Factors associated with quality of life among joint and nuclear families using the World Health Organization's quality of life instrument (WHOQOL-BREF).

Family system has been found to affect the quality of life (QOL) among joint and nuclear family systems. In Pakistan, there is scarcity of literature about QOL among joint and nuclear family systems. We determined the factors associated with QOL scores in joint and nuclear family systems in Pakistani general population in District Abbottabad, Pakistan. We conducted a population based cross sectional study in all 52 Union Councils (UCs) of District Abbottabad, Khyber Pakhtunkhwa province, Pakistan from March 2015 to August 2015. Multistage cluster sampling technique was used to select 2063 participants from both nuclear and joint family houses. A validated Urdu version of WHO QOL-BREF was used to assess level of quality of life among participants. Univariate and multivariate analysis was done to nd out the association of different socio demographic variables with QOL among both family systems. A multilevel linear regression using backward analysis allowing to obtain nal model for each domain was done to nd out the variables that affect QOL score among both family systems.


Introduction
Family is one of the fundamental units of societies and takes care of the diverse needs of people [1]. It is the basic source of providing care to all of its members. Because of this fact elderly persons of the house occupy respectful position in Asian culture. Family system encourages the life of individuals in all aspects which enables them to live happy and productive life [2]. Culture has been shown to regulate the family network by building family type, family size and form [3,4] and the family functioning by de ning barriers, cooperation rules, connection patterns, adequate practices, regulation and ranking in the family [4][5][6][7].
There are different classi cations of family systems [8,9]. Most commonly used classi cation has two types i.e. joint and nuclear family systems [10]. A nuclear family system is de ned as "a two generation family consisting of a father and mother and children or a single, possibly widow, parent and his/her children" [11]. Similarly joint or extending family is de ned as "three or more generations lived together with both vertical and lateral extension having a single line of authority, either patrilineal or matrilineal" [11]. Joint families are stable, ful ll basic needs of members, provide opportunity for savings as expenditures are distributed, protection of members during emergencies and catastrophe, gives social security for the elderly and other dependent members and opportunity for leisure time and recreation. On the other hand joint family system is associated with less physical space, autonomy and privacy and is more conservative [12].
Nuclear family system provides privacy, sense of freedom, opportunity for joint decision making by husband and wife and maximum time for their children. On the other hand in nuclear family, if both the spouses are working than they have to keep their children home alone or to be baby-sitted, which increases the expenditures. Furthermore, in a nuclear family feeling of safety and security is lacking and there is less family support [12].
Extent of these systems varies from countries to countries and within countries as well. Traditionally Pakistan had joint family system and bonding within a family. Like other Asian countries, over the time, balance is shifting towards nuclear family system in Pakistan. Multiple factors are responsible for this shifting trend from joint to nuclear system. These include; nancial pressures, decreasing living space, movement for job and rapid urbanization. This trend is faster in urban areas than rural areas. The superiority of one of these systems is a matter of debate these days. The researchers are on a quest for evidence based information regarding the current debate about the quality of life of an individual, based on a family system [13].
In Pakistan, a large number of the aged people depend on their family especially on their children or grandchildren for physical, communal and nancial support [2] which is more convenient in joint families. It was recommended by Mason (1992) that urbanization is expected to negatively affect the family's capacity and willingness for care of the elderly and it will also decrease the chances of living grown up children with their parents [14]. Studies from Asian countries have shown that most of the help for the elderly people comes from their home by their children/grandchildren [15,16].
Although all of the work done before was on health-related QOL all around the world, but there are no such study exploring the predictors of quality of life of people who live in nuclear or joint family system. Our study presented the predictors of quality of life scores in joint and nuclear family systems in Pakistani general population sample from District Abbottabad, Pakistan.

Study design and setting
We conducted a population based cross sectional study in all 52 Union Councils of District Abbottabad, Khyber Pakhtunkhwa province, Pakistan from March 2015 to August 2015. We recruited 2063 participants for our study. Abbottabad is the main district of Khyber Pakhtunkhwa province of Pakistan having more than 1.2 million population living in 52 union councils. The primary language spoken here is Hindko (used by 94% of the rural population and 75% of urban residents) followed by Urdu which is also spoken and understood in rural & urban areas [17].

Sample size
We used WHO software for Sample Size Determination in Health Studies. A difference of 2.5 in quality of life score was considered as signi cant between two groups. Pooled standard deviation of scores of two groups was taken as 12 from the pilot study. To detect this difference at 95% con dence level with 90% power with design effect of 1.8 and 10% in ation for missing information, the nal calculated sample size was 968 in each group, which makes the total sample size of 1936 participants.

Sampling plan
Participants of this study were selected from all union councils (UCs) of District Abbottabad. Multi -stage cluster sampling technique was employed in this study. Each union council was further divided into several blocks called Mohallah. We did proportionate sampling according to the 1998 population census [18] of UCs for the selection of Mohallah & on the next stage households. In the rst stage we randomly selected these blocks (Mohallah) in each of the UC from a list by using simple random sampling technique. In the next stage we selected households in that selected block by using a random sampling technique again. The total number of houses selected in each block was also proportional to the population size of respective block. For the selection of family type, from the list of household of each block, we made a list of joint & nuclear family system households and enrolled equal number of houses from both family types. A simple random sampling technique was used for the selection of person (≥18 years) from each house.
Simple random sampling was done by applying the lottery method for selecting the ≥18 year's participant for the study. The inclusion criteria used for selection of individual were age greater than 18 years and permanent resident of union council for at least 5 years. Guests and temporary residents were excluded from the study.

Study tool
We used, WHOQOL-BREF, a 26-item, self-administrated generic questionnaire that covers four domains of QOL (psychological 6 items, physical 7 items, social relationships 3 items and environmental 8 items).
Each question scored on a scale from one to ve, with high score indicating good QOL with the exception of three questions, which include pain and discomfort, need for medical treatment and negative feelings [19]. The seven items included in the physical health domain were mobility, daily life activities, pain, sleep, functional capacity and energy. The psychological domain measured negative thinking, self-image, positive approach, self-esteem, mindset, ability to learn, memory, consolidation, religion and the psychic conditions. Questions such as social support, sex-life and personal relationship come under the social relationship domain. The environmental health domain contains questions on nancial assets, security, health and social services, living in natural environment, opportunities for advance learning experience, relaxation, and natural environment (air, noise, pollution and transportation) [20]. The total raw score for these ve dimensions were transformed into 0 to 100 scale according to the standard procedure de ned in WHO QOL user manual [19], and then analysis of this reconstruct score was done. Psychometric properties and validation of this WHOQOL-BREF questionnaire was done in National language "Urdu". Cronbach's alpha for each of ve domains were 0.78, 0.71, 0.73 and 0.56 respectively [21]. To assess the feasibility and clarity of the items, a pilot study was conducted on 30 individuals conveniently selected from the study area. We also developed a structured demographic questionnaire which included variables such as age, gender, marital status, type of family (joint and nuclear), residence type (urban and rural), house ownership (owner, not owner), respondent education (no education, madrassa, can read/write, primary-up to grade 5, secondary education-up to grade 12 and tertiary-up to grade 16 or above), working status (employed, unemployed and retired).
The socio-economic characteristics were assessed by taking household conditions, sources of drinking water, sanitation facilities, availability of electricity, housing facilitates, possession of durable goods, mean of transport, inventory of house hold and personal items such as chairs, clocks, buckets, radios, television sets, fans, stoves or cookers, cars, and telephones. This list was composed of 21 such items used in World Bank's Social Capital Integrated Questionnaire (SC-IQ) was also used to study social capital among families. SC-IQ consists of 27 questions in six domains [24]. With the help of subject experts, we extracted ve questions from the core questionnaire with having Cronbach's alpha 0.64. These ve selected questions were overall trust, trust in local government, trust in central government, community cooperation and safety at home.

Data collection
One day training session was conducted for administering the questionnaires prior to data collection for lady health workers of all UCs by principal investigator. The questionnaire was administered through face to face interviews in the households by trained lady health workers of that union council. To ensure privacy and con dentiality, interviews were conducted in an independent room or area separate from other members of the family.

Data analysis and statistical methods
Data was analyzed using Stata version 13.0 (Stata Corp, College Station, TX, USA). Descriptive statistics such as frequencies and proportions and means with standard deviation were calculated. We carried out univariate and multivariate linear regression analyses with domain scores as dependent and other variables as independent variables. In the multivariate analysis, we included all the variables and then used stepwise backward approach to eliminate variables with a p value > 0.05. Muti-level analysis was performed with two -level continuous random intercept model with individuals nested within clusters was applied to explore the variability explained by individuals and cluster level variables taking the correlated nature of data into account. P-value of <0.05 was considered as signi cant.

Results
Demographic characteristic of study participants A total of 2116 households were approached. Out of this, 56 refused (non-response 2.64%) to participate in this study. Analysis was done on 2063 participants. Out of 2063 study participants, 1053 (51.04%) belonged to joint family system and 1010 (48.6%) to nuclear family. Younger (18 -30 years) and elderly (>50 years) were more in joint families (39%) and (20%) respectively compared to (20%) and (10%) in nuclear families.
Educational status of the participants was comparable in two groups as proportions of individuals with no education were 15.5% and 15.7 in joint and nuclear families respectively. Majority were living in their own houses 849 (80.5%) in joint and 750 (74.3%) in nuclear family. A higher proportion of the participants (80.5%) in joint family groups owned a house compared to (71%) in nuclear family group. Working group were (56.5%) in joint and (56.1%) in nuclear. Higher proportion of the participant were satis ed in living in joint family system (87.5%) compared to (81%) in nuclear family system (Table 1). Table 2 shows mean score of WHO QOL-BREF scores of participants in joint families. Those living in the urban areas, had signi cantly higher scores in all four dimensions. Male had higher scores in physical and psychological domains compared to females. However, no differences were observed in relationship and environmental domains. Younger age group <30years had higher scores than elderly >50 years of age. Divorced had highest scores in physical and psychological domains while married had highest scores in relationship domain. No signi cant differences were observed in environment domain between different categories of marital status. Lack of education, presence of any physical disability or disease, unemployment, lower socio-economic status and low social capital were associated with lower scores in all domains.

Joint family system WHO QOL-BREF scores
Final multiple linear regression model for joint family system: Table 3 shows the results of the nal multiple linear regression model of joint family system. (Results of univariate analysis are presented in supplementary le 1). In our nal model, rural residence was negatively associated with physical, psychological and environmental domains QOL scores and there was 4.59, 3.54 and 5.32 units reduction when changing from urban to rural (P=0.001) respectively. There was no signi cant association with relationship domain. Female gender was also negatively associated with QOL scores in all domains except environmental domain where no signi cant association was observed. Increasing age was negatively associated with QOL scores. One decade increase in age lead to 0.22, 0.16 and 0.12 units reduction in scores of physical, psychological and relationship domains. Presence of disease was also signi cantly associated as scores declined with the presence of disease in physical and psychological domains. However there was no signi cant association of disease status with relationship and environment domains. Socio-economic status also had a signi cant association as a change in SES from high to low resulted in a reduction of QOL scores in all the domains. Similarly increase in social capital was also positively associated with QOL scores in all four domains.
Nuclear family system WHO QOL-BREF scores: The mean score of each domain among different subgroups in joint family system is presented in Table 4. Pattern of differences between the subgroups in nuclear family system was similar to joint family system. The mean of all four domains was signi cantly higher among those living in urban areas. Male had higher scores than female. Younger age people <30 years of age had signi cantly higher scores than elderly in physical domain only. There were no signi cant differences in other three domains with respect to age. House ownership did not affect the QOL scores in any of the domain. Signi cant differences in scores were observed across different marital status strata. Those with no education generally had lower scores than others. Presence of any disease or disability signi cantly reduced the QOL scores. Compared with working/employed subjects, unemployed subjects had lower QOL scores. Participants with higher socioeconomic status, and social capital levels had higher QOL scores in all domains.
Final multiple linear regression model for nuclear family system: Table 5 presents the results of the nal multiple linear regression model of nuclear family system. (Results of univariate analysis are presented in supplementary le 2). In our nal model, rural residence was negatively associated with physical, psychological and environmental domains. Female gender and increasing age were also negatively associated with QOL scores in all domains except environmental domain. Presence of disease or disability led to signi cant decline in the QOL in physical domains.
However, there was no signi cant association of disease and disability with QOL scores in other domains.
QOL scores signi cantly declined with changing socio-economic status from high to low in all four domains. Social capital was also positively associated with QOL scores in all the domains.

Discussion
Our study is one of its kind to assess the predictors of QOL domains in joint and nuclear families in Pakistan. We found that male gender, urban residence, younger age, higher socio-economic status and social capital were positive predictors. While increasing age and presence of illness were associated with lower QOL scores. Predictors were similar in for all domains of QOL across two types of studied families with few exceptions. . This could also be due to prevailing male dominancy in the society which can lead to deprivation of female and thus low QOL. In our study rural residence was associated with lower QOL scores in all except relationship domain compared to urban residence. This association was similar for both types of the families. This is in contrast to the nding from India where there was no association of residence with any of the domains of QOL [28]. Lack of resources and opportunities for education, job and recreation in rural areas could be the possible cause of low QOL scores. Ageing is associated with physical and mental changes in the body which affects the health and QOL. We found that increasing age lead to decrease in the QOL scores in all domains except environmental domain in both types of families. Other studies have also reported similar association of age with QOL scores [26,30]. With the increasing life expectancy countries will experience increasing proportion of elderly population. This calls for reorientations of systems and services to ensure healthy elderly. We did not nd any signi cant difference in the predictors of QOL among both family types. Our ndings are interested in a way that it is considered that QOL differs in both family systems and their predictors would also be different. There is a need to do further studies to explore this nding.
Our study is one of its kind from Pakistan to assess the levels and predictors of QOL in joint and nuclear families from the randomly selected general population. We used robust statistical procedures and performed multi-level analysis to draw conclusions. However certain limitations need to be considered while interpreting the results of this study. First our sample was drawn from a single city which may limit the generalizability of our results. Second, questionnaire was administered by the interviewer which could introduce social desirability bias in the response. To minimize this we ensured privacy during interviews and no other household member was allowed in the interview room. Thirdly, this was a cross-sectional study and temporal associations could not be ascertained with certainty and we cannot say surely whether the predictors of our study preceded the quality of life.

Conclusion
Our study determined the levels and predictors of QOL scores of individuals in joint and nuclear families using validated WHO QOL BREF. Predictors were similar across both types of families. Male gender, urban residence, younger age, higher socio-economic status and social capital were positive predictors of QOL score while increasing age and presence of illness were associated with lower QOL scores among both family systems. We recommend to carry out further studies in different segments of population to further characterize the predictors.

Consent for publication
A written informed consent was gained for all participants.

Availability of data and material
Corresponding author will provide all the relevant data used in this study upon request.

Competing interest
The authors declare that they have no competing interests.    The short dashes mean that the variable was removed by the stepwise deletion process in regression ana    The short dashes mean that the variable was removed by the stepwise deletion process in regression analysis