sites. Low levels of education may have contributed to ignorance of chronic diseases and under-reporting [
11] On the other hand, the prevalence of self-reported impairments was also much lower among older people in rural Daxing, consistent with their better self-rated overall health. Also, when zero inflation was accounted for the disability score count in the rural site was 40% lower. The lesser needs for care among rural elderly, based upon global assessment by the interviewer, is again consistent with a lower prevalence of chronic disease in Daxing. However, in interpreting these differences in health perception we should bear in mind Amartya Sen's allusion to the substantial evidence that "people in states that provide more education and better medical and health facilities are in a better position to diagnose and perceive their own morbidities than the people in less advantaged states, where there is less awareness of treatable conditions (to be distinguished from "natural" states of being)" [
40]. Selective mortality may be an additional explanation for the differences in health outcomes. For rural residents a 30% excess mortality is consistently observed across several data sets, from midlife onwards. The younger age and higher proportion of widows and widowers in Daxing compared with Xicheng is consistent with a difference in midlife mortality between the two populations. Unhealthier lifestyles among the rural elderly may have contributed. Consistent with our findings, a survey in Hubei Province showed higher levels of smoking and alcohol use, and much lower levels of physical activity among older people in rural compared with urban districts [
41]. While our data suggests a decline in the prevalence of current smoking among older people compared with the Beijing Longitudinal Ageing Study conducted in 1991; [
11] this decline was more pronounced in urban (from 48.2% to 16.6%) than in rural districts (from 43.5% to 30.4%). In summary, our data, considered in the context of other Chinese surveys, is in no way reassuring regarding the underlying health status of the Chinese rural elderly population.
The differences in our survey in the accessibility and effectiveness of the urban and rural health services were striking. In the Third Chinese National Health Services Survey, rural and urban residents with an illness in the past two weeks were equally likely to seek help from a physician; hospitalisations were less frequent among rural residents, but only among those aged 65 and over [
37,
42]. However, fewer than 7% of our rural sample as opposed to nearly 40% of the urban used any health service in the three months preceding the interview. In both sites, physical health was the strongest predictor of the use of health services. Our findings were not explained by the younger age and better health of rural residents. The limited availability of local health services, [
38,
43] rural poverty, [
37,
44] the lack of effective insurance cover after the collapse of the rural Cooperative Medical System, and sharp increases in charges under the new fee-for-service system [
42] are all likely to be implicated. Economic factors (household assets, receipt of pension and possessing health insurance) were all independently associated with accessing healthcare in urban Xicheng, and may have explained some of the differences in help-seeking between the two sites; limited variance of these factors probably accounts for the lack of association in rural Daxing. Detection and control of hypertension is an important index of the effectiveness of community healthcare. The control of blood-pressure-related disease is a global health priority [
45]. The prevalence of hypertension among older people in China has risen sharply over the period 1991-2006, [
12,
46,
47] and prevention and control are also clear national priorities. Parameters for awareness and control in urban Xicheng were similar to those recently reported for older people in urban Chengdu, [
48] while those for rural Daxing were a little worse than those from the national InterASIA survey of 2000-2001, described at that time as 'unacceptably low' [
49].
Underutilisation of health services, and lack of routine medical checks may explain the low detection rates [
13,
22,
50]. Lack of control among those who were detected and treated was a particular problem in rural Daxing. In Chengdu, [
4] lack of control of hypertension was associated with infrequent blood pressure checks, under-treatment, poor treatment adherence, and ignorance of risk factors and potential complications. Hypertension in mid-life is a recognized risk factor for dementia [
51‐
53] Therefore, the extent to which prevention and control of hypertension can be established early in the coming epidemic in China and other LAMIC may have important implications for the size of the predicted increase in numbers of people with dementia in those regions [
54]. As others have noted, there is an urgent need to promote access to healthcare in China [
42]. Adequate insurance or subsidy to cover health care costs, need to be extended to those outside of the urban cadres, particularly rural residents, those without formal employment and older people [
18]. Community healthcare services need to be strengthened. However, attention needs also to be given to increasing the demand for healthcare; health promotion and education to encourage healthy behaviours and help-seeking [
55]. Older people need to be targeted [
41].
In Daxing, the burden of support and care, where it was required, fell mainly on family members who had often given up work to care. In Xicheng, family members rarely gave up work to care, paid caregivers being employed instead. These stark differences are understandable in the context of China's rapid economic development. Urban Beijing is experiencing a boom, while development in rural areas stagnates. Widening differentials in salary levels between the city and the country drive the trend towards the employment of women from less developed provinces to care for dependent older people in the city. Residential care is costlier, and associated with considerable stigma. Some caution is indicated in interpreting the higher levels of carer strain among urban compared with rural carers, since measurement bias between urban and rural settings may have been implicated; nevertheless, the finding seems plausible. Although the literature is inconsistent on this point, [
56] juggling work roles with those of parent, organisational and 'hands-on' caregiver for an older relative can be stressful. In Daxing, traditional extended family living arrangements are still the norm, with neighbours and relatives available to provide additional informal care. In China, as in the Dominican Republic [
35] and the USA [
36] dementia is consistently associated with greater needs for care, more time spent caregiving and greater caregiver strain. Non-communicable diseases are already leading causes of mortality in China [
55] and the pace of demographic ageing in China is such that predicted increases in numbers of dependent people [
57], and numbers of people with dementia [
54] will be greater in absolute and relative terms than for almost any other world region. Developing policies and investing in long-term care should be key priorities, alongside health sector reform.
Competing interests
The 10/66 Dementia Research Group works closely with Alzheimer's Disease International (ADI), the non-profit federation of 77 Alzheimer associations around the world. ADI is committed to strengthening Alzheimer associations worldwide, raising awareness regarding dementia and Alzheimer's Disease and advocating for more and better services for people with dementia and their caregivers. ADI is supported in part by grants from GlaxoSmithKline, Novartis, Lundbeck, Pfizer and Eisai.
Authors' contributions
MP leads the 10/66 Dementia Research Group study and CF acts as research coordinator assisted by EA and RS. SL and YH are the principal investigators in China, and ZL is the study coordinator in China. They were assisted in the conduction of the study by FY and WD. ZL and EA wrote the first draft of the paper and carried out the analyses with the assistance of MP and YH. All other authors reviewed the report and provided further contributions and suggestions. All authors approved the final manuscript.